Marine Sanctuaries Conservation Series ONMS-15-02

Climate Change Vulnerability Assessment for the 

North-central California Coast and Ocean 

U.S. Department of Commerce

National Oceanic and Atmospheric Administration

National Ocean Service

Office of National Marine Sanctuaries May 2015 
About the Marine Sanctuaries Conservation Series

The Office of National Marine Sanctuaries, part of the National Oceanic and 

Atmospheric Administration, serves as the trustee for a system of 14 marine protected 

areas encompassing more than 170,000 square miles of ocean and Great Lakes waters. 

The 13 national marine sanctuaries and one marine national monument within the 

National Marine Sanctuary System represent areas of America’s ocean and Great Lakes 

environment that are of special national significance. Within their waters, giant 

humpback whales breed and calve their young, coral colonies flourish, and shipwrecks 

tell stories of our maritime history. Habitats include beautiful coral reefs, lush kelp 

forests, whale migrations corridors, spectacular deep-sea canyons, and underwater 

archaeological sites. These special places also provide homes to thousands of unique or 

endangered species and are important to America’s cultural heritage. Sites range in size 

from one square mile to almost 140,000 square miles and serve as natural classrooms, 

cherished recreational spots, and are home to valuable commercial industries. 

Because of considerable differences in settings, resources, and threats, each marine 

sanctuary has a tailored management plan. Conservation, education, research, 

monitoring and enforcement programs vary accordingly. The integration of these 

programs is fundamental to marine protected area management. The Marine 

Sanctuaries Conservation Series reflects and supports this integration by providing a 

forum for publication and discussion of the complex issues currently facing the sanctuary 

system. Topics of published reports vary substantially and may include descriptions of 

educational programs, discussions on resource management issues, and results of 

scientific research and monitoring projects. The series facilitates integration of natural 

sciences, socioeconomic and cultural sciences, education, and policy development to 

accomplish the diverse needs of NOAA’s resource protection mandate. All publications 

are available on the Office of National Marine Sanctuaries Web site 

(http://www.sanctuaries.noaa.gov). 
Climate Change Vulnerability Assessment 

for the North-central California Coast and Ocean 

Hutto, S.V., K.D. Higgason, J.M. Kershner, W.A. Reynier, D.S. Gregg 

Silver Spring, Maryland

May 2015

U.S. Department of Commerce

Penny Pritzker, Acting Secretary

National Oceanic and Atmospheric Administration

Kathryn Sullivan, Ph.D.

Acting Under Secretary of Commerce for Oceans and Atmosphere

National Ocean Service

Russell Callender, Ph.D., Acting Assistant Administrator

Office of National Marine Sanctuaries

Daniel J. Basta, Director
Disclaimer

Report content does not necessarily reflect the views and policies of the Office of 

National Marine Sanctuaries or the National Oceanic and Atmospheric Administration, 

nor does the mention of trade names or commercial products constitute endorsement or 

recommendation for use. 

Report Availability

Electronic copies of this report may be downloaded from the Office of National Marine 

Sanctuaries web site at http://sanctuaries.noaa.gov. 

Cover

(left) Sea Palm; (top): North-central California coastline; (bottom, center): black 

oystercatcher; (bottom, right): California hydrocoral 

Suggested Citation

Hutto, S.V., K.D. Higgason, J.M. Kershner, W.A. Reynier, D.S. Gregg. 2015. Climate 

Change Vulnerability Assessment for the North-central California Coast and Ocean. 

Marine Sanctuaries Conservation Series ONMS-15-02. U.S. Department of Commerce, 

National Oceanic and Atmospheric Administration, Office of National Marine 

Sanctuaries, Silver Spring, MD. 473 pp. 

Contact 

Sara Hutto, Climate Change Specialist, Gulf of the Farallones National Marine 

Sanctuary: sara.hutto@noaa.gov 

Kelley Higgason, Climate Change Coordinator, Gulf of the Farallones National Marine 

Sanctuary: kelley.higgason@noaa.gov.
Project Planning Committee Members

Sarah Allen - National Park Service

Ben Becker – Point Reye National Seashore 

Rebecca Fris – California Landscape Conservation Cooperative 

Andrew Gunther – Bay Area Ecosystems Climate Change Consortium 

Lara Hansen – EcoAdapt 

Daphne Hatch – Golden Gate National Recreation Area

Jessi Kershner – EcoAdapt 

Deborah Schlafmann – California Landscape Conservation Cooperative 

Sam Veloz – Point Blue Conservation Science 

Project Staff 

Darrell Gregg – Gulf of the Farallones National Marine Sanctuary

Lara Hansen – EcoAdapt 

Kelley Higgason – Gulf of the Farallones National Marine Sanctuary 

Sara Hutto – Gulf of the Farallones National Marine Sanctuary

Jessi Kershner – EcoAdapt 

Whitney Reynier – EcoAdapt 

Sanctuary Superintendent

Maria Brown – Gulf of the Farallones National Marine Sanctuary

Reviewers and Contributors

Report 

Sarah Allen – National Park Service, Pacific West Region

Ben Becker – Point Reyes National Seashore 

Maria Brown – Gulf of the Farallones National Marine Sanctuary 

Lara Hansen – EcoAdapt 

Daphne Hatch – Golden Gate National Recreation Area

Jaime Jahncke – Point Blue Conservation Science 

Jessi Kershner – EcoAdapt 

Vulnerability Assessments

Please see Appendix C for a list of contributors and reviewers of individual focal resource 

assessments.

Funders and Sponsors

Project funders Workshop sponsors 

California Landscape Conservation Cooperative California Academy of Sciences

Gulf of the Farallones National Marine Sanctuary Golden Gate National Parks Conservancy

i
Abstract 

This vulnerability assessment is a science-based effort to identify how and why focal resources 

(habitats, species, and ecosystem services) across the North-central California coast and ocean 

region are likely to be affected by future climate conditions. The goal of this assessment is to 

provide expert-driven, scientifically sound assessments to enable marine resource managers to 

respond to, plan, and manage for the impacts of climate change to habitats, species, and 

ecosystem services within the region. This information can help prioritize management actions, 

and can help managers understand why a given resource may or may not be vulnerable to a 

changing climate, enabling a more appropriate and effective management response. Climate 

change vulnerability of 44 focal resources, including eight habitats, populations of 31 species, 

and five ecosystem services was assessed by considering exposure and sensitivity to climate 

changes and non-climate stressors and adaptive capacity. The 44 focal resources were identified 

and assessed by representatives from federal and state agencies, non-governmental organizations 

and academic institutions. Coastal habitats in the study region, including beaches and dunes, 

estuaries, and the rocky intertidal, along with associated species and ecosystem services, were 

identified through this assessment as being most vulnerable, and will likely be prioritized for 

future management action.

 

Key Words

Climate change, climate-smart, adaptation, vulnerability assessment, Gulf of the Farallones 

National Marine Sanctuary, GFNMS, climate impact, focal resources, habitats, species, 

ecosystem services

ii
Table of Contents

Topic Page 

Project Planning Committee Members ............................................................................................ i

Project Staff ..................................................................................................................................... i

Sanctuary Superintendent ................................................................................................................ i

Reviewers and Contributors ............................................................................................................. i

Project Funders ................................................................................................................................ i

Abstract ........................................................................................................................................... ii

Key Words ...................................................................................................................................... ii

Table of Contents ........................................................................................................................... iii

List of Figures and Tables.............................................................................................................. iv

Executive Summary ........................................................................................................................ 5

Vulnerability Assessment Report Section-by-Section .................................................................... 6

Introduction ..................................................................................................................................... 7

Study Region ....................................................................................................................... 7

Climate-Smart Adaptation for the North-central California Coast ..................................... 8

Climate-Smart Conservation ............................................................................................. 10

Vulnerability Assessment Overview ................................................................................. 10 

Climate Factors for the Study Region ............................................................................... 12

Vulnerability Assessment Results Summary ................................................................... 16

Process and Methodology ............................................................................................................. 17

Development of Collaborative Process ............................................................................. 17

Defining Terms ................................................................................................................. 17

Focal Resources Methodology .......................................................................................... 17

Vulnerability Assessment Methodology ........................................................................... 18

Vulnerability Assessment Application ............................................................................. 25

Results ........................................................................................................................................... 27

Vulnerability Assessment Reports ................................................................................................ 37

Habitats ............................................................................................................................. 38

Species ............................................................................................................................ 103

Ecosystem Services ......................................................................................................... 297

Conclusion and Next Steps ......................................................................................................... 342

Literature Cited ........................................................................................................................... 344

Report Photo and Figure Credits................................................................................................. 347

Appendix A: Focal Resources Workshop agenda and participants ............................................ 348

Appendix B: Vulnerability Assessment Workshop agenda and participants ............................. 351

Appendix C: Contributors and Reviewers to assessment reports ............................................... 353

Appendix D: Vulnerability Assessment Scores .......................................................................... 355

iii
List of Figures and Tables

Figure/Table Number and Title Page

Figure 1. Sea Palm, one of 44 focal resources assessed. ................................................................ 5

Figure 2. Rodeo Lagoon, estuarine habitat in the study region. ..................................................... 5

Figure 3. Map of study region (thick red lines), with related sanctuary boundaries (black solid 

lines) and proposed sanctuary expansion areas (black dashed lines). ............................................ 7

Figure 4. Steps of the "Climate-Smart Conservation Cycle" from the National Wildlife 

Federation's Quick Guide to Climate-Smart Conservation; Glick et al. 2011........................10

Figure 5. Structure of the vulnerability assessment model used in this process......................19

Figure 6. Overall vulnerabilities of eight habitats based on the climate change sensitivity, 

exposure, and adaptive capacity assessment..............................................................27

Figure 7. Overall vulnerabilities of all 31 species based on the climate change sensitivity, 

exposure, and adaptive capacity assessment..............................................................29

Figure 8. Overall vulnerabilities of all six fish species based on the climate change sensitivity, 

exposure, and adaptive capacity assessment..............................................................31

Figure 9. Overall vulnerabilities of all 14 invertebrate, plant and algal species based on the 

climate change sensitivity, exposure, and adaptive capacity assessment. ................................... .32

Figure 10. Overall vulnerabilities of all 11 bird and mammal species based on the climate change 

sensitivity, exposure, and adaptive capacity assessment................................................33 

Figure 11. Overall vulnerabilities of five ecosystem services based on the climate change 

sensitivity, exposure, and adaptive capacity assessment.. ..............................................34

Table 1. The calculated scores for overall vulnerability, exposure, sensitivity and adaptive 

capacity for the eight habitats assessed, ordered by decreasing vulnerability. ............................. 28

Table 2. The calculated scores for overall vulnerability, exposure, sensitivity and adaptive 

capacity for the 31 species assessed, ordered by decreasing vulnerability. .................................. 30

Table 3. The calculated scores for overall vulnerability, exposure, sensitivity and adaptive 

capacity for the five ecosystem services assessed, ordered by decreasing vulnerability. ............. 35

iv
Executive Summary

Marine resource managers realize the immediate threats of climate change to the resilience, 

health, and ecosystem services of the coastal and ocean places they protect, yet the resources to 

develop appropriate management options to prepare for and respond to a changing environment 

are limited (Gregg et al. 2011). Adaptation planning techniques and processes are well 

developed, but there is a lack of application of these methods for marine systems (Gregg et al. 

2011). This report is the first step in a process to enable marine resource managers to respond to, 

plan, and manage for the impacts of climate change to habitats, species, and ecosystem services 

within the North-central California coast and ocean region by utilizing expert-driven, 

scientifically sound assessments to provide prioritized, stakeholderled climate-smart adaptation strategies. 

This vulnerability assessment is a science-based effort to identify how 

and why focal resources (habitats, species, and ecosystem services) 

across the North-central California coast and ocean region are likely 

to be affected by future climate conditions. This information can 

facilitate efficient allocation of limited resources by identifying 

priority areas for management action and responses, ultimately 

helping to sustain optimal conditions for the region’s resources. This 

information can also help managers understand why a given resource 

may or may not be vulnerable to a changing climate, enabling a more 

appropriate and effective management response. 

Climate change vulnerability of 44 focal resources, including eight habitats, populations of 31 

species, and five ecosystem services was assessed by considering exposure and sensitivity to 

climate changes and non-climate stressors and adaptive capacity. The 44 focal resources were 

identified and assessed by representatives from federal and state agencies, non-governmental 

organizations and academic 

institutions. Climate information 

used in this assessment was 

provided by the Climate Change 

Impacts Report, a joint working 

group report of the Cordell Bank 

and Gulf of the Farallones 

National Marine Sanctuary 

Advisory Councils. This 

assessment focuses on the Northcentral California coast and 

ocean region, from Point Año 

Nuevo, San Mateo County, in 

the south to Alder Creek, 

Mendocino County, in the north, 

including three national marine 

sanctuaries, two national parks, and one US Fish and Wildlife Refuge, and one National 

Monument (Figure 3). Most resources considered in this assessment were identified by workshop 

participants as moderately vulnerable to climate change, with a range from low-moderate 

Figure 1. Sea Palm, one of 

44 focal resources assessed.

Figure 2. Rodeo Lagoon, estuarine habitat in the study region.

5
vulnerability to moderate-high vulnerability. Coastal habitats in the study region, including 

beaches and dunes, estuaries, and the rocky intertidal, along with associated species and 

ecosystem services, were identified through this assessment as being most vulnerable, and will 

likely be prioritized for future management action.

Vulnerability Assessment Report Section-by-Section 

The introduction provides a brief overview of the study region and expected climate changes in 

the region, as well as an overview of the project, how the information from vulnerability 

assessments can be used, and a summary of assessment results. The methodology section 

describes in greater detail the methods used to select resources, as well as the development of the 

vulnerability assessment methodology and its application. The results section provides 

descriptive figures and tables, discusses assessment results, and is followed by the individual 

assessments for each focal resource, incorporating the scores received during the vulnerability 

assessment workshop with information from the scientific literature. Finally, conclusions and 

next steps are addressed. Appendices A and B provide information regarding the two decisionsupport workshops, including agendas and participants, and Appendix C lists contributors and 

reviewers of the individual assessment reports. Appendix D provides an overview of the 

vulnerability assessment component scores for each resource.

6
Introduction

Study Region 

The North-central California coast and 

ocean is a globally significant, highly 

diverse, productive marine and coastal 

ecosystem that is home to abundant 

wildlife, valuable fisheries, three national 

marine sanctuaries and two national parks. 

It is a treasured resource of the San 

Francisco Bay Area’s seven million 

residents that rely on this unique marine 

ecosystem for their livelihoods and 

recreation. It provides breeding and 

feeding grounds for at least 25 endangered 

or threatened species, including blue, fin, 

sperm, and humpback whales and one of 

the southernmost U.S. populations of 

threatened Steller sea lions. This area is 

especially important to approximately 

350,000 wintering shorebirds, seabirds, 

and waterbirds, and many fish species 

including sturgeon, halibut, endangered 

coho salmon, and the commercially

important Pacific herring, that rely on 

creeks and extensive eelgrass beds to 

spawn. Significant coastal areas, including 

Tomales Bay, Bolinas Lagoon, Drakes 

Estero and Esteros Americano and San 

Antonio, support a diversity of habitats, including eelgrass beds, intertidal sand and mud flats, 

and salt and freshwater marshes that provide numerous ecosystem services such as carbon 

sequestration, flood control, and improved water quality (GFNMS 2008). 

For this assessment, the study region (Figure 3), bound by Point Año Nuevo, San Mateo County, 

in the south and Alder Creek, Mendocino County, in the north, includes coastal land and waters 

managed by three national marine sanctuaries (Gulf of the Farallones, Cordell Bank, Monterey 

Bay), two national parks (Point Reyes National Seashore and Golden Gate National Recreation 

Area), the US Fish and Wildlife Service Farallon National Wildlife Refuge, and the Bureau of 

Land Management California Coastal National Monument. There are eight major habitat types in 

the region that were evaluated for this assessment: 

Beaches and dunes: Located along the coastal border of the study region, including the Farallon 

Islands, beaches are composed of three distinct zones defined by the level of tidal inundation: the 

coastal strand and supra-littoral zone, which includes dunes, the middle intertidal zone, and the 

lower intertidal beach zone. 

Rocky intertidal: Located along the coastal border of the study region, including the Farallon 

Isalnds, this habitat is rocky substrate found between high and low tide water levels. 

Figure 3. Map of study region (thick red lines), with 

related sanctuary boundaries (black solid lines) and 

proposed sanctuary expansion areas (black dashed lines).

7
Kelp forest: Located primarily at depths from 4 meters to 25 meters, dense forests of kelp inhabit 

the rocky nearshore environment. The bull kelp, Nereocystis luetkeana, is the dominant canopyforming kelp, with an understory of other kelp species (e.g. Pterygophora californica, and other 

Laminarials).

Cliffs: Located along rocky portions of the coastline including the Farallon Islands, these are 

vertical or near-vertical rocky faces above the water line that provide habitat for pinnipeds, birds 

and rare native plants and are subject to erosion due to exposure to wave action, wind, and rain. 

Nearshore: Including the water column and soft-bottom subtidal, the nearshore habitat extends 

from the surf out to waters that are approximately 30 meters deep (100 feet). 

Estuaries: The estuarine habitat includes small and sandbar-built estuaries within the study 

region, such as Pescadero Marsh, Estero Americano and Estero de San Antonio, and moderately 

sized bays such as Tomales Bay, Bolinas Lagoon and Drakes Estero. San Francisco Bay is not 

included in this assessment. 

Pelagic water column: Extending out from the nearshore habitat, the pelagic water column 

includes the sea surface to the seabed, and is a highly heterogeneous and dynamic environment. 

Offshore rocky reefs: Including banks and seamounts, offshore rocky reefs are discrete features 

that provide complex and heterogeneous environments for colonization by deep-water corals, 

sponges, other invertebrates, and numerous fish species. The reefs considered in this assessment 

include Cordell Bank, Rittenburg Bank, and Fanny Shoals. 

For a more detailed description of the study region and associated habitats, see Appendix C: Gulf 

of the Farallones Regional Ecosystem Description of the report, “Ocean Climate Indicators: A 

Monitoring Inventory and Plan for Tracking Climate Change in the North-central California 

Coast and Ocean Region” (Duncan et al. 2013). 

Climate-Smart Adaptation for the North-central California Coast 

In 2009, the Gulf of the Farallones and Cordell Bank Sanctuary Advisory Councils recognized 

the importance of understanding climate change impacts to sanctuary resources, and called for 

the formation of a working group of local scientists from 16 agencies, organizations, and 

institutions to assess and downscale global climate change information into a regional climate 

change survey for north-central California coast and ocean ecosystems. The resulting

Climate Change Impacts Report (Largier et al. 2010) documents recent observations and 

potential impacts, including: observed increase in surface ocean temperature offshore of the 

continental shelf; observed increase in extreme weather events (winds, waves, and storms); 

expected decrease in seawater pH due to uptake of carbon dioxide by the ocean; observed

northward shift of key species (including Humboldt squid, volcano barnacle, gray whales, and 

bottlenose dolphins); possible shift in dominant phytoplankton (from diatom to dinoflagellate 

blooms); and the potential for effects of climate change to be compounded by parallel 

environmental changes associated with local human activities. This document serves as a robust, 

peer-reviewed, and scientifically sound foundation for climate adaptation planning. 

Recommendations from this report include the reduction of manageable stressors to enhance 

ecosystem resilience and the creation of policies and management strategies to minimize future

impacts. In response to the recommendations and final report, the GFNMS established the 

Climate-Smart Conservation Program as an effort to integrate adaptation planning, monitoring, 

mitigation, and climate change communication, into sanctuary management. For a conceptual 

ecological model depicting climate change drivers and associated biological responses, see 

8
Appendix D: Conceptual Ecological Model for North-central California Coast and Ocean of the 

report, “Ocean Climate Indicators: A Monitoring Inventory and Plan for Tracking Climate 

Change in the North-central California Coast and Ocean Region” (Duncan et al. 2013). 

Additionally, GFNMS, in partnership with USGS Western Ecological Research Center, led an 

effort to develop physical and biological ocean climate indicators for the study region. These 

indicators provide vital information about the presence and implications of climate change on the 

ecosystems within the region. The indicators were specifically developed to support sciencebased decision-making at local, state, and federal agencies, and they are the first regional ocean 

climate indicators developed by the National Marine Sanctuary System. A working group of the 

GFNMS Advisory Council also developed the report, “Ocean Climate Indicators: A Monitoring 

Inventory and Plan for Tracking Climate Change in the North-central California Coast and 

Ocean Region” (Duncan et al. 2013) that includes monitoring strategies and activities; the best 

available monitoring data identified; opportunities for improving or expanding existing 

monitoring, or for establishing new indicator monitoring; and case studies providing specific 

examples of the indicators' utility in a decision-making context. 

As a next step to this foundational science, GFNMS, along with project partners, Bay Area 

Ecosystems Climate Change Consortium (BAECCC), California Landscape Conservation 

Cooperative (CA LCC), EcoAdapt, Farallones Marine Sanctuary Association (FMSA), Golden 

Gate National Recreation Area (GGNRA), National Park Service Pacific West Region, Point 

Blue Conservation Science, Point Reyes National Seashore, and the US Fish and Wildlife 

Service are collaborating on the Climate-Smart Adaptation Project for the North-central 

California Coast and Ocean. The goal of the project is to enable marine resource managers to 

respond to, plan, and manage for the impacts of climate change to habitats, species, and 

ecosystem services within the North-central California coast and ocean region by utilizing 

expert-driven, scientifically sound assessments to provide prioritized, stakeholder-led climatesmart adaptation strategies. Specifically, the project seeks to integrate climate-smart adaptation 

into existing management frameworks, and provide guidance to help ensure long-term viability 

of the habitats and resources that natural resource agencies are mandated to protect. To meet the 

project goal, the following overarching objectives will be achieved: 

1) Produce scientifically sound vulnerability assessments of focal resources through expert 

elicitation and literature review.

2) Develop and prioritize climate change adaptation action recommendations that can be 

feasibly implemented by managers, while considering a range of plausible future climate 

scenarios that incorporate interdisciplinary collaborative input. 

3) Develop an implementation plan for sanctuary management based on the approved 

adaptation actions. 

4) Serve as a pilot climate-smart adaptation project for other marine protected areas, such as

national marine sanctuaries, both nationally and within California. 

The Climate-Smart Adaptation project consists of two phases: 1) Vulnerability Assessment, and 

2) Adaptation Planning. This vulnerability assessment report is the product of Phase 1, which 

consisted of two workshops of scientists, natural resource managers, and policy experts to define 

focal resources and assess climate vulnerabilities of these resources, as well as an extensive 

literature review (see Vulnerability Assessment Project Overview). Phase 2 of the project, 

9
initiated in 2015, convenes a GFNMS Advisory Council working group of scientists and 

resource managers to define distinct future climate scenarios for the study region and develop 

prioritized adaptation action recommendations. These recommendations will be forwarded to the 

GFNMS Advisory Council for approval, and the approved recommendation will then be 

forwarded to the GFNMS superintendent, as well as other coastal resource management agencies 

in the region for consideration in their current or future adaptation planning efforts. GFNMS will 

then adopt a final set of climate-smart adaptation strategies based on the Sanctuary Advisory 

Council recommendations, and develop an adaptation implementation plan. 

Climate-Smart Conservation 

As outlined by Ellie Cohen, President and CEO of 

Point Blue Conservation Science, Climate-Smart 

Conservation addresses impacts of climate change 

in concert with existing threats and promotes 

nature-based solutions to: 

1) Reduce greenhouse gas emissions and 

enhance carbon sinks; 

2) Reduce climate change impacts on wildlife 

and people and enhance the ability to 

adapt; and

3) Sustain vibrant, diverse ecosystems 

Climate-Smart Conservations principles guide an 

approach to conservation that: links actions to 

climate impacts; embraces forward-looking goals; 

considers broader landscape context; adopts 

strategies robust to uncertainty; employs agile and 

informed management; minimizes carbon footprint; accounts for climate influence on project 

success; safeguards people and nature; and avoids maladaptation (Stein et al. 2014). The 

National Wildlife Federation’s Climate-Smart Conservation Cycle (Figure 4) highlights the 

iterative steps involved with this process. 

Vulnerability Assessment Overview

Marine resource managers realize the immediate threats of climate change to the resilience, 

health, and ecosystem services of the coastal and ocean places they protect, yet the resources to 

develop appropriate management options to prepare for and respond to a changing environment 

are limited (Gregg et al. 2011). Vulnerability assessments provide a foundation for understanding 

how and to what degree resources are threatened by climate change, and can help resource 

managers and conservation planners set management and planning priorities as well as enable 

more efficient and effective allocation of resources. This is the first step in developing adaptive 

management strategies to prepare for and respond to projected climate changes. 

This vulnerability assessment is a science-based effort to identify how and why important 

resources across the North-central California coast and ocean region are likely to be affected by

future climate conditions. In this context, vulnerability is a function of the sensitivity of the 

resource to climate change, its anticipated exposure to those changes, and its capacity to adapt to 

Figure 4. Steps of the "Climate-Smart 

Conservation Cycle" from the National Wildlife 

Federation's Quick Guide to Climate-Smart 

Conservation (Glick et al. 2011).

10
changes. Specifically, sensitivity is defined as a measure of whether and how a resource is likely 

to be affected by a given change in climate, or factors driven by climate; exposure is defined as 

the degree of change in climate or climate-driven factors a resource is likely to experience; and 

adaptive capacity is defined as the ability of a resource to accommodate or cope with climate 

change impacts with minimal disruption (Glick et al. 2011). This information can facilitate 

priority setting for management action and responses, and better characterize the cause of 

vulnerability for more effective management. The analyses and conclusions are based on 

available information and expert opinion. 

Climate change vulnerability assessments provide two kinds of information that are critical in 

adaptation planning: (1) they identify which resources are likely to be most affected by changing 

climate conditions, and (2) they improve understanding as to why these resources are likely to be 

vulnerable. Knowing which resources are most vulnerable better enables managers to set 

priorities for conservation action, while understanding why provides a basis for developing 

appropriate climate-smart adaptation responses (Glick et al. 2011). 

The overarching goal of this assessment is to provide vulnerability information and supporting 

tools and resources that will help coast and ocean managers plan their management of important 

resources in a changing climate. To meet this goal, the assessment has three main objectives:

1. Use the latest scientific knowledge and understanding of climate trends (current, historic, 

projected future) for the North-central California coast and ocean to evaluate the 

sensitivity, exposure, and adaptive capacity of selected habitats, species, and ecosystem 

services (termed focal resources). 

2. Produce scientifically sound vulnerability assessments for focal resources through expert 

elicitation, regional modeling, and literature review. 

3. Provide vulnerability assessment training, resources, support, and tools to participants to 

apply this process to similar efforts in their own work.

To achieve these objectives, a vulnerability assessment model was developed and applied 

consistently across the North-central California coast and ocean region that improves 

understanding of why resources may be vulnerable, how these vulnerabilities may vary across 

the region, and where and how management could intervene to reduce vulnerabilities. This report 

describes how this vulnerability methodology was developed, and summarizes the results that 

were obtained when the methodology was applied to the region. 

Climate change vulnerability of North-central California coast and ocean resources was assessed 

by considering exposure to climate change, sensitivity to climate and non-climate stressors, and 

adaptive capacity. Proposed resources were identified during the Focal Resources Workshop, 

and the final 44 resources were decided by the assessment workshop participants and sanctuary 

staff. Climate exposure information for the region was provided to workshop participants 

through a Climate Change Impacts Report (Largier et al. 2010) that was developed by a joint 

working group of Gulf of the Farallones and Cordell Bank National Marine Sanctuary Advisory 

Councils, and by Tom Suchanek, USGS, during a presentation at the Vulnerability Assessment 

Workshop. These resources included information on potential climate change impacts to habitats 

and biological communities along the north-central California coast, with an emphasis on the 

most likely ecological impacts and the impacts that would be most severe if they occur.

11
The Vulnerability Assessment Workshop was convened to evaluate the vulnerability of each 

resource, and included participants from resource management agencies, academic institutions, 

and non-governmental conservation organizations from the surrounding region. Sensitivity, 

adaptive capacity, and exposure were assessed on a 1-5 scale (1 = low, 5 = high) based on 

participant expertise. Interpretation of questions likely varied among participants, and there was 

no standardization among participants. Each ranking also included a confidence evaluation (1-3 

scale; 1 = low, 3 = high).

Climate Factors for the Study Region 

The following climate factors (listed alphabetically) were identified by participants of the 

Vulnerability Assessment Workshop for North-central California coast and ocean resources. 

These factors were identified due to their importance in understanding future changes in climate 

that the region’s resources may experience. For information regarding key factors identified for 

specific resources, see the vulnerability assessment results section.

Changes in air temperature

Air temperatures along the California coastline will likely exhibit high variability in the future 

(Largier et al. 2010). Lebassi et al. (2009) analyzed 253 California National Weather Stations 

from 1950-2005 and found that air temperature in low-elevation coastal areas cooled 

(-0.30°C/decade) and inland stations warmed (+0.16° C/decade). However, a gradual retraction 

of the North Pacific High could contribute to decreased formation of the marine layer with 

declines in coastal fog and increases in temperature (Johnstone and Dawson 2010). By the end of 

the century, extreme heat days are expected to increase dramatically for all areas in the Bay 

Area, but coastal areas (including San Francisco) are estimated to endure a much higher number 

of such events (Ekstrom and Moser 2012). 

Increased coastal erosion and run-off

An enhanced potential for coastal erosion is expected across the study region due to rising sea 

level, enhanced storm intensity and frequency, and increased wave action (PWA 2009). 

Mendocino County is projected to lose the largest area of land (dunes and cliffs) to coastal 

erosion, and Marin County will be greatly impacted by dune erosion (PWA 2009). Rising air 

temperatures are expected to decrease Sierra snowpack and decrease the precipitation ratio of 

snowfall to rainfall (Knowles et al. 2004), which will likely lead to increased winter run-off, 

decreased summer run-off, and higher annual peak run-off, impacting the study area via San 

Francisco Bay. An anticipated increase in intensity and occurrence of fire may also increase runoff (Kiparsky and Gleick 2005). Overall, increased erosion and run-off are likely to occur in 

association with winter storms that bring large waves and heavy precipitation to the region 

(Largier et al. 2010). 

Altered currents and mixing 

Currents and mixing are heterogeneous along the California coastline, making projections of 

future climate-related impacts difficult to discern (Largier et al. 2010). In addition, natural 

interannual and interdecadal variability (i.e., due to El Niño Southern Oscillation (ENSO), 

Pacific Decadal Oscillation (PDO) and North Pacific Gyre Oscillation (NPGO) shifts) can 

exceed magnitudes caused by climate change (McPhaden and Zhang 2004, DiLorenzo et al. 

2008). In general, the California Current is controlled by the North Pacific High pressure cell and 

the Aleutian Low pressure cell, and when the Aleutian Low is weaker than the North Pacific 

12
High, the California Current exhibits a strong southerly flow and contributes to cooler surface 

waters, reduced stratification, stronger upwelling, and more productivity along the California 

coastline (Largier et al. 2010). Some climate models suggest that weakening atmospheric 

circulation could reduce the southerly flow of the California Current (Meehl and Teng 2007, 

Vecchi and Soden 2007), potentially decreasing regional ocean productivity. During the past 30 

years, the California Current System (CCS) has experienced significant environmental shifts and 

subsequent impacts on marine productivity, including intensification of El Niño events 

(McGowan et al. 1998, Fiedler 2002) and of wind-driven upwelling (Sydeman et al. 2014). 

Future intensification of these events is expected (Snyder et al. 2003, Auad et al. 2006, Sydeman 

et al. 2014), which will likely continue to alter oceanographic conditions and primary 

productivity in the CCS, creating a diverse assortment of marine conditions (Wolf et al. 2010). 

The timing and magnitude of upwelling has become much more variable over the last six 

centuries (Black et al. 2014), and is projected to change significantly during the current century 

(Snyder et al. 2003, Auad et al. 2006, Sydeman et al. 2014), displaying greater spatial and 

temporal variability (Snyder et al. 2003, Black et al. 2014). 

Decreased dissolved oxygen (DO)

Significant changes to dissolved oxygen can result from a number of physical and biological 

processes, including circulation, ventilation, air-sea exchange, large algal blooms, production 

and respiration (Keeling and Garcia 2002, Deutsch et al. 2005, Bograd et al. 2008). Models 

predict a decline in midwater oceanic DO, due to enhanced stratification and reduced ventilation 

(Sarmiento et al. 1998, Keeling and Garcia 2002). Weaker transport of the California Current 

could reduce dissolved oxygen levels in waters along the California coast (Bograd et al. 2008, 

Stramma et al. 2008). Low-DO waters are typically restricted to deeper environments, though 

shoaling of the oxygen minimum zone and the upwelling of low-DO waters may increase the 

likelihood of exposure to anoxia for nearshore resources (Largier et al. 2010), leading to high 

mortality of demersal fish and benthic invertebrate communities (Grantham et al. 2004, Chan et 

al. 2008). This expansion of the oxygen minimum zone could have cascading effects on benthic 

and pelagic communities (Largier et al. 2010), including range expansion of certain species 

(Humboldt squid, Gilly et al. 2006). 

Changes in El Niño events

The number of El Niño events likely will not change, though the likelihood of super El Niños 

doubled from one every 20 years in the previous century to one every 10 years in the 21st 

century (Cai et al. 2013). Warm El Niño years have been intensifying (McGowan et al. 1998, 

Fiedler 2002), during which a 90% reduction in zooplankton biomass has been recorded 

(Rommich and McGowan 1995). The high waves during El Niño events will be more extreme 

when combined with the trend of increased wave height (Largier et al. 2010). 

Increased flooding

Increased flooding of low-lying coastal areas is expected in the study region due to rising sea 

level, increased storm activity and intensity, and increased extreme precipitation events. 

Decreased pH

Globally, average surface ocean pH has decreased by 0.1 units since pre-industrial times (Doney 

et al. 2009). Upwelled waters along the coast of California, including the CCS, have very low pH 

13
and strong upwelling events result in understaturation of calcite and aragonite, two common 

types of calcium carbonate secreted by marine organisms (Lischka et al. 2010), for the entire 

shelf (Feely et al. 2008, Largier et al. 2010, Alin et al. 2012). Using two emissions scenarios, the 

saturation state of aragonite is projected to drop rapidly in the CCS within the next 30 years, with 

much of the nearshore region developing summertime undersaturation in the top 60 meters 

(Gruber et al. 2012). By 2050, more than half of the waters in the CCS will be undersaturated 

year-round (Gruber et al. 2012), with impacts to shelled marine organisms, including pteropods 

(Hauri et al. 2013), and larval and juvenile fish (Munday et al. 2009, Hamilton et al. 2013). 

Changes in precipitation

Precipitation has increased in California since the early 20th century (Groisman et al. 2001, Mote 

et al. 2005). Some models project a continued trend in increasing precipitation across California, 

with the greatest increase in northern California (Kim et al. 2002, Snyder et al. 2002), while 

others suggest no change or only a slight increase for northern California and a slight decrease 

for central California (DWR 2006). Future projections include increased variability of 

precipitation (drier dry years, wetter wet years) (DWR 2006, Largier et al. 2010), increased 

frequency of extreme winter precipitation events, and more rapid melting of spring snowpack, 

potentially causing more intense periods of river flow and freshwater discharge in winter and 

spring (DWR 2006). 

Changes in salinity

Due to the expected increase in extreme precipitation events and extreme heat events, the 

California coast and ocean can expect greater fluctuations in salinity due to runoff and 

evaporation (Snyder and Sloan 2005, Largier et al. 2010). Salinity also fluctuates in accordance 

with upwelling, as increased stratification and/or wind reductions could lead to upwelling of 

shallower, less saline water (Largier et al. 2010). ENSO events and decreased mixing of deep 

saline waters (due to persistent heating of surface waters) have been implicated as causes of 

long-term freshening of surface waters in Southern California (McGowan et al. 1998, GomezValdez and Jeronimo 2009). Salinity impacts the solubility of CO2 in the ocean (Raven and 

Falkowski 1999), contributes to shifts in regional and large-scale circulation patterns (DiLorenzo 

et al. 2008), and impacts many habitats and species in the study region, including marsh 

community structure (Callaway et al. 2007). 

Sea level rise

Sea level along the California coast has increased by about 15 centimeters over the last 100 years 

(CEC 2006), while the longest-running tide gauge in the nation, located in San Francisco Bay, 

indicates 2.01 millimeters of rise per year, or approximately 20.1 cm over the last 100 years 

(NOAA 2009). According to the National Research Council's 2012 sea level rise projections for 

North-central California, 12-61 cm of sea level rise is expected by 2050 and 42-167 cm is 

expected by 2100. 

Changes in sea surface temperature

Global ocean temperatures have increased 0.11°C from 1971-2010 in the upper 75 meters (IPCC 

2014), though warming is spatially variable (Largier et al. 2010). Sea surface temperatures have 

been increasing since 1955 at offshore and at shore monitoring stations along the Pacific Coast 

(McGowan et al. 1998, Enfield and Mestas-Nunes 1999, Sagarin et al. 1999, Mendelssohn et al. 

14
2003, Palacios et al. 2004), though there has been local upwelling-driven cooling along the 

continental shelf in central California over the past 30 years (Mendelssohn and Schwing 2002, 

Garcia-Reyes and Largier 2010). Continued warming of nearshore and enclosed bay waters is 

expected, while water temperatures are expected to cool over the continental shelf (Largier et al. 

2010). Sea surface temperature impacts stratification and ocean circulation patterns, influencing 

primary productivity. 

Changes in sediment supply1

Sediment supply and movement affects a variety of coastal and marine habitats and is influenced 

by both natural variability (e.g., in precipitation, streamflow input, wind and current patterns, 

storm frequency and intensity, local erosion) and human activities (Barnard et al. 2013 and 

citations therein; Hein et al. 2013; Hestir et al. 2013). In North-central California, open coastal 

and marine ecosystem sediment dynamics are linked with anthropogenic activity within regional 

sediment-sheds (e.g., dredging, water diversion, development, restoration projects), underscoring 

the importance of exploring terrestrial, deltaic, coastal, and marine sediment transport 

connections during project planning and development (Hein et al. 2013). Although sediment 

supply has varied significantly among different North-central coast areas over the past two 

centuries (Barnard et al. 2013 and citations therein), it is estimated that the San Francisco Bay 

Coastal System lost 240 million cubic meters of sediment from 1965-2005 (Schoellhamer 2011). 

The study region has also experienced reduced ebb-tidal delta surface area and volume (Barnard 

et al. 2013 and citations therein) and accelerated erosion (Dallas and Barnard 2011), indicative of 

reduced sediment supply (Barnard et al. 2013). Future shifts in precipitation (e.g., snow to rain) 

will likely cause peak streamflow and sediment loads to occur earlier in the year (Ganju and 

Schoellhamer 2010), while extreme precipitation events and flooding can affect the timing and 

overall supply of sediment coming from smaller tributaries (Hestir et al. 2013). In general, 

continued or exacerbated reductions in sediment supply may threaten the persistence of some 

habitats in the face of sea level rise (Ganju and Shcoellhamer 2010; Knowles 2010; Callaway et 

al. 2012) and have additional implications for marine productivity and fish stocks (Barnard et al. 

2013 and citations therein; Hestir et al. 2013 and citations therein). 

Increased storminess

Winter storms (i.e., North Pacific winter cyclones/extra-tropical cyclones) have been increasing 

in frequency and intensity since 1948 (Graham and Diaz 2001, Zhang et al. 2004). Storms 

increase precipitation and wave height and can cause temporarily higher sea levels (e.g., winddriven storm surge). Peak storm wave heights have been increasing along the Pacific Coast (i.e., 

Washington, Oregon, and Northern California), although there have not yet been statistically 

significant increases in Central California (Largier et al. 2010). Models suggest that the tracks of 

storms in the northeast Pacific Ocean are migrating poleward (Hartmann et al. 2013), with a 

decrease in the frequency of storms at mid latitudes (including the study region), but an increase 

in intensity of storms at both high and mid latitudes (McCabe et al. 2001). Additionally, the 

number of El Niño events is projected to likely not change, though the likelihood of super El 

1 For more in-depth discussions of sediment supply and movement dynamics in the study region, please see: 

Barnard, P. L., B. E. Jaffe and D. H. Schoellhamer (eds). 2013. A multi-discipline approach for understanding 

sediment transport and geomorphic evolution in an estuarine-coastal system: San Francisco Bay. Marine Geology

345:1-326. Available online at http://www.sciencedirect.com/science/journal/00253227/345. 

15
Niños doubled from one every 20 years in the previous century to one every 10 years in the 21st 

century (Cai et al. 2013). 

Vulnerability Assessment Results Summary 

The vulnerabilities for all 44 focal resources are presented in the figures, tables and individual 

assessment reports in the Results section. In general, most resources were assessed as having 

moderate vulnerability. 

The eight habitats assessed were scored as having moderate to moderate-high adaptive capacity, 

but highly variable degrees of exposure and sensitivity, ranging from low-moderate to moderatehigh. The most vulnerable habitats – beaches/dunes, estuaries, and rocky intertidal – exist at the 

land-sea interface. The 31 species assessed were scored as having highly variable adaptive 

capacity, from low to moderate-high, and highly variable exposure and sensitivity scores, from 

low-moderate to high. The majority of the ten species identified as being most vulnerable are 

those that use the three most vulnerable habitats –beaches/dunes, estuaries, and the rocky 

intertidal. The five ecosystem services assessed generally scored higher for exposure and 

sensitivity than species or habitats, ranging from moderate-high to high. Adaptive capacity was

more variable, ranging from low-moderate to moderate-high. Those services that are provided 

primarily by the region’s coastal habitats were identified as being most vulnerable – flood and 

erosion protection, which is provided by estuarine and beach/dune habitat, carbon storage and 

sequestration, which is provided by estuarine habitat, and water purification, which is provided 

by estuarine and beach habitat. 

The adaptive capacity component of this vulnerability assessment considered potential 

management approaches for a given resource to facilitate adaptation to changing climate 

conditions. Most management approaches focused on alleviating current non-climate stressors 

(e.g., protecting upland habitat, restoration activities), but represent important management 

action considerations to enhance resource resilience to climate change. The information in this 

vulnerability assessment is intended to help managers develop and prioritize adaptation strategies 

to conserve resources by better integrating the effects of climate change.

16
Process and Methodology

Development of Collaborative Process

This project used a collaborative, expert elicitation-based approach that involved representatives 

from numerous federal and state agencies, non-profit organizations, and academic institutions 

(see Appendices A and B for full list of workshop participants and affiliations). Expert elicitation 

has a long history in conservation and regulation. These approaches are effective where there is 

greater uncertainty about resource function or future projections, but detailed knowledge and 

expertise from local stakeholders. Participants in this process had extensive knowledge about the 

ecology, management, and threats to north-central California coast and ocean habitats, species, 

and ecosystem services, and also comprise many of the professionals who will use the results of 

the project. A series of two invitational workshops were held in San Francisco: Focal Resources 

Workshop in February 2014, and Vulnerability Assessment Workshop in June 2014. Focal 

Resources Workshop participants were asked to apply their knowledge of the region’s ecological 

resources to make recommendations for those species, habitats, and ecosystem services that are 

most vital to the region for which to assess vulnerability to climate impacts and non-climate 

stressors. Using the vulnerability assessment methodology described below as a guide, 

Vulnerability Assessment Workshop participants were asked to apply their knowledge and 

expertise about a selected resource (habitat, species, or ecosystem service) to evaluate its 

vulnerability to climate and non-climate stressors. Participants in this workshop provided both 

scores and confidence evaluations for resource assessments.

Defining Terms

Exposure: A measure of how much of a change in climate or climate-driven factors a resource is 

likely to experience (Glick et al. 2011).

Sensitivity: A measure of whether and how a resource is likely to be affected by a given change 

in climate or factors driven by climate (Glick et al. 2011).

Adaptive Capacity: The ability of a resource to accommodate or cope with climate change 

impacts with minimal disruption (Glick et al. 2011).

Vulnerability: The propensity or predisposition to be adversely affected. Vulnerability 

encompasses a variety of concepts and elements including sensitivity or susceptibility to harm 

and lack of capacity to cope and adapt (IPCC 2014). 

Focal Resources Methodology 

Selection Process

Gulf of the Farallones National Marine Sanctuary, in collaboration with project partners, 

convened the Focal Resources Workshop on February 11, 2014 at the California Academy of 

Sciences in San Francisco, CA (see Appendix A for agenda and participants). The goal of this 

workshop was to finalize a list of North-central California coast and ocean focal resources 

(species, habitats and ecosystem services) for use in vulnerability assessments. Information from 

the workshop such as a workshop summary, presentations, handouts, readings, and other 

resources can be found on the workshop support page. 

17
Working in break-out groups, 30 scientists, managers, and policy experts representing 21 

institutions, organizations, and agencies discussed and developed consensus recommendations 

for species, habitats and ecosystem services for inclusion in the vulnerability assessments. Given 

the time and resources available for the vulnerability assessments, it was not feasible to assess all 

72 recommended focal resources individually. Therefore, the project planning committee 

finalized the smaller list of focal resources based on feedback received from the break-out groups 

using the following process. Further culling of this list took place at the Vulnerability Assessment 

Workshop, as participants prioritized the resources to be completed during and following the 

workshop based on available time and resources. 

Species

Species that were suggested by a break-out group to be adequately assessed in one of the habitat 

assessments were removed from the final list (e.g. bull kelp may be adequately assessed via the

kelp forest habitat assessment). Species that displayed similar life history characteristics as 

another listed species were removed (e.g. steelhead trout is similar to coho/Chinook salmon; 

humpback whale is similar to the blue whale). All species with multiple recommendations from 

break-out groups were retained in the final list. The recommended group of invertebrates 

remained very large, so the planning committee decided to base any further culling of this group 

on available expertise (certain species would not be assessed at the workshop if the required 

expertise was not available), and by the participants of the Vulnerability Assessment Workshop. 

Habitats 

The list of habitats was finalized by combining the dune and beach habitats and by combining 

offshore rocks with the rocky intertidal habitat. Islands were removed, and were assessed by a 

suite of other habitats (including rocky intertidal, beaches/dunes, and cliffs). 

Ecosystem Services

The list of ecosystem services was finalized by combining protection from erosion and 

protection from flooding, and removing scientific discovery (it was determined by the planning 

committee this would be too difficult to assess).

Vulnerability Assessment Methodology 

Vulnerability Assessment Methodology Overview 

The vulnerability assessment methodology used in this process comprises three vulnerability 

components (sensitivity, adaptive capacity, and exposure), confidence evaluations for all 

components, and overall vulnerability and confidence scores for a resource (Figure 11). In this 

report, each component of vulnerability includes expert assigned scores as well as written 

summaries describing expert comments and information from the scientific literature. The aim of 

the summaries that accompany scores is to make transparent the rationales and assumptions 

underlying the scores and confidences assigned to each variable.

Sensitivity, adaptive capacity, and exposure components were broken down into specific 

elements better suited to assessing the vulnerability of particular resources for this assessment. 

For example, sensitivity comprises three main elements for habitats and ecosystem services, and 

five elements for species. Elements for each vulnerability component were delineated by 

EcoAdapt, and are described in more detail below. 

18
Expert participants assigned one of five scores (High-5, Moderate-High-4, Moderate-3, LowModerate-2, or Low-1) for each component of vulnerability. Interpretation of questions likely 

varied among participants, and there was no standardization among participants. Expert-assigned 

scores for each component were then averaged (mean) to generate an overall score for that 

particular component. For example, scores for each element of habitat sensitivity were averaged 

to generate an overall habitat sensitivity score. Scores for the exposure component of 

vulnerability were weighted less than scores for the sensitivity and adaptive capacity components 

of vulnerability by a factor of 0.5. Exposure was weighted lower than sensitivity and adaptive 

capacity due to uncertainty about the magnitude and rate of future change. Sensitivity, adaptive 

capacity, and exposure scores were then combined into an overall vulnerability score calculated 

as follows: 

Vulnerability = Climate Exposure (0.5) + Sensitivity 

 Adaptive Capacity

Elements for each component of vulnerability were also assigned one of three confidence scores

(High-3, Moderate-2, or Low-1). This ensured the degree of confidence that assessors had in 

scoring each variable was explicit. Confidence scores for each vulnerability component were 

averaged (mean) to generate an overall confidence score. 

The user is encouraged to pay close attention to the summaries and individual scores for each 

resource. Familiarity with each vulnerability component in addition to a resource’s overall score

better informs why a particular resource is vulnerable and what management actions may reduce 

vulnerabilities given possible tradeoffs. Additionally, due to participant differences in question 

interpretation, users are encouraged to exercise caution when comparing results between 

resources; however, at this time they provide the best tool available to describe vulnerabilities. 

Figure 5. Structure of the vulnerability assessment methodology used in this process.

19
Model Elements – Habitats

This section lists the elements that were considered in the expert elicitation-based vulnerability 

assessment model for habitats.2

 

Habitat Sensitivity & Exposure

1. Climate and Climate-Driven Factors 

There are two ways to consider habitat sensitivity to climate and climate-driven factors: (1) does 

the habitat exist in a relatively narrow climatic zone, and (2) does the habitat experience large 

changes in composition or structure due to small changes in climate or climate-driven factors? 

Habitats that exist in a narrow climatic zone and/or experience large changes in composition or 

structure in response to small changes in climate likely have higher sensitivity (Lawler 2010). 

Climate and climate-driven factors considered included air temperature, ocean temperature, 

precipitation, chemistry (i.e., salinity, oxygen, pH), sea level rise, wave action, 

currents/mixing/stratification, coastal erosion, and others. Habitat benefits from climate and 

climate-driven factors were also considered.

2. Disturbance Regimes 

Habitats may be sensitive to particular disturbance regimes such as wind, flooding, diseases, or 

storms, among others. Habitats that experience larger changes in composition or structure due to 

small changes in disturbance regimes are likely more sensitive (Lawler 2010). 

3. Future Climate Exposure 

A number of climate and climate-driven changes may be important to consider for marine and 

coastal habitats. These factors may include, but are not limited to: increased air or ocean 

temperature, changes in precipitation, sea level rise, changes in salinity, decreased oxygen or pH, 

increased flooding, and others. In addition to ranking exposure, participants were asked to 

document any potential areas of refugia from a particular climate or climate-driven change. 

4. Non-Climate Stressors 

Non-climate stressors may have independent, synergistic, additive, or antagonistic effects with 

climate change (Hansen and Hoffman 2011). Habitats that have to endure multiple non-climate 

stressors may be more sensitive to climate changes. Non-climate stressors for marine and coastal 

habitats may include land use change, aquaculture, energy production, roads and armoring, 

overwater/underwater structures, dredging, harvest, invasive and other problematic species, 

recreation, or pollution and poisons, among others. Participants were asked to identify nonclimate stressors most likely to increase sensitivity of the habitat to climate change, assess the 

degree to which the stressor affects sensitivity and degree of current exposure (both local and 

regional) to the stressor, and evaluate confidence.

Habitat Adaptive Capacity

1. Extent, Integrity and Continuity 

Habitats that are currently widespread in their geographic extent, with high integrity and 

continuity may be better able to withstand and persist into the future despite climate and nonclimate stressors. Habitats that are degraded, isolated, limited in extent, or currently declining 

due to climate and non-climate stressors will likely have lower adaptive capacity (Manomet 

Center for Conservation Sciences 2012). Geographic extent, structural and functional integrity, 

and continuity were considered for marine and coastal habitats. 

2 Elements generated by EcoAdapt.

20
2. Resistance and Recovery 

Some habitats may be more resistant to changes, stressors, or maladaptive human responses, or 

are able to recover more quickly from stressors once they do occur, resulting in greater adaptive 

capacity (Manomet Center for Conservation Sciences 2012). For example, some habitats may 

have more rapid regeneration times and/or are dominated by species with short generation times. 

Habitats with a shorter recovery period from the impacts of stressors (e.g., <20 years) may have 

greater intrinsic adaptive capacities than slower developing or recovering habitats, as these 

habitats may be more intrinsically vulnerable to the potential intervening effects of climate 

change.

3. Habitat Diversity 

Habitats that include diverse physical and topographical characteristics (e.g., variety in aspects, 

sediment types) may be better able to persist under changing climate conditions than habitats that 

are less varied because they exist across widely differing conditions (Manomet Center for 

Conservation Sciences 2012). The level of diversity of component species and functional groups 

in a habitat may also affect its adaptive capacity (or sensitivity) to climate change impacts. For 

example, in habitats where each functional group is represented by multiple species, response to 

changes in climate varies among the species resulting in greater adaptive capacity (Glick et al. 

2011). Dependency on a single keystone or foundation species can also affect the adaptive 

capacity of the habitat, contingent upon the species vulnerability to climate change. 

4. Management Potential 

Humans have the potential to intervene and change habitats in ways that reduce the impacts of 

climate change. Management potential reflects our ability to impact the adaptive capacity and 

resilience of a habitat to climate and climate-driven changes. Management potential can be 

evaluated in two ways: (1) Societal value - Is the habitat highly valued? Habitats with a high 

societal value likely have higher adaptive capacity, as people may have a greater interest in 

protecting and/or maintaining them; and (2) Managing or alleviating climate impacts - Can 

habitat impacts be managed or alleviated? If human intervention or management has a high 

likelihood of alleviating climate impacts, the adaptive capacity of the habitat is likely higher. The 

costs and benefits of management actions will vary among habitats. Actions will be most feasible 

when resources are culturally and economically valued and the costs of implementing new 

management strategies are low. 

Model Elements – Species 

This section lists the elements that were considered in the expert elicitation-based vulnerability 

assessment model for species.3

Species Sensitivity & Exposure 

1. Climate and Climate-Driven Factors

Species sensitivity to climate and climate-driven factors may be direct (e.g., physiological) or 

indirect (e.g., ecological relationships). Physiological sensitivity is directly related to a species’ 

physiological ability to tolerate changes in climate or climate-driven factors that are higher or 

lower than the range that they currently experience. Species life history may also be affected by 

changes in climate or climate-driven factors. Species that are able to tolerate a wide range of 

variables are likely less sensitive to climate change (Glick et al. 2011). Ecological relationships 

(e.g., predator/prey, foraging, habitat, pollination, dispersal, competition) may also be affected 

3 Elements generated by EcoAdapt.

21
by climate or climate-driven factors; those relationships significantly affected by small changes 

in climate likely have higher sensitivity. Climate and climate-driven factors considered included 

air temperature, ocean temperature, precipitation, chemistry (i.e., salinity, oxygen, pH), sea level 

rise, wave action, currents/mixing/ stratification, coastal erosion, and others. Species benefits 

from climate and climate-driven factors were also considered. 

2. Disturbance Regimes 

Species may be sensitive to particular disturbance regimes such as wind, flooding, diseases, or 

storms, among others. Species that experience larger changes in response to small changes in 

disturbance regimes are likely more sensitive (Lawler 2010). 

3. Future Climate Exposure 

A number of climate and climate-driven factors may be important to consider for marine and 

coastal species. These factors may include, but are not limited to: increased air or ocean 

temperature, changes in precipitation, sea level rise, changes in salinity, decreased oxygen or pH, 

increased flooding, and others. In addition to ranking exposure, participants were asked to 

document any potential areas of refugia from a particular climate or climate-driven change.

4. Life History4

Species reproductive strategy may influence sensitivity to climate change; for example, species 

with longer generation times and fewer offspring (K-selection) may be at increased extinction 

risk under long-term climate change. Species with a short generation time that produce many 

offspring (r-selection) may be better able to take advantage of climate changes (Glick et al. 

2011). 

5. Dependencies

Species that use multiple habitats or have multiple prey or forage species are likely less sensitive 

to climate change (generalist). Conversely, species with very narrow habitat needs, single prey or 

forage species, or dependence on another sensitive species or habitat for life history purposes 

likely have greater sensitivity to climate changes (specialist). 

6. Non-Climate Stressors 

Non-climate stressors may have independent, synergistic, additive, or antagonistic effects with 

climate change (Hansen and Hoffman 2011). Species that have to endure multiple non-climate 

stressors may be more sensitive to climate changes. Non-climate stressors for marine and coastal 

species may include land use change, aquaculture, energy production, roads and armoring, 

overwater/underwater structures, dredging, harvest, invasive and other problematic species, 

recreation, or pollution and poisons, among others. Participants were asked to identify nonclimate stressors most likely to increase sensitivity of the species to climate change, assess the 

degree to which the stressor affects sensitivity and degree of current exposure (both local and 

regional) to the stressor, and evaluate confidence. 

Species Adaptive Capacity

1. Extent, Status and Dispersal Ability 

Species that are currently widespread in their geographic extent, with a robust population status, 

high connectivity, and a high ability to disperse may be better able to withstand and persist into 

the future despite climate and non-climate stressors. Species that are endemic, endangered, or 

with isolated or fragmented populations and/or limited ability to disperse will likely have lower 

4 Though information regarding species life history was collected from workshop participants and included in the 

species assessment reports, this information was not included in analysis of vulnerability.

22
adaptive capacity (Manomet Center for Conservation Sciences 2012). Geographic extent, 

population status, population connectivity, and dispersal distance were considered for marine and 

coastal species.

2. Intraspecific/Life History Diversity 

Species that demonstrate a diversity of life history strategies (e.g., variations in age at maturity, 

reproductive or nursery habitat use, or resource use) are likely to have greater adaptive capacity. 

Similarly, species able to express different and varying traits (e.g., phenology, behavior, 

physiology) in response to environmental variation have greater adaptive capacity than those that 

cannot modify their physiology or vary behavior to better cope with climate changes and its 

associated effects. Many species exhibit phenotypic plasticity in response to inter-annual 

variation in temperature. Some species and/or populations will be better able to adapt 

evolutionarily to climate change. For example, species may have greater adaptive capacity if 

they exhibit characteristics such as faster generation times, genetic diversity, heritability of traits, 

larger population size, or multiple populations with connectivity among them to allow for gene 

flow.

3. Management Potential 

Humans have the potential to intervene in ways that reduce the impacts of climate change on a 

particular species. Management potential reflects our ability to impact the adaptive capacity and 

resilience of a species to climate and climate-driven changes. Management potential can be 

evaluated in two ways: (1) Societal value - Is the species highly valued? Species with a high 

societal value (e.g., commercial fish species) likely have higher adaptive capacity, as people may 

have a greater interest in protecting and/or maintaining their populations; and (2) Managing or 

alleviating climate impacts - Can impacts on the species be managed or alleviated? If human 

intervention or management has a high likelihood of alleviating climate impacts, the adaptive 

capacity of the species is likely higher. The costs and benefits of management actions will vary 

among species. Actions will be most feasible when resources are culturally and economically 

valued and the costs of implementing new management strategies are low. 

Model Elements – Ecosystem Services

This section lists the elements that were considered in the expert elicitation-based vulnerability 

assessment model for ecosystem services.5

 

Ecosystem Service Sensitivity & Exposure 

1. Climate and Climate-Driven Factors 

The sensitivity of an ecosystem service may largely be determined by the sensitivities of those 

components (e.g., species, habitat, ecosystem process or function) that provide or support the 

service. Ecosystem services with components sensitive to climate or climate-driven factors are 

likely more sensitive. For example, the sensitivity of fisheries as an ecosystem service is largely 

determined by the sensitivity of the target fish species to climate changes. Climate and climatedriven factors considered included air temperature, ocean temperature, precipitation, chemistry 

(i.e., salinity, oxygen, pH), sea level rise, wave action, currents/mixing/stratification, coastal 

erosion, and others. Ecosystem service benefits from climate and climate-driven factors were 

also considered. 

2. Disturbance Regimes 

5 Elements generated by EcoAdapt.

23
Ecosystem services may be sensitive to particular disturbance regimes such as wind, flooding, 

diseases, or storms, among others. Services that experience larger changes in function (or ability 

to be provided) due to small changes in disturbance regimes are likely more sensitive. 

3. Non-Climate Stressors 

Non-climate stressors may have independent, synergistic, additive, or antagonistic effects with 

climate change. Ecosystem services that have to endure multiple non-climate stressors may be 

more sensitive to climate changes. Non-climate stressors for marine and coastal services may 

include land use change, aquaculture, energy production, roads and armoring, 

overwater/underwater structures, dredging, harvest, invasive and other problematic species, 

recreation, or pollution and poisons, among others. Participants were asked to identify nonclimate stressors most likely to increase sensitivity of the service to climate change, assess the 

degree to which the stressor increases sensitivity of the service, evaluate the degree to which the 

stressor currently affects the service, and evaluate confidence.

4. Future Climate Exposure 

A number of climate and climate-driven changes may be important to consider for marine and 

coastal ecosystem services. These factors may include, but are not limited to: increased air or 

ocean temperature, changes in precipitation, sea level rise, changes in salinity, decreased oxygen 

or pH, increased flooding, and others. In addition to ranking the degree to which the ecosystem 

service is likely to be affected by future climate changes, participants were asked to document 

any potential areas of refugia. 

Ecosystem Service Adaptive Capacity

1. Intrinsic Value 

Some ecosystem services may have higher intrinsic value than others (e.g., recreation or water 

quality). Because of this, people may be willing to change their behavior to continue to access 

the service, thus conferring greater adaptive capacity. However, economic drivers as well as 

service location (e.g., is it important that the service continue to be accessed in its current 

location?) may also need to be considered as they can influence adaptive capacity.

2. Management Potential 

Management potential reflects our ability to impact the adaptive capacity and resilience of an 

ecosystem service to climate and climate-driven changes. Management potential can be 

evaluated in two ways: (1) Management guidelines - How rigid or specific are the rules 

governing the management of the service itself or the areas that provide the service. For 

example, does the service fall under specific management guidelines (e.g., water quality) or does 

it occur in an area with specific management rules (e.g., marine protected area)? and (2) 

Managing or alleviating climate impacts - Can climate impacts to the service be managed or 

alleviated? If human intervention or management has a high likelihood of alleviating climate 

impacts, the adaptive capacity of the service is likely higher. The costs and benefits of 

management actions will vary among services. Actions will be most feasible when services are 

culturally and economically valued and the costs of implementing new management strategies 

are low.

Confidence Evaluation 

Each of the sensitivity, adaptive capacity, and exposure elements described above for resources 

were assigned a confidence score: High-3, Moderate-2, or Low-1. These approximate confidence 

levels were based on the Manomet Center for Conservation Sciences (2012) 3-category scale, 

24
which collapsed the 5-category scale developed by Moss and Schneider (2000) for the IPCC 

Third Assessment Report to avoid implying a greater level of certainty precision. This 

vulnerability assessment model not only evaluates the confidence associated with the individual 

element scores, but also uses these scores to estimate the overall level of confidence for each 

component of vulnerability by calculating mean confidence scores across elements.

Vulnerability Assessment Application

Methodology Application

Gulf of the Farallones National Marine Sanctuary, in collaboration with project partners, 

convened a 2-day workshop entitled A Vulnerability Assessment Workshop for the North-central 

California Coast and Ocean, held June 10-11, 2014 at Fort Mason in San Francisco, CA (see 

Appendix B for workshop agenda and participants). The main focus of the workshop was 

assessing the vulnerabilities of resources (habitats, species, and ecosystem services). 

Approximately 35 scientists and resource managers participated in this workshop, representing 

25 agencies, organizations, and academic institutions. Information from the workshop such as 

the agenda, presentations, handouts, readings, and other resources can be found on the workshop 

support page. 

This workshop was structured to provide participants with a foundation of information from 

which they could assess the vulnerabilities of selected resources. Participants were introduced to 

general vulnerability assessment theory and approaches, provided with past and projected 

climate trends in the north-central California coast region, and organized into several different 

small working group arrangements to discuss and evaluate the vulnerability of resources. 

Workshop participants were directed to apply the vulnerability assessment methodology 

described above to the list of resources. As this was an expert elicitation process, participants 

were encouraged to make decisions based on their knowledge and expertise, and the workshop 

process and vulnerability assessment methods were designed to be flexible to support 

collaborative modification and improvement. Most of the 44 resources were assessed during this 

workshop; 11 species that were not assessed at the workshop but identified as important focal 

species for the region were assessed by regional experts outside of the workshop. See Appendix 

C for a list of contributors to these assessments. 

Participant evaluations and comments were compiled and assembled into this vulnerability 

assessment report. As part of this report, individual resource vulnerability reports were created 

which synthesize participant comments and peer-review references for each resource. These 

vulnerability reports are detailed in the next section of this report. 

Peer Review Process

Each species and habitat vulnerability assessment summary was reviewed by a local expert in the 

resource, and comments and revisions from these reviewers were incorporated into the 

summaries before the completion of the final draft report. Only changes in text were accepted; 

scores provided by workshop participants were not altered through the peer review process. 

Following this first round of reviews, the complete draft vulnerability assessment report was sent 

to members of the project planning committee, including scientists and resource managers, who 

25
also reviewed the ecosystem services summaries. Comments and revisions from these reviewers 

were incorporated into the final report. See Appendix C for a complete list of reviewers.

26
Results

The vulnerabilities for all 44 focal resources are summarized in Figures 6-11. These figures are 

arranged such that resources listed in the upper left region were judged to have less vulnerability 

than those listed in the lower right region. Tables 1-3 provide the calculated vulnerability and 

component scores for all focal resources by decreasing vulnerability score. Tables 4 and 5 

present all climate and non-climate stressors that were identified in this assessment. Stressors are 

ranked from most impactful to least, based on the mean sensitivity score assigned for all species 

and habitats. 

The scores presented are comparable only within the resources considered here, and are not 

standardized in any way to other climate change vulnerability assessments. The information 

supporting these scores and figures is available in the individual Vulnerability Assessment 

Reports and should be referred to before using the overview results in decision-making. This 

vulnerability assessment can be used as a foundation from which management and planning can 

be strengthened by better integrating the effects of climate change. However, it is also important 

to continue to gather information to better understand local climate, its interactions with nonclimate stressors, and the impacts to resources. This assessment is intended to be updatable so 

that as new information becomes available on sensitivity, adaptive capacity, or exposure for a 

given resource, it can be integrated and used to re-evaluate vulnerability. 

Habitats

Figure 6. Overall vulnerabilities of eight habitats based on the climate change sensitivity, exposure, and 

adaptive capacity assessment. Overall vulnerability increases with increasing sensitivity and exposure, and 

decreasing adaptive capacity. Habitats listed in the upper left region were judged less vulnerable than those 

listed in the lower right region. Overall confidence ranged from moderate to high.

27
The eight habitats assessed were scored as having moderate to moderate-high adaptive capacity, 

but highly variable degrees of exposure and sensitivity, ranging from low-moderate to moderatehigh (Figure 6). 

The most vulnerable habitats (Table 1), beaches/dunes, estuaries, and rocky intertidal, exist at the 

land-sea interface. These habitats are expected to experience greater exposure and sensitivity to 

climate changes and non-climate stressors. Key climate-driven factors identified for the 

beach/dune, estuarine, and rocky intertidal habitats include sea level rise, wave action, and 

coastal erosion. Flooding and inundation of these habitats is a primary concern, as well as 

disturbance to the structural and functional integrity of the habitats due to increased storms, 

wind, and wave events. Key non-climate stressors identified for the three most vulnerable 

habitats include coastal armoring and invasive species. Coastal armoring inhibits the ability for a 

habitat to migrate inland or upland in response to rising sea level, and accelerated, localized loss 

of habitat may be expected in areas where the upland border of the habitat abuts roads, levees or 

other armored structures. Invasive species threaten the abundance and/or diversity of native 

species, disrupt ecosystem balance, threaten local marine-based economies and can even alter the 

habitat itself (for example, by altering dune morphology). 

The least vulnerable habitats identified (Table 1) were offshore rocky reefs and kelp forests, but 

for different reasons. Offshore rocky reefs were evaluated to have overall low-moderate 

exposure to climate factors, and low-moderate sensitivity to climate and non-climate stressors, 

whereas kelp forests were evaluated to have a high adaptive capacity due to high habitat 

diversity and a moderate-high ability to recover from impacts. Offshore rocky reefs may be less 

vulnerable to climate change because they are less exposed and less sensitive to climate impacts, 

while kelp forests will likely experience greater exposure, but are predicted to be able to better 

adapt to those impacts. 

Table 1. The calculated scores for overall vulnerability, exposure, sensitivity and adaptive capacity for the 

eight habitats assessed, ordered by decreasing vulnerability.

Beaches 

and Dunes Estuaries 

Rocky 

Intertidal Cliffs Nearshore

Pelagic 

Water 

Column

Offshore 

Rocky 

Reefs

Kelp 

Forest 

SENSITIVITY

Average 3.9 4.1 4.0 3.2 2.8 2.7 2.0 2.9

Rank Mod-High Mod-High Mod-High Moderate Moderate Moderate Low-Mod Moderate

EXPOSURE

Average 4.5 4.3 4.1 2.3 4.0 4.1 2.3 2.5

Rank High High Mod-High Low-Mod Mod-High Mod-High Low-Mod Low-Mod

ADAPTIVE CAPACITY

Average 3.1 3.5 4.0 2.8 3.3 3.7 2.7 3.9

Rank Moderate Mod-High Mod-High Moderate Moderate Mod-High Moderate Mod-High

VULNERABILITY

28
Weighted 

Score

3.1 2.8 2.0 1.5 1.5 1.1 0.5 0.3

Final 

Rank

Mod-High Mod-High Moderate Moderate Moderate Moderate Low-Mod Low-Mod

Species

Figure 7. Overall vulnerabilities of all 31 species based on the climate change sensitivity, exposure, and 

adaptive capacity assessment. Due to space limitation in the figure, two groups of species with similar scores 

have been lumped. Overall vulnerability increases with increasing sensitivity and exposure, and decreasing 

adaptive capacity. Species listed in the upper left region were judged less vulnerable than those listed in the 

lower right region. Overall confidence ranged from moderate to high.

Species were assessed as having wide-ranging adaptive capacity (Figure 7), from low adaptive 

capacity as seen in the ashy storm petrel, to moderate-high adaptive capacity, as seen in Pacific 

krill and the ochre sea star. Exposure and sensitivity were highly variable as well, ranging from 

low-moderate to high. With the exception of the pteropod and blue whale (which use the 

offshore pelagic habitat) and ashy storm petrel (which uses coastal cliff and offshore habitat), the 

majority of the top ten species identified as being most vulnerable (Table 2) are those that use the 

three most vulnerable habitats –beaches/dunes, estuaries, and the rocky intertidal. 

29
Table 2. The calculated scores for overall vulnerability, exposure, sensitivity and adaptive capacity for the 31 

species assessed, ordered by decreasing vulnerability.

Black 

Oyster 

catcher

American 

Dune 

Grass Pteropod Black Rail

Western 

Snowy 

Plover Sea Palm

Ashy 

Storm 

Petrel

Blue 

Whale

Tidewater 

Goby

Olympia 

Oyster

SENSITIVITY

Average 4.6 3.8 3.6 3.8 3.8 3.8 3.4 3.9 3.0 3.2

Rank High Mod-High Mod-High Mod-High Mod-High Mod-High Moderate Mod-High Moderate Moderate

EXPOSURE

Average 4.6 5.0 5.0 2.5 4.0 4.0 2.5 5.0 3.0 4.3

Rank High High High Low-Mod Mod-High Mod-High Low-Mod High Moderate High

ADAPTIVE CAPACITY

Average 2.9 2.5 2.7 2.0 2.8 2.9 1.8 3.8 2.0 2.9

Rank Moderate Low-Mod Moderate Low-Mod Moderate Moderate Low Mod-High Low-Mod Moderate

VULNERABILITY

Weighted 

Score

4.0 3.8 3.4 3.1 3.0 2.9 2.9 2.6 2.5 2.4

Final Rank Mod-High Mod-High Mod-High Mod-High Mod-High Mod-High Mod-High Mod-High Moderate Moderate

Red 

Abalone

Gaper 

Clam

Southern 

Sea Otter

Cassin’s 

Auklet

Brandt’s 

Cormorant

Common 

Murre

California 

Mussel Copepod

California 

Hydrocor

al, Red 

Sponge

Pigeon 

Guillemot, 

Tufted 

Puffin

Ochre Sea 

Star

SENSITIVITY

Average 3.5 2.9 2.6 3.5 3.5 3.1 2.0 3.2 3.4 3.0

Rank Mod-High Moderate Low-Mod Mod-High Mod-High Moderate Low-Mod Moderate Moderate Moderate

EXPOSURE

Average 3.0 4.1 3.5 2.5 2.6 4.1 5.0 3.1 2.5 4.1

Rank Moderate Mod-High Mod-High Low-Mod Moderate ModHighHigh Moderate Low-Mod Mod-High

ADAPTIVE CAPACITY

Average 2.8 2.7 2.5 2.9 3.0 3.4 2.9 3.2 3.2 3.5

Rank Moderate Moderate Low-Mod Moderate Moderate Moderate Moderate Moderate Moderate Mod-High

VULNERABILITY

Weighted 

Score

2.3 2.3 1.9 1.8 1.8 1.7 1.6 1.6 1.5 1.5

Final 

Rank

Moderate Moderate Moderate Moderate Moderate Moderate Moderate Moderate Moderate Moderate

30
Pacific 

Herring

Coralline 

Algae Sea Urchin

Pacific 

Sardine

Widow 

Rockfish

Northern 

Anchovy

Mole 

Crab

Blue 

Rockfish

Pacific 

Krill

SENSITIVITY

Average 2.6 2.4 3.3 3.3 3.0 2.9 2.0 3.0 1.6

Rank Low-Mod Low-Mod Moderate Moderate Moderate Moderate Low-Mod Moderate Low

EXPOSURE

Average 3.7 3.0 2.3 3.3 3.2 3.3 4.8 2.7 5.0

Rank Mod-High Moderate Low-Mod Moderate Moderate Moderate High Moderate High

ADAPTIVE CAPACITY

Average 2.9 2.4 3.2 3.8 3.5 3.4 3.4 3.7 4.0

Rank Moderate Low-Mod Moderate Mod-High Mod-High Moderate Moderate Mod-High Mod-High

VULNERABILITY

Weighted 

Score

1.5 1.4 1.2 1.2 1.1 1.1 1.0 0.7 0.1

Final 

Rank

Moderate Moderate Moderate Moderate Moderate Moderate Moderate Moderate Low-Mod

Figure 8. Overall vulnerabilities of all six fish species based on the climate change sensitivity, exposure, and 

adaptive capacity assessment. Overall vulnerability increases with increasing sensitivity and exposure, and 

decreasing adaptive capacity. Species listed in the upper left region were judged less vulnerable than those 

listed in the lower right region. Overall confidence ranged from moderate to high.

All six fish species considered in this assessment were identified as having moderate exposure 

and sensitivity to climate and non-climate stressors (Figure 8). The ability for the species to 

adapt to a changing climate is what determined the range in vulnerability. The tidewater goby 

31
was identified as being most vulnerable to climate change, and is the only fish species in the top 

ten most vulnerable of all species assessed (Table 2), primarily due to its limited geographic 

extent, fragmented habitat as a result of degradation from land use change, and limited dispersal. 

Blue rockfish was identified as being the least vulnerable of the fish species due to its robust, 

highly connected population, and great value to commercial and recreational fisheries, indicating 

that action would likely be taken to conserve the sustainability of the fishery. The most 

frequently identified climate sensitivities for fish species include pH, dissolved oxygen, salinity, 

and dynamic ocean conditions. Harvest and pollution were commonly identified non-climate 

stressors for all fish species.

Figure 9. Overall vulnerabilities of all 14 invertebrate, plant and algal species based on the climate change 

sensitivity, exposure, and adaptive capacity assessment. Overall vulnerability increases with increasing 

sensitivity and exposure, and decreasing adaptive capacity. Species listed in the upper left region were judged 

less vulnerable than those listed in the lower right region. Overall confidence ranged from moderate to high.

The diverse grouping of invertebrate, plant and algal species exhibits diverse responses to the 

vulnerability assessments, with sensitivity, exposure and adaptive capacity ranging from lowmoderate to moderate-high (Figure 9). American dune grass and sea palm, the only plant/algae 

species assessed, were identified as the most vulnerable of this group due to their relatively 

higher exposure and sensitivity and lower adaptive capacity, and are the only species of this 

group in the top ten most vulnerable of all species assessed (Table 2). Pacific krill, the least 

vulnerable species in this group and of all species assessed, was identified as having very low 

sensitivity to climate change, little to no sensitivity to non-climate stressors, and relatively high 

adaptive capacity. The species is not dependent on specific prey or a sensitive habitat, has a 

robust and highly connected population, and exhibits some degree of behavioral plasticity in 

32
response to changing environmental conditions. Generally, most invertebrate species ranked as 

having moderate exposure and sensitivity and moderate adaptive capacity.

Figure 10. Overall vulnerabilities of all 11 bird and mammal species based on the climate change sensitivity, 

exposure, and adaptive capacity assessment. Overall vulnerability increases with increasing sensitivity and 

exposure, and decreasing adaptive capacity. Species listed in the upper left region were judged less vulnerable 

than those listed in the lower right region. Overall confidence ranged from moderate to high.

The bird and mammal species assessed cover a range of vulnerabilities (Figure 10), though in 

general were identified as being more vulnerable overall as compared to fish and invertebrate 

species; in fact, half of the species in this group are in the top ten most vulnerable of all species 

assessed (Table 2). The black oystercatcher received the highest vulnerability ranking, in part 

due to its high dependency on vulnerable habitats and high sensitivity and exposure to climate 

drivers and non-climate stressors like land use change and recreation. The other highly 

vulnerable bird species include ashy storm petrel, black rail, and Western snowy plover. The 

least vulnerable bird species identified are the tufted puffin and pigeon guillemot, which were 

grouped along with the ashy storm petrel as “cavity nesters” due to their similar characteristics; 

however, unlike the petrel, the puffin and guillemot have relatively greater adaptive capacity due 

to their more robust, widespread, and connected populations. The two mammal species assessed 

varied markedly in all components of vulnerability; the blue whale was identified as having 

overall moderate-high vulnerability with high sensitivity and exposure, whereas the Southern sea 

otter was moderately vulnerable, with moderate sensitivity and exposure. However, the blue 

whale was indicated as having a greater capacity to adapt to climate changes than the sea otter.

33
Ecosystem Services

Figure 11. Overall vulnerabilities of five ecosystem services based on the climate change sensitivity, exposure, 

and adaptive capacity assessment. Overall vulnerability increases with increasing sensitivity and exposure, 

and decreasing adaptive capacity. Services listed in the upper left region were judged less vulnerable than 

those listed in the lower right region. Overall confidence was high for all ecosystem services.

The five ecosystem services assessed generally scored higher for exposure and sensitivity than 

species or habitats, ranging from moderate-high to high (Figure 11). Adaptive capacity was more 

variable, ranging from low-moderate to moderate-high. Those services that are provided 

primarily by the region’s coastal habitats were identified as being most vulnerable (Table 3) – 

flood and erosion protection, which is provided by estuarine and beach/dune habitat, carbon 

storage and sequestration, which is provided by estuarine habitat, and water quality, which is 

provided by estuarine and beach habitat. 

The two most vulnerable ecosystem services were identified by workshop participants as being 

vulnerable for very different reasons. Habitats that protect human infrastructure from flooding 

and erosion are expected to experience relatively higher exposure and sensitivity to both climatedriven and non-climate stressors that will negatively impact sediment deposition and erosion, 

compromising the ability to provide this service. Alternatively, carbon storage and sequestration 

was identified as having a lower capability to adapt to climate change, primarily due to the lack 

of public support in protecting this ecosystem service which may make management of climate 

impacts challenging.

The least vulnerable ecosystem service category, recreation and tourism, was identified as having 

relatively high capacity to adapt to climate changes because the general public values recreation 

and tourism greatly, and will likely be willing to change behavior to retain these services, for 

34
example by modifying the location and extent of recreation and tourism activities. Also, local 

economies depend on this service category, so there will likely be strong support for protecting 

the provision of recreation and tourism locally. 

Table 3. The calculated scores for overall vulnerability, exposure, sensitivity and adaptive capacity for the 

five ecosystem services assessed, ordered by decreasing vulnerability.

Flood and Erosion 

Protection Carbon Storage

Water 

Purification

Food 

Production 

Recreation & 

Tourism

SENSITIVITY

Average 4.8 3.0 3.8 3.8 3.2

Rank High Moderate Mod-High Mod-High Moderate

EXPOSURE

Average 5.0 5.0 4.0 4.0 4.0

Rank High High Mod-High Mod-High Mod-High

ADAPTIVE CAPACITY

Average 3.3 2.3 3.3 3.8 4.0

Rank Moderate Low-Mod Moderate Mod-High Mod-High

VULNERABILITY

Weighted Score 4.0 3.2 2.6 2.1 1.2

Final Rank Mod-High Mod-High Moderate Moderate Moderate

Climate and Non-Climate Stressors

Tables 4 and 5 provide a ranked list of all climate and non-climate stressors identified by 

workshop participants during the sensitivity portion of the assessment for species and habitats. 

Stressors are ranked by decreasing mean sensitivity score; the number of resources that indicated 

each stressor as a sensitivity is also included. Stressors that scored a high mean sensitivity for 

many resources (e.g. wave action and invasive species) may represent priorities for managers to 

address because they apply to multiple resources in the study region and have a high overall 

impact. Managers may also want to consider developing climate-smart adaptation strategies and 

actions that address multiple high-ranking climate and non-climate stressors together. Some 

stressors are tightly linked and may be considered as consequences of the same climate stressor, 

such as wave action and coastal erosion, which are consequences of increasing storm severity 

and frequency. 

35
Table 4. Climate stressors identified in the vulnerability assessment, listed by decreasing average sensitivity 

score for those species and habitats that identified the climate stressor as a sensitivity. Asterisk denotes those 

stressors identified by only 1 or 2 resources.

Climate Stressor Average sensitivity score Number of resources

Storm severity/frequency 4.67 6

Wave action 3.5 22

Coastal erosion 3.25 24

Salinity 3.23 26

pH 3.2 30

Sedimentation 3.17 4

Dynamic ocean conditions 

(currents/mixing/stratification)

3.14 29

Dissolved oxygen 3.08 24

Sea surface temperature 3.04 27

Sea level rise 2.94 18

Air temperature 2.81 21

Precipitation 2.54 26

Turbidity* 3 2

Upwelling* 5 1

Wind* 3 1

Pacific Decadal Oscillation* 4 1

Table 5. Non-climate stressors identified in the vulnerability assessment, listed by decreasing average 

sensitivity score for those species and habitats that identified the non-climate stressor as a sensitivity. Asterisk 

denotes those stressors identified by only 1 or 2 resources.

Non-Climate Stressor Average sensitivity score Number of resources

Roads/Armoring 3.88 8

Invasive and problematic species 3.78 17

Aircraft and vessels 3.67 3

Recreation 3.54 13

Pollution and poisons (including 

oil spills and run-off)

3.43 31

Land use change 3.33 14

Overwater/underwater structures 3.25 4

Harvest 3.07 20

Energy production 2 6

Natural predation* 4.5 2

Dredging * 4 2

Boat groundings * 3 2

Anthropogenic noise* 5 1

Disease* 5 1

Transportation * 2 1

Researcher disturbance* 1 1

36
Vulnerability Assessment Reports

The following section presents individual climate change vulnerability assessment reports for all 

44 habitats, species, and ecosystem services considered as part of the Climate-Smart Adaptation 

Project for the North-central California Coast and Ocean. Reports are listed in alphabetical order 

within resource categories, with habitat reports presented first, followed by species reports, and 

ecosystem services reports. Four reports combine information for multiple species due to the 

similarities in most aspects of vulnerability: the Cavity Nesters report includes ashy storm petrel, 

tufted puffin, and pigeon guillemot; the Surface Nesters report includes Brandt’s cormorant and 

common murre; Northern anchovy and Pacific sardine are combined in one report, as are 

California hydrocoral and red sponge. 

Each individual assessment report is formatted in the same manner, with an executive summary 

that provides a brief introduction to the resource and its characteristics, as well as a summary 

score table that provides the vulnerability component scores and confidence levels. The reports 

are comprised of evaluations and comments from an expert-elicitation workshop, peer-review 

comments following the workshop, and relevant references from the literature. Supporting 

information was either gathered from available literature and cited as such, or was provided by 

workshop participants and cited as: Vulnerability Assessment Workshop, pers. comm., 2014. 

The sections titled “additional participant comments” include information supplied by 

participants that is supplementary.

During the workshop, participants assigned one of five rankings (5: High, 4: Moderate-High, 3: 

Moderate, 2: Low-Moderate, or 1: Low) to each finer resolution element of vulnerability 

components, and provided a corresponding confidence score to the ranking. These individual 

rankings and confidence scores were then averaged (mean) to generate rankings and confidence 

scores for sensitivity, exposure and adaptive capacity. The resulting reports represent an

evaluation of vulnerability based on existing information and expert input. These reports are 

intended to help managers develop and prioritize adaptation strategies to conserve these 

resources in the face of climate change, and are intended to be living documents that can be 

revised and expanded upon as new information becomes available. 

37
Beaches and Dunes1

Executive Summary Beach and dune systems are formed 

from unconsolidated sand from coastal 

bluffs and watersheds, are shaped by a 

myriad of marine and terrestrial 

processes, and provide habitat for a 

variety of species, including pinnipeds, 

sea and shorebirds, and unique vegetation. Key climate sensitivities identified for this habitat by 

workshop participants include sea level rise, coastal erosion, wave action, and sediment supply 

and movement. Key non-climate sensitivities include coastal armoring and road construction, 

overwater/underwater structures, recreation, invasive species, and dredging. Beach and dune 

habitats are transcontinental in geographic extent, have moderate habitat connectivity, and have 

moderate structural and functional integrity due to impacts from coastal, inland, and watershed 

development. Beach and dune habitats have relatively low-moderate physical/topographical and 

functional group diversity, but moderate component species diversity, and feature key species 

such as sand crabs and talitrid amphipods. Overall, beach and dune habitats are highly valued 

and can recover quickly if they have space to migrate or have enough sediment supply to keep up 

with sea level rise and erosion. Potential management measures include beach nourishment and 

protection of retreat areas. 

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): sea level rise (5, high), 

wave action (5, high), coastal erosion (5, high), sediment supply and movement (5, high), wind 

(3, high), precipitation (2, moderate), pH (1, low) 

Climate and climate-driven changes that may benefit the habitat: coastal erosion

• Description of benefits: Increased erosion of coastal cliffs and inland areas may prove 

beneficial to some beaches by increasing supplies of sediment that enable sediment 

deposition rates to keep up with rates of sea level rise. 

Overall habitat sensitivity to climate and climate-driven factors: High

• Confidence of workshop participants: High 

Additional participant comments

Beaches and dunes are naturally very dynamic systems; if given room to migrate, they are likely 

to be resilient to climate and climate-driven changes, though much of their overall areal habitat 

extent might be lost

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Beaches and Dunes Score Confidence 

Sensitivity 4 Moderate-High 3 High

Exposure 5 High 3 High

Adaptive Capacity 3 Moderate 3 High

Vulnerability 4 Moderate-High 3 High

38
Supporting literature

Beach and dune systems are formed from unconsolidated sand from coastal bluffs and 

watersheds, and are shaped by a myriad of marine and terrestrial processes (Largier et al. 2010). 

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. 

Sea Level Rise

Sea level rise can inundate current beach and dune systems and increase rates of shoreline 

erosion, potentially forcing upland retreat of beach and dune habitats (Feagin et al. 2005). Where 

development or other barriers (i.e., cliffs) block upland retreat, beach and dune habitats could 

suffer reduced areal extent and/or increased fragmentation, shifting from continuous habitat to 

narrower, steeper, and isolated pocket beaches (Largier et al. 2010). Reductions in beach and 

dune habitat could affect many species, including pinnipeds (e.g., elephant seals, harbor seals, 

sea lions) and nesting shore birds (e.g., western snowy plover). In addition, sea level rise can 

contribute to changes in relative proportions of the different ecological zones within beach 

habitats, which could lead to propagating changes in all levels of the food web (Dugan et al. 

2008). Sea level rise can also disrupt successional dynamics and degrade habitat quality by 

preventing the formation of mature coastal dune vegetation communities (Feagin et al. 2005). 

Wave Action

Wave action, which varies seasonally and according to local and more broad scale climatic 

processes, shapes beach and dune systems, contributes to erosion, and affects key species. Wave 

heights in winter can be in excess of 8 m and are driven by extra-tropical cyclones in the North 

Pacific, smaller, shorter period waves in summer are generated from winds stemming from the 

North Pacific High (Wingfield and Storlazzi 2007), and local winds affect wave heights 

throughout the year. Waves, particularly larger wave heights associated with late winter El Niño 

events, are often the main driver of beach and dune erosion, as these large, late winter waves 

coincide with when beaches are at their narrowest widths (Storlazzi and Griggs 2000; Wingfield 

and Storlazzi 2007). Waves can also increase coastal flooding (Storlazzi and Griggs 2000; 

Wingfield and Storlazzi 2007), potentially inundating dune and beach areas and forcing 

landward retreat of these habitats (Feagin et al. 2005). Waves can also shift distributions of 

sandy shorelines. For example, shifts in the Pacific Decadal Oscillation (PDO) can alter wave 

directions, exposing sheltered beaches to significant erosion and/or rotating sandy shoreline 

segments to the north and increasing erosion in southern ends of littoral cells (Sallenger et al. 

2002). In addition, intense wave action during storms or larger wave heights coinciding with 

high tides can negatively affect key species such as sand crabs and talitrid amphipods, impacting 

larger food webs (Dugan et al. 2008) and nutrient cycling (Lastra et al. 2008). 

Coastal Erosion 

Coastal erosion can have varying impacts on beach and dune systems. For example, beach 

erosion combined with sea level rise can reduce beach and dune habitat, especially in areas 

where beaches are backed by coastal cliffs (i.e., a majority of beaches in the study area) (Largier 

et al. 2010). Reduction of beach and dune habitat can negatively impact component species such 

as sand crabs and wrack consumers, as well as species that depend on beach habitats for breeding 

and nesting (i.e., pinnipeds and seabirds) (Largier et al. 2010). Alternatively, erosion of coastal 

cliffs may help some beach and dune systems keep pace with sea level rise by increasing local 

sediment delivery and enhancing sandy beach habitat (Sarah Allen, pers. comm., 2014). In 

39
addition, erosion of upland or inland sediments can increase sediment transport and delivery to 

beach and dune areas (Sarah Allen, pers. comm., 2014). 

Sediment Supply and Movement 

Sediment supply and movement influences the areal extent of beach and dune systems, and is 

controlled by a variety of climate and climate-driven factors (i.e., wave action, coastal erosion, 

currents, precipitation), as well as by changes within the “sediment-shed” (i.e., changes in the 

watershed, coastal wetlands, or the littoral cell) (Revell et al. 2007; Largier et al. 2010; 

Vulnerability Assessment Workshop, pers. comm., 2014). Surpluses in local sediment budgets 

typically increase beach width and minimize shoreline erosion, while sediment deficits result in 

narrower beaches with significant rates of coastal erosion (Largier et al. 2010). Reductions in 

beach width can also expose dune habitats to increased wave exposure (Largier et al. 2010). 

Sediment supply will vary according to many factors. For example, short, heavy precipitation 

events can increase freshwater sediment discharge and bolster beach and dune systems, though 

this dynamic is mediated by inland water and sediment retention structures such as dams (Slagel 

and Griggs 2008; Largier et al. 2010). Alternatively, wave action can deliver or remove 

sediment, leading to dynamic changes in beach shape and size over the course of different 

seasons. 

Beaches and dunes are also sensitive to precipitation and pH, but to a lesser extent than the aforementioned factors. For example, pH can affect sand crab shell formation and the foraging value 

of beach and dune habitat (Vulnerability Assessment Workshop, pers. comm., 2014), while 

precipitation and subsequent runoff can increase sediment delivery to beach and dune systems 

and/or contribute to shifting soil salinities in dune vegetation communities (Williams et al. 1999; 

Greaver and Sternberg 2007).

II. Sensitivities to disturbance regimes

Disturbance regimes identified: wind and storms 

Overall habitat sensitivity to disturbance regimes: High

• Confidence of workshop participants: High 

Additional participant comments

Wind, influenced by air and sea surface temperatures, affects sediment supply and movement, 

periodically adding, removing, and repositioning sand within beach and dune systems. Storms 

affect wave height, influence rates of erosion, and can alter sediment supply. 

Supporting literature

Winds are typically stronger in spring and summer and weaker in fall and winter (Largier et al. 

2010). Alongshore winds increased from 1940-1990 (Bakun 1990; Schwing and Mendelssohn 

1997; Mendelssohn and Schwing 2002), and are expected to increase in all seasons in the future, 

particularly in summer and fall, due to increasing differences in land-ocean pressures and 

temperatures (Snyder et al. 2003; Auad et al. 2006; Largier et al. 2010). In addition to the 

impacts mentioned by workshop participants, winds may impact the delivery of cold, nutrientrich water to beach habitat, impacting the availability of food for suspension feeders (Dan 

Robinette, pers. comm., 2014). Storms are typically more common in winter, and can vary in 

40
intensity, magnitude, and direction according to larger climate forcings such as the El Niño 

Southern Oscillation (ENSO) or the Pacific Decadal Oscillation. 

III. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): coastal roads/armoring (5, high), 

overwater/underwater structures (4, high), recreation (3, high), invasive species (3, moderate), 

dredging (3, moderate) 

Overall habitat sensitivity to non-climate stressors: Moderate-High

• Confidence of workshop participants: High 

Overall habitat exposure to non-climate stressors: Moderate

• Confidence of workshop participants: High 

Additional participant comments

Shifting water storage demands could affect dam operations in the future, with further impacts 

on sediment delivery to beach and dune habitats. Recreation can have direct impacts on beach 

and dune systems, but is also a critical factor in maintaining stewardship support. Invasive and 

problem species outcompete native dune vegetation, can lock up foredune sand supply, and 

prevent upland migration of this system. Dredging can influence sediment supply for beach and 

dune systems by reducing supply if dredged sediment is disposed of outside the littoral cell, 

which can increase beach and dune sensitivity to climate changes. Alternatively, dredged 

materials can be used for beach nourishment, which could bolster beach and dune resilience 

(e.g., by offsetting erosion), though also negatively impact the infaunal community. 

Supporting literature

Armoring/Roads 

Coastal armoring and road construction prevent upland beach and dune migration in response to 

sea level rise and increased passive erosion, increasing the sensitivity of beach and dune systems. 

Passive erosion related to armoring or road structures can shift habitat zones downward on the 

beach profile by “drowning” upper beach areas, disproportionally degrading upper and mid 

beach habitat (Dugan et al. 2008). These effects will only become more pronounced with sea 

level rise as these structures interact with waves and tides (Dugan et al. 2008). In addition, 

armoring can replace beach habitat, reducing beach extent and negatively impacting bird species 

(Dugan et al. 2008). Armoring is projected to increase, although beach nourishment is now being 

used more frequently as an alternative (Defeo et al. 2009). 

Overwater/Underwater Structures

Overwater and underwater structures can alter sediment supply and delivery and impair the 

resiliency of beach and dune habitats. Dams and debris basins in watersheds can trap sediments 

and alter peak flows, effectively reducing sediment transport to beach and dune systems which 

increases littoral cell sediment deficits and the potential for erosion (Willis and Griggs 2003; 

Slagel and Griggs 2008; Largier et al. 2010). For example, multiple dam projects on the Russian 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

41
River reduced annual coarse-grained sediment supplies by more than 30% (Slagel and Griggs 

2008). 

Recreation

Recreational use can lead to trampling of vegetation or sensitive habitat areas, as well as to

behavioral modifications in beach and dune wildlife (e.g., bird nest abandonment and seal beach 

abandonment) (Grigg et al. 2002; Schlacher et al. 2007; Largier et al. 2010). The accumulation 

of plastics and other human trash as a result of recreation and use can negatively impact beach 

and dune systems through direct impacts to species (entanglement, ingestion, smothering) and 

indirect impacts to the habitat itself (clean-up efforts and introduction of invasive species) (EPA 

2012). Coastal recreational pressure could increase as a result of population growth and 

increased inland temperatures (Vulnerability Assessment Workshop, pers. comm., 2014). 

Invasive and problem species

Many dunes have been invaded by European beachgrass (Ammophilia arenaria), resulting in 

reduced species richness (Barbour et al. 1976), changes in dune shape and orientation relative to 

the ocean (Barbour and Johnson 1988), and degradation of the habitats that back dunes, such as 

swales (Randall and Hoshovosky 2000). Iceplant/hottentot fig (Carpobrotus edulis), another 

harmful non-native plant, creates deep mats that exclude native vegetation (California State 

Parks 2009). Additionally, non-native species such as the sea fig (Carpobrotus chilensis) and the 

Uruguayan pampas grass (Cortaderia selloana) could also negatively impact dune systems in the 

study region (ONMS 2014). Non-invasive, problem species, such as gulls, ravens, foxes, 

coyotes, dogs, feral cats, skunks and racoons often follow human activity into beach and dune 

habitat, negatively impacting shorebird species, such as the snowy plover, and altering ecological 

dynamics (Campbell 2013; Dan Robinette, pers. comm., 2014). 

IV. Other sensitivities: none identified 

Additional participant comments

Increasing pressure for more water storage projects may result in impacts to the supply and 

transport of replenishing sediments to beach and dune habitats. Additionally, a growing 

population and increased inland air temperatures may result in increased pressure on beach and 

dune habitats. Because of their dynamic nature beach and dune habitats that have sufficient 

room to migrate will probably be fairly resilient to climate change impacts. However, much of 

the areal extent of these habitats may be lost.

Adaptive Capacity

I. Extent, integrity, and continuity

Geographic extent of the habitat: 5 (Transcontinental) 

• Confidence of workshop participants: High 

Structural and functional integrity of habitat: 3 (Altered but not degraded) 

• Confidence of workshop participants: Moderate 

Continuity of habitat: 3 (Patchy across an area with some connectivity among patches)

• Confidence of workshop participants: Moderate 

42
Supporting literature

Sandy beaches are a small but important component of the North-central California coastline

(SIMoN 2014), and occur in varying forms, primarily pocket beaches tucked amongst the rocky 

coastline and narrow beaches that front cliffs, as well as occasional linear beaches backed by 

dunes (Hapke et al. 2006). The largest beaches occur near the Gualala and Russian Rivers, and 

beach/dune systems occur near Bodega Head and Point Reyes (Largier et al. 2010). The 

structural and functional integrity of dunes is undermined by beach front development, which 

prevents natural adaptation to changes in shoreline stability (Clark 1996), erosion, and sea level 

rise (Nordstrom 2000; Schlacher et al. 2007). Other factors, such as altered sediment dynamics

and coastal and watershed perturbations, also decrease the integrity of this ecosystem. 

II. Resistance and recovery

Habitat resistance to the impacts of stressors/maladaptive human responses: Low-Moderate

• Confidence of workshop participants: Moderate 

Ability of habitat to recover from stressor/maladaptive human response impacts: Moderate

• Confidence of workshop participants: Moderate 

Additional participant comments

Beach and dune habitats are naturally very dynamic, and with sufficient room to migrate, may 

prove to be resilient to climate change impacts. However, coastal development and coastal 

roads/armoring may adversely impact the ability of beach and dune habitats to recover from and 

adapt to rising sea levels and increased coastal erosion.

III. Habitat diversity

Physical and topographical diversity of the habitat: Low-Moderate

• Confidence of workshop participants: Moderate 

Diversity of component species within the habitat: Moderate

• Confidence of workshop participants: Moderate 

Diversity of functional groups within the habitat: Low-Moderate

• Confidence of workshop participants: Moderate

Keystone or foundational species within the habitat: Beach and dune habitat quality depends on 

some key species, such as sand crabs (Emerita analoga) that are critical to the food web, and 

talitrid amphipods (family Talitridae) for wrack processing.

Additional participant comments

Other diversity factors important to consider are landscape-level diversity and an intact habitat 

mosaic, as these are important factors in determining the functionality and value of beach and 

dune habitats. 

Supporting literature

Beaches and dunes are formed from unconsolidated sand from watersheds and coastal bluffs, and 

are constantly being shaped by wind, waves, and tides. Dune habitats are found in the 

supralittoral zone, while beach habitats feature three ecological zones: supra-littoral at or above 

43
the drift line, middle intertidal, and lower intertidal (Largier et al. 2010). Landscape level 

diversity and intact habitat mosaics determine the functional and habitat value of beach and dune 

systems. (Peter Baye, pers. comm., 2014). Beaches and dunes provide key habitat for a variety of 

species. For example, dunes are home to many unique and threatened plants, while the 

uppermost intertidal zones of sandy beaches are important for California grunion (Leuresthes 

tenuis) and smelt spawning (Thompson 1919) and pinniped pup rearing. Open beach and dune 

habitats also provide feeding and nesting habitat for shorebirds, including the threatened western 

snowy plover (Charadrius alexandrines nivosus), which nests in the dry sand zone. Sand crabs 

are the most abundant invertebrate in beach and dune habitats, acting as a critical component of 

the food web by filter-feeding plankton from the ocean and acting as a food source for 

shorebirds, gulls and sea otters (Largier et al. 2010; SIMoN 2014). Talitrid amphipods play a key 

role in wrack processing and nutrient cycling (Lastra et al. 2008). Both of these groups are highly 

sensitive to changes in erosion and storms, among other factors (Largier et al. 2010). 

IV. Management potential

Value of habitat to people: High

• Confidence of workshop participants: High 

• Description of value: Humans value beach and dune habitats for their natural storm 

protection, aesthetics, and for the recreational opportunities that they provide, such as 

surfing, fishing, vacations, and driving of off-road vehicles.

Likelihood of managing or alleviating climate change impacts on habitat: Moderate

• Confidence of workshop participants: High 

• Description of potential management options: Management likelihood varies by location. 

For example, some beaches and dunes will likely be prioritized for beach nourishment, 

especially those that are of high recreational or ecological value. Protected areas also 

provide opportunities for beach and dune systems to retreat in the face of sea level rise 

and erosion. In comparison, beach and dune areas that are backed by development or 

natural barriers (i.e., cliffs) that prevent migration or prevent natural beach nourishment

are likely to disappear. For many of these threatened locations, there is no economic 

justification for nourishment intervention based on their perceived level of use. Beach 

nourishment or near-shore disposal sites for dredged materials are available management 

steps to bolster the adaptive capacity of beach and dune systems. 

Supporting literature

Beach clean-ups are a means of both improving quality of habitat and building public support 

and investment in beach health (Dan Robinette, pers. comm., 2014). 

V. Other adaptive capacities:

Critical factors not addressed that may affect habitat’s adaptive capacity: sediment supply and 

transport 

• Degree to which these factors affect the habitat’s adaptive capacity: High

• Confidence of workshop participants: High 

44
Additional participant comments 

Sediment supply and transport are critical to beach and dune habitats, and are impacted by both 

climate change impacts and human disturbances.

Exposure 

I. Future climate exposure6

Future climate and climate-driven factors identified (score7, confidence8): sea level rise (5, high), 

increased storminess (5, high), increased coastal erosion and runoff (5, high), increased flooding 

(3, low) 

Degree of exposure to future climate and climate-driven factors: High

• Confidence of workshop participants: High 

Additional participant comments

Potential refugia areas include beaches and dunes that are very wide and/or those that have room 

to migrate inland (i.e., are not back by development or natural barriers), which may represent 

only a small percentage of habitat area within the study region. Beach and dune systems are 

sensitive to extreme increases in the duration or frequency of flooding. 

Literature Cited 

Auad, G., A. Miller, and E. Di Lorenzo. 2006. Long-term forecast of oceanic conditions in California and their

biological implication. Journal of Geophysical Research 111, C09008, doi:10.1029/2005JC003219.

Bakun, A. 1990. Global climate change and intensification of coastal ocean upwelling. Science 247:198-201.

Barbour, M.G., T.M. De Jong, and A.F. Johnson. 1976. Synecology of beach vegetation along the Pacific Coast of 

the United States of America: a first approximation. Journal of Biogeography 3:55–69. 

Barbour, M.G., and A.F. Johnson. 1988. Beach and dune. Pages 223–261 in M.G. Barbour and J. Major, eds., 

Terrestrial vegetation of California. California Native Plant Society Special Publication No. 9. Sacramento, 

CA. Bird, E.C.F. 2000. Coastal Geomorphology: an Introduction. John Wiley, Chichester, UK.

California State Parks. 2009. Iceplant. Retrieved July 17, 2014: 

http://www.parks.ca.gov/pages/23071/files/iceplant%203up%20final.pdf. 

Campbell, C. 2013. Monitoring Western Snowy Plovers at Point Reyes National Seashore, Marin County, 

California: 2012 annual report. Natural Resource Technical Report. NPS/SFAN/NRTR—2013/825. 

National Park Service. Fort Collins, Colorado. Published Report-2204673. Available at 

http://www.sfnps.org/download_product/4526/0. 

Clark, J.R. 1996. Coastal Zone Management Handbook. CRC Press, Boca Raton, FL.

Defeo, O.A. McLachlan, D. Schoeman, T. Schlacher, J. Dugan, A. Jones, M. Lastra, F. Scapini. 2009. Threats to 

sandy beach ecosystems: a review. Estuar. Coastl. Shelf Sci. 81:1-12.

Dugan, J.E., D.M. Hubbard, I. F. Rodil, D. L. Revell and S. Schroeter. 2008. Ecological effects of coastal armoring

on sandy beaches. Marine Ecology 29: 160-170.

Environmental Protection Agency (EPA). 2012. Marine Debris Impacts. Accessed February 19, 2015. 

http://water.epa.gov/type/oceb/marinedebris/md_impacts.cfm. 

Feagin, R.A., D.J. Sherman, and W.E. Grant. 2005. Coastal erosion, global sea-level rise, and the loss of sand dune

plant habitats. Frontiers in Ecology and the Environment 7:359-364

Greaver T.L. and L.S.L. Sternberg. 2007. Fluctuating deposition of ocean water drives plant function on coastal sand 

6 Supporting literature for future exposure to climate factors is provided in the introduction. 7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

45
dunes. Global Change Biology 13, 216-223.

Grigg, E. K., Green, D. E., Allen, S.G., and Markowitz, H. 2002. Diurnal and nocturnal haul out patterns of harbor 

seals (Phoca vitulina richardsi) at Castro Rocks, San Francsico Bay, California. California Fish and Game 

88(1):15-27. 

Hapke, C.J., Reid, D., Richmond, B.M., Ruggiero, P., List, J. 2006. National assessment of shoreline change Part 3:

Historical shoreline change and associated coastal land loss along sandy shorelines of the California Coast. 

U.S.Geological Survey Open File Report 2006-1219.

Kundzewicz, Z., Mata, L., Arnell N., Döll, P., Kabat, P., Jiménez, B., Miller, K., Oki, T., Sen, Z. and I.

Shiklomanov. 2007. Freshwater resources and their management. Climate Change 2007: Impacts, 

Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report of the 

Intergovernmental Panel on Climate Change, M.L. Parry, O.F. Canziani, J.P. Palutikof, P.J. van der Linden 

and C.E. Hanson, Eds., Cambridge University Press, Cambridge, UK, 173-210.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine SanctuariesAdvisory Councils. 121pp. 

Lastra, M., H.M. Page, J.E. Dugan, D.M. Hubbard, and I.F. Rodil. 2008. Processing of allochthonous macrophyte

subsidies by sandy beach consumers: estimates of feeding rates and impacts on food resources. Marine 

Biology 154:163-174.

Mendelssohn, R. and F.B. Schwing. 2002. Common and uncommon trends in SST and wind stress in California and

Peru-Chile current systems. Progress in Oceanography 53. p.141-162.

Nordstrom. K.F. 2000. Beaches and dunes of developed coasts. Cambridge University Press, Cambridge, UK.

Office of National Marine Sanctuaries. 2014. Cordell Bank and Gulf of the Farallones National Marine Sanctuaries 

Expansion Draft Environmental Impact Statement. U.S. Department of Commerce, National Oceanic and 

Atmospheric Administration, Office of National Marine Sanctuaries, Silver Spring, MD.

Randall, J.M. and M.C. Hoshovsky. 2000. Invasive Plants of California’s Wildlands. University of California Press. 

Berkely, CA.

Revell, D.L., J.J. Marra, and G.B. Griggs. 2007. Sandshed Management. Special issue of Journal of Coastal

Research - Proceedings from the International Coastal Symposium 2007, Gold Coast, Australia. SI 50:93-8. 

Sallenger, A.H., W. Krabill, J. Brock, R. Swift, S. Manzinar, and H.F. Stockdon. 2002. Sea-Cliff erosion as a

function of beach changes and extreme wave run-up during the 1997-98 El Niño. Marine Geology 

187:279-297.

Sanctuary Integrated Monitoring Network (SIMoN): Gulf of the Farallones National Marine Sanctuary. 2014. 

Retrieved June 18, 2014 from http://sanctuarysimon.org/farallones/.

Schlacher, T.A., J.E. Dugan, D.S. Schoeman, M. Lastra, A. Jones, F. Scapini, A. McLachlan, and O. Defeo. 2007.

Sandy beaches at the brink. Diversity and Distributions 13:556-560.

Schwing, F. B. and R. Mendelssohn. 1997. Increased coastal upwelling in the California Current System. Journal of

Geophysical Research 102:3421-3438.

Slagel, M. J. and G.B. Griggs. 2008. Cumulative Losses of Sand to the California Coast by Dam Impoundment.

Journal of Coastal Research 24(3)571-584.

Snyder, M.A., L.C. Sloan, N.S. Diffenbaugh, and J.L. Bell. 2003. Future climate change and upwelling in the

California Current. Geophysical Research Letters 30:1-4.

Storlazzi, C. and G. Griggs. 2000. Influence of El Niño-Southern Oscillation (ENSO) events on the evolution of

Central California's shoreline. GSA Bulletin 112 (2), 236-249.

Thompson, W. F. 1919. The spawning of the grunion (Leuresthes tenuis ). California Fish and Game 5:201.

Williams, K., K.C. Ewel, R.P. Stumpf, F.E. Putz and T.W. Workman. 1999. Sea-level rise and coastal forest retreat

on the west coast of Florida, USA. Ecology 80:2045-2063

Willis, C.M. and G.B. Griggs. 2003. Reductions in Fluvial Sediment Discharge by Coastal Dams in California and

implications for Beach Sustainability. Journal of Geology 111:167-182

Wingfield, D.K. and C.D. Storlazzi. 2007. Variability in oceanographic and meteorologic forcing along Central

California and its implications on nearshore processes. Journal of Marine Systems v. 68, p. 457-472.

46
Cliffs1

Executive Summary Cliffs2 occur as steep, rocky faces of 

variable height along the coastline and 

among the Farallon Islands. Key 

climate sensitivities identified for this 

habitat by workshop participants 

include coastal erosion, extreme 

weather events, wave action, sea level rise, and precipitation. Key non-climate sensitivities

include land use changes, roads and armoring and urban runoff. Cliffs are transcontinental in 

geographic extent, occurring along much of the coastline within the study area. They have 

moderate-high structural and functional integrity, featuring occasional alterations (i.e., seawalls 

or revetments). Cliffs have moderate habitat connectivity but low component species and 

functional group diversity. They feature highly adapted native vegetation and provide critical 

habitat for a variety of seabirds and pinnipeds. Cliffs are generally resistant to climate changes, 

though resistance varies by rock type, and have low recovery potential once disturbed or 

degraded. Cliffs are valued for their aesthetic qualities and recreational opportunities.

Management options are primarily limited to urban or developed areas, and include managing 

urban development and runoff to minimize exposure and contribution to coastal cliff erosion. 

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score3, confidence4): extreme weather events (5, 

high), wave action (4, high), coastal erosion (4, high), precipitation (3, moderate), sea level rise 

(3, high), air temperature (2, moderate), salinity (2, low) 

Climate and climate-driven changes that may benefit the habitat: none identified

Overall habitat sensitivity to climate and climate-driven factors: Moderate

• Confidence of workshop participants: High

Additional participant comments

In general, cliffs are more sensitive to changes in extremes rather than mean changes in these 

factors. 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report. 2 In completing this vulnerability assessment, workshop participants evaluated cliffs that provide suitable habitat 

(i.e., not unstable, sandy cliffs).

3 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

4 Confidence level indicated by workshop participants.

Cliffs Score Confidence 

Sensitivity 3 Moderate-High 3 High

Exposure 2 Low-Moderate 2 Moderate

Adaptive Capacity 3 Moderate-High 3 High

Vulnerability 3 Moderate 3 High

47
Supporting literature

Literature review was conducted for those factors scoring 3 or higher, although the other 

sensitivities identified should also be considered. 

Extreme Weather Events

Extreme weather events (i.e., storms) increase erosion and can lead to bursts of large-scale 

coastal erosion (Center for Ocean Solutions 2014). Storm events such as El Niños usually 

coincide with larger wave heights, which can accelerate basal cliff erosion and lead to large-scale 

cliff failure or retreat (Griggs and Russell 2012, Sanctuary Integrated Monitoring Network 

(SIMoN) 2014). For example, the winter 1997-98 El Niño caused 12 coastal homes in Pacifica to 

be condemned when local cliff tops retreated 13 m and cliff bases retreated 10 m (SIMoN 2014). 

Compared to annual erosion rates in this area, the 1997-98 El Niño caused the same amount of 

erosion as would be expected over a 50-year period (SIMoN 2014). Storms also typically 

increase precipitation, contributing to runoff-based erosion and ground destabilization via 

saturation (Griggs and Russell 2012). Storms are typically more common in winter, and can vary 

in intensity, magnitude, and direction according to larger climate forcings such as the El Niño 

Southern Oscillation (ENSO) or the Pacific Decadal Oscillation (PDO) (Largier et al. 2010).

Wave Action

Wave action contributes to the basal erosion of cliffs and erosion of protective beach fronts 

(Griggs and Russell 2012). Wave action varies seasonally and according to local and more broad 

scale climatic processes. For example, wave heights in winter can be in excess of 8 m and are 

driven by extra-tropical cyclones in the North Pacific, smaller, shorter period waves in summer 

are generated from winds stemming from the North Pacific High (Wingfield and Storlazzi 2007), 

and local winds affect wave heights throughout the year. Wave heights can also increase during 

ENSO events (Storlazzi and Griggs 2000, Wingfield and Storlazzi 2007) and/or shift direction 

with shifts in the PDO (Sallenger et al. 2002). In general, cliffs along headlands, points, and 

promontories experience higher wave action and subsequent impacts (Hapke and Reid 2007). 

Coastal Erosion 

The sensitivity of cliffs to erosion varies by geologic rock type (Hapke and Reid 2007), the 

presence of internal weaknesses, orientation, wave exposure, the width of protective fronting 

beaches (Griggs et al. 2005, Griggs and Russell 2012), and terrestrial processes (i.e., runoff) 

(Griggs and Russell 2012). For example, higher relief cliffs tend to feature more stable rock 

types (i.e., granite, volcanic, or Franciscan Complex/Formation), while lower relief features such 

as coastal bluffs or marine terraces are often composed of weaker rock types (i.e., Tertiary 

sedimentary units such as sandstone, shale, siltstone, or alluvium) (Griggs and Patsch 2004, 

Hapke and Reid 2007). Rates of erosion vary widely over small spatial scales (Hapke and Reid 

2007, SIMoN 2014). Slope failures can greatly increase local rates of erosion, and have occurred 

in many portions of the study region (i.e., along the south-facing cliffs along the Point Reyes 

headland and along the Devil’s Slide between Half Moon Bay and Point San Pedro) (Hapke and 

Reid 2007, SIMoN 2014).

Erosion can reduce and/or degrade habitat area. For example, on-going erosion can alter 

vegetation composition and structure, while large-scale erosion (i.e., landslides, slumps, 

blockfalls) can degrade or eliminate pinniped resting/haul out areas and nesting habitat for 

seabirds (Hapke and Reid 2007). In addition, erosion can limit recreational opportunities (i.e., by 

48
creating dangerous or impassable trail conditions) (Largier et al. 2010) or affect human 

infrastructure (i.e., highways, housing, and sewage lines) (Griggs and Russell 2012, SIMoN 

2014). 

Precipitation

Precipitation can increase erosion potential via runoff and decrease cliff stability, contributing to 

physical alterations of cliff habitat (Griggs and Patsch 2004, Largier et al. 2010, Griggs and 

Russell 2012). For example, runoff-induced erosion is one of the main drivers of erosion in cliffs 

protected from wave action by large fronting beaches (Griggs and Russell 2012). Precipitation 

can also contribute to ground saturation, which can destabilize cliff areas and potentially lead to 

landslides (Griggs and Patsch 2004, Griggs and Russell 2012). 

Sea Level Rise

Sea level rise can increase the exposure of cliffs to wave action by reducing the width of 

protective beach front area and/or exposing new, higher cliff areas to wave action (Heberger et 

al. 2009, Griggs and Russell 2012). This increased exposure to wave attack can accelerate 

erosion (Heberger et al. 2009). These interconnected impacts may be more prevalent in the study 

area during El Niño winters, which feature warmer sea surface temperatures, higher sea levels, 

and stronger storms with higher waves and storm surge (Storlazzi and Griggs 2000). Digital 

elevation models of the South Farallon Islands indicate that a rise of 0.5m would result in 

permanent flooding of 23,000 m2 of island habitat (Point Blue, unpublished data), resulting in a 

redistribution of wildlife populations that would impact seabird habitat by reducing the available 

nesting areas and leading to nest destruction (Largier et al. 2010). 

II. Sensitivities to disturbance regimes

Disturbance regimes identified: storms, wind, flooding, and drought 

Overall habitat sensitivity to disturbance regimes: Moderate-High

• Confidence of workshop participants: High

Supporting literature

Storms can increase wave heights, sea level, and precipitation, potentially increasing erosion 

rates or leading to cliff failure (Griggs and Russell 2012, Center for Ocean Solutions 2014, 

SIMoN 2014). Wind affects local wave heights (Wingfield and Storlazzi 2007, Largier et al. 

2010). Alongshore winds increased from 1940-1990 (Bakun 1990, Schwing and Mendelssohn 

1997, Mendelssohn and Schwing 2002), and are expected to increase in all seasons in the future, 

particularly in summer and fall, due to increasing differences in land-ocean pressures and 

temperatures (Snyder et al. 2003, Auad et al. 2006, Largier et al. 2010). Terrestrial flooding can 

increase runoff-based erosion or ground saturation and destabilization in cliff habitats, while 

flooding of lower portions of marine terraces can wash away thin soil layers used by burrow 

nesting species (Largier et al. 2010). Drought can affect vegetation growing in cliff habitat. 

49
III. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score5, confidence6): land use change (4, high), coastal 

roads/armoring (4, high), urban runoff (3, moderate), recreation (2, high), invasive species (2, 

moderate), overwater/underwater structures (2, moderate) 

Overall habitat sensitivity to non-climate stressors: Moderate

• Confidence of workshop participants: High

Overall habitat exposure to non-climate stressors: Low

• Confidence of workshop participants: High

Additional participant comments

Though overall exposure to non-climate stressors is low, exposure in urban areas (especially for 

runoff and land use change) is much higher than in non-developed portions of the study area. 

Supporting literature

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. 

Land Use Changes

Land use changes (i.e., development, watershed alterations) that disrupt sediment supply to 

protective fronting beaches can increase the potential for erosion and retreat in coastal cliffs 

habitats (Willis and Griggs 2003, Hapke and Reid 2007, Slagel and Griggs 2008, Largier et al. 

2010). For example, when beaches shrink in response to sediment deficits, cliffs can be exposed 

to higher wave action (Largier et al. 2010). In addition, development and landscape irrigation on 

top of coastal cliffs can increase internal pore pressures of cliff materials, decreasing resilience 

and accelerating coastal erosion (Griggs and Patsch 2004). The construction of jetties or 

breakwaters can also increase wave attack on down coast cliffs by depriving fronting beaches of 

sand, while simultaneously decreasing wave attack on up coast cliffs by increasing sediment 

delivery to their respective fronting beaches (Griggs and Patsch 2004). 

Roads and Armoring 

Coastal armoring is typically practiced to protect existing infrastructure (i.e., roads, 

development) (California Department of Boating and Waterways (CDWB) and State Coastal 

Conservancy (SCC) 2002). For example, engineered structures such as revetments or seawalls 

placed at cliff bases can reduce erosion and cliff retreat rates by reducing wave exposure (Hapke 

and Reid 2007). The study region features many of these protective structures, especially in 

developed areas (CDWB and SCC 2002, Hapke and Reid 2007, Hanak and Moreno 2008). For 

example, as of 1985, 77% of 14.4 km of shoreline north of Monterey Bay had been armored 

(Griggs and Patsch 2004). However, these structures only serve as a temporary solution, they 

typically cannot completely prevent cliff erosion (Hapke and Reid 2007), and they can limit 

sediment delivery to local beaches and/or prevent migration of beaches in response to sea level 

rise, effectively reducing protective fronting for coastal cliff habitats (CDBW and SCC 2002, 

5 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

6 Confidence level indicated by workshop participants.

50
Hapke and Reid 2007, Dugan et al. 2008, Largier et al. 2010). In addition, armoring can reduce 

habitat area for coastal cliff species (Barron et al. 2011).

Urban Runoff 

Urban runoff can contribute to runoff erosion in coastal cliff habitats and/or increase the 

likelihood of cliff failure by oversaturating the ground (Griggs and Russell 2012). For example, 

installed culverts and drains can concentrate runoff to specific portions of bluff faces, 

accelerating erosion in these areas (Griggs and Patsch 2004). Projected population growth and 

rapid urbanization along the Central California coastline could lead to the installation of more 

impervious surfaces (Jaiswal and Newkirk 2005), which can increase rates of urban runoff and 

exacerbate erosion trends in coastal cliff habitats. 

IV. Other sensitivities identified by workshop participants

Other critical factors likely to influence the sensitivity of the habitat: tsunamis and earthquakes

• Confidence of workshop participants: Moderate-High

• Confidence of workshop participants in the degree to which these factors influence 

habitat sensitivity: Moderate 

Supporting literature

Extreme events such as earthquakes and tsunamis can lead to temporary exposure to extreme 

wave heights or cliff failures. The study region lies along the active San Andreas Fault system, 

an 800-mile long transform boundary between the Pacific and North American plates (Ryan et 

al. 2001). More specifically, the study region occurs along the San Gregorio Fault zone, a 250-

mile long stretch of coastal faults spanning from Bolinas Bay to Big Sur (Ryan et al. 2001). 

Earthquakes can cause fracturing, sliding, or slumping of cliffs and bluffs (Ryan et al. 2001, 

CDBW and SCC 2002), reducing habitat area and/or quality. Tsunamis can be generated locally 

(i.e., via subaerial or submarine landslides) or in faraway locations when large areas of seafloor 

are rapidly displaced (Ryan et al 2001). Tsunamis can increase erosion, contribute to cliff 

failures, and/or scour cliff faces, affecting cliff vegetation and cliff-nesting species. 

Adaptive Capacity

I. Extent, integrity, and continuity

Geographic extent of the habitat: 5 (Transcontinental) 

• Confidence of workshop participants: High

Structural and functional integrity of habitat: 4 (Minor to moderate alterations)

• Confidence of workshop participants: High 

Continuity of habitat: 3 (Patchy across an area with some connectivity among patches)

• Confidence of workshop participants: High

Supporting literature

Over 72% of California’s coastline features cliffs of varying heights (Griggs and Patsch 2004). 

Cliff habitats are periodically disrupted by coastal lowlands, such as beaches, dunes, and 

estuaries (Griggs and Patsch 2004). Coastal cliffs occurring along developed areas of the study 

51
region feature some alterations, including seawalls and/or revetments used to reduce wave 

exposure and erosion (Hapke and Reid 2007). 

II. Resistance and recovery

Habitat resistance to the impacts of stressors/maladaptive human responses: Moderate-High

• Confidence of workshop participants: Moderate 

Ability of habitat to recover from stressor/maladaptive human response impacts: Low-Moderate 

• Confidence of workshop participants: Moderate 

Supporting literature

Cliffs are composed of different uplifted rock types that have been eroding over many centuries 

(CDBW and SCC 2002, Griggs and Patsch 2004), demonstrating how this habitat is generally 

resistant to extreme changes in response to changing climate conditions. Resistance also varies 

by rock type (CDBW and SCC 2002, Hapke and Reid 2007), with the Franciscan Formation, 

granitic and volcanic rocks being most resistant to erosion (Griggs and Patsch 2004). However, 

unlike beaches and dunes, which can recede or advance from season to season, cliff erosion only 

progresses landward (Griggs and Patsch 2004), limiting the recovery potential for cliff habitats. 

III. Habitat diversity

Physical and topographical diversity of the habitat: Low-Moderate

• Confidence of workshop participants: High 

Diversity of component species within the habitat: Low

• Confidence of workshop participants: High 

Diversity of functional groups within the habitat: Low

• Confidence of workshop participants: High 

Keystone or foundational species within the habitat: none identified

Supporting literature

Cliffs feature many highly adapted native plant species, including herbaceous perennials such as 

the seaside daisy (Erigeron glaucus) and coastal buckwheat (Eriogonum latifolium) (North Coast 

Native Nursery 2014). Cliffs provide habitat for several nesting seabirds, including common 

murres (Uria aalge), pigeon guillemots (Cepphus columba), pelagic cormorants (Phalacrocorax 

pelagicus), and tufted puffins (Fratercula cirrhata) (Pyle 2001). Cliffs also provide haul-out space 

for some pinnipeds, including harbor seals (Phoca vitulina), California sea lions (Zalophus 

californianus), and northern elephant seals (Mirounga angustirostris) (Roletto 2001). The 

northern coastline of the study area typically features higher relief cliffs, while lower relief 

coastal bluffs and marine terraces are found more commonly south of Point Reyes (Griggs and 

Patsch 2004, Hapke and Reid 2007). The Farallon Islands also feature many rocky cliff lines. 

52
IV. Management potential

Value of habitat to people: Moderate-High

• Confidence of workshop participants: Moderate 

• Description of value: Cliffs are valued for their aesthetic qualities and recreational 

opportunities (i.e., scenic vistas along hiking trails).

Likelihood of managing or alleviating climate change impacts on habitat: Low-Moderate

• Confidence of workshop participants: Moderate 

• Description of potential management options: Management efforts will likely focus on 

managing urban development and runoff to minimize exposure and contribution to 

coastal cliff erosion.

V. Other adaptive capacities: none identified 

Exposure 

I. Future climate exposure7

Future climate and climate-driven factors identified (score8, confidence9): increased coastal 

erosion and runoff (4, high), increased storminess (4, high), sea level rise (2, moderate), 

increased flooding (2, low), changes in precipitation (2, moderate), changes in air temperature (1, 

moderate), changes in salinity (1, high) 

Degree of exposure to future climate and climate-driven factors: Low-Moderate 

• Confidence of workshop participants: Moderate 

Supporting literature

Increased coastal erosion and runoff

Over a 70-year period, Central California experienced cliff retreat along 208 km of coastline, 

with average retreat rates measuring -0.3m/yr and average overall retreat distances measuring 

17.3 m, though there was high variability within the study region (Hapke and Reid 2007). For 

example, the highest rates of erosion in Central California occurred along promontories or points 

such as Point San Luis, Point Sal, and Point Conception, which typically experience higher wave 

energy (Hapke and Reid 2007). Hazard erosion areas have been identified and mapped10, and 

erosion is likely to increase in the study region in the future due to a combination of increasing 

storm frequency and intensity, sea level rise, and changing wave activity (Phil William and 

Associates 2009, Ackerly 2012). For example, if sea levels increase 1.4 m, total alongshore and 

acrossshore cliff erosion in the study area could reach 15.4 square miles (Largier et al. 2010). 

Further, by 2100, cliff erosion could extend an average of 61 m inland, with maximum inland 

erosion distances reaching 206 m (Largier et al. 2010). 

7 Supporting literature for future exposure to climate factors is provided in the introduction. 8 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

9 Confidence level indicated by workshop participants.

10 http://www.pacinst.org/reports/sea_level_rise/hazlist.html

53
Precipitation

In combination with increased development of coastal areas (CDWB and SCC 2002), increased 

extreme precipitation events may contribute to larger runoff volumes, which can increase coastal 

cliff erosion and/or contribute to ground saturation, potentially leading to cliff failure (Griggs 

and Patsch 2004). 

Literature Cited 

Ackerly, D. 2012. Future Climate Scenarios for California: Freezing Isoclines, Novel Climates, and Climatic 

Resilience of California's Protected Areas: California Energy Commission.

Auad, G., A. Miller, and E. Di Lorenzo. 2006. Long-term forecast of oceanic conditions in California and their

biological implication. Journal of Geophysical Research 111, C09008, doi:10.1029/2005JC003219.

Bakun, A. 1990. Global climate change and intensification of coastal ocean upwelling. Science 247:198-201.

Barron, S., A. Delaney, P. Perrin, J. Martin, F. O'Neill, A. De Jongh, L. O'Neill, S. Barron and J. Roche. 2011. 

National survey and assessment of the conservation status of Irish sea cliffs: National Parks and Wildlife 

Service.

California Department of Boating and Waterways (CDBW) and State Coastal Conservancy (SCC) 2002. California 

Beach Restoration Study. Sacramento, CA.

Center for Ocean Solutions. 2014. Coastal Erosion. Accessed June 2014. 

http://centerforoceand.org/climate/impacts/cumulative-impacts/coastal-erosion/. 

Dugan, J.E., D.M. Hubbard, I. F. Rodil, D. L. Revell and S. Schroeter. 2008. Ecological effects of coastal armoring

on sandy beaches. Marine Ecology 29: 160-170.

Griggs, G. and N. Russell. 2012. City of Santa Barbara Sea-Level Rise Vulnerability Study: California Energy 

Commission. 

Griggs, G.B. and K.B. Patsch. 2004. California’s Coastal Cliffs and Bluffs. In: Formation, Evolution, and Stability 

of Coastal Cliffs – Status and Trends. U.S. Geological Survey Professional paper 1693. Pp. 53-64.

Griggs, G. B., K. Patsch and L. E. Savoy. 2005. Living with the changing California coast: Univ of California Press.

Hanak, E. and G. Moreno. 2008. California coastal management with a changing climate. Public Policy Institute of 

California. San Francisco, CA.

Hapke, C. J. and D. Reid. 2007. National Assessment of Shoreline Change Part 4: Historical Coastal Cliff Retreat

along the California Coast. U. S. Geological Survey.

Heberger, M., H. Cooley, P. Herrera, P. H. Gleick and E. Moore. 2009. The Impacts of Sea Level Rise on the 

California Coast. California Climate Change Center. 

Jaiswal, A. and S. Newkirk. 2005. A Practical Plan for Pollution Prevention: Urban Runoff Solutions for the 

Monterey Region. Natural Resources Defense Council.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Mendelssohn, R. and F.B. Schwing. 2002. Common and uncommon trends in SST and wind stress in California and

Peru-Chile current systems. Progress in Oceanography 53. p.141-162.

North Coast Native Nursery. 2014. A Guide to California Native Plants." Accessed June 2014. 

http://www.northcoastnativenursery.com/Resources/Plant%20Guide/guidetocaliforni.html. 

Phil William & Associates, Ltd (PWA). 2009. California Coastal Erosion Response to Sea Level Rise – Analysis

and Mapping. Report to the Pacific Institute funded by the California Ocean Protection. 

Pyle, P. 2001. Seabirds. In Beyond the Golden Gate - Oceanography, Geology, Biology, and Environmental Issues 

in the Gulf of the Farallones, edited by H.A. Karl, J.L. Chin, E. Ueber, P. H. Stauffer and J.W. Hendley II, 

150-161. Menlo Park, CA.

Roletto, J. 2001. Marine Mammals. In Beyond the Golden Gate - Oceanography, Geology, Biology, and 

Environmental Issues in the Gulf of the Farallones, edited by H.A. Karl, J.L. Chin, E. Ueber, P. H. Stauffer 

and J.W. Hendley II, 162-176. Menlo Park, CA.

Ryan, H. F., S. L. Ross and R. W. Graymer. 2001. Earthquakes, Faults, and Tectonics." In Beyond the Golden Gate 

- Oceanography, Geology, Biology, and Environmental Issues in the Gulf of the Farallones, edited by H.A. 

Karl, J.L. Chin, E. Ueber, P. H. Stauffer and J.W. Hendley II, 37-46. Menlo Park, CA.

Sallenger, A.H., W. Krabill, J. Brock, R. Swift, S. Manzinar, and H.F. Stockdon. 2002. Sea-Cliff erosion as a

54
function of beach changes and extreme wave run-up during the 1997-98 El Niño. Marine Geology 

187:279-297.

Schwing, F. B. and R. Mendelssohn. 1997. Increased coastal upwelling in the California Current System. Journal of

Geophysical Research 102:3421-3438.

Sanctuary Integrated Monitoring Network (SIMoN). 2014. Monitoring Project: Oblique Aerial Photography - 

Coastal Erosion from El Nino Winter Storms. Accessed June 2014. 

http://sanctuarysimon.org/obsregistry/reg_simon/reg_PDF.php?projectID=100189. 

Slagel, M. J. and G.B. Griggs. 2008. Cumulative Losses of Sand to the California Coast by Dam Impoundment.

Journal of Coastal Research 24(3)571-584.

Snyder, M.A., L.C. Sloan, N.S. Diffenbaugh, and J.L. Bell. 2003. Future climate change and upwelling in the

California Current. Geophysical Research Letters 30:1-4.

Storlazzi, C. and G. Griggs. 2000. Influence of El Niño-Southern Oscillation (ENSO) events on the evolution of

Central California's shoreline. GSA Bulletin 112 (2), 236-249.

Willis, C.M. and G.B. Griggs. 2003. Reductions in Fluvial Sediment Discharge by Coastal Dams in California and

implications for Beach Sustainability. Journal of Geology 111:167-182

Wingfield, D.K. and C.D. Storlazzi. 2007. Variability in oceanographic and meteorologic forcing along Central

California and its implications on nearshore processes. Journal of Marine Systems v. 68, p. 457-472.

55
Estuaries: ephemeral and year-round1

Executive Summary The estuarine habitat includes small and

sandbar-built estuaries within the study 

region, such as Pescadero Marsh, Estero 

Americano and Estero de San Antonio, and 

moderately sized bays such as Tomales Bay, 

Drakes Estero, and Bolinas Lagoon. Key 

climate sensitivities identified for this habitat by workshop participants include sea level rise, sea 

surface temperature, precipitation, and wave action. Key non-climate sensitivities include land 

use change, overwater/underwater structures, roads and armoring and invasive species. This 

habitat has a transcontinental geographic extent, is patchily distributed throughout the study 

region, and is considered to be in a somewhat degraded condition, due to land use pressures, 

water diversion, pollutants and sedimentation. A diverse range of coastal formations and the 

interplay of terrestrial, freshwater and marine influences result in a highly diverse and productive 

community that supports multiple commercial and recreational fisheries and provides protection 

from coastal erosion that may impact populated coastal communities. Resistance to stressors is 

low, though recovery from stressors may be possible with appropriate conservation efforts and 

ongoing management activities. 

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven factors identified (score2, confidence3): sea level rise (5, high), sea 

surface temperature (4, high), wave action (4, high), precipitation (4, high), air temperature (3, 

high), dissolved oxygen levels (3, high), pH (3, high), coastal erosion (3, moderate), dynamic 

ocean conditions (currents/mixing/stratification) (2, high), salinity (2, high), turbidity (2, 

moderate)

Climate and climate-driven factors that may benefit the habitat: none provided 

Overall habitat sensitivity to climate and climate-driven factors: Moderate-High

• Confidence of workshop participants: High 

Supporting literature

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Estuaries Score Confidence

Sensitivity 4 Moderate-High 3 High

Exposure 5 High 3 High

Adaptive Capacity 4 Moderate-High 3 High

Vulnerability 4 Moderate-High 3 High

56
Sea Level Rise

Sea level rise will exacerbate shoreline erosion and cause saltwater intrusion, possibly increasing 

salinity by as much as 9 practical salinity units in the region’s estuaries (Knowles and Cayan 

2002). Unless there is a comparable increase in elevation of the land surface due to sediment 

delivery and availability, estuarine habitat will not be able to adjust to rising sea levels, and 

flooding will also be expected (Largier et al. 2010, Ackerly et al. 2012). Tidal flux may be 

altered, including the timing and extent of the rise and fall of the tide (Largier et al. 2010). 

Estuarine habitats more dependent on organic deposition (microtidal) rather than inorganic 

sediment deposition (mesotidal) will likely be more impacted by changes in sea level (Stevenson 

et al. 1986, Stevenson and Kearney 2009). 

Sea Surface Temperature

Increasing water and air temperatures are magnified in estuaries relative to the outer coast and 

are important drivers of community and ecosystem responses in estuaries. Increasing water 

temperatures can result in the range expansion of both native and non-native species into new 

areas (Williams and Grosholz 2008), and can have significant demographic effects as well. 

Water temperatures may also impact the incidence of disease in estuarine species, estuarine 

circulation, the amount of oxygen that can dissolve in the water (which is critical for the survival 

of estuarine species), and key physiological processes in estuarine species that are temperaturedependent (NOAA Ocean Service Education 2008).

Precipitation 

Changing patterns in precipitation may have consequences for the impact of invasive species, 

sediment deposition, erosion, flooding, river flow (which may impact the timing of mouth 

opening and closure of some estuaries), water chemistry and run-off. The seasonality of 

estuarine hydrology, including rainfall and water flow from rivers into estuaries will influence 

the transport and deposition of sediments with long-term consequences for estuarine physical 

structure. Increase in storm and precipitation intensity will likely lead to more frequent and 

severe flooding of estuaries and will greatly impact river flow, which will likely alter the timing 

of estuarine mouth opening and closing (Largier et al. 2010). 

Wave Action 

Increased storm activity, including wave action, will have important implications for flooding of 

estuarine habitat, the state of the estuarine mouth, and the timing of estuarine mouth opening and 

closing (Largier et al. 2010). The mouths of estuaries will tend to close with stronger wave 

energy, and may close earlier or later than usual depending on the interaction with river flow. 

II. Sensitivities to disturbance regimes

Disturbance regimes considered: storms, flooding, and disease 

Overall habitat sensitivity to disturbance regimes: Moderate-High

• Confidence of workshop participants: High 

Supporting literature

Flooding 

Increased flooding is expected with sea level rise and more intense precipitation events (see 

above). The estuarine habitat is highly sensitive to flooding because of the critical habitat that 

may be inundated, including mud flats for shorebird foraging (Stralberg et al. 2008) and pinniped 

57
resting and breeding (Sarah Allen, pers. comm., 2014). Landward migration of intertidal habitat 

may be restricted due to armoring, roads, and other structures. 

Storms

Models suggest that the tracks of storms in the northeast Pacific Ocean will experience an 

increase in occurrence of extreme conditions, though the number of extreme events may not 

change (Largier et al. 2010). Increased storm intensity will impact both wave energy and the 

timing and intensity of precipitation events, with major consequences for estuarine habitat (see 

Wave Action and Precipitation sections above). 

III. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): land use change (5, high), coastal 

roads/armoring (4, high), invasive species (4, high), overwater/underwater structures (4, high) 

Overall habitat sensitivity to non-climate stressors: High

• Confidence of workshop participants: High 

Overall habitat exposure to non-climate stressors: Moderate-High

• Confidence of workshop participants: High 

Supporting literature

Land Use Change 

Land use pressures have impacted water quality in some of the region’s estuaries, resulting in 

changes to sediment and freshwater regimes (ONMS 2010). Increased sedimentation can result 

from land use, causing the burying of oyster and eelgrass habitat and increasing the duration of 

mouth closure. Livestock grazing and agricultural runoff (primarily animal waste from dairies 

and rangelands) can result in high coliform and bacterial contamination, increased sedimentation 

and contamination with toxic materials (e.g., high mercury levels) in estuary waters (ONMS 

2010). Freshwater diversions for agriculture and other human uses cause hypersaline conditions, 

slow circulation, and may result in the persistent closing of estuarine mouths due to reduced tidal 

prism (ONMS 2010). 

Overwater/Underwater Structures

Fishing activities can impact eelgrass and oyster beds, and mariculture of several bivalve species 

in Tomales Bay has potential negative impacts, including the presence of mariculture-farming 

equipment that can reduce eelgrass cover, alter sediment deposition patterns, and provide large 

amounts of hard substrate that is not naturally present, thus altering species communities, and 

maintenance operations that trample sediments and damage eelgrass beds (Carr et al. 2008). 

Substantial loss of native oyster beds in Tomales Bay has resulted from increased moorings and 

anchored and abandoned vessels that impact the benthos. Vessel propellers, anchors, and 

moorings can damage the underground root and rhizome system of eelgrass and impact oyster 

beds (ONMS 2010). 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

58
Roads/Armoring 

An important factor that will influence estuarine response to sea level rise is the ability of 

estuaries to migrate inland. Where the upland border abuts roads, levees or other armored 

structures, an accelerated loss of habitat may be expected (Fletcher et al. 1997, Dugan et al. 

2008). Road construction and coastal armoring continues to be a problem in the study region, 

specifically Bolinas Lagoon and Tomales Bay, and in other areas of coastal development. 

Although localized, these activities can have a high impact as they can convert habitat type, 

increase erosion rates, and have the potential to result in large-scale debris (ONMS 2010). 

Invasive species and other problematic species 

Invasive species effectively out-compete native species and decrease native species diversity and 

abundance. These impacts are more largely felt near harbors, including San Francisco Bay, 

Pillar Point Harbor, and Bodega Harbor. It is estimated that about 143 species of invasives are 

present in the region, most of which exist in the estuarine zone (Byrnes et al. 2007), including 

European green crabs (Carcinus maenas) which prey on and compete with native crabs, Japanese 

mud snails (Batillaria attramentaria) whose dense aggregations impact mudflat communities 

(Dewar et al. 2008), and smooth cordgrass (Spartina alterniflora) and its hybridization with the 

native cordgrass (Spartina foliosa), resulting in loss of habitat for salmon and oysters, and 

economic losses for those who rely on these species (Brusati 2008, ONMS 2010). Invasive 

species threaten the abundance and/or diversity of native species, disrupt ecosystem balance and 

threaten local marine-based economies (SIMoN 2014). Climate change is likely to enhance the 

negative impacts of coastal invaders. Stachowicz et al. (2002) documented earlier and greater 

recruitment of invasive tunicates as well as increased growth under warmer sea surface 

temperatures, and predicted that increasing temperatures will ultimately lead to more successful 

invasive species. 

IV. Other sensitivities 

Other critical factors likely to influence habitat sensitivity to climate change: restoration 

potential, resilience, and public awareness

Degree to which these factors influence habitat sensitivity to climate change: High

• Confidence of workshop participants: High

Adaptive Capacity

I. Extent, integrity, and continuity

Geographic extent of the habitat: 5 (Transcontinental) 

• Confidence of workshop participants: High 

Structural and functional integrity of habitat: 2 (somewhat degraded) 

• Confidence of workshop participants: High 

Continuity of habitat: 2 (somewhat isolated and/or fragmented, i.e. patchy)

• Confidence of workshop participants: High 

59
Supporting literature

Estuaries occur worldwide along the coastal zone wherever rivers meet the ocean; they cover a 

global area of around 106 km2

 and encompass around 4% of the world’s continental shelf. 

Major estuaries found in the study region include Tomales Bay, Bolinas Lagoon, Estero 

Americano and Estero de San Antonio, Drakes and Limantour Esteros, and Abbotts Lagoon. 

Pescadero and Scott’s Creek marshes are also in the study region. The 2010 GFNMS Condition 

Report rates the region’s estuaries and lagoons as good/fair to fair/poor condition due to land use 

pressures, water diversion, pollutants and sedimentation. The state has listed Tomales Bay, 

Estero Americano and Estero de San Antonio as impaired bodies of water under the 303(d) 

listing (SWRCB 2006) due to a broad range of impacts, including high nutrient loading, 

increased siltation and bacteria. Biodiversity in the region’s estuaries is rated as fair/poor to 

declining, due to loss and alteration of eelgrass habitat, a key habitat for estuarine species, 

particularly in Bolinas Lagoon (T. Moore, pers. comm., as cited in ONMS 2010). 

II. Resistance and recovery

Habitat resistance to stressors/maladaptive human responses: Low

• Confidence of workshop participants: High 

Ability of habitat to recover from stressor/maladaptive human response impacts: Moderate-High

• Confidence of workshop participants: High 

Supporting literature

Conservation efforts may help achieve partial recovery of upper trophic levels, but have failed 

thus far to restore ecosystem structure and function (Lotze et al. 2006). In a comprehensive 

review of estuarine and coastal recovery, Borja et al. (2010) concluded that, though estuaries do 

respond well to restoration efforts, full recovery of an estuarine system may take a minimum of 

15-25 years, with biodiversity of the system lagging behind. Recommendations for climatesmart restoration solutions include raising infrastructure off the marsh to allow for flooding and 

movement, allowing estuaries to open and close as conditions change, embrace resiliency and 

restore living shorelines (Ross Clark, pers. comm., Headwaters to Ocean Conference, 2014). 

III. Habitat diversity

Physical and topographical diversity of the habitat: High

• Confidence of workshop participants: High 

Diversity of component species within the habitat: High

• Confidence of workshop participants: High 

Diversity of functional groups within the habitat: Moderate-High

• Confidence of workshop participants: Moderate 

Keystone or foundational species within the habitat: none identified

Supporting literature

A diverse range of coastal formations is included in the estuary designation, including bays, 

inlets, lagoons, wetlands, marshes and esteros. Estuaries may be bar-built and ephemeral, yearround open river mouths, or perennially tidal (SWRCB 2006). Because of this diversity in 

terrestrial, freshwater and marine influences, estuaries support highly diverse communities, 

60
including eelgrass nursery habitat for commercially and recreationally important fish species, 

shorebirds, waterfowl, crabs, shrimp and many other invertebrates (Largier et al. 2010, SIMoN 

2014). Eelgrass (Zostera marina) is a keystone species in the estuarine habitat; 10 to 100 times 

more animals can be found in eelgrass beds compared to adjacent sandy and muddy habitats 

(Olyarnik 2007). This species has shown signs of decline in some estuaries, including nearly 

extinct levels in Bolinas Lagoon (Leet et al. 2001, GFNMS 2008). A key factor for eelgrass 

health is water clarity and quality, which is greatly impacted by human activities and land use. 

An additional component of estuarine habitat is sand bars that are exposed at low tides and 

provide important habitat to shorebirds, waterbirds and pinnipeds (Sarah Allen, pers. comm., 

2015). 

IV. Management potential

Value of habitat to people: Moderate-High

• Confidence of workshop participants: High 

• Description of value: no information provided 

Likelihood of managing or alleviating climate change impacts on habitat: Moderate

• Confidence of workshop participants: Low

• Description of likelihood of managing or alleviating climate change impacts: The 

likelihood of managing or alleviating climate change impacts will depend on the extent of 

existing habitat and the value of the habitat. 

Supporting literature

Estuaries are valued, in part, due to the fisheries that are supported by nursery grounds, including 

commercial harvest of oysters in aquaculture facilities, sport take of clams, and some fishing for 

herring, rock crab, perch and halibut (ONMS 2010). Estuaries are also recognized as providing a 

buffer from coastal erosion and inundation for populated communities along the coast. Past and 

ongoing management activities that have reduced impacts to the region’s estuaries include 

implementation of best management practices to reduce runoff, the closure and restoration of a 

mercury mine, the development of a vessel management plan to address illegal moorings in 

eelgrass, and the removal of abandoned vessels from Tomales Bay (ONMS 2010). Information 

on current management activities can be found for Bolinas Lagoon 

(http://farallones.noaa.gov/eco/bolinas/bolinas.html) and Tomales Bay 

(http://farallones.noaa.gov/eco/tomales/tomales.html).

V. Other adaptive capacity factors 

Other critical factors that may affect habitat’s adaptive capacity: room to migrate

Degree to which factors affect habitat’s adaptive capacity: High

• Confidence of workshop participants: High 

Additional participant comments 

Beach and dune habitats that are bound by natural or human built structures will have a low 

adaptive capacity to climate change impacts.

61
Exposure 

I. Future climate exposure6

Future climate and climate-driven changes identified (score7, confidence8): changes in 

precipitation (5, high), changes in sea surface temperature (5, high), increased coastal erosion 

and runoff (5, high), increased storminess (5, high), increased flooding (5, high), changes in air 

temperature (4, high), sea level rise (4, moderate), decreased pH (3, moderate), decreased 

dissolved oxygen (3, moderate) 

Exposure of habitat to future climate and climate-driven changes: High

• Confidence of workshop participants: High 

Literature Cited

Ackerly, D. D., R. A. Ryals, W. K. Cornwell, S. R. Loarie, S. Veloz, K. D.Higgason, W. L. Silver, and T. E. 

Dawson. 2012. Potential Impacts of Climate Change on Biodiversity and Ecosystem Services in the San 

Francisco Bay Area. California Energy Commission. Publication number: CEC-500-2012- 037.

Borja, A., D.M. Dauer, M. Elliott, C.A. Simenstad. 2010. Medium and long-term Recovery of Estuarine and Coastal 

Ecosystems: Patterns, Rates and Restoration Effectiveness. Estuaries and Coasts 33(6): 1249-60.

Brusati, E. 2008. Smooth cordgrass (Spartina alterniflora) newsletter. Plant Conservation Alliance's Alient Plant 

Working Group. California Invasive Plant Council. 

Byrnes, J.E., P.L. Reynolds, J.J. Stachowicz. 2007. Invasions and extinctions reshape coastal marine food webs. 

PLoS ONE 2(3): e295. 

Carr, M. and SAT support staff. 2008. Potential impacts of mariculture activities in the MLPA North Central Coast 

Study Region. Prepared for the MLPA Master Plan Science Advisory Team. Revised January 4, 2008.

Dewar, J. C. Bowles, H. Weiskel, E. Grosholz. 2008. The impacts of an invasive gastropod Batillaria attramentaria 

on benthic habitats in a Central California bay. American Geophysical Union, Fall meeting, abstract 

#OS41E-1273.

Dugan, J.E., D.M. Hubbard, I. F. Rodil, D. L. Revell and S. Schroeter. 2008. Ecological effects of coastal armoring 

on sandy beaches. Marine Ecology 29: 160-170.

Fletcher, C. H., R. A. Mullane, B. M. Richmond. 1997. Beach loss along armored shorelines on Oahu, Hawaiian 

Islands. Journal of Coastal Research 13: 209-215 

Gulf of the Farallones National Marine Sanctuary (GFNMS). 2008. Bolinas Lagoon ecosystem restoration project: 

recommendations for restoration and management. Unpublished report, prepared by the Working Group 

of the Sanctuary Advisory Council for the Gulf of the Farallones National Marine Sanctuary, San 

Francisco,CA, 101pp. 

Knowles, N. and D.R. Cayan. 2002. Potential effects of global warming on the Sacramento/San Joaquin watershed 

and the San Francisco estuary. Geophysical Research Letters 29:1891. 

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp.

Leet, W., C. Dewees, R. Klingbeil, E. Larson, eds. 2001. California's Living Marine Resources: A Status Report.

California Department of Fish and Game. ANR Publication #SG01-11. 593pp. 

Lotze, H.K, S. Lenihan, J. Bourque, H. Bradbury, G. Cooke, C. Kay, M. Kidwell, X. Kirby, H. Peterson, B. C. 

Jackson. 2006. Depletion, Degradation, and Recovery Potential of Estuaries and Coastal Seas. 

Science 312: 1806-1809.

National Oceanic and Atmospheric Administration (NOAA) Ocean Service Education. 2008. Estuaries. 

http://oceanservice.noaa.gov/education/kits/estuaries/estuaries10_monitoring.html. 

6 Supporting literature for future exposure to climate factors is provided in the introduction. 7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

62
Office of National Marine Sanctuaries (ONMS). 2010. Gulf of the Farallones National Marine Sanctuary Condition

Report. U.S. Department of Commerce, National Oceanic and Atmospheric Administration, Office 

of National Marine Sanctuaries, Silver Spring, MD. 97 pp.

Olyarnik, S. 2007. Seagrasses in Tomales Bay: the unsung heroes of the habitat. Upwelling: the newsletter of the 

Farallones Mary Sanctuary Association. February.

Sanctuary Integrated Monitoring Network (SIMoN): Gulf of the Farallones National Marine Sanctuary. 2014. 

Retrieved May 14, 2014 from http://sanctuarysimon.org/farallones/sections/estuaries/overview.php. 

Stachowicz, J.J., J.R. Terwin, R.B. Whitlatch and R.W. Osman. 2002. Linking climate change and biological 

invasions: ocean warming facilitates non-indigenous species invasion. Proceedings of the National 

Academy of Sciences 99: 15497–15500. 

State Water Resources Control Board (SWRCB). 2006. Clean Water Act Section 303(d) List of Water Quality 

Limited Segments Requiring TMDLs.

Stevenson, J. C., L. G. Ward, and M. S. Kearney. 1986. Vertical accretion in marshes with varying rates of sea level 

rise. Pages 241–259 in D. Wolf (ed.), Estuarine Variability. New York: Academic Press. 

Stevenson, J.C. and M.S. Kearney. 2009. Impacts of global climate change and sea level rise on tidal wetlands. In: 

Silliman, B.R., Grosholz, E.D. and Bertness, M.D. (eds). Human Impacts on Salt Marshes. Berkeley, CA: 

University of California Press. 

Stralberg, D., Applegate, D. L., Phillips, S. J., Herzog, M. P., Nur, N. and N. Warnock. 2008. Optimizing wetland 

restoration and management for avian communities using a mixed integer programming approach. 

Biological Conservation 142: 94-109. 

Williams, S.L. and E. D. Grosholz. 2008. The invasive species challenge in estuarine and coastal environments: 

Marrying management and science. Estuaries and Coasts 31: 3-20

63
Kelp Forest1

Executive Summary The rocky nearshore environment in the 

study region is characterized by dense 

forests of kelp that occur at varying 

depths (approximately 4 to 25 meters). 

The bull kelp, Nereocystis luetkeana, is 

the dominant canopy-forming kelp and 

tolerates high wave action. Kelp forest habitats can also feature sub-canopies of feather boa kelp, 

Egregia menziesii, and understories of other kelp species (e.g. Pterygophora californica, and 

other Laminariales). Key climate sensitivities identified for this habitat by workshop participants 

include dissolved oxygen, salinity, wave action, sea surface temperature, and dynamic ocean 

conditions. Key non-climate sensitivities include pollution and oil spills. Kelp forest habitat has 

a broad geographic extent, is patchy in its distribution, and considered to have moderate to high 

structural and functional integrity. This habitat has a high degree of topographical and biological 

diversity, which supports recreational activities, multiple fisheries, and, to a lesser extent, kelp 

harvesting. As the dominant canopy-forming kelp in the study region, bull kelp is able to rapidly 

colonize new areas, though only under certain environmental conditions that favor it over other 

competitors (including giant kelp). Community dynamics between bull kelp, its grazers, and their 

predators is important in structuring the distribution of the kelp forest habitat. Potential 

management measures include alterations to the allowable urchin harvest to limit their grazing

impact. 

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): salinity (5, high), dissolved 

oxygen levels (5, high), wave action (5, high), sea surface temperature (4, high), pH (3, 

moderate), dynamic ocean conditions (currents/mixing/stratification) (3, moderate), sea level rise 

(2, low), precipitation (2, moderate), coastal erosion (1.5, moderate), air temperature (1, high) 

Climate and climate-driven changes that may benefit the habitat: pH, dynamic ocean conditions, 

and sea surface temperature

• Description of benefits: Potential benefits to this habitat include the expected decrease in 

pH and associated increase in dissolved carbon dioxide, enhanced larval and nutrient 

transport that may result from altered currents and mixing, and decreased sea surface 

temperature due to enhanced upwelling that would benefit bull kelp and recruitment 

success for nearshore rockfishes. 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Kelp Forest Score Confidence 

Sensitivity 3 Moderate 2 Moderate

Exposure 2 Low-Moderate 3 High

Adaptive Capacity 3 Moderate 3 High

Vulnerability 2 Low-Moderate 3 High

64
Overall habitat sensitivity to climate and climate-driven factors: Moderate

• Confidence of workshop participants: High

Additional participant comments

Nereocystis luetkeana, the bull kelp, is the central component of kelp forests in the North-central 

California region; sensitivity to change in the kelp forest habitat is directly linked to the 

sensitivity of this species. 

Supporting literature

Literature review was conducted for those factors scoring 3 or higher, although the other 

sensitivities identified should also be considered. 

Salinity 

The role of salinity in impacting and structuring kelp forest ecosystems has received little 

attention (Dayton 1985), though adverse effects of diluted salinity have been documented on two 

species of laminarian algae (Norton and South 1969) and on the germination of the Arctic kelp 

Alaria esculenta (Fredersdorf et al. 2009). Hurd (1919) demonstrated that bull kelp sporophytes 

develop blisters and wilt when subjected to rapid reductions in environmental salinity. 

Alternatively, healthy kelp forests have been observed growing in freshwater lenses in the 

Pacific Northwest (Dayton 1985). 

Dissolved Oxygen

During strong spring upwelling events, kelp forest habitat may be exposed to low-oxygen waters, 

though hypoxic conditions are generally limited to greater depths (Largier et al. 2010). 

Grantham et al. (2004) documented mass die-offs of fish and invertebrates inshore of the 70m 

isobath during a severe hypoxic event in coastal Oregon in 2002, suggesting that extreme 

shoaling of the oxygen minimum zone to kelp forest depths would be catastrophic to the 

ecological community. However, kelp forest habitat may more likely act as a refuge during 

deeper hypoxic events due to the shallow depths of the habitat (abnormal fish aggregations 

observed <25m in Oregon, Grantham et al. 2004) and the high production of oxygen by the algal 

community (Frieder et al. 2012). 

Wave action 

Increasing significant wave heights will have a much greater impact on the southern-most kelp 

species in the region, the giant kelp, than it will on the dominant species in the region, the bull 

kelp, due to bull kelp’s great adaptability to extreme physical forces. However, increased wave 

action may impact sediment redistribution and alter sand scour dynamics within reef 

communities, and may also force the movement of nearshore kelp forests into deeper water 

(Graham 1997) and create greater intra-annual variability in kelp productivity and abundance 

(Graham et al. 1997). 

Sea Surface Temperature

In California, nearshore waters have shown an increasing temperature trend since 1955 

(Mendelssohn et al. 2003), though water temperature over the continental shelf has cooled over 

the last 30 years (by as much as 1°C in some locations) due to stronger seasonal upwelling 

(Mendelssohn and Schwing 2002; Garcia-Reyes and Largier 2010). Continued warming of 

nearshore and enclosed bay waters is expected, while water temperatures are expected to cool 

over the continental shelf (Largier et al. 2010). Schiel et al. (2004) documented the effect of a 

65
3.5°C increase in temperature in San Luis Obispo county caused by the thermal outfall of a 

nuclear power plant on kelp forest habitat dominated by a canopy of bull kelp and an understory 

mostly comprised of Pterygophora californica and Laminaria setchellii. After initiation of the 

thermal outfall, bull kelp was replaced by the giant kelp Macrocystis pyrifera and subcanopy 

kelps decreased while foliose red algae increased in abundance. Within the study region, this 

highlights the potential for bull kelp to be negatively affected by increased water temperatures 

and replaced by better-adapted competitors, although potential competitors (e.g., giant kelp) may 

also be sensitive to increased water temperatures, among other factors (Edwards and HernándezCarmona 2005, Edwards and Estes 2006). A sustained sea temperature increase of 3°C is 

projected to greatly reduce kelp forests, which were temporarily damaged by the 1998 El Niño. 

Culture studies with bull kelp show that the thermal conditions allowing reproduction of the 

microscopic stages range from 3°C to 17°C (Vadas 1972). 

Dynamic ocean conditions (currents/mixing/stratification) 

At a local scale, kelp forest habitat is less sensitive to this factor than at a large, regional scale. 

Nutrient delivery and offshore transport of larvae and spores may be enhanced by intensified

upwelling, which would be beneficial to bull kelp, benthic macroalgae, and phytoplankton (but 

may also disturb food particle concentration, which is critical to larval survival). However, in 

nearshore regions sheltered from the direct effects of upwelling, these factors may be reduced 

(Bakun 1990, Largier et al. 2010). In Southern California, where stratification is observed during 

summer, nitrate availability limits kelp forest productivity (Zimmerman and Kremer 1984, 1986; 

Zimmerman and Robertson 1985), which could occur in sheltered northern waters, bringing 

significant change to these habitats. 

II. Sensitivities to disturbance regimes

Disturbance regimes identified: disease and storms

Overall habitat sensitivity to disturbance regimes: Moderate-High

• Confidence of workshop participants: Moderate 

Additional participant comments 

Invertebrate diseases may impact trophic interactions. Storms increase turbulence that 

exacerbates kelp dislodgement and sedimentation that may reduce the recovery of stormdamaged forests. 

Supporting literature

Disease

Kelp forests are indirectly affected by disease; impacts of a sea otter or sea star disease may 

result in increased grazing by urchins (Conrad et al. 2005), and disease presence in local urchin 

populations may limit the grazing impact on kelp (Behrens and Lafferty 2004). The only known 

parasite that commonly infects bull kelp is Streblonema sp., a brown alga that causes distortions 

of the stipe including abnormal outgrowths and extended rugose areas. These deformations can 

weaken the stipe and may result in breakage during exposure to strong surge or storm conditions 

(CEQA 2001).

Storms

Increasingly intense run-off during extreme storm events may cause increased sedimentation that 

may negatively impact understory growth due to sand scour, and increased freshwater input to 

66
the nearshore subtidal that may lead to higher resuspension of sediment resulting in increased 

turbidity and light attenuation. Increased turbidity will compromise kelp growth, and culture 

experiments indicate that total light quantity is the single most important factor in the 

development of the microscopic stages of bull kelp (Vadas 1972). 

III. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): pollution (5, high), oil spills (3, low), 

harvest (grazers) (2, moderate), harvest (algae/kelp) (1, high), harvest (mid-trophic level species)

(1, high) 

Overall habitat sensitivity to non-climate stressors: Moderate

• Confidence of workshop participants: Moderate 

Overall habitat exposure to non-climate stressors: Low-Moderate

• Confidence of workshop participants: Moderate 

Additional participant comments 

Workshop participants expressed that they were not confident in their knowledge about the 

combined effects/interactions of non-climate stressors on kelp forest habitats because of a lack of 

data.

Supporting literature

Literature review was conducted for those factors scoring 3 or higher, although the other 

sensitivities identified should also be considered. 

Pollution and oil spills

Pollutants, including agricultural and livestock waste, wastewater, sewage outfalls, historic 

mining and industrial wastes, can be carried into the study region via the freshwater outflow 

from San Francisco Bay (Largier et al. 2010), significantly reducing water clarity and negatively 

impacting the survival and growth of bull kelp (Springer et al. 2006). High sedimentation from 

coastal run-off may bury new plant shoots. Studies on microscopic stages of kelp suggest that 

kelp is sensitive to sewage, industrial waste discharges, and other causes of poor water and 

sediment quality (NOAA 2013). Falkenburg et al. (2013) demonstrated that for kelp forest turf 

algae, whose expansion can restrict recruitment for kelp canopy species, the combined effect of 

increased CO2 and increased nutrients is greater than the sum of the individual impacts, and that 

by limiting the nutrient input to kelp forest habitat, managers can substantially mitigate the 

potential for enhanced competitive interaction between turfing algae and kelp canopy species.

IV. Other sensitivities identified by workshop participants

Other critical factors likely to influence the sensitivity of the habitat: human population growth 

along the coast and the interactions between climate and non-climate factors

• Degree to which these factors affect the habitat’s sensitivity: Moderate-High

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

67
• Confidence of workshop participants in the degree to which these factors influence 

habitat sensitivity: Low-Moderate

Adaptive Capacity

I. Extent, integrity, and continuity

Geographic extent of the habitat: 5 (Transcontinental) 

• Confidence of workshop participants: High 

Structural and functional integrity of habitat: 4 (Minor to moderate alterations)

• Confidence of workshop participants: High 

Continuity of habitat: 2 (Somewhat isolated and/or fragmented, i.e. patchy) 

• Confidence of workshop participants: High 

Supporting literature

Forests of bull kelp exist primarily along the Pacific coast of North America and are the 

dominant kelp forest north of Santa Cruz, California. Extensive beds of bull kelp can be found 

from Point Conception, CA to Unmak Island, AK (Abbott and Hollenberg 1976). When it grows 

alongside giant kelp, bull kelp will form a forest understory. 

II. Resistance and recovery

Habitat resistance to the impacts of stressors/maladaptive human responses: Moderate

• Confidence of workshop participants: Moderate 

Ability of habitat to recover from stressor/maladaptive human response impacts: Moderate-High

• Confidence of workshop participants: Moderate 

Supporting literature

Bull kelp can rapidly colonize a newly cleared or scoured location, though its longevity as the 

dominant canopy-forming kelp among other competitors is dependent upon favorable 

environmental conditions (Kalvass and Larson 2001). 

III. Habitat diversity

Physical and topographical diversity of the habitat: High

• Confidence of workshop participants: High 

Diversity of component species within the habitat: High

• Confidence of workshop participants: High 

Diversity of functional groups within the habitat: High

• Confidence of workshop participants: High 

Keystone or foundational species within the habitat: Kelp, urchin, and sea otters 

68
Supporting literature

Kelp forest habitats harbor high diversity, including diverse fish, algae, and invertebrate taxa

(Carr et al. 2013). However, the functional redundancy of habitat-forming kelp species is very 

low, and kelp forests in the North-central California region are reliant on the abundance of the 

bull kelp species. This species alone supports a very diverse community of invertebrates, fishes 

and understory algae that rely on its presence. Sea urchins (Strongylocentrotus spp.) and their 

predators (large fishes, birds, crabs, sunflower stars, commercial/recreational fishing, and sea 

otters only in the very southern stretch of the study area) play critical roles in the stable 

equilibrium ecosystem. Sea urchins graze kelp and may reach population densities large enough 

to destroy kelp forests at a rate of 30 feet per month (NOAA 2013). Urchins move in "herds," 

and enough urchins may remain in the "barrens" of a former kelp forest to negate any attempt at 

regrowth. Sea urchin predators, playing a critical role in containing the urchin populations, prey 

on urchins and thus control the numbers of kelp grazers (NOAA 2013). 

IV. Management potential

Value of habitat to people: High

• Confidence of workshop participants: High 

• Description of value: Kelp forests are valued for their aesthetics, cultural value, and for 

the recreational (scuba, kayaking) and fishing opportunities they provide (rockfish). 

Likelihood of managing or alleviating climate change impacts on habitat: Low-Moderate

• Confidence of workshop participants: Moderate 

• Description of potential management options: Managers may be able to modify the 

allowable urchin harvest to better manage grazers and predators in the system. 

V. Other adaptive capacity factors identified by workshop participants

Critical factors not addressed that may affect habitat’s adaptive capacity: nutrients

• Degree to which these factors affect the habitat’s adaptive capacity: Moderate

• Confidence of workshop participants: Low

Exposure6

I. Future climate exposure

Future climate and climate-driven factors identified (score7, confidence8): increased storminess 

(5, high), decreased pH (5, high), sea level rise (5, high), altered currents and mixing (4, 

moderate), El Niño (2, low), decreased dissolved oxygen levels (2, low), changes in salinity (1, 

high), changes in precipitation (1, high), increased flooding (1, high), increased coastal erosion

and runoff (1, high), changes in sea surface temperature (1, moderate)

Degree of exposure to future climate and climate-driven factors: Low-Moderate 

• Confidence of workshop participants: High 

6 Supporting literature for future exposure to climate factors is provided in the introduction.

7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

69
Supporting literature

Sea level rise will affect kelp forest communities through decreased light availability to sessile 

macroalgae and a forced shoreward migration, which will depend on available rocky substrate at 

shallower depths (Graham et al. 2003, 2008). Sea level rise may also change the shape of the 

coastline and substrate composition (i.e., rocky vs. sandy shores; Graham 2007), and thus impact 

the availability and living conditions of macroalgae and their associated species. The associated 

elevation of dissolved CO2 with decreasing pH may benefit bull kelp and other noncalcareous 

macroalgae by increasing growth and production (Hepburn et al. 2011), but this could also lead 

to competitive interactions between canopy kelp species and turfing algae (Falkenberg et al. 

2013). 

Literature Cited

Abbott, I.A. and G.J. Hollenberg. 1976. Marine algae of California. pp. [i]-xii, 1-827, 701 figs. Stanford, California: 

Stanford University Press.

Bakun, A. 1990. Global climate change and intensification of coastal ocean upwelling. Science 247:198-201.

Behrens, M.D. and K.D. Lafferty. 2004. Effects of marine reserves and urchin disease on southern Californian rocky 

reef communities. Mar Ecol Prog Ser 279: 129-139. 

Carr, M., E. Saarman, and D. Malone. 2013. North Central Coast Baseline Surveys of Kelp Forest Ecosystems: a 

report prepared for Sea Grant. 

California Environmental Quality Act (CEQA). 2001. Chapter 3 - Environmental Settings. pp 3-1 - 3-90.

Conrad, P.A., M.E. Grigg, C. Kreuder, E.R. James, J. Mazet, H. Dabritz, D.A. Jessup, F. Gulland, M.A. Miller. 

2005. Sea otters serve as sentinels for protozoal pathogens transmitted from the terrestrial hosts to marine 

mammals (abstract). In Cary Conference 2005: Infectious Disease Ecology, 56. Millbrook, NY: Institute of 

Ecosystem Studies.

Dayton, P.K. 1985. Ecology of Kelp Communities. Annual Review of Ecological Systematics 16:215-45.

Edwards, M. S. and J. A. Estes. 2006. Catastrophe, recovery and range limitation in NE Pacific kelp forests: a largescale perspective. Marine Ecology Progress Series 320:79-87.

Edwards, M.S. and G. Hernández-Carmona. 2005. Delayed recovery of giant kelp near its southern range limit in the 

North Pacific following El Niño. Marine Biology 147 (1):273-279.

Falkenburg L.J., S.D. Connell, and B.D. Russell. 2013. Disrupting the effects of synergies between stressors: 

improved water quality dampens the effects of future CO2 on a marine habitat. Journal of Applied Ecology 

50: 51-8.

Fredersdorf, J., R. Muller, S. Becker, C. Wiencke and K. Bischof. 2009. Interactive effects of radiation, temperature 

and salinity on different life history stages of the Arctic kelp Alaria esculenta (Phaeophyceae). Oecologia

160 (3): 483-92.

Frieder, C.A., S.H. Nam, T.R. Martz, and L.A. Levin. 2012. High temporal and spatial variability of dissolved 

oxygen and pH in a nearshore California kelp forest. Biogeosciences 9: 3917-30.

Garcia-Reyes, M. and J. Largier. 2010. Observations of increased wind-driven coastal upwelling off central 

California. Journal of Geophysical Research: Oceans (1978–2012) 115: C4. 

Graham, M.H. 1997. Factors determining the upper limit of giant kelp, Macrocystis pyrifera, along the Monterey 

Peninsula, central California, USA. Journal of Experimental Marine Biology and Ecology 218:127-149.

Graham, M.H. 2007. Sea-level change, effects on coastlines. Denny, M.W. and SD Gaines (eds), Encyclopedia of 

Tidepools, University of California Press, pp. 497-498. 

Graham, M.H., Harrold, C, Lisin, S, Light, K, Watanabe, J, and M.S. Foster. 1997. Population dynamics of 

Macrocystis pyrifera along a wave exposure gradient. Marine Ecology Progress Series 148:269-279. 

Graham, M.H., P.K. Dayton, and J.M. Erlandson. 2003. Ice-ages and ecological transitions on temperate coasts. 

Trends in Ecology and Evolution 18:33-40. 

Graham, M.H., B.S. Halpern, M.H. Carr. 2008. Diversity and dynamics of Californian subtidal kelp forests. Pp. 103- 

134 in McClanahan, T.R. and G.R. Branch (eds), Food Webs and the Dynamics of Marine Benthic 

Ecosystems, Oxford University Press. 

Grantham, B.A., F. Chan, K.J. Nielsen, D.S. Fox, J.A. Barth, A. Huyer, J. Lubchenco, and B.A. Menge. 2004. 

Upwelling-driven nearshore hypoxia signals ecosystem and oceanographic changes in the northeast 

70
Pacific. Nature 429: 749-54.

Hepburn, C.D., D.W. Pritchard, C.E. Cornwall, R.J. McLeaod, J. Beardall, J.A. Raven, and C.L. Hurd. 2011. 

Diversity of carbon use strategies in a kelp forest community: implications for a high CO2 ocean. Global 

Change Biology 17(7): 2488-97.

Hurd, A.M. 1919. The Relation between the Osmotic Pressure of Nereocystis and the Salinity of the Water. In: 

Volume 2 of University of Washington Publications. Puget Sound Biological Station. Pp. 188-199.

Kalvass, P. and M. Larson. 2001. California’s Living Marine Resources: A Status Report. Bull Kelp. California 

Department of Fish and Game. ANR Publication #SG01-11.

Keister, J.E., and P.T. Strub. 2008. Spatial and interannual variability in mesoscale circulation in the northern 

California Current System. Journal of Geophysical Research-Oceans 113. 

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine SanctuariesAdvisory Councils. 121pp. 

Mendelssohn, R. and F.B. Schwing. 2002. Common and uncommon trends in SST and wind stress in California and 

Peru-Chile current systems. Progress in Oceanography 53:141-62. 

Mendelssohn, R., F.B. Schwing, and S.J. Bograd. 2003. Spatial structure of subsurface temperature variability in the 

California Current, 1950–1993. Journal of Geophysical Research 108 (C3): 3093.

National Oceanic and Atmospheric Administration. 2013. Ecosystems: Impacts on Kelp Forests. Retrieved June 5, 

2014 from http://sanctuaries.noaa.gov/about/ecosystems/kelpimpacts.html. 

Norton, T.A. and G.R. South. 1969. Influence of reduced salinity on the distribution of two laminarian algae. Oikos 

20:320-26.

Schiel, D. R., Steinbeck, J. R., and M. S. Foster. 2004. Ten years of induced ocean warming causes comprehensive 

changes in marine benthic communities. Ecology 85(7): 1833-39.

Springer, Y., C. Hays, M, Carr, M. Mackey, J. Bloeser. 2006. Ecology and Management of the Bull Kelp, 

Nereocystis luetkeana: A Synthesis with Recommendations for Future Research. A report to the Lenfest 

Ocean Program at The Pew Charitable Trusts.

Vadas, R.L. 1972. Ecological implications of culture studies on Nereocystis luetkeana. Journal of Phycology 8: 196- 

203.

Zimmerman, R.C. and J.N. Kremer. 1984. Episodic nutrient supply to a kelp forest ecosystem in southern 

California. Journal of Marine Research 42:591-604. 

Zimmerman, R.C. and J.N. Kremer. 1986. In situ growth and chemical composition of the giant kelp, Macrocystis 

pyrifera: response to temporal changes in ambient nutrient availability. Marine Ecology Progress Series 

27:277-85. 

Zimmerman, R.C. and D.L. Robertson. 1985. Effects of El Niño on local hydrography and growth of the giant kelp, 

Macrocystis pyrifera, at Santa Catalina Island, California. Limnology and Oceanography 30:1298-1302. 

71
Nearshore soft-bottom1

 

Executive Summary The nearshore zone extends from the surf 

out to waters that are approximately 30 

meters deep (100 feet). This habitat lacks 

hard substrate and is greatly impacted by 

waves and currents. Key climate 

sensitivities identified for this habitat by 

workshop participants include coastal 

erosion, pH, wave action and turbidity. Key non-climate sensitivities include pollution and land 

use change. The nearshore soft-bottom habitat has a wide-ranging and continuous distribution 

and is considered to have moderate-high functional integrity, with only minor to moderate 

alterations, likely a result of compromised water quality. This habitat has moderate-high 

potential to resist climate impacts due to these characteristics, and may be able to recover 

moderately well due to the extensive dispersal capabilities of macroinvertebrate larvae. The 

habitat itself is rather homogenous, and there is moderate diversity in species and functional 

groups, with two major biological communities organized along a wave gradient. Societal value 

and management potential for this habitat are considered low-moderate.

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): coastal erosion (5, high), 

turbidity (4, moderate), pH (4, moderate), wave action (4, high), sea surface temperature (3, 

moderate), dynamic ocean conditions (currents/mixing/stratification) (3, low), precipitation (2, 

low), salinity (2, moderate), dissolved oxygen levels (2, moderate) 

Climate and climate-driven changes that may benefit the habitat: none identified

Overall habitat sensitivity to climate and climate-driven factors: Moderate

• Confidence of workshop participants: Moderate 

Supporting literature

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. 

Coastal Erosion 

Nearshore habitats may be directly impacted by coastal erosion or indirectly via human 

responses such as armoring and beach nourishment that will impact sediment supply and run-off 

(Largier et al. 2010). Erosion transports sediment into nearshore waters, which does help to 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Nearshore softbottomScore Confidence 

Sensitivity 3 Moderate 3 High

Exposure 4 Moderate-High 3 High

Adaptive Capacity 3 Moderate 3 High

Vulnerability 3 Moderate 3 High

72
maintain soft-bottom habitat. However, if sedimentation is excessive, negative impacts can 

include smothering of benthic invertebrates, reduced survival of fish eggs, oxygen depletion and 

increased turbidity (Schueler 1997). 

Turbidity 

Turbidity has been shown to negatively impact soft-bottom invertebrates, including mass die-offs 

of mole crabs in Atlantic Beach (Reilly and Bellis 1983), significantly reduced growth of clams 

(Lindquist and Manning 2001), and reduced feeding success of filter feeders due to gill clogging. 

A reduction in filter feeding invertebrates may further reduce water clarity and water clearing 

capacity (Auster and Langton 1999). Increased turbidity also reduces light penetration which 

reduces primary productivity of benthic microflora and phytoplankton (Auster and Langton 

1999). Decreased primary productivity will affect demersal zooplankton that support higher 

trophic level organisms. 

pH 

Nearshore habitat of the north-central California coast is vulnerable to exposure of future 

acidification from seasonal upwelling, which transports acidified waters that are under-saturated 

with respect to aragonite from offshore onto the continental shelf (Feely et al. 2008; Gruber et al. 

2012). However, carbonate chemistry in nearshore coastal areas can also vary according to 

localized freshwater inputs and/or other factors (e.g., acid-base reactions), which can compound 

or ameliorate acidification trends at various time scales and affect both the benthic and pelagic 

habitats critical for marine invertebrates (Waldbusser and Salisbury 2014). Acidified upwelled 

water may negatively impact calcifying organisms by making it more difficult to calcify and by 

potentially dissolving calcified structures (Gazeau et al. 2007, Doney et al. 2009, Doney 2010, 

Gruber et al. 2012, Bednarsek et al. 2014), which can affect marine food webs (Sydeman and 

Thompson 2013 and citations therein) and can lead to changes in population abundances due to 

altered predation dynamics (Dixson et al. 2010). 

Wave action 

Waves are a critical feature of disturbance to the nearshore habitat, removing as much as a meter 

of sediment at depths greater than 10 meters (Hodgson and Nybakken 1973). Sediment 

redistribution and the topography of the habitat are both highly impacted by increased significant 

wave heights (Largier et al. 2010). Biological communities in the nearshore soft-bottom are 

organized along a wave-induced gradient (crustaceans inhabiting the more wave-impacted zone, 

and polychaetes dominating the deeper, more stable, fine-sand and mud zone, Oliver and Kvitek 

1996). Changes in the magnitude and frequency of wave activity may impact the composition 

and depth range of these communities. 

II. Sensitivities to disturbance regimes

Disturbance regimes identified: wind, storms, and disease 

Overall habitat sensitivity to disturbance regimes: Moderate

• Confidence of workshop participants: High 

Supporting literature

Wind 

Wind plays a critical role in the delivery of cold, nutrient-rich upwelled waters to the nearshore 

habitat. Increased nutrient delivery may benefit macroalgae and phytoplankton (Largier et al. 

73
2010), as well as increase productivity, which is associated with enhanced seabird breeding 

success (Ainley et al. 1995, Abraham and Sydeman 2004, Sydeman et al. 2006, Jahncke et al. 

2008). However, intensification of upwelling, and subsequent enhanced offshore transport, may 

also lead to increased dispersion of larvae and spores, and enhanced turbulent mixing that may 

negatively impact food particle availability necessary for larval survival (Bakun 1990).

Storms

Storms also enhance turbulence in the nearshore region and lead to increasingly intense run-off 

that may cause increased sedimentation and higher resuspension of sediment, resulting in 

increased turbidity and light attenuation (Largier et al. 2010). Increased runoff and sedimentation 

associated with storms can alter water quality and quantity at river mouths and in open coastal 

habitat (Gibson et al. 2003), affecting delta formation and the quality of soft-bottom habitats in 

these areas (Sarah Allen, pers. comm., 2014). Storm waves are a critical feature of nearshore 

dynamics (see wave action section above), but severe storm events may reduce planktonic food 

sources and negatively impact local populations of fish and invertebrates (McGowan et al. 1998). 

Disease

The prevalence of disease in marine organisms is expected to increase in response to warming 

water temperatures (Harvell et al. 2002), and has been documented in seagrasses, sea urchins and 

sea stars (Harvell et al. 1999, Hewson et al. 2014). Increased water temperature both increases

organism susceptibility to infection, and also enhances the virulence and success of pathogens 

(Largier et al. 2010). 

III. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): pollution and poisons (4, high), land use 

changes (4, high), transportation (2, high), energy production (1, high), 

Overall habitat sensitivity to non-climate stressors: Moderate

• Confidence of workshop participants: High

Overall habitat exposure to non-climate stressors: Low-Moderate

• Confidence of workshop participants: High 

Supporting literature

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. 

Pollution and poisons 

Pollutants, including agricultural and livestock waste, wastewater, sewage outfalls, historic 

mining, and industrial wastes, can be carried into the study region via the freshwater outflow 

from San Francisco Bay (Largier et al. 2010), significantly reducing water clarity. The release of 

pollutants during dredging of soft bottom habitats has been documented, and may potentially 

expose species to additional pollutants (Sarah Allen, pers. comm., 2014). Increased extreme 

precipitation events will impact the timing and intensity of runoff of terrestrial pollutants, which 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

74
will have important consequences for the timing and intensity of harmful algal blooms 

(Anderson et al. 2008, Kudela et al. 2008). 

Land Use Change 

Land use pressures, such as agriculture, ranching, mining and coastal development, impact 

nearshore water quality by increasing sedimentation, turbidity and run-off of pollutants (Gibson 

et al. 2003, ONMS 2010). Land use changes can also drive shifts in freshwater delivery (volume 

and timing) to river mouths and open coastal environments; both water pulses and water 

reductions can affect habitat structure and quality and the health of component species (Gibson et 

al. 2003) in nearshore soft-bottom habitats.

IV. Other sensitivities 

Other critical factors likely to influence the sensitivity of the habitat: ocean temperatures at depth 

and in the mid-water column

• Confidence of workshop participants: Moderate 

• Confidence of workshop participants in the degree to which these factors influence 

habitat sensitivity: Moderate

Supporting literature

Water temperature at depth and throughout the water column may increase during more frequent 

and intense El Niño events and decrease during more intense seasonal upwelling events. Low 

reproductive success in seabirds (Ainley et al. 1995, Abraham and Sydeman 2004, Sydeman et 

al. 2006, Jahncke et al. 2008) and low productivity/survival in pinnipeds (Sydeman and Allen 

1999) have been correlated with increased water temperatures, especially during El Niño events. 

Adaptive Capacity

I. Extent, integrity, and continuity

Geographic extent of the habitat: 5 (Transcontinental) 

• Confidence of workshop participants: High 

Structural and functional integrity of habitat: 4 (Minor to moderate alterations, likely a result of 

compromised water quality) 

• Confidence of workshop participants: High 

Continuity of habitat: 5 (Continuous) 

• Confidence of workshop participants: High 

Supporting literature

Soft-bottom subtidal habitat accounts for roughly 80% of the nearshore zone in the southern 

portion of the study region (SIMoN 2014). On-going monitoring studies in Monterey Bay 

National Marine Sanctuary indicate that large, structural sessile habitat-forming invertebrates 

(e.g., sponges, anemones, tube worms) appear to be healthy and no major perturbations have 

been observed (SIMoN 2014). 

75
II. Resistance and recovery

Habitat resistance to the impacts of stressors/maladaptive human responses: Moderate-High

• Confidence of workshop participants: High 

Ability of habitat to recover from stressor/maladaptive human response impacts: no answer

provided 

Supporting literature

No rating for recovery from disturbance and impacts was provided by workshop participants, 

though nearshore soft-bottom macroinvertebrate larvae were found to have the greatest potential 

for extensive dispersal relative to other habitats (Grantham et al. 2003), suggesting that many 

species in this habitat may be able to colonize new areas or move to more suitable conditions if 

necessary. 

III. Habitat diversity

Physical and topographical diversity of the habitat: Low-Moderate

• Confidence of workshop participants: High 

Diversity of component species within the habitat: Moderate

• Confidence of workshop participants: High 

Diversity of functional groups within the habitat: Moderate

• Confidence of workshop participants: Moderate 

Keystone or foundational species within the habitat: none identified

Supporting literature

The homogenous soft-bottom habitat is composed exclusively of soft sediments such as sand and 

mud; however, at the mouth of the San Francisco Bay are the largest sand waves on the west 

coast (6 m in height, 80 m from crest to crest) that offer a very distinct and unique habitat 

(Gibbons and Barnard, 2007). Two major biological communities exist in this habitat along a 

wave-induced gradient: a crustacean zone of small, mobile, deposit-feeding crustaceans, 

including the sand-burrowing amphipods and surface-active cumaceans and ostracods, and the 

polychaete zone, dominated by worms that inhabit fairly permanent tubes/burrows and other 

sessile and suspension-feeding organisms (Oakden 1981, Slattery 1980, Slattery 1985). Fish 

diversity in this habitat is relatively low compared to adjacent reefs, but abundance can be very 

high and serve as important forage for predatory fish, seabirds and marine mammals (SIMoN 

2014). 

Gray whales may be considered a keystone species because they are recognized as ecological 

engineers for their foraging behavior. They have a dramatic effect on bottom sediments, as one 

whale can plow 100 acres in one summer while foraging in the soft bottom sediments of Alaska. 

Resident whales that over-summer in central California are becoming more frequent (Sarah 

Allen, pers. comm., 2014). 

76
IV. Management potential

Value of habitat to people: Low-Moderate

• Confidence of workshop participants: High 

• Description of value: most of the general public does not interact with the soft-bottom 

subtidal, and value lies in the use of this habitat for commercial and recreational fishing 

(including halibut, anchovy, sardine, Dungeness crab). 

Likelihood of managing or alleviating climate change impacts on habitat: Low-Moderate

• Confidence of workshop participants: High 

• Description of potential management actions: to limit human impacts such as dredging 

and bottom-tending fishing gear that may exacerbate climate impacts.

Supporting literature

Resource managers may value this habitat for its role in nutrient cycling and abundance of forage 

organisms that support birds, fish and marine mammals (Oregon DFW 2014). 

V. Other adaptive capacities: none identified 

Exposure 

I. Future climate exposure6

Future climate and climate-driven factors identified (score7, confidence8): increased coastal 

erosion and runoff (5, high), decreased pH (5, high), changes in sea surface temperature (4, 

moderate), increased storminess (4, high), altered currents and mixing (2, moderate) 

Degree of exposure to future climate and climate-driven factors: Moderate-High

• Confidence of workshop participants: High 

Literature Cited 

Abraham, C.L. and W.J. Sydeman. 2004. Ocean climate, euphausiids and auklet nesting: interannual trends and 

variation in phenology, diet and growth of a planktivorous seabird. Marine Ecology Progress Series 

274:232-250. 

Ainley, D.G., W.J. Sydeman and J. Norton. 1995. Upper trophic level predators indicate interannual negative and 

positive anomalies in the California Current food web. Marine Ecology Progress Series 118:69-79.

Anderson, D., J. Burkholder, W. Cochlan, P. Glibert, C. Gobler, C. Heil, R. Kudela, M. Parsons, J. Rensell, D. 

Townsend, V. Trainer, and G. Vargo. 2008. Harmful algal blooms and eutrophication: Examples and 

linkages from selected coastal regions of the United States. Harmful Algae 8: 39-53. 

Auster, P. J. and R.W. Langton. 1999. The effects of fishing on fish habitat. p. 150-187 in L. Benaka (ed.). Fish 

habitat: essential fish habitat and rehabilitation. American Fisheries Society, Bethesda, MD, Symposium

22 , 459 p. 

Bakun, A. 1990. Global climate change and intensification of coastal ocean upwelling. Science 247: 198-201.

Dixson, D.L., P.L. Munday, and G.P. Jones. 2010. Ocean acidification disrupts the innate ability of fish to detect

6 Supporting literature for future exposure to climate factors is provided in the introduction.

7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

77
predator olfactory cues. Ecology Letters 13, 68-75.

Bednaršek, N., R. Feely, J. Reum, B. Peterson, J. Menkel, S. Alin and B. Hales. 2014. Limacina helicina shell 

dissolution as an indicator of declining habitat suitability owing to ocean acidification in the California 

Current Ecosystem. Proceedings of the Royal Society B: Biological Sciences 281 (1785):20140123.

Doney, S. C. 2010. The growing human footprint on coastal and open-ocean biogeochemistry. Science 328 

(5985):1512-1516.

Doney, S. C., V. J. Fabry, R. A. Feely and J. A. Kleypas. 2009. Ocean acidification: the other CO2 problem. Annual 

Review of Marine Science 1:169-192.

Feely, R.A., C.L. Sabine, J.M. Hernandez-Ayon, D. Ianson, and B. Hales. 2008. Evidence for upwelling of corrosive 

"acidified" seawater onto the continental shelf. Science 320, 1490. 

Gazeau, F., C. Quiblier, J. M. Jansen, J. P. Gattuso, J. J. Middelburg and C. H. Heip. 2007. Impact of elevated CO2 

on shellfish calcification. Geophysical Research Letters 34 (7).

Gibbons, H. and P.L. Barnard. 2007. Sand Waves at the Mouth of San Francisco Bay, California [Postcard]: U.S. 

Geological Survey General Information Product 54 [http://pubs.usgs.gov/gip/2007/54/]. 

Gibson, R., M. Barnes and R. Atkinson. 2003. Impact of changes in flow of freshwater on estuarine and open coastal 

habitats and the associated organisms. Oceanography and Marine Biology, An Annual Review, Volume 40: 

An Annual Review 40:233.

Grantham, B.A., G.L. Eckert, and A.L. Shanks. 2003. Dispersal potential of marine invertebrates in diverse habitats. 

Ecological Applications 13:S108-S116.

Gruber, N., C. Hauri, Z. Lachkar, D. Loher, T. L. Frölicher and G.-K. Plattner. 2012. Rapid progression of ocean 

acidification in the California Current System. Science 337 (6091):220-223.

Harvell, C.D., K. Kim, J.M. Burkholder, R.R. Colwell, P.R. Epstein, D.J. Grimes, E.E. Hofmann, E.K. Lipp, 

A.D.M.E.Osterhaus, R.M. Overstreet, J.W. Porter, G.W. Smith and G.R. Vasta. 1999. Emerging marine 

diseases – climate links and anthropogenic factors. Science 285:1505-1510. 

Harvell, C.D., C.E. Mitchell, J.R. Ward, S. Altizer, A.P. Dobson, R.S. Ostfeld and M.D. Samuel. 2002. Climate 

warming and disease risks for terrestrial and marine biota. Science 296:2158-2162.

Hewson, I., J. B. Button, B. M. Gudenkauf, B. Miner, A. L. Newton, J. K. Gaydos, J. Wynne, C. L. Groves, G. 

Hendler and M. Murray. 2014. Densovirus associated with sea-star wasting disease and mass mortality. 

Proceedings of the National Academy of Sciences 111 (48):17278-17283.

Hodgson, A. T. and J. W. Nybakken. 1973. A quantitative summary of the benthic infauna of northern Monterey 

Bay, California. Moss Landing Marine Labs Tech. Rep. 73-8, 241 p.

Jahncke, J., Saenz, B.L., Abraham, C.L., Rintoul, C., Bradley, R.W., and Sydeman, W.J. 2008. Ecosystem responses 

to short-term climate variability in the Gulf of the Farallones, California. Progress in Oceanography 

77:182-193. 

Kudela, R.M., JQ Lane, and WP Cochlan. 2008. The potential role of anthropogenically derived nitrogen in the 

growth of harmful algae in California, USA. Harmful Algae 8, 103-110. 

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine SanctuariesAdvisory Councils. 121pp. 

Lindquist, N. and L. Manning. 2001. Impacts of beach nourishment and beach scraping on critical habitat and 

productivity of surf fishes. NC Division of Marine Fisheries, Fisheries Resource Grant 98-EP-05: 41.

McGowan, J.A., D.R. Cayan, and L.M. Dorman. 1998. Climate-ocean variability and ecosystem response in the 

Northeast Pacific. Science 281: 210-217.

Oakden, J.M. 1981. Feeding and habitat selection in five species of central California Phoxocephalid amphipods.

MA Thesis, California State University.

Oliver, J. and R. Kvitek. 1996. Shallow Soft Bottom Habitats. In: Guerrero J, and R Kvitek (editors), Monterey Bay 

National Marine Sanctuary Site Characterization. Retrieved July 17, 2014 

from http://montereybay.noaa.gov/sitechar/shallow.html

Office of National Marine Sanctuaries (ONMS). 2010. Gulf of the Farallones National Marine Sanctuary Condition

Report. U.S. Department of Commerce, National Oceanic and Atmospheric Administration, Office 

of National Marine Sanctuaries, Silver Spring, MD. 97 pp.

Oregon Department of Fish and Wildlife. 2014. Climate Change and Oregon’s Subtidal Habitats.

http://www.dfw.state.or.us/conservationstrategy/docs/climate_change/Subtidall_Fact_Sht.pdf. 

Sanctuary Integrated Monitoring Network (SIMoN). 2014. Sandy Floor. Retrieved July 17, 2014 from

http://sanctuarysimon.org/monterey/sections/sandyFloor/overview.php. 

Schueler, T. R. 1997. Impact of suspended and deposited sediment. Watershed Protection Techniques 2(3): 443-4. 

78
Reilly, F.J. and B.J. Bellis. 1983. The ecological impact of beach nourishment with dredged materials on the 

intertidal zone at Bogue Banks, North Carolina. U.S. Army Corps of Engineers, Coastal Engineering 

Research Center, Fort Belvoir, VA. 

Slattery, P.N. 1980. Ecology and life histories of dominant infaunal crustaceans inhabiting the subtidal high energy

beach at Moss Landing, California. MA Thesis, San Jose State University.

Slattery, P.N. 1985. Life histories of infaunal amphipods from subtidal sands of Monterey Bay, California. Journal 

of Crustacean Biology 5(4): 635-649.

Sydeman, W.J. and S. Allen. 1999. Pinniped population dynamics in central California: Correlations with sea 

surface temperature and upwelling indices. Marine Mammal Science 15(2):446-461.

Sydeman, W., and S.A. Thompson. 2013. Potential Impacts of Climate Change on California’s Fish and Fisheries. 

Oakland, CA: Farallon Institute for Advanced Ecosystem Research. Literature Review.

Sydeman, W.J., R.W. Bradley, P. Warzybok, C.L. Abraham, J. Jahncke, K.D. Hyrenbach, V. Kousky, J.M. Hipfner, 

and M.D. Ohman. 2006. Planktivorous auklet Ptychoramphus aleuticus responses to ocean climate, 2005: 

unusual atmospheric blocking? Geophysical Research Letters 33 L22S09. 

Waldbusser, G. G. and J. E. Salisbury. 2014. Ocean acidification in the coastal zone from an organism's perspective: 

multiple system parameters, frequency domains, and habitats. Annual Review of Marine Science 6:221-

247.

Widdicombe, S. and J.J. Spicer. 2008. Predicting the impact of ocean acidification on benthic biodiversity: What 

can animal physiology tell us? Journal of Experimental Marine Biology and Ecology 366: 187-197.

79
Offshore rocky reefs1

Executive Summary Offshore rocky reefs, including banks 

and seamounts, are generally discrete 

features that provide complex and 

heterogeneous environments for 

colonization by deep-water corals, 

sponges, other invertebrates, and 

numerous fish species. Key climate 

sensitivities identified for this habitat by workshop participants include dissolved oxygen, 

dynamic ocean conditions (currents/mixing/stratification), and pH. The key non-climate 

sensitivity identified as a potential future threat that currently is not impacting the study region is 

invasive tunicates. Benthic shallow banks are an isolated and patchy habitat type, and exhibit 

moderate to moderate-high structural and functional integrity. This habitat has a low-moderate to 

moderate level of physical diversity but a moderate-high level of diversity of component species 

and functional groups. Hydrocorals and sponges provide an important role in benthic shallow 

banks by forming habitat features for benthic communities. Potential management measures 

include reducing human stressors, as it is unlikely climate stressors can be alleviated. 

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): dissolved oxygen levels (5, 

high), pH (3, low), dynamic ocean conditions (currents/mixing/stratification) (3, moderate), sea 

surface temperature (1, low)

Climate and climate-driven changes that may benefit the habitat: dynamic ocean conditions 

(currents/mixing/stratification)

• Description of benefits: enhanced wind-driven upwelling that brings cold, nutrient rich 

water to the area may occur in response to changes in wind patterns and dynamic ocean 

conditions and may have beneficial effects on benthic shallow bank habitats. 

Overall habitat sensitivity to climate and climate-driven changes: Low-Moderate

• Confidence of workshop participants: High 

Additional participant comments

Benthic species with a center of distribution in higher latitudes may have a more difficult time 

adapting to warming temperatures, as these species are at the southern end of their distribution 

and likely close to their thermal tolerance limits. In contrast, benthic species with a center of 

distribution in lower latitudes may expand their distribution north as ocean temperatures warm. 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Offshore rocky 

reefs

Score Confidence 

Sensitivity 2 Low-Moderate 2 Moderate

Exposure 2 Low-Moderate 2 Moderate

Adaptive Capacity 3 Moderate 3 High

Vulnerability 2 Low-Moderate 2 Moderate

80
However, there are complex interactions between temperature and other physical parameters that 

will have synergistic and unpredictable effects on benthic communities. For example, if 

increased sea surface temperature leads to decreased productivity, it would likely have a 

significant impact on benthic communities.

Supporting literature

Dissolved Oxygen 

Areas adjacent to upwelling centers (e.g., Point Arena) are particularly susceptible to low 

dissolved oxygen, as the upwelling process naturally delivers low oxygen water from the deep 

ocean. An extensive Oxygen Minimum Zone (OMZ) exists along the continental margin of the 

northeast Pacific Ocean (Kamykowski and Zentara 1990), although the current source for 

upwelled water is shallower than this zone (Grantham et al. 2004). Recent work indicates that in 

the vicinity of Point Conception, the OMZ has shoaled by up to 90 meters (Bograd et al. 2008). 

If the OMZ were to migrate shallow enough to provide the source water for coastal upwelling, 

hypoxic events may be observed with significant and complex ecological changes and impacts 

(Bograd et al. 2008). For example, shoaling of the OMZ could lead to direct hypoxia-related 

effects on benthic organisms where the OMZ contacts the continental margin (Levin 2003). 

pH 

pH is very low in upwelled waters along the coast of western North America, including in this 

study region (Feely et al. 2008). Low pH (i.e., “ocean acidification”) water can be corrosive to a 

wide variety of organisms including corals, sea urchins, and mollusks (Guinotte and Fabry 

2008), with possible declines in calcification rates (Gazeau et al. 2007). Larval and juvenile 

stages of benthic organisms, which spend the developmental phase of their early life history in 

the water column, may be impacted by ocean acidification (Kurihara et al. 2007), and declines in 

pH will likely add cumulatively to the stress of benthic organisms. Declines in the biomass of 

plankton will likely affect benthic communities. 

Dynamic ocean conditions (currents/mixing/stratification)

Because sessile benthic organisms rely on the movement of currents to deliver suspended 

particulate food, “any significant disruption to the timing or intensity of seasonal upwelling 

winds resulting in reduced productivity over time would likely have negative impacts” (e.g., 

survival, recruitment success) on benthic organisms (Largier et al. 2010). This climate factor also 

impacts the habitat’s exposure to sea surface temperature, dissolved oxygen and pH. 

Ocean temperature

Increased water temperature will likely have a negative effect on benthic communities if it leads 

to less productive conditions (Vulnerability assessment workshop, pers. comm., 2014). Warm 

water conditions have also been shown to affect juvenile rockfish, with subsequent impacts on 

seabirds. For example, trawl data from NOAA National Marine Fisheries Service shows a sharp 

decline in juvenile rockfish in response to warm water conditions observed in the central 

California Current region in 2005. Similarly, diet studies on common murres have shown a 

decrease in juvenile rockfish during years with warm sea surface temperatures and/or warm PDO 

periods (Miller and Sydeman 2004). Conversely, the appearance of juvenile rockfish in the diet 

of rhinoceros auklet was higher in years with low sea surface temperatures (Thayer and Sydeman 

2007). 

81
II. Sensitivities to disturbance regimes: 

Disease was identified as one possible disturbance regime that may be a source of sensitivity for 

benthic shallow banks, however the potential impact is unknown. 

III. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): invasive species (3, moderate), pollution 

(1, moderate), harvest (gear) (1, moderate) 

Overall habitat sensitivity to non-climate stressors: Low-Moderate

• Confidence of workshop participants: Moderate 

Overall habitat exposure to non-climate stressors: Low

• Confidence of workshop participants: Moderate 

Supporting literature

Although not identified by workshop participants, new cables and pipelines would represent an 

additional non-climate threat to benthic shallow banks due to their significant impact on benthic 

habitat during construction and placement of cables (ONMS 2009). 

Invasive species

Though not currently impacting the study region, there is some concern regarding an invasive 

tunicate, Didemnum sp., that has been observed in nearby coastal areas and has covered large 

areas of Georges’ Bank on the east coast (Bullard et al. 2007). The invasive tunicate is similar to 

a native Didemnum species, and sampling will be necessary to elucidate which species is present 

on Cordell Bank (ONMS 2009) and other offshore reefs in the study region. 

Pollution and poisons 

Due to the offshore nature of this habitat type, and the distance from population centers on the 

mainland, water quality is considered to be in fairly good condition (ONMS 2009). However, oil 

spills and dispersants are a threat to the health of this ecosystem, and there have been several 

large spills in the region over the last decade. 

Harvest (gear)

Significant amounts of derelict fishing gear have been documented in rocky areas of Cordell 

Bank (ONMS 2009). The most common gear types observed are long-lines and gill nets; most of 

this gear is entangled among boulders or on high relief rock. Entanglement can lead to damage of 

sensitive habitats that provide food and shelter for invertebrates and fishes, including structureforming hydrocorals and sponges (Barnes and Thomas 2005). Many areas in the sanctuary 

(~86%) are now closed to the use of some type of bottom contact gear and bottom trawling, and 

the condition of biologically structured habitats is likely to improve. However, recovery may be 

slow due to the slow growth of some habitat-forming organisms (e.g., cold water corals). 

Workshop participants also noted that it is difficult to assess the affects of harvest gear on 

benthic shallow banks, and that the impact of harvest gear is dependent on location. 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

82
IV. Other sensitivities: none identified 

Adaptive Capacity

I. Extent, integrity, and continuity

Geographic extent of the habitat: 3 (Distribution within single state to two states)

• Confidence of workshop participants: High 

Structural and functional integrity of habitat: 3 (Altered but not degraded) 

• Confidence of workshop participants: High 

Continuity of habitat: 1 (Isolated and/or fragmented) 

• Confidence of workshop participants: High 

Additional participant comments

Although offshore rocky reefs, including banks and seamounts, are ubiquitous worldwide, they 

are patchy in their distribution and may act as “stepping stones” for the dispersal of species. In 

this study region, benthic shallow banks occur as discrete rocky reef banks that are isolated in 

space and have higher elevations and a different substrate than the surrounding seabed of the 

continental shelf. Benthic shallow banks exhibit moderate to moderate-high structural and 

functional integrity, due to relatively good water quality conditions but some degradation due to 

derelict fishing gear.

II. Resistance and recovery

Degree of habitat’s resistance to the impacts of stressors/maladaptive human responses: no 

answer provided 

Ability of habitat to recover from stressor/maladaptive human response impacts: Low-Moderate 

• Confidence of workshop participants: High 

Additional participant comments

Benthic habitat overall is fairly resilient, but species assemblage might change in response to 

climate change.

III. Habitat diversity

Physical and topographical diversity of the habitat: Low-Moderate

• Confidence of workshop participants: High

Diversity of component species within the habitat: Moderate-High

• Confidence of workshop participants: High 

Diversity of functional groups within the habitat: Moderate-High

• Confidence of workshop participants: High 

Keystone or foundational species within the habitat: none provided 

83
Supporting literature

Much of Cordell Bank, Rittenberg Bank, and Fanny Shoal is granite reef with a mixture of 

boulders, smaller rocks, sand, and mud. The bathymetry and location of Cordell Bank (e.g., 

nearness to upwelling centers) combine to make it a very productive marine habitat. The vertical 

structure, habitat complexity, and rocky substrate of benthic shallow banks provide ideal habitat 

for colonization by deep-water corals, sponges, other invertebrates, and numerous fish species. 

Hydrocorals and sponges are important components of benthic shallow banks as they form 

habitat for benthic communities. Diversity in the water surrounding Cordell Bank as well as the 

bank itself includes 246 species of fish, 26 species of marine mammal, 59 species of bird, and 

numerous benthic algae and invertebrates. In 2012, 23 taxa of managed fish species, 113 coral 

colonies, 322 seapens and seawhips, and 2,628 sponges were observed on Rittenberg Bank. The 

banks serve as critical habitat for young of the year, juvenile, and adult rockfish, as well as for 

settlement of larvae from the water column (ONMS 2009). 

IV. Management potential

Value of habitat to people: Moderate-High

• Confidence of workshop participants: Low-Moderate 

• Description of value: This habitat is valued because of the inclusion of banks and 

seamounts in national marine sanctuaries on the west coast, in particular a sanctuary 

focused on Cordell Bank and the expansion of Monterey Bay National Marine Sanctuary 

for the purpose of including Davidson Seamount. Another example of societal value is 

that Cordell Bank is known as a historically good fishing spot and an area where whales 

and seabirds congregate. 

Likelihood of managing or alleviating climate change impacts on habitat: Low

• Confidence of workshop participants: High 

• Description of potential management options: It is difficult to manage climate changes in 

deep water; managers may be better able to minimize other human stressors on this 

habitat type. 

V. Other adaptive capacities: none identified

Exposure 

I. Future climate exposure6

Future climate and climate-driven changes identified (score7, confidence8): decreased pH (4, 

high), decreased dissolved oxygen levels (2, low), altered currents and mixing (2, moderate), 

changes in sea surface temperature (1, low)

Exposure to future climate and climate-driven changes: Low-Moderate

• Confidence of workshop participants: Moderate 

6 Supporting literature for future exposure to climate factors is provided in the introduction.

7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

84
Additional participant comments

Potential areas of refugia may include deep reefs, possibly protected from decreased oxygen if 

the event is localized and from temperature increases that occur at shallower depths, and areas 

located outside of upwelling centers. Workshop participants also noted that increases in ocean 

temperature are also important to consider for this habitat type, and there are likely no potential 

areas of refugia from this factor. 

Literature Cited

Barnes, P.W. and J.P. Thomas, eds. 2005. Benthic habitats and the effects of fishing. American Fisheries Society, 

Symposium 41, Bethesda, Maryland.

Bograd, S., C. Castro, E. DiLorenzo, D. Palacios, H. Bailey, W. Gilly, and F. Chavez. 2008. Oxygen declines and 

the shoaling of the hypoxic boundary in the California Current. Geophysical Research Letters 35: L12607.

Bullard, S.G., G. Lambert, M.R. Carman, J. Byrnes, R.B. Whitlatch, G. Ruiz, R.J. Miller, L. Harris, P.C. Valentine, 

J.S. Collie, J. Pederson, D.C. McNaught, A.N. Cohen, R.G. Asch, J. Dijkstra, and K. Heinonen. 2007. The 

colonial ascidian Didemnum sp. A: current distribution, basic biology and potential threat to marine 

communities of the Northeast and West coasts of North America. Journal of Experimental Biology and 

Ecology 342: 99-108.

Feely, R.A., C.L. Sabine, J.M. Hernandez-Ayon, D. Ianson, and B. Hales. 2008. Evidence for upwelling of corrosive 

"acidified" seawater onto the continental shelf. Science 320: 1490.

Gazeau, F., C. Quiblier, J.M. Jansen, J. Gattuso, J.J. Middelburg, and C.H.R. Heip. 2007. Impact of elevated CO2 on 

shellfish calcification. Geophysical Research Letters 34: L07603.

Grantham, B.A., F. Chan, K.J. Nielsen, D.S. Fox, J.A. Barth, A. Huyer, J. Lubchenco, and B.A. Menge. 2004. 

Upwelling-driven nearshore hypoxia signals ecosystem and oceanographic changes in the northeast 

Pacific. Nature 429: 749-54.

Guinotte, J.M. and V.J. Fabry. 2008. Ocean acidification and its potential effects on marine ecosystems. In: Ostfeld, 

R.S. and W.H. Schlesinger, eds. The Year in Ecology and Conservation Biology 2008, Annals of the New 

York Academy of Sciences, pp. 320-342.

Kamykowski, D.Z. and S.J. Zentara. 1990. Hypoxia in the world ocean as recorded in the historical data set. DeepSea Research 37: 1861-74.

Kurihara, H., S. Kato, and A. Ishimatsu. 2007. Effects of increased seawater pCO2 on early development of the 

oyster Crassostrea gigas. Aquatic Biology 1: 91-98.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine SanctuariesAdvisory Councils. 121pp. 

Levin, L.A. 2003. Oxygen minimum zone benthos: Adaptation and community response to hypoxia. Oceanography 

and Marine Biology 41: 1-45.

Miller, A.K. and W.J. Sydeman. 2004. Rockfish response to low-frequency ocean climate change as revealed by the 

diet of a marine bird over multiple time scales. Marine Ecology Progress Series 281: 207-216.

Office of National Marine Sanctuaries (ONMS). 2009. Cordell Bank National Marine Sanctuary (CBNMS) 

Condition Report 2009. US Department of Commerce, National Oceanic and Atmospheric Administration, 

Office of National Marine Sanctuaries, Silver Spring, MD, USA.

Palacios, D.M., S.J. Bograd, R. Mendelssohn, F.B. Schwing. 2004. Long-term and seasonal trends in stratification in 

the California Current, 1950-1993. Journal of Geophysical Research 109.

Thayer, J.A. and W.J. Sydeman. 2007. Spatio-temporal variability in prey harvest and reproductive ecology of a 

piscivorous seabird, Cerorhinca monocerata, in an upwelling system. Marine Ecology Progress Series 329: 

253-265.

85
Pelagic Water Column1

Executive Summary The pelagic water column in the study 

region includes the sea surface to seabed, 

and is a highly heterogeneous and 

dynamic environment. Light and nutrient 

availability are the principal factors that 

determine the abundance and distribution 

of organisms in this habitat type. 

Biological activity is controlled by a balance between wind-driven upwelling and stratification of 

the water column. Key climate sensitivities identified for this habitat by workshop participants 

include upwelling, ocean temperature, dissolved oxygen, pH, and dynamic ocean conditions, and 

no key non-climate sensitivities were identified. The pelagic water column is a continuous, 

transboundary habitat type, and exhibits moderate-high structural and functional integrity. This 

habitat has a low degree of physical diversity but a moderate-high degree of diversity of 

component species and functional groups. This is a bottom-up driven system, where krill are 

considered keystone species and large changes in population size are related to changing oceanic 

conditions. Declines in krill abundance have negative impacts on higher trophic levels that 

depend upon them. Potential management measures include reducing human stressors, as it is 

unlikely climate stressors can be alleviated.

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): dynamic ocean conditions 

(currents/mixing/stratification) (5, high), upwelling (5, high), dissolved oxygen levels (4, high), 

pH (4, moderate), sea surface temperature (3, high), precipitation (3, high), air temperature (2, 

moderate), salinity (1, moderate) 

Climate and climate-driven changes that may benefit the habitat: upwelling

• Description of benefits: Changes in ocean pH and sea surface temperature may be 

beneficial to kelp and changes in dynamic ocean conditions may increase nutrient and 

larval transport. 

Overall habitat sensitivity to climate and climate-driven factors: Moderate

• Confidence of workshop participants: High 

Additional participant comments 

Potential benefits to this habitat include increased production that may result from enhanced 

wind-driven upwelling that brings cold, nutrient rich water to the surface. There may be both 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Pelagic Water 

Column

Score Confidence 

Sensitivity 3 Moderate 3 High

Exposure 4 Moderate-High 3 High

Adaptive Capacity 4 Moderate-High 3 High

Vulnerability 3 Moderate 3 High

86
winners and losers as a result of changing conditions, as different species will be impacted 

differently. The impacts of changes in sea surface temperature and ocean temperature, which 

impact ocean stratification, and prevailing wind patterns, which drives upwelling, are unknown. 

It is possible that increased upwelling could counter the impacts of increased stratification.

Supporting literature

Although not identified by workshop participants, species range shifts such as the jumbo squid – 

which has already expanded into the region and persisted – have the potential to significantly 

impact the biodiversity and community composition within Cordell Bank National Marine 

Sanctuary (ONMS 2009). 

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. 

Dynamic ocean conditions (currents/mixing/stratification)

Thermoclines have become stronger and deeper in offshore waters of the region (Palacios et al. 

2004), and stratification due to climate change has already been reported to alter zooplankton 

communities in offshore waters (Roemmich and McGowan 1995). Similarly, in the Bering Sea, 

warmer and more stratified waters have led to increased numbers of gelatinous zooplankton 

(Brodeur and Terazaki 1999). 

Upwelling

Seasonal variations in upwelling can affect phytoplankton and zooplankton abundances, with 

subsequent impacts on higher trophic levels. For example, years with strong, early alongshore 

winds led to strong and early upwelling, resulting in increased abundance of important 

zooplankton species (e.g., euphausiids and copepods) and above-average breeding success of 

Cassin’s auklet. Strong upwelling is generally associated with high seabird reproductive success 

because of its positive effect on ocean productivity (Ainley et al. 1995, Abraham and Sydeman 

2004, Sydeman et al. 2006, Jahncke et al. 2008). Conversely, in 2005 and 2006, the opposite 

scenario occurred where a later spring upwelling was observed due to weak and/or delayed 

alongshore winds. Significant bottom-up effects in the ecosystem were observed and 

documented as a result of this delayed upwelling, including low primary production, low krill 

abundance, shifts in the zooplankton community (e.g., decreased abundance of adult krill and 

copepods and increased abundance of gelatinous zooplankton), a decline in at-sea seabird 

abundance, late and reduced reproductive success in seabirds (e.g., Cassin’s auklets abandoned 

nests and failed to breed due to lack of available adult krill) (Jahncke et al. 2008), and declines in 

blue whale (another krill predator) sightings (PRBO unpublished data cited in Largier et al. 

2010). The decline in adult krill in 2005 may also be related to decreased survival of Chinook 

salmon entering the ocean that year and low salmon returns in 2008. 

Dissolved Oxygen

Areas adjacent to upwelling centers (e.g., Point Arena) are particularly susceptible to low 

dissolved oxygen, as the upwelling process naturally delivers low oxygen water from the deep 

ocean. An extensive Oxygen Minimum Zone (OMZ) exists along the continental margin of the 

northeast Pacific Ocean (Kamykowski and Zentara 1990), although the current source for 

upwelled water is shallower than this zone (Grantham et al. 2004). Recent work indicates that in 

the vicinity of Point Conception, the OMZ has shoaled by up to 90 meters (Bograd et al. 2008). 

87
If the OMZ were to migrate shallow enough to provide the source water for coastal upwelling, 

hypoxic events may be observed with significant and complex ecological changes and impacts 

(Bograd et al. 2008). 

pH 

Feely et al. (2008) show that pH is very low in upwelled waters along the coast of western North 

America, including in this study region. Large-scale increases in CO2 and pH and localized 

upwelling that brings low dissolved oxygen and high CO2 water will likely affect the pelagic 

water column (Vulnerability Assessment Workshop, pers. comm., 2014). Low pH water 

becomes corrosive to a wide variety of organisms, and calcification rates are likely to decline 

(Gazeau et al. 2007). Shell-building pteropods and foraminiferans that form the base of ocean 

food webs will be adversely impacted by increasing acidity (Spero et al. 1997, Fabry et al. 2008). 

Larval and juvenile stages of benthic organisms, which spend the developmental phase of their 

early life history in the water column, may also be impacted by ocean acidification (Kurihara et 

al. 2007). 

II. Sensitivities to disturbance regimes

Disturbance regimes identified: wind and storms 

Overall habitat sensitivity to disturbance regimes: High

• Confidence of workshop participants: High 

Additional participant comments

Wind drives upwelling, with subsequent impacts on ocean temperature, salinity, nutrients, and 

production. 

Supporting literature

Regional models (Snyder et al. 2003, Auad et al. 2006) have found that increased global 

temperatures lead to stronger wind stress along the California Coast, and analysis of wind data in 

the region show an enhancement in alongshore winds between 1982-2007 (Garcia-Reyes and 

Largier 2010), particularly during the summer and early fall. Studies have also observed an 

increase in the occurrence of extreme conditions; for example, extreme wind speeds have 

increased in North Pacific winter cyclones since 1948. Winter storms have also increased in 

intensity since 1950 (Bromirski et al. 2003). Models suggest that the tracks of storms in the 

northeast Pacific will migrate, on average, further north and experience an increase in the 

occurrence of extreme conditions. For example, the likelihood of super El Niños doubles from 

every 20 years in the previous century to one every 10 years in the 21st century (Cai et al. 2013). 

High waves that occur during El Niño events are likely to be more extreme when combined with 

higher sea level and increased wave heights due to climate change. For more on wind, please see 

the Upwelling sections in Sensitivity and Future Climate Exposure. 

88
III. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): harvest (1, moderate), pollution (oil spills 

and dispersants) (1, moderate) 

Overall habitat sensitivity to non-climate stressors: Low

• Confidence of workshop participants: Moderate 

Overall habitat exposure to non-climate stressors: Low

• Confidence of workshop participants: Moderate

Additional participant comments

Due to the offshore nature of this habitat type, and the distance from population centers on the 

mainland, water quality is considered to be in fairly good condition. However, oil spills and 

dispersants are a threat to the health of this ecosystem, and there have been several large spills in 

the region over the last decade.

Supporting literature

Although not identified by workshop participants, invasive species and harmful algal blooms 

may represent additional non-climate threats to the pelagic water column. Shifts in the size, 

frequency, or timing of gelatinous zooplankton blooms in response to climate change have 

become a concern in many coastal marine ecosystems worldwide, as abundant, gelatinous 

zooplankton can induce trophic cascades as well as alter energy flows to upper-level consumers 

(Robinson and Graham 2014). At least one invasive species of gelatinous zooplankton, the moon 

jelly, is found in nearshore and offshore waters of California. Increases in harmful algal blooms 

(HABs) may be an indirect effect of warming ocean temperature (Van Dolah 2005). Currently 

there have been no indications to suggest that water quality in the region is compromised due to 

HABs (ONMS 2009), although with the possible rise in ocean temperature the emergence and 

spread of HABs and other diseases may increase (Largier et al. 2010). 

IV. Other sensitivities

Other critical factors likely to influence the sensitivity of the habitat: noise 

• Confidence of workshop participants: Moderate 

• Confidence of workshop participants in the degree to which these factors influence 

habitat sensitivity: Low

Additional participant comments 

Noise pollution decreases the quality of the habitat for many species. The amount of noise in the 

pelagic water column will likely be impacted by local ocean conditions, such as temperature and 

salinity. Increasing use of the ocean environment will likely result in increased noise in the 

pelagic water column.

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

89
Supporting literature

Around 2,000 large commercial vessels transit through Cordell Bank NMS every year. While 

vessel numbers transiting the sanctuary do not appear to be increasing (1999-2005, United States 

Coast Guard, Automatic Identification System, unpublished data cited in ONMS 2009), it is 

unknown to what extent vessel traffic (including discharge, noise, collision) has on marine 

species or how this has changed through time. Documented ship strikes of humpback, blue and 

fin whales have occurred throughout the coastal waters of California.

Adaptive Capacity

I. Extent, integrity, and continuity

Geographic extent of the habitat: 5 (Transcontinental) 

• Confidence of workshop participants: High 

Structural and functional integrity of habitat: 4 (Minor to moderate alterations)

• Confidence of workshop participants: High 

Continuity of habitat: 5 (Continuous) 

• Confidence of workshop participants: High 

Additional participant comments

Due to its offshore nature, most water quality parameters for the pelagic water column suggest 

relatively good conditions. 

II. Resistance and recovery

Habitat resistance to the impacts of stressors/maladaptive human responses: no answer provided 

Ability of habitat to recover from stressor/maladaptive human response impacts: Moderate-High

• Confidence of workshop participants: High 

III. Habitat diversity

Physical and topographical diversity of the habitat: Low

• Confidence of workshop participants: High 

Diversity of component species within the habitat: Moderate-High

• Confidence of workshop participants: High 

Diversity of functional groups within the habitat: Moderate-High

• Confidence of workshop participants: High 

Keystone or foundational species within the habitat: copepod, krill, and rockfish (bottom-up 

driven system) 

Supporting literature

Diversity in the pelagic water surrounding Cordell Bank as well as the bank itself includes over 

180 species of fish, 28 species of marine mammal, over 50 species of bird, and numerous benthic 

algae and invertebrates (CBNMS 2010). Krill are considered keystone species, and large changes 

in population size are related to changing oceanic conditions. For example, in 2005, anomalous 

90
atmospheric conditions delayed upwelling and affected primary productivity, with subsequent 

impacts on krill population growth and the condition of higher trophic levels dependent upon 

krill (Sydeman et al. 2006, Jahncke et al. 2008). 

IV. Management potential

Value of habitat to people: High

• Confidence of workshop participants: High 

• Description of value: The pelagic water column is valued for its recreational and 

commercial value.

Likelihood of managing or alleviating climate change impacts on habitat: Low

• Confidence of workshop participants: High

• Description of potential management options: It is difficult to manage changes in 

temperature, pH, or upwelling in the pelagic water column, so managers may be better 

able to manage human stressors on this habitat type. 

V. Other adaptive capacities: none identified

Exposure 

I. Future climate exposure6

Future climate and climate-driven factors identified (score7, confidence8): air temperature (5, 

high), sea surface temperature (5, high), dissolved oxygen levels (5, high), ocean pH (5, high), 

upwelling (5, high), altered currents and mixing (5, high), precipitation (2, high), salinity (1, 

high) 

Degree of exposure to future climate and climate-driven factors: Moderate-High

• Confidence of workshop participants: High 

Upwelling

The effect of a long-term increase in upwelling intensity is difficult to predict; increased 

upwelling may mitigate the negative consequences of rising sea surface temperature to some 

extent by cooling surface temperature and increasing productivity in the system. Enhanced 

upwelling that is more persistent may result in a greater but more diffuse supply of 

phytoplankton to waters over the outer shelf and slope; however, enhanced surface heating may 

reduce phytoplankton availability further offshore due to increased stratification (Largier et al. 

2010). Changes in the timing or magnitude of seasonal winds driving coastal upwelling could 

reduce larval survival for many resident species, as a number of offshore benthic organisms that 

live in the California Current have early life histories linked to an annual production cycle driven 

by coastal upwelling. Upwelling that occurs too early in the year or is too intense and lacks in 

periodic relaxation events may disrupt the zooplankton food supply that seabirds rely on. 

Similarly, any significant disruption to the timing or intensity of seasonal upwelling winds 

6 Supporting literature for future exposure to climate factors is provided in the introduction.

7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure. 8 Confidence level indicated by workshop participants.

91
resulting in reduced productivity over time would likely have negative impacts on long-term 

survival of benthic organisms. 

Literature Cited

Abraham, C.L. and W.J. Sydeman. 2004. Ocean climate, euphausiids and auklet nesting: interannual trends and 

variation in phenology, diet and growth of a planktivorous seabird. Marine Ecology Progress Series 274: 

235-50.

Ainley, D.G., W.J. Sydeman, and J. Norton. 1995. Upper trophic level predators indicate interannual negative and 

positive anomalies in the California Current food web. Marine Ecology Progress Series 118: 69-79.

Auad, G., A. Miller, and E. DiLorenzo. 2006. Long-term forecast of oceanic conditions in California and their 

biological implication. Journal of Geophysical Research 111: C09008.

Bindoff, N.L., J. Willebrand, V. Artale, A. Cazenave, J. Gregory, S. Gulev, K. Hanawa, C. Le Quere, S. Levitus, Y. 

Nojiri, C.K. Shum, L.D. Talley, and A. Unnikrishnan. 2007. Observations: Oceanic Climate Change and 

Sea Level. In: Climate Change 2007: The Physical Science Basis. Contribution of Working Group I to the 

Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Solomon, S., D. Qin, M. 

Manning, Z. Chen, M. Marquis, K.B. Averyt, M. Tignor, and H.L. Miller, eds. Cambridge University 

Press, Cambridge, UK.

Bograd, S., C. Castro, E. DiLorenzo, D. Palacios, H. Bailey, W. Gilly, and F. Chavez. 2008. Oxygen declines and 

the shoaling of the hypoxic boundary in the California Current. Geophysical Research Letters 35: L12607.

Brodeur, R.D. and M. Terazaki. 1999. Springtime abundance of chaetognaths in the shelf region of the northern 

Gulf of Alaska, with observations on the vertical distribution and feeding of Sagitta elegans. Fisheries 

Oceanography 8: 93-103.

Bromirski, P.D., R.E. Flick, and D.R. Cayan. 2003. Storminess variability along the California coast: 1858-2000. 

Journal of Climate 16: 982-93.

Cai, W. S. Borlace, M. Lengaigne, P. van Rensch, M. Collins, G. Vecchi, A. Timmermann A. Santoso, M.J. 

McPhaden, L. Wu, M.H. England, G. Wang, E. Guilyardi, and F. Jin. 2013. Increasing Frequency of 

Extreme El Niño Events Due to Greenhouse Warming. Nature Climate Change 4: 111-16. 

Cordell Bank National Marine Sanctuary (CBNMS). 2010. About the Sanctuary. Accessed March 13, 2015 from:

http://cordellbank.noaa.gov/about/welcome.html. 

Doney, S. C., V. J. Fabry, R. A. Feely, and J. A. Kleypas. 2009. Ocean acidification: The other CO2 problem. 

Annual Review of Marine Science 1:169-192. 

Fabry, V.J., B.A. Seibel, R.A. Feely, and J.C. Orr. 2008. Impacts of ocean acidification on marine fauna and 

ecosystem processes. ICES Journal of Marine Science 64: 414-432.

Feely, R.A., C.L. Sabine, J.M. Hernandez-Ayon, D. Ianson, and B. Hales. 2008. Evidence for upwelling of corrosive 

"acidified" seawater onto the continental shelf. Science 320: 1490.

Garcia-Reyes, M. and J. Largier. 2010. Observations of increased wind-driven coastal upwelling off central 

California. Journal of Geophysical Research: Oceans (1978–2012) 115: C4. 

Gazeau, F., C. Quiblier, J.M. Jansen, J. Gattuso, J.J. Middelburg, and C.H.R. Heip. 2007. Impact of elevated CO2 on 

shellfish calcification. Geophysical Research Letters 34: L07603.

Grantham, B.A., F. Chan, K.J. Nielsen, D.S. Fox, J.A. Barth, A. Huyer, J. Lubchenco, and B.A. Menge. 2004. 

Upwelling-driven nearshore hypoxia signals ecosystem and oceanographic changes in the northeast 

Pacific. Nature 429: 749-54.

Intergovernmental Panel on Climate Change (IPCC). 2007. Summary for Policymakers. In: Climate Change 2007: 

The Physical Science Basis. Contribution of Working Group I to the Fourth Assessment Report of the 

Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK.

Jahncke, J. B.L. Saenz, C.L. Abraham, C. Rintoul, R.W. Bradley, and W.J. Sydeman. 2008. Ecosystem responses to 

short-term climate variability in the Gulf of the Farallones, California. Progress in Oceanography 77: 182-

193.

Kamykowski, D.Z. and S.J. Zentara. 1990. Hypoxia in the world ocean as recorded in the historical data set. DeepSea Research 37: 1861-74.

Keister, J.E., and P.T. Strub. 2008. Spatial and interannual variability in mesoscale circulation in the northern 

California Current System. Journal of Geophysical Research-Oceans 113. 

Kurihara, H., S. Kato, and A. Ishimatsu. 2007. Effects of increased seawater pCO2 on early development of the 

92
oyster Crassostrea gigas. Aquatic Biology 1: 91-98.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine SanctuariesAdvisory Councils. 121pp. 

Levitus, S., J.I. Antonov, T.P. Boyer, and C. Stephens. 2000. Warming of the world ocean. Science 287: 2225-29.

Mendelssohn, R. and F.B. Schwing. 2002. Common and uncommon trends in SST and wind stress in California and 

Peru-Chile current systems. Progress in Oceanography 53:141-62. 

Mendelssohn, R., F.B. Schwing, and S.J. Bograd. 2003. Spatial structure of subsurface temperature variability in the 

California Current, 1950–1993. Journal of Geophysical Research 108 (C3): 3093.

Office of National Marine Sanctuaries (ONMS). 2009. Cordell Bank National Marine Sanctuary (CBNMS) 

Condition Report 2009. US Department of Commerce, National Oceanic and Atmospheric Administration, 

Office of National Marine Sanctuaries, Silver Spring, MD, USA.

Palacios, D.M., S.J. Bograd, R. Mendelssohn, F.B. Schwing. 2004. Long-term and seasonal trends in stratification in 

the California Current, 1950-1993. Journal of Geophysical Research 109.

Robinson, K.L. and W.M. Graham. 2014. Warming of subtropical coastal waters accelerates Mnemiopsis leidyi 

growth and alters timing of spring ctenophore blooms. Marine Ecology Progress Series 502: 105-115.

Roemmich, D. and J. McGowan. 1995. Climatic warming and the decline of zooplankton in the California Current. 

Science 267: 1324-26.

Spero, H., J. Bijma, D.W. Lea, E.B. Bemis. 1997. Seawater carbonate chemistry and carbon and oxygen isotopes 

during experiments with planktonic foraminifera Orbulina universa and Globigerina bulloides, 1997. 

doi:10.1594/PANGAEA.721923. 

Snyder, M.A., L.C. Sloan, N.S. Diffenbaugh, and J.L. Bell. 2003. Future climate change and upwelling in the 

California Current. Geophysical Research Letters 30: 1-4.

Sydeman, W.J., R.W. Bradley, P. Warzybok, C.L. Abraham, J. Jahncke, K.D. Hyrenbach, V. Kousky, J.M. Hipfner,

and M.D. Ohman. 2006. Planktivorous auklet Ptychoramphus aleuticus responses to ocean climate, 2005: 

unusual atmospheric blocking? Geophysical Research Letters 33 L22S09.

Van Dolah, F.M. 2005. Effects of harmful algal blooms. In: J. Reynolds III, W.F. Perrin, R.R. Reeves, S. 

Montgomery, and T.J. Ragen. Marine Mammal Research: Conservation beyond crisis. John Hopkins 

University Press, Baltimore, MD, USA.

93
Rocky Intertidal1

Executive Summary The rocky intertidal habitat consists of 

rocky substrate found between high and 

low tide water levels. This habitat has a 

transcontinental geographic extent, is 

moderately continuous throughout the 

study region, and is considered to be in 

relatively pristine condition by workshop participants. Key climate sensitivities identified for 

this habitat by workshop participants includes air temperature, salinity, wave action, pH, and 

erosion. Key non-climate sensitivities include armoring, pollution/oil spills, 

recreation/trampling, and invasive species/species range expansions. Rocky intertidal habitat is 

widespread, continuous, and a dominant feature of the study region, composing 39% of the 

shoreline. This system generally displays high recovery potential, in part due to species’ short 

lifespans and high fecundity, as well as high species diversity, due to the diversity in substrate 

type. Community dynamics are dependent on the abundance, distribution, and interactions of the 

California mussel (Mytilus californianus) and the ochre sea star (Pisaster ochraceus). 

Management potential is considered low due to the inability to prevent climate impacts from 

affecting the habitat. However, societal value for this habitat is considered high due to its 

importance in research, recreation, and harvest. 

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): air temperature (5, high), 

salinity (5, moderate), pH (4, low-moderate), wave action (5, high), coastal erosion (4, lowmoderate) sea surface temperature (3, low-moderate), sea level rise (3, moderate-high), dynamic 

ocean conditions (currents/mixing/stratification) (3, low), precipitation (2, low), dissolved 

oxygen levels (2, low-moderate)

Climate and climate-driven changes that may benefit the habitat: none 

Overall habitat sensitivity to climate and climate-driven factors: Moderate-High

• Confidence of workshop participants: Moderate 

Additional participant comments

Intertidal zonation plays a role in the degree of sensitivity experienced; lower intertidal areas are 

not as adapted to variation in physical factors as compared to higher intertidal areas, though the 

high intertidal will be expected to encounter more extremes.

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Rocky Intertidal Score Confidence

Sensitivity 4 Moderate-High 2 Moderate

Exposure 4 Moderate-High 2 Moderate

Adaptive Capacity 4 Moderate-High 2 Moderate

Vulnerability 3 Moderate 2 Moderate

94
Supporting literature

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. 

Air Temperature

Most rocky intertidal organisms are ectothermic, and therefore sensitive to changes in air and 

water temperature (Largier et al. 2010). As extreme heat events are expected to increase along 

California’s coast (Ekstrom and Moser 2012), many organisms may be negatively impacted by 

heat stress and surpass critical lethal high body temperatures, such as the California mussel 

(Mytilus californianus) (Mislan et al. 2014). Entire intertidal areas may more frequently 

experience mass mortality events (as documented in the Bodega Marine Reserve, Harley 2008). 

These effects will likely not be consistent across the boundaries of the habitat, as organisms in 

more northerly latitudes and higher in the intertidal zone have been documented to show greater 

sensitivity (Gilman et al. 2006). 

Salinity

Salinity plays a strong role in rocky intertidal tide pools and is directly influenced by changes in 

precipitation patterns. Extreme high salinities can occur during low tides that coincide with high 

temperatures, enhancing evaporation rates. Conversely, extreme precipitation events may cause 

a sudden decrease in salinity for exposed tidal organisms. Studies on the effect of salinity 

extremes (both high and low) indicate that, when combined with temperature stress, salinity can 

negatively impact rocky intertidal invertebrates through increased embryonic mortality 

(Przeslawski 2005, Deschaseaux 2009) and decreased adult aerobic performance (Vajed Samiei 

2011). 

pH 

The effects of decreased pH on intertidal habitat will likely be felt most strongly during 

upwelling events that bring cold and deep water to the surface (Feely et al. 2008). This water is 

undersaturated in aragonite, and may impede the ability of calcifying organisms to build calcium 

carbonate shells, and potentially result in the dissolution of existing shells (Largier et al. 2010). 

Many studies have shown this effect on intertidal organisms, including the California mussel, 

which precipitated weaker, thinner and smaller shells under projected 2100 CO2 concentrations 

(Gaylord et al. 2011) and coralline algae, which demonstrated decreased recruitment and growth 

under more acidic conditions (Kuffner et al. 2008). 

Wave Action and Erosion 

Projected increase in storm activity suggests that intertidal organisms will experience more 

frequent and more intense physical forces due to wave action (Largier et al. 2010). Wave action 

can result in varying effects, from the selective removal of larger intertidal organisms, which 

may influence size structure and species interactions (Largier et al. 2010), to increased coastal 

erosion that may result in the burying of intertidal habitat (Vulnerability Assessment Workshop, 

pers. comm., 2014). Coastal cliff and bluff erosion may also impede the ability of intertidal 

organisms to migrate inland in response to rising sea levels (Largier et al. 2010).

95
II. Sensitivities to disturbance regimes

Disturbance regimes identified: wind, storms, disease, flooding, and extreme heat events 

Overall habitat sensitivity to disturbance regimes: High

• Confidence of workshop participants: Moderate 

Supporting literature

Wind is highly desiccating to intertidal organisms and can dry out species that need to retain 

moisture for survival, enhancing the negative impact of increased air temperature (Bell 1995). 

Storms increase physical forces through enhanced wave exposure and increased erosion of 

coastal cliffs that can bury intertidal habitats (see wave action section above). Flooding may 

have a similar effect by increasing sedimentation to the intertidal area, but may also result in 

compromised water quality (PISCO 2014), including an increase in harmful algal bloom events. 

Disease has the potential to greatly impact key species within the intertidal habitat, as 

demonstrated by the sea star wasting syndrome and the black abalone withering foot syndrome 

(Vulnerability Assessment Workshop, pers. comm., 2014). Increase in disease is often linked to 

increase in water temperature, as both pathogen survival and host susceptibility are enhanced 

(Friedman et al. 1997, Harvell et al. 1999, Raimondi et al. 2002, Largier et al. 2010). Extreme 

heat events can result in mass mortality of intertidal organisms (see air temperature section 

above). 

III. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): armoring (4, moderate), pollution/oil 

spills (4, low), recreation (4, low-moderate), invasive species (4, low), and boat groundings (3, 

low-moderate), land use change (3, low), harvest (3, low) 

Overall habitat sensitivity to non-climate stressors: Moderate-High

• Confidence of workshop participants: Low

Overall habitat exposure to non-climate stressors: Moderate-High

• Confidence of workshop participants: Moderate 

Additional participant comments

Coastal armoring limits the ability of intertidal habitat to migrate upland or inland with rising sea 

level, but can also enhance intertidal areas by creating additional hard substrate. Oil can inhibit 

the resilience of rocky intertidal habitat and can smother and kill intertidal organisms, including 

mussels, acorn barnacles, limpets and other species. These effects are highly localized – near San 

Francisco Bay, Pillar Point Harbor, and Bodega Harbor. Trampling of the intertidal system by 

recreational users, researchers and harvesters is a documented negative stressor. Land-use 

change alters run-off and sediment supply to intertidal areas. Boat groundings are highly 

localized events that can cause significant damage to the habitat.

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

96
Supporting literature

Non-climate stressors will likely exacerbate the impacts of climate-driven stressors by reducing 

the resiliency of the rocky intertidal habitat – the ability to absorb and respond to perturbations – 

and enhancing vulnerability (Largier et al. 2010). 

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. 

Armoring

The impact of coastal armoring on rocky intertidal habitat depends on the specific armoring 

structure utilized. As sea level rises and increasing coastal erosion threaten the coastal cliffs and 

bluffs along California’s shoreline, bluff revetments and coastal armoring will be more 

frequently used, effectively prohibiting upland migration of the habitat (Largier et al. 2010). 

Pollution and oil spills

Pollutants, including agricultural and livestock waste, wastewater, sewage outfalls, historic 

mining, and industrial wastes, can be carried into the study region via the freshwater outflow 

from San Francisco Bay (Largier et al. 2010), inhibiting the resilience of intertidal habitat and 

stimulating phytoplankton growth. This habitat is also sensitive to oil spills, with over 6,000 

commercial vessels using the San Francisco Bay every year (Largier et al. 2010). 

Recreation and trampling 

The high visitation levels that occur in the rocky intertidal habitat (including Pillar Point, 

Duxbury Reef, Pescadero Point and Salt Point) can cause crushing of organisms and changes in 

the diversity and abundance of organisms (Largier et al. 2010). 

Invasive species and species range expansions

Invasive species effectively out-compete native species and decrease native species diversity and 

abundance. These impacts are more largely felt near harbors, including San Francisco Bay, 

Pillar Point Harbor, and Bodega Harbor. To date, almost 150 species of introduced marine algae 

and animals have been identified in the study region. Invasive species threaten the abundance 

and/or diversity of native species, disrupt ecosystem balance and threaten local marine-based 

economies (SIMoN 2014b). Climate change is likely to enhance the negative impacts of coastal 

invaders. Stachowicz et al. (2002) documented earlier and greater recruitment of invasive 

tunicates as well as increased growth under warmer sea surface temperatures, and predicted that 

increasing temperatures will ultimately lead to more successful invasive species. Species range 

expansions have also been documented for coastal California, likely due to increasing sea surface 

temperature. In Monterey over a 60-year period, Barry et al. (1995) documented an increase in 

abundance of 10 to 11 Southern species and a decrease in 5 to 7 Northern species. Connolly and 

Roughgarden (1998) documented a northward range expansion of 300 km (from San Francisco 

to Cape Mendocino) by volcano barnacles (Tetraclita rubescens), a common intertidal species.

IV. Other sensitivities: none identified 

97
Adaptive Capacity

I. Extent, integrity, and continuity

Geographic extent of the habitat: 5 (Transcontinental)

• Confidence of workshop participants: High 

Structural and functional integrity of habitat: 5 (Pristine)

• Confidence of workshop participants: High 

Continuity of habitat: 3 (Patchy across an area with some connectivity among patches) 

• Confidence of workshop participants: High 

Supporting literature

Rocky intertidal habitat accounts for 39% of the shoreline in the southern portion of the study 

region (SIMoN 2014a), and is a dominant feature along the coastline. Intertidal habitat is 

interrupted by coastal cliffs, sandy beaches, and estuaries and lagoons but biologically connected 

through larval transport (SIMoN 2014b). Rocky shore habitat within the study region includes 

areas such as Bodega Head, Duxbury Reef, the Point Reyes Headlands, the rocky shores of 

Tomales Bay and the intertidal shores of the Farallon Islands (SIMoN 2014b). 

II. Resistance and recovery

Habitat resistance to the impacts of stressors/maladaptive human responses: Low-Moderate

• Confidence of workshop participants: Moderate

Ability of habitat to recover from stressor/maladaptive human response impacts: High

• Confidence of workshop participants: High 

Additional participant comments

High recovery potential may be attributed to the species’ far-reaching dispersal capabilities, short 

generation times, short lifespans and high fecundity. 

Supporting literature

A recovery study of four intertidal assemblages along the California coast demonstrated that the 

fastest recovery rate occurred in zones dominated by short-lived species (Conway-Cranos 2009). 

III. Habitat diversity

Physical and topographical diversity of the habitat: Moderate-High

• Confidence of workshop participants: High 

Diversity of component species within the habitat: High

• Confidence of workshop participants: High

Diversity of functional groups within the habitat: High

• Confidence of workshop participants: High 

Keystone or foundational species within the habitat: California mussel and ochre sea star

98
Additional participant comments

Other diversity factors that impact species diversity include zonation, rock type, rugosity, and 

wave action – all of these factors have diverse outcomes and diverse associated communities. 

Supporting literature

More than 320 invertebrate species and 250 algal species have been identified by various surveys 

and monitoring programs in the southern portion of the study region’s boundaries. High species 

diversity in the rocky intertidal in this region may be attributed, in part, to “the unusual mix of 

substrate – such as the soft shale at Duxbury Reef and hard shale at Estero de San Antonio – and 

the alternating estuaries and lagoons that line the sanctuary's shores” (SIMoN 2014b). 

Rocky intertidal habitat is dependent on the abundance, distribution, and interactions of the 

California mussel, Mytilus californianus, and ochre sea star, Pisaster ochraceus . P. ochraceus

has long been considered a keystone species in the rocky intertidal system that exerts great 

predator influence, especially on its primary food source, the California mussel (Paine 1966, 

Menge et al. 2004) by setting the lower limit of mussel beds. Paine (1966) concluded that 

predation by P. ochraceus facilitates species coexistence among competitors and sets the 

biological zonation in the rocky intertidal by maintaining a diversity of molluscs (e.g., mussels), 

crustaceans (e.g., barnacles), and cnidarians (e.g., sea anemone) in coastal intertidal 

communities. With P. ochraceus present, mussels dominate the higher zone, and a diversity of 

invertebrates dominates the middle zone. When P. ochraceus are removed, mussels expand into 

the middle zone and out-compete the other invertebrate species.

IV. Management potential

Value of habitat to people: Moderate-High

• Confidence of workshop participants: Low-Moderate 

• Description of value: Rocky intertidal habitat has a moderate value to the general public 

for its aesthetics and recreational opportunities, high value to researchers in studying 

ecological relationships, zonation, community dynamics, and many other tenants of 

ecology, and is valued by resource managers for the shoreline protection the habitat 

provides. 

Likelihood of managing or alleviating climate change impacts on habitat: Low-Moderate

• Confidence of workshop participants: High 

• Description of potential management options: The challenge lies in the inability to 

prevent many climate impacts from occurring (e.g., increasing air temperature and wave 

exposure) or to enhance the habitat’s ability to respond to potential impacts. Managers 

may be able to protect and make room for inland/upland migration by limiting 

development, and areas that receive high visitation could be surrounded by protected 

areas that can serve as a source of species propagules.

V. Other adaptive capacities: none identified 

99
Exposure 

I. Future climate exposure6

Future climate and climate-driven factors identified (score7, confidence8): changes in air 

temperature (5, high), changes in precipitation (5, high), changes in salinity (5, moderate), 

changes in sea surface temperature (5, moderate-high), decreased pH (5, high), sea level rise (5, 

high), altered currents and mixing (4, low-moderate), increased coastal erosion and runoff (3, 

moderate), increased flooding (3, moderate), increased storminess (3, moderate), decreased 

dissolved oxygen(2, low) 

Degree of exposure to future climate and climate-driven factors: Moderate-High

• Confidence of workshop participants: Moderate 

Literature Cited

Barry, J.P., C.H. Baxter, R.D. Sagarin and S.E. Gilman. 1995. Climate-related, long-term faunal changes in a 

California rocky intertidal community. Science 267:672-675. 

Bell, E.C. 1995. Environmental and morphological influences on thallus temperature and desiccation of the 

intertidal alga Mastocarpus papillatus Kutzing. JEMBE 191: 29-55.

California Energy Commission. 2006. Our Changing Climate: Assessing the Risks to California. CEC-500-2006- 

077, 16pp. 

Connolly, S.R. and J. Roughgarden. 1998. A range extension for the volcano barnacle, Tetraclita rubescens. 

California Fish and Game 84:182-183. 

Conway-Cranos, L. 2009. Recovery dynamics in rocky intertidal communities: Patterns, mechanisms and 

simulations. Dissertation: University of California, Santa Cruz.

Department of Water Resources (DWR). 2006. Progress on Incorporating Climate Change into Planning and 

Management of California’s Water Resources. Technical Memorandum Report. Sacramento, California. 

http://baydeltaoffice.water.ca.gov/climatechange/reports.cfm

Deschaseaux, E.S.M. , A.M. Taylor, W.A. Maher, A.R. Davis. 2009. Cellular responses of encapsulated gastropod 

embryos to multiple stressors associated with climate change. JEMBE 383(2):130-136.

Doney, S. C., V. J. Fabry, R. A. Feely, and J. A. Kleypas. 2009. Ocean acidification: The other CO2 problem. 

Annual Review of Marine Science 1:169-192

Ekstrom, J. A. and S. C. Moser. 2012. Climate Change Impacts, Vulnerabilities and Adaptation in San Francisco 

Bay: Synthesis. PIER Research Report, Sacramento, Publication # CEC-500-2012-071, 65pp. 

Feely, R.A., C.L. Sabine, J.M. Hernandez-Ayon, D. Ianson, and B. Hales. 2008. Evidence for upwelling of corrosive 

"acidified" seawater onto the continental shelf. Science 320, 1490 DOI: 10.1126/science.1155676. 

Friedman, C.S., M. Thomson, C. Chun, P.L. Haaker and R.P. Hedrick. 1997. Withering syndrome of the black 

abalone, Haliotis cracherodii (Leach): Water temperature, food availability, and parasite as possible causes. 

Journal of Shellfish Research 16:403-411.

Garcia-Reyes, M. and J. Largier. 2010. Observations of increased wind-driven coastal upwelling off central 

California. Journal of Geophysical Research: Oceans (1978–2012) 115: C4.

Gaylord,B., T.M. Hill, E. Sanford, E.A. Lenz, L.A. Jacobs, K.N.,Sato, A.D. Russell and A. Hettinger. 2011. 

Functional Impacts of ocean acidification in an ecologically critical foundation species. The Journal of 

Experimental Biology 214:2586-2594.

Gilman, S. E., D. S. Wethey, and B. Helmuth. 2006. Variation in the sensitivity of organismal body temperature to 

climate change over local and geographic scales. Proceedings of the National Academy of Sciences 

103:9560-9565. 

Groisman, P., R. Knight and T. Karl. 2001. Heavy precipitation and high streamflow in the contiguous United 

6 Supporting literature for future exposure to climate factors is provided in the introduction. 7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

100
States: trends in the 20th century. Bulletin of the American Meteorological Society 82: 219-246.

Harley, C. D. G. 2008. Tidal dynamics, topographic orientation, and temperature-mediated mass mortalities on 

rocky shores. Marine Ecology-Progress Series 371:37-46.

Harvell, C.D., K. Kim, J.M. Burkholder, R.R. Colwell, P.R. Epstein, D.J. Grimes, E.E. Hofmann, E.K. Lipp, 

A.D.M.E. Osterhaus, R.M. Overstreet, J.W. Porter, G.W. Smith and G.R. Vasta. 1999. Emerging marine 

diseases – climate links and anthropogenic factors. Science 285:1505-1510. 

International Panel on Climate Change (IPCC). 2007b. Summary for Policymakers. In: Climate Change 2007: 

Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report 

of the Intergovernmental Panel on Climate Change. Parry M.L., O.F. Canziani, J.P. Palutikof, P.J. van der 

Linden and C.E. Hanson (Eds.), Cambridge University Press, Cambridge, UK, 7-22.

Johnstone, J.A. and T.E. Dawson. 2010. Climate context and ecological implications of summer fog decline in the 

coast redwood region. Proceedings of the National Academy of Sciences, USA 107: 4533 – 4538. 

Kim, J., Kim, T., Arritt, R. and N. Miller. 2002. Impacts of increased atmospheric CO2 on the Hydroclimate of the 

Western United States. Journal of Climate 15: 1926-1943

Kuffner, I.B., A.J. Andersson, P.L. Jokiel, K.S. Rodgers and F.T. Mackenzie. 2008. Decreased abundance of 

crustose coralline algae due to ocean acidification. Nature Geoscience 1:114-117.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine SanctuariesAdvisory Councils. 121pp. 

Lebassi, B., J. Gonzalez, D. Fabris, E. Maurer, N. Miller, C. Milesi, P. Switzer, and R. Bornstein. 2009. Observed 

1948-2005 Cooling of summer daytime temperatures in coastal California. Journal of Climate 22:3558-

3573. 

Mendelssohn, R., F.B. Schwing, and S.J. Bograd. 2003. Spatial structure of subsurface temperature variability in the 

California Current, 1950–1993. Journal of Geophysical Research 108 (C3): 3093. 

Mendelssohn, R. and F.B. Schwing. 2002. Common and uncommon trends in SST and wind stress in California and 

Peru-Chile current systems. Progress in Oceanography 53. p.141-162. 

Menge, B.A., C. Blanchette, P. Raimondi, T. Freidenburg, S. Gaines, J. Lubchenco, D. Lohse, G. Hudson, M. Foley 

and J. Pamplin. 2004. Species interaction strength: testing model predictions along an upwelling gradient. 

Ecological Monographs 74:663-684. 

Mislan, K.A.S., B. Helmuth and D.S. Wethey. 2014. Geographical variation in climatic sensitivity of

intertidal mussel zonation. Global Ecology and Biogeography. doi:10.1111/geb.12160.

Mote, P.W., A.F. Hamlet, M.P. Clark, D.P. Lettenmaier. 2005. Declining mountain snowpack in western North 

America. Bulletin of the American Meteorological Society 86:39-49. 

National Research Council. 2012. Sea-Level Rise for the Coasts of California, Oregon, and Washington: Past, 

Present, and Future. Washington, DC: The National Academies Press.

NOAA Coastal Services Center. 2009. Local Strategies for Addressing Climate Change. 

https://coast.noaa.gov/magazine/climatechangestrategies.pdf?redirect=301ocm. 

Paine, R. T. 1966. "Food Web Complexity and Species Diversity". The American Naturalist 100 (910): 65–75.

Przeslawski, R., Davis, A. R. and Benkendorff, K. (2005), Synergistic effects associated with climate change and the 

development of rocky shore molluscs. Global Change Biology, 11: 515–522. doi: 10.1111/j.1365- 

2486.2005.00918.x

Raimondi, P. T., C. M. Wilson, R. F. Ambrose, J. M. Engle, and T. E. Minchinton. 2002. Continued declines of 

black abalone along the coast of California: are mass mortalities related to El Niño events? Marine 

Ecology Progress Series 242:143-152.

Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO): Rocky Shores. 2014. Retrieved June 18, 2014 

from http://www.piscoweb.org/research/rocky-shores. 

Sanctuary Integrated Monitoring Network (SIMoN). 2014a. Rocky Shores: Monterey Bay National Marine 

Sanctuary. Retrieved June 18, 2014 from: 

http://sanctuarysimon.org/monterey/sections/rockyShores/overview.php

Sanctuary Integrated Monitoring Network (SIMoN). 2014b. Rocky Shores: Gulf of the Farallones National Marine 

Sanctuary. Retrieved June 18, 2014, from: 

http://sanctuarysimon.org/farallones/sections/rockyShores/overview.php. 

Snyder, M., Bell, J., Sloan, L., Duffy, P. and B. Govindasamy. 2002. Climate responses to a doubling of 

atmospheric carbon dioxide for a climatically vulnerable region. Geophysical Research Letters 29(11): 

10.1029/2001GL014431. 

Stachowicz, J.J., J.R. Terwin, R.B. Whitlatch and R.W. Osman. 2002. Linking climate change and biological 

101
invasions: ocean warming facilitates non-indigenous species invasion. Proceedings of the National 

Academy of Sciences 99: 15497–15500. 

Vajed Samiei, J., Novio Liñares, J.A., Abtahi, B. 2011. The Antagonistic Effect of Raised Salinity on the Aerobic 

Performance of a Rocky Intertidal Gastropod Nassariusdeshayesianus (Issel, 1866) Exposed to Raised 

Water Temperature. Journal of the Persian Gulf 2(6): 29-36.

102
American Dune Grass (Elymus mollis)1

Executive Summary American dune grass is a 

rhizomatous perennial that is an 

important pioneer and sand 

stabilizing species in dune habitats 

along the United States and 

Canadian Pacific coasts. Key climate sensitivities identified by workshop participants include 

sea level rise, wave action, coastal erosion and sediment supply and key non-climate sensitivities

include roads/armoring, recreation, and invasive species. American dune grass exhibits a broad 

geographic extent, and a stable but diminished population that is fragmented. Overall, the 

species has low-moderate diversity/plasticity, though it is known to hybridize with other species, 

employs both sexual and asexual reproduction, and displays variable ecophysiological 

phenotypes based on environmental variability. Value for this species is generally low, with 

some preference given to the more effective sand-stabilizing invasive beach grass, and 

management potential is moderate, with invasive removal and upland habitat protection as viable 

options. The greatest threat to American dune grass is the invasive European beach grass, and 

dunes that are dominated by native, rather than invasive, species, including American dune grass, 

will likely be more resilient to climate impacts. 

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): sea level rise (4, high), 

wave action (4, high), sediment supply (4, high), coastal erosion (4, high), precipitation (2, 

moderate), air temperature (1, low) 

Climate and climate-driven changes that may benefit the species: none identified

Overall species sensitivity to climate and climate-driven factors: Moderate

• Confidence of workshop participants: High 

Additional participant comments

The sensitivity of dune grass to climate factors is primarily due to the sensitivity of the dune 

habitat; however, if there is sufficient room to migrate inland, the species may be able to adapt 

and persist. Potential areas of refugia from climate impacts include seeps and drainages in 

coastal bluffs behind dunes, and moist hollows on sloping terraces (Peter Baye, pers. comm., 

2014).

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

American Dune Grass Score Confidence 

Sensitivity 4 Moderate-High 3 High

Exposure 5 High 3 High

Adaptive Capacity 2 Low-Moderate 2 Moderate

Vulnerability 4 Moderate-High 3 High

103
Supporting literature

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should be considered. 

Sea Level Rise

Sea level rise can inundate dune systems and increase rates of shoreline erosion, potentially 

forcing upland retreat of beach and dune habitats (Feagin et al. 2005). Where development or 

other barriers (i.e., cliffs) block upland retreat, dune habitats may suffer reduced areal extent 

and/or increased fragmentation, shifting from continuous habitat to narrower, steeper, and 

isolated pockets (Largier et al. 2010). In addition, sea level rise can contribute to changes in 

relative proportions of the different ecological zones within dune habitats, which could lead to 

propagating changes in all levels of the food web (Dugan et al. 2008). In a high sea level rise 

scenario of 0.88m, complete breakdown of the dune plant successional process occurred in an 

experimental plot in Texas, with only early colonizers able to take root but not able to provide 

enough ameliorative force for the further development of the plant community, indicating that 

sea level rise may disrupt successional dynamics and degrade habitat quality by preventing the 

formation of mature coastal dune vegetation communities (Feagin et al. 2005). 

Wave Action

Wave action, which varies seasonally and according to local and more broad-scale climatic 

processes, shapes dune systems, contributes to dune erosion, and affects key species. Waves, 

particularly larger wave heights associated with late winter El Niño events, are often the main 

driver of beach and dune erosion (Storlazzi and Griggs 2000, Wingfield and Storlazzi 2007), 

increase coastal flooding (Storlazzi and Griggs 2000, Wingfield and Storlazzi 2007), potentially 

inundating dune areas and forcing landward retreat (Feagin et al. 2005), and shift distributions of 

sandy shorelines. For example, shifts in the Pacific Decadal Oscillation (PDO) can alter wave 

directions, exposing sheltered beaches and dunes to significant erosion and/or rotating sandy 

shoreline segments to the north and increasing erosion in southern ends of littoral cells (Sallenger 

et al. 2002). 

Coastal Erosion 

American dune grass is an important part of dune ecology, as it is often one of the first plants to 

colonize during the early stages of dune development (Imbert and Houle 2000) and is an 

important sand stabilizer due to its rhizomatous growth, preventing erosion of coastal dunes 

(Gagné and Houle 2002). The invasive European beach grass, which is now more abundant, is 

also an effective sand stabilizer, but forms tall dunes that prevent inland movement of sand, 

potentially exacerbating coastal erosion and preventing the inland movement of dunes in 

response to sea level rise (UW 2013). Erosion combined with sea level rise will likely reduce 

dune habitat, especially in areas where dunes are backed by coastal cliffs (i.e., a majority of 

beaches in the study area) (Largier et al. 2010). Alternatively, erosion of coastal cliffs may help 

some beach and dune systems keep pace with sea level rise by increasing local sediment delivery 

and enhancing dune habitat (Sarah Allen, pers. comm., 2014). In addition, erosion of upland or 

inland sediments can increase sediment transport and delivery to beach and dune areas (Sarah 

Allen, pers. comm., 2014). 

Sediment Supply

Sediment supply and movement influences the areal extent of dune systems, and is controlled by 

a variety of climate and climate-driven factors (i.e., wave action, coastal erosion, currents, 

104
precipitation), as well as by changes within the “sediment-shed” (i.e., changes in the watershed, 

coastal wetlands, or the littoral cell) (Revell et al. 2007, Largier et al. 2010, Vulnerability 

Assessment Workshop, pers. comm., 2014). Surpluses in local sediment budgets typically 

increase beach and dune width and minimize shoreline erosion, while sediment deficits result in 

narrower beaches and dunes with significant rates of coastal erosion (Largier et al. 2010). 

Reductions in beach width expose dune habitats to increased wave exposure (Largier et al. 

2010). Sediment supply will vary according to many factors. For example, short, heavy 

precipitation events can increase freshwater sediment discharge and bolster beach and dune 

systems, though this dynamic is mediated by inland water and sediment retention structures such 

as dams (Slagel and Griggs 2008, Largier et al. 2010). Alternatively, wave action can deliver or 

remove sediment, leading to dynamic changes in beach shape and size over the course of 

different seasons. 

II. Sensitivities to disturbance regimes

Disturbance regimes identified: storms

Overall species sensitivity to disturbance regimes: Moderate

• Confidence of workshop participants: Moderate 

Additional participant comments

Although storms can damage the structure of dune habitats, they can quickly recover. 

III. Dependencies

Species dependence on one or more sensitive habitat types: High

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: dunes 

Species dependence on specific prey or forage species: low 

• Confidence of workshop participants: High

Other critical dependencies: sediment supply to keep pace with sea level rise 

• Degree of dependence: High 

• Confidence of workshop participants: Moderate 

Specialization of species (1=generalist; 5=specialist): 5

• Confidence of workshop participants: High

Supporting literature

The species may also be somewhat dependent on restoration efforts due to its inability to 

compete with the invasive European beach grass (Bennett 2005). Because of these generally high

dependencies, this species is considered a specialist, and therefore may have limited flexibility to 

adapt to environmental changes. 

105
IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): invasive species (5, high), coastal 

roads/armoring (4, high), recreation (3, moderate) 

Overall species sensitivity to non-climate stressors: Moderate-High

• Confidence of workshop participants: High 

Overall species exposure to non-climate stressors: Moderate-High

• Confidence of workshop participants: High

Additional participant comments

Coastal roads and armoring can prevent the migration of American dune grass in response to 

rising sea levels, and invasive species may be able to spread faster in new dune habitat areas.

Coastal recreational pressure could increase as a result of population growth and increased inland 

temperatures. European beach grass is more aggressive and dominant, and therefore is able to 

spread faster and colonize new areas more quickly than American dune grass. 

Supporting literature

Invasive Species

The invasive European beach grass, which is now the most abundant dune grass species (Pojar 

and MacKinnon 1994), is considered the most pervasive exotic species currently threatening 

coastal dunes (Pickart 1997). European beach grass was first planted in California in the 1800s 

for sand stabilization purposes (Bennett 2005), and was generally preferred by nearby 

landowners because it is more efficient than native species at effectively trapping shifting sands 

(Vulnerability Assessment Workshop, pers. comm., 2014), though this preference has recently 

declined (Peter Baye, pers. comm., 2014). However, the efficient trapping of sand by European 

beach grass significantly alters dune morphology, threatening the federally listed Western Snowy 

Plover and displacing entire native plant communities, including the American dune grass 

(Pickart 1997, Bennett 2005). Dunes become very tall (up to 10m) when colonized by European 

beach grass, which prevents the inland movement of sand, potentially exacerbating coastal 

erosion and preventing the inland migration of the dune in response to sea level rise (UW 2013). 

Roads/Armoring

Coastal armoring and road construction limits the ability of dune habitat and associated species, 

including American dune grass, to migrate upland or inland with rising sea level (Largier et al. 

2010, Vulnerability Assessment Workshop, pers. comm., 2014). Passive erosion can also result 

from armoring, with habitat zones shifting downward on the beach/dune profile, 

disproportionally degrading upper and mid beach habitat (Dugan et al. 2008). Armoring is 

projected to increase in response to rising sea level and increased coastal erosion, although beach 

nourishment is now being used more frequently as an alternative (Defeo et al. 2009). 

Recreation

Trampling of small pioneer colonies from regenerating vegetative fragments may have a 

significant impact on post-storm recovery of small populations, particularly where European 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

106
beachgrass is more abundant (Peter Baye, pers. comm., 2014). Recreational use can lead to 

trampling of vegetation or sensitive habitat areas, as well as to behavioral modifications in beach 

and dune wildlife (e.g., bird nest abandonment) (Grigg et al. 2002, Schlacher et al. 2008, Largier 

et al. 2010). 

V. Other sensitivities: none identified 

Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 5

• Confidence of workshop participants: High 

Population status of the species (1=endangered; 5=robust): 3

• Confidence of workshop participants: Moderate 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 1

• Confidence of workshop participants: High 

Dispersal ability of the species: Low-Moderate 

• Confidence of workshop participants: Moderate 

Maximum annual dispersal distance: <1km 

• Confidence of workshop participants: Low

Additional participant comments

As a foredune species, American dune grass does have slightly greater adaptive capacity than 

other dune species and will be able to withstand a greater amount of sea level rise than species 

closer to mean high tide. 

Supporting literature

This species exhibits a broad geographic extent along the US West coast, from Alaska to 

California (MBA 2014). 

II. Intraspecific/Life history diversity

Diversity of life history strategies: Low-Moderate 

• Confidence of workshop participants: Moderate 

Genetic diversity: no answer provided 

Behavioral plasticity: n/a

Phenotypic plasticity: Moderate

• Confidence of workshop participants: Low

Overall degree of diversity/plasticity of the species: Moderate

• Confidence of workshop participants: Low

107
Additional participant comments

The species is capable of reproducing both sexually and asexually, can alter its phenology, and 

can allocate energy derived from photosynthesis either to reproduction or biomass accumulation 

in response to environmental conditions (Vulnerability Assessment Workshop, pers. comm., 

2014). American dune grass reproduces in successive cycles, takes around one year to reach 

reproductive maturity, and reproduces sexually once per year with more frequent asexual, 

vegetative reproduction (Vulnerability Assessment Workshop, pers. comm., 2014). 

Supporting literature

Genetic diversity of the species is unknown, though it does hybridize readily with multiple other 

species (Wang and Hsaio 1984). Dune grass also demonstrates phenotypic variation of some 

ecophysiological traits, including carbon assimilation rate and water use efficiency, based on its 

location on a dune, enabling the species to be present throughout all stages of dune succession 

(Imbert and Houle 2000). A reviewer of this document noted that the species exhibits high 

phenotypic plasticity, as it is able to “grow in dune systems from nutrient-rich macroalgal driftlines of beaches (productive, luxuriant growth), to stressful high dune crests with high moisture 

deficits in summer, where it grows at low density, small size, and slow rates. Its ability to 

regenerate from winter storm-eroded vegetative fragments after immersion in full strength 

seawater, and establish in beach sand, and grow through multiple annual deposits of sand, 

indicates a high degree of phenotypic plasticity and a very wide ecological amplitude, compared 

with associated native species. High phenotypic plasticity is also consistent with its circumboreal 

distribution and latitudinal range from arctic to Central California beaches.” (Peter Baye, pers. 

comm., 2014). 

III. Management potential

Value of species to people: Low

• Confidence of workshop participants: High 

• Description of value: some aesthetic value

Likelihood of managing or alleviating climate change impacts on species: Moderate

• Confidence of workshop participants: Moderate 

• Description of potential management options: protect inland dune areas to allow for 

migration and maintain sediment supply to keep pace with sea level rise.

Additional participant comments

The societal value for this species was rated as low due to the increased value that the invasive 

species, European beach grass, has with landowners and road users because of its superior ability 

to accumulate and retain sand and sediment (though this sentiment is likely outdated and applies 

only to the northern reaches of the species range, where more of the coastal land is privately 

owned, Peter Baye, pers. comm., 2014). The primary driver for American dune grass 

abundance, however, seems to be the non-climate threat of the invasive European beach grass. If 

management efforts can focus on the removal of beach grass, dune grass will likely be much 

more resilient. Identifying persistent populations that provide vegetative propagules to adjacent 

beaches during storm erosion events may be an important local strategy for conservation of 

refugia (Peter Baye, pers. comm., 2014). 

108
V. Other adaptive capacities: none identified 

Supporting literature

Though no additional adaptive capacities were identified for the species, Peter Baye, a coastal 

plant ecologist, noted that American dune grass has many adaptive qualities that may enable it to 

exploit the increase in storm wave overwash and disturbance to dune systems expected with 

climate change, especially as compared to the invasive European beach grass. Dune grass 

“allocates more growth to horizontal rhizome spread, and has higher tolerance to substrate 

salinity and flooding than European beach grass”. He continues, “where barrier beaches undergo 

rapid transgression, dune development and accretion rates are likely to be reduced, and the extent 

of washover fans, and frequency of winter overwash, are likely to increase as beaches retreat 

under conditions of limited littoral sand supply. These geomorphic conditions may be conducive 

to either recovery of American dune grass, or a favorable opportunity for managing it over 

European beach grass.” 

Exposure 

I. Future climate exposure6

Future climate and climate-driven changes identified (score7, confidence8): increased coastal 

erosion (5, high), increased storminess (5, high), sea level rise (5, high), changes in sediment

supply (5, high) 

Degree of exposure to future climate and climate-driven changes: High

• Confidence of workshop participants: High

Additional participant comments

Potential areas of refugia exist for all of these factors if there is adequate room for dune habitat to 

migrate inland. 

Literature Cited

Bennett, M. 2005. Establishment of American Dunegrass (Leymus mollis) Communities at Upland Dredge Material 

Disposal Sites for Sand Stabilization and Invasive Plant Species Control. US Army Corps of Engineers. 

http://depts.washington.edu/uwbg/research/theses/Matt_Bennett_2005-ACE_Report.pdf. 

Defeo, O.A. McLachlan, D. Schoeman, T. Schlacher, J. Dugan, A. Jones, M. Lastra, F. Scapini. 2009. Threats to 

sandy beach ecosystems: a review. Estuar. Coastl. Shelf Sci. 81:1-12.

Dugan, J.E., D.M. Hubbard, I. F. Rodil, D. L. Revell and S. Schroeter. 2008. Ecological effects of coastal armoring

on sandy beaches. Marine Ecology 29: 160-170.

Feagin, R.A., D.J. Sherman, and W.E. Grant. 2005. Coastal erosion, global sea-level rise, and the loss of sand dune

plant habitats. Frontiers in Ecology and the Environment 7:359-364.

Gagné, J. and G. Houle. 2002. Factors responsible for Honckenya peploides (Caryophyllaceae) and Leymus mollis 

(Poaceae) spatial segregation on subarctic coastal dunes. Am. J. Bot. 89(3): 479-485.

6 Supporting literature for future exposure to climate factors is provided in the introduction. 7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

109
Grigg, E. K., Green, D. E., Allen, S.G., and Markowitz, H. 2002. Diurnal and nocturnal haul out patterns of harbor 

seals (Phoca vitulina richardsi) at Castro Rocks, San Francsico Bay, California. California Fish and Game 

88(1):15-27. 

Imbert, E. and G. Houle. 2000. Ecophysiological differences among Leymus mollis populations across a subarctic 

dune system caused by environmental, not genetic, factors. New Phytologist 147: 601-8.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Monterey Bay Aquarium (MBA). 2014. American Dune Grass. Accessed August 20, 2014, from:

http://www.montereybayaquarium.org/animal-guide/plants-and-algae/american-dune-grass

Pickart, A. 1997. Control of European beachgrass (Ammophila arenaria) on the West Coast of the United States. 

1997 Symposium Proceedings. California Exotic Pest Plant Council.

Pojar, J. and A. MacKinnon. 1994. Plants of the Pacific Northwest Coast. Lone Pine Press.

Revell, D.L., J.J. Marra, and G.B. Griggs. 2007. Sandshed Management. Special issue of Journal of Coastal

Research - Proceedings from the International Coastal Symposium 2007, Gold Coast, Australia. SI 50:93-8.

Sallenger, A.H., W. Krabill, J. Brock, R. Swift, S. Manzinar, and H.F. Stockdon. 2002. Sea-Cliff erosion as a

function of beach changes and extreme wave run-up during the 1997-98 El Niño. Marine Geology 187:

279-297.

Schlacher, T.A., J.E. Dugan, D.S. Schoeman, M. Lastra, A. Jones, F. Scapini, A. McLachlan, and O. Defeo. 2007.

Sandy beaches at the brink. Diversity and Distributions 13: 556-560.

Slagel, M. J. and G.B. Griggs. 2008. Cumulative Losses of Sand to the California Coast by Dam Impoundment.

Journal of Coastal Research 24(3): 571-584.

Storlazzi, C. and G. Griggs. 2000. Influence of El Niño-Southern Oscillation (ENSO) events on the evolution of

Central California's shoreline. GSA Bulletin 112 (2): 236-249.

University of Washington (UW). 2013. Coastal Dunes System of Western North America. Accessed August 22, 

2014 from: http://depts.washington.edu/ehuf473/OutCoastal%20Dune%20Systems.htm. 

Wang, R. R. and C. Hsaio. 1984. Morphology and cytology of interspecific hybrids of Leymus mollis. J. Hered. 

75(6):488-92.

Wingfield, D.K. and C.D. Storlazzi. 2007. Variability in oceanographic and meteorologic forcing along Central

California and its implications on nearshore processes. Journal of Marine Systems 68: 457-472.

110
California Black Rail (Laterallus jamaicensis coturniculus)1

Executive Summary The black rail is a small and 

inconspicuous bird that inhabits high 

portions of salt marshes, shallow 

freshwater marshes, wet meadows, and 

flooded grassy vegetation in isolated 

pockets across North, Central and 

South America and the Caribbean, including a subspecies that inhabits a small portion of 

California. Key climate sensitivities identified by workshop participants include sea level rise, 

salinity and storm severity/frequency and key non-climate sensitivities include predation, land 

use change/habitat loss, pollution and poisons, and invasive species. California’s breeding 

population of black rails is fragmented and isolated, and listed as threatened in the state, with the 

species overall considered “near-threatened” by the IUCN. The majority of California’s 

breeding population of black rails occurs in the northern San Francisco Bay region, with a 

smaller population along the outer coast of Marin County, estimated at 280 individuals, and 

some documented sightings in the south bay near coyote creek and alviso slough. The black rail 

has low-moderate dispersal capabilities, a low degree of diversity/plasticity, and low-moderate 

societal value due to its inconspicuous and secretive nature. The likelihood of managing this 

species in the face of climate change is considered moderate-high, with management actions 

such as habitat restoration and predator control considered to have multiple habitat-level benefits 

and garnering great support in the conservation and management communities. 

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): sea level rise (5, high), 

salinity (4, high), storm intensity (4, high), precipitation (3, moderate), wave action (2, high) 

Climate and climate-driven changes that may benefit the species: no answer provided 

Overall species sensitivity to climate and climate-driven factors: High

• Confidence of participant: Moderate

Supporting literature

The black rail is highly sensitive to climate change because of its dependency on tidal marsh 

habitat which itself is highly sensitive to sea level rise and salinity changes, and to extreme 

weather events, especially in areas with less vegetative cover and less or distant marsh-upland 

refugia (Julian Wood, pers. comm., 2014). 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Black Rail Score Confidence 

Sensitivity 4 Moderate-High 3 High

Exposure 2 Low-Moderate 3 High

Adaptive Capacity 2 Low-Moderate 3 High

Vulnerability 4 Moderate-High 3 High

111
Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should be considered. 

Sea Level Rise

Unless there is a comparable increase in elevation of the land surface due to sediment delivery 

and availability, estuarine and tidal marsh habitat will not be able to adjust to rising sea levels, 

and more frequent and intense flooding will be expected (Largier et al. 2010, Ackerly et al. 

2012). Black rails are extremely vulnerable to predation when forced out of their dense coastal 

marsh habitat at extreme high tide (Evens and Page 1986, Evens 1999, BirdLife International 

2012), which occurs rarely now, but will likely increase as the combined effects of sea level rise 

and subsidence exacerbate periodic flooding of tidal marsh habitat (Evens 1999). Increased 

flooding also destroys black rail nests, which are constructed in clumps of vegetation on the 

ground (Evens and Page 1986). 

Salinity

Though salinity was identified as a potential sensitivity for the black rail, the literature does not 

indicate that it is a major factor affecting distribution of the species. Manolis (1978) found black 

rails existing in marshes with salinities ranging from low (Olema Marsh, Marin County) to high 

(San Pablo Bay marshes), and population surveys indicated that black rails prefer marshes that 

range from saline to brackish (Spautz et al. 2005). Salinity may impact black rails, however, 

through the alteration of the estuarine and tidal marsh biota (Largier et al. 2010). Changing 

precipitation patterns and saltwater intrusion due to sea level rise will likely result in greater 

salinity variation and may change the abundance and distribution of marsh vegetation (Largier et 

al. 2010). However, the composition of marsh biota does not seem to impact black rail presence 

as much as the density of the vegetation (Spautz et al. 2005). 

Storm Intensity

Increased storm intensity will impact both wave energy and the timing and intensity of 

precipitation events, with major consequences for flooding and salinity in tidal marsh habitat 

(Largier et al. 2010). The black rail is sensitive to extreme weather events, especially in areas 

with less vegetative cover and less or distant upland refugia (Julian Wood, pers. comm., 2014). 

II. Sensitivities to disturbance regimes

Disturbance regimes identified: storms and flooding 

Overall species sensitivity to disturbance regimes: High

• Confidence of participant: Moderate

Additional participant comments 

Storms and flooding can increase adult mortality and reduce nest survival as a result of increased 

exposure to the elements and predation. 

Supporting literature

When their preferred habitat is flooded, the black rail is forced out of the protective cover of 

marsh vegetation and is highly vulnerable to predation (Evens 1999). Flooding of black rail 

habitat occurs now during extremely high tides, but will likely increase in frequency due to rising 

sea levels, subsidence, heavy rainfall during El Niño events, and increased water retention due to 

development. Models suggest that the number of El Niño events likely will not change, though 

112
the likelihood of super El Niños doubles from one every 20 years in the previous century to one 

every 10 years in the 21st century (Cai et al. 2013). The high waves during El Niño events will 

be more extreme when combined with the trend of increased wave height (Largier et al. 2010), 

resulting in more frequent flooding of black rail habitat. 

III. Dependencies

Species dependence on one or more sensitive habitat types: High

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: tidal marsh

Species dependence on specific prey or forage species: Low-Moderate 

• Confidence of workshop participants: Moderate 

Other critical dependencies: no answer provided 

Specialization of species (1=generalist; 5=specialist): 3

• Confidence of workshop participants: Moderate 

Supporting literature

The black rail may be considered a habitat specialist and a diet generalist (Laurie Hall, pers. 

comm., 2014). It is highly dependent on tidal marsh habitat which itself is highly sensitive to sea 

level rise and salinity changes (Julian Wood, pers. comm., 2014), and has a low-moderate

dependency on specific prey, probing for a variety of insects, spiders, small crustaceans, snails, 

and seeds on the ground or in shallow water (Eddleman et al. 1994). Population surveys indicate 

that black rails prefer marshes that are close to water (bay or river), large, away from urban 

areas, and saline to brackish with a high proportion of low and dense marsh vegetation (Spautz et 

al. 2005). 

IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): predation (5, high), land use change (5, 

high), pollution (4, moderate), invasive species (4, high), coastal roads and armoring (3, high) 

Overall species sensitivity to non-climate stressors: Moderate-High

• Confidence of participant: High

Overall species exposure to non-climate stressors: Moderate-High

• Confidence of participant: High

Supporting literature

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by participant.

113
Predation

Habitat loss and increased flooding have worked in concert to increase the black rail’s 

susceptibility and exposure to predation by herons, egrets and raptors (Evens and Page 1986). 

As black rails are forced to retreat from the protective cover of marsh vegetation at high tides 

and during flooding events, avian predators, as well as foxes, rats and domesticated cats, have 

easy access to the typically hidden birds (Evens and Page 1986, Evens 1999). Marshes that are 

surrounded by development are more susceptible to mammalian predators due to the presence of 

people that often attract them to the area.

Land Use Change/Habitat Loss

The black rail thrives in extensive "high" marsh, areas which usually occur between the high 

tideline and the dry upland (Eddleman et al. 1994, Evens 1999). Population surveys in San 

Francisco Bay in the 1980s indicated that the species breeds almost exclusively in the North Bay 

(Evens 1999), though since this work, many birds have been captured in the South Bay, with a 

breeding population at Coyote Creek and possibly in the Eden Landing Ecological Reserve in 

Hayward (Laurie Hall, pers. comm., 2014). Subsidence, development, and the construction of 

levees and roads have effectively eliminated most of the higher marsh habitat in the South Bay 

region (Evens 1999). The loss of habitat along the outer coast of Marin County due to 

conversion to agriculture is cited as the primary cause for losses in Tomales Bay and Bolinas 

Lagoon (Evens et al. 1991), though recent restoration of portions of the Giacomini Marsh has 

resulted in black rail sightings in Tomales Bay (Laurie Hall, pers. comm., 2014). High marsh 

habitat is critical to the black rail for protection from predation at high tide and as refugia from 

flooding due to rising sea levels (Eddleman et al. 1994; BirdLife International 2012; Julian 

Wood, pers. comm., 2014). 

Pollution/Poisons 

Toxic contamination, including oil spills, has been shown to have adverse biological effects on 

estuarine birds in the San Francisco Bay region, including population declines associated with 

organochlorine contamination and impaired reproduction associated with selenium and heavy 

metals (Ohlendorf et al. 1986, Ohlendorf and Flemming 1988). Methylmercury levels were 

found to be above the “no observed adverse effect” levels for a majority of black rails tested 

from San Francisco Bay, putting the population at risk for reproductive effects (Tsao et al. 2009) 

Invasive Species

Invasive species effectively out-compete native species and decrease native species diversity and 

abundance. It is estimated that about 143 species of invasives are present in the region, most of 

which exist in the estuarine zone (Byrnes et al. 2007), greatly altering the structure and function 

of marsh and estuarine habitats, impacting the black rail. For example, the invasive Phragmite 

reed on the east coast of the United States has aggressively colonized the narrow transition zone 

between high marsh and upland habitat, creating a monoculture that differs markedly from the 

natural breeding habitat of the black rail (CCD 2014). 

V. Other sensitivities: none identified 

114
Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 2

• Confidence of participant: High

Population status of the species (1=endangered; 5=robust): 1

• Confidence of participant: High

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 2

• Confidence of participant: High

Dispersal ability of the species: Low-Moderate 

• Confidence of participant: Moderate

Maximum annual dispersal distance: no answer provided 

Supporting literature

The majority of the breeding population of the black rail is in northern San Francisco Bay, but 

also along the outer coast of Marin County in Bolinas Lagoon and Tomales Bay (Evens et al. 

1991, Spautz et al. 2005) and in South Bay near Coyote Creek and Alviso Slough (Laurie Hall, 

pers. comm., 2014). The species is considered “near threatened” on the IUCN Red List of 

Threatened Species due to the moderately rapid decline across its range (BirdLife International 

2012) and is listed as threatened in the state of California (Spautz et al. 2005). Though dispersal 

was rated as low-moderate by workshop participants, genetic work by local researchers 

demonstrates frequent gene flow among bay area marshes, indicating that the species is capable 

of sustaining long-distance travel (Laurie Hall, pers. comm., 2014). 

II. Intraspecific/Life history diversity

Diversity of life history strategies: Low

• Confidence of workshop participants: Moderate 

Genetic diversity: no answer provided 

Behavioral plasticity: no answer provided 

Phenotypic plasticity: no answer provided 

Overall degree of diversity/plasticity of the species: Low

• Confidence of workshop participants: low 

Supporting literature

The black rail likely has low behavioral plasticity, as it relies on thick marsh vegetation for 

protection from predation (BirdLife International 2012). Strong genetic divergence exists among 

black rail subspecies, but there is evidence of substantial gene flow among distinct geographic 

populations within California (Girard et al. 2010). 

The black rail takes about a year to reach sexual maturity, experiences two reproductive events in 

a single year, and lives to be around 5-9 years in age (Julian Wood, pers. comm., 2014). The 

reproductive biology of this species is poorly known; males and females vocalize in breeding 

115
grounds and form mating pairs that incubate 6-8 eggs together in ground nests (Eddleman et al. 

1994). The chicks hatch after 17-20 days and are semi-precocious, requiring feeding by the 

parents (Eddleman et al. 1984). 

III. Management potential

Value of species to people: Low-Moderate

• Confidence of workshop participants: Moderate 

• Description of value: some value for birders 

Likelihood of managing or alleviating climate change impacts on species: Moderate-High

• Confidence of workshop participants: Moderate 

• Description of potential management options: habitat restoration and predator control, 

having multiple benefits for tidal marsh habitat and wildlife, are more likely to be 

pursued and supported (Julian Wood, pers. comm., 2014). 

Supporting literature

An example of successful restoration of black rail habitat can be found in the Sierra foothills, 

where the Department of Fish and Wildlife creates black rail habitat by running irrigation water 

down small slopes to create wetlands. The birds colonize them quickly and use them for breeding 

(Laurie Hall, pers. comm., 2014).

IV. Other adaptive capacity factors: none identified

Exposure 

I. Future climate exposure6

Future climate and climate-driven changes identified: increased flooding (3, high), sea level rise

(3, high), changes in salinity (2, high), changes in precipitation (1, moderate) 

Degree of exposure to future climate and climate-driven changes: Moderate

• Confidence of workshop participants: High 

Additional participant comments

Potential areas of refugia identified for these factors include high marsh habitat and marshupland transition zone. 

Literature Cited

Ackerly, D. D., R. A. Ryals, W. K. Cornwell, S. R. Loarie, S. Veloz, K. D.Higgason, W. L. Silver, and T. E. 

Dawson. 2012. Potential Impacts of Climate Change on Biodiversity and Ecosystem Services in the San 

Francisco Bay Area. California Energy Commission. Publication number: CEC-500-2012- 037.

BirdLife International 2012. Laterallus jamaicensis. The IUCN Red List of Threatened Species. Version 2014.2. 

Accessed on September 2, 2014, from: http://www.iucnredlist.org/details/22692353/0. 

Byrnes, J.E., P.L. Reynolds, J.J. Stachowicz. 2007. Invasions and extinctions reshape coastal marine food webs. 

PLoS ONE 2(3): e295.

6 Supporting literature for future exposure to climate factors is provided in the introduction.

116
Cai, W. S. Borlace, M. Lengaigne, P. van Rensch, M. Collins, G. Vecchi, A. Timmermann A. Santoso, M.J. 

McPhaden, L. Wu, M.H. England, G. Wang, E. Guilyardi, F. Jin. 2013. Increasing Frequency of Extreme 

El Nino Events Due to Greenhouse Warming. Nature Climate Change 4: 111-16.

Center for Conservation Biology (CCD). 2014. Population Threats to Black Rails. Accessed September 2, 2014, 

from: http://www.ccbbirds.org/what-we-do/research/species-of-concern/blackrail/threats/. 

Eddleman, W. R., R. E. Flores, and M. Legare. 1994. Black Rail (Laterallus jamaicensis). In The Birds of North 

America, No. 123 (A. Poole and F. Gill, Eds.). Philadelphia: The Academy of Natural Sciences; 

Washington, D.C.: The American Ornithologists' Union.

Evens, J.G. 1999. "Mystery of the Marsh: the California Black Rail." Tideline: 19 (4) pp. 1-3.

Evens, J.G. and G.W. Page. 1986. Predation on black rails during high tides in salt marshes. Condor 88:107-109.

Evens, J.G., G.W. Page, S.A. Laymon and R.W. Stallcup. 1991. Distribution, Relative Abundance and Status of the 

California Black Rail in Western North America. Condor 93: 952-966.

Girard, P., J.Y. Takekawa, and S.R. Beissinger. 2010. Uncloaking a Cryptic, Threatened Rail with Molecular 

Markers: Origins, Connectivity, and Demography of a Recently Discovered Population. Conservation 

Genetics 11:2409–2418. 

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp.

Manolis, T. D. 1978. Status of the Black Rail in central California. W. Birds 9:151- 158. 

Ohlendorf, H.M., R.H. Lowe, P.R. Kelly, and T.E. Harvey. 1986. Selenium and heavy metals in San Francisco Bay 

diving ducks. Journal of Wildlife Management 50:64-71.

Ohlendorf, H.M. and W.J. Fleming. 1988. Birds and environmental contaminants in San Francisco and Chesapeake 

bays. Marine Pollution Bull. 19: 487495. 

Spautz, H., N. Nur and D. Stralberg. 2005. California Black Rail (Laterallus jamaicensis coturniculus) Distribution 

 and Abundance in Relation to Habitat and Landscape Features in the San Francisco Bay Estuary. USDA 

Forest Service Gen. Tech. Rep. PSW-GTR-191.

Tsao, D.C., A.K. Miles, J.Y. Takekawa, I. Woo. 2009. Potential Effects of Mercury on Threatened California 

 Black Rails. Environmental Contamination Toxicology 56(2): 292-301.

 

117
Black Oystercatcher (Haematopus bachmani)

1

Executive Summary 

The black oystercatcher is a large, 

conspicuous, non-migratory rocky 

shore bird with a distinctive bill that 

enables the animal to pry open 

intertidal invertebrates. The species 

ranges from Alaska to Baja California. Key climate sensitivities identified by workshop 

participants for the black oystercatcher include sea level rise, wave action, precipitation, and 

erosion, and key non-climate sensitivities include land use change, pollution/poisons, and 

recreation. The black oystercatcher exhibits a transcontinental geographic extent and a somewhat 

fragmented and diminished, though fairly stable, population that predominantly resides in the 

northern stretches of its range. The population in California is thought to number around 800 

individuals, and the degree of dispersal is fairly limited, though dispersal to some extent by 

juveniles is critical in maintaining genetic diversity. The societal value for this species is high 

due to its aesthetic value to the general public and its value as an indicator of ecosystem health 

for the rocky intertidal. Management potential is considered to be moderate, with some 

possibility to better manage disturbance from public visitation and to better protect the few 

meters of land above the beach that may serve as climate refugia for nesting habitat. 

Sensitivity 

I. Sensitivity to climate and climate driven changes Climate and climate-driven changes identified (score2

, confidence3): sea level rise (5, high), 

wave action (5, high), precipitation (4, high), coastal erosion (4, moderate), air temperature (1, 

moderate)

Climate and climate-driven changes that may benefit the species: none identified

Overall species sensitivity to climate and climate-driven factors: Moderate-High

• Confidence of workshop participants: Moderate

Additional participant comments

It is expected that sea level rise and coastal erosion will lead to habitat loss, and increased storm 

frequency and intensity would be expected to increase reproductive disturbance. Loss of 

breeding and nesting habitat is also expected with increased erosion, as is the loss of pre-existing 

nests to burying from eroded sediment. 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

California Mussel Score Confidence 

Sensitivity 5 High 3 High

Exposure 5 High 3 High

Adaptive Capacity 3 Moderate 2 Moderate

Vulnerability 4 Moderate-High 3 High

118
Supporting literature

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. Sea level rise and wave action negatively 

impact the species through the same mechanism of coastal flooding, so these stressors are 

discussed together. 

Sea Level Rise and Wave Action

The impact of sea level rise and enhanced wave action to oystercatchers is primarily through the 

exacerbation of flooding at high tide. In the long-term, sea level rise will reduce the availability 

of nesting and breeding habitat (Vulnerability Assessment Workshop, pers. comm., 2014), but 

acute flooding events, due to the combination of sea level rise, wave activity and high tide, can 

result in nest loss and an overall decline in reproductive success (Tessler et al. 2007). Clutches 

are regularly lost to flooding of nesting sites; a study of Alaskan nesting sites attributed 32% of 

nest losses to flooding events (Tessler et al. 2007). 

Precipitation 

Also a contributor to flooding, heavy precipitation events can negatively impact breeding success 

of black oystercatchers by inundating nesting sites that are built into depressions (Tessler et al. 

2007). 

Erosion 

Enhanced coastal erosion, due to sea level rise and an increase in wave and storm severity, may 

result in the burying of intertidal (feeding) habitat for oystercatchers (Vulnerability Assessment 

Workshop, pers. comm., 2014) and may impede the ability of intertidal organisms (oystercatcher 

food source) to migrate inland in response to rising sea levels (Largier et al. 2010). 

II. Sensitivity to changes in disturbance regimes

Disturbance regimes identified: wind, storms, and flooding 

Overall species sensitivity to disturbance regimes: High

• Confidence of workshop participants: High

Additional participant comments

The identified disturbance regimes would greatly impact the breeding success of the black 

oystercatcher, but not the survival of adults.

Supporting literature

As storms are predicted to become more frequent and more severe, winter survival of adult and 

juvenile oystercatchers is expected to decline (Tessler et al. 2007) and reproductive disturbance 

will likely occur due to increased flooding from wave action and precipitation (see climate 

sensitivities above). Severe weather events, including high wind events and enhanced flooding, 

impact seabirds directly through the loss of nests and/or chicks (Hennicke and Flachsbarth 2009), 

and indirectly, by inhibiting adult feeding which reduces chick provisioning (Schreiber 2002). 

119
III. Dependencies

Species dependence on one or more sensitive habitat types: High

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: rocky intertidal habitat for foraging and the 

narrow band of rocky and mixed substrate headland and island habitat above mean high 

tide for breeding and nesting 

Species dependence on specific prey or forage species: Moderate-High

• Confidence of workshop participants: Moderate 

Other critical dependencies: none identified 

Specialization of species (1=generalist; 5=specialist): 5 

• Confidence of workshop participants: High 

Additional participant comments 

The black oystercatcher would likely not be able to quickly adapt to another breeding habitat, so 

if the narrow band of rocky and mixed substrate habitat above mean high tide is negatively 

affected by sea level rise, development, erosion, or other stressors, the species would be highly 

impacted.

Supporting literature

The species feeds exclusively on intertidal invertebrates such as limpets and mussels (SIMoN 

2014a). 

IV. Sensitivity and exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): land use change (5, moderate), recreation

(5, moderate), pollution and poisons (4, moderate) 

Overall species sensitivity to non-climate stressors: Moderate-High

• Confidence of workshop participants: High 

Overall species exposure to non-climate stressors: no answer provided 

Additional participant comments 

Land Use Change 

How land is used in and near oystercatcher habitat (especially breeding/nesting habitat upland of 

rocky intertidal habitat) and how this use may change has real repercussions for the species 

through possible changes to the severity and frequency of disturbance from humans, coastal 

erosion, and nutrient run-off. 

Recreation

The presence and activity of humans and dogs in oystercatcher habitat causes disturbance and 

can decrease nesting, or increase predation through the attraction of dogs or ravens to high 

human use zones. 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

120
Supporting literature

Recreation

A study in Oregon found that the majority of nests that were accessible to humans failed, 

presumably a result of increased disturbance (Tessler et al. 2007). Also, because nesting sites are 

highly vulnerable to flooding, increased boating activity and visitation to nesting areas increases 

the probability that nests may be flooded by boat wakes, especially when visitation coincides 

with high tide (Tessler et al. 2007). 

Pollution/Poisons 

Poor water quality due to pollution can affect California mussels, which are a primary food 

source for oystercatchers. Because mussels are highly efficient filter feeders, heavy metals and 

organic pollutants can accumulate in their tissues (SIMoN 2014b), negatively impacting 

oystercatchers as they are consumed. Oil spills are also a threat to oystercatchers; up to 20% of 

the population in Prince William Sound was killed by the 1989 Exxon Valdez spill, breeding 

activity was disrupted, and chick survival was reduced (Andres 1994, 1997). 

V. Other sensitivities: none identified

Adaptive Capacity

I. Extent, Status, and Dispersal Ability

Geographic extent of the species (1=endemic; 5=transboundary): 5 

• Confidence of workshop participants: High

Population status of the species (1=endangered; 5=robust): 3

• Confidence of workshop participants: Moderate 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 2-3 

• Confidence of workshop participants: Moderate

Dispersal ability of the species: unknown 

• Confidence of workshop participants: Low

Maximum annual dispersal distance: no answer provided 

Supporting literature

This species exhibits a transcontinental geographic extent, from the Aleutian Islands, Alaska to 

Baja California, Mexico (SIMoN 2014a), and a population numbering approximately 10,000 

individuals with only around 800 in California (Tessler et al. 2007). The black oystercatcher is 

considered a USFWS Focal Species for priority conservation action and a species of special 

concern within multiple jurisdictions, and is the least abundant shorebird species in North 

America (Tessler et al. 2007). Southern populations (including the study region) are thought to 

have very little migratory movement away from nesting sites, though some movement does 

occur, especially in juveniles and subadults (Tessler et al. 2007).

121
II. Intraspecific/Life History Diversity

Diversity of life history strategies: Low

• Confidence of workshop participants: Low

Genetic diversity: unknown 

• Confidence of workshop participants: n/a

Behavioral plasticity: Low

• Confidence of workshop participants: Moderate

Phenotypic plasticity: no answer provided 

Overall degree of diversity/plasticity of the species: Low

• Confidence of workshop participants: Low-Moderate 

Additional participant comments 

The black oystercatcher is long-lived, breeds once per year (or maybe twice, in the case of a 

failed brood), and may produce 1-2 chicks each successful breeding event.

Supporting literature

Little is known of the genetic diversity of the species, though it is hypothesized that juvenile 

dispersal is critical to maintaining genetic diversity in light of high site fidelity and a vast 

geographic range (Tessler et al. 2007).

III. Management Potential

Value of species to people: High

• Confidence of workshop participants: Moderate

• Description of value: value to the general public as an easily recognizable, charismatic 

and aesthetic species of the California coast

Likelihood of managing or alleviating climate change impacts on species: Moderate-High

• Confidence of workshop participants: Moderate

• Description of potential management options: protect habitat from public (recreational) 

use that may serve as climate refugia (higher elevation areas that are more protected from 

big storms)

Supporting literature

The black oystercatcher is valued by the scientific community as a key indicator of ecosystem 

health for the rocky intertidal (Tessler et al. 2007). 

IV. Other adaptive capacity factors: none identified

122
Exposure 

I. Future climate exposure6

Future climate and climate-driven changes identified (score7, confidence8): increased flooding 

(5, high), sea level rise (5, high), increased storminess (5, high), changes in precipitation (4, 

moderate), increased coastal erosion and runoff (4, moderate) 

Degree of exposure to future climate and climate-driven changes: Moderate-High

• Confidence of workshop participants: Moderate 

Additional participant comments

Increased flooding of low-lying coastal areas, including oystercatcher feeding and nesting 

habitat, is expected in the study region due to rising sea level, increased storm activity and 

intensity, and increased extreme precipitation events. 

Literature Cited

Andres, B. A. 1994. The effects of the Exxon Valdez oil spill on black oystercatchers breeding in Prince William 

Sound, Alaska, Exxon Valdez Oil Spill State/Federal Natural Resource Damage Assessment Final Report

(Bird Study Number 12/Restoration Study Number 17), U.S. Fish and Wildlife Service, Anchorage, AK. 

Andres, B. A. 1997. The Exxon Valdez oil spill disrupted the breeding of black oystercatchers. Journal of Wildlife 

Management 61: 1322-1328. 

Hennicke, J.C. and Flachsbarth, K. 2009. Effects of Cyclone Rosie on breeding Red-tailed Tropicbirds Phaethon 

rubricauda on Christmas Island, Indian Ocean. Marine Ornithology 37: 175–178.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Schreiber, E.A. 2002. Climate and weather effects on seabirds. In: Schreiber, E.A. & Burger, J. (Eds.). Biology of 

marine birds. Boca Raton, Florida: CRC Press. pp. 179–215.

Sanctuary Integrated Monitoring Network (SIMoN). 2014a. Haematopus bachmani - Black Oystercatcher. Accessed 

June 2014. http://sanctuarysimon.org/species/haematopus/bachmani/black-oystercatcher.

Sanctuary Integrated Monitoring Network (SIMoN). 2014b. Mytilus californianus - California Mussel. Accessed 

June 2014. http://www.sanctuarysimon.org/species/mytilus/californianus/california-mussel.

Tessler, D.F., J.A. Johnson, B.A. Andres, S. Thomas, and R.B. Lanctot. 2007. Black Oystercatcher (Haematopus 

bachmani) Conservation Action Plan. International Black Oystercatcher Working Group, Alaska 

Department of Fish and Game, Anchorage, Alaska, U.S. Fish and Wildlife Service, Anchorage, Alaska, and 

Manomet Center for Conservation Sciences, Manomet, Massachusetts. 115 pp.

6 Supporting literature for future exposure to climate factors is provided in the introduction. 7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

123
Blue Whale (Balaenoptera musculus) 1

Executive Summary Blue whales are filter-feeding baleen 

whales that concentrate in areas 

downstream from upwelling centers 

where krill are concentrated into large 

swarms. In the study region, blue 

whales are often sighted near Cordell 

Bank and the broad shelf and shelf break in the Gulf of the Farallones. The Eastern North 

Pacific stock ranges from the Gulf of Alaska to Southern California in the summer and fall to 

feed and between Mexico and Panama in the winter and spring to breed. Key climate 

sensitivities identified by workshop participants for this species include sea surface temperature 

and dynamic ocean conditions (currents/mixing/stratification) and key non-climate sensitivities 

include pollution and poisons, human interactions, and anthropogenic noise. Blue whales exhibit 

a transcontinental geographic extent and an endangered population due to extensive whaling, 

though the Eastern North Pacific stock is recovering and growing. The species has high 

dispersal capability, with adults traveling great distances to access breeding and feeding grounds, 

and exhibits behavioral adaptation to anthropogenic noise, variable morphology and genetics 

among subspecies, and variable genetic structure due to hybridization among subspecies and 

with the related fin whale. The societal value for blue whales is high due to value to the tourism 

industry as charismatic megafauna. The challenge in managing this species is due to its 

cosmopolitan distribution, though human impacts (including noise, entanglement and vessel 

strikes) are currently managed for the Eastern North Pacific stock that occurs in the study region. 

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): sea surface temperature (2, 

moderate) and dynamic ocean conditions (currents/mixing/stratification) (2, low) 

Climate and climate-driven changes that may benefit the species: no answer provided 

Overall species sensitivity to climate and climate-driven factors: Low-Moderate

• Confidence of workshop participants: Low

Supporting literature

Though the only climate-driven factors identified for this species received low-moderate 

sensitivity scores, literature review was conducted on these factors in order to provide some 

information on their impact. However, it should be noted that the blue whale is likely more 

sensitive to direct impacts from human activity rather than from climate change. 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Blue Whale Score Confidence 

Sensitivity 4 Moderate-High 3 High

Exposure 5 High 2 Moderate

Adaptive Capacity 4 Moderate-High 3 High

Vulnerability 4 Moderate-High 3 High

124
Sea Surface Temperature 

Modeling based on ten years of data collected by Applied California Current Ecosystem Studies

(ACCESS) cruises indicate that two climate indices are critical factors in predicting blue whale 

presence in the region (Vulnerability Assessment Workshop, pers. comm., 2014). These climate 

indices, which also impact sea surface temperature in the study region, are the Pacific Decadal 

Oscillation (PDO) and the North Pacific Gyre Oscillation (NPGO). The PDO is a long-term 

fluctuation in ocean climate that changes state every 20-40 years (Trenberth 1990, Trenberth and 

Hurell 1994), with warmer ocean temperatures observed during the positive phase, and cooler 

temperatures during the negative phase. The NPGO describes decadal scale fluctuations in sea 

surface temperature when paired with the PDO, as well as in salinity, chlorophyll, and 

thermocline depth, which has important implications for upwelling (DiLorenzo et al. 2008, 

Largier et al. 2010). A positive PDO and a negative NPGO indicate less productive ocean 

conditions, as was observed in 2005 and 2006, along with weak upwelling and low blue whale 

sightings (Elliott and Jahncke 2014). Further, abundance of North Pacific krill (Euphausia 

pacifica), the primary prey for blue whales, is thought to be negatively correlated with the PDO 

and sea surface temperature, declining during warm ocean periods (Brinton and Townsend 

2003). 

Dynamic ocean conditions (currents/mixing/stratification) 

There is not yet enough data to support the direct impact of oceanographic conditions such as 

upwelling on blue whale presence and abundance, but given that upwelling has a significant 

impact on krill distribution, there is likely a strong indirect effect of upwelling on blue whales 

(Vulnerability Assessment Workshop, pers. comm., 2014). Krill are more abundant with earlier 

and stronger upwelling events and less abundant in years that experience weaker and/or later 

upwelling. Associated blue whale sightings have been correlated with these events, including 

decreased blue whale sightings in 2005 and 2006 in association with weak upwelling and a 

decline in krill (Jahncke et al. 2008). 

II. Sensitivities to disturbance regimes: none identified 

III. Dependencies

Species dependence on one or more sensitive habitat types: Low-Moderate

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: continental shelf to provide krill 

concentrations 

Species dependence on specific prey or forage species: High (krill)

• Confidence of workshop participants: High 

Other critical dependencies: upwelling and favorable oceanographic conditions for reproductive 

success due to the availability of krill

• Degree of dependence: Moderate

• Confidence of workshop participants: High 

Specialization of species (1=generalist; 5=specialist): 5

• Confidence of workshop participants: High 

125
IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): pollution and poisons (5, high), human 

interactions (5, high), anthropogenic noise (5, high) 

Overall species sensitivity to non-climate stressors: High

• Confidence of workshop participants: High 

Overall species exposure to non-climate stressors: High

• Confidence of workshop participants: High 

Additional participant comments

Exposure to pollutants may contribute to acute impacts, such as pregnancy termination, and 

chronic impacts, such as promoting growth of cancerous tumors.

Supporting literature

Pollution and Poisons 

Though it is difficult to establish a link between observed levels of contamination and direct 

health impacts in wild populations of cetaceans (Elfes 2008), exposure to pollutants may 

negatively impact reproduction (Steiger and Calambokidis 2000). The pollutants most often 

associated with these impacts include PCBs and synthetic organochlorine pesticides (including 

DDT), both of which bioaccumulate in the fatty tissues of marine mammals and are transferred 

from female whales to calves during gestation and lactation (Trumble et al. 2013). However, 

much more research is needed to fully understand the effects of pollutants on blue whales, as the 

effect may not be significant considering the successful recovery of the Eastern Pacific stock 

(Sarah Allen, pers. comm., 2014). 

Human Interaction

Blue whales in central California are affected by multiple factors due to interactions with 

humans, including whale watching disturbances, shipping vessel strikes, and fisheries 

interactions (Vulnerability Assessment Workshop, pers. comm., 2014). Whale watching boats 

seek out blue whales, and there is some evidence that closely-approaching boats cause behavioral 

responses such as avoidance and alteration of diving behavior (Calambokidis et al. 2004). 

Vessel strikes have been identified as a threat to the recovery of the blue whale population 

(NMFS 1998) and the West Coast Region of the Office of National Marine Sanctuaries identified 

the issue of vessel strikes as a regional management priority. This region has one of the busiest 

ports for large shipping vessels on the west coast, with over 6,000 commercial vessels transiting 

in and out of San Francisco Bay every year (GFNMS 2008), whose routes often overlap with 

prime feeding grounds and transiting zones for large whales (Joint Working Group on Vessel 

Strikes and Acoustic Impacts 2012). Approximately four blue whales are killed by vessel strike 

every year, and this figure may be much higher due to unreported or unnoticed collisions (Joint 

Working Group on Vessel Strikes and Acoustic Impacts 2012). Fishing activity may cause harm 

to blue whales through entanglement in fishing gear, which can cause impaired foraging, 

increased drag, and tissue damage, including infection and hemorrhage, which can all lead to 

death of an individual (Moore and van der Hoop 2012). Though direct observation of blue whale 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

126
mortality due to entanglement is rare, with two documented cases, entanglement rates are likely 

underestimated because of lack of detection (NMFS 2014). 

Anthropogenic Noise 

Noise from ships, aircraft, and industry and military activity (NRC 2005) can mask 

communication among blue whales and limit prey detection (Clark et al. 2009), cause direct 

physiological damage, and disrupt feeding, breeding and traveling behaviors, leading to chronic 

stress and population-level impacts (CBD 2012, Rolland et al. 2012). Noise has increased 

exponentially in the region over the past 60 years, largely due to an increased commercial fleet 

(NRC 2003, McDonald et al. 2006). 

V. Other sensitivities: none identified 

Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 5

• Confidence of workshop participants: High 

Population status of the species (1=endangered; 5=robust): 1

• Confidence of workshop participants: High 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): no answer 

provided 

Dispersal ability of the species: High 

• Confidence of workshop participants: High 

Maximum annual dispersal distance: >100km 

• Confidence of workshop participants: no answer provided 

Supporting literature

Blue whales exhibit a transcontinental geographic extent, but an endangered population status 

due to extensive commercial whaling that drastically reduced populations worldwide (SIMoN

2006). The Eastern North Pacific stock was reduced from approximately 4,900 individuals to 

less than 2,000 when whaling ceased in 1966 (Braham 1984). This stock is currently one of the 

more healthy and growing populations worldwide, and current estimates based on markrecapture studies number the population at around 2,500 individuals, potentially reaching 

carrying capacity (Calambokidis et al. 2010, NMFS 2011). Dispersal capability is high, with 

individuals traveling greater than 100 km between feeding and breeding grounds (Vulnerability 

Assessment Workshop, pers. comm., 2014). Though individuals are fairly solitary, they do 

loosely aggregate in prime feeding grounds (SIMoN 2006, Vulnerability Assessment Workshop, 

pers. comm., 2014). 

II. Intraspecific/Life history diversity

No information regarding blue whale diversity and plasticity was provided by workshop 

participants.

127
Supporting literature

There are thought to be between six and twelve distinct populations of blue whales around the 

world based both on different song types as well as genetics, and in the North Pacific, at least 

two populations exist based on these song types (Calambokidis 2011). Variation in phenotypic 

plasticity is observed among these distinct populations, suggesting that selective pressure on 

geographically widespread populations from varying environmental conditions results in variable 

morphologies, including size and proportions (Gilpatrick and Perryman 2008). The size of the 

whales in the eastern Pacific population is smaller, for example than that those in the Southern 

Hemisphere. Hybridization has been observed in at least 5 cases between blue and fin whales 

(Bérubé and Aguilar 1998) and between two distinct Southern Hemisphere blue whale 

subspecies (Attard et al. 2012), potentially suggesting an enhanced capacity for genetic variation 

and adaptation. Behavioral plasticity has been observed in right whales in response to noise 

pollution from vessels and human activities through alteration of their communication by 

changing the frequency, source level, redundancy, and timing of their communications (Parks et 

al. 2007, Rolland et al. 2012). Blue whales reproduce in successive cycles (iteroparous), become 

sexually mature around 10 years of age, and can have up to 1 calf every 2-3 years, with a 12-

month gestation (Vulnerability Assessment Workshop, pers. comm., 2014). 

III. Management potential

Value of species to people: High

• Confidence of workshop participants: High 

• Description of value: value to the tourism industry as charismatic megafauna

Likelihood of managing or alleviating climate change impacts on species: Moderate

• Confidence of workshop participants: Moderate 

• Description of potential management options: None provided, as there is difficulty in 

managing such a cosmopolitan species that occurs throughout the Eastern Pacific

Supporting literature

Management authority for the blue whale falls to the National Marine Fisheries Service, which 

has produced the Pacific Offshore Cetacean Take Reduction Plan6

 to reduce negative impacts 

from commercial fishing and a recovery plan7

 for the North Pacific population. Efforts to limit 

the degree of human interactions have become a management priority for the sanctuary program 

as well through the use of dynamic shipping lane restrictions (Joint Working Group on Vessel 

Strikes and Acoustic Impacts 2012).

IV. Other adaptive capacity factors: none identified 

6 http://www.nmfs.noaa.gov/pr/interactions/trt/poctrp.htm

7 http://www.nmfs.noaa.gov/pr/pdfs/recovery/whale_blue.pdf

128
Exposure 

I. Future climate exposure8

Future climate and climate-driven changes identified (score9, confidence10): changes in sea 

surface temperature (5, high) and altered currents and mixing (5, low) 

Degree of exposure to future climate and climate-driven changes: High 

• Confidence of workshop participants: Moderate 

Supporting literature

Potential areas of refugia include areas with topographic upwelling rather than along the 

continental shelf where cool waters occur, for example Cape Mendocino and Point Arena (Sarah 

Allen, pers. comm., 2014). 

Literature Cited 

Attard C.R., L.B. Beheregaray, K.C. Jenner, P.C. Gil , M.N. Jenner, M.G. Morrice, K.M. Robertson, and 

L.M. Möller. 2012. Hybridization of Southern Hemisphere blue whale subspecies and a sympatric area off 

Antarctica: impacts of whaling or climate change? Molecular Ecology (23):5715-27.

Bérubé, M. and A. Aguilar. 1998. A new hybrid between a blue whale, Balaenoptera musculus, and a fin whale, B. 

physalus: frequency and implications of hybridization. Marine Mammal Science 14: 82–98. 

Braham, H.W. 1984. The status of endangered whales. Marine Fisheries Review 46.

Calambokidis, J., T. Chandler, E. Falcone, A. Douglas. 2004. Research on large whales off California, Oregon, and

Washington in 2003. Annual Report for 2003. Prepared by Cascadia Research for the Southwest Fisheries 

Science Center.

Calambokidis, J. 2011. Baja Blue Whale Research 2011: Summary of research conducted by Cascadia Research 

as a part of an Oceanic Society Research Expedition with volunteers from Road Scholar Expedition Dates: 

March 26 – April 2, 2011. Retrieved August 18, 2014 from: 

http://www.cascadiaresearch.org/reports/BAJA%20BLUE%20WHALE%20RESEARCH%202011.pdf

Calambokidis, J., E. Falcone, A. Douglas, L. Schlender, and J. Huggins. 2010. Photographic identification of 

humpback and blue whales off the U.S. West Coast: results and updated abundance estimates from 2008

field season. Final Report for Contract AB133F08SE2786 from Southwest Fisheries Science Center. 18pp.

Clark, C. W., W. T. Ellison, B. L. Southall, L. Hatch, S. M. Van Parijs, A. Frankel, D. Ponirakis. 2009. Acoustic 

masking in marine ecosystems: intuitions, analysis, and implication. Marine Ecology Progress Series 395: 

201-222.

Convention on Biological Diversity (CBD). 2012. Scientific synthesis on the impacts of underwater noise on marine 

and coastal biodiversity and habitats. UNEP/CBD/SBSTTA/16/INF/12.

Elfes, C.T. 2008. Persistent organic pollutant levels in North Pacific and North Atlantic humpback whales 

 (Megaptera novaeangliae). A Master’s Thesis presented to University of Washington. 85 pp.

Elliott, M. L. and J. Jahncke. 2014. Ocean Climate Indicators Status Report – 2013. Unpublished Report. Point Blue 

Conservation Science, Petaluma, California. Point Blue contribution number 1982. 

Gilpatrick, J.W. and W.L. Perryman. 2008. Geographic variation in external morphology of North Pacific and

Southern Hemisphere blue whales (Balaenoptera musculus). Journal of Cetacean Research and 

Management 10(1): 9-21.

Jahncke, J., Saenz, B.L., Abraham, C.L., Rintoul, C., Bradley, R.W., and Sydeman, W.J. 2008. Ecosystem responses 

to short-term climate variability in the Gulf of the Farallones, California. Progress in Oceanography 

77:182-193.

Joint Working Group on Vessel Strikes and Acoustic Impacts. 2012. Vessel Strikes and Acoustic Impacts. Report of 

8 Supporting literature for future exposure to climate factors is provided in the introduction.

9 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

10 Confidence level indicated by workshop participants.

129
a Joint Working Group of Gulf of the Farallones and Cordell Bank National Marine Sanctuaries Advisory 

Councils. San Francisco, CA. 43 pp. 

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

McDonald, M.A., J.A. Hildebrand, S.M. Wiggins. 2006. Increases in deep ocean ambient noise in the northeast 

pacific west of San Nicolas Island, California. Journal of the Acoustical Society of America 120:711-8. 

Moore, M.J. and J. M. van der Hoop. 2012. The Painful Side of Trap and Fixed Net Fisheries: Chronic 

Entanglement of Large Whales. Journal of Marine Biology 2012: 230653. 

National Marine Fisheries Service (NMFS). 1998. Recovery plan for the blue whale (Balaenoptera musculus). 

Prepared by Reeves R.R., P.J. Clapham, R.L. Brownell, Jr., and G.K. Silber for the National Marine 

Fisheries Service, Silver Spring, MD. 42 pp.

National Marine Fisheries Service. 2011. Blue Whale (Balaenoptera musculus musculus): Eastern North Pacific 

Stock.

National Marine Fisheries Service. 2014. Blue Whale. Retreived August 18, 2014 from:

http://www.nmfs.noaa.gov/pr/species/mammals/cetaceans/bluewhale.htm. 

National Research Council (NRC). 2003. Ocean Noise and Marine Mammals. Washington: National Academy 

Press. 204 pp.

National Research Council (NRC). 2005. Marine Mammal Populations and Ocean Noise: Determining When Noise 

Causes Biologically Significant Effects. Committee on Characterizing Biologically Significant Marine

Mammal Behavior. National Academies Press, Washington, DC. 142 pages.

Parks, S.E., C.W. Clark, P.L. Tyack. 2007. Short and long-term changes in right whale calling behavior: the 

potential effects of noise on acoustic communication. Journal of Acoustical Society of America. 122:3725- 

31. 

Rolland, R.M., S.E. Parks, K.E. Hunt, M. Castellote, P.J. Corkeron, D.P. Nowacek, S.K. Wasser and S.D. Kraus. 

2012. Evidence that ship noise increases stress in right whales. Proc. R. Soc.B. 

doi:10.1098/rspb.2011.2429.

Sanctuary Integrated Monitoring Network (SIMoN). 2006. Special Status Species: Blue Whale. Retrieved July 24, 

2014, from: http://sanctuarysimon.org/monterey/sections/specialSpecies/blue_whale.php#range. 

Steiger G.H. and J. Calambokidis. 2000. Reproductive rates of humpback whales off California. Marine Mammal 

Science 16:220-239.

Trumble, S.J., E.M. Robinson, M. Berman-Kowalewski, C.W. Potter, and S. Usenko. 2013. Blue whale earplug

reveals lifetime contaminant exposure and hormone profiles. PNAS 110: 16922.

130
Blue Rockfish (Sebastes mystinus)1

Executive Summary Blue rockfish is a medium-sized, 

midwater rockfish important in both the 

recreational and commercial catches in 

California, and is the most abundant 

rockfish in central California kelp 

forests (CDFG 2010). The species 

occurs from Alaska to Baja California, from surface waters to a maximum depth of 600 meters. 

Key climate sensitivities identified by workshop participants for the blue rockfish include 

dissolved oxygen, pH, salinity, and the Pacific Decadal Oscillation, and key non-climate 

sensitivities include harvest, energy production, and oil spills. Blue rockfish exhibit a 

transcontinental geographic extent and a stable, continuous population that is at abundant levels. 

The species has a relatively high dispersal capability for both the larval and adult stages, and 

exhibits relatively moderate-high diversity in life history strategies, genetics, and 

phenotypic/behavioral plasticity. The societal value for blue rockfish is moderate-high due to its 

value for harvest, recreational diving and tourism, but managers may have difficulty in managing 

this species due to the inability to control the impacts expected from climate change, which will 

likely outweigh any manageable impacts such as harvest and pollution. 

Sensitivity 

I. Sensitivity to climate and climate driven changes Climate and climate-driven changes identified (score2

, confidence3): dissolved oxygen (DO) 

levels (5, high), ocean pH (4, low), salinity (4, moderate), Pacific Decadal Oscillation (PDO) (4, 

high), sea surface temperature (3, moderate), dynamic ocean conditions 

(currents/mixing/stratification) (2, moderate-high) 

Climate and climate-driven changes that may benefit the species: sea surface temperature

Description of benefit: Increased sea surface temperatures may promote more jellyfish 

production, which are prey for blue rockfish, increasing food supplies. Increasing sea surface 

temperatures may also result in increased distribution of blue rockfish. 

Overall species sensitivity to climate and climate-driven factors: Moderate-High

• Confidence of workshop participants: Moderate

Supporting literature

Literature review was conducted for those factors scoring 3 or higher, although the other 

sensitivities identified should also be considered. 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Blue Rockfish Score Confidence 

Sensitivity 3 Moderate 3 High

Exposure 3 Moderate 2 Moderate

Adaptive Capacity 4 Moderate-High 3 High

Vulnerability 3 Moderate 3 High

131
Sea surface temperature

Enhanced ocean temperatures impact fish physiology by increasing the organism’s oxygen 

demands (Portner and Knust 2007), reducing oxygen solubility in seawater, reducing the 

performance of energy metabolism proteins (Fields et al. 1999) and negatively impacting growth 

and respiration (Largier et al. 2010). Changes in temperature can also impact rockfish age to 

maturity and consumption (Harvey 2009). Shifts in the latitudinal and depth distribution of 

fishes are also expected as water temperature increases, depending on species tolerance (Largier 

et al. 2010). Warmer water temperature, due to El Niño conditions, have been shown to 

negatively impact female rockfish fecundity and growth rates, and repeated exposure to El Niño 

events may result in delay of maturation age, which can result in the reduction of lifetime egg 

production (Harvey 2005). 

Salinity

In a salinity study in southern California, varying salinity levels were found to have no affect on 

juvenile and adult rockfish (various species) (Weston Solutions 2012). However, as nonmigratory residents of kelp and rocky reef habitats during juvenile and adult life stages (Burford 

et al. 2011), blue rockfish may be indirectly affected by salinity changes that affect habitat 

structure, ecosystem processes, or marine food webs (Bodkin et al. 1987).4

Dissolved oxygen (DO) levels 

Significant changes to dissolved oxygen (DO) can result from a number of physical and 

biological processes, including circulation, ventilation, air-sea exchange, production and 

respiration (Keeling and Garcia 2002, Deutsch et al. 2005, Bograd et al. 2008). A decline in 

midwater oceanic DO is predicted due to enhanced stratification and reduced ventilation 

(Sarmiento et al. 1998, Keeling and Garcia 2002). Areas adjacent to upwelling centers like Point 

Arena are particularly susceptible to low DO levels as the upwelling process naturally delivers 

low oxygen water onto the continental shelf from the deep ocean (Largier et al. 2010). DO 

levels under 2 mg/L have been observed to negatively impact rockfish prey sources (NMFS 

2013), lead to mass mortality events (Palsson et al. 2008), and alter rockfish behavior and habitat 

use through movement to more tolerable conditions at shallower depths (Palsson et al. 2005). 

Though there is little information regarding habitat requirements of rockfish larvae, the larval 

stages of many other fish species are vulnerable to low DO (Boehlert and Morgan 1980, NMFS 

2013). 

Ocean pH

The direct effects of decreased pH on fishes within the study region are not well understood 

(Largier et al. 2010), though one study outside of the region documented the impact of lower pH 

levels on larval clownfish olfactory cues, which caused disorientation (Munday et al. 2009). 

Altered behavioral responses, in the form of increased time spent seeking refuge, have recently 

been documented in juvenile rockfish when exposed to lower pH waters (7.75; projected for the 

next century in California) for one week, with recovery of normal behavior taking 12 days after a 

return to seawater at a normal pH level. The cause was traced to altered ion concentration in the 

blood, which impacts the fish’s sensory system (Hamilton et al. 2013). 

4 For more information on salinity impacts in relevant habitats, please see the Kelp Forest, Nearshore, and/or the 

Offshore Rocky Reef habitat summaries.

132
Pacific Decadal Oscillation (PDO)

The PDO is a longer-term fluctuation (20-40 years) in ocean climate (Trenberth 1990). During 

the warm (positive) PDO phase, climate change impacts are expected to be exacerbated, 

including enhanced warming of surface waters, increased rainfall, erosion and run-off, and 

reduced upwelling (Largier et al. 2010). Seabird diet studies have shown a decrease in the 

availability of juvenile rockfish during warm (positive) PDO periods (Miller and Sydeman 

2004), and reduced fecundity of female rockfish (as well as reduced growth rate) was correlated 

with changes in ocean circulation and temperature, likely a result of reduced food supply 

(Harvey 2005). 

II. Sensitivity to disturbance regimes

Disturbance regimes identified: disease and storms

Overall species sensitivity to disturbance regimes: Moderate-High

• Confidence of workshop participants: High

Additional participant comments

Storms may cause loss of prime habitat (kelp forests) which will impact blue rockfish 

recruitment and survival, and increase turbulence that exacerbates kelp dislodgement and 

sedimentation that may reduce the recovery of storm-damaged forests. 

Supporting literature

Disease

Disease is projected to increase with warming water temperatures, due to enhanced pathogen 

development and survival, as well as host susceptibility (Harvell et al. 2002). Blue rockfish have 

no known diseases, but may be indirectly impacted by disease through their dependence on the 

kelp forest habitat. 

III. Dependencies 

Species dependence on one or more sensitive habitat types: Moderate-High

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: kelp forest and nearshore habitat 

Species dependence on specific prey or forage species: Low-Moderate 

• Confidence of workshop participants: High 

Other critical dependencies: oceanographic conditions 

• Degree of dependence: Low-Moderate

• Confidence of workshop participants: High

Specialization of species (1=generalist; 5=specialist): 3

• Confidence of workshop participants: High 

Additional participant comments

Blue rockfish are dependent on productive oceanographic conditions, including upwelling and 

cool surface waters for reproductive success. This species does not recruit well with poor 

upwelling and during El Niño events. 

133
Supporting literature

Blue rockfish are dependent on kelp forest and nearshore habitat for recruitment of young-ofyear fish and for protection and abundant food for adults (CDFG 2010). The species is less 

dependent on a specific food source, feeding on a variety of jellyfish, tunicates, algae, and small 

fish (CDFG 2010). 

IV. Sensitivity and exposure to non-climate stressors Non-climate stressors identified (score5

, confidence6): harvest (4, high), energy production (3, 

moderate), and pollution (oil spills) (3, moderate) 

Overall species sensitivity to non-climate stressors: Moderate

• Confidence of workshop participants: High

Overall current exposure to non-climate stressors: Low-moderate

• Confidence of workshop participants: Low

Additional participant comments

Although currently well-managed, including the use of marine protected areas to protect some 

stocks, blue rockfish are vulnerable to management error via poor recruitment. Oil spills would 

have direct impacts to the species and indirect impacts to the habitat and ecological relationships 

of blue rockfish. 

Supporting literature

Harvest

Although well managed in marine protected areas, blue rockfish may become more vulnerable to 

fishing pressure as climate impacts alter their basic physiology, including age to maturity, 

fecundity and growth rate (Helmuth et al. 2010). Managers will need to take into account the 

diverse and complex impacts of climate stressors on blue rockfish when assessing stocks 

(Helmuth et al. 2010). 

Energy production 

An emerging potential issue in the region is the production of wave energy conversion devices 

(Largier et al. 2010). These structures may impact nearshore wave energy and wave-driven 

processes, which could impact species zonation, distribution and abundance in the nearshore 

environment of the study region (Largier et al. 2010). Construction and maintenance of energy 

production devices, including associated cables to shore, could also have direct impacts on the 

region through entrainment of organisms such as young-of-year rockfish, increased turbidity, and 

disturbance to the seafloor (Nelson et al. 2008). 

Pollution (oil spills)

Over 6,000 commercial vessels transit in and out of San Francisco Bay every year, with 5% of 

these as large cargo vessels that can carry up to one million gallons of bunker fuel (GFNMS 

2008). All transiting vessels, including military, research and fishing vessels, carry crude oil or 

fuel, posing a potential risk to resources in the region (Largier et al. 2010). After the 1989 

5 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

6 Confidence level indicated by workshop participants.

134
Exxon Valdez oil spill in Prince William Sound, Alaska, demersal rockfish species were the only 

fish species found dead in significant numbers, likely due to elevated hydrocarbon metabolites 

(Marty et al. 2003). 

V. Other sensitivities: none identified

Adaptive Capacity

I. Extent, Status, and Dispersal Ability

Geographic extent of the species (1=endemic; 5=transboundary): 5 

• Confidence of workshop participants: High

Population status of the species (1=endangered; 5=robust): 4 

• Confidence of workshop participants: High

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 5 

• Confidence of workshop participants: High

Dispersal ability of the species: Moderate-High 

• Confidence of workshop participants: High

Maximum annual dispersal distance: Larval dispersal 75-100km; adult dispersal 5-25km 

• Confidence of workshop participants: Moderate

Supporting literature

The blue rockfish is the most common species of nearshore rockfish in California (SIMoN 

2014); however, the southern population (south of Cape Mendocino) is less stable and likely 

decreasing as compared to the northern population, due to fishing pressure and environmental 

variability (Cope 2004). The species has a moderate-high dispersal capability, with most research 

indicating adult movement of less than 6 miles (CDFG 2010). 

II. Intraspecific/Life History Diversity

Diversity of life history strategies: Moderate

• Confidence of workshop participants: High

Genetic diversity: Moderate-High

• Confidence of workshop participants: Moderate-High

Behavioral plasticity: Moderate

• Confidence of workshop participants: Low

Phenotypic plasticity: Moderate

• Confidence of workshop participants: Moderate

Overall degree of diversity/plasticity of the species: Moderate

• Confidence of workshop participants: Moderate

135
Supporting literature

Blue rockfish spawn once per year, take two to five years to reach sexual maturity, produce 

relatively few offspring and have high parental investment (Vulnerability Assessment Workshop, 

pers. comm., 2014; CDFG 2010). One of the faster growing species of rockfish, blue rockfish 

have been aged to a maximum of 44 years (CDFG 2010). High levels of population 

differentiation have been detected throughout the species’ range, with a distinct break in genetic 

differentiation at Cape Mendocino (Cope 2004). Subpopulations north and south of this 

biogeographic barrier have had little contact for thousands of years, suggesting that repopulation 

of the more heavily fished southern population may not be possible from the less-fished northern 

population (Cope 2004). Recent genetic evidence suggests that blue rockfish are actually 

composed of two closely-related species that overlap in range but are behaviorally and 

reproductively isolated, currently described as “blue-sided” and “blue-blotched” (Peterson et. al, 

in review). 

III. Management Potential

Value of species to people: Moderate-High

• Confidence of workshop participants: High

• Description of value: Blue rockfish is valued as a food source by commercial and 

recreational fisheries, and for its aesthetics by recreational divers and tourists 

Likelihood of managing or alleviating climate change impacts on species: Low-Moderate

• Confidence of workshop participants: Low

• Description of potential management options: None provided. Climate factors will 

primarily drive the success of this species, not necessarily the more manageable nonclimate factors of harvest and pollution. 

Supporting literature

Blue rockfish is often identified as an important recreational species in California for anglers, 

and is usually the most frequently caught rockfish north of Point Conception (CDFG 2010). 

IV. Other adaptive capacity factors: none identified

Additional participant comments

The overall success of the species will depend on successful recruitment of the species in the 

future.

Exposure 

I. Future climate exposure7 Future climate and climate-driven changes identified (score8

, confidence9): Changes in El Niño 

events (5, moderate), increased storminess (4, high), decreased pH (3, high), changes in sea 

7 Supporting literature for future exposure to climate factors is provided in the introduction.

8 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

9 Confidence level indicated by workshop participants.

136
surface temperature (2, moderate), changes in salinity (1, moderate), decreased dissolved oxygen 

(DO) levels (1, moderate) 

Degree of exposure to future climate and climate-driven changes: Moderate

• Confidence of workshop participants: Low-Moderate 

Literature Cited

Behrens, M.D. and K.D. Lafferty. 2004. Effects of marine reserves and urchin disease on southern Californian rocky 

reef communities. Mar Ecol Prog Ser 279: 129-139.

Bodkin, J. L., G. R. VanBlaricom and R. J. Jameson. 1987. Mortalities of kelp-forest fishes associated with large 

oceanic waves off central California, 1982–1983. Environmental Biology of Fishes 18 (1):73-76.

Burford, M. O., G. Bernardi and M. H. Carr. 2011. Analysis of individual year-classes of a marine fish reveals little 

evidence of first-generation hybrids between cryptic species in sympatric regions. Marine Biology 158 

(8):1815-1827.

California Department of Fish and Game (CDFG). 2010. Abbreviated Life History of Blue Rockfish. Retrieved July 

18, 2014 from: https://www.dfg.ca.gov/marine/nearshorefinfish/bluerockfish.asp. 

Cope, J.M. 2004. Population genetics and phylogeography of the blue rockfish (Sebastes mystinus) from 

Washington to California. Canadian Journal of Fisheries and Aquatic Sciences 61(3): 332-342.

Fields, P.A., J.B. Graham, R.H. Rosenblatt, G.N. Somero. 1999. Effects of expected global climate change on 

marine faunas. Trends in Ecology and Evolution 8:361-367. 

Gulf of the Farallones National Marine Sanctuary (GFNMS). 2008. Management Plan. 

http://farallones.noaa.gov/manage/plan.html#plan. 

Hamilton, T.J., Holcombe, A. and Tresguerres, M. 2013. CO2-induced ocean acidification increases anxiety in 

Rockfish via alteration of GABAA receptor functioning. Proceedings of the Royal Society B: Biological 

Sciences 281(1775).

Harvell, C.D., C.E. Mitchell, J.R. Ward, S. Altizer, A.P. Dobson, R.S. Ostfeld and M.D. Samuel. 2002. Climate 

warming and disease risks for terrestrial and marine biota. Science 296:2158-2162.

Harvey, C.J. 2005. Effects of El Niño Events on Energy Demand and Egg Production of Rockfish (Scorpaenidae: 

Sebastes): A Bioenergetics Approach. Fishery Bulletin 103 (71):71-83.

Harvey, C.J. 2009. Effects of Temperature Change on Demersal Fishes in the California Current: A Bioenergetics 

Approach, Canadian Journal of Fisheries and Aquatic Sciences 66: 1449-56.

Helmuth, B., L. Yamane, K.J. Mach, S. Chhotray, P. Levin, S. Woodin. 2010. All Climate Change is Local: 

Understanding and Predicting the Effects of Climate Change from an Organism’s Point of View. Stanford 

Journal of Law, Science and Policy 2(1). 

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Marty, G.D., A. Hoffman, M.S. Okihiro, K. Hepler and D. Hanes. 2003. Retrospective analysis: bile hydrocarbons 

and histopathology of demersal rockfish in Prince William Sound, Alaska, after the Exxon Valdez oil spill. 

Marine Environmental Research 56(5): 569-584.

Miller, A. K. and W. J. Sydeman. 2004. Rockfish response to low-frequency ocean climate change as revealed by 

the diet of a marine bird over multiple time scales. Marine Ecology Progress Series 281: 207-216. 

Munday, P.L, D.L. Dixson, J.M. Donelson, G.P. Jones, M.S. Pratchett, G.V. Devitsina, and K.B. Døving. 2009. 

Ocean acidification impairs olfactory discrimination and homing ability of a marine fish. Proceedings of 

the National Academy of Sciences 106:1848-1852. 

Nelson PA, D Behrens, J Castle, G Crawford, RN Gaddam, SC Hackett, J Largier, DP Lohse, KL Mills, PT 

Raimondi, M Robart, WJ Sydeman, SA Thompson, S Woo. 2008. Developing Wave Energy In 

Coastal California: Potential SocioEconomic And Environmental Effects. California Energy 

Commission, PIER Energy-Related Environmental Research Program & California Ocean Protection 

Council CEC-500-2008-083. 

Petersen, C.H., L. Gilbert-Horvath, D. Pearson, and J.C. Garza. Sympatric distribution and incipient speciation 

among blue rockfish (Sebastes mystinus) in central California. Molecular Ecology. In review. 

Portner, H.O. and R. Knust. 2007. Climate change affects marine fishes through the oxygen limitation of thermal 

137
tolerance. Science 315:95-97. 

Sanctuary Integrated Monitoring Network (SIMoN). Sebastes mystinus – Blue Rockfish. Retrieved July 24, 2014 

from: http://sanctuarysimon.org/species/sebastes/mystinus/blue-rockfish. 

Trenberth, K.E. 1990. Recent observed interdecadal climate changes in the northern-hemisphere. Bulletin of the 

American Metereological Society 71:988-993. 

Weston Solutions, Inc. 2012. High Salinity Sensitivity Study: Short- and Long-Term Exposure Assessments. 

Oakland, CA.

138
California Hydrocoral (Stylaster californicus) and Red Sponge

(Ophlitaspongia pennata)

1

Executive Summary The California hydrocoral and red 

sponge are important deep-water 

habitat-forming invertebrates for 

benthic communities of offshore banks, 

ranging from British Columbia to Baja 

California, Mexico. The hydrocoral is 

restricted to depths of 30-75 meters, 

whereas the red sponge is observed from these depths up to the intertidal zone. Relatively little 

information exists regarding these deep-water species, especially experimental data regarding 

climate impacts. Key climate sensitivities identified for these species by workshop participants 

include dissolved oxygen, pH, and dynamic ocean conditions (currents/mixing/upwelling), and 

key non-climate sensitivities include pollution and poisons, harvest and invasive species. 

Hydrocorals and sponges exhibit patchy distributions across their range and populations that are 

diminished, but generally stable. Both species may have limited dispersal due to their short 

larval stage. Genetic, behavioral, and morphological diversity is not well studied, though some 

examples of phenotypic plasticity have been documented. The societal value for the California 

hydrocoral and red sponge is considered moderate-high due to their function as critical 

components of offshore reef communities and valuable habitat/protection for juvenile fishes, but 

the likelihood of managing or alleviating climate impacts was rated as low-moderate.

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): dynamic ocean conditions 

(currents/mixing/stratification) (4, high), dissolved oxygen (DO) levels (3, low), pH (3, low) 

Climate and climate-driven changes that may benefit the species: ocean temperature

• Description of benefits: Changes in ocean temperatures can affect the distribution of 

these species.

Overall species sensitivity to climate and climate-driven factors: Low-Moderate

• Confidence of workshop participants: Moderate 

Additional participant comments

There are few climate factors that impact these species, but they are highly sensitive to those that 

do.

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

California Hydrocoral 

and Red Sponge

Score Confidence 

Sensitivity 3 Moderate 2 Moderate

Exposure 3 Moderate 3 High

Adaptive Capacity 3 Moderate 3 High

Vulnerability 3 Moderate 3 High

139
Supporting literature

Oxygen

When dissolved oxygen (DO) concentrations fall to hypoxic levels, there are severe 

consequences for offshore benthic communities, as the oxygen depleted water mass suffocates 

everything that cannot move out of the area, including corals and sponges (Largier et al. 2010). 

Areas adjacent to upwelling centers like Point Arena are particularly susceptible to low DO 

levels as the upwelling process naturally delivers low oxygen water onto the continental shelf 

from the deep ocean (Largier et al. 2010). 

pH 

Ocean acidification leads to decreased skeleton production in hydrocorals due to the 

undersaturation of aragonite, which is required for calcification. Because these organisms are 

found in deeper water, the exposure to low-pH water associated with upwelling events will likely 

be more immediate (Largier et al. 2010). Decline in the biomass of plankton will also affect 

deeper benthic communities, especially hydrocorals that feed largely on plankton. Ocean 

acidification may also impact coral and sponge larval stages during the developmental phase of 

their early life history, as has been experimentally demonstrated for copepods, urchins and 

mussels (Kurihara et al. 2004). 

Dynamic ocean conditions (currents/mixing /upwelling

Corals and sponges depend on currents to deliver food, so any significant disruption to the timing 

or intensity of seasonal upwelling winds resulting in reduced productivity over time would have 

negative impacts on long term survival of benthic animals (Largier et al. 2010). These species 

spend the first part of their lives as free-floating plankton, which facilitates dispersal, feeding and 

predator avoidance, and change in the timing or magnitude of seasonal winds driving coastal 

upwelling could reduce coral and sponge larval survival (Largier et al. 2010). 

II. Sensitivity to disturbance regimes: none identified 

III. Dependencies

Species dependence on one or more sensitive habitat types: High

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: rocky substrate 

Species dependence on specific prey or forage species: Low-Moderate 

• Confidence of workshop participants: Moderate 

Other critical dependencies: none 

Specialization of species (1=generalist; 5=specialist): 3

• Confidence of workshop participants: Low

Supporting literature

An additional dependency, as noted in the climate impacts section, for both species is the 

consistency of currents to provide an abundant food supply (ONMS 2009): microzooplankton, 

bacterial particulates, and small particulate organic matter for the hydrocoral, and dissolved 

organic matter for sponges. 

140
IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): invasive species (5, high), pollution and 

poisons (4, high), harvest (4, high) 

Overall species sensitivity to non-climate stressors: High

• Confidence of workshop participants: High

Overall species exposure to non-climate stressors: Low

• Confidence of workshop participants: High 

Supporting literature

Pollution and poisons 

Runoff of sediments, contaminants, and nutrients from agriculture, industry, sewage, and land 

clearing have been documented to cause extensive damage to coral and sponge species in 

tropical coral reefs worldwide by reducing recruitment, reducing growth and calcification, 

encouraging the growth of benthic competitors, and causing hypoxic conditions (ISRS 2004). 

However, because of the offshore nature of these banks and the distance from population centers 

on the mainland, water quality is considered to be in fairly good condition (ONMS 2009). Oil 

spills continue to pose a threat to the health of this ecosystem, and there have been several large 

spills in the region over the last decade (ONMS 2009). 

Harvest

The impacts from harvest on corals and sponges largely results from the use of bottom-tending 

gear (Vulnerability Assessment Workshop, pers. comm., 2014) and lost fishing gear that has 

been documented entangling these species (ONMS 2009). Significant amounts of derelict fishing 

gear have been documented in rocky areas of Cordell Bank and in surveys from 2001-2005, 

fishing gear was consistently observed on the bottom, with long-lines and gill nets the most 

common gear type observed (ONMS 2009). This gear becomes entangled on high relief areas 

that are frequently covered with hydrocorals and sponges. As 86% of Cordell Bank NMS’s 

boundaries are now closed to some type of bottom-tending gear, the condition of biologically 

structured habitats should improve (ONMS 2009). 

Invasive Species

A number of non-native species are present in the vicinity of offshore benthic communities in the 

study region, but none are currently confirmed to exist in these habitats. However, there is some 

concern regarding an invasive tunicate, Didemnum sp. that has been observed in nearby coastal 

areas (Tomales and Bodega Bays) and has covered large areas of Georges' Bank on the east coast 

(Bullard et al. 2007). The invasive tunicate is similar to a native Didemnum species, and is 

known to spread rapidly and overgrow native benthic species, including corals and sponges 

(Bullard et al. 2007). Sampling will be necessary to determine which species is present on 

offshore banks in the study region (ONMS 2009). 

V. Other sensitivities: none identified 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

141
Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 3

• Confidence of workshop participants: High 

Population status of the species (1=endangered; 5=robust): 3

• Confidence of workshop participants: Moderate 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 3

• Confidence of workshop participants: Moderate 

Dispersal ability of the species: Moderate-High 

• Confidence of workshop participants: High 

Maximum annual dispersal distance: no answer provided 

Supporting literature

Though these species were identified as having moderate-high dispersal capability by workshop 

participants, the literature indicates that dispersal may be limited. Studies of related Alaskan 

hydrocoral species indicated a very short larval lifespan that led to settlement in close proximity 

to the parent colony, unless sufficiently strong currents are able to transport larvae long distances 

in a short amount of time (Brooke and Stone 2007). Limited dispersal implies potential recovery 

of a colony that has experienced light disturbance, but limited capability for the recovery and recolonization of seriously impacted areas (Brooke and Stone 2007). Similarly, most sponge 

larvae have a short dispersal period, usually less than three days, before settling, and will spend a 

few hours in a “creeping” stage to find suitable habitat (Shanks 2001). 

II. Intraspecific/Life history diversity

No information or ratings for these characteristics of diversity were provided by workshop 

participants, as much of this information is unknown at this time for these species. 

Supporting literature

Understanding the genetic diversity of the California hydrocoral is complicated by its variable 

morphology (including coloration and branching pattern), and recent analysis suggests that the 

deep-water species considered here may be genetically the same as the intertidal Stylantheca 

porphyra encrusting coral (Cairns and Macintyre 1992). Behavioral plasticity is likely low for 

both species as they are sessile organisms that are not able to escape exposure to stressors. 

However, some indications of phenotypic plasticity can be found for these species, including the 

morphological variation seen in hydrocorals (mentioned above), the ability to asexually 

reproduce from fragments by the red sponge, and the ability for cyclosystems on hydrocorals 

(small openings in the tissue that house the stinging tentacles used for feeding) to rapidly 

regenerate on damaged branches (Ostarello 1973). 

Hydrocorals have slow growth rates, long lives, and internal fertilization with brooded larvae 

(Brook and Stone 2007). Studies indicate a short larval lifespan (3-8 hours) with larvae 

dispersing very short distances and settling near the parent colony (Ostarello 1973, Fritchman 

1974). It is unknown how long it takes for hydrocorals to reach reproductive maturity or how 

frequently they can reproduce (Vulnerability Assessment Workshop, pers. comm., 2014), though 

142
studies of related Alaskan species indicate that reproduction is either continuous or seasonal and 

protracted (Brook and Stone 2007). The red sponge reproduces both sexually through broadcast 

spawning, and asexually through fragmentation (regeneration from a broken off fragment, 

Shanks 2001). 

III. Management potential

Value of species to people: Moderate-High

• Confidence of workshop participants: High 

• Description of value: Valued for their function as critical components of offshore reef 

communities and valuable habitat for juveniles of several commercially important species 

of groundfish 

Likelihood of managing or alleviating climate change impacts on species: Low-Moderate

• Confidence of workshop participants: Moderate 

• Description of possible management options: none identified because it will be difficult 

to mitigate for oceanographic conditions such as changing pH, temperature, and altered 

currents/mixing that will likely affect corals and sponges

IV. Other adaptive capacity factors: none identified 

Exposure 

I. Future climate exposure6

Future climate and climate-driven changes identified: decreased pH (4, high), changes in sea 

surface temperature (3, high), altered currents/mixing (3, high), decreased dissolved oxygen 

(DO) levels (2, low) 

Degree of exposure to future climate and climate-driven changes: Moderate

• Confidence of workshop participants: Moderate 

Literature Cited 

Bullard, S.G., G. Lambert, M.R. Carman, J. Byrnes, R.B. Whitlatch, G. Ruiz, R.J. Miller, L. Harris, P.C. Valentine, 

J.S. Collie, J. Pederson, D.C. McNaught, A.N. Cohen, R.G. Asch, J. Dijkstra and K. Heinonen. 2007. The 

colonial ascidian Didemnum sp. A: current distribution, basic biology and potential threat to marine 

communities of the Northeast and West coasts of North America. Journal of Experimental Biology and 

Ecology 342:99-108.

Brooke, S. and R. Stone. 2007. Reproduction of deep-water hydrocorals (family Stylasteridae) from the Aleutian 

Islands, Alaska. Bulletin of Marine Science 81(3): 519-532.

Cairns, S.D. and I.G. Macintyre. 1992. Phylogenetic implications of calcium carbonate mineralogy in the 

Stylasteridae (Cnidaria: Hydrozoa). Palaios 7(1):96-107.

Fritchman, H. K. 1974. The planula of the stylasterine hydrocoral Allopora petrograpta (Fisher): its structure, 

metamorphosis and development of the primary cyclosystem. Pages 245–258 in A. M. Cameron, B. M. 

Cambell, A. B. Cribb, R. Endean, J. S. Jell, O. A. Jones, P. Mather and F. H. Talbot, eds. Proc. Second Int. 

Coral Reef Symp. Vol. 2. The Great Barrier Reef Committee, Brisbane, Australia.

ISRS. 2004. The effects of terrestrial runoff of sediments, nutrients and other pollutants on coral reefs. Briefing 

6 Supporting literature for future exposure to climate factors is provided in the introduction.

143
Paper 3, International Society for Reef Studies, pp: 18

Kurihara H., S. Kato, and A. Ishimatsu. 2004. Sub-lethal effects of elevated concentration of CO2 on planktonic 

copepods and sea urchins. Journal of Oceanography 60:743-750.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Office of National Marine Sanctuaries (ONMS). 2009. Cordell Bank National Marine Sanctuary Condition Report 

2009. US Department of Commerce, National Oceanic and Atmospheric Administration, Office of National 

Marine Sanctuaries, Silver Spring, MD. 58 pp.

Ostarello, G. L. 1973. Natural history of the hydrocoral Allopora californica (Verrill 1866). Biol. 

Bull. 145: 548–564.

Shanks, A. L. (ed.) 2001. An Identification Guide to the Larval Marine Invertebrates of the Pacific Northwest. 

Oregon State University Press, Corvallis, OR.

144
California Mussel (Mytilus californianus)1

Executive Summary The California mussel is a bivalve 

invertebrate that forms dense, clustered 

aggregates of individuals in the rocky 

mid-intertidal habitat from Alaska to 

Baja California (SIMoN 2014). Key 

climate sensitivities identified by 

workshop participants include air temperature, salinity, wave action, pH and erosion, and key 

non-climate sensitivities include armoring, pollution and poisons, recreation and introduced 

species. The California mussel exhibits a transcontinental geographic extent, a healthy, 

continuous population, and a high dispersal capability. The entire California mussel population 

is genetically homogenous, but variation in gene expression allows for varied physiological 

responses and local adaptation. The societal value for this species was rated as moderate due to 

harvest and scientific value, and management potential was considered to be low-moderate, with 

some possibility to better manage disturbance from tidepool visitation and to better protect 

upland habitat for migration. 

Sensitivity 

I. Sensitivity to climate and climate driven changes Climate and climate-driven changes identified (score2

, confidence3): air temperature (5, high), 

salinity (5, moderate), wave action (5, high), ocean pH (4, low-moderate), coastal erosion (4, 

low-moderate), sea surface temperature (3, low-moderate), dynamic ocean conditions 

(currents/mixing/stratification) (3, low), sea level rise (3, moderate-high), precipitation (2, low), 

dissolved oxygen (DO) levels (2, low-moderate)

Climate and climate-driven changes that may benefit the species: wave action 

• Description of benefit: Increased wave action could benefit the California mussel by 

negatively impacting Pisaster, one of its major predators. 

Overall species sensitivity to climate and climate-driven factors: High

• Confidence of workshop participants: Moderate

Supporting literature

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

California Mussel Score Confidence 

Sensitivity 3 Moderate 3 High

Exposure 4 Moderate-High 2 Moderate

Adaptive Capacity 3 Moderate 3 High

Vulnerability 3 Moderate 3 High

145
Air temperature

Mussels are well adapted to large variations in temperature exposure due to daily emersion at

low tide, with daily internal body temperature ranges of close to 15 ̊C (Carefoot 1977), and 

annual ranges around 34 ̊C (Elvin and Gonor 1979). Larger individuals, and those growing in 

close clusters, are able to maintain a lower body temperature than others (Helmuth 2008). 

Individuals began to die when body temperature exceeded 36 °C as a function of thermal stress; 

around half were killed by exposure to 38 °C, and all died when their body temperature exceeded 

41 °C (Denny et al. 2011). Body temperature, however, is not solely a function of air 

temperature, and can be impacted by wind velocity, the timing and duration of tides, solar 

irradiation, wave splash and orientation to the sun (Helmuth et al. 2011), so the direct impact of 

increasing air temperature will likely not be straight-forward.

Salinity

Low salinity impacts the survival of mussel gametes and larvae, with susceptibility beginning at 

salinities lower than 300/00 (with seawater typically around 350/00), which may explain why 

this species is not found in brackish water (Young 1941). 

Wave action

Considered the competitive dominant species in wave-exposed rocky shores, mussels are highly 

adapted to high wave action through the use of strong filaments called byssal threads that attach 

them securely to bare rock (SIMoN 2014). Mussels may benefit from an increase in wave action 

if it results in a decrease in the abundance of its main predator, the ochre sea star, or a decrease in 

the overlap of the two species’ tidal extents (Vulnerability Assessment Workshop, pers.comm., 

2014). Recovery from storm disturbance can be fairly rapid if the number of removed 

individuals is small and surrounded by mussels that can move in, or can take 10 years or more if 

entire beds of mussels are removed (Vesco and Gillard 1980, Kinnetics 1992). Enhanced wave 

action may result in the selective removal of larger individuals.

Ocean pH

pH levels predicted to occur by 2100 were found to degrade the mechanical integrity of larval 

mussel shells, which may result in a lengthened larval phase, and/or enhance vulnerability to 

predation and desiccation upon settling on the substrate (Gaylord et al. 2011). In another study, 

elevated pCO2 did not impact adult tissue or shell growth of mytilid mussels (which includes the 

California mussel), but did alter the strength of the byssal threads that attach the mussel to the 

substrate (O’Donnell et al. 2013). Threads were weaker and less extensible, decreasing 

individual tenacity by 40%, which has serious implications for the viability of mussels with 

increased wave action and decreased pH both predicted to occur.

Coastal erosion

Enhanced coastal erosion, due to sea level rise and an increase in wave and storm severity, may 

result in the burying of intertidal habitat (Vulnerability Assessment Workshop, pers. comm., 

2014) and may also impede the ability of intertidal organisms to migrate inland in response to 

rising sea levels (Largier et al. 2010). 

II. Sensitivity to changes in disturbance regimes

Disturbance regimes identified: wind, disease, storms, flooding, and extreme heat events

Overall species sensitivity to disturbance regimes: High

• Confidence of workshop participants: Moderate

146
Additional participant comments

Disease has the potential to greatly impact the California mussel indirectly if the sea star wasting 

syndrome results in decreased abundance of its main predator, the ochre sea star.

Supporting literature

Wind 

Wind is highly desiccating to intertidal organisms and can dry out species that need to retain 

moisture for survival, enhancing the negative impact of increased air temperature (Bell 1995), 

but can also result in lower body temperatures in California mussels due to cooling. 

Disease

In addition to the potential indirect effects of disease as mentioned by workshop participants, a 

general increase in disease is often linked to increases in water temperature, as both pathogen 

survival and host susceptibility are enhanced (Friedman et al. 1997, Harvell et al. 1999, 

Raimondi et al. 2002, Largier et al. 2010). 

Storms

Storms increase physical forces through enhanced wave exposure and increased erosion of 

coastal cliffs that can bury intertidal habitats (see wave action and erosion sections above). 

Flooding 

Flooding may have a similar effect by increasing sedimentation to the intertidal area, but may 

also result in compromised water quality (PISCO 2014), including an increase in harmful algal 

bloom events. 

 

Extreme heat events

Extreme heat events can result in mass mortality of intertidal organisms; though temperature 

interacts with a number of other factors to affect the internal temperature of the California 

mussel (see air temperature section above).

III. Sensitivity and exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): coastal armoring (4, moderate), invasive 

species (4, moderate), pollution and poisons (4, low), recreation (4, low-moderate), land use 

change (3, low), harvest (3, low), boat groundings (3, low-moderate)

Overall species sensitivity to non-climate stressors: Moderate

• Confidence of workshop participants: Low

Overall current exposure to non-climate stressors: Low-moderate

• Confidence of workshop participants: Moderate

Additional participant comments

In addition to invasive species, rocky intertidal organisms, including the California mussel, will 

likely be impacted by species range expansions due to increasing sea surface temperature. Oil 

spills are a component of localized pollution that can smother organisms and inhibit the 

resilience of the rocky intertidal habitat.

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

147
Supporting literature

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. 

Coastal armoring

As sea level rises and increasing coastal erosion threatens the coastal cliffs and bluffs along 

California’s shoreline, bluff revetments and coastal armoring will be more frequently used, and 

the effect depends on the specific armoring structure utilized (Largier et al. 2010). Coastal 

armoring would likely limit the ability of intertidal organisms, including the California mussel, 

to migrate upland or inland with rising sea level, but may also add additional available habitat by 

creating hard substrate (Vulnerability Assessment Workshop, pers. comm., 2014). 

Invasive species

Invasive species effectively out-compete native species and decrease native species diversity and 

abundance. These impacts are more largely felt near harbors, including San Francisco Bay, 

Pillar Point Harbor, and Bodega Harbor. To date, almost 150 species of introduced marine algae 

and animals have been identified in the study region. Invasive species threaten the abundance 

and/or diversity of native species, disrupt ecosystem balance and threaten local marine-based 

economies (SIMoN 2014), and climate change is likely to enhance the negative impacts of 

coastal invaders. Species range expansions have been documented for coastal California, likely 

due to increasing sea surface temperature, including a documented increase in abundance of 10 

to 11 Southern species and a decrease in 5 to 7 Northern species (Barry et al. 1995) and a 

northward range expansion of 300 km (from San Francisco to Cape Mendocino) by volcano 

barnacles (Tetraclita rubescens), a common intertidal species (Connolly and Roughgarden 

1998). The direct impact of these species on the California mussel may be through increased 

competition for space, though more complex ecological interactions and impacts are unknown 

(Vulnerability Assessment Workshop, pers. comm., 2014). 

Pollution and poisons 

Pollutants, including agricultural and livestock waste, wastewater, sewage outfalls, historic 

mining, and industrial wastes, can be carried into the study region via the freshwater outflow 

from San Francisco Bay (Largier et al. 2010), inhibiting the resilience of intertidal habitat and 

stimulating phytoplankton growth. Because mussels are highly efficient filter feeders, the 

concentration of heavy metals and organic pollutants in their tissues is a concern for human 

consumption; harvest of mussels is prohibited from May through October due to red tides, 

blooms of dinoflagellates and diatoms (SIMoN 2014) that are caused, in part, by enhanced 

nutrient run-off.

Recreation

Trampling of the intertidal system by recreational users, researchers and harvesters is a 

documented negative stressor (Largier et al. 2010). The high visitation levels that occur in the 

rocky intertidal habitat (including Pillar Point, Duxbury Reef, Pescadero Point and Salt Point) 

can cause crushing of organisms and changes in the diversity and abundance of organisms 

(Largier et al. 2010). Though there is some indication that mussels remain unaffected by 

trampling (Beauchamp and Gowing 1982), there are many documented instances of negative 

impacts, including reduced percent cover of mussels, reduced adult density, reduced mussel bed 

thickness, and reduced mussel biomass at sites with higher visitation rates compared to lower 

148
visitation rates across the California coast (Brosnan and Crumrine 1994, Smith and Murray 2004, 

Smith et al. 2008, Van De Werfhorst and Pearse 2007). 

IV. Dependencies

Species dependence on one or more sensitive habitat types: Low

• Confidence of workshop participants: High 

Species dependence on specific prey or forage species: Low

• Confidence of workshop participants: High

Other critical dependencies: availability of existing mussel beds or bare rock in the mid-intertidal 

of wave-exposed shores for settling larvae 

• Degree of dependence: High

• Confidence of workshop participants: High

Specialization of species (1=generalist; 5=specialist): 3 

• Confidence of workshop participants: High

V. Other sensitivities: none identified 

Additional participant comments

The overall sensitivity of California mussels is primarily driven by sea level rise. 

Adaptive Capacity

I. Extent, Status, and Dispersal Ability

Geographic extent of the species (1=endemic; 5=transboundary): 5 

• Confidence of workshop participants: High

Population status of the species (1=endangered; 5=robust): 5

• Confidence of workshop participants: Moderate

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 5 

• Confidence of workshop participants: Moderate

Dispersal ability of the species: High 

• Confidence of workshop participants: Moderate

Maximum annual dispersal distance: 50-100km for larvae

• Confidence of workshop participants: High

II. Intraspecific/Life History Diversity

Diversity of life history strategies: Low

• Confidence of workshop participants: High

Genetic diversity: Moderate-High

• Confidence of workshop participants: High

149
Behavioral plasticity: Low

• Confidence of workshop participants: High

Phenotypic plasticity: Moderate

• Confidence of workshop participants: High

Overall degree of diversity/plasticity of the species: Moderate

• Confidence of workshop participants: High

Supporting literature

In contrast to the workshop participants scoring, the literature indicates a nearly genetically 

homogenous population across the entirety of the mussel’s geographic range, due in part to 

extensive gene flow and lack of strong selective gradients (Addison et al. 2008). However, there 

is geographic variation in thermal tolerance, with individuals from the northern-most range 

exhibiting adaptations to cooler conditions (Logan et al. 2012). This variation could not be 

completely attributed to phenotypic plasticity, and the authors concluded that genetic diversity 

(through local adaptation) may be one contributing factor to this variation (Logan et al. 2012). 

Additionally, Place et al. (2008) documented variation in physiological response to emersion 

across the mussel’s range due to significant variation in gene expression. 

III. Management Potential

Value of species to people: Moderate

• Confidence of workshop participants: High

• Description of value: value to the general public for harvest and tidepool recreation, and 

to the scientific community as an important component of rocky intertidal and ecology 

research.

Likelihood of managing or alleviating climate change impacts on species: Low-Moderate

• Confidence of workshop participants: High

• Description of potential management options: manage visitation to decrease trampling 

impacts, and secure upland habitat for migration in response to sea level rise. 

Supporting literature

There is added value for the species due to its role as a critical indicator of water quality, due to 

its efficient filtering capabilities that concentrate organic pollutants and heavy metals in their 

tissues (SIMoN 2014). 

IV. Other adaptive capacity factors: none identified 

Additional participant comments

An additional component to this species’ adaptive capacity that is important to consider is the 

predator-prey relationship with the ochre sea star that will likely be altered by climate impacts. 

Mussel beds are largely limited to expanding to the low intertidal by predation from the ochre 

sea star, so any negative impacts on the sea star due to a changing climate (including enhanced 

disease virulence and wave action) may result in a benefit to the California mussel. 

150
Exposure 

I. Future climate exposure6

Future climate and climate-driven changes identified (score7, confidence8): changes in air 

temperature (5, high), changes in sea surface temperature (5, moderate -high), changes in 

precipitation (5, high), changes in salinity (5, moderate), decreased pH (5, high), sea level rise (5, 

high), increased flooding (3, moderate), altered currents and mixing (4, low- moderate), 

increased storminess (3, moderate), decreased dissolved oxygen (DO) levels (2, low), increased

coastal erosion and runoff (2, moderate) 

Degree of exposure to future climate and climate-driven changes: Moderate-High

• Confidence of workshop participants: Moderate 

Literature Cited 

Addison, J.A., B.S. Ort, K.A. Mesa, G.H. Pogson. 2008. Range-wide genetic homogeneity in the California sea 

mussel (Mytilus californianus): a comparison of allozymes, nuclear DNA markers, and mitochondrial DNA 

sequences. Molecular Ecology 17(19): 4222-32.

Barry, J.P., C.H. Baxter, R.D. Sagarin and S.E. Gilman. 1995. Climate-related, long-term faunal changes in a 

California rocky intertidal community. Science 267:672-675. 

Beauchamp, K.A. and M.M. Gowing. 1982. A quantitative assessment of human trampling effects on a rocky 

intertidal community. Marine Environmental Research 7(4): 279-93.

Bell, E.C. 1995. Environmental and morphological influences on thallus temperature and desiccation of the 

intertidal alga Mastocarpus papillatus Kutzing. JEMBE 191: 29-55.

Brosnan, D.M. and L.L. Crumrine. 1994. Effects of human trampling on marine rocky shore communities. Journal 

of Experimental Marine Biology and Ecology 177(1): 79-97.

Carefoot, T. 1977. Pacific seashores: A guide to intertidal ecology. Seattle: University of Washington Press. 208 pp.

Connolly, S.R. and J. Roughgarden. 1998. A range extension for the volcano barnacle, Tetraclita rubescens. 

California Fish and Game 84:182-183. 

Denny, M.W., W.W. Dowd, L. Bilir, K.J. Mach. 2011. Spreading the risk: Small-scale body temperature variation 

among intertidal organisms and its implications for species persistence. Journal of Experimental Marine 

Biology and Ecology 400: 175-90.

Elvin, O.W. and J.J. Gonor. 1979. The thermal regime of an intertidal Mytilus californianus Conrad population on 

the central Oregon coast. Journal of Experimental Marine Biology and Ecology 39:265-79. 

Friedman, C.S., M. Thomson, C. Chun, P.L. Haaker and R.P. Hedrick. 1997. Withering syndrome of the black 

abalone, Haliotis cracherodii (Leach): Water temperature, food availability, and parasite as possible 

causes. Journal of Shellfish Research 16:403-411.

Gaylord, B., T.M. Hill, E. Sanford, E.A. Lenz, L.A. Jacobs, K.N. Sato, A.D. Russell, A. Hettinger. 2011. Functional 

impacts of ocean acidification in an ecologically critical foundation species. Journal of Experimental 

Biology 214:2586-94.

Harvell, C.D., K. Kim, J.M. Burkholder, R.R. Colwell, P.R. Epstein, D.J. Grimes, E.E. Hofmann, E.K. Lipp, 

A.D.M.E. Osterhaus, R.M. Overstreet, J.W. Porter, G.W. Smith and G.R. Vasta. 1999. Emerging marine 

diseases – climate links and anthropogenic factors. Science 285:1505-1510. 

Helmuth, B. 2008. Intertidal mussel microclimates: Predicting the body temperature of a sessile invertebrate. 

Ecological Monographs 68(1): 51-74. 

Helmuth, B., L. Yamane, S. Lalwani, A. Matzelle, A. Tockstein, N. Gao. 2011. Hidden signals of climate change in 

intertidal ecosystems: What (not) to expect when you are expecting. Journal of Experimental Marine 

Biology and Ecology 400:191-99.

6 Supporting literature for future exposure to climate factors is provided in the introduction. 7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

151
Kinnetics Laboratories, Inc. 1992. Study of the rocky intertidal communities of Central and Northern California. 

Report to the Minerals Management Service. OCS Study MMS 91-0089.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine SanctuariesAdvisory Councils. 121pp. 

Logan, C.A., L.E. Kost, G.N. Somero. 2012. Latitudinal differences in Mytilus califonianus thermal physiology. 

Marine Ecology Progress Series 450: 93-105.

O’Donnell, M.J., M.N. George, and E. Carrington. 2013. Mussel byssus attachment weakened by ocean 

acidification. Nature Climate Change 3: 587-90.

Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO): Rocky Shores. 2014. Retrieved June 18, 2014 

 from: http://www.piscoweb.org/research/rocky-shores. 

Place, S.P., M.J. O’Donnell, G.E. Hofmann. 2008. Gene expression in the intertidal mussel Mytilus californianus: 

physiological response to environmental factors on a biogeographic scale. Marine Ecology Progress Series 

356:1-14.

Raimondi, P. T., C. M. Wilson, R. F. Ambrose, J. M. Engle, and T. E. Minchinton. 2002. Continued declines of 

black abalone along the coast of California: are mass mortalities related to El Niño events? Marine 

Ecology Progress Series 242:143-152.

Sanctuary Integrated Monitoring Network (SIMoN). 2014. California Mussel. Retrieved July 28, 2014 from: 

http://sanctuarysimon.org/species/mytilus/californianus/california-mussel.

Smith, J.R. and S.N. Murray. 2005. The effects of experimental bait collection and trampling on a Mytilus 

Californianus mussel bed in southern California. Marine Biology 147(3): 699-706.

Smith, J.R., P. Fong, and R.F. Ambrose. 2008. The Impacts of Human Visitation on Mussel Bed Communities 

Alongthe California Coast: Are Regulatory Marine Reserves Effective in Protecting These Communities? 

Environmental Management 41(4): 599-612.

Van De Werfhorst, L.C. and J.S. Pearse. 2007. Trampling in the rocky intertidal of central California: a follow-up 

study. Bulletin of Marine Science 81(2): 245-254.

Vesco, L.L. and R. Gillard. 1980. Recovery of benthic marine populations along the Pacific Coast of the United 

States following man-made and natural disturbances including pertinent life history information. U.S. 

Department of the Interior, Bureau of Land Management Service, POCS Reference Paper No. 53-54.

Young, R.T. 1941. The distribution of the mussel (Mytilus californianus) in relation to the salinity of its 

environment. Ecology 22:379-86.

152
Cassin’s Auklet (Ptychoramphus aleuticus)

1

Executive Summary

The Cassin’s auklet is a resident

zooplanktivorous seabird that 

spends a majority of life at sea, 

coming ashore only to breed on 

offshore islands. Key climate 

sensitivities identified by 

participants include sea surface temperature, dynamic ocean conditions 

(currents/mixing/stratification), and extreme weather events, and key non-climate sensitivities

include oil spills and invasive rodents. Cassin’s auklets have a transcontinental geographic 

extent, with diminished but generally stable populations within the study region and high 

population connectivity. The Farallon Islands breeding colonies have experienced significant 

declines, and future population declines are projected due to shifting oceanographic conditions 

and associated impacts on marine food webs. Cassin’s auklets have a moderate-high dispersal 

ability with a maximum annual dispersal distance of over 100 km. Cassin’s auklets have 

moderate-high life history strategy diversity, low-moderate genetic diversity (within the study 

region), and moderate behavioral and phenotypic plasticity. Cassin’s auklets were evaluated to 

be of low societal value and to have a low likelihood of managing or alleviating climate impacts. 

Potential management options to protect breeding populations of this species include eradicating 

house mice on Southeast Farallon Island, eradicating invasive plant species and restoring native 

vegetation on breeding colony islands to facilitate soil stabilization for burrowing, and reducing 

recreational and vessel disturbance.

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): extreme weather events (4, 

high), sea surface temperature (3, high), dynamic ocean conditions 

(currents/mixing/stratification) (3, moderate), salinity (for prey species) (2, low), oxygen (for 

prey species) (2, low), pH (for prey species) (2, low), sea level rise (2, high), coastal erosion (2, 

moderate), air temperature (1, moderate), precipitation (1, high), wave action (1, moderate)

Climate and climate-driven changes that may benefit the species: sea surface temperature and 

dynamic ocean conditions 

• Description of benefit: Increased upwelling, ocean cooling, and stronger and/or 

repositioned currents could all benefit the Cassin’s auklet by enhancing marine food webs 

Overall species sensitivity to climate and climate-driven factors: Low-Moderate

• Confidence of participants: Moderate

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by participants.

Cassin’s Auklet Score Confidence

Sensitivity 4 Moderate-High 3 High

Exposure 2 Low-Moderate 2 Moderate

Adaptive Capacity 3 Moderate 3 High

Vulnerability 3 Moderate 3 High

153
Additional participant comments

Cassin’s auklets were evaluated to have low-moderate sensitivity to a variety of climate and 

climate-driven factors, and are mainly sensitive to factors that affect their prey base or burrow 

habitat, such as sea surface temperature, currents/mixing/stratification, and extreme weather 

events

Supporting literature

Literature review was conducted for those factors scoring 3 or higher, although the other 

sensitivities identified should also be considered. 

Extreme Weather Events

Extreme rainfall can flood low-lying areas and burrows, causing egg or chick mortality (Point 

Blue, pers. comm., 2014, Sydeman, pers. comm., 2014). 

Sea Surface Temperature

Sea surface temperatures reflect general ocean conditions, and can have indirect impacts on the 

Cassin’s auklet through altering ecological interactions (i.e., prey availability) (Sydeman, pers. 

comm., 2014). For example, warmer ocean temperatures resulted in a 90% reduction in 

zooplankton biomass (Roemmich and McGowan 1995), potentially contributing to the major 

decline of the Farallon Island Cassin’s auklet population during the early 1970s to late 1980s 

(Ainley et al. 1994). Further, abundance of North Pacific krill (Euphausia pacifica), a key prey 

species for Cassin’s auklets, is thought to be negatively correlated with the Pacific Decadal 

Oscillation (PDO) and sea surface temperature, declining during warm ocean periods (Brinton 

and Townsend 2003). Major basin-scale shifts in oceanographic conditions, such as shifts in the 

Southern Oscillation Index (SOI), El Niño Southern Oscillation (ENSO), and PDO can affect sea 

surface temperature and other oceanographic conditions, impacting demographic patterns of 

Cassin’s auklets. For example, Lee et al. (2007) found that survival, breeding propensity, 

breeding success, and recruitment all decreased for the Southeast Farallon Island Cassin’s auklet 

population during El Niño years, likely as a result of climate-driven perturbations in local food 

webs. In comparison, La Niña years increased survival and reproduction (Lee et al. 2007). 

Dynamic ocean conditions (currents/mixing/stratification) 

The Cassin’s auklet is a zooplanktivore that forages within the California Current System (CCS) 

(Lee et al. 2007). The CCS has highly variable productivity, and is largely influenced by SOI and 

ENSO patterns (Goericke et al. 2004, Lee et al. 2007) and equatorial wind-driven upwelling 

(Huyer 1983). Productivity patterns tend to be current-wide, affecting Cassin’s auklets 

throughout their range (Lee et al. 2007). Changes in currents, mixing, and stratification in 

conjunction with shifts in upwelling and other ocean conditions (i.e., sea surface temperature, 

salinity, pH) can affect the Cassin’s auklet by affecting marine productivity and prey availability 

(Lee et al. 2007, Sydeman, pers. comm., 2014). For example, breeding success and recruitment 

increased after 1998 as a result of stronger upwelling and mixing mechanisms and higher marine

productivity (Peterson and Schwing 2003, Goericke et al. 2004). 

154
II. Sensitivities to disturbance regimes

Disturbance regimes identified: disease, storms, flooding, drought 

Overall species sensitivity to disturbance regimes: Moderate-High

• Confidence of participants: High 

Supporting literature

As colonial nesters (Harfenist 2004), infectious disease can spread rapidly and extensively. 

Storms, bringing precipitation and higher wave heights, could contribute to the flooding of lowlying breeding habitat and burrows, causing egg or chick mortality (Point Blue pers. comm., 

2014). Higher winds during storms can also decrease foraging success, requiring longer foraging 

effort (Bailey and Kaiser 1993, Ronconi and Hipfner 2009). Drought could affect vegetation that 

stabilizes burrows (Adams 2008). 

III. Dependencies

Species dependence on one or more sensitive habitat types: breeding habitat: High; feeding 

habitat: Low-Moderate

• Confidence of participants: High 

• Sensitive habitats species is dependent upon: breeding habitat: offshore, predator-free 

islands; feeding habitat: mid-water pelagic

Species dependence on specific prey or forage species: High

• Confidence of participants: High

Other critical dependencies: timing of breeding 

• Degree of dependence: High

• Confidence of participants: High 

Specialization of species (1=generalist; 5=specialist): 4

• Confidence of participants: High 

Supporting literature

Cassin’s auklets breed colonially on offshore islands that are free of predators (Harfenist 2004, 

Adams 2008), nesting in rock crevices or excavated dirt burrows that are stabilized by vegetation 

(e.g., Maritime Goldfields, Lasthenia maritima) (Ainley and Boekelheide 1990, Lee et al. 2007, 

Adams 2008). They will also nest in artificial nest boxes (Ainley and Boekelheide 1990). They

are obligate zooplanktivores, feeding on copepods and krill (Sydeman et al. 1997). However, 

Cassin’s auklets have only a low-moderate dependency on feeding habitat, as they forage in a 

diversity of offshore pelagic areas (i.e., at mid-water column over the continental shelf break or 

continental shelf) and along coastal headlands (e.g., Point Reyes) where predictable upwelling 

occurs leading to higher zooplankton densities (Adams 2008). 

155
IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): oil spills (5, high), invasive rodents (5, 

high), fisheries (2, low), energy production (2, high), land use change (2, high), pollution (1, 

moderate), invasive plants (1, low), researcher disturbance (1, moderate) 

Overall species sensitivity to non-climate stressors: Low-Moderate

• Confidence of participants: Moderate

Overall species exposure to non-climate stressors: Low

• Confidence of participants: High 

Supporting literature

Literature review was conducted for those factors scoring 3 or higher, although the other 

sensitivities identified should also be considered. 

Oil Spills

Cassin’s auklets are vulnerable to oil spills as they are very small, spend a majority of their life at 

sea, and forage through wing-propelled diving (Nisbet 1994, Carter et al. 2000). There are 

documented cases of oil spills leading to Cassin’s auklet mortality (Page et al. 1990). The at-sea

flocking behavior of Cassin’s auklets increases the likelihood of large population impacts should 

an oil spill occur within the foraging vicinity of breeding colonies (Nisbet 1994, Carter et al. 

2000); such an event could drastically exacerbate the on-going population decline of this species 

(Adams 2008). 

Invasive Rodents 

Invasive rodents change ecological relationships (e.g., by eating native vegetation and/or 

drawing new predators) and can cause direct mortality of Cassin’s auklet eggs and chicks 

(Adams 2008). Cassin’s auklets typically have to make a tradeoff between foraging and 

incubation; foraging is critical to adult survival, but foraging expeditions leave eggs vulnerable 

to rodent predation (Bailey and Kaiser 1993, Ronconi and Hipfner 2009). Cassin’s auklets 

typically have longer foraging forays than other nesting bird species (e.g., tufted puffins), 

especially during poor conditions (e.g., strong winds), increasing their vulnerability to rodent 

predation (Bailey and Kaiser 1993, Ronconi and Hipfner 2009). Cassin’s auklets are most 

sensitive to rats, but have higher exposure to mice, especially to house mice (Mus musculus) on 

the Farallon Islands (U.S. Fish and Wildlife Service 2013). Disturbance or predation from 

invasive rodents can exacerbate the on-going population decline of this species (Adams 2008). 

V. Other sensitivities

Other critical factors likely to influence the sensitivity of the species: climate impacts on 

zooplankton (krill and copepods), and major basin-scale oceanographic change (e.g. El Niño 

events)

• Degree to which these factors impact the sensitivity of the species to climate change: 

High

• Confidence of participants: High 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by participants.

156
Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 4.5 

• Confidence of participants: High 

Population status of the species (1=endangered; 5=robust): 3

• Confidence of participants: High 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 3.5 

• Confidence of participants: High 

Dispersal ability of the species: Moderate-High

• Confidence of participants: Moderate 

Maximum annual dispersal distance: >100km 

• Confidence of participants: High 

Supporting literature

The Cassin’s auklet is a resident zooplanktivorous seabird that spends a majority of life at sea, 

coming ashore only to breed on offshore islands within the study region (Sydeman et al. 1997, 

Lee et al. 2007). The Cassin’s auklet has a transcontinental geographic extent, ranging from 

Alaska to Baja California (Harfenist 2004). Within the study region, Cassin’s auklets feature

diminished but generally stable populations with moderate-high (i.e., almost continuous) 

population connectivity. Studies of the Cassin’s auklet population on Southeast Farallon Island 

indicate that the population may have declined 75% or more between 1971 and 2002, including a 

50% decline from the early 1970s to late 1980s (Ainley et al. 1994) and declining an average of 

6.1% per year from 1991-2002 (Lee et al. 2007). The population rebounded slightly after 1998 in 

response to cooler ocean temperatures (Peterson and Schwing 2003, Goericke et al. 2004). 

Future projections for the Farallon Island colonies indicate further decline (i.e., -11 to -45% 

absolute decline in population growth rate by the end of the century) due to changing ocean 

conditions and prey availability (Wolf et al. 2010). While incubating and rearing chicks, they are 

usually found within 50 km of nest sites (Hunt et al. 1981, Briggs et al. 1987, Allen 1994, Adams 

et al. 2004a cited in Adams 2008). 

II. Intraspecific/Life history diversity

Diversity of life history strategies: Moderate-High

• Confidence of participants: High 

Genetic diversity: Moderate

• Confidence of participants: Moderate

Behavioral plasticity: Moderate

• Confidence of participants: High 

Phenotypic plasticity: Moderate

• Confidence of participants: High 

Overall degree of diversity/plasticity of the species: Moderate

• Confidence of participants: High

157
Supporting literature

Indications of reproductive plasticity in the Cassin’s auklet include a high geographic variability 

in the timing of breeding, and delayed breeding according to prey availability (Bertram et al. 

1999, Harfenist 2004). The species typically has one reproductive event per year, resulting in 

one chick (Harfenist 2004), but the Farallon Island population will sometimes raise 2 broods if 

conditions are ideal (Ainley and Boekelheide 1990, Harfenist 2004). Breeding periods are 

variable and can last from January through August (Ainley and Boekelheide 1990). The species 

displays high breeding and nest site fidelity, is socially monogamous (Harfenist 2004, Lee et al. 

2007), and takes 2-4 years to reach reproductive maturity (Speich and Manuwal 1974). Wallace 

et al. (2015) demonstrate that there is high genetic connectivity between Cassin’s auklets 

breeding between the Aleutian and Farallon Islands; however, Cassin’s auklets breeding in the 

Channel Islands and along the coast of Mexico show genetic diversity and separation from 

northern populations. Examples of behavioral plasticity include nocturnal tending of nests, which 

may be an adaptation to avoid predation from large gulls (Cornell Lab of Ornithology 2014), and 

feeding on larval fish and squid in addition to zooplankton (Adams 2008). 

III. Management potential

Value of species to people: Low-Moderate

• Confidence of participants: Moderate 

• Description of value: Most people, aside from pelagic bird watchers, are unaware of this 

species due to its offshore range and nocturnal behavior on land. 

Likelihood of managing or alleviating climate change impacts on species: Low

• Confidence of participants: High

• Description of potential management options: no answer provided 

Supporting literature

Potential management options to protect breeding populations of this species include eradicating 

house mice on Southeast Farallon Island (Adams 2008, USFWS 2013), eradicating invasive 

plant species and restoring native vegetation on breeding colony islands to facilitate soil 

stabilization for burrowing (Adams 2008), and reducing recreational and vessel disturbance 

(Adams 2008). 

IV. Other adaptive capacity factors: none identified 

Exposure 

I. Future climate exposure6

Future climate and climate-driven changes identified (score7, confidence8): altered 

currents/mixing (4, moderate), increased air and sea surface temperatures (3, moderate), changes 

in salinity (3, moderate), decreased pH (3, moderate), decreased dissolved oxygen (3, moderate), 

6 Supporting literature for future exposure to climate factors is provided in the introduction.

7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by participants.

158
changes in precipitation (2, moderate), increased coastal erosion and run-off (2, moderate), 

increased flooding (2, moderate), increased storminess (2, moderate) 

Degree of exposure to future climate and climate-driven changes: Low-Moderate

• Confidence of participants: Moderate

Additional participant comments

Increased air temperatures and/or heat events are of particular concern for Cassin’s auklets 

nesting in constructed nest boxes on the Farallon Islands, as high temperatures could cause adult 

mortality (Sydeman, pers. comm., 2014). 

Literature Cited 

Adams, J. 2008. Species Accounts: Cassin's Auklet (Pytchoramphus aleuticus). In California Bird Species of 

Special Concern: A ranked assessment of species, subspecies, and distinct populations of birds of 

immediate conservation concern in California. Studies of Western Birds 1., edited by W David Shuford and 

Thomas Gardali. Western Field Ornithologists, Camarillo, CA and California Department of Fish and 

Game, Sacramento, CA.

Ainley, D. G. and R. J. Boekelheide. 1994. Seabird population trends along the west coast of North America: causes 

and the extent of regional concordance. Studies in Avian Biology 15:119-133. 

Ainley, D. G., W. J. Sydeman, S. A. Hatch and U. W. Wilson 1990. Seabirds of the Farallon Islands: ecology, 

dynamics, and structure of an upwelling-system community: Stanford University Press.

Bailey, E. P. and G. W. Kaiser. 1993. Impacts of introduced predators on nesting seabirds in the northeast Pacific. 

Vermeer, Kees. 

Bertram, D. F., A. Harfenist, A. J. Gaston and T. Golumbia. 1999. Effects of the 1997-1998 El Niño on seabirds 

breeding in British Columbia. Pacific Seabirds 26:23.

Brinton, E. and A. Townsend. 2003. Decadal variability in abundances of the dominant euphausiid species in 

southern sectors of the California Current. Deep Sea Research Part II: Topical Studies in Oceanography 50 

(14):2449-2472.

Carter, H. R., D. L. Whitworth, J. Y. Takekawa, T. W. Keeney, P. R. Kelly and D. Browne. 2000. At-sea threats to 

Xantus’ murrelets (Synthliboramphus hypoleucus) in the Southern California Bight. Proceedings of the fifth 

California Islands symposium.

Goericke, R., S. Bograd, G. Gaxiola-Castro, J. Gomez-Valdes, R. Hooff, A. Huyer, K. Hyrenbach, B. Lavaniegos, 

A. Mantyla and W. Peterson. 2004. The state of the California Current, 2003-2004: A rare "normal" year. 

California Cooperative Oceanic Fisheries Investigations Report 45:27.

Harfenist, A. 2004. Cassin's Auklet. In Accounts and Measures for Managing Identified Wildlife - Accounts V. 

Huyer, A. 1983. Coastal upwelling in the California Current system. Progress in Oceanography 12 (3):259-284.

Lee, D. E., N. Nur and W. J. Sydeman. 2007. Climate and demography of the planktivorous Cassin's auklet 

Ptychoramphus aleuticus off northern California: implications for population change. Journal of Animal 

Ecology 76 (2):337-347.

Nisbet, I. C. T. 1994. Effects of pollution on marine birds. In Seabirds on islands: threats, case studies and action 

plans: proceedings of the Seabird Specialist Group Workshop held at the XX World Conference of the 

International Council for Bird Preservation, University of Waikato, Hamilton, New Zealand, 19-20 

November 1990, edited by David N Nettleship, Joanna Burger and Michael Gochfeld. BirdLife 

International.

Page, G. W., H. R. Carter and R. G. Ford. 1990. Numbers of seabirds killed or debilitated in the 1986 Apex Houston 

oil spill in central California. Studies in Avian Biology 14:164-174.

Peterson, W. T. and F. B. Schwing. 2003. A new climate regime in northeast Pacific ecosystems. Geophysical 

Research Letters 30 (17).

Roemmich, D. and J. McGowan. 1995. Climatic warming and the decline of zooplankton in the California Current.

Science 267 (5202):1324-1326.

Ronconi, R. and J. Hipfner. 2009. Egg neglect under risk of predation in Cassin's Auklet (Ptychoramphus aleuticus).

Canadian Journal of Zoology 87 (5):415-421.

159
Speich, S. and D. A. Manuwal. 1974. Gular pouch development and population structure of Cassin's Auklet. The 

Auk: 291-306.

Sydeman, W. J., K. A. Hobson, P. Pyle and E. B. McLaren. 1997. Trophic relationships among seabirds in central 

California: combined stable isotope and conventional dietary approach. Condor 99:327-336.

U.S. Fish and Wildlife Service (USFWS). 2013. Farallon National Wildlife Refuge: South Farallon Islands Invasive 

House Mouse Eradication Project. Revised Draft Environmental Impact Statement. US Department of the 

Interior, Fish and Wildlife Service, Pacific Southwest Region.

Wallace, S. J., S. G. Wolf, R. W. Bradley, A. Laurie Harvey and V. L. Friesen. 2015. The influence of 

biogeographical barriers on the population genetic structure and gene flow in a coastal Pacific seabird.

Journal of Biogeography 42 (2):390-400. 

Wolf, S. G., M. A. Snyder, W. J. Sydeman, D. F. Doak and D. A. Croll. 2010. Predicting population consequences 

of ocean climate change for an ecosystem sentinel, the seabird Cassin's auklet. Global Change Biology 16 

(7):1923-1935.

160
Cavity Nesters: Ashy Storm Petrel (Oceanodroma homochroa), 

Tufted Puffin (Fratercula cirrhata), Pigeon Guillemot (Cepphus 

columba)

1

Executive Summary

Cavity nesting species, including the 

ashy storm petrel, tufted puffin, and 

pigeon guillemot, inhabit offshore rocky 

outcrops and islands within the study 

region, forage on a diversity of marine 

species, and are sensitive to both 

anthropogenic and natural disturbance. 

Key climate sensitivities identified for 

these species by workshop participants 

include sea surface temperature, 

dynamic ocean conditions 

(currents/mixing/stratification), and extreme weather conditions. Key non-climate sensitivities 

include aircraft and vessels, recreation, invasive species, harvest, and pollution and poisons. 

Tufted puffins and pigeon guillemots have a transcontinental geographic extent and 

healthy and/or expanding populations within the study region, while ashy storm petrels have a 

declining endemic population within the study region and are classified as a species of concern. 

All of these species feature low to moderate genetic diversity, life history strategy diversity, and 

behavioral and phenotypic plasticity. Tufted puffins have moderate-high societal value, while 

ashy storm petrels and pigeon guillemots have low to low-moderate societal value. Management 

potential for mitigating or alleviating climate stressors is considered low, but managing nonclimate stressors (i.e., predation, disturbance) has higher potential. 

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): extreme weather events (5, 

high), sea surface temperature (3, moderate), dynamic ocean conditions 

(currents/mixing/stratification) (3, moderate), air temperature (2, moderate), salinity (2, low), 

dissolved oxygen (DO) levels (2, low), pH (2, low), coastal erosion (2, moderate), sea level rise

(1, high), wave action (1, moderate), precipitation (1, moderate) 

Climate and climate-driven changes that may benefit the species: no answer provided 

Overall species sensitivity to climate and climate-driven factors: Low-Moderate

• Confidence of workshop participants: Moderate 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Ashy Storm Petrel Score Confidence

Sensitivity 3 Moderate 3 High

Exposure 2 Low-Moderate 2 Moderate

Adaptive Capacity 1 Low 3 High

Vulnerability 4 Moderate-High 3 High

Tufted Puffin and 

Pigeon Guillemot

Score Confidence

Sensitivity 3 Moderate 3 High

Exposure 2 Low-Moderate 2 Moderate

Adaptive Capacity 3 Moderate 3 High

Vulnerability 3 Moderate 3 High

161
Additional participant comments

Cavity nesting species are mainly sensitive to factors that affect prey availability or breeding 

habitat, including sea surface temperatures, currents/mixing/stratification, and extreme weather 

conditions. 

Supporting literature

Literature review was conducted for those factors scoring 3 or higher, although the other 

sensitivities identified should also be considered. 

Sea Surface Temperatures

Warmer sea surface temperatures can cause large thermoclines in the water column, increasing 

stratification, reducing ocean mixing and nutrient delivery to upper ocean photic zones and 

resulting in decreased primary productivity and forage fish abundance, which can shift seabird 

breeding timing, reduce seabird breeding success, and/or lead to adult starvation (Mills et al. 

2005, Warzybok and Bradley 2011, Young et al. 2012, Warzybok et al. 2012, Audubon Society 

2014). For example, rockfish become much less abundant in pigeon guillemot diets during 

periods of warm ocean temperature, a trend that is often correlated with decreased fledgling 

success (Sydeman et al. 2001). Further, in 2011 and 2012, pigeon guillemots on Southeast 

Farallon Island were only able to fledge one chick, likely due to a higher dependence on less 

favorable prey species (i.e., saury and flatfishes) following a reduction of favored rockfish 

(Warzybok and Bradley 2011, Warzybok et al. 2012). Different prey species likely exhibit 

different sensitivities to shifts in water temperature and other ocean conditions, and their relative 

abundance impacts survival, reproductive timing, and reproductive success of nesting seabirds 

(Mills et al. 2005) within the study region. 

Water temperatures are influenced by both long- and short-term climate trends (Young et al. 

2012). For example, El Niño events and warm (positive) phases of the Pacific Decadal 

Oscillation (PDO) are often associated with warmer water temperatures, while La Niñas and cool 

(negative) phases of the PDO are associated with cooler water temperatures and higher 

productivity (Largier et al. 2010, Young et al. 2012). Both ENSO phases affect cavity nesting 

species (Sydeman et al. 2001, Mills et al. 2005). For example, the 1982-83 El Niño led to large 

population declines in tufted puffins breeding on the Farallon Islands (Ainley et al. 1990), likely 

due to warmer water temperatures and reduced ocean productivity (Mills et al. 2005). Pigeon 

guillemots are also very sensitive to the ENSO cycle, thriving during La Niña years and 

struggling during El Niño years (Mills et al. 2005). In comparison, ashy storm petrels have 

shown little population and/or breeding success fluctuation in response to ENSO events (Carter 

et al. 2008). 

Dynamic ocean conditions (currents/mixing/stratification) 

Ashy storm petrels, tufted puffins, and pigeon guillemots forage on a variety of prey species 

delivered by the California Coastal Current and different upwelling zones, and reproduction 

timing is correlated with high prey availability (Carter et al. 2008, McChesney and Carter 2008, 

Young et al. 2012, Sanctuary Integrated Monitoring Network (SIMoN) 2014). For example, the 

ashy storm petrel relies on fronts and eddies to provide concentrated prey foraging locations 

(Yen et al. 2006). Changes in currents, wind, upwelling rates and timing, stratification, and ocean 

mixing can alter the delivery timing and availability of prey species (Young et al. 2012), which 

could affect seabird reproductive success and survival. El Niño events can decrease upwelling 

162
and mixing, reducing nutrient delivery to photic zones and decreasing primary productivity, 

which can lead to food web collapses and negative impacts on seabird fitness and reproduction 

(Young et al. 2012). 

Extreme Weather Conditions 

Extreme weather conditions (i.e., downpours, storms) can degrade and/or eliminate breeding 

habitat and/or affect survival of adults and chicks (Mills et al. 2005). 

II. Sensitivities to disturbance regimes

Disturbance regimes identified: disease, storms, flooding, drought, and interspecific disturbance 

related to climate-driven behavior changes of other species 

Overall species sensitivity to disturbance regimes: High

• Confidence of workshop participants: High 

Additional participant comments

Climate-driven changes in the distributions or behavioral activities of gull and burrowing owl 

species within the breeding ranges of ashy storm petrels, tufted puffins, and pigeon guillemots 

could affect foraging and/or breeding success.

Supporting literature

No information was found in the peer-reviewed literature regarding the impact of storms, 

flooding and drought on these species. 

Disease

As colonial nesters, infectious disease can spread quickly and extensively, and cavity nesting 

seabirds are particularly susceptible to fungi and fleas (Muzaffar and Jones 2004). 

Interspecific disturbance 

Cavity nesting seabirds are also sensitive to interspecific disturbance and predation. For example, 

Western Gulls (Larus occidentalis) prey on ashy storm petrels (Carter et al. 2008), and have also 

been documented to prey on tufted puffin chicks or kleptoparasitize foraging puffin adults 

bringing food back to nests (Speich and Wahl 1989, Jaques and Strong 2001 cited in McChesney 

and Carter 2008). Western gull populations have expanded on the Farallon Islands, and current 

gull habitat overlaps puffin and petrel habitat, increasing the potential for negative interspecific 

interactions (Carter et al. 2008, McChesney and Carter 2008). Gulls (various spp.) also pirate 

prey from pigeon guillemots (SIMoN 2014). In addition, burrowing owls (Athene cunicularia) 

have been documented to prey upon ashy storm petrels when house mice populations decline in 

fall and winter (Carter et al. 2008). Recent population modeling from Farallon Islands data show 

that Burrowing Owl predation on storm petrels has helped lead to recent declines in that 

population (Nur et al. Submitted).

163
III. Dependencies

Species dependence on one or more sensitive habitat types: Moderate-High

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon4

: ASSP: pelagic and surface waters; TUPU: 

pelagic and offshore foraging; PIGU: benthic and nearshore

Species dependence on specific prey or forage species: Moderate

• Confidence of workshop participants: High 

Other critical dependencies: timing of breeding and forage availability

• Degree of dependence: High

• Confidence of workshop participants: High 

Specialization of species (1=generalist; 5=specialist): 3

• Confidence of workshop participants: High 

Supporting literature

Ashy storm petrels nest on offshore islands between the southern Channel Islands and central 

Mendocino County, including a major breeding colony on the South Farallon Islands with at 

least 50% of the world’s population (Carter et al. 2008). They breed in crevices found in rock 

walls, sea caves, cliffs, talus slopes or driftwood piles, which can be structurally unstable (JamesVeitch 1970, Carter et al. 1992, Ainley 1995, McIver 2002 cited in Carter 2008). They feed in 

surface pelagic waters over and seaward of the continental shelf (Carter et al. 2008), and prey 

species include euphausiids, other crustaceans, larval fish, and squid (Carter et al. 2008). 

Tufted puffins breed on offshore rocks and islands, and occasionally will breed on mainland sites 

that have minimal disturbance (McChesney and Carter 2008). They nest primarily in burrows, 

though they will use rock crevices if suitable burrowing soil is unavailable (McChesney and 

Carter 2008). Tufted puffins forage in offshore pelagic areas, visiting the continental shelf and 

slope during breeding season and a variety of more distant pelagic settings during the nonbreeding season (McChesney and Carter 2008). Juveniles primarily eat fish, while adults show 

more plasticity in prey choice (Ainley et al. 1990, Gaston and Jones 1998 cited in McChesney 

and Carter 2008). 

Pigeon guillemots breed on rocky outcrops or islands and occasionally along coastal cliffs and 

rocky shores on the mainland, nesting in crevices, holes, tree roots, abandoned puffin burrows, or 

in man-made structures that provide suitable crevices (i.e., beached ship hulls, pipes, old tires) 

(SIMoN 2014). Pigeon guillemots are pelagic foragers, diving for prey nearshore in both the 

water column and benthic habitats (SIMoN 2014). Chicks consume mainly fish while adults 

forage on a variety of vertebrates and invertebrates (SIMoN 2014). 

4 ASSP = ashy storm petrel; TUPU = tufted puffin; PIGU = pigeon guillemot

164
IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score5, confidence6): land use change (2, high), pollution and 

poisons (5, high), harvest (3, high), energy production (2, high), recreation (4, high), invasive 

species (5, high), aircraft and vessels (3, high) 

Overall species sensitivity to non-climate stressors: Moderate-High

• Confidence of workshop participants: High

Overall species exposure to non-climate stressors: Low

• Confidence of workshop participants: High 

Supporting literature

Literature review was conducted for those factors scoring 3 or higher, although the other 

sensitivities identified should also be considered. 

Aircraft and Vessels

Aircraft and vessel disturbance can cause nest abandonment. For example, squid fishing boats 

can illuminate nesting colonies of ashy storm petrels at night, causing them to abandon breeding 

sites (Carson et al. 2008). In addition, too frequent disturbance or visitation for research purposes 

can also cause nest or site abandonment of pigeon guillemots (Audubon Society 2014). 

Recreation

Recreation (i.e., walking, hiking) in sensitive breeding habitat can disturb breeding activity 

and/or kill cavity nesting seabirds. For example, the ashy storm petrel nests in unstable locations 

(i.e., driftwood piles) that can shift and crush adults, chicks, or eggs if physically disturbed 

(Carter et al. 2008). In addition, pigeon guillemots will abandon their nests if they experience too 

frequent disturbance from human activities (Audubon Society 2014). 

Invasive Species

Rodents, particularly house mice (Mus musculus), were introduced to the Farallon Islands in the 

19th century (U.S. Fish and Wildlife Service (USFWS) 2013). House mice can have direct 

impacts on seabirds; for example, they have been rarely documented to eat the eggs and small 

chicks of ashy storm petrels (Mills 2000). Rodents also change ecological relationships on 

islands (e.g., by eating native plants and invertebrates and/or by drawing in new predators), 

which can affect resident seabird populations. For example, Burrowing Owls have been 

documented to prey on ashy storm petrels on the South Farallon Islands when house mice 

populations decline in fall and winter (Carter et al. 2008), and have substantial population 

impacts on those storm petrels (Nur et al. Submitted). Other invasive species can also affect 

seabirds by altering competition dynamics. For example, introduced rabbits on Southeast 

Farallon Island may have increased competition for nest sites for the tufted puffin during the 

early to mid-20th century, leading to local population declines (McChesney and Carter 2008). 

Harvest

Fishery harvests can lead to direct mortality and/or prey reduction for cavity nesting seabirds. 

For example, gill net fisheries7 can kill ashy storm petrels (Carter et al. 2008) and pigeon 

5 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

6 Confidence level indicated by workshop participants.

7 Gill net fisheries are banned along much of the California coastline. 

165
guillemots (SIMoN 2014). Harvest of fish prey species could reduce food availability for 

foraging seabirds such as the tufted puffin, ashy storm petrel, and pigeon guillemot (Carter et al. 

2008, McChesney and Carter 2008, Farallones Marine Sanctuary Association 2014), potentially 

exacerbating climate-driven trends in prey availability and reproductive success. For example, 

there are established fisheries for some well-known tufted puffin prey species, including the 

Pacific sardine, Sardinops sagax, (McChesney and Carter 2008) which may already be declining 

locally due to changing ocean conditions (Warzybok et al. 2012). 

Pollution and Poisons 

Seabirds are vulnerable to oil spills, oil operations, and water pollution. Oil spills have led to the 

direct mortality of tufted puffins (Page et al. 1990, McChesney and Carter 2008) and pigeon 

guillemots (Cornell Lab of Ornithology 2014, SIMoN 2014). Ashy storm petrels have so far 

largely escaped impact from oil spills due to their foraging locations further out at sea8, but a 

large spill could threaten the large at-sea aggregations around the Farallon Islands and Monterey 

Bay (Spear and Ainley 2007). In addition, deceased ashy storm petrels have been found on at-sea 

oilrigs and at mainland sites with bright flights (i.e., San Francisco Bay) (Carter et al. 2008). In 

addition, seabirds are vulnerable to bioaccumulation of marine contaminants. For example, 

eggshell thinning due to contaminants has been documented in ashy storm petrels, affecting 

reproductive success (Carter et al. 2008). Ashy storm petrels are also sensitive to plastic 

pollution, often ingesting plastic particles when they mistake them for prey (Ainley et al. 1990).

V. Other sensitivities: none identified

Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary)9: ASSP: 2; TUPU: 5; PIGU: 5 

• Confidence of workshop participants: High 

Population status of the species (1=endangered; 5=robust)5: ASSP: 2; TUPU: 5; PIGU: 5 

• Confidence of workshop participants: High

Population connectivity of the species (1=isolated/fragmented; 5=continuous): ASSP: 2; TUPU: 

5; PIGU: 5 

• Confidence of workshop participants: no answer provided 

Dispersal ability of the species: no answer provided 

Maximum annual dispersal distance: no answer provided 

Ashy storm petrels are endemic to California, and are found only from central Mendocino 

County to the southern end of the Channel Islands (Carter et al. 2008). They are a threatened 

species, classified as a “Bird Species of Special Concern (breeding), priority 2” in California, as 

over 95% of their breeding activity occurs on offshore islands and rocks along the California 

8 Alternatively, ashy storm petrels could have been impacted by regional oil spills, but due to their distant at-sea 

foraging locations their carcasses may never have washed ashore (Center for Biological Diversity 2007).

9 ASSP = ashy storm petrel; TUPU = tufted puffin; PIGU = pigeon guillemot

166
coastline (Carter et al. 2008). A majority of ashy storm petrels in the study region are resident 

seabirds, spending non-breeding season in offshore waters near breeding habitats, and 

congregating in Monterey Bay during the fall (Roberson 2002). The South Farallon Islands host 

a large portion of the world’s breeding ashy storm petrels, as do the Channel Islands (Carter et al. 

2008). However, the South Farallon Islands population declined 40% from 1972-1992, has been 

declining since 2007, and is likely to face future declines due to predation from Burrowing Owls

(Mills 2000, Warzybok et al. 2012, Nur et al. Submitted).

Tufted puffins breed along the Pacific Coast of North America and Asia (McChesney and Carter 

2008); in California, they can be found from the Oregon border to the southern Farallon Islands, 

as well as further south at Prince Island (McChesney and Carter 2008). Tufted puffins are 

considered a “Bird Species of Special Concern (breeding), priority 1” in California, as they have 

been extirpated from some parts their historic California range (i.e., the Channel Islands) 

(McChesney and Carter 2008). However, within the study region, they have healthy and/or 

expanding populations (Abraham et al. 2000) with high (i.e., continuous) population 

connectivity. For example, the breeding colony on Southeast Farallon Island has been 

rebounding since population lows in the early to mid-20th century and in 2004 (Ainley et al. 

1990, Warzybok and Bradley 2011), and recent population estimates (2009-2011) indicate that 

the colony now has more active nests than at any other recorded point in history (Warzybok and 

Bradley 2011). Tufted puffins can be found year-round in the study area (McChesney and Carter 

2008). During breeding season, tufted puffins are typically found within 40 miles of the breeding 

colony, while during the non-breeding season, they may travel several hundred kilometers away 

to forage (Briggs et al. 1987, Briggs et al. 1992 cited in McChesney and Carter 2008). 

Pigeon guillemots breed throughout the North Pacific from Alaska to California and from the 

Bering Sea to the Kuril and Aleutian Islands (SIMoN 2014). The Farallon Islands hosts one of 

the world’s largest breeding colonies of pigeon guillemots (SIMoN 2014), and the colony on 

Southeast Farallon Island had the highest population numbers ever recorded in 2012 (Warzybok 

et al. 2012). Pigeon guillemots can be migratory during the non-breeding season, migrating as far 

north as British Columbia (SIMoN 2014). 

II. Intraspecific/Life history diversity

Diversity of life history strategies10: ASSP: 1; TUPU: 2; PIGU: 3 

• Confidence of workshop participants: High 

Genetic diversity10: ASSP: 3; TUPU: 3; PIGU: 3 

• Confidence of workshop participants: Low

Behavioral plasticity10: ASSP: 2; TUPU: 2; PIGU: 2 

• Confidence of workshop participants: Moderate 

Phenotypic plasticity10: ASSP: 1; TUPU: 2; PIGU: 2 

• Confidence of workshop participants: Moderate 

Overall degree of diversity/plasticity of the species: Low-Moderate 

• Confidence of workshop participants: High

10 ASSP = ashy storm petrel; TUPU = tufted puffin; PIGU = pigeon guillemot

167
Supporting literature

Examples of behavioral plasticity in ashy storm petrels includes their tendency to scavenge food 

from fishing vessels rather than forage in surface waters (Ainley et al. 1990), and their nocturnal 

behavior (Mills 2000), which is believed to be an adaptation to avoid predation from diurnal 

predators (Ainley et al. 1990). Nur et al. (1999) suggest that there is no genetic differentiation 

between the subpopulations living on the Farallon and Channel Islands, as roughly 1.6% of 

regional populations disperse between these islands. Ashy storm petrels have one reproductive 

event per year, laying only one egg anywhere from mid-March to late October and incubating for 

long periods; chicks fledge anytime between late July and January (James-Veitch 1970, Ainley et 

al. 1974, Ainley 1995, McIver 2002 cited in Carter et al. 2008). Low reproductive potential 

leads to slow population growth and makes it difficult for this species to recover from impacts 

(i.e., predation, breeding disturbance, food web collapses) (Carter et al. 2008). 

U.S. populations of tufted puffins are non-migratory and physically separated from other 

northern populations, and display altered breeding timing depending on location (National 

Resources Defense Council 2014). They may adjust breeding phenology to compensate for 

within-season shifts in sea surface temperature and prey availability (Gjerdrum et al. 2003). 

Tufted puffins have one reproductive event per year (but can relay after breeding failure), 

breeding from late April through September and lay only one egg (Ainley et al. 1990). 

Incubation lasts for 45 days (Ainley et al. 1990). 

Breeding timing in pigeon guillemots is highly correlated with food availability, and even within 

a single population, breeding times will be highly variable depending on favored prey species of 

each adult pair (i.e., schooling fish or non-schooling fish) (Ainley et al. 1990). Pigeon guillemots 

with different foraging ecologies have also been documented to differentially adjust their time 

budgets (i.e., foraging versus resting time) according to clutch size, prey choice, and prey 

availability (Litzow and Piatt 2003). For example, pairs foraging on schooling fishes were able to 

maintain food delivery rates to chicks despite decreasing food abundance by increasing forage 

time, while individuals foraging on non-schooling fishes delivered fewer meals to chicks rather 

than increasing forage time (Litzow and Piatt 2003). Pigeon guillemots have one reproductive 

event per year, breeding from May to late June and typically laying 2 eggs (SIMoN 2014). 

Incubation last from 30-32 days, and fledging occurs 29-39 days after hatching (SIMoN 2014). 

III. Management potential

Value of species to people11: ASSP: 1; TUPU: 4; PIGU:2 

• Confidence of workshop participants: High 

• Description of value: none answer provided 

Likelihood of managing or alleviating climate change impacts on species: Low

• Confidence of workshop participants: High 

• Description of potential management options: no answer provided 

11 ASSP = ashy storm petrel; TUPU = tufted puffin; PIGU = pigeon guillemot

168
Supporting literature

For ashy storm petrels, controlling disturbance from western gulls and burrowing owls, 

maintaining and creating important breeding habitat features (i.e., crevice-containing structures), 

and establishing protective at-sea perimeters and human visitation closures to reduce visitation 

and disturbance to breeding colonies from fishing vessels, kayakers, and tourists (Carter et al. 

2008). For tufted puffins and pigeon guillemots, prioritize and enforce the protection of offshore 

breeding islands and rocks to minimize human disturbance and introduction of other competitors 

or predators (McChesney and Carter 2008, SIMoN 2014). 

IV. Other adaptive capacity factors: none identified

Exposure12

I. Future climate exposure

Future climate and climate-driven changes identified (score13, confidence14): altered currents and 

mixing (4, moderate), changes in salinity (3, moderate), increased storminess (3, moderate), 

changes in sea surface temperature (3, moderate), decreased dissolved oxygen (DO) levels (3, 

moderate), decreased pH (3, moderate), changes in precipitation (2, moderate), increased 

flooding (2, moderate), increased coastal erosion and runoff (2, moderate), changes in air 

temperature (2, moderate), sea level rise (1, moderate)

Degree of exposure to future climate and climate-driven changes: Low-Moderate

• Confidence of workshop participants: Moderate 

Additional participant comments

Climate change will likely have indirect impacts on these cavity nesting species by affecting prey 

availability and breeding habitat. 

Literature Cited

Abraham, C. L., K. L. Mills and W. J. Sydeman. 2000. Population size and reproductive performance of seabirds on 

Southeast Farallon Island, 2000. Unpublished report.

Ainley, D. G. and R. J. Boekelheide. 1990. Seabirds of the Farallon Islands: ecology, dynamics, and structure of an 

upwelling-system community: Stanford University Press.

Audobon Society. 2014. Pigeon Guillemot. Accessed June 2014. http://www.audubon.org/field-guide/bird/pigeonguillemot. 

Carter, H. R., W. R. McIver and G. J. McChesney. 2008. Species Accounts: Ashy Storm-Petrel. In California Bird 

Species of Special Concern: A ranked assessment of species, subspecies, and distinct populations of birds 

of immediate conservation concern in California. Studies of Western Birds 1., edited by W David Shuford 

and Thomas Gardali. Western Field Ornithologists, Camarillo, CA, and California Department of Fish and 

Game, Sacramento, CA.

Center for Biological Diversity. 2007. Petition to list the Ashy Storm-Petrel (Oceanodroma homochroa) as a 

threatened or endangered species under the Endangered Species Act.

12 Supporting literature for future exposure to climate factors is provided in the introduction. 13 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

14 Confidence level indicated by workshop participants.

169
Cornell Lab of Ornithology. 2014. Pigeon Guillemot. Accessed June 2014. 

http://www.allaboutbirds.org/guide/Pigeon_Guillemot/lifehistory.

Farallones Marine Sanctuary Association. 2014. Seabirds and Shorebirds of the Gulf of the Farallones. Educational 

document.

Gjerdrum, C., A. M. Vallée, C. C. S. Clair, D. F. Bertram, J. L. Ryder and G. S. Blackburn. 2003. Tufted puffin 

reproduction reveals ocean climate variability. Proceedings of the National Academy of Sciences 100 

(16):9377-9382.

Largier, J. L., B. S. Cheng and K. D. Higgason (editors). 2010. Report of a Joint Working Group of the Gulf of the 

Farallones and Cordell Bank National Marine Sanctuaries Advisory Councils.

Litzow, M. A. and J. F. Piatt. 2003. Variance in prey abundance influences time budgets of breeding seabirds: 

evidence from pigeon guillemots Cepphus columba. Journal of Avian Biology 34 (1):54-64.

McChesney, G. J. and H. R. Carter. 2008. Species Accounts - Tufted Puffin. In California Bird Species of Special 

Concern: A ranked assessment of species, subspecies, and distinct populations of birds of immediate 

conservation concern in California. Studies of Western Birds 1., edited by W David Shuford and Thomas 

Gardali. Western Field Ornithologists, Camarillo, CA, and California Department of Fish and Game, 

Sacramento, CA.

Mills, K. L. 2000. Status and Conservation Efforts of Ashy Storm on the Farallon Islands. Accessed June 2014. 

http://www.thefreelibrary.com/Status+and+Conservation+Efforts+of+Ashy+Storm+on+the+Farallon+Islan

ds.-a067411006.

Mills, K. L., W. J. Sydeman and P. J. E. Hodum. 2005. Climate and Food: "Bottom-Up" Control of Seabird 

Population Parameters and Population Dynamics. In The California Current Marine Bird Conservation 

Plan. PRBO Conservation Science.

Muzaffar, S. B. and I. L. Jones. 2004. Parasites and diseases of the auks (Alcidae) of the world and their ecology—a 

review. Marine Ornithology 32 (2):121-146.

National Resources Defense Council. 2014. Petition to list the Contiguous U.S. Distinct Population Segment of the 

Tufted Puffin (Fratercula cirrhata) under the Endangered Species Act.

Nur, N., R. Bradley, L. Salas, and J. Jahncke. 2014. Evaluating population impacts of reduced predation by owls on 

storm-petrels as the result of a proposed island mouse eradication. Submitted to Ecological Applications.

Nur, N., W. Sydeman, D. Girman, T. Smith and D. Gilmer. 1999. Population status, prospects, and risks faced by 

two seabirds of the California Current: the Ashy Storm-Petrel, Oceanodroma homochroa, and Xantus’ 

Murrelet Synthliboramphus hypoleucus. Unpublished report, Point Reyes Bird Observatory, Stinson Beach, 

California

Page, G. W., H. R. Carter and R. G. Ford. 1990. Numbers of seabirds killed or debilitated in the 1986 Apex Houston 

oil spill in central California. Studies in Avian Biology 14:164-174.

Roberson, D. 2002. Monterey Bay Birds. 2 ed. Carmel, CA: Monterey Peninsula Audubon Society.

Sanctuary Integrated Monitoring Network (SIMoN). 2014. Cepphus columba - Pigeon guillemot. Accessed June 

2014 from: http://sanctuarysimon.org/species/cepphus/columba/pigeon-guillemot.

Spear, L. B. and D. G. Ainley. 2007. Storm-petrels of the eastern Pacific Ocean: species assembly and diversity 

along marine habitat gradients. Ornithological Monographs 62.

Sydeman, W. J., M. M. Hester, J. A. Thayer, F. Gress, P. Martin and J. Buffa. 2001. Climate change, reproductive 

performance and diet composition of marine birds in the southern California Current system, 1969–1997. 

Progress in Oceanography 49 (1):309-329.

U.S. Fish and Wildlife Service (USFWS). 2013. Farallon National Wildlife Refuge: South Farallon Islands Invasive 

House Mouse Eradication Project. Revised Draft Environmental Impact Statement. US Department of the 

Interior, Fish and Wildlife Service, Pacific Southwest Region.USFWS 2013

Warzybok, P. M., R. W. Berger and R. W. Bradley. 2012. Status of seabirds on southeast Farallon Island during the 

2012 breeding season. Unpublished report prepared for the U.S. Fish and Wildlife Service. PRBO 

Conservation Science, Petaluma, CA.

Warzybok, P. M. and R. W. Bradley. 2011. Status of seabirds on Southeast Farallon Island during the 2011 Breeding 

Season. Unpublished report to the U.S. Fish and Wildlife Service. PRBO Conservation Science, Petaluma, 

CA.

Yen, P., W. Sydeman, S. Bograd and K. Hyrenbach. 2006. Spring-time distributions of migratory marine birds in the 

southern California Current: Oceanic eddy associations and coastal habitat hotspots over 17 years. Deep 

Sea Research Part II: Topical Studies in Oceanography 53 (3):399-418.

170
Young, L., R. Suryan, D. Duffy and W. Sydeman. 2012. Climate change and seabirds of the California current and 

Pacific Islands ecosystems: Observed and potential impacts and management implications. Report to the 

US Fish and Wildlife Service, Region 1.

171
Boreal Copepods1

Executive Summary Boreal copepods are a group of 

small, cold-water planktonic 

crustaceans that serve as an 

important food source for many 

marine organisms in the study 

region and are the most abundant 

and diverse zooplankton taxon. Key climate sensitivities identified by workshop participants 

include sea surface temperature, salinity, and dynamic ocean conditions 

(currents/mixing/stratification) and key non-climate sensitivities include pollution and poisons. 

Boreal copepods have a moderate geographic distribution, a continuous, stable population at 

abundant levels, and high dispersal capabilities. In contrast to transitional and equatorial copepod 

species, boreal copepods rely on the presence of cold water and are much higher in fat content, 

providing optimal food for many of the region’s marine organisms. Copepods exhibit moderate 

phenotypic and behavioral plasticity, including the ability to convert the oil in their bodies to 

more dense fats in order to sink to greater depths to avoid predation and suboptimal 

oceanographic conditions. Copepods have low societal value, though they are recognized as 

critical components of the food web and important prey for higher trophic organisms. 

Management potential of these species is also considered low because abundance is driven by 

oceanographic processes, including upwelling and currents that vary the salinity and temperature 

of the region’s seawater.

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): sea surface temperature (4, 

high), salinity (4, high), and dynamic ocean conditions (currents/mixing/stratification) (4, high) 

Climate and climate-driven changes that may benefit the species: no answer provided 

Overall species sensitivity to climate and climate-driven factors: Moderate-High

• Confidence of workshop participants: High 

Additional participant comments

The future direction of copepod abundance in the study region is tightly linked to the direction 

and magnitude of change in coastal upwelling, which is not currently well understood. As the 

primary delivery method of deep, cold, nutrient-rich water, upwelling is the primary driver of 

boreal copepod abundance in the region. 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report. Boreal copepods are cold water species found along the Oregon and North-central California 

coast.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Copepod Score Confidence

Sensitivity 2 Low-Moderate 3 High

Exposure 5 High 3 High

Adaptive Capacity 3 Moderate 1 Low

Vulnerability 3 Moderate 2 Moderate

172
Supporting literature

Sea Surface Temperatures

Warmer sea surface temperatures can cause large thermoclines in the water column, increasing 

stratification, reducing ocean mixing and nutrient delivery to upper ocean photic zones, resulting 

in decreased primary productivity that impacts trophic functioning (Young et al. 2012). Warmer 

temperatures have been correlated with lower boreal copepod abundance and higher abundance 

of transitional and equatorial species, which has been correlated to lower coho salmon survival 

(Peterson and Schwing 2003, Peterson 2009, Bi et al. 2011). This may be attributed to the higher 

lipid content of boreal copepod species compared to their southern counterparts, which make 

them a better food source for juvenile salmon that need to accumulate enough body fat to survive 

their first winter at sea (Beamish et al. 2004) and to make it upstream to spawn (Bi et al. 2011). 

Peak biomass of one dominant boreal copepod species has been documented to occur earlier in 

the year and for a shorter duration due to increasing sea surface temperature, which will have 

severe implications for trophic functioning and survival of predators (Batten and Mackas 2009). 

Inter-annual variation in boreal copepod abundance can be explained by variation in water 

temperatures that are influenced by both long- and short-term climate trends (Bi et al. 2011, 

Young et al. 2012). El Niño events and warm (positive) phases of the Pacific Decadal Oscillation 

(PDO) are often associated with warmer water temperatures, while La Niña events and cool 

(negative) phases of the PDO are associated with cooler water temperatures and higher 

productivity (Largier et al. 2010; Young et al. 2012). Abundance of boreal copepods also 

exhibits intra-annual variability between winter and summer seasons due to the alternation of 

coastal currents that bring warmer water to the region in winter and cooler water in summer 

(Peterson and Miller 1977). Colder sea surface temperatures during the winter correlated with 

higher boreal copepod abundance in our region (Fontana et al. 2014). 

Salinity

Boreal copepods are sensitive to decreased salinity levels, as observed in the Baltic Sea when the 

biomass of copepods declined in response to enhanced freshwater run-off and subsequent 

decrease in seawater salinity (Vuorinen et al. 1998). This decline in neritic copepods resulted in 

lower carbon content of the food eaten by herring, a lower stomach fullness index, and a lower 

mesenteric fat amount in herring, despite an increase in total zooplankton biomass, indicating 

that bottom-up processes such as changes in salinity can have far-reaching food web impacts 

(Flinkman et al. 1998). Increased boreal copepod abundance was correlated with higher salinity 

waters in our region (Fontana et al. 2014). 

Dynamic ocean conditions (currents/mixing/stratification

Upwelling may counteract rising sea surface temperatures and promote primary productivity 

(Largier et al. 2010), but intense upwelling could shift zooplankton to deeper waters (Pringle 

2007), potentially decreasing food availability for marine organisms (Largier et al. 2010). El 

Niño events decrease upwelling and mixing, and positive phases of the PDO lead to 

downwelling, reducing nutrient delivery to photic zones, decreasing primary productivity, and 

decreasing the abundance of lipid-rich boreal copepod species (Bi et al. 2011, Young et al. 

2012). Boreal copepod abundance in our region was higher in years where stronger alongshore 

wind stress and weaker westward cross-shore flow were observed during the previous winter 

(Fontana et al. 2014). 

173
II. Sensitivities to disturbance regimes

Disturbance regimes identified: Wind

Overall species sensitivity to disturbance regimes: Moderate-High

• Confidence of workshop participants: High 

Additional participant comments

Boreal copepods exhibit moderate-high sensitivity to wind-driven upwelling which brings cold, 

salty and nutrient-rich water to the surface, enhancing primary productivity and resulting in 

increased abundance of boreal copepods (see “climate factors” section above for more 

information). 

III. Dependencies

Species dependence on one or more sensitive habitat types: Low

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: none 

Species dependence on specific prey or forage species: Low

• Confidence of workshop participants: Low

Other critical dependencies: ability to diapause 

• Degree of dependence: Low-Moderate

• Confidence of workshop participants: Moderate 

Specialization of species (1=generalist; 5=specialist): 2

• Confidence of workshop participants: High 

Additional participant comments

Copepods have very low dependency both on specific habitats and food sources, feeding on a 

variety of phytoplankton, organic detritus and other small crustaceans, and are considered to 

more closely resemble generalists. The species assemblage does, however, rely on its ability to 

go into diapause, sinking to deeper waters when oceanographic conditions are not favorable for 

reproduction. If conditions do not improve, reproductive opportunities may be missed 

altogether, so optimum conditions of cold, nutrient-rich water is critical to maintain abundance. 

IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): pollution and poisons (1, high) 

Overall species sensitivity to non-climate stressors: Low

• Confidence of workshop participants: High 

Overall species exposure to non-climate stressors: Low

• Confidence of workshop participants: High

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

174
Supporting literature

Pollution and poisons 

Copepods are particularly sensitive to dispersants used in response to oil spills, more so than 

other zooplankton, displaying increased mortality when exposed to dispersants alone, and 

interrupted swimming behavior when exposed to dispersants and crude oil (Cohen et al. 2014). 

In another study, dispersant-treated oil was found to be 3 times more toxic than crude oil alone to 

mesozooplankton, copepods included, and the presence of protozoans in oil-microbial food web 

interactions was found to reduce sublethal effects of oil on copepods (Almeda et al. 2013). Over 

6,000 commercial vessels transit in and out of San Francisco Bay every year, with 5% of these as 

large cargo vessels that can carry up to one million gallons of bunker fuel (GFNMS 2008). All 

transiting vessels, including military, research and fishing vessels, carry crude oil or fuel, posing 

a potential risk to copepod populations in the region (Largier et al. 2010). 

V. Other sensitivities: none identified 

Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 3 

• Confidence of workshop participants: Low

Population status of the species (1=endangered; 5=robust): 4 

• Confidence of workshop participants: Low

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 5

• Confidence of workshop participants: Low

Dispersal ability of the species: High 

• Confidence of workshop participants: Low

Maximum annual dispersal distance: >100km 

• Confidence of workshop participants: Low

II. Intraspecific/Life history diversity

Diversity of life history strategies: Low-Moderate 

• Confidence of workshop participants: Low

Genetic diversity: Low-Moderate

• Confidence of workshop participants: Low

Behavioral plasticity: Moderate

• Confidence of workshop participants: Moderate 

Phenotypic plasticity: Moderate 

• Confidence of workshop participants: Moderate 

Overall degree of diversity/plasticity of the species: Low-Moderate 

• Confidence of workshop participants: Low

175
Additional participant comments

An example of behavioral plasticity is diapause, a physiological state of dormancy in response to 

unfavorable environmental conditions. Some species (including Calanus and Neocalanus spp.) 

can go into diapause, sinking to greater depths when oceanographic conditions are unfavorable 

and returning to surface waters when conditions improve. 

Supporting literature

An additional example of behavioral plasticity is the ability for copepods to feed near the surface 

at night, and then sink into deeper waters during the day by changing oils into more dense fatsto 

avoid visual predators (Pond and Tarling 2011). 

Some species of copepods may reproduce only once in their lifetime, while others may be able to 

reproduce multiple times, with females either releasing eggs directly into the water or retaining 

them in a sac until they hatch into nauplius larvae (Barnes 1982). Boreal copepods in this 

region reach sexual maturity within 12 months (Conover 1988; Vulnerability Assessment 

Workshop, pers. comm., 2014) with the entire life cycle taking anywhere from a week up to one 

year, depending on the species (Barnes 1982). 

III. Management potential

Value of species to people: Low

• Confidence of workshop participants: Low

• Description of value: Copepods are valued as a food source to culturally, recreationally, 

and commercially important species such as salmon and rockfish. 

Likelihood of managing or alleviating climate change impacts on species: Low

• Confidence of workshop participants: Moderate 

• Description of potential management options: None available, as copepods are so 

completely influenced by large-scale oceanographic processes, they would be expected to 

“retreat” to higher latitudes if conditions become consistently unfavorable in this region. 

IV. Other adaptive capacity factors: none identified 

Exposure 

I. Future climate exposure6

Future climate and climate-driven changes identified (score7, confidence8): altered 

currents/mixing (5, high), changes in sea surface temperature (5, high), changes in salinity (5, 

high) 

Degree of exposure to future climate and climate-driven changes: High

• Confidence of workshop participants: no answer provided 

6 Supporting literature for future exposure to climate factors is provided in the introduction.

7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

176
Literature Cited

Almeda, R., Z. Wambaugh, Z. Wang, C. Hyatt, Z. Liu and E.J. Buskey. 2013. Interactions between Zooplankton and

Crude Oil: Toxic Effects and Bioaccumulation of Polycyclic Aromatic Hydrocarbons. PLoS ONE 8(6): 

e67212.

Barnes, R.D. 1982. Invertebrate Zoology. Philadelphia, Pennsylvania: Holt-Saunders International. pp. 683–692.

Batten, S.D. and D.L. Mackas. 2009. Shortened duration of the annual Neocalanus plumchrus biomass peak in the 

Northeast Pacific. Marine Ecology Progress Series 393: 189-198.

Beamish, R. J., C. Mahnken, and C. M. Neville. 2004. Evidence that reduced early marine growth is associated with

lower marine survival of coho salmon. Trans. Am. Fish. Soc. 133(1): 26–33.

Bi, H., W.T. Peterson, and P.T. Strub. 2011. Transport and coastal zooplankton communities in the northern 

California Current System. Geophysical Research Letters 38: L12607.

Cohen, J.H., L.R. McCormick, and S.M. Burkhardt. 2014. Effects of dispersant and oil on survival and swimming 

activity in a marine copepod. Bulletin of Environmental Contamination and Toxicology 92(4):381-7.

Conover, R.J. 1988. Comparative life histories in the genera Calanus and Neocalanus in high latitudes of the 

northern hemisphere. Hydrobiologia 167/168: 127-142.

Flinkman, J., E. Aro, I. Vuorinen, and M. Viitasalo. 1998. Changes in northern Baltic zooplankton and herring 

nutrition from 1980s to 1990s: top-down and bottom-up processes at work. Marine Ecology Progress 

Series 165:127-136.

Fontana, R. E., M. L. Elliott, J. L. Largier, and J. Jahncke. 2014. Variation in zooplankton abundance and 

composition in a strong, persistent coastal upwelling region. Progress in Oceanography, in review

Gulf of the Farallones National Marine Sanctuary (GFNMS). 2008. Management Plan. 

http://farallones.noaa.gov/manage/plan.html#plan. 

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Peterson, W. T., and C. B. Miller. 1977. Seasonal cycle of zooplankton abundance and species composition along 

the central Oregon coast. Fisheries Bulletin 75: 717–724.

Peterson, W. T. 2009. Copepod species richness as an indicator of long term changes in the coastal ecosystem of 

the northern California Current. CalCOFI Rep. 50: 73–81.

Peterson, W. T., and F. B. Schwing. 2003. A new climate regime in northeast Pacific ecosystems. Geophysical 

Research Letters 30(17): 1896.

Pond, D.W. and G. A. Tarling. 2011. Phase transitions of wax esters adjust buoyancy in diapausing Calanoides 

acutus. Limnology and Oceanography 56 (4): 1310–1318.

Pringle, J.M. 2007. Turbulence avoidance and the wind-driven transport of plankton in the surface Ekman layer. 

Continental Shelf Research 27:670-678.

Vuorinen, I., J. Hanninen, M. Viitasalo, U. Helminen, and H. Kuosa. 1998. Proportion of copepod biomass declines 

with decreasing salinity in the Baltic Sea. ICES Journal of Marine Science, 55: 767–774.

Young, L. R.M. Suryan, D. Duffy, and W.J. Sydemann. 2012. Climate Change and Seabirds of the California 

Current and Pacific Islands Ecosystems: Observed and Potential Impacts and Management Implications. 

Final Report to the U.S. Fish and Wildlife Service, Region 1. Unpublished.

177
Coralline Algae (various species)1

Executive Summary Coralline algae are a family of 

calcifying red algae composed of many 

species that occur in two morphologies, 

articulate and crustose, and can be 

found in subtidal and intertidal habitats 

throughout the study region, inhabiting 

depths of up to 500 feet. Key climate sensitivities identified by workshop participants include air 

and sea surface temperature and pH, and key non-climate sensitivities include nutrient pollution. 

The coralline algal assemblage exhibits a transcontinental geographic extent, a healthy and/or 

expanding population that is somewhat fragmented, and a low dispersal capability. Coralline 

algae exhibit moderate life history strategy diversity (with microscopic and macroscopic stages), 

low behavioral plasticity, and low-moderate phenotypic plasticity, though the literature indicates 

that this species assemblage has high diversity in morphology and reproductive strategy, 

enabling the group to respond to changing environmental conditions. The societal value for 

coralline algae was rated as low, though managers and scientists realize the ecological value of 

the assemblage, with a low-moderate likelihood of managing or alleviating climate impacts.

Sensitivity 

I. Sensitivity to climate and climate driven changes 

Climate and climate-driven changes identified (score2, confidence3): air temperature (4, high), 

sea surface temperature (4, high), ocean pH (4, moderate), coastal erosion (2, high), salinity (2, 

low), precipitation (1, high) 

Climate and climate-driven changes that may benefit the species: none identified

Overall species sensitivity to climate and climate-driven factors: Moderate-High

• Confidence of workshop participants: Moderate 

Supporting literature

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. Corallines have been suggested to both benefit 

from future climate changes due to decreased competition from species more vulnerable, and to 

suffer from climate changes due to their own vulnerability to ocean acidification (Miklasz 2012). 

Though workshop participants characterized coralline algae as having only low-moderate 

sensitivity to climate and non-climate impacts, literature review conducted suggests this 

sensitivity may be higher. 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Coralline Algae Score Confidence 

Sensitivity 2 Low-Moderate 3 High

Exposure 3 Moderate 3 High

Adaptive Capacity 2 Low-Moderate 3 High

Vulnerability 3 Moderate 3 High

178
Air Temperature

Though intertidal coralline algae are relatively resistant to desiccation and heat stress through 

moisture retention (Padilla 1984, Miklasz 2012), photosynthesis has been documented to 

abruptly stop in two species of articulate coralline algae during low tide (Guenther and Martone 

2014). Bleaching (physiological stress that leads to complete loss of pigment) of entire intertidal 

areas has been observed (Harley 2008) and may become more frequent as the number of extreme 

heat days increases. Air temperature does not seem to be a leading factor in coralline bleaching, 

but interacts with both light and desiccation, causing a 50% reduction in pigmentation within 24 

minutes of exposure (Martone et al. 2010). Increased air temperature, in combination with 

daytime low tides and enhanced winds, may have serious implications for intertidal coralline.

Sea Surface Temperature

Increased sea surface temperature has been shown to exacerbate the effects of elevated CO2 in 

seawater, which effectively lowers net calcification rates for coralline algae (Koch et al. 2013). 

Martin and Gattuso (2009) documented death of a Mediterranean coralline alga under elevated 

water temperature (+3 ̊C), with a two- to three-fold increase in algal necrosis when combined 

with elevated CO2. The authors suggest that net dissolution will likely exceed net calcification 

by the end of the century due to increased water temperature and decreased pH. 

Ocean pH

As calcifying red algae, corallines are highly sensitive to changes in pH (Koch et al. 2013). 

Elevated CO2 lowers net calcification and this effect is amplified by increased water temperature 

(Koch et al. 2013). Decreased pH also interrupts diffusion and transportation of hydrogen ions 

and dissolved inorganic carbon, which are vital in promoting calcification over dissolution (Koch 

et al. 2013). Koch et al. (2013) suggest that fleshy algae may become more dominant and outcompete calcifying species in a more acidic ocean. Supporting this idea, Kuffner et al. (2008) 

experimentally showed decreased recruitment and growth of crustose coralline algae in higher 

CO2 conditions, along with increased growth of fleshy red algae. 

II. Sensitivity to changes in disturbance regimes

Disturbance regimes identified: none identified by workshop participants, though storm activity 

has been identified by reviewers as a possible disturbance regime of importance. 

III. Dependencies

Species dependence on one or more sensitive habitat types: High

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: rocky substrate of intertidal and subtidal 

kelp forest habitats 

Species dependence on specific prey or forage species: Low

• Confidence of workshop participants: High 

Other critical dependencies: presence of grazers that feed on competing fleshy algae

• Degree of dependence: Moderate-High

• Confidence of workshop participants: High 

Specialization of species (1=generalist; 5=specialist): 1

• Confidence of workshop participants: High 

179
IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): pollution (2, moderate) 

Overall species sensitivity to non-climate stressors: Low

• Confidence of workshop participants: High 

Overall species exposure to non-climate stressors: Low-Moderate

• Confidence of workshop participants: High 

Supporting literature

Nutrient Pollution

Nutrient pollution can cause decreased growth and abundance of coralline algae due to increased 

microalgal growth, increased sedimentation, decreased light availability and increased growth of 

fleshy algal competitors (Björk et al. 2009). Decreased calcification was documented in 

coralline algae when exposed to high phosphate levels (Björk et al. 2009), which may exacerbate 

the effect of decreased calcification due to decreasing pH. 

Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 5

• Confidence of workshop participants: High 

Population status of the species (1=endangered; 5=robust): 5

• Confidence of workshop participants: Moderate 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 2

• Confidence of workshop participants: Moderate 

Dispersal ability of the species: Low 

• Confidence of workshop participants: Moderate 

Maximum annual dispersal distance: 1-5km 

• Confidence of workshop participants: Moderate 

Supporting literature

This species assemblage inhabits the world’s oceans from the tropics to polar regions (Johansen 

1981). Coralline algae have a low dispersal capability, as spores are able to attach to the bottom 

within hours of release, and often recruit near the parent alga (Miklasz 2012). This characteristic 

limits the dispersal distance, but enhances the potential for local adaptation (Hoffman et al. 

2014). 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

180
II. Intraspecific/Life history diversity

Diversity of life history strategies: Moderate

• Confidence of workshop participants: Moderate 

Genetic diversity: no answer provided 

Behavioral plasticity: Low

• Confidence of workshop participants: High 

Phenotypic plasticity: Low-Moderate 

• Confidence of workshop participants: Moderate 

Overall degree of diversity/plasticity of the species: Low-Moderate 

• Confidence of workshop participants: Moderate 

Supporting literature

In general, the literature indicates that coralline algae exhibit a great diversity in morphology and 

reproduction. The high morphological diversity in this family of algae enables multiple 

adaptation strategies that fill multiple ecological niches (Miklasz 2012). More finely branched 

articulate species excel at resisting desiccation stress and maintaining photosynthesis, while more 

stout species inhibit the movement of grazers (Padilla 1984). Crustose forms are best adapted for 

space competition, and often overgrow each other (Padilla 1984), with one species documented 

to be able to change its morphology depending on water motion and light (Steneck 1986). Some 

morphological diversity can be attributed to an herbivory response, including protuberances and 

especially thick epithalli (Miklasz 2012). Additionally, the reproductive strategies of coralline 

algae are plastic, adjusting to environmental conditions, including stress and disturbance. Some 

coralline are long-lived (up to 100 years, Halfar et al. 2007) and some are considered “ephemeral 

weeds” that can reach reproductive maturity in as little as a few weeks after settlement (Morcom 

et al. 1997). Like most red algae, coralline alternate between asexual and sexual reproduction 

(Miklasz 2012). Coralline algae reproduce intermittently throughout their lifespan (polycyclic) 

and are able to reproduce many times in a year, given optimal environmental conditions. There 

is a great diversity in reproductive timing and frequency in this family of algae – from constant 

reproduction in most articulate corallines, to seasonal reproduction in most crustose species, and 

for some, restricted to a few months of a year, and for others, occurring most of the year except a 

few months (Miklasz 2012). All of this indicates that coralline algae, as a species assemblage,

are very successful at responding to their environment, and may have greater diversity and 

plasticity than indicated by workshop participants. 

III. Management potential

Value of species to people: Low

• Confidence of workshop participants: High 

• Description of value: no answer provided 

Likelihood of managing or alleviating climate change impacts on species: Low-Moderate

• Confidence of workshop participants: High 

• Description of potential management options: no answer provided 

181
Supporting literature

The societal value for this species assemblage was rated as low, though scientists recognize the 

importance of coralline algae as the dominant assemblage in intertidal systems (Largier et al. 

2010), and in providing habitat and settlement cues for invertebrate larvae (Johansen 1981) and 

kelp zoospores (Hutto 2011). 

Exposure 

I. Future climate exposure6

Future climate and climate-driven changes identified (score7, confidence8): reduced pH (5, 

high), changes in sea surface temperature (3, moderate), changes in air temperature (1, high) 

Degree of exposure to future climate and climate-driven changes: Moderate

• Confidence of workshop participants: High

Additional participant comments

Potential areas of refugia from increased air temperature include low intertidal, subtidal, and 

tidepool habitats, and refugia from increased sea surface temperature include deeper subtidal

zones, as water may be expected to cool in these areas due to enhanced upwelling. No potential 

areas of refugia were identified for increased pH.

Literature Cited

Björk , M., S.Mzee Mohammed, M. Björklund , and A. Semesi. 2009. Coralline Algae, Important Coral-Reef 

Builders Threatened by Pollution. Ambio 24 (7/8):. 502-505.

Guenther, R.J. and P.T. Martone. 2014. Physiological performance of intertidal coralline algae during a simulated 

tidal cycle. Journal of Phycology 50: 310-321.

Halfar, J., R. Steneck, B. Schone, G. W. K. Moore, M. Joachimski, A. Kronz, J. Fietzke, and J. Estes. 2007. 

Coralline alga reveals first marine record of subarctic North Pacific climate change. Geophysical Research 

Letters 34: 1-5. 

Harley, C. D. G. 2008. Tidal dynamics, topographic orientation, and temperature-mediated mass mortalities on 

rocky shores. Marine Ecology-Progress Series 371:37-46.

Hoffman, G.E., T.G. Evens, M.W. Kelly, J.L. Padilla-Gamino, C.A. Blanchette, L. Washburn, F. Chan, M.A. 

McManus, B.A. Menge, B. Gaylord, T.M. Hill, E. Sanford, M. LaVigne, J.M. Rose, L. Kapsenberg, and 

J.M. Dutton. 2014. Exploring local adaptation and the ocean acidification seascape – studies in the 

California Current Large Marine Ecosystem. Biogeosciences 11: 1053-64.

Hutto, S.V. 2011. Differential recruitment of Postelsia palmaeformis across substrate types and potential 

facilitative effects of turfing algae. MS Thesis, Moss Landing Marine Laboratories.

Johansen, H. W. 1981. Coralline algae, a first synthesis. CRC Press, Inc. Boca Raton, Florida. 239 pp.

Koch, M., Bowes, G., Ross, C., and Zhang, X. H. 2013. Climate change and ocean acidification effects on 

seagrasses and marine macroalgae. Global Change Biology 19:103–132.

Kuffner, I.B., A.J. Andersson, P.L. Jokiel, K.S. Rodgers and F.T. Mackenzie. 2008. Decreased abundance of 

crustose coralline algae due to ocean acidification. Nature Geoscience 1:114-117.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

6 Supporting literature for future exposure to climate factors is provided in the introduction.

7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

182
and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Martin, S. and J.P. Gattuso. 2009. Response of Mediterranean coralline algae to ocean acidification and elevated 

temperature. Global Change Biology. 15:2089-2100. 

Martone, P.T., M. Alyono, and S. Stites. 2010. Bleaching of an intertidal coralline alga: untangling the effects of 

light, temperature, and desiccation. Marine Ecology Progress Series 416: 57-67.

Morcom, N. F., S. A. Ward, and W. J. Woelkerling. 1997. Competition of epiphytic nongeniculate corallines 

(Corallinales, Rhodophyta): overgrowth is not victory. Phycologia 36: 468-471. 

Padilla, D. K. 1984. The importance of form - differences in competitive ability, resistance to consumers and 

environmental stress in an assemblage of coralline algae. Journal of Experimental Marine Biology and 

Ecology 79: 105-127. 

Steneck, R. S. 1986. The ecology of coralline algal crusts - convergent patterns and adaptative strategies. Annual 

Review of Ecology and Systematics 17: 273-303. 

183
Gaper Clam (Tresus nuttalli and Tresus capax)

1

Executive Summary The gaper clam, also referred to as 

horse or horseneck clam, is a bivalve 

filter-feeder that inhabits lower 

intertidal and subtidal zones (to depths 

of 150 feet) in mud, sand and gravel 

substrate from Alaska to Baja 

California. T. nuttalli is more common to the south, and T. capax is more common to the north. 

Key climate sensitivities identified for these species by participants include sea surface 

temperature, precipitation, pH, and coastal erosion and key non-climate sensitivities include 

pollution and poisons. This species exhibits a transcontinental geographic extent and a stable 

population at abundant levels that supports a sustainable recreational fishery. Dispersal 

capability is likely relatively low due to the species’ short planktonic larval stage. The gaper 

clam exhibits overall low diversity due to low-moderate life history strategy diversity, moderate 

genetic diversity, low behavioral plasticity, and low phenotypic plasticity. Gaper clams are 

residents of nearshore, subtidal and intertidal estuarine habitat, so this species is adapted to a 

wide range of environmental variation. However, sessile, benthic species have no way to avoid 

exposure brought on by future climate change scenarios and other anthropogenic effects, with 

siphon retraction as the only behavioral modification available. The gaper clam holds moderate 

societal value due to the popular sport fishery that exists in some parts of the region, including 

Tomales and Bodega Bays, but management potential for this species is considered lowmoderate due to the inability to manage for climate impacts.

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): sea surface temperature (4, 

moderate), precipitation (4, moderate), pH (4, moderate), coastal erosion (4, moderate), air 

temperature (3, moderate), dissolved oxygen (DO) levels (3, moderate), wave action (3, 

moderate), dynamic ocean conditions (currents/mixing/stratification) (2, moderate), salinity (2, 

moderate)

Climate and climate-driven changes that may benefit the species: sea level rise 

• Description of benefit: Sea level rise may decrease the amount of time clams are exposed 

to predation from shorebirds during low tides and increase the amount of time clams can 

feed while they are submerged.

Overall species sensitivity to climate and climate-driven factors: Moderate

• Confidence of participants: Moderate 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by participants.

Gaper Clam Score Confidence 

Sensitivity 3 Moderate 2 Moderate

Exposure 4 Moderate-High 2 Moderate

Adaptive Capacity 3 Moderate 3 High

Vulnerability 3 Moderate 2 Moderate

184
Additional participant comments 

In general, because of the nature of estuarine habitats, clams have the ability to withstand 

changes in temperature and salinity as well as periods of anoxia; however, laboratory studies 

have shown that early life stages of related clams are sensitive to lower pH, increased 

temperature and hypoxia as well as a combination of these factors. 

Supporting literature

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. 

Sea Surface Temperature

Increasing water and air temperatures are magnified in estuaries relative to the outer coast and 

are important drivers of community and ecosystem responses, potentially resulting in range 

expansions of both native and non-native species (Williams and Grosholz 2008), enhancing the 

incidence of disease in estuarine species, and impacting estuarine circulation and dissolved 

oxygen (which is critical for the survival of the gaper clam, NOAA Ocean Service Education 

2008). Descriptions of gaper clam characteristics indicate that adult and juvenile life stages can 

withstand temperatures ranging between 2-20 ̊C (Lauzier et al. 1998). Literature specific to the 

gaper clam and related bivalves indicates significant impacts to the species’ larval stages. 

Larvae experienced 100% mortality at 20 ̊C (68 ̊F) and no significant difference in mortality 

among the 15, 10 and 5 ̊C treatments, though larval metamorphosis took significantly longer in 

the colder treatments (Bourne and Smith 1972). In another study on related clam species, 

increased temperature (24 and 28 ̊C) significantly depressed survival, development, growth, and 

lipid synthesis in larvae (Talmage and Gobler 2011). 

Precipitation

Changing patterns in precipitation may have consequences for the impact of invasive species, 

sediment deposition, erosion, flooding, river flow (which may impact the timing of mouth 

opening and closure of some estuaries), water chemistry and run-off. Increases in storm and 

precipitation intensity will likely lead to more frequent and severe flooding of intertidal gaper 

clam habitat (Largier et al. 2010). Gaper clams have been identified to tolerate salinities ranging 

between 27-33ppt (Lauzier et al. 1998). 

pH 

Currently, there are large gaps in the scientific understanding of the impact of low pH on 

estuarine molluscs, including the additive effects of multiple oceanographic changes and the 

capacity for species to acclimate and/or adapt to these changes (Gazeau et al. 2013). We can, 

however, generally expect species such as the gaper clam to suffer negative effects to the 

production and growth of their shells. In a study on related clam species, increased CO2 

concentrations (~250, 390, and 750 ppm, representative of past, present, and future summer 

conditions in temperate estuaries) significantly depressed survival, development, growth and 

lipid synthesis in larvae, which were much more vulnerable to increased CO2 than juveniles 

(Talmage and Gobler 2011). Because acidified water is often also low in dissolved oxygen, the 

combined effect of acidified and hypoxic water were tested on two bivalve species (bay scallop 

and hard clam) and found to have synergistic negative effects on both species, with reduced 

survivorship, growth and metamorphosis documented for larval stages, and reduced growth 

documented for later stages (Gobler et al. 2014). 

185
Coastal erosion

Gaper clams may be directly impacted by coastal erosion or indirectly via human responses such 

as armoring and beach nourishment that will impact sediment supply and run-off (Largier et al. 

2010). Erosion transports sediment into nearshore waters, which does help to maintain softbottom habitat. However, if sedimentation is excessive, negative impacts can include 

smothering of gaper clams, oxygen depletion and increased turbidity (Schueler 1997). 

An increased tidal prism is thought to have contributed to the conversion of a few dominant 

habitat types to a patchwork of habitat types and the formation of subtidal channels in Elkhorn 

Slough, an estuary located just south of the study region (Ritter et al. 2008). The subsequent loss 

of fine sediment due to the increased tidal prism resulted in a shift from gaper clams to boring 

clams (ESTWPT 2007). 

II. Sensitivities to disturbance regimes

Disturbance regimes identified: disease, storms, and flooding 

Overall species sensitivity to disturbance regimes: Moderate

• Confidence of workshop participants: Low

Supporting literature

Disease

Increase in disease is often linked to increase in water temperature, as both pathogen survival and 

host susceptibility are enhanced (Friedman et al. 1997, Harvell et al. 1999, Raimondi et al. 2002, 

Largier et al. 2010). Infection of gaper clams by a haplosporidan parasite was documented in 

Yaquina bay, Oregon in the 1970s, with a 43% infection rate. Twenty percent of those infected 

were emaciated and sluggish in response to prodding, and had a watery and transparent mantle 

and underdeveloped gonads (Armstrong and Armstrong 1973). Mass mortality in related clams 

has been attributed to similar parasites. Other parasites reported in gaper clams are cyclopoid 

copepods that infect the gill and a larval tapeworm (Echeneibothrium sp) that completes its adult 

cycle in the bat ray (Myliobatis californicus) (Katansky et al. 1969, Lauzier et al. 1998). 

Flooding 

Increased flooding is expected with sea level rise and more intense precipitation events (see 

climate sensitivities above). The estuarine habitat is highly sensitive to flooding because of 

inundation and restricted landward migration due to armoring, roads and other structures 

(Largier et al. 2010).

Storms

Models suggest that the tracks of storms in the northeast Pacific Ocean will experience an 

increase in occurrence of extreme conditions, though the number of extreme events may not 

change (Largier et al. 2010). Increased storm intensity will impact both wave energy and the 

timing and intensity of precipitation events, with major consequences for estuarine habitat (see 

Precipitation and Erosion sections above). 

III. Dependencies

Species dependence on one or more sensitive habitat types: High

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: soft-bottom subtidal areas and estuaries

186
Species dependence on specific prey or forage species: Low

• Confidence of workshop participants: High 

Other critical dependencies: no answer provided 

Specialization of species (1=generalist; 5=specialist): 2

• Confidence of workshop participants: High

IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): pollution and poisons (5, moderate), 

harvest (3, low), dredging (3, low), overwater/underwater structures (3, low), recreation (2, low) 

Overall species sensitivity to non-climate stressors: Moderate

• Confidence of workshop participants: Low

Overall current exposure to non-climate stressors: Moderate

• Confidence of workshop participants: Low

Supporting literature

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. 

Pollution/Poisons: 

Though there are no direct studies of the impact of pollutants on the gaper clam, exposure to 

agricultural and livestock waste, wastewater, sewage outfalls, historic mining, and industrial 

wastes (Largier et al. 2010) will likely cause the accumulation of toxins and heavy metals in the 

tissues of gaper clams, potentially impacting individual health and population abundance, as has 

been documented in other bivalve species (Pacific Biodiversity Institute, SIMoN 2014). This 

exposure to pollutants may potentially lower the fitness of clams in combination with other 

environmental stressors (Christy Juhasz, pers. comm., 2014). Toxin exposure has been shown to 

lower survival under laboratory conditions in a similar clam species when exposed to the 

pollutant cadmium and anoxic conditions (de Zwaan et al. 1995). The release of pollutants 

during dredging of soft bottom habitats has been documented, and may potentially expose 

species to additional pollutants (pers. comm. Sarah Allen, NPS). Increased extreme precipitation 

events will impact the timing and intensity of runoff of terrestrial pollutants, which will have 

important consequences for the timing and intensity of harmful algal blooms (Anderson et al. 

2008; Kudela et al. 2008). 

V. Other sensitivities: none identified 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

187
Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 5

• Confidence of workshop participants: High 

Population status of the species (1=endangered; 5=robust): 4

• Confidence of workshop participants: Moderate 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 4 

• Confidence of workshop participants: Moderate 

Dispersal ability of the species: Low-Moderate 

• Confidence of workshop participants: Moderate 

Maximum annual dispersal distance: 5-25km 

• Confidence of workshop participants: Low

Supporting literature

Though the species is harvested recreationally, both intertidal and subtidal populations seem to 

be at sustainable levels, with subtidal individuals providing a spawning refuge from harvest 

(Moore 2001). The gaper clam has low-moderate dispersal capability, possibly limited to less 

than 25 km due to the relatively short duration of the planktonic larval stage (21-30 days, 

depending on water temperature, Bourne and Smith 1972, Clark et al. 1975) and the retention 

effects of the coastal boundary layer (Largier 2003, Christy Juhasz, pers. comm., 2014). 

II. Intraspecific/Life history diversity

Diversity of life history strategies: Low-Moderate 

• Confidence of workshop participants: Moderate 

Genetic diversity: Moderate

• Confidence of workshop participants: Moderate

Behavioral plasticity: Low

• Confidence of workshop participants: Moderate 

Phenotypic plasticity: Low

• Confidence of workshop participants: Low

Overall degree of diversity/plasticity of the species: Low-Moderate

• Confidence of workshop participants: Moderate 

Additional participant comments

Gaper clams are residents of nearshore, intertidal and subtidal estuarine habitat, so this species is 

adapted to a wide range of physical oceanographic changes that fluctuate during daily tidal 

cycles and seasonally, between winter and spring months (e.g. changes in salinity and hypoxia). 

However, sessile, benthic species have no way to avoid exposure brought on by future climate 

change scenarios and other anthropogenic effects, and intertidal populations are more likely to 

experience and be more susceptible to future change. The only behavioral modification the gaper 

188
clams can make in response to environmental exposure is to retract its siphon, however they are 

unable to fully close their shell valves. 

Supporting literature

The gaper clam produces many offspring over a relatively short lifespan, with a maximum 

lifespan of 17 years (Moore 2001). The clams reach sexual maturity at about 2 to 3 years of age, 

and can release gametes more than once, though it is unknown how many times per year (Clark 

et al. 1975, Moore 2001, Christy Juhasz, pers. comm., 2014). Machell and De Martini (1971) 

showed that reproduction of T. capax clams in Humboldt Bay, CA (north of the study region) 

spawned between January and April, coinciding with decreases in seasonal water temperature 

and salinity. Clark et al. (1975) found that T. nuttallii populations in Elkhorn Slough spawned 

around the same time period between February and April, but were still actively spawning 

throughout the year and attributed this to large daily fluctuations in temperature 

III. Management potential

Value of species to people: Moderate

• Confidence of workshop participants: High

• Description of value: Value exists for the popular sport fishery within the study region in 

Tomales Bay, Bodega Bay and Drakes Estero.

Likelihood of managing or alleviating climate change impacts on species: Low-Moderate

• Confidence of workshop participants: Moderate

• Description of possible management options: none identified 

Supporting literature

In Tomales Bay in the 1990s, as many as 1,200 people were counted during one low tide digging 

for clams (Moore 2001); more current estimates are not available, and these numbers have likely 

dropped due to lack of transportation for clammers. In Bodega Bay a high count of several 

hundred clammers was observed during a low tide in 2012 (Christy Juhasz, pers. comm., 2014). 

Harvest is not considered a management concern for the gaper clam, however, and local 

population declines have been attributed instead to reduced tidal flow and increased 

sedimentation, which may reduce gaper clam habitat, and climatic factors, including long-term 

climate change and short-term ENSO cycles, which are difficult to manage (Moore 2001). 

IV. Other Adaptive Capacity Factors: none identified

189
Exposure 

I. Future climate exposure6

Future climate and climate-driven changes identified (score7, confidence8): changes in air 

temperature (5, high), increased coastal erosion and runoff (5, moderate), decreased pH (4, 

moderate), decreased dissolved oxygen (DO) levels (4, high), changes in sea surface temperature

(4, high), increased flooding (4, moderate), changes in precipitation (4, moderate), changes in 

salinity (4, moderate), increased storminess (3, moderate)

Degree of exposure to future climate and climate-driven changes: Moderate

• Confidence of workshop participants: Moderate 

Additional participant comments

Gaper clams reside in nearshore intertidal estuarine habitats and experience a wide range of 

physical oceanographic conditions on a daily (tidal cycles) and seasonal basis. However, this 

sessile benthic species has no way to avoid increased exposure resulting from anthropogenic 

climate change.

Literature Cited

Anderson, D., J. Burkholder, W. Cochlan, P. Glibert, C. Gobler, C. Heil, R. Kudela, M. Parsons, J. Rensell, D. 

Townsend, V. Trainer, and G. Vargo. 2008. Harmful algal blooms and eutrophication: Examples and 

linkages from selected coastal regions of the United States. Harmful Algae 8: 39-53. 

Armstrong, D.A. and J.L. Armstrong. 1973. A haplosporidan infection in gaper clams, Tresus capax (Gould), from 

Yaquina Bay, Oregon. Proceedings of the National Shellfisheries Assocation 64:68-72.

Bourne, N. and D.W. Smith. 1972. The effect of temperature on the larval development of the horse clam, Tresus 

capax. Proc Nat Shell Assoc. 62:35-37.

Clark, P., J. Nybakken, L. Laurent. 1975. Aspects of the life history of Tresus nuttallii in Elkhorn Slough. California 

Fish and Game 61(4): 215-227. 

de Zwaan A., P. Cortesi, O.Cattani. 1995. Resistance of bivalves to anoxia as a response to pollution-induced 

environmental stress. The Science of the Total Environment. 171:121-125.

Elkhorn Slough Tidal Wetland Project Team (ESTWPT). 2007. Elkhorn Slough tidal Wetland strategic plan. A 

report describing Elkhorn Slough’s estuarine habitats, main impacts, and broad conservation and 

restoration recommendations. 100 pp. 

Friedman, C.S., M. Thomson, C. Chun, P.L. Haaker and R.P. Hedrick. 1997. Withering syndrome of the black 

abalone, Haliotis cracherodii (Leach): Water temperature, food availability, and parasite as possible 

causes. Journal of Shellfish Research 16:403-411.

Gazeau, F., L.M. Parker, S. Comeau, J.Gattuso, W.A. O’Connor, S. Martin, H.Pörtner, and P.M. Ross. 2013. 

Impacts of ocean acidification on marine shelled molluscs. Mar. Biol. 160: 2207-2245. 

Gobler, C.J., E.L. DePasquale, A.W. Griffith, and H. Baumann. 2014. Hypoxia and acidification have additive and 

synergistic negative effects on the growth, survival, and metamorphosis of early life stage bivalves. PloS 

ONE. 9 (1): e83648.

Harvell, C.D., K. Kim, J.M. Burkholder, R.R. Colwell, P.R. Epstein, D.J. Grimes, E.E. Hofmann, E.K. Lipp, 

A.D.M.E. Osterhaus, R.M. Overstreet, J.W. Porter, G.W. Smith and G.R. Vasta. 1999. Emerging marine 

diseases – climate links and anthropogenic factors. Science 285:1505-1510.

Kudela, R.M., JQ Lane, and WP Cochlan. 2008. The potential role of anthropogenically derived nitrogen in the 

growth of harmful algae in California, USA. Harmful Algae 8, 103-110. 

6 Supporting literature for future exposure to climate factors is provided in the introduction. 7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

190
Largier, J.L. 2003. Considerations in estimating larval dispersal distances from oceanographic data. Ecological 

Applications, 13(1): S71-S89.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Lauzier R.B., C.M. Hand, A. Campbell, S. Heizer. 1998. A review of the biology and fisheries of the horse clams 

 (Tresus capax and Tresus nuttallii). Canadian Stock Assessment Secreteriat, Research Document N898/88,

28pp.

Machell J.R. and J.D. De Martini. 1971. An annual reproductive cycle of the gaper clam, Tresus capax, (Gould), in 

south Humboldt Bay. California Fish and Game 57(4): 274-282.

Moore, T.O. 2001. California Living Marine Resources: A Status Report. Gaper Clams. California Department of 

Fish and Game. Accessed August 26, 2014 from: 

https://nrm.dfg.ca.gov/FileHandler.ashx?DocumentID=34267. 

Pacific Biodiversity Institute. Olympia Oyster. Accessed August 26, 2014, from: 

http://www.pacificbio.org/initiatives/ESIN/OtherInvertebrates/OlympiaOyster/OlympiaOyster_pg.html. 

Raimondi, P. T., C. M. Wilson, R. F. Ambrose, J. M. Engle, and T. E. Minchinton. 2002. Continued declines of 

black abalone along the coast of California: are mass mortalities related to El Niño events? Marine Ecology 

Progress Series 242:143-152.

Ritter, A.F., K. Wasson, S.I. Lonhart, R.K. Preisler, A. Woolfolk, K.A. Griffith, S. Connors, K.W. Heiman. 2008. 

Ecological signatures of anthropogenically altered tidal exchange in estuarine ecosystems. Estuaries and 

Coasts 31:554–571.

Schueler, T. R. 1997. Impact of suspended and deposited sediment. Watershed Protection Techniques 2(3): 443-4. 

Sanctuary Integrated Monitoring Network (SIMoN). 2014. California Mussel. Retrieved July 28, 2014 from: 

http://sanctuarysimon.org/species/mytilus/californianus/california-mussel. 

Talmage, S.C. and C.J. Gobler. 2011. Effects of elevated temperature and carbon dioxide on the growth and survival 

of larvae and juveniles of three species of Northwest Atlantic bivalves. PloS ONE. 6 (10): e26941.

Williams, S.L. and E. D. Grosholz. 2008. The invasive species challenge in estuarine and coastal environments: 

Marrying management and science. Estuaries and Coasts 31: 3-20. 

191
Krill1

Executive Summary Krill are small euphausiid 

crustaceans that swarm in great 

concentrations in the study region 

due to high local productivity. Key 

climate sensitivities identified by 

workshop participants include sea 

surface temperature and dynamic ocean conditions (currents/mixing/stratification), and key nonclimate sensitivities include pollution and poisons. The two most common species in this 

region, Thysanoessa spinifera and Euphausia pacifica, have a broad, transcontinental geographic 

distribution and a continuous, stable population at abundant levels. T. spinifera is found mostly 

in shallower water over the continental shelf and E. pacifica is usually found in deeper water 

toward the margin of the shelf and beyond. Krill biomass in the region varies interannually, 

potentially due to variations in water temperature. The literature indicates a variety of behavioral 

and physiological responses and adaptations to variable environmental conditions, such as water 

temperature, oxygen concentration and predation, both among and within species. Krill were 

identified as having low-moderate societal value, though they are critical components of the 

region’s food web and a source of food for many species, and moderate management potential 

that may be possible through regulation of future harvest, though most stressors to this species 

are currently a result of oceanographic processes and climate impacts that would be difficult to 

manage.

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): dynamic ocean conditions 

(currents/mixing/stratification) (3, moderate), sea surface temperature (2, moderate) 

Climate and climate-driven changes that may benefit the species: upwelling

• Description of benefit: Increased upwelling could lead to an increase in krill biomass.

Overall species sensitivity to climate and climate-driven factors: Moderate

• Confidence of workshop participants: Moderate 

Additional participant comments 

Little information is available on the direct impact of sea surface temperature on krill abundance, 

though this climate factor may affect their relative productivity in the study region. As the 

primary delivery method of deep, cold, nutrient-rich water, upwelling likely leads to increased 

krill abundance. 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Krill Score Confidence

Sensitivity 1 Low 3 High

Exposure 5 High 3 High

Adaptive Capacity 4 Moderate-High 2 Moderate

Vulnerability 2 Low-Moderate 3 High

192
Supporting literature

Dynamic ocean conditions (currents/mixing/stratification)

Changes in the timing of upwelling impact krill, as late upwelling is generally associated with 

poor ocean productivity, low krill abundance, and subsequent late seabird breeding (Abraham 

and Sydeman 2004, Jahncke et al. 2008), whereas strong and early upwelling is associated with 

increased abundance of krill and above-average seabird breeding success. Weak upwelling 

years, including 2005 and 2006, result in a decline in phytoplankton and zooplankton abundance, 

including lipid-rich adult krill. This decline caused seabird breeding failure, decreased salmon 

survival and decreased blue whale sightings (Jahncke et al. 2008, Largier et al. 2010). Strong 

upwelling, on the other hand, may counteract rising sea surface temperatures and promote 

primary productivity (Largier et al. 2010), but could shift zooplankton to deeper waters (Pringle 

2007), potentially decreasing food availability for marine organisms (Largier et al. 2010). El 

Niño events decrease upwelling and mixing, and positive phases of the PDO lead to 

downwelling, reducing nutrient delivery to photic zones, decreasing primary productivity 

(Young et al. 2012), potentially decreasing the abundance of krill. 

Sea Surface Temperature

Warmer sea surface temperatures can cause large thermoclines in the water column, increasing 

stratification, reducing ocean mixing and nutrient delivery to upper ocean photic zones, resulting 

in decreased primary productivity that impacts krill abundance and trophic functioning (Young et 

al. 2012). Results from the 30-year California Cooperative Oceanic Fisheries Investigation 

(CalCOFI) dataset indicate overall an 80% decrease in zooplankton biomass since the early 

1950s, with associated increases in ocean temperature in the southern California Bight region 

(Roemmich and McGowan 1995; McGowan et al. 1996, 1998, 2003). However, a closer look at 

the two dominant krill species in the region indicates no significant decrease, and instead, an 

increase in the abundance of a sub-tropical species (Brinton and Townsend 2003). Overall, the 

zooplankton community in the region has become more diverse and more sub-tropical as sea 

surface temperatures increase, with a greater composition of smaller and less lipid-rich species, 

which may have significant impacts on energy transfer and food web dynamics (Largier et al. 

2010). 

II. Sensitivities to disturbance regimes

Disturbance regimes identified: wind

Overall species sensitivity to disturbance regimes: Moderate

• Confidence of workshop participants: Moderate 

Additional participant comments

Changes in prevailing wind patterns can cause changes in the timing and intensity of upwelling, 

which will potentially impact krill abundance and productivity (see Dynamic Ocean Conditions 

section above). 

193
III. Dependencies

Species dependence on one or more sensitive habitat types: Low

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: none 

Species dependence on specific prey or forage species: Low

• Confidence of workshop participants: Moderate 

Other critical dependencies: no answer provided 

Specialization of species (1=generalist; 5=specialist): 2

• Confidence of workshop participants: High 

IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): pollution and poisons (1, high) 

Overall species sensitivity to non-climate stressors: Low

• Confidence of workshop participants: High 

Overall species exposure to non-climate stressors: Low

• Confidence of workshop participants: High 

Additional participant comments

The only stressor that would be expected to significantly impact species abundance is fishing 

pressure, which does not currently exist in this region, though commercial fisheries do exist in 

the Southern ocean and around Japan. 

Supporting literature

Though the only non-climate stressor identified for this species received a low sensitivity score, 

literature review was conducted on this factor in order to provide some information on its impact. 

However, it should be noted that krill is likely more sensitive to direct impacts from climate 

change rather than human activity. 

Pollution and Poison 

Dispersed oil is expected to negatively impact krill and other zooplankton in the study region 

(Mearns 2012, Vulnerability Assessment Workshop, pers. comm., 2014). Over 6,000 

commercial vessels transit in and out of San Francisco Bay every year, with 5% of these as large 

cargo vessels that can carry up to one million gallons of bunker fuel (GFNMS 2008). All 

transiting vessels, including military, research and fishing vessels, carry crude oil or fuel, posing 

a potential risk to euphausiid populations in the region (Largier et al. 2010). 

V. Other sensitivities: none identified 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

194
Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 5

• Confidence of workshop participants: High 

Population status of the species (1=endangered; 5=robust): 4.5 

• Confidence of workshop participants: Moderate 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 5

• Confidence of workshop participants: Low

Dispersal ability of the species: High 

• Confidence of workshop participants: Low

Maximum annual dispersal distance: >100km 

• Confidence of workshop participants: Low

Supporting literature

Euphausiid biomass in the region, measured by acoustics, peaked in July 2013, and adult krill, 

which are larger and higher in lipid content than juveniles, dominate the zooplankton samples 

during cold water years, including 2013 (Elliott and Jahncke 2014). However, the percentage of 

adult stages in euphausiid samples appears to be declining since mid-2010 (Elliott and Jahncke 

2014). 

II. Intraspecific/Life history diversity

Vulnerability assessment workshop participants did not provide information for krill 

diversity/plasticity. However, evidence does exist that krill species display plasticity in behavior 

and phenotype to respond to environmental variation. For example, a dominant species in this 

study region, Euphausia pacifica, is able to shrink between moulting periods as an adaptation to 

periods of abnormally high water temperature (Marinovic and Mangel 1999), and variable 

hatching time of krill eggs has been documented as a function of temperature (Ross et al.

1988, Iguchi and Ikeda 1994). While faster development occurs at higher temperatures, this may 

not be the case in upwelling systems, where sustained warmer temperatures are often associated 

with periods of poorer productivity and less food available to euphausiids (Feinberg et al. 2006). 

Larval stages of an Antarctic species of krill can regulate metabolism over a wide range of 

oxygen concentrations and temperatures, apparently an adaptation to the highly variable 

conditions encountered during vertical migration (Quentin and Ross 1989). Swarming and 

migration behavior vary by species; Thysanoessa spinifera forms dense surface swarms during 

the day time for increased mating opportunities, which in turn provides enhanced feeding 

opportunities for large whales, and Euphausia pacifica exhibits mass diurnal vertical migration, 

swarming at the surface at night for mating and to minimize exposure to predators while feeding 

(Howard 2010). 

Krill produce many offspring with a short generation time. Reproductive maturity is reached 

within 24 months (Vulnerability Assessment Workshop, pers. comm., 2014), the lifespan of krill 

species in this study region (Nicol and Endo 1999), and krill utilize broadcast spawning, with the 

female releasing her fertilized eggs into the water column that typically hatch within 2 days 

195
(Gómez-Gutiérrez 2002). Krill can have multiple reproductive events in one season, with time 

between spawning lasting on the order of days (Cuzin-Roudy 2000). 

III. Management potential

Value of species to people: Low-Moderate

• Confidence of workshop participants: Moderate 

• Description of value: though low value to the general public, krill are recognized as being 

critical components of the region’s food web and a source of food for many species 

Likelihood of managing or alleviating climate change impacts on species: Moderate

• Confidence of workshop participants: High 

• Description of potential management options: though most stressors to this species are 

currently a result of oceanographic processes and climate impacts that would be difficult 

to manage, regulation of future harvest is a potential management option 

Supporting literature

Krill are an important component of the pelagic food web, as they convert the primary 

productivity of their prey into a more suitable form for consumption for many species of marine 

top predators, including seabirds, fishes and whales (Saether et al. 1986, Elliott and Jahncke 

2014). 

IV. Other adaptive capacity factors: none identified 

Exposure 

I. Future climate exposure6

Future climate and climate-driven changes identified (score7, confidence8): changes in sea 

surface temperature (5, high), changes in salinity (5, high), altered currents/mixing (5, high) 

Degree of exposure to future climate and climate-driven changes: High

• Confidence of workshop participants: no score provided 

Additional participant comments

Exposure to climate factors is directly related to the future direction of upwelling frequency and 

intensity.

6 Supporting literature for future exposure to climate factors is provided in the introduction.

7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

196
Literature Cited

Abraham, C.L. and W.J. Sydeman. 2004. Ocean climate, euphausiids and auklet nesting: interannual trends and 

variation in phenology, diet and growth of a planktivorous seabird. Marine Ecology Progress Series 

274:235-250.

Brinton, E and A., Townsend. 2003. Decadal variability in abundances of the dominant euphausiid species in the 

southern sectors of the California Current. Deep Sea Research II 50:2449‐2472.

Cuzin-Roudy, J. 2000. Seasonal reproduction, multiple spawning, and fecundity in northern krill, Meganyctiphanes 

norvegica, and Antarctic krill, Euphausia superba. Canadian Journal of Fisheries and Aquatic 

Sciences 57 (S3): 6–15. 

Elliott, M. L. and J. Jahncke. 2014. Ocean Climate Indicators Status Report – 2013. Unpublished Report. Point Blue 

Conservation Science, Petaluma, California. Point Blue contribution number 1982.

Feinberg, L., C. Shaw, and W. Peterson. 2006. Larval development of Euphausia pacifica in the laboratory: 

variability in developmental pathways. Marine Ecology Progress Series 316: 127-137.

Gómez-Gutiérrez, J. 2002. Hatching mechanism and delayed hatching of the eggs of three broadcast spawning 

euphausiid species under laboratory conditions. Journal of Plankton Research 24 (12): 1265–1276.

Gulf of the Farallones National Marine Sanctuary (GFNMS). 2008. Management Plan. 

http://farallones.noaa.gov/manage/plan.html#plan. 

Howard, D. 2010. Krill in Cordell Bank National Marine Sanctuary. National Oceanic and Atmospheric 

Administration. Retrieved August 15, 2014.

Iguchi, N. and Ikeda, T. 1994. Experimental study on brood size, egg hatchability and early development time of 

the euphausiid Euphausia pacifica from Toyama Bay, Southern Japan. Sea. Bull. Sea Nat. Fish. Res. 

Inst. 44: 49–57.

Jahncke, J., Saenz, B.L., Abraham, C.L., Rintoul, C., Bradley, R.W., and Sydeman, W.J. 2008. Ecosystem responses 

to short-term climate variability in the Gulf of the Farallones, California. Progress in Oceanography 

77:182-193.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Marinovic, B. and M. Mangel. 1999. Krill can shrink as an ecological adaptation to temporarily unfavourable 

environments. Ecology Letters 2: 338–343.

McGowan, J.A., D. Chelton, and A. Conversi. 1996. Plankton patterns, climate, and change in the California 

Current. CalCOFI Reports 37:45-68. 

McGowan, J.A., D.R. Cayan, and L.M. Dorman. 1998. Climate‐ocean variability and ecosystem response in the 

Northeast Pacific. Science 281:210-217. 

McGowan, J.A., S.J. Bograd, R.J. Lynn, and A.J. Miller. 2003. The biological response to the 1977 regime shift in 

the California Current. Deep Sea Research II 50:2567-2582.

Mearns, A. 2012. Oil dispersants: to use or not use. Oral presentation, Cordell Bank and Gulf of the Farallones 

National Marine Sanctuaries Advisory Councils’ Vessel Spills Working Group, Petaluma, CA. 

Nicol, S. and Y. Endo. 1999. Krill fisheries: Development, management and ecosystem implications. Aquatic 

Living Resources 12 (2): 105–120.

Pringle, J.M. 2007. Turbulence avoidance and the wind-driven transport of plankton in the surface Ekman layer. 

Continental Shelf Research 27:670-678.

Quentin, L. B. and Ross, R. M. 1989. Effects of oxygen, temperature and age on the metabolic rate of the embryos 

and early larval stage of the Antarctic krill Euphausia superba Dana. J. Exp. Mar. Biol. Ecol. 133: 103– 

127.

Roemmich, D., J. McGowan. 1995. Climatic warming and the decline of zooplankton in the California Current. 

Science 267: 1324-1326.

Ross, R. M., Quetin L. B. and Kirsch, E. 1988. Effect of temperature on development times and survival on early 

larval stages of Euphausia superba Dana. J. Exp. Mar. Biol. Ecol. 121: 55–71.

Saether, O., T.E. Ellingsen and V. Mohr. 1986. Lipids of North Atlantic krill. Journal of Lipid Research 27(3): 274- 

85.

Young, L. R.M. Suryan, D. Duffy, and W.J. Sydemann. 2012. Climate Change and Seabirds of the California 

Current and Pacific Islands Ecosystems: Observed and Potential Impacts and Management Implications. 

Final Report to the U.S. Fish and Wildlife Service, Region 1. Unpublished.

197
Pacific Mole Crab (Emerita analoga)

1

Executive Summary The Pacific mole crab (also called sand 

crab) is a decapod crustacean that 

burrows in the sand in the swash zone 

and uses its antennae to filter feed. 

This species occurs along sandy 

beaches from Alaska to Baja California 

in North America, and from Peru to Argentina in South America. 

Key climate sensitivities identified for this species by participants includes salinity, erosion, pH, 

and precipitation and key non-climate sensitivities include roads/armoring and land use change. 

The Pacific mole crab exhibits a transcontinental geographic extent, a healthy, continuous and 

connected population, and a high dispersal capability due to the long planktonic larval stage. 

This species overall displays moderate diversity/plasticity, including limited genetic diversity 

due to its high dispersal, but behavioral and phenotypic plasticity based on variable beach 

morphodynamics and diversity in reproductive strategy, including variable developmental forms 

that are able to reproduce and variable timing of reproductive cycles. The societal value for this 

species is considered low, with some value held by shore fishermen (though the scientific 

community values this species greatly for its important role as prey for birds and fish), and 

management potential is considered low-moderate, with some possibility to manage for beach 

erosion and nourishment. 

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): salinity (5, high), coastal 

erosion (3.5, moderate), precipitation (3, moderate), pH (3, moderate), sea level rise (2, low), 

dynamic ocean conditions (currents/mixing/stratification) (2, low), harmful algal blooms (2, 

low), sea surface temperature (1, moderate)

Climate and climate-driven changes that may benefit the species: wave action 

• Description of benefit: Increased wave action could make some sheltered beaches a more 

suitable wave-exposed habitat for mole crabs. 

Overall species sensitivity to climate and climate-driven factors: Moderate

• Confidence of workshop participants: Moderate 

Additional participant comments 

Local populations are heavily dependent on successful larval recruitment, and changes in 

dynamic ocean conditions in response to climate change could have significant impacts on local 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Pacific mole crab Score Confidence 

Sensitivity 2 Low-Moderate 3 High

Exposure 5 High 3 High

Adaptive Capacity 3 Moderate 2 Moderate

Vulnerability 3 Moderate 3 High

198
populations. Additionally, decreasing ocean pH levels, exposure to fresh and brackish water, and 

HABs may have adverse impacts on local population abundance. 

Supporting literature

Literature review was conducted for those factors scoring 3 or higher, although the other 

sensitivities identified should also be considered. Altered currents and mixing were also 

identified as a potential source of sensitivity for the species, though the degree of sensitivity is 

unknown, due to the possible impact on larval transport and subsequent recruitment (Sorte et al. 

2001; Amy Dean, pers. comm., 2014).

Salinity

Artificial freshwater discharge from a canal was found to significantly impact the distribution, 

abundance, and life history traits of a related species of mole crab, Emerita brasiliensis, with 

decreased abundance of juveniles, males, females and ovigerous females, decreases in weight 

and fecundity, and disruption of female maturity patterns associated with the canal (Lercari and 

Defeo 1999). 

Erosion 

There is existing evidence of a high level of disturbance to mole crab populations if beaches are 

highly eroded, and there are beaches in California that lose much of their sand in the winter; if 

there is no sand, there is no habitat for mole crabs (Amy Dean, pers. comm., 2014). However, 

more recent experimental evidence on a related species, Emerita talpoida, indicates that the 

species can rapidly recover, and in some cases, maintain its abundance during even substantial 

loss of beach sand due to storm activity (Peterson et al., unpublished). Additionally, though it 

would be assumed that increased wave energy would impose a greater metabolic cost on mole 

crabs trying to maintain their position in the swash zone, no significant difference was found in

oxygen uptake of the Pacific mole crab at varying levels of wave energy (Lastra et al. 2004), 

which suggests acclimation to this environmental variable. Consequently, it may be the response 

to erosion by managers that could impact this species most. Beach nourishment has been shown 

to inhibit adult E. talpoida burrowing behavior, negatively impacting its ability to feed and to 

maintain its position in the swash zone, due to an increased proportion of large shell pieces 

(>2mm) in nourished sand (Manning et al. 2013). 

pH 

The effects of decreasing pH on mole crabs will likely be felt most strongly during upwelling 

events that bring cold and deep water to the surface (Feely et al. 2008). This water is 

undersaturated in aragonite, and is expected to impede the ability of mole crabs to strengthen 

their exoskeletons with calcium carbonate, resulting in weaker exoskeletons (Raven 2005, 

Largier et al. 2010). Many studies have shown this effect on other invertebrate species, 

including the California Mussel, which precipitated weaker, thinner and smaller shells under 

projected 2100 CO2 concentrations (Gaylord et al. 2011). 

Precipitation

The potential impact of precipitation on the Pacific mole crab will likely be caused by

subsequent increased exposure to freshwater due to more intense periods of river flow and 

freshwater discharge, altering the local salinity and impacting local mole crab abundance (see 

salinity section above). Altered precipitation patterns may also impact the timing of material 

transport to beach systems. Short, heavy precipitation events can increase freshwater sediment 

199
discharge and bolster beach and dune systems, though this dynamic is mediated by inland water 

and sediment retention structures such as dams (Slagel and Griggs 2008, Largier et al. 2010). 

II. Sensitivities to disturbance regimes

Disturbance regimes identified: storms and flooding 

Overall species sensitivity to disturbance regimes: Moderate

• Confidence of workshop participants: Moderate 

Additional participant comments

The mole crab was identified as moderately sensitive to storm and flooding events, primarily due 

to its sensitivity to change in salinity (see precipitation and salinity sections above). In general, 

however, this species is highly adapted to live in disturbed environments, so likely will not be 

greatly impacted by disturbance regimes.

III. Dependencies

Species dependence on one or more sensitive habitat types: Low

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: none listed 

Species dependence on specific prey or forage species: Low

• Confidence of workshop participants: High 

Other critical dependencies: reproductive dependency 

• Degree of dependence: Moderate

• Confidence of workshop participants: Moderate 

Specialization of species (1=generalist; 5=specialist): 1

• Confidence of workshop participants: High 

Additional participant comments

The mole crab has a low dependency on sensitive habitat due to the expected persistence of 

wave-disturbed beaches and is considered to be more of a generalist, and therefore may have 

greater flexibility to adapt to environmental changes. 

Supporting literature

The ability of the species to burrow into a variety of grain sizes (Dugan et al. 2000), and a low 

dependency on specific prey, as the species filters various suspended food particles, such as 

detritus and phytoplankton, from the water column with its antennae (SIMoN 2014). 

IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): land use change (5, high), coastal 

roads/armoring (3, moderate), pollution and poisons (2, moderate) 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

200
Overall species sensitivity to non-climate stressors: Moderate

• Confidence of workshop participants: High

Overall species exposure to non-climate stressors: Low

• Confidence of workshop participants: Moderate

Supporting literature

Literature review was conducted for those factors scoring 3 or higher, although the other 

sensitivities identified should also be considered. 

Roads/Armoring

Coastal armoring and road construction, in response to enhanced erosion of bluffs and cliffs in 

the study region, prevent upland beach and dune migration in response to sea level rise (Largier 

et al. 2010, Vulnerability Assessment Workshop, pers. comm., 2014) and increased passive 

erosion, increasing the sensitivity of beach and dune systems (Dugan et al. 2008). These effects 

will only become more pronounced with sea level rise as these structures interact with waves and 

tides (Dugan et al. 2008). In addition, armoring can replace beach habitat, reducing beach extent 

and negatively impacting mole crabs (Dugan et al. 2008). Armoring is projected to increase, 

although beach nourishment is now being used more frequently as an alternative (Defeo et al. 

2009). 

Land Use Change 

Land use change (i.e., development, watershed alterations, livestock grazing and agriculture) 

may disrupt sediment supply to beaches, and impact water quality in the region, resulting in high 

coliform, bacterial and toxic metal contamination (e.g., high mercury levels, ONMS 2010). In 

addition, development and landscape irrigation on top of coastal cliffs that often back beaches in 

the study region can increase internal pore pressures of cliff materials, decreasing resilience and 

accelerating coastal erosion (Griggs and Patsch 2004). The construction of jetties or breakwaters 

can deprive down coast fronting beaches of sand, while simultaneously increasing sediment 

delivery to up coast fronting beaches (Griggs and Patsch 2004). 

V. Other sensitivities: none identified

Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 4

• Confidence of workshop participants: High 

Population status of the species (1=endangered; 5=robust): 5

• Confidence of workshop participants: High 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 5 

• Confidence of workshop participants: High 

Dispersal ability of the species: High 

• Confidence of workshop participants: High 

201
Maximum annual dispersal distance: unknown 

Supporting literature

This species exhibits a broad geographic extent, from Alaska to Baja California, Mexico, in 

North America (SIMoN). The long planktonic period of the larval stage (lasting up to 130 days) 

enables wide dispersal of the species, potentially colonizing new areas and annually restocking 

already existing populations (Efford 1970, Tam et al. 1996) depending on coastal water transport 

dynamics. Dispersal plays an important role in the maintenance of northern populations (Oregon 

up to Vancouver Island), as these populations are thought to be supplied with larval stock from 

the more established California populations via larval drift in the Davidson Current (Sorte et al. 

2001). 

II. Intraspecific/Life history diversity

Diversity of life history strategies: Moderate

• Confidence of workshop participants: Moderate 

Genetic diversity: Moderate

• Confidence of workshop participants: Low

Behavioral plasticity: Low-Moderate

• Confidence of workshop participants: Low

Phenotypic plasticity: Moderate-High

• Confidence of workshop participants: Low

Overall degree of diversity/plasticity of the species: Moderate

• Confidence of workshop participants: Low

Supporting literature

Because of the wide dispersal capabilities of the planktonic larval stages, the species is thought 

to be approaching genetic homogeneity in the northeast Pacific (Dawson et al. 2011). There is 

evidence of complex sexual variation in a related mole crab species, Emerita brasiliensis, 

including seven developmental forms that are able to reproduce (e.g. precocious females, 

juveniles, intersex individuals), variable sex ratios and variable timing of reproductive cycles 

(Delgado and Defeo 2008). Phenotypic and behavioral diversity has been observed in the Pacific 

mole crab in association with variable beach morphodynamics, including growth pattern, 

reproductive biology and burrowing capacity, suggesting that the species is responsive to 

environmental variation (Brazeiro 2005). 

III. Management potential

Value of species to people: Low

• Confidence of workshop participants: High 

• Description of value: Shore based fisherman value this species as bait.

Likelihood of managing or alleviating climate change impacts on species: Low-Moderate

• Confidence of workshop participants: Low

202
• Description of potential management options: manage for beach erosion, as the species is 

expected to repopulate a disturbed beach fairly quickly (within a week or two, Hayden 

and Dolan 1974) if conditions improve and are suitable for their survival 

Additional participant comments

Because mole crab populations are heavily dependent upon successful recruitment, which is 

influenced by dynamic ocean conditions, it will be difficult to actively manage climate change 

impacts to this species. The overall adaptive capacity assessment of this species assumes that 

recruitment is not affected by climate change impacts.

Supporting literature 

Though this species is not generally valued by the public, the mole crab is recognized as a 

critical component of food web dynamics, providing the majority of biomass for birds and fishes 

in beach habitat in the study region (Largier et al. 2010). Though participants scored the 

management potential for the mole crab as low-moderate, there are many management actions 

dealing with coastal armament and upstream processes that can be taken to manage potential 

impacts (Dan Robinette, pers. comm., 2014). 

IV. Other adaptive capacity factors: none identified

Exposure 

I. Future climate exposure6

Future climate and climate-driven changes identified (score7, confidence8): changes in sea 

surface temperature (5, high), changes in precipitation (5, high), increased coastal erosion and 

runoff (5, high), sea level rise (5, high), decreased pH (5, high), altered currents and mixing (5, 

high), changes in salinity (5, high), increased storminess (5, high), increased flooding (3, 

moderate)

Degree of exposure to future climate and climate-driven changes: High

• Confidence of workshop participants: Moderate 

Additional participant comments

Potential areas of refugia include poleward range shifts to avoid increased sea surface 

temperature, migration landward in response to sea level rise (if beach is available), and subtidal 

habitat to escape the impacts of erosion. 

6 Supporting literature for future exposure to climate factors is provided in the introduction. 7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

203
Literature Cited

Brazeiro, A. 2005. Geomorphology induces life history changes in invertebrates of sandy beaches: the case of the 

mole crab Emerita analogain Chile. Journal of the Marine Biological Association of the United Kingdom 

85(1):113-120.

Dawson, M. N., Barber, P. H., González-Guzmán, L. I., Toonen, R. J., Dugan, J. E. and Grosberg, R. K. 2011. 

Phylogeography of Emerita analoga (Crustacea, Decapoda, Hippidae), an eastern Pacific Ocean sand crab

with long-lived pelagic larvae. Journal of Biogeography, 38: 1600–1612. 

Defeo, O.A. McLachlan, D. Schoeman, T. Schlacher, J. Dugan, A. Jones, M. Lastra, F. Scapini. 2009. Threats to 

sandy beach ecosystems: a review. Estuar. Coastl. Shelf Sci. 81:1-12.

Delgado, E. and O. Defeo. 2006. A complex sexual cycle in sandy beaches: the reproductive strategy of Emerita 

brasiliensis (Decapoda: Anomura). Journal of the Marine Biological Association of the United Kingdom,

86, pp 361-368. 

Dugan, J.E., D.M. Hubbard, and M. Lastra. 2000. Burrowing abilities and swash behavior of three crabs, Emerita 

analoga Stimpson, Blepharipoda occidentalis Randall, andLepidopa californica Efford (Anomura, 

Hippoidea), of exposed sandy beaches. JEMBE 255 (2): 229-245.

Dugan, J.E., D.M. Hubbard, I. F. Rodil, D. L. Revell and S. Schroeter. 2008. Ecological effects of coastal armoring

on sandy beaches. Marine Ecology 29: 160-170.

Efford, I.E. 1970. Recruitment to sedentary marine populations as exemplified by the sand crab, Emerita 

analoga (Decapoda, Hippidae). Crustaceana 18 (3): 293–308.

Feely, R.A., C.L. Sabine, J.M. Hernandez-Ayon, D. Ianson, and B. Hales. 2008. Evidence for upwelling of corrosive 

"acidified" seawater onto the continental shelf. Science 320, 1490 DOI: 10.1126/science.1155676.

Gaylord, B., T.M. Hill, E. Sanford, E.A. Lenz, L.A. Jacobs, K.N. Sato, A.D. Russell, A. Hettinger. 2011. Functional 

impacts of ocean acidification in an ecologically critical foundation species. Journal of Experimental 

Biology 214:2586-94.

Griggs, G.B. and K.B. Patsch. 2004. California’s Coastal Cliffs and Bluffs. In: Formation, Evolution, and Stability 

of Coastal Cliffs – Status and Trends. U.S. Geological Survey Professional paper 1693. Pp. 53-64.

Hayden, B. and R. Dolan. 1974. Impact of beach nourishment on distribution of Emerita talpoida, the common 

mole crab. Journal of the Waterways, Harbors, and Coastal Engineering Division 10538: 123-132.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Lastra, M., E. Jaramillo, J. Lopez, H. Contreras, C. Duarte, and J.G. Rodriguez. 2004. Population abundances, tidal 

movement, burrowing ability and oxygen uptake of Emerita analoga (Stimpson) (Crustacea, Anomura) on 

a sandy beach of south-central Chile. Marine Ecology, 25, 71-89.

Lercari, D. and O. Defeo. 1999. Effects of Freshwater Discharge in Sandy Beach Populations: The Mole 

Crab Emerita brasiliensis in Uruguay. Estuarine, Coastal and Shelf Science 49(4): 457-468.

Manning, L.M., C.H. Peterson, and S.R. Fegley. 2013. Degradation of surf-fish foraging habitat driven by persistent 

sedimentological modifications caused by beach nourishment. Bulletin of Marine Science 89(1): 83-106.

Office of National Marine Sanctuaries (ONMS). 2010. Gulf of the Farallones National Marine Sanctuary Condition

Report. U.S. Department of Commerce, National Oceanic and Atmospheric Administration, Office 

of National Marine Sanctuaries, Silver Spring, MD. 97 pp.

Peterson, C.H. Unpublished data. From: Peterson, C.H. and J. Michel. Beach Processes and the Life Histories of 

Benthic Invertebrates on Beach and Tidal Flat Habitats Affected by the Cosco Busan Oil Spill, California. 

Technical Memorandum. Available: 

http://www.fws.gov/contaminants/Restorationplans/CoscoBusan/Cosco_Settlement/App_K_Benthic_Invert

s_Peterson_MichelAccess.pdf. 

Raven, J. A. 2005. Ocean acidification due to increasing atmospheric carbon dioxide. Policy Document 12/05. Royal 

Society, London, UK. 

Sanctuary Integrated Monitoring Network (SIMoN). Sandy Beaches. Retrieved August 19, 2014 from: 

http://sanctuarysimon.org/farallones/sections/beaches/overview.php

Slagel, M. J. and G.B. Griggs. 2008. Cumulative Losses of Sand to the California Coast by Dam Impoundment.

Journal of Coastal Research 24(3)571-584.

Sorte, C.J., W. T. Peterson, C.A. Morgan, and R. L. Emmett. 2001. Larval dynamics of the sand crab, Emerita 

analoga, off the central Oregon coast during a strong El Niño period. Journal of Plankton Research 

23 (9): 939-944. 

204
Tam, Y. K., I. Kornfield, and F.P. Ojeda. 1996. Divergence and zoogeography of mole crabs, Emerita spp. 

(Decapoda: Hippidae), in the Americas. Mar. Biol., 125, 489–497.

205
Northern Anchovy (Engraulis mordax) and Pacific Sardine

(Sardinops sagax caerulea)

1

Executive Summary Northern anchovy and Pacific sardine 

are small forage fish that serve as a 

critical food source for many important 

fish, bird and mammal species and 

support commercial and recreational 

fisheries in the study region. Northern 

anchovy occur from British Columbia

to the Gulf of California in large 

schools near the ocean’s surface, and 

Pacific sardine range from Southeast 

Alaska to the Gulf of California in 

nearshore and offshore waters along the 

coast. Key climate sensitivities

identified for both species by workshop participants include sea surface temperature, dynamic 

ocean conditions (currents/mixing/stratification), dissolved oxygen, and pH. The only nonclimate sensitivity identified is harvest. Both the Pacific sardine and Northern anchovy exhibit a 

transcontinental geographic extent and diminished, but stable, populations that are patchy with 

some degree of connectivity, due to moderate to high dispersal, depending on size and age of the 

fish as well as season. They exhibit overall moderate-high intraspecific diversity with moderate 

phenotypic and behavioral plasticity in morphology, diet, spawning behavior and age structure, 

which enables some degree of response to changes in environmental conditions. The Northern 

anchovy has considerably greater genetic diversity than the Pacific sardine, possibly due to life 

history differences and the collapse of the sardine fishery in the 1930s. Both species are valued 

for the commercial and recreational fisheries they support and their role in pelagic ecosystems. 

The likelihood to manage or alleviate climate impacts may be possible through further fisheries 

regulations, with is considered low-moderate for anchovy because there currently is no active 

management of this fishery (though that can easily change if necessary), and moderate for 

sardine, as this species is federally managed on an annual basis. 

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): 

• Both species: sea surface temperature (5, high), dynamic ocean conditions 

(currents/mixing/stratification) (5, high), pH (4, low), dissolved oxygen (DO) levels (4, 

high), salinity (3, moderate) 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by participants.

Northern Anchovy Score Confidence 

Sensitivity 3 Moderate 2 Moderate

Exposure 3 Moderate 2 Moderate

Adaptive Capacity 3 Moderate 2 Moderate

Vulnerability 3 Moderate 2 Moderate

Pacific Sardine Score Confidence 

Sensitivity 3 Moderate 2 Moderate

Exposure 3 Moderate 2 Moderate

Adaptive Capacity 4 Moderate-High 2 Moderate

Vulnerability 3 Moderate 2 Moderate

206
• Anchovy only: coastal erosion (3, low), air temperature (2, moderate), precipitation (2,

moderate)

Climate and climate-driven changes that may benefit the species: no answer provided 

Overall species sensitivity to climate and climate-driven factors: Moderate

• Confidence of participants: Moderate 

Additional participant comments

The Northern anchovy and Pacific sardine are pelagic species that occasionally travel in 

nearshore waters and can be affected by a variety of long-term climate changes. Climate change 

is expected to most affect these species through prey availability, by significantly impacting 

chlorophyll and primary ocean productivity, and consequently the food sources for anchovy and 

sardine, as well as preferred spawning habitat. 

Supporting literature

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. 

Sea Surface Temperature

Anchovy and sardine populations alternate in abundance about every 25 years depending on 

ocean temperature; in the mid-1970s, the Pacific changed from a cool “anchovy regime” to a 

warm “sardine regime” and a shift back to an anchovy regime occurred in the middle to late 

1990s (Chavez 2003). Sardine spawn in a wider range of temperatures (13-25 ̊C) than anchovy 

(11.5-16.5 ̊C). Average conditions during a sardine regime are similar to those during an El 

Niño event, when ocean temperature is warmer and productivity is lower (Chavez 2003); as 

ocean temperature continues to warm due to climate change, we may expect increasing 

frequency and length of sardine regimes. The spatial and seasonal distribution of sardine 

spawning is temperature-dependent; in warmer water, the center of spawning activity moves 

northward and occurs over a longer period of time (Butler 1987, Ahlstrom 1960), and sardine 

eggs and larvae are most abundant at temperatures of 13-15 ̊C (55-59 ̊F) (Hill et al. 2014). 

Currents/Mixing/Stratification

In this broad category of climate impacts, upwelling and El Niño processes were identified as 

influencing the sensitivity of anchovy and sardines due to the impact on sea surface temperature. 

Upwelling has a significant impact on larval fish and the availability of food, which may drive 

population trends for the species (Vulnerability Assessment Workshop, pers. comm., 2014). 

Both processes may help drive the distribution and abundance of the species by impacting which 

fish “regime” is dominant; sardines are more abundant during warm water El Niño conditions, 

and anchovy dominate during cool water conditions that can be driven by coastal upwelling 

(Chavez 2003). Additional research suggests that this regime shift is controlled by the 

fluctuating abundance of the preferred prey of sardine and anchovy, with smaller plankton 

(preferred by sardine via filter feeding) being favored by weak upwelling, and larger plankton 

(preferred by anchovy via direct biting) being favored by strong upwelling (Rykaczewski and 

Checkley 2008). This upwelling difference may also separate sardine and anchovy populations 

to the offshore and nearshore habitats, respectively, as strong upwelling occurs along the coastal 

margin and weak upwelling occurs offshore from wind stress (Rykaczewski and Checkley 2008). 

207
Oxygen

Dissolved oxygen is an environmental parameter that greatly impacts marine species and can 

lead to mass mortality events, behavioral modification, and a reduction in prey sources (Palsson 

et al. 2005, Palsson et al. 2008, NMFS 2013). Larvae of related sardine and anchovy species of 

the northern Benguela upwelling system have been documented to avoid low-dissolved oxygen 

waters, staying in waters with dissolved oxygen concentrations greater than 2 mL/L (Kreiner et 

al. 2011). Bertrand et al. (2012) suggest that along the upwelling coast of Peru, anchovy and 

sardines have different levels of tolerance to oxygen concentrations due to their different body 

sizes (smaller anchovies being more tolerant of lower dissolved oxygen) and other physiological 

differences. This relationship is the basis for the regime shift between anchovy and sardine 

populations, with sardine abundance declining during periods of upwelling that bring 

undersaturated concentrations of dissolved oxygen from oxygen minimum zones to the surface 

(Bertrand et al. 2012). 

pH 

The direct effects of decreased pH on fishes within the study region are not well understood 

(Largier et al. 2010), though one study outside of the region documented the impact of lower pH 

levels on larval clownfish olfactory cues, which caused disorientation (Munday et al. 2009). The 

impact of ocean acidification may also be felt indirectly by sardine and anchovy through impacts 

to their food supply, specifically zooplankton that form calcium carbonate shells, like copepods 

and pteropods. Decreased pH enhances shell degradation in pteropods and decreases 

calcification and oxygen consumption (Comeau et al. 2009, Lischka et al. 2010, Seibel et al. 

2012), potentially impacting the abundance of this important food source.

II. Sensitivities to disturbance regimes

Disturbance regimes identified: wind and storms 

Overall species sensitivity to disturbance regimes: Low-Moderate

• Confidence of participants: Low 

Additional participant comments

Both wind and storms have the potential to affect currents, mixing, upwelling and sea surface 

temperature and these factors can influence feeding patterns and habitat selection by sardine and 

anchovy populations (see climate-driven factors above).

III. Dependencies

Species dependence on one or more sensitive habitat types: Moderate-High (anchovy), High 

(sardine)

• Confidence of participants: High 

• Sensitive habitats species is dependent upon: offshore/pelagic water column 

Species dependence on specific prey or forage species: Moderate

• Confidence of participants: Moderate 

Other critical dependencies: none identified 

Specialization of species (1=generalist; 5=specialist): 3

• Confidence of participants: Moderate 

208
IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): harvest (5, high), pollution and poisons (2, 

moderate)

Overall species sensitivity to non-climate stressors: Moderate-High

• Confidence of participants: High

Overall species exposure to non-climate stressors: Low (in the study region) 

• Confidence of participants: High

Additional participant comments

Because anchovy and sardine are open-water species, many of the common non-climate stressors

that impact those in enclosed bays, estuaries and coastal waters are not expected to impact these 

species. 

Supporting literature

Literature review was conducted only for harvest, as pollution and poisons scored only 

moderate-low for these species. 

Harvest

Currently managed under the Coastal Pelagic Species Fishery Management Plan by the Pacific 

Fisheries Management Council, Pacific sardine and Northern anchovy are thought to be wellmanaged and not over-fished (Hill et al. 2014). Continuing current management of both species 

will be crucial to protecting their abundance and viability as the climate continues to change. 

Historically, the sardine fishery developed during World War I in response to rising food 

demand, and collapsed in the 1950s. This collapse was initially blamed primarily on fishing 

pressure, though now is partially attributed to a climatic shift in ocean temperature, which 

controls the boom and bust cycles of both sardines and anchovies (see Sea Surface Temperature 

above). Abundance assessments are undertaken every year, and used to set an annual catch limit 

for the species (NOAA 2013). 

The northern anchovy fishery was small until the collapse of the sardine stock in the 1950s, 

when anchovy then became the most abundant fish for the canning industry (NOAA 2013). 

Once the sardine fishery recovered, demand for anchovy decreased and today supports a small 

but valuable bait fishery (NOAA 2013). The northern anchovy is significantly less managed 

than the sardine, with the southern stock (San Francisco to Baja California) having last been 

assessed in 1995, and the northern stock (San Francisco to Washington) having never been 

assessed. This species is monitored but not assessed on an annual basis due to the low 

commercial landings (NOAA 2013). Should landings increase, managers will likely consider 

further assessing the species and implementing additional fishing regulations (NOAA 2013). 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by participants.

209
V. Other sensitivities

Other critical factors likely to influence the sensitivity of the species: chlorophyll and ocean 

productivity 

• Degree to which these factors impact the sensitivity of the species to climate change: 

High

• Confidence of participants: High 

Additional participant comments

Climate change could have a huge effect on chlorophyll and ocean productivity, and 

consequentially, food sources for the anchovy. Overall, climate change will most impact 

anchovy through changes in its food source (prey availability) and preferred spawning habitat. 

Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 5

• Confidence of participants: High 

Population status of the species (1=endangered; 5=robust): 3

• Confidence of participants: Low 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 3

• Confidence of participants: High 

Dispersal ability of the species: Moderate 

• Confidence of participants: Moderate

Maximum annual dispersal distance: 50-75km 

• Confidence of participants: Low 

Additional participant comments

Northern anchovy occur from British Columbia to the Gulf of California, Mexico, and the 

Pacific sardine occurs from Southeast Alaska to the Gulf of California, Mexico. With the 

substantially large range of the adult populations, both species are able to disperse, with 

maximum dispersal considered to be 50-75 km for anchovy and greater than 100 km for sardine. 

Extreme natural variability is characteristic of both species, so connectivity across species ranges 

at a given time is dependent on size and age as well as season. 

II. Intraspecific/Life history diversity

Diversity of life history strategies: Moderate

• Confidence of participants: Low 

Genetic diversity: High

• Confidence of participants: High 

Behavioral plasticity: Moderate

• Confidence of participants: Low 

210
Phenotypic plasticity: Moderate

• Confidence of participants: Low 

Overall degree of diversity/plasticity of the species: Moderate

• Confidence of participants: Low 

Supporting literature

Though both species were identified by workshop participants as having high genetic variance, 

there is no evidence of genetic variation among the three Pacific sardine subpopulations (Hill et 

al. 2014), suggesting high gene flow across the entire species range. This is in contrast to the 

Northern anchovy, which shows substantial genetic variation within and between populations 

from the California stock (Hedgecock et al. 1989). This difference is thought to be the result of 

differing life history characteristics and the more recent arrival of the Pacific sardine to the 

California Current System (Gaggiotti and Vetter 1999). Morphometric differences among 

sardines have been attributed to phenotypic plasticity rather than genetic diversity (Hedgecock et 

al. 1989, De La Cruz-Agüero and García-Rodríguez 2004). Additionally, sardine exhibit 

plasticity in diet, spawning behavior and age structure, enabling the species to quickly adapt and 

exploit favorable environmental conditions (Agostini 2005). Anchovy display plasticity also in 

diet, based on food availability (Sirotenko and Danilevskin 1978), and in annual spawning 

events; for example, the decline of the sardine population was accompanied by a significant 

increase in the duration of anchovy spawning (Smith 1972). 

Sardines may live up to 15 years, though commercial catches are typically composed of 

individuals less than 5 years (Hill et al. 2014). Sardines spawn in loosely aggregated schools in 

the upper 50 meters of the water column, with spawning peaking in April in the study region 

(Hill et al. 2014). Anchovies are shorter-lived, rarely exceeding 4 years old, with peak spawning 

activity between February and April, and females release batches of eggs every 7 to 10 days 

(NOAA 2013).

III. Management potential

Value of species to people: Moderate-High (anchovy), High (sardine)

• Confidence of participants: High 

• Description of value: Value for both recreational and commercial fisheries. The 

commercial anchovy fishery was valued at $1,059,476 in 2013; the sardine fishery was 

valued at $1,555,912 in 2013. 

Likelihood of managing or alleviating climate change impacts on species: Low-Moderate

(anchovy), Moderate (sardine) 

• Confidence of participants: Moderate 

• Description of potential management options: The Northern anchovy is not currently 

actively managed; however, this can change relatively quickly if significant levels of 

catch occur or if biological or economic concerns arise. The Pacific sardine is federally 

managed on an annual basis and change in temperature (the species greatest sensitivity) is 

considered when setting harvest, which will help alleviate fishing pressure in response to 

climate change. 

IV. Other adaptive capacity factors: none identified 

211
Exposure 

I. Future climate exposure6

Future climate and climate-driven changes identified (score7, confidence8): changes in sea 

surface temperature (5, high), decreased dissolved oxygen (DO) levels (4, high), decreased pH 

(4, low), changes in salinity (3, moderate), increased coastal erosion and runoff (3, low), 

increased storminess (2, low), altered currents and mixing (2, low) 

Degree of exposure to future climate and climate-driven changes: Moderate

• Confidence of participants: Moderate 

Additional participant comments

Potential areas of refugia from these climate factors are more northern or southern pelagic 

waters, or changes in depth. 

Literature Cited

Ahlstrom, E. H. 1960. Synopsis on the biology of the Pacific sardine (Sardinops caerulea). Proc. World Sci. Meet. 

Biol. Sardines and Related Species, FAO, Rome, 2: 415-451.

Agostini, V.N. 2005. Climate, ecology and productivity of Pacific sardine (Sardinops sagax) and hake (Merluccius 

productus). Ph.D. Dissertation. University of Washington.

Bertrand A., A. Chaigneau, S. Peraltilla, J. Ledesma, M. Graco, F. Monetti, F.P. Chavez. 2012. Oxygen: A 

Fundamental Property Regulating Pelagic Ecosystem Structure in the Coastal Southeastern Tropical 

Pacific. PLoS ONE 7(2).

Butler, J. L. 1987. Comparisons of the larval and juvenile growth and larval mortality rates of Pacific sardine and 

northern anchovy and implications for species interactions. Ph. D. Thesis, Univ. Calif., San Diego, 240 pp. 

Chavez, F.P., J. Ryan, S.E. Lluch-Cota, C.M. Niguen. 2003. From anchovies to sardines and back: multidecadal 

change in the Pacific Ocean. Science 299 (5604):217-221.

Comeau, S., Gorsky, G., Jeffree, R., Teyssié, J.-L., and Gattuso, J.-P. 2009. Impact of ocean acidification on a key

Arctic pelagic mollusc (Limacina helicina), Biogeosciences, 6, 1877-1882.

De La Cruz-Agüero, J. and F.J. García-Rodríguez. 2004. Morphometric stock structure of the Pacific sardine 

Sardinops sagax (Jenyns, 1842) off Baja California, Mexico. In: Elewa, A.M. (Ed.), Morphometrics: 

Applications in Biology and Paleontology. Springer-Verlag, New York, NY, pp. 115–124.

Gaggiotti, O.E. and R.D. Vetter. 1999. Effect of life history strategy, environmental variability, and overexploitation 

on the genetic diversity of pelagic fish populations. Canadian Journal of Fisheries and Aquatic Sciences 

56(8): 1376-88.

Hedgecock, D., E.S. Hutchinson, G. Li, F.L. Sly and K. Nelson. 1989. Genetic and Morphometric Variation in the 

Pacific Sardine, Sardinops sagax caerulea: Comparisons and Contrasts with Historical Data and with 

Variability in the Northern Anchovy, Engraulis mordax. Fishery Bulletin, U.S. 87:653-671.

Hill, K.T., P.R. Crone, D.A. Demer, J. Zwolinski, E. Dorval, and B.J. Macewicz. 2014. Assessment of the Pacific 

Sardine Resource in 2014 for USA Management in 2014-15. NOAA Technical Memorandum NOAA-TMNMFS-SWFSC-531.

Kreiner, A., D. Yemane, E.K. Stenevik, N.E. Moroff. 2011. The selection of spawning location of sardine 

 (Sardinops sagax) in the northern Benguela after changes in stock structure and environmental conditons. 

Fisheries Oceanography 20(6): 560-9.

6 Supporting literature for future exposure to climate factors is provided in the introduction.

7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by participants.

212
Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Lischka, S., J. Budenbender, T. Boxhammer and U. Riebesell. Impact of ocean acidification and elevated 

temperatures on early juveniles of the polar shelled pteropod Limacina helicina: mortality, shell 

degradation, and shell growth. Biogeosciences Discussion 7: 8177-8214.

Munday, P.L, D.L. Dixson, J.M. Donelson, G.P. Jones, M.S. Pratchett, G.V. Devitsina, and K.B. Døving. 2009. 

Ocean acidification impairs olfactory discrimination and homing ability of a marine fish. Proceedings of 

the National Academy of Sciences 106:1848-1852. 

National Oceanic and Atmospheric Administration (NOAA). 2013. FishWatch: Pacific Sardine and Northern 

Anchovy. Accessed September 5, 2014 from: 

http://www.fishwatch.gov/seafood_profiles/species/sardine/species_pages/pacific_sardine.htm and 

http://www.fishwatch.gov/seafood_profiles/species/anchovy/species_pages/northern_anchovy.htm

National Marine Fisheries Service (NMFS). 2013. Proposed Designation of Critical Habitat for the Distinct 

Population Segments of Yelloweye Rockfish, Canary Rockfish, and Bocaccio. Draft Biological Report. 

Accessed Sept 4, 2014 from: 

http://www.westcoast.fisheries.noaa.gov/publications/protected_species/other/rockfish/2013_draft_rockfish

_biological_report.pdf

Palsson, W.A., R.E. Pacunski, and T.R. Parra. 2005. GASP! The Response of Marine Fishes to Water with Low 

Dissolved Oxygen in Southern Hood Canal, Washington. Proceedings of the 2005 Puget Sound Georgia 

Basin Research Conference.

Palsson, W. A., R. E. Pacunski, T. R. Parra, and J. Beam. 2008. The effects of hypoxia on marine fish populations in 

southern Hood Canal, Washington. American Fisheries Society Symposium. Volume 64, pages 255 to 280.

Rykaczewski, R.R. and D.M. Checkley, Jr. 2008. Influence of ocean winds on the pelagic ecosystem in upwelling 

regions. Proceedings of the National Academy of Sciences, U.S.A. 105: 1965-1970.

Seibel BA, Maas AE, Dierssen HM. 2012. Energetic Plasticity Underlies a Variable Response to Ocean 

Acidification in the Pteropod, Limacina helicina antarctica. PLoS ONE 7(4): e30464.

Sirotenko, M.D. and N.N. Danilevskin. 1978. Quantitative feeding indices of the Black Sea anchovy, Engraulis 

encrasicolus ponticus. Journal of Icthyology 17(4):610-617.

Smith, P.E. 1972. The increase in spawning biomass of northern anchovy. Fisheries Bulletin 70:849-874.

213
Ochre Sea Star (Pisaster ochraceus)

1

Executive Summary

The ochre sea star is the largest 5-ray 

intertidal sea star in the study region. 

Its geographic range extends from 

Prince William Sound, Alaska to Isla 

Cedros, Baja California. Key climate 

sensitivities identified by workshop 

participants include air temperature, salinity, wave action and erosion, and key non-climate 

sensitivities include disease. The ochre sea star exhibits a transcontinental geographic extent, a 

healthy, continuous population (with the exception during a sea star wasting syndrome event that 

greatly diminishes the population), and a high dispersal capability. There is very little genetic 

diversity in the species due to extensive dispersal; the basis for the species’ color polymorphism 

may be genetic, but is thought to be controlled by ecological factors. The ochre sea star displays 

behavioral and phenotypic responses to changes in food availability and exposure at low tide, 

and can regenerate body parts when lost due to dislodgement and predation. The societal value 

for this species was rated as moderate due to aesthetic value by the general public and scientific 

value in studying ecological relationships. Management potential was considered to be lowmoderate, with some possibility to better manage disturbance from tidepool visitation and to 

better protect upland habitat for migration.

Sensitivity 

I. Sensitivity to climate and climate driven changes Climate and climate-driven changes identified (score2

, confidence3): air temperature (5, high), 

salinity (5, moderate), wave action (5, high), coastal erosion (4, low-moderate), sea surface 

temperature (3, low-moderate), sea level rise (3, moderate-high), dynamic ocean conditions 

(currents/mixing/stratification) (3, low), precipitation (2, low), dissolved oxygen (DO) levels (2, 

low-moderate), ocean pH (2, low-moderate)

Climate and climate-driven changes that may benefit the species: none identified 

Overall species sensitivity to climate and climate-driven factors: Moderate

• Confidence of workshop participants: Moderate

Additional participant comments

The ochre sea star is highly sensitive to wave action due to dislodgement, and is found only in 

the low to mid intertidal (reaching into the subtidal) for this reason. 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Ochre Sea Star Score Confidence 

Sensitivity 3 Moderate 3 High

Exposure 4 Moderate-High 2 Moderate

Adaptive Capacity 4 Moderate-High 3 High

Vulnerability 3 Moderate 3 High

214
Supporting literature

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. Additionally, elevated CO2 and water 

temperature may directly benefit the species, due to increased growth and feeding rates (Gooding 

et al. 2009). 

Air Temperature

The effect of temperature on the physiology of the ochre sea star is complex; acute exposure to 

high temperatures positively impact feeding rates, whereas long-term exposure to high 

temperatures can depress feeding and growth rates and is actively resisted by individuals through 

an increase in body water content (Pincebourde et al. 2009). Individuals relocated to the high 

intertidal from the mid intertidal showed decreased feeding, weight loss and mortality (Petes et 

al. 2008), and rates of oxygen consumption increased with increasing air temperature (Fly et al. 

2012), all of which indicate a metabolic cost to exposure. However, through increased water 

content and relocation to lower tidal zones, individuals are able to escape the impacts of 

exposure and high air temperatures. 

Salinity

Activity and feeding response is directly impacted by salinity, with lower activity occurring at 

low salinity levels (15 psu) as compared to higher levels (30 psu, typical of open ocean). 

However, at 15 psu, individuals collected from sites with low natural salinity were more active 

than individuals collected at the higher salinity level locations, suggesting acclimatization or 

adaptation to low salinity is possible, though limits to this tolerance exist (Held and Harley 

2009). 

Wave Action

Though sea stars can secure themselves to the substrate using their tubefeet, they can be removed 

if wave forces are very high (SIMoN 2014), and consistently high wave forces may restrict the 

species to lower tidal heights. 

Erosion 

Enhanced coastal erosion, due to sea level rise and an increase in wave and storm severity, may 

result in the burying of intertidal habitat and may also impede the ability of intertidal organisms 

to migrate inland in response to rising sea levels (Largier et al. 2010). 

II. Sensitivity to disturbance regimes

Disturbance regimes identified: wind, storms, disease, flooding, and extreme heat events 

Overall species sensitivity to disturbance regimes: High

• Confidence of workshop participants: Moderate

Supporting literature

Wind is highly desiccating to intertidal organisms and can dry out species that need to retain 

moisture for survival, enhancing the negative impact of increased air temperature (Bell 1995). 

Storms increase physical forces through enhanced wave exposure and increased erosion of 

coastal cliffs that can bury intertidal habitats (see wave action and erosion sections above). 

Flooding may have a similar effect by increasing sedimentation to the intertidal area, but may 

also result in compromised water quality (PISCO 2014), including an increase in harmful algal 

215
bloom events. Disease is the primary non-climate stressor that can be expected to impact the 

ochre sea star (see disease section below), and will likely be exacerbated by increased water 

temperature, as both pathogen survival and host susceptibility are enhanced (Friedman et al. 

1997, Harvell et al. 1999, Raimondi et al. 2002, Largier et al. 2010). Extreme heat events can 

exacerbate the impacts of exposure to air (see air temperature section above).

III. Sensitivity and exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): disease (5, high) and recreation (1, high) 

Overall species sensitivity to non-climate stressors: Moderate

• Confidence of workshop participants: High

Overall current exposure to non-climate stressors: Moderate

• Confidence of workshop participants: High 

Additional participant comments

The sea star wasting syndrome is a primary concern for the health of this species due to the 

massive die-offs that have occurred over the last year. 

Supporting literature

Literature review was not conducted for recreation due to the low sensitivity score assigned, 

though this factor should still be considered when examining overall impact to the species from 

non-climate stressors. 

Disease

Sea star wasting syndrome describes symptoms that occur in over 15 species of sea stars that 

lead to tissue decay, fragmentation, and eventual death. The latest occurrence of the syndrome 

began in June 2013 in Washington and has since spread from Alaska to Baja California, the 

entire extent of the ochre sea star’s range. Previous syndrome events were associated with the 

warm water temperatures of El Nino events (1983-84, 1997-98), but that association does not 

exist with this latest occurrence, which has exhibited an unprecedented geographic and temporal 

extent (Sea Star Wasting Syndrome 2014). Very recently, the cause of the syndrome was 

determined to be viral (Hewson et al. 2014). Because sea stars are dominant predators of 

intertidal and subtidal habitats and are considered keystone species, the ecological consequences 

of this syndrome may be severe. Recent studies, however, have shown substantial recruitment of 

new sea stars to a few areas in the region, which may enable rapid replenishment of affected 

populations if recruitment is widespread and the new recruits are unaffected by the syndrome 

(Sea Star Wasting Syndrome 2014). 

IV. Dependencies

Species dependence on one or more sensitive habitat types: Low

• Confidence of workshop participants: High

• Sensitive habitats species is dependent upon: no answer given 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

216
Species dependence on specific prey or forage species: Low

• Confidence of workshop participants: High

Other critical dependencies: hard substrate in the low to mid intertidal for settling larvae and 

foraging adults 

• Degree of dependence: High

• Confidence of workshop participants: High

Specialization of species (1=generalist; 5=specialist): 2 

• Confidence of workshop participants: High

V. Other sensitivities: none identified

Adaptive Capacity

I. Extent, Status, and Dispersal Ability

Geographic extent of the species (1=endemic; 5=transboundary): 5 

• Confidence of workshop participants: High

Population status of the species (1=endangered; 5=robust): 5 

• Confidence of workshop participants: High

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 5 

• Confidence of workshop participants: High

Dispersal ability of the species: High 

• Confidence of workshop participants: High

Maximum annual dispersal distance: 75-100km by larvae from broadcast spawning

• Confidence of workshop participants: Low

Additional participant comments

The health of the population is highly compromised during sea star wasting syndrome events 

(see disease section above), and therefore the success of future ochre sea star populations is 

uncertain. 

II. Intraspecific/Life History Diversity

Diversity of life history strategies: Low

• Confidence of workshop participants: High

Genetic diversity: Moderate-High

• Confidence of workshop participants: High

Behavioral plasticity: Moderate

• Confidence of workshop participants: High

Phenotypic plasticity: Low-Moderate

• Confidence of workshop participants: High

217
Overall degree of diversity/plasticity of the species: Moderate

• Confidence of workshop participants: High

Supporting literature

This species is long-lived (though a subject of debate, considered to be around 20 years, SIMoN 

2014) and exhibits high reproductive output through broadcast spawning, reproducing 

seasonally, many times throughout its life. Spawning occurs in April and May in the study 

region and in July further north (SIMoN 2014). In contrast to the genetic diversity score 

provided by workshop participants, the literature suggests that the ochre sea star has very low 

population genetic structure, suggesting high gene flow and low genetic diversity throughout its 

range (Harley et al. 2006). Color polymorphism is a striking characteristic of the species that 

varies with geography that may have an underlying genetic component, though is considered to 

be ecologically controlled, with some connection to diet (Harley et al. 2006). The species grows 

in proportion to its food supply and will increase or decrease in size in response to food 

availability, and can regenerate tube feet that may be ripped off due to dislodgement and any of 

its 5 rays that may be lost to predation (SIMoN 2014). Neurosensory cells scattered throughout 

their body enable behavioral responses to mechanical, chemical and optical stimuli (SIMoN 

2014). 

III. Management Potential

Value of species to people: Moderate

• Confidence of workshop participants: Low

• Description of value: aesthetic value and high affinity for the species held by the general 

public and the high research value in the study of rocky intertidal ecology and keystone 

species

Likelihood of managing or alleviating climate change impacts on species: Low-Moderate

• Confidence of workshop participants: Low

• Description of potential management options: Managing the impacts from recreation 

and coastal visitors may decrease negative impacts on the species, and the protection of 

upland/inland habitat may enable migration.

IV. Other adaptive capacity factors: none identified

Exposure 

I. Future climate exposure6 Future climate and climate-driven changes identified (score7

, confidence8): changes in air 

temperature (5, high), changes in sea surface temperature (5, moderate-high), changes in 

precipitation (5, high), changes in salinity (5, moderate), sea level rise (5, high), decreased pH (5, 

high), altered currents and mixing (4, low-moderate), increased storminess (3, moderate), 

increased coastal erosion (3, moderate), decreased dissolved oxygen (DO) levels (2, low) 

6 Supporting literature for future exposure to climate factors is provided in the introduction. 7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

218
Degree of exposure to future climate and climate-driven changes: Moderate-High

• Confidence of workshop participants: Moderate 

Additional participant comments

Potential areas of refugia from climate exposure include subtidal habitat to escape the impacts of 

air temperature and disturbance from increased storminess and wave action.

Literature Cited

Bell, E.C. 1995. Environmental and morphological influences on thallus temperature and desiccation of the 

intertidal alga Mastocarpus papillatus Kutzing. Journal of Experimental Marine Biology and Ecology 191: 

29-55.

Fly, E.K., C.J. Monaco, S. Pincebourde, A. Tullis. 2012. The influence of intertidal location and temperature on the 

metabolic cost of emersion in Pisaster ochraceus. Journal of Experimental Marine Biology and Ecology 

422-423: 20-28.

Friedman, C.S., M. Thomson, C. Chun, P.L. Haaker and R.P. Hedrick. 1997. Withering syndrome of the black 

abalone, Haliotis cracherodii (Leach): Water temperature, food availability, and parasite as possible 

causes. Journal of Shellfish Research 16:403-411.

Gooding, R.A., C.D.G. Harley, and E. Tang. 2009. Elevated water temperature and carbon dioxide concentration

increase the growth of a keystone echinoderm. PNAS 106 (23): 9316-21.

Harley, C.D.G., M.S. Pankey, J.P. Wares, R.K. Grosberg, M.J. Wonham. 2006. Color polymorphism and genetic 

structure in the sea star Pisaster ochraceus. Biological Bulletin 211(3): 248-62.

Harvell, C.D., K. Kim, J.M. Burkholder, R.R. Colwell, P.R. Epstein, D.J. Grimes, E.E. Hofmann, E.K. Lipp, 

A.D.M.E. Osterhaus, R.M. Overstreet, J.W. Porter, G.W. Smith and G.R. Vasta. 1999. Emerging marine 

diseases – climate links and anthropogenic factors. Science 285:1505-1510. 

Held, M.B.E. and C.D.G. Harley. 2009. Responses to low salinity by the sea star Pisaster ochraceus from high- and 

low-salinity populations. Invertebrate Biology 128(4): 381-90.

Hewson, I., J B. Button, B. M. Gudenkauf, B. Miner, A. L. Newton, J. K. Gaydos, J. Wynne, C. L. Groves, G. 

Hendler, M. Murray, S. Fradkin, M. Breitbart, E. Fahsbender, K. D. Lafferty, A. M. Kilpatrick, C. M. 

Miner, P. Raimondi, L. Lahner, C. S. Friedman, S. Daniels, M. Haulena, J. Marliave, C. A. Burge, M. E. 

Eisenlord, and C.D. Harvell. 2014. Densovirus associated with sea-star wasting disease and mass mortality. 

PNAS 111: 17278-83.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Partnership for Interdisciplinary Studies of Coastal Oceans (PISCO): Rocky Shores. 2014. Retrieved June 18, 2014 

from http://www.piscoweb.org/research/rocky-shores. 

Petes, L.E., M. E. Mouchka, R. H. Milston-Clements, T. S. Momoda, B. A. Menge. 2008. Effects of environmental

stress on intertidal mussels and their sea star predators. Oecologica 156: 671–680.

Pincebourde, S., Sanford, E., Helmuth, B. 2009. An intertidal sea star adjusts thermal inertia to avoid extreme body 

temperatures. Am. Nat. 174, 890–897.

Raimondi, P. T., C. M. Wilson, R. F. Ambrose, J. M. Engle, and T. E. Minchinton. 2002. Continued declines of 

black abalone along the coast of California: are mass mortalities related to El Niño events? Marine 

Ecology Progress Series 242:143-152.

Sanctuary Integrated Monitoring Network (SIMoN). 2014. Ochre Sea Star. Retrieved July 29, 2014 from: 

http://sanctuarysimon.org/species/pisaster/ochraceus/ochre-sea-star

Sea Star Wasting Syndrome. 2014. Pacific Rocky Intertidal Monitoring: Trends and Synthesis. Retrieved July 30,

2014 from: http://www.eeb.ucsc.edu/pacificrockyintertidal/data-products/sea-star-wasting/index.html. 

219
Olympia Oyster (Ostrea lurida)1

Executive Summary The Olympia oyster is a bivalve filterfeeder that historically formed dense, 

clustered aggregates of individuals in 

low tidelands and estuaries from 

Northern British Columbia to Baja 

California. The species has suffered 

precipitous decline in the study region, and is the focus of many management and restoration 

efforts. Key climate sensitivities identified for this species by participants includes salinity and 

precipitation, and key non-climate sensitivities include dredging, invasive species, and pollution 

and poisons. The Olympia oyster exhibits a broad distribution and a fragmented population that 

is diminished from historical levels due primarily to over-harvest in the 1800s and early 1900s 

and pollution of the region’s estuaries. The species has a high dispersal capability, but generally 

low diversity and plasticity. There is some indication of phenotypic plasticity in growth and 

physiology in response to environmental stressors, but this work is ongoing. Societal value for 

the Olympia oyster is high due to the commercial fishery that exists in some regions, as well as 

its critical role in improving estuarine water quality and providing benthic habitat, which is 

recognized by regional managers seeking to restore the native oyster. Management potential for 

climate stressors is low-moderate, though non-climate stressors, such as run-off from river 

outflows and invasive species, as well as broad-scale restoration efforts, can certainly be 

managed to increase the species’ resiliency to climate change. 

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): precipitation (5, high), 

salinity (5, high), dissolved oxygen (DO) levels (3, high), ocean pH (3, high), coastal erosion (3, 

moderate), sedimentation (3, high), air temperature (2, high), sea surface temperature (2, high), 

wave action (2, moderate), dynamic ocean conditions (currents/mixing/stratification) (2, 

moderate)

Climate and climate-driven changes that may benefit the species: sea level rise 

• Description of benefit: Sea level rise may result in increased habitat area for the species. 

However, the distribution of the species my simply shift upwards in response to sea level 

rise.

Overall species sensitivity to climate and climate-driven factors: Moderate

• Confidence of workshop participants: High 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity. 3 Confidence level indicated by workshop participants.

Olympia Oyster Score Confidence 

Sensitivity 3 Moderate 3 High

Exposure 5 High 3 High

Adaptive Capacity 3 Moderate 3 High

Vulnerability 3 Moderate 3 High

220
Additional participant comments

Depending on the depth, sea level rise may benefit the species in some areas by opening up 

additional habitat with appropriate tidal range, though this is limited somewhat by additional 

predation pressure at lower tidal elevations which may lead to the species range simply shifting 

inland in response.

Supporting literature

Through the National Estuarine Research Reserve System (NERRS) Science Collaborative, 

researchers have studied the effects of many of these climate factors on oysters using lab 

experimentation and field surveys; confidence in the sensitivity of this species to climate change 

is high due to this work (Cheng et al. 2015, Ted Grosholz, pers. comm., 2014). 

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. 

Salinity and Precipitation

Low salinity events commonly occur in late winter and spring during heavy, seasonal 

precipitation events that cause freshwater inundation of low-lying estuarine habitat, causing a 

sudden drop in salinity (Ferner 2013). This coincides with the development of older juvenile 

Olympia oysters (Ferner 2013), which were found to be highly sensitive to salinities below 15 

psu, and salinities below 25 psu for extended periods of time (Cheng et al. 2015). More intense 

and longer duration low-salinity events leads to higher mortality and lower food intake by 

Olympia oysters in laboratory experiments, with population-level differences in this response 

(Cheng et al. 2015, Ferner 2013). Additional experimentation to test the additive effects of low 

salinity and high temperature during daytime low tides is ongoing (Ferner 2013). 

II. Sensitivities to disturbance regimes

Disturbance regimes identified: storms and flooding 

Overall species sensitivity to disturbance regimes: High

• Confidence of workshop participants: High 

Additional participant comments

The Olympia oyster was identified as being sensitive to storm and flooding disturbance regimes, 

due to its sensitivity to salinity (see salinity section above). The exposure to low-salinity water 

due to heavy precipitation and enhanced flooding from storm activity (especially near rivers) can 

have severe impacts on entire populations by causing mass mortality. 

III. Dependencies

Species dependence on one or more sensitive habitat types: Moderate

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: Hard substrate 

Species dependence on specific prey or forage species: Low

• Confidence of workshop participants: High 

Other critical dependencies: none provided 

221
Specialization of species (1=generalist; 5=specialist): 3

• Confidence of workshop participants: High 

Supporting literature

The Olympia oyster overall has a low-moderate dependency on physical and biological 

characteristics that may impact its sensitivity, including a moderate dependency on hard, stable 

substrate for habitat within estuaries (Zabin et al. 2009) and a low dependency on specific prey, 

filtering suspended food particles, such as detritus and phytoplankton (Couch and Hassler 1989), 

from the water column. 

IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): pollution and poisons, dredging, and 

invasive species

Overall species sensitivity to non-climate stressors: High

• Confidence of workshop participants: High

Overall species exposure to non-climate stressors: Moderate

• Confidence of workshop participants: High

Additional participant comments

Currently, populations are limited in some locations, and loss of habitat to dredging may reduce 

habitat and population sizes, thus reducing resiliency of populations to climate change. 

Dredging

Dredging may increase turbidity and sedimentation, alter tidal mixing and circulation, reduce 

nutrient outflow from marshes and swamps, and increase susceptibility to recurrent low 

dissolved oxygen levels (Johnston 1981). Oysters are particularly vulnerable to the effects of 

siltation, and may be harmed by contaminants released into the water column by dredging 

operations (Johnston 1981). 

Invasive Species

Olympia oysters are impacted both directly and indirectly by invasive species. Two invasive 

predatory drills (gastropods) directly prey upon Olympia oysters and significantly limit their 

recovery and abundance (Buhle and Ruesink 2009). Further, predatory invasive oyster drills can 

limit the lower tidal distribution of Olympia oysters which may leave oysters more exposed to 

future increases in air temperatures (Kimbro et al. 2009). Indirectly, estuarine habitat dominated 

by invasive crabs and whelks exhibit much greater mortality of Olympia oysters as compared to 

habitat dominated by native crabs and whelks through alteration of the food web dynamics by 

inhibiting trait-mediated and density-mediated trophic cascades (Kimbro et al. 2009). Finally, 

the Olympia oyster is directly displaced by larger non-native oysters, including the Pacific oyster

(Pacific Biodiversity Institute, Trimble et al. 2009). 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

222
Pollution and poisons 

As filter feeders, Olympia oysters provide a critical water-filtering service for the region’s 

estuaries, effectively improving water quality. However, in extracting various pollutants from 

the water, oysters quickly concentrate toxins in their tissues, which has been demonstrated to 

negatively impact individual health and population abundance (Pacific Biodiversity Institute). In 

Washington, spat production and adult growth of Olympia oysters were negatively impacted by 

the discharge of sulfite waste from pulp and paper mills, wiping out most of Puget Sound’s 

population in the mid-1900s (Korringa 1976). Currently, populations are still threatened by 

exposure to mill and wastewater discharge and motor fuel, which causes physiological stress, 

degeneration of gill tissue, uptake of hydrocarbons, and mortality (Clark et al. 1974, Trimble et 

al. 2009). Also, anthropogenic nutrient loading can produce threatening levels of low dissolved 

oxygen (Wasson 2010, Cheng et al. 2015). 

V. Other sensitivities: none identified

Additional participant comments

Olympia Oysters are very sensitive to the aforementioned climate and climate-driven changes. 

Local populations may be limited to areas with sufficient salinity levels and low levels of natural 

and human predation. 

Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 5 

• Confidence of workshop participants: High 

Population status of the species (1=endangered; 5=robust): 3

• Confidence of workshop participants: High 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 2 

• Confidence of workshop participants: High 

Dispersal ability of the species: Moderate 

• Confidence of workshop participants: High 

Maximum annual dispersal distance: 5-25km 

• Confidence of workshop participants: Moderate 

Supporting literature 

The Olympia oyster ranges from Northern British Columbia to Baja California, Mexico (Polson 

and Zacherl 2009). Once very abundant and widespread, the Olympia oyster has experienced a 

64% decline in the spatial extent of oyster habitat and an 88% decline in oyster biomass over the 

last 100 years due to rampant harvest that occurred in the late 1800s and early 1900s (Ermgassen 

et al. 2013). The Olympia oyster has high dispersal capability and substantial gene flow among 

populations, with larvae traveling 5-25 km (Stick et al. 2009, Ted Grosholz, pers. comm., 2014). 

A study in Southern California found a high level of larval exchange among sites separated by as 

many as 75 km of coastline (Carson 2010). Larval movement and connectivity within San 

223
Francisco Bay is currently being investigated by the NERR Science Collaborative by comparing 

shell chemistry at various sites; preliminary results suggest distinct trace element signatures 

across sites in the Bay (Cheng, NERRS Science Collaborative, unpublished data). 

II. Intraspecific/Life history diversity

Diversity of life history strategies: Low-Moderate 

• Confidence of workshop participants: Moderate 

Genetic diversity: Moderate

• Confidence of workshop participants: Moderate 

Behavioral plasticity: Low

• Confidence of workshop participants: High 

Phenotypic plasticity: Moderate

• Confidence of workshop participants: High 

Overall degree of diversity/plasticity of the species: Low-Moderate

• Confidence of workshop participants: High

Supporting literature

Multi-stressor experiments have shown phenotypic plasticity in growth and physiology of 

Olympia oysters in response to experimental manipulation of temperature, salinity and dissolved 

oxygen (Cheng and Bible, NERRS Science Collaborative, unpublished data). The oyster is 

slow-growing, takes a year to reach sexual maturity, and may spawn a few times in a given year 

under optimal laboratory conditions (Baker 1995). Spawning typically occurs in this region in 

mid-summer (Hopkins 1937) when males release sperm that are taken in by females for internal 

fertilization. A brood of 250 to 300,000 larvae develop for 10 to 12 days before being released, 

where they remain in the water column for 11 to 16 days before settling to the substrate (Hopkins 

1937). 

III. Management potential

Value of species to people: High

• Confidence of workshop participants: High 

• Description of value: Value as a commercially fished species, and as an important 

component for habitat restoration efforts in San Francisco Bay. 

Likelihood of managing or alleviating climate change impacts on species: Low-Moderate

• Confidence of workshop participants: Moderate 

• Description of potential management options: Water management with regard to 

watershed runoff and river outflows could ameliorate future low salinity events and low 

dissolved oxygen events, control of non-native predators would help to modify 

interactions with air temperatures (allowing occupancy of lower tidal zones), and 

restoration of populations would likely increase recruitment and population size, 

enhancing the oyster’s resiliency to climate change.

224
Supporting literature

An ongoing, large-scale restoration program is being conducted by the San Francisco Bay Living 

Shorelines program supported by the California State Coastal Conservancy (Grosholz and Zabin, 

unpubl. data, http://www.sfbaylivingshorelines.org/sf_shorelines_science.html). Efforts to 

understand obstacles to and develop best practices for Olympia oyster restoration efforts are 

ongoing through the NERRS Science Collaborative project, titled “Managing for resilience in the 

face of climate change: a scientific approach to targeted restoration efforts in San Francisco Bay 

and Elkhorn Slough, California6

”. The project is producing restoration planning tools to help 

regional managers select appropriate sites for successful restoration programs, taking into 

account projected climate conditions, and will be a valuable resource for managers and planners 

in the study region. 

IV. Other adaptive capacities: none identified

Additional participant comments

The Olympia oyster may be able to adapt to some climate change scenarios. Improved 

management of this important species can facilitate greater resiliency to future climate change 

impacts. 

Exposure 

I. Future climate exposure7

Future climate and climate-driven changes identified (score8, confidence9): increased flooding 

(5, high), changes in precipitation (5, high), changes in salinity (5, high), decreased pH (4, high), 

changes in sea surface temperature (4, high), changes in air temperature (4, high), increased 

coastal erosion and runoff (4, high), increased storminess (3, moderate) 

Degree of exposure to future climate and climate-driven changes: High

• Confidence of workshop participants: High

Additional participant comments

Potential areas of refugia include mid-estuarine zones that may experience less exposure to low 

pH, upwelled waters, and estuarine zones that are less influenced and impacted by river inflows, 

which may decrease the species exposure to erosion/run-off, flooding, and changes in 

precipitation and salinity.

Literature Cited

Baker, P. 1995. Review of ecology and fishery of the Olympia oyster, Ostrea lurida with annotated bibliography 

Journal of Shellfish Research 1: 501-518.

Buhle, E.R., and J.L. Ruesink. 2009. Impacts of invasive oyster drills on Olympia oyster (Ostrea lurida Carpenter 

6 Project website: http://www.sfbaysubtidal.org/oysters_and_climate-about.html 7 Supporting literature for future exposure to climate factors is provided in the introduction.

8 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

9 Confidence level indicated by workshop participants.

225
1864) Recovery in Willapa Bay, Washington, United States. Journal of Shellfish Research. 28(1):87-96.

Carson, H.S. 2010. Population connectivity of the Olympia oyster in Southern California. Limnology and 

Oceanography 55(1): 134–148.

Cheng, B. S., J. M. Bible, A. L. Chang, M. Ferner, K. Wasson, C. Zabin, M. Latta, A.K. Deck, A. Todgham, and E. 

D. Grosholz. 2015. Local and global stressor impacts on a coastal foundation species: using an ecologically 

realistic framework. Global Change Biology DOI: 10.1111/gcb.12895. 

Clark, R.C., Jr., J.S. Finley, and G.G. Gibson. 1974. Acute effects of outboard motor effluent on two marine 

shellfish. Environ. Sci. Technol. 8: 1009- 1014.

Couch, D. and T.J. Hassler. 1989. Species Profiles: Life Histories and Environmental Requirements of Coastal 

Fishes and Invertebrates (Pacific Northwest) Olympia Oyster. US Fish and Wildlife Service Biological 

Report 82(11.124).

Ermgassen, P., M.D. Spalding, B. Blake, L.D. Coen, B. Dumbauld, S. Geiger, J.H. Grabowski, R. Grizzle, M. 

Luckenbach, K. McGraw, W. Rodney, J.L. Ruesink, S.P. Powers, and R. Brumbaugh. 2013. Historical 

ecology with real numbers: past and present extent and biomass of an imperilled estuarine habitat. 

Proceedings of the Royal Society B. doi:10.1098/rspb.2012.0313.

Ferner, M., K. Wasson and A. Deck. 2013. Managing for resilience in the face of climate change: a scientific 

approach to targeted oyster restoration in San Francsico Bay anand Elkhorn Slough, California. NERRS 

Science Collaborative Progress Report for the Period 03/01/13 through 08/31/13. Accessed from 

http://www.nerrs.noaa.gov/Doc/PDF/Science/ferner_pr_fall_2013.pdf. 

Hopkins, A.E. 1937. Experimental observations on spawning, larval development, and setting in the Olympia oyster 

Ostrea lurida. U.S. Bur. Fish. Bull. 48:439-503.

Johnston, S.A. 1981. Estuarine dredge and fill activities: A review of impacts. Environmental Management 5(5): 

427-440.

Kimbro, D.L., E.D. Grosholz, A.J. Baukus, N.J. Nesbitt, N.M. Travis, S. Attoe, and C. Coleman-Hulbert. 2009.

Invasive species cause large-scale loss of native California oyster habitat by disrupting trophic cascades. 

Oecologia 160:563–575.

Korringa, P. 1976. Farming the flat oysters of the genus Ostrea: A multidisciplinary treatise. Elsevier, Amsterdam. 

238 pp.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Pacific Biodiversity Institute. Olympia Oyster. Accessed August 26, 2014, from: 

http://www.pacificbio.org/initiatives/ESIN/OtherInvertebrates/OlympiaOyster/OlympiaOyster_pg.html. 

Polson, M.P. and D.C. Zacherl. 2009. Geographic Distribution and Intertidal Population Status for the Olympia 

Oyster, Ostrea lurida Carpenter 1864, from Alaska to Baja. Journal of Shellfish Research 28(1):69-77. 

Stick, D. A., C. J. Langdon, M. A. Banks, M.D. Camara. 2009. Analysis of genetic structure within and among 

remnant populations of the Olympia oyster, Ostrea lurida. Journal of Shellfish Research 28: 732-732. 

Trimble, A. C., J. L. Ruesink, B. R. Dumbauld. 2009. Factors preventing the recovery of a historically 

overexploited shellfish species, Ostrea lurida Carpenter 1864. Journal of Shellfish Research 28: 97-106. 

Wasson, K. 2010. Informing Olympia Oyster restoration: evaluation of factors that limit populations in a California 

estuary. Wetlands 30: 449-459. 

Zabin, C. J., S. Attoe, E. D. Grosholz and C. Coleman-Hulbert. 2009. Shellfish Restoration Goals: Final Report for 

the Subtidal Goals Committee, 107 pp.

226
Pacific Herring (Clupea pallasii)

1

Executive Summary Pacific herring is a coastal schooling 

species of fish found from the surface 

waters to depths of 1,300 feet, 

migrating inshore every year to spawn 

in estuaries (including San Francisco 

and Tomales Bays). Pacific herring

have numerous populations throughout the Pacific Ocean, ranging from Korea, around the rim of 

the North Pacific Basin to Baja California, Mexico. Key climate sensitivities identified for this 

species by workshop participants include sea surface temperature and salinity. No key nonclimate sensitivities were identified by workshop participants; however, habitat degradation (due 

to pollution and dredging) may be an important consideration for the species. Pacific herring 

exhibits a broad, transcontinental distribution across the western and eastern Pacific coasts. 

Though workshop participants reported that the population regionally is diminished, recent 

biomass estimates based on commercial data indicate above-average spawning biomass in San 

Francisco Bay for the last 4 years. Pacific herring exhibit overall moderate diversity, with some 

degree of phenotypic plasticity in environmental tolerance, and broad geographic variation in 

size, genetic composition and recruitment. There is a low overall awareness of the species and 

the role it plays in ecosystems and food webs, resulting in low value to the general public. 

However, multiple actions can be taken to protect the future viability of the species, including 

precautionary management of harvest and protection of spawning grounds in the region’s 

estuaries.

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): sea surface temperature (4, 

high), salinity (4, high), precipitation (3, high), pH (3, moderate), and dynamic ocean conditions 

(currents/mixing/stratification) (3, moderate), air temperature (2, high), dissolved oxygen (DO) 

levels (2, moderate)

Climate and climate-driven changes that may benefit the species: none identified

Overall species sensitivity to climate and climate-driven factors: Moderate

• Confidence of workshop participants: High 

1 Refer to the “Introduction to Assessment Summaries” section on page xx for an explanation of the format, layout 

and content of this summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Pacific Herring Score Confidence 

Sensitivity 2 Low-Moderate 3 High

Exposure 4 Moderate-High 2 Moderate

Adaptive Capacity 3 Moderate 2 Moderate

Vulnerability 3 Moderate 2 Moderate

227
Supporting literature

Herring have demonstrated a very rapid response to short-term, climate-related variability with 

decreased recruitment and abundance occurring very suddenly with changes to oceanographic 

conditions (Beamish 2008). 

Sea Surface Temperature

Enhanced ocean temperatures impact fish physiology by increasing the organism’s oxygen 

demands (Portner and Knust 2007), reducing oxygen solubility in seawater, reducing the 

performance of energy metabolism proteins (Fields et al. 1993) and negatively impacting growth 

and respiration (Largier et al. 2010). Shifts in the latitudinal and depth distribution of fishes are 

also expected as water temperature increases, depending on species tolerance (Largier et al. 

2010). Generally in California, herring are exposed to a temperature range between 8-10 ̊C (46-

50 ̊F) (Miller and Schmidtke 1956). Pacific herring eggs are sensitive to changes in sea surface 

temperature, with survival of viable larvae exhibiting a lower tolerance limit of 4-5 ̊C (39-40 ̊F), 

a higher tolerance limit of 10 ̊C (50 ̊F) and maximum survival of larvae occurring at 6.85 ̊C 

(44 ̊F) (Alderdice and Velsen 1971). Catch statistics indicate that maximum population 

abundance occurs at spawning temperatures of 5-9 ̊C (40-48 ̊C) (Alderdice and Velsen 1971). 

However, larvae exhibit a wide range of temperature tolerance depending on their geographic 

location, suggesting plasticity in environmental tolerance (Barnhart 1988). Warm, nutrientdepleted waters of the 1982-83 El Niño event was associated with poor herring growth, possibly 

due to a reduction in food availability, and altered population distribution (Spratt 1984a,b). 

Ware (1991) also documented smaller adult sizes associated with warmer ocean temperatures 

during El Niño events due to reduced zooplankton abundance. 

Salinity

Most spawning areas are characterized as having reduced salinity within calm and protected 

waters (CDFW 2014). Hatching success has been shown to decrease with increasing salinity 

(Taylor 1971), but extended periods below 20 ppt may inhibit herring spawning (Reilly and 

Moore 1983). However, there exists high variance in salinity tolerance in larvae, especially 

across the species geographic range (Barnhart 1988), and possibly determined by the conditions 

experienced by the eggs during incubation (Alderdice and Hourston 1985). In general, larvae 

appear to be euryplastic, able to withstand a range of environmental conditions, though optimal 

hatch and survival rates do vary across conditions which will likely impact population abundance 

of Pacific herring (Barnhart 1988). Salinity may be expected to vary more widely in the future 

due to enhanced precipitation events and flooding due to sea level rise and storm activity. 

II. Sensitivities to disturbance regimes

Disturbance regimes identified: storms and flooding 

Overall species sensitivity to disturbance regimes: Moderate

• Confidence of workshop participants: Moderate 

Supporting literature

Because herring are dependent on sensitive nearshore and estuarine habitat for spawning, 

flooding due to sea level rise and more intense precipitation events and increased storminess is 

expected to impact the dynamics of herring populations (Beamish 2008). Sea level rise will 

increase shoreline erosion and saltwater intrusion in estuaries, possibly increasing salinity by as 

228
much as 9 practical salinity units (Knowles and Cayan, 2002). Unless there is a comparable 

increase in elevation of the land surface due to sediment delivery and availability, estuarine 

habitat will not be able to adjust to rising sea levels, and flooding will occur more frequently 

(Largier et al. 2010, Ackerly et al. 2012). Increased storm activity, including wave action, will 

have important implications for flooding of estuarine habitat, the state of the estuarine mouth, 

and the timing of estuarine mouth opening and closing (Largier et al. 2010). The mouths of 

estuaries will tend to close with stronger wave energy, and may close earlier or later than usual 

depending on the interaction with river flow. 

III. Dependencies

Species dependence on one or more sensitive habitat types: High

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: estuaries 

Species dependence on specific prey or forage species: Low-Moderate 

• Confidence of workshop participants: Low

Other critical dependencies: none identified 

Specialization of species (1=generalist; 5=specialist): 3

• Confidence of workshop participants: Moderate 

Supporting literature

Within estuarine habitat, Pacific herring are dependent on suitable spawning surfaces such as 

eelgrass and algae (Barnhart 1988). The loss of this biogenic habitat may have resulted in 

declined spawning in some areas of the study region, including Bolinas Lagoon (Sarah Allen, 

pers. comm., 2014). Biogenic habitat is one of most important factors that affect spawning, and 

sea surface temperature, salinity, and human stressors can affect eelgrass growth and expansion 

and thereby affect herring spawning (Sarah Allen, pers. comm., 2014). 

IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): harvest (1, high) 

Overall species sensitivity to non-climate stressors: Low

• Confidence of workshop participants: High

Overall species exposure to non-climate stressors: Low

• Confidence of workshop participants: High

Additional participant comments

Workshop participants did not identify any significant non-climate stressors for Pacific herring, 

and indicated that the species has only low sensitivity and low current exposure to harvest, 

though future harvest could play a stronger role in the sensitivity of the species. An additional 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity. 5 Confidence level indicated by workshop participants.

229
possible sensitivity identified by workshop participants is the lack of structures to aid in 

spawning, likely a result of habitat degradation and loss. 

Supporting literature

In California, gill net fishing is permitted, though the market is relatively minor at this time, and 

herring roe are harvested only in San Francisco Bay for export to Japan (CDFW 2014). Loss of 

biogenic habitat (seagrass) that is critical for spawning through dredging and construction, and 

habitat degradation due to impaired water quality, are significant threats to herring populations 

(NMFS 2014). Impaired water quality has been linked to reduced metabolism in herring 

embryos and eggs (Eldridge et al. 1977) and enhanced mortality of eggs (Rice and Harrison 

1978). Dredging, which results in an increase of sediment in spawning habitat, has been 

identified as an important impact to the species, as the presence of sediment on substrate is 

effective in inhibiting spawning behavior (Stacey and Hourston 1982). 

V. Other sensitivities: none identified 

Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 4

• Confidence of workshop participants: Moderate

Population status of the species (1=endangered; 5=robust): 3

• Confidence of workshop participants: Moderate 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 3 

• Confidence of workshop participants: Moderate

Dispersal ability of the species: High 

• Confidence of workshop participants: Moderate 

Maximum annual dispersal distance: 25-50km 

• Confidence of workshop participants: Low

Supporting literature

Though workshop participants reported that the population regionally is diminished, recent 

biomass estimates based on commercial data indicate above-average spawning biomass in San 

Francisco Bay for the last 4 years (Greiner et al. 2014). Data is not available for the Tomales 

Bay population, but because both Tomales and San Francisco herring feed in the California 

Current Large Marine Ecosystem, it may be assumed that the Tomales Bay population is seeing 

increased recruitment similar to San Francisco (Ryan Bartling, pers. comm., 2015). 

230
II. Intraspecific/Life history diversity

Diversity of life history strategies: Low-Moderate 

• Confidence of workshop participants: Low

Genetic diversity: Moderate

• Confidence of workshop participants: Moderate 

Behavioral plasticity: Moderate

• Confidence of workshop participants: Low

Phenotypic plasticity: Moderate

• Confidence of workshop participants: Low

Overall degree of diversity/plasticity of the species: Moderate

• Confidence of workshop participants: Low

Supporting literature

There is some indication of plasticity in larval tolerance to environmental conditions, including 

temperature and salinity, based on geographic location and exposure of the eggs during 

incubation (Barnhart 1988). Broad geographic variation across the Pacific herring range, 

including size, genetic composition and recruitment, is likely adaptive and in response to local 

prey resources and climate regimes (Hay et al. 2008).

Beginning in October, and continuing as late as April (CDFW 2014), adult herring migrate 

inshore to estuaries to breed every year, spawning in shallow coastal areas between the subtidal 

and intertidal zones, depositing eggs on kelp, eelgrass, and other structures such as pier pilings 

and riprap (NMFS 2014). In the study region, Tomales Bay and San Francisco Bay have the 

largest spawning populations (Spratt 1981). Maximum lifespan is 19 years (NMFS 2014), but 

varies by geography. In San Francisco Bay, lifespan is up to 8 years with 80% of the population 

aged 6 years or less (Ryan Bartling, pers. comm., 2014). 

III. Management potential

Value of species to people: Low

• Confidence of workshop participants: High 

• Description of value: There is a low overall awareness of the species and the role it plays 

in ecosystems and food webs. 

Likelihood of managing or alleviating climate change impacts on species: Low-Moderate

• Confidence of workshop participants: Moderate 

• Description of potential management options: Management priorities for this species may 

include a precautionary approach to harvest, further research into requirements for 

successful recruitment, and protection of herring spawning grounds. 

IV. Other adaptive capacity factors: none identified 

231
Exposure6

I. Future climate exposure

Future climate and climate-driven changes identified (score7, confidence8): changes in salinity

(4, moderate), decreased pH (4, moderate), increased storminess (4, moderate), changes in sea 

surface temperature (4, moderate), changes in precipitation (3, moderate), increased coastal 

erosion and runoff (3, moderate) 

Degree of exposure to future climate and climate-driven changes: Moderate-High

• Confidence of workshop participants: Moderate 

Supporting literature

Precipitation may cause an increase in freshwater exposure which affects eelgrass and algae 

substrate on which eggs are laid, but sea level rise and heat events that increase 

evapotranspiration may cause a decrease in local salinity (Largier et al. 2010). Refugia from 

climate exposure may be found in bays and estuaries where sea surface temperature may be 

lower and where eelgrass occurs (Sarah Allen, pers. comm., 2014). 

Literature Cited

Ackerly, D. D., R. A. Ryals, W. K. Cornwell, S. R. Loarie, S. Veloz, K. D.Higgason, W. L. Silver, and T. E. 

Dawson. 2012. Potential Impacts of Climate Change on Biodiversity and Ecosystem Services in the San 

Francisco Bay Area. California Energy Commission. Publication number: CEC-500-2012- 037.

Alderdice, D. F. and A. S. Hourston. 1985. Factors influencing development and survival of Pacific herring (Clupea 

harengus pallasi ) eggs and larvae to beginning of exogenous feeding. Can. J. Fish. Aquat. Sci. 42 (Suppl . 

1): 56-68. 

Alderdice, D.F. and F.P.J. Velsen. 1971. Some Effects of Salinity and Temperature on Early Development of Pacific 

Herring (Clupea pallasi). Journal of the Fisheries Research Board of Canada, 1971, 28(10): 1545-1562.

Barnhart, R.A. 1988. Species profiles: life histories and environmental requirements of coastal fishes and 

invertebrates (Pacific Southwest) -- Pacific herring. U.S. Fish Wildl. Serv. Biol. Rep. 82(11.79). U.S. Army 

Corps of Engineers, TR EL-82-4. 14 pp.

Beamish, R.J., editor. 2008. Impacts of Climate and Climate Change on the Key Species in the Fisheries in the

North Pacific. PICES Working Group on Climate Change, Shifts in Fish Production, and Fisheries 

Management. PICES Scientific Report No. 35.

California Department of Fish and Wildlife (CDFW). 2014. State-Managed California Commercial Herring Fishery. 

Accessed September 4, 2014, from: http://www.dfg.ca.gov/marine/herring/. 

Eldridge, M. B., T. Echeverria, and J.A. Whiddle. 1977. Energetics of Pacific herring (Clupea harengus pallasi) 

embryos and larvae exposed to low concentrations of benzene, a monoaromatic component of crude oil. 

Trans. Am. Fish. Soc. 106(5):452- 461. 

Fields, P.A., J.B. Graham, R.H. Rosenblatt, G.N. Somero. 1993. Effects of expected global climate change on 

marine faunas. Trends in Ecology and Evolution 8:361-367. 

Greiner, T., R. Bartling, A. Weltz. 2014. Summary of the 2013-2014 Pacific Herring Spawning Population and 

Commercial Fisheries in San Francisco Bay. California Department of Fish and Wildlife.

Hay, D.E., K.A. Rose, J. Schweigert, and B.A. Megrey. 2008. Geographic variation in North Pacific herring 

populations: Pan-Pacific comparisons and implications for climate change impacts. Progress in 

Oceanography 77 (2008) 233–240.

Knowles, N. and D.R. Cayan. 2002. Potential effects of global warming on the Sacramento/San Joaquin watershed 

6 Supporting literature for future exposure to climate factors is provided in the introduction.

7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

232
and the San Francisco estuary. Geophysical Research Letters 29:1891. 

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Miller, D.J., and J. Schmidtke. 1956. Report on the distribution and abundance of Pacific herring (Clupea pallasi) 

along the coast of central and southern California. Calif. Fish Game 42: 163-187. 

National Marine Fisheries Service (NMFS). 2014. Pacific Herring. Accessed September 4, 2014 from: 

http://www.nmfs.noaa.gov/pr/species/fish/pacificherring.htm. 

Portner, H.O. and R. Knust. 2007. Climate change affects marine fishes through the oxygen limitation of thermal 

tolerance. Science 315:95-97. 

Reilly, P.N. and T.O. Moore. 1983. Pacific herring, Clupea harengus pallasi , studies in San Francisco Bay, 

Monterey Bay, and the Gulf of the Farallones, July 1982 to March 1983. Calif. Fish Game Mar. Res. 

Admin. Rep. 83-5. 49 pp.

Rice, D.W., Jr., and F. L. Harrison. 1978. Copper sensitivity of Pacific herring (Clupea harenqus pallasi) during its 

early life history. U.S. Natl. Mar. Fish. Serv. Fish. Bull. 76(2): 347-356.

Spratt, J.D. 1981. Status of the Pacific herring Clupea harengus pallasi resource in California, 1972 to 1980. Calif. 

Fish Game, Fish. Bull. 171:l-107. 

Spratt, J. D. 1984a. Biomass estimate of Pacific herring, Clupea harengus pallasi, in California from the 1983-84 

spawning-ground surveys. Calif. Fish Game Mar. Res. Admin. Rep. 84-2. 29 pp. 

Spratt, J. D. 1984b. Biological characteristics of the catch from 1983-84 Pacific herring, Clupea harengus pallasi, 

roe fishery in California. Calif. Fish Game Mar. Res. Admin. Rep. 84-4. 18 pp.

Taylor, F.H.C. 1971. Variation in hatching success in Pacific herring Clupea pallasi eggs with water depth, 

temperature, salinity , and egg mass thickness. Rapp. P.-V. Reun. Cons. Int. Explor. Mer 160: 34- 41.

233
Pteropod1

Executive Summary Pteropods are pelagic marine 

gastropods, consisting of two 

orders: the shelled Thecosomata 

and the non-shelled Gymnosomata. 

For the purposes of this 

assessment, focus will be on the 

shelled pteropods. Key climate sensitivities identified for this species assemblage by workshop 

participants include pH and dynamic ocean conditions (currents/mixing/stratification). No nonclimate stressors were identified. Pteropod species have a broad, transcontinental geographic 

distribution and a continuous, stable population at abundant levels with moderate-high dispersal 

capabilities. Pteropods exhibit overall low diversity and plasticity, though morphological and 

behavioral diversity does exist between species, and plasticity has been documented in pteropod 

physiology. Additionally, pteropods exhibit multiple reproductive/life history strategies 

depending on the species. Genetic diversity in these species is largely unknown, though there is 

some evidence of high genetic differentiation in the Thecosome pteropods. Pteropods have low 

societal value due to their inconspicuous, offshore nature, though they do serve as a vital part of 

the ecosystem. The management potential for the species assemblage is considered low because 

pteropods are most critically impacted by the current and expected decrease in pH, which cannot 

be managed on a regional scale. 

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): pH (5, high), dynamic 

ocean conditions (currents/mixing/stratification) (4, high) 

Climate and climate-driven changes that may benefit the species: none identified

Overall species sensitivity to climate and climate-driven factors: High

• Confidence of workshop participants: High

Additional participant comments 

There is documented evidence that the ocean’s chemistry is changing (pH is lowering due to 

increased CO2 uptake), and there is also documented evidence of how this change in pH affects 

pteropods 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Pteropod Score Confidence

Sensitivity 4 Moderate-High 2 Moderate

Exposure 5 High 3 High

Adaptive Capacity 3 Moderate 2 Moderate

Vulnerability 4 Moderate-High 2 Moderate

234
Supporting literature

pH 

Limacina helicina has been used extensively to study the effects of ocean acidification on the 

shelled pteropods (Elliott and Jahncke 2014). This species is a critical mid-trophic component of 

pelagic food webs, both as a consumer and as prey for commercially important fish species, 

whales, and seabirds (Lischka et al. 2010). Shell diameter, shell increment and shell degradation 

in juveniles of L. helicina are significantly impacted by pCO2 scenarios projected by the end of 

this century, severely affecting the abundance of juveniles that are critical for the following 

year’s reproduction (Lischka et al. 2010). Adults exhibited a 28% decrease in calcification under 

conditions expected by 2100 (Comeau et al. 2009) and a 20% decrease in oxygen consumption 

(Seibel et al. 2012). Severe pteropod shell dissolution due to anthropogenic ocean acidification 

is estimated to have doubled in nearshore waters since pre-industrial conditions across the 

California Current Ecosystem (CCE), and will likely triple by 2050 (Bednaršek et al. 2014). 53% 

of onshore individuals and 24% of offshore individuals were found, on average, to exhibit severe 

dissolution damage in the CCE (Bednaršek et al. 2014), which indicates that habitat suitability 

for pteropods in the study region is declining. 

Dynamic ocean conditions (currents/mixing/stratification) 

As the primary delivery method of naturally low-pH and under-saturated waters (with respect to 

aragonite and calcite) that are enriched in CO2 (Gruber et al. 2012), upwelling is the primary 

driver of pteropod abundance in the region (Vulnerability Assessment Workshop, pers. comm., 

2014). Strong upwelling events transport these deep, under-saturated waters onto the continental 

shelf, sometimes reaching surface waters (Feely et al. 2008)). Though this is a natural process 

that may counteract rising sea surface temperatures and promote primary productivity (Largier et 

al. 2010), intense upwelling could shift plankton to deeper waters (Pringle 2007), potentially 

decreasing food availability for pteropods (Largier et al. 2010) and further exacerbate the undersaturation of aragonite necessary for shell building in pteropod juveniles. El Niño events and 

positive phases of the PDO suppress upwelling, reducing nutrient delivery to photic zones, 

decreasing primary productivity, but also decreasing pteropod exposure to under-saturated 

waters (Bi et al. 2011, Young et al. 2012). 

II. Sensitivities to disturbance regimes: none identified

III. Dependencies

Species dependence on one or more sensitive habitat types: Low-Moderate

• Confidence of workshop participants: Moderate 

• Sensitive habitats species is dependent upon: no answer provided 

Species dependence on specific prey or forage species: Moderate-High

• Confidence of workshop participants: Moderate

Other critical dependencies: reproductive strategies of different pteropod species 

• Degree of dependence: Low-Moderate

• Confidence of workshop participants: Moderate 

Specialization of species (1=generalist; 5=specialist): 4

• Confidence of workshop participants: Moderate 

235
Supporting literature

Pteropods may more closely resemble specialists due to physiological adaptations to a 

holoplanktonic lifestyle, including aggressive planktonic predation, well-developed swimming 

behavior in gynmosomes (Harbison and Gilmer 1992, Lalli 1970, Lalli and Gilmer 1989), and 

the production of anti-predation compounds to reduce palatability in thecosomes (McClintock 

and Baker 1998). 

IV. Sensitivity and current exposure to non-climate stressors: none identified

Supporting literature

Though workshop participants did not identify any non-climate stressors for pteropods, the 

impact of oil, identified for copepods, also applies to this species assemblage. Dispersed oil is 

expected to negatively impact pteropods and other zooplankton in the study region (Mearns 

2012). Over 6,000 commercial vessels transit in and out of San Francisco Bay every year, with 

5% of these as large cargo vessels that can carry up to one million gallons of bunker fuel 

(GFNMS 2008). All transiting vessels, including military, research and fishing vessels, carry 

crude oil or fuel, posing a potential risk to pteropod populations in the region (Largier et al. 

2010).

V. Other sensitivities: none identified 

Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 5

• Confidence of workshop participants: High 

Population status of the species (1=endangered; 5=robust): 4

• Confidence of workshop participants: Low

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 5

• Confidence of workshop participants: Moderate 

Dispersal ability of the species: Moderate-High 

• Confidence of workshop participants: Moderate 

Maximum annual dispersal distance: >100km 

• Confidence of workshop participants: Moderate 

II. Intraspecific/Life history diversity

Diversity of life history strategies: Low-Moderate 

• Confidence of workshop participants: Moderate 

Genetic diversity: Moderate

• Confidence of workshop participants: Moderate

Behavioral plasticity: Low

• Confidence of workshop participants: Low

236
Phenotypic plasticity: Low

• Confidence of workshop participants: Low

Overall degree of diversity/plasticity of the species: Low-Moderate

• Confidence of workshop participants: Moderate

Supporting literature

Pteropods exhibit multiple reproductive/life history strategies depending on the species. Some 

species (e.g. Limacina helicina) are protandric hermaphrodites that use internal fertilization and 

produce floating egg masses, while others (e.g. L. helicoides, L. inflata) brood their young until 

they are juveniles or early veligers. The former strategy (egg masses) shows the highest 

fecundity; however, the planktonic egg masses may be exposed to corrosive waters and higher 

mortality rates than in the past (Lalli and Wells 1978). The genetics of pteropods is poorly 

studied, though significant genetic variation has been observed for some species, particularly 

Thecosome pteropods (Jennings et al. 2010). In this study region, Limacina helicina, is the most 

abundant Thecosome pteropod and is currently being documented and studied; six other 

Thecosome pteropods have been documented in our region but in far lower densities (Point Blue 

Conservation Science, unpublished data). Metabolic plasticity was demonstrated in response to 

regional phytoplankton concentration, with varying response to pCO2 dependent on the baseline 

level of metabolism (Seibel et al. 2012). Though workshop participants indicated pteropods 

exhibit low behavioral plasticity, there is some indication that some species can change their 

daily vertical distribution pattern by migrating to upper supersaturated waters to avoid corrosive 

waters (Bednaršek 2015). 

III. Management potential

Value of species to people: Low

• Confidence of workshop participants: High 

• Description of value: low societal value due to their inconspicuous, offshore nature, 

though they do serve as a vital part of the ecosystem

Likelihood of managing or alleviating climate change impacts on species: Low

• Confidence of workshop participants: High 

• Description of possible management options: None identified. Because pteropods are so 

critically impacted by the current and expected decrease in pH, the only way to 

effectively manage the species would be to prevent ocean acidification from occurring. 

IV. Other adaptive capacity factors: none identified 

Exposure 

I. Future climate exposure4

Future climate and climate-driven changes identified (score5, confidence6): decreased pH (5, 

high), altered currents and mixing (5, high) 

4 Supporting literature for future exposure to climate factors is provided in the introduction.

237
Degree of exposure to future climate and climate-driven changes: High

• Confidence of workshop participants: High 

Literature Cited 

Bednaršek, N., R.A. Feely, J.C.P. Reum, W. Peterson, J. Menkel, S.R. Alin, and B. Hales. 2014. Limacina helicina 

shell dissolution as an indicator of declining habitat suitability due to ocean acidification in the California 

Current Ecosystem. Proc. Roy. Soc. B: 281, 20140123, doi: 10.1098/rspb.2014.0123. 

Bednaršek, N. 2015. “Vulnerability and Adaptation Strategies of Pteropods in the California Current Ecosystem”. 

Conservation Science Webinar Series, US Fish and Wildlife Service. March 19, 2015. 

Bi, H., W.T. Peterson, and P.T. Strub. 2011. Transport and coastal zooplankton communities in the northern 

California Current System. Geophysical Research Letters 38: L12607. 

Comeau, S., Gorsky, G., Jeffree, R., Teyssié, J.L., and Gattuso, J.P. 2009. Impact of ocean acidification on a key

Arctic pelagic mollusc (Limacina helicina), Biogeosciences, 6, 1877-1882. 

Elliott, M. L. and J. Jahncke. 2014. Ocean Climate Indicators Status Report – 2013. Unpublished Report. Point Blue 

Conservation Science, Petaluma, California. Point Blue contribution number 1982.

Feely, R.A., C.L. Sabine, J.M. Hernandez-Ayon, D. Ianson, and B. Hales. 2008. Evidence for upwelling of corrosive 

"acidified" seawater onto the continental shelf. Science 320, 1490. 

Gruber N, Hauri C, Lachkar Z, Loher D, Frolicher TL, Plattner GK. 2012. Rapid progression of ocean acidification 

 in the California Current System. Science 337(220). 

Gulf of the Farallones National Marine Sanctuary (GFNMS). 2008. Management Plan. 

http://farallones.noaa.gov/manage/plan.html#plan. 

Harbison, G. and R. Gilmer. 1992. Swimming, buoyancy and feeding in shelled pteropods—a comparison of field 

 and laboratory observations. Journal of Molluscan Studies 58, 337–339.

Jennings, R.M., A. Bucklin, H. Ossenbrugger, and R.R. Hopcraft. 2010. Species diversity of planktonic gastropods 

 (Pteropoda and Heteropoda) from six ocean regions based on DNA barcode analysis. Deep-Sea Research 

 II 57: 2199-2210.

Lalli, C.M., 1970. Structure and function of the buccal apparatus of Clione limacine (Phipps) with a review of 

feeding in gymnosomatous pteropods. Journal of the Experimental Marine Biological Association of the 

UK 4, 101–118.

Lalli, C.M. and Wells. 1978. Reproduction in the genus Limacina (Opisthobranchia: Thecosomata). J. Zool., Lond. 

186: 95-108.

Lalli, C.M. and R.W. Gilmer. 1989. Pelagic snails: the biology of holoplanktonic gastropod mollusks. Stanford 

University Press, Stanford CA. 

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Lischka, S., J. Budenbender, T. Boxhammer and U. Riebesell. Impact of ocean acidification and elevated 

temperatures on early juveniles of the polar shelled pteropod Limacina helicina: mortality, shell 

degradation, and shell growth. Biogeosciences Discussion 7: 8177-8214.

McClintock, J.B. and B.J. Baker. 1998. Chemical ecology in Antarctic seas. American Scientist 86, 254-63.

Mearns, A. 2012. Oil dispersants: to use or not use. Oral presentation, Cordell Bank and Gulf of the Farallones 

National Marine Sanctuaries Advisory Councils’ Vessel Spills Working Group, Petaluma, CA. 

Pringle, J.M. 2007. Turbulence avoidance and the wind-driven transport of plankton in the surface Ekman layer. 

Continental Shelf Research 27:670-678.

Seibel BA, Maas AE, Dierssen HM. 2012. Energetic Plasticity Underlies a Variable Response to Ocean 

Acidification in the Pteropod, Limacina helicina antarctica. PLoS ONE 7(4): e30464. 

Young, L. R.M. Suryan, D. Duffy, and W.J. Sydemann. 2012. Climate Change and Seabirds of the California 

Current and Pacific Islands Ecosystems: Observed and Potential Impacts and Management Implications. 

Final Report to the U.S. Fish and Wildlife Service, Region 1. Unpublished.

5 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

6 Confidence level indicated by workshop participants.

238
Red Abalone (Haliotis rufescens)

1

Executive Summary Red abalone, a marine gastropod 

mollusk, is the largest abalone species 

in North America. This species inhabits 

rocks and crevices from the low 

intertidal to 180m in depth, ranging 

from Sunset Bay, Oregon to Baja 

California. Key climate sensitivities identified by workshop participants include dissolved 

oxygen, pH, air and sea surface temperature, and salinity and key non-climate sensitivities

include harvest. Red abalone exhibit a transcontinental geographic extent and a very diminished, 

but stable population that is predominantly restricted to subtidal habitat due to historic overharvest. Larvae have moderate-high dispersal capability, possibly dispersing up to 25 km, though 

distinct genetic variation among populations indicates that some geographic barriers to dispersal 

exist. Red abalone exhibit low-moderate behavioral diversity and low phenotypic plasticity, with 

some indication of plasticity in sensitivity to environmental change. The high societal value for 

red abalone is due to its value for harvest, aesthetics and recreation. The likelihood of managing 

or alleviating climate impacts is considered moderate, and will depend on managers’ ability to 

maintain healthy populations to retain genetic diversity and recovery potential. 

Sensitivity 

I. Sensitivity to climate and climate driven changes 

Climate and climate-driven changes identified (score2, confidence3): air temperature (5, high), 

dissolved oxygen (DO) levels (5, high), ocean pH (5, moderate), sea surface temperature (4, 

high), salinity (4, moderate), wave action (3, high), dynamic ocean conditions 

(currents/mixing/stratification) (3, high), sea level rise (2, low), coastal erosion (2, high) 

Climate and climate-driven changes that may benefit the species: upwelling

• Description of benefit: Increased upwelling could increase productivity, but it may also 

exacerbate ocean acidification

Overall species sensitivity to climate and climate-driven factors: Moderate-High

• Confidence of workshop participants: High 

Additional participant comments

Though few red abalone are found in the intertidal due to over-harvest, sensitivity to warm air 

temperatures is still a concern for red abalone because it is a cold-adapted species.

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Red Abalone Score Confidence 

Sensitivity 4 Moderate-High 3 High

Exposure 3 Moderate 3 High

Adaptive Capacity 3 Moderate 3 High

Vulnerability 3 Moderate 3 High

239
Supporting literature

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered. No information was found regarding the impact 

of salinity or air temperature on red abalone. 

Oxygen

Exposure to low-oxygen waters may be expected to occur more frequently with the projected 

increase in enhanced upwelling events (Largier et al. 2010). Mortality rates of juvenile red 

abalone exposed to low-oxygen water (40% saturation, mg/L) for short periods of time (3-6 

hours every 3-5 days) did not differ from control animals; however, when exposure was 

extended to two 24 hour periods over 15 days, mortality rates were 5-20% higher than controls, 

and growth rates were significantly reduced (Kim et al. 2010). When combined with low-pH 

conditions, individual variation in growth rate increased, suggesting some degree of phenotypic 

plasticity (Kim et al. 2010). These results suggest that prolonged exposure to low-oxygen, 

upwelled water may significantly impact juvenile red abalone survival. 

pH 

pH is expected to continue to decrease, resulting in greater acidification of coastal waters, and 

this decrease will be more pronounced in upwelling centers, including the study region (Largier 

et al. 2010). Growth rates were significantly reduced for juvenile red abalone exposed to low-pH 

water (7.5) for two 24-hour periods over 15 days, though variation in the change in growth rate 

among individuals suggests some degree of phenotypic plasticity in pH sensitivity (Kim et al. 

2010). Low pH (7.87) also resulted in significantly lower thermal tolerance in 2 of 4 larval stages 

tested, suggesting variability in sensitivity throughout the species life history (Zippay and 

Hofmann 2010). 

Sea Surface Temperature

Sperm production in male red abalone is significantly lower when exposed to warm water (18°C) 

for 6 months, dropping from 300,000 presperm cells/mm3

 to 46,000 presperm cells/mm3

(Rogers-Bennett 2010). Warmer water is also linked to slower growth rate (Haaker et al. 1998), 

decreased reproduction (Vilchis et al. 2005), and an increase in the onset of withering foot 

syndrome (Moore et al. 2002, Vilchis et al. 2005), a serious bacterial infection that causes 

mortality. The bacterium can reside within the tissues of abalone without manifestation of the 

syndrome, but warm water has been implicated as a trigger for development of the syndrome 

(Rogers-Bennett 2010). 

II. Sensitivity to changes in disturbance regimes

Disturbance regimes identified: storms, disease, and harmful algal blooms (HABs) 

Overall species sensitivity to disturbance regimes: High

• Confidence of workshop participants: High 

Additional participant comments

Disease will likely have the largest impacts on red abalone. Extreme storm events that cause 

scouring and dislodgement of abalone may have significant adverse impacts to the species. 

240
Supporting literature

Storms

Increasingly intense run-off during extreme storm events may cause increased sedimentation that 

may negatively impact red abalone due to sand scour, and increased freshwater input to the 

nearshore subtidal that may lead to higher resuspension of sediment resulting in increased 

turbidity and light attenuation (Largier et al. 2010). 

Disease

Disease is projected to increase with warming water temperatures, due to enhanced pathogen 

development and survival, as well as host susceptibility (Harvell et al. 2002), and in red abalone, 

the onset of withering foot syndrome has been attributed to exposure to warm water temperatures 

(Vilchis et al. 2005) with mass syndrome expression occurring during strong El Niño events 

(Moore et al. 2011). 

Harmful algal blooms (HABs)

HABs have increased in frequency and severity along the California coast during the past few 

decades, with blooms of dinoflagellates and Pseudo-nitzschia becoming more common 

(Southern California Marine Institute (SCMI) 2014). Substantial mortality of filter feeders, 

grazers and predators have been documented following a bloom (Southgate et al. 1984, 

Robertson 1991), and MPA baseline data indicated a 40% decline in red abalone density between 

2010 and 2011 at sites along the Sonoma Coast, which coincided with a HAB in that region 

(Carr 2013). This event in Sonoma County (Bodega Bay to Anchor Bay) resulted in the largest 

die-off of marine invertebrates ever associated with a HAB in this region. 

III. Dependencies

Species dependence on one or more sensitive habitat types: Moderate-High

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: rocky reefs; where sea otters are present, 

cracks and crevices are relied upon as habitat (Steve Lonhart, pers. comm., 2014) 

Species dependence on specific prey or forage species: Low-Moderate 

• Confidence of workshop participants: High 

Other critical dependencies: sufficient adult density to ensure reproductive success of the species 

(Allee effect)

• Degree of dependence: High

• Confidence of workshop participants: High 

Specialization of species (1=generalist; 5=specialist): 3

• Confidence of workshop participants: High 

IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): harvest (5, high), pollution and poisons 

(3, low), and invasive and problematic species (2, low) 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

241
Overall species sensitivity to non-climate stressors: Moderate

• Confidence of workshop participants: Low

Overall species exposure to non-climate stressors: Low-Moderate

• Confidence of workshop participants: High 

Additional participant comments

Harvesting can negatively impact the species through the resulting Allee effect, which can 

restrict genetic diversity and the ability of the species to recover from climate change impacts.

Supporting literature

Literature review was conducted for those factors scoring 4 or higher, although the other 

sensitivities identified should also be considered.

Harvest

Red abalone is the largest abalone species in North America, and is highly valued by both sea 

otters and humans, commanding high prices for its highly prized meat and iridescent shell used 

in jewelry, resulting in over-harvest (SIMoN 2014). The commercial fishery peaked in 1967 and 

steadily declined until it was closed in 1997. Over-harvest of the species can result in the Allee 

effect, due to insufficient adult density to support reproductive success, and restrict genetic 

diversity, which can have major implications for the species’ ability to recover from climate 

events (Levitan et al. 1992). 

V. Other sensitivities: None identified

Adaptive Capacity

I. Extent, Status, and Dispersal Ability

Geographic extent of the species (1=endemic; 5=transboundary): 5

• Confidence of workshop participants: High 

Population status of the species (1=endangered; 5=robust): 3

• Confidence of workshop participants: Moderate 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 2

• Confidence of workshop participants: High 

Dispersal ability of the species: (adult) – Low; (larval) – Moderate-High 

• Confidence of workshop participants: Moderate 

Maximum annual dispersal distance: 5-25km (larval)

• Confidence of workshop participants: Moderate 

Supporting literature

The species is now most abundant subtidally, and is rare in the intertidal likely due to over 

harvesting (SIMoN 2014). While adults are capable of significant movement due to their strong 

muscular foot (and will move away from predatory sea stars), they often remain stationary, some 

242
staying hidden in the same crevice for their entire life (SIMoN 2014). Current estimates of larval 

dispersal in the literature range from several kilometers (Morgan and Shepherd 2006) up to 10 

km (Hobday and Tegner 2002), though these estimates are based on only a 4-7 day larval 

duration. Recent work shows that larvae may remain competent in the water column for up to 32 

days, which would allow for a greater dispersal distance, though settlement after 20 days resulted 

in significantly lower subsequent postlarval survival (Mccormick et al. 2012). 

II. Intraspecific/Life history diversity

Diversity of life history strategies: Moderate

• Confidence of workshop participants: Moderate 

Genetic diversity: no answer provided 

• Confidence of workshop participants: n/a 

Behavioral plasticity: Low-Moderate

• Confidence of workshop participants: Moderate 

Phenotypic plasticity: Low

• Confidence of workshop participants: High 

Overall degree of diversity/plasticity of the species: Low-Moderate

• Confidence of workshop participants: Moderate 

Additional participant comments

Though adults have somewhat limited mobility, individuals are able to “clamp down” and seal

tightly to the substrate to limit exposure to oxygen stress in the subtidal and heat stress in the 

intertidal.

Supporting literature

Individual variation in growth rate response to upwelled water (low-pH and low-oxygen water) 

has been observed in juvenile red abalone, suggesting some degree of phenotypic plasticity in 

sensitivity to those factors (Kim et al. 2010). Genetic studies on multiple species of abalone find 

high genetic variation among populations, indicating that barriers to dispersal exist along the 

California coastline (Palumbi 2014); in particular, Cape Mendocino seems to be a breakpoint in 

the genetic structure of the red abalone (Gruenthal et al. 2007). This species is a broadcast 

spawner that can produce up to a million gametes in one breeding event, but is slow growing and 

can take 4 years to reach sexual maturity (SIMoN 2014). Spawning is greatest in the spring, 

typically from February to April, and can be triggered by environmental cues such as a sudden 

change in water temperature and exposure to air for 1-2 hours (SIMoN 2014). 

III. Management potential

Value of species to people: High

• Confidence of workshop participants: High 

• Description of value: valued for harvest, aesthetics, and recreation 

Likelihood of managing or alleviating climate change impacts on species: Moderate

• Confidence of workshop participants: Moderate 

243
• Description of potential management options: Management efforts should focus on 

maintaining health populations of sufficient size to ensure genetic diversity and recovery 

potential from disturbances and climate change impacts.

IV. Other Adaptive Capacity Factors

Critical factors not addressed that may affect species’ adaptive capacity: interactive effect of 

shell-boring worms and shells weakened by ocean acidification 

• Degree to which these factors affect the habitat’s adaptive capacity: Moderate

• Confidence of workshop participants: Low

Exposure 

I. Future climate exposure6

Future climate and climate-driven changes identified (score7, confidence8): decreased pH (5, 

high), sea level rise (5, high), changes in air temperature (5, high), decreased dissolved oxygen 

(DO) levels (3, moderate), changes in sea surface temperature (1, moderate), changes in salinity

(1, high), and changes in precipitation (1, high) 

Degree of exposure to future climate and climate-driven changes: Moderate

• Confidence of workshop participants: High 

Literature Cited

Carr, M., E. Saarman, D. Malone. 2013. North Central Coast Baseline Surveys of Kelp Forest Ecosystems: a report 

prepared for Sea Grant.

Gruenthal KM, Acheson LK, Burton RS. 2007. Genetic structure of natural populations of California red abalone 

 (Haliotis rufescens) using multiple genetic markers. Marine Biology 152(6):1237-1248.

Haaker, P. L., D. O. Parker, K. C. Barsky & C. S. Y. Chun. 1998. Growth of red abalone,Haliotis rufescens, 

(Swainson,), at Johnsons Lee, Santa Rosa Island, California. J. Shellfish Res. 17:747–753.

Harvell, C.D., C.E. Mitchell, J.R. Ward, S. Altizer, A.P. Dobson, R.S. Ostfeld and M.D. Samuel. 2002. Climate 

warming and disease risks for terrestrial and marine biota. Science 296:2158-2162.

Hobday, A. J., and M. J. Tegner. 2002. The warm and the cold: Influence of temperature and fishing on local 

population dynamics of red abalone. California Cooperative Oceanic Fisheries Investigations Reports 

43:74–96.

Kim, T.W., Barry, J.P., and Micheli, F. 2010. The effects of intermittent exposure to low-pH and lowoxygen conditions on survival and growth of juvenile red abalone. Biogeosciences 10:7255-62.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Levitan, D. R., M. A. Sewell and F.-S. Chia. 1992. How distribution and abundance influence fertilization success in 

the sea urchin Strongylocentotus franciscanus. Ecology 73 (1):248-254.

Mccormick, T. B., L. M. Buckley, G. Navas, G. Barber, B. Billups, V. Gill, B. Jones, N. Peterson, B. Saylor and J. 

Sayre. 2012. Larval Competency of Red Abalone (Haliotis rufescens): A New Timeframe for Larval 

Distribution. Journal of Shellfish Research 31 (4):1183-1187.

6 Supporting literature for future exposure to climate factors is provided in the introduction.

7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

244
Moore, J. D., C. A. Finley, C. S. Friedman & T. T. Robbins. 2002. Withering syndrome and restoration of southern 

California abalone populations. CCOFI Rep. 43:112–119.

Moore, J. D., B. C. Marshman and C. S. Chun. 2011. Health and survival of red abalone Haliotis rufescens from San 

Miguel Island, California, USA, in a laboratory simulation of La Niña and El Niño conditions. Journal of 

Aquatic Animal Health 23 (2):78-84.

Morgan, L. E., and S. A. Shepherd. 2006. Populations and spatial structure of two common temperate reef 

herbivores: abalone and sea urchins. Pages 205–246 in J. P. Kritzer and P. F. Sale, editors. Marine 

metapopulations. Elsevier Academic Press, Burlington, Massachusetts, USA. 

Palumbi. 2014. Projects: Genetics, Geography & Environment. Population Genomics of Abalone Along the 

California Coast. Accessed June 2014. http://palumbi.stanford.edu/abalone.html. 

Robertson, A. 1991. Effects of a toxic bloom of Chrysomulina polylepis on the common dog-whelk, Nucella 

lapillus, on the Swedish west coast. Journal of the Marine Biological Association of the United Kingdom 

71: 569-578.

Rogers-Bennett, L., R. F. Dondanville, J. D. Moore and L. I. Vilchis. 2010. Response of red abalone reproduction to 

warm water, starvation, and disease stressors: implications of ocean warming. Journal of Shellfish Research

29 (3):599-611.

Sanctuary Integrated Monitoring Network (SIMoN). 2014. Mytilus californianus - California Mussel. Accessed June 

2014. http://www.sanctuarysimon.org/species/mytilus/californianus/california-mussel.

Southgate, T., K. Wilson, T.F. Cross, and A.A. Myers. 1984. Recolonization of a rocky shore in S.W. Ireland 

following a toxic bloom of the dinoflagellate Gyrodinium aureolum. Journal of the Marine Biological 

Association of the United Kingdom 64: 485–492.

Southern California Marine Institute (SCMI). 2014. Ecology of Harmful Algal Blooms ECOHAB. Accessed June 

2014. http://scmi.us/category/research/ecology-of-harmful-algal-blooms-ecohab.

Vilchis, L. I., M. J. Tegner, J. D. Moore, C. S. Friedman, K. L. Riser, T. T. Robbins & P. K. Dayton. 2005. Ocean 

warming effects on growth, reproduction, and survivorship of Southern California abalone. Ecol. Appl. 

15:469–480.

Zippay, M.L and G.E. Hofmann. 2010. Effect of pH on gene expression and thermal tolerance of early life history 

stages of red abalone (Haliotis rufescens). Journal of Shellfish Research 29(2): 429-439.

245
Sea Urchin, Red (Strongylocentrotus franciscanus) and Purple (S. 

purpuratus)

1

Executive Summary Red and purple sea urchins, 

echinoderm invertebrates, inhabit low 

intertidal rocky reefs and subtidal kelp 

forests, reaching depths around 100 

meters along the Pacific coast of North 

America, from Alaska to Baja 

California. The overall vulnerability of these species will likely vary greatly between intertidal 

and subtidal populations. Key climate sensitivities identified by workshop participants include 

dissolved oxygen, ocean pH, dynamic ocean conditions, air temperature and sea surface 

temperature and key non-climate sensitivities include pollution and poisons and harvest. Red and 

purple sea urchins exhibit transcontinental geographic extents and stable, continuous populations 

that are at abundant levels. Long-lived pelagic larvae enable high dispersal capability. The 

species are highly diverse genetically, and exhibit low-moderate behavioral plasticity, though 

they can alter the timing of spawning to coincide with phytoplankton density and alter their 

morphology in response to current flow. Societal value for urchins is moderate-high due to their 

culinary value, value to tourism, prey for sea otters, and as a viable fishery. The likelihood of 

managing or alleviating climate impacts was rated as low, though many management alternatives 

have been suggested in the literature to better manage harvest. 

Sensitivity 

I. Sensitivity to climate and climate driven changes 

Climate and climate-driven changes identified (score2, confidence3): dissolved oxygen (DO) 

levels (4, high), ocean pH (4, high), dynamic ocean conditions (currents/mixing/stratification) (4, 

high), air temperature (4, high), sea surface temperature (3, high) 

Climate and climate-driven changes that may benefit the species: none provided 

Overall species sensitivity to climate and climate-driven factors: Moderate-High

• Confidence of workshop participants: High 

Supporting literature

Dissolved Oxygen

When dissolved oxygen (DO) concentrations fall to hypoxic levels, there are severe 

consequences for benthic communities, as the oxygen depleted water mass suffocates everything 

that cannot move out of the area, including sea urchins (Largier et al. 2010). Areas adjacent to 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Red Abalone Score Confidence 

Sensitivity 3 Moderate 3 High

Exposure 2 Low-Moderate 2 Moderate

Adaptive Capacity 3 Moderate 3 High

Vulnerability 3 Moderate 2 Moderate

246
upwelling centers like Point Arena are particularly susceptible to low DO levels as the upwelling 

process naturally delivers low oxygen water onto the continental shelf from the deep ocean 

(Largier et al. 2010). High mortality of benthic invertebrates has been attributed to severe 

hypoxic events due to the shoaling of the oxygen minimum zone (Grantham et al. 2004, Chan et 

al. 2008). Further, reduced dissolved oxygen has been experimentally shown to reduce 

fertilization rates in an Australian species of urchin (Riveros et al. 1996). 

pH 

Ocean acidification is expected to negatively impact the production of calcium carbonate 

structures in many adult invertebrate species, including sea urchins (Guinotte and Fabry 2008), 

and has been demonstrated to negatively impact the larval stages of many calcium-building 

species (Largier et al. 2010), including reduced fertilization and delayed development in sea 

urchins (Kurihara et al. 2004, Yu et al. 2011). Decreased pH also decreases the production of 

heat shock proteins in the red sea urchin, impairing the animal’s ability to respond to thermal 

stress (O’Donnell et al. 2008) and has been shown to impair cellular stress-response mechanisms 

that enable urchins to tolerate other environmental stressors (Evans and Hofmann 2012). A 

study of green sea urchin larvae indicated high plasticity in response to decreased pH (though 

increased mortality and decreased growth were still consequences of this decrease), with a 

physiological tipping point of 7.0 (Dorey et al. 2013). 

Currents/mixing/stratification 

Sea urchins spend the first part of their lives as free-floating plankton, which facilitates dispersal, 

feeding, and predator avoidance. Change in the timing or magnitude of seasonal currents and/or 

upwelling could reduce sea urchin larval survival (Largier et al. 2010) and impact larval 

dispersal (Vulnerability Assessment Workshop, pers. comm., 2014). 

Temperature

A study on thermal tolerance in the purple sea urchin indicates that individuals from Pacific 

Grove, CA (just south of the study region) tolerate temperatures ranging from 5-23 ̊C (with an 

average annual range of 9-17 ̊C); however, exposure to cooler temperatures led to respiratory 

and behavioral acclimation, whereas exposure to warmer temperatures (20 ̊C) did not, and 

exposure to 25 ̊C was invariably lethal (Farmanfarmaian and Giese 1963). The southern range 

limit of the species is potentially controlled by this sensitive thermal tolerance of adults (Ebert 

2010). Conversely, a range of temperatures (10-32 ̊C) had no impact on the survival of multiple 

larval stages or the expression of the stress-induced gene hsp70 in the purple urchin (Hammond 

and Hofmann 2010). 

II. Sensitivities to disturbance regimes

Disturbance regimes identified: disease and storms

Overall species sensitivity to disturbance regimes: Moderate-High

• Confidence of workshop participants: High 

Additional participant comments

Storms increase turbulence that exacerbates dislodgement of both sea urchins and the kelp that 

urchins often use as habitat and food. 

247
Supporting literature

Storms

Increasingly intense run-off during extreme storm events may cause increased sedimentation that 

may negatively impact sea urchins due to sand scour, and increased freshwater input to the 

nearshore subtidal that may lead to higher re-suspension of sediment resulting in increased 

turbidity and light attenuation (Largier et al. 2010). 

Disease

Disease is projected to increase with warming water temperatures due to enhanced pathogen 

development and survival as well as host susceptibility (Harvell et al. 2002), and increases in 

disease have been documented in Strongylocentrotus spp. in both the North Atlantic (pathogen 

unknown, >50% mortality) and Norway (pathogen unknown, 90% mortality) (Harvell et al. 

1999). Fourteen bacterial strains have been detected in purple urchins collected in Monterey, 

CA, only 2 of which were able to initiate lesions (Gilles and Pearse 1986), and multiple localized 

mass mortalities of the red sea urchin have occurred in the study region, resulting in loss of 

spines and epidermis, lesions, and death (Pearse et al. 1977). 

III. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): pollution and poisons (5, moderate), 

harvest (3, moderate) 

Overall species sensitivity to non-climate stressors: Moderate-High

• Confidence of workshop participants: Moderate 

Overall species exposure to non-climate stressors: Moderate

• Confidence of workshop participants: Moderate 

Supporting literature

Pollution and poisons 

Sea urchins can serve as indicators of poor water quality, as they are often one of the first 

organisms to show stress in polluted water, including lack of movement and drooping spines 

(MBA 2014). Exposure to oil has been documented to lead to defective embryogenesis and high 

larval mortality in a related species of urchin (Vashchenko 1980) and common chemicals found 

in anti-fouling paints have been shown to be toxic to urchin larvae in China (Kobayashi and 

Okamura 2002). 

Harvest

The red sea urchin has a significant commercial fishery, and is fished throughout its range for the 

collection of gonads for the sushi trade. Commercial catch peaked in the late 1980s, and the 

catch per unit effort has been dropping since inception of the fishery in the 1970s (Andrew et al. 

2002). Purple urchins have been harvested in California, but on a very limited basis (CDFG 

2003). The market for the purple urchin is highly variable and much more specialized. 

Management measures are currently in place to protect the stock of red sea urchins, including 

restricted access and season, and a minimum size that allows for multiple years of spawning, 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

248
though the species is considered to be over-harvested and additional management options have 

been considered (Dewees et al. 2003).

IV. Dependencies

Species dependence on one or more sensitive habitat types: High

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: rocky reef, rocky intertidal areas, and kelp 

forests

Species dependence on specific prey or forage species: Low, the species feeds on a variety of 

macroalgae

• Confidence of workshop participants: High 

Other critical dependencies: none identified 

Specialization of species (1=generalist; 5=specialist): 2

• Confidence of workshop participants: High 

V. Other sensitivities

Other critical factors likely to influence the sensitivity of the species: trophic relationship with 

predators 

• Degree to which these factors impact the sensitivity of the species to climate change: 

Moderate-High

• Confidence of workshop participants: Moderate

Adaptive Capacity

I. Extent, Status, and Dispersal Ability

Geographic extent of the species (1=endemic; 5=transboundary): 5

• Confidence of workshop participants: High 

Population status of the species (1=endangered; 5=robust): 4

• Confidence of workshop participants: Low

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 5

• Confidence of workshop participants: Moderate 

Dispersal ability of the species: High 

• Confidence of workshop participants: High 

Maximum annual dispersal distance: >100km 

• Confidence of workshop participants: High 

Additional participant comments

The adaptive capacity of these species will likely vary greatly between intertidal and subtidal 

populations. The two species have long-lived pelagic larvae that enable high dispersal, with 

maximum larval dispersal considered to be greater than 100 km. 

249
II. Intraspecific/Life history diversity

Diversity of life history strategies: Low

• Confidence of workshop participants: High 

Genetic diversity: High

• Confidence of workshop participants: Moderate 

Behavioral plasticity: Low-Moderate

• Confidence of workshop participants: High 

Phenotypic plasticity: Low 

• Confidence of workshop participants: High 

Overall degree of diversity/plasticity of the species: Low-Moderate 

• Confidence of workshop participants: High 

Additional participant comments

Sea urchins are broadcast spawners with external fertilization, producing many gametes in 

successive cycles and reproducing 3 times per year. Both species take around two years to reach 

sexual maturity. 

Supporting literature

Despite having long-lived planktonic larvae, which should contribute to genetic homogenization, 

genetic studies indicate significant population subdivision in both sea urchin species, with high 

genetic differentiation over relatively short geographic distances (Edmands et al. 1996, Moberg 

and Burton 2000). A few examples of behavioral plasticity exist in the literature. The red urchin 

has been documented to alter its morphology based on current flow by flattening its spines to 

become more streamlined in response to high current velocity, presumably contributing to better 

attachment and preventing dislodgement (Stewart and Britton-Simmons 2011). There is some

indication that the timing of spawning coincides with annual peak in phytoplankton bloom not by 

accident, but that spawning may be induced by a chemical released by phytoplankton 

(Himmelman 1975). Studies both north and south of the study region indicate that the majority 

of spawning occurs between December and March (Holland and Giese 1965, Gonor 1973). 

III. Management potential

Value of species to people: Moderate-High

• Confidence of workshop participants: High 

• Description of value: culinary value, value to tourism, prey for sea otters and as a viable 

fishery

Likelihood of managing or alleviating climate change impacts on species: Low

• Confidence of workshop participants: Moderate 

• Description of potential management options: no answer provided 

Supporting literature

A policy of protecting urchins in shallow-water refugia would offer an effective management 

strategy by enhancing recruitment (shallow-water individuals have larger gonads and larger 

spawning events) and by sheltering juveniles (Rogers-Bennett et al. 1995). 

250
IV. Other Adaptive Capacity Factors

Critical factors not addressed that may affect species’ adaptive capacity: population bottlenecks 

during larval settlement, and climate change impacts specific to the larval stage’s ability to 

recruit and survive 

• Degree to which these factors affect the habitat’s adaptive capacity: Moderate-High

• Confidence of workshop participants: Low

Exposure 

I. Future climate exposure6 Future climate and climate-driven changes identified (score7

, confidence8): decreased pH (4, 

moderate), decreased dissolved oxygen (DO) levels (4, moderate), increased storminess (2, low), 

changes in air temperature (2, high), changes in sea surface temperature (1, moderate), altered 

currents and mixing (1, low) 

Degree of exposure to future climate and climate-driven changes: Low-Moderate

• Confidence of workshop participants: no score provided 

Literature Cited

Andrew, N., Y. Agatsuma, E. Ballesteros, A. Bazhin, E. Creaser, D. Barnes, L. Botsford, A. Bradbury, A. Campbell 

and J. Dixon. 2002. Status and management of world sea urchin fisheries. Oceanography and Marine 

Biology Annual Review 40:343-425.

California Department of Fish and Game (CDFG). 2003. Purple Sea Urchin. In Annual Status of the Fisheries 

Report. 

Chan, F., J. Barth, J. Lubchenco, A. Kirincich, H. Weeks, W. T. Peterson and B. Menge. 2008. Emergence of anoxia 

in the California Current large marine ecosystem. Science 319 (5865):920-920.

Dewees, C. M., J. M. Lawrence and O. Guzman. 2003. Sea urchin fisheries: A California Perspective. In Sea 

Urchins: Fisheries and Ecology, 37. Lancaster, PA: DE Stech Pubs. 

Dorey, N., P. Lançon, M. Thorndyke and S. Dupont. 2013. Assessing physiological tipping point of sea urchin 

larvae exposed to a broad range of pH. Global Change Biology 19 (11):3355-3367.

Ebert, T. A. 2010. Demographic patterns of the purple sea urchin Strongylocentrotus purpuratus along a latitudinal 

gradient, 1985–1987. Marine Ecological Progress Series 406:105-120.

Edmands, S., P. Moberg and R. Burton. 1996. Allozyme and mitochondrial DNA evidence of population 

subdivision in the purple sea urchin Strongylocentrotus purpuratus. Marine Biology 126 (3):443-450.

Evans, T. G. and G. E. Hofmann. 2012. Defining the limits of physiological plasticity: how gene expression can 

assess and predict the consequences of ocean change. Philosophical Transactions of the Royal Society B: 

Biological Sciences 367 (1596):1733-1745.

Farmanfarmaian, A. and Giese, A.C. 1963. Thermal tolerance and acclimation in the western purple sea urchin,

Strongylocentrotus purpuratus. Physiol. Zool. 36: 237-343.

Gilles, K. W. and J. S. Pearse. 1986. Disease in sea urchins Strongylocentrotus purpuratus: Experimental infection 

and bacterial virulence. Diseases of Aquatic Organisms 1 (2):105-114.

Gonor, J. J. 1973. Reproductive cycles in oregon populations of the echlnoid, Strongylocentrotvs purpuratus

(Stimpson). I. Annual gonad growth and ovarian gametogenic cycles. Journal of Experimental Marine 

Biology and Ecology 12 (1):45-64.

6 Supporting literature for future exposure to climate factors is provided in the introduction.

7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants. 

251
Grantham, B. A., F. Chan, K. J. Nielsen, D. S. Fox, J. A. Barth, A. Huyer, J. Lubchenco and B. A. Menge. 2004. 

Upwelling-driven nearshore hypoxia signals ecosystem and oceanographic changes in the northeast Pacific. 

Nature 429 (6993):749-754.

Guinotte, J.M and V.J. Vabry. 2008. Ocean acidification and its potential effects on marine ecosystems. In: Ostfeld, 

R.S., Schlesinger, W.H. (Eds.), The Year in Ecology and Conservation Biology 2008, Annals of the New 

York Academy of Sciences, pp. 320–342.

Hammond, L. M. and G. E. Hofmann. 2010. Thermal tolerance of Strongylocentrotus purpuratus early life history 

stages: mortality, stress-induced gene expression and biogeographic patterns. Marine Biology 157 

(12):2677-2687.

Harvell, C.D., K. Kim, J.M. Burkholder, R.R. Colwell, P.R. Epstein, D.J. Grimes, E.E. Hofmann, E.K. Lipp, 

A.D.M.E. Osterhaus, R.M. Overstreet, J.W. Porter, G.W.D. Smith and G.R. Vasta. 1999. Emerging marine 

diseases – climate links and anthropogenic factors. Science 285:1505-1510.

Harvell, C.D., C.E. Mitchell, J.R. Ward, S. Altizer, A.P. Dobson, R.S. Ostfeld and M.D. Samuel. 2002. Climate 

warming and disease risks for terrestrial and marine biota. Science 296:2158-2162.

Himmelman, J. H. 1975. Phytoplankton as a stimulus for spawning in three marine invertebrates. Journal of 

Experimental Marine Biology and Ecology 20 (2):199-214.

Holland, N. D. and A. C. Giese. 1965. An autoradiographic investigation of the gonads of the purple sea urchin 

(Strongylocentrotus purpuratus). The Biological Bulletin 128 (2):241-258.

Kobayashi, N. and H. Okamura. 2002. Effects of new antifouling compounds on the development of sea urchin. 

Marine Pollution Bulletin 44 (8):748-751.

Kurihara H., S. Kato, and A. Ishimatsu. 2004. Sub-lethal effects of elevated concentration of CO2 on planktonic 

copepods and sea urchins. Journal of Oceanography 60:743-750.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Moberg, P. and R. Burton. 2000. Genetic heterogeneity among adult and recruit red sea urchins, Strongylocentrotus 

franciscanus. Marine Biology 136 (5):773-784.

Monterey Bay Aquarium (MBA). 2014. Purple sea urchin. Accessed June 2014. 

http://www.montereybayaquarium.org/animal-guide/invertebrates/purple-sea-urchin.

O’Donnell, M.J., L.M. Hammond, G.E. Hofmann. 2008. Predicted impact of ocean acidification on a marine 

invertebrate: elevated CO2 alters response to thermal stress in sea urchin larvae. Marine Biology 156:439-

446.

Pearse, J. S., Costa, D. P., Yellin, M. B., Agegian, C. R. 1977. Localized mass mortality of red sea urchin, 

Strongylocentrotus fransiscanus, near Santa Cruz, California. Fisheries Bulletin 75: 645-648.

Riveros, A., M. Zuniga, A. Larrain and J. Becerra. 1996. Relationships between fertilization of the Southeastern 

Pacific sea urchin Arbacia spatuligera and environmental variables in polluted coastal waters. Marine 

Ecology Progress Series 134 (1):159-169.

Rogers-Bennett, L., W. A. Bennett, H. C. Fastenau and C. M. Dewees. 1995. Spatial variation in red sea urchin 

reproduction and morphology: implications for harvest refugia. Ecological Applications 5 (4):1171-1180.

Stewart, H. L. and K. H. Britton-Simmons. 2011. Streamlining behaviour of the red urchin Strongylocentrotus 

franciscanus in response to flow. The Journal of Experimental Biology 214 (16):2655-2659.

Vashchenko, M. 1980. Effects of oil pollution on the development of sex cells in sea urchins. Helgoländer 

Meeresuntersuchungen 33 (1-4):297-300.

Yu, P. C., P. G. Matson, T. R. Marz and G. E. Hofmann. 2011. The ocean acidification seascape and its relationship 

to the performance of calcifying marine invertebrates: Laboratory experiments on the development of 

urchin larvae framed by environmentally-relevant pCO2/pH. Journal of Experimental Marine Biology and 

Ecology 400 (1-2):288-295.

252
Sea Palm (Postelsia palmaeformis)

1

Executive Summary Sea palm is a rocky intertidal kelp 

found along the coast from Vancouver 

Island, British Columbia to San Luis 

Obispo County, California, restricted to 

mid-high tidal ranges in areas with high 

wave action. Sea palm exhibits a broad 

geographic extent, a robust population that is somewhat fragmented, and a low dispersal 

capability. Key climate sensitivities identified by workshop participants include air temperature, 

salinity, wave action, pH and coastal erosion, and key non-climate sensitivities include harvest. 

This alga has moderate-high diversity in life history (with microscopic and macroscopic stages 

and variable reproduction timing), low behavioral plasticity, and moderate phenotypic plasticity 

due to its ability to respond morphologically and reproductively to environmental changes. The 

societal value for sea palm was rated as low-moderate, though commercial harvest of the species 

is increasing, and management potential was rated as low-moderate, though there is great 

opportunity in providing further protection for the species through management and regulation of 

commercial harvest.

Sensitivity 

I. Sensitivity to climate and climate driven changes

Climate and climate-driven changes identified (score2, confidence3): air temperature (5, high), 

salinity (5, moderate), wave action (5, high), ocean pH (4, low- moderate), coastal erosion (4, 

low- moderate), sea surface temperature (3, low- moderate), sea level rise (3, moderate -high), 

dynamic ocean conditions (currents/mixing/stratification) (3, low), precipitation (2, low), 

dissolved oxygen (DO) levels (2, low- moderate) 

Climate and climate-driven changes that may benefit the species: wave action

Description of benefit: Increased wave action could potentially dislodge space competitors from 

rock habitat, leaving more available space for sea palms which are adapted to high wave stress.

Overall species sensitivity to climate and climate-driven factors: Moderate

• Confidence of workshop participants: Moderate

Additional participant comments

This species was identified as having moderate-high indirect sensitivity to pH, due to the 

negative impact that decreased pH is expected to have on the California mussel, a competitor for 

space, and on coralline algae, an important habitat for sea palm zoospores. Though sea palm was 

identified as being only moderately sensitive to water temperature, recent work by Dr. Michael 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Sea Palm Score Confidence 

Sensitivity 4 Moderate-High 3 High

Exposure 4 Moderate-High 2 Moderate

Adaptive Capacity 3 Moderate 3 High

Vulnerability 4 Moderate-High 3 High

253
Graham of Moss Landing Marine Laboratories has shown that zoospores are not able to grow 

into mature sporophytes in 18 ̊C temperature water (Arley Muth, pers. comm., 2014). 

Supporting literature

Literature review was conducted for those factors scoring 4 or higher (with the exception of pH, 

for which no information is available aside from participant comments above), although the other 

sensitivities identified should also be considered. 

Air temperature

Increased air temperature may indirectly negatively impact sea palm by exacerbating the 

physiological stress associated with emersion at low tide and at times of low wave action. 

Desiccation, or drying out, of algal tissue during emersion results in reduced photosynthetic 

efficiency, bleaching and sloughing off of algal tissue, and eventual mortality (Nielsen et al. 

2006). Generally, sea palm adults are not exposed long enough to desiccating conditions to cause 

adverse effects, but this is reliant on constant wave splash and can be exacerbated by high 

temperatures (Vulnerability Assessment Workshop, pers. comm., 2014). The microscopic stages 

of sea palm are likely more sensitive to increased air temperature due to the enhanced risk of 

drying out when exposed on bare rock (Hutto 2011). 

Salinity

The impact of salinity on kelp species has received little attention (Dayton 1985), though adverse 

effects of diluted salinity have been documented on two species of laminarian algae 

(Norton and South 1969) and on the germination of the Arctic kelp Alaria esculenta

(Fredersdorf et al. 2009). Hurd (1919) demonstrated that bull kelp sporophytes develop blisters 

and wilt when subjected to rapid reductions in environmental salinity. Alternatively, healthy kelp 

forests have been observed growing in freshwater lenses in the Pacific Northwest (Dayton 

1985). 

Wave action

The relationship this species has with wave action is not straight-forward, and the species may 

actually benefit from an increase in wave force due to the removal of competitors for space 

(primarily the California mussel), though likely only up to a certain velocity (Vulnerability 

Assessment Workshop, pers.comm., 2014). Recent work that attempted to replicate the 

damaging effect of enhanced wave force by removing various numbers of fronds from mature 

adult sea palms demonstrated a temporary reduction in reproductive output followed by a fairly 

quick recovery, indicating no long-term effect of frond removal (Graham, unpublished data). 

However, studies investigating the impact of harvesting the fronds from adults demonstrated a 

significant reduction in recruitment and population size (Thompson et al. 2010). Overall, the 

species is highly adapted to extreme wave action due to its morphology and tissue characteristics 

(Holbrook 1991) and transplant studies have shown that the adults will not survive a low-energy 

environment due to enhanced desiccation (Nielsen et al. 2006), indicating that the sea palm will 

likely benefit from increased wave action.

Coastal erosion

Sea palm may be sensitive to the effects of coastal erosion through the direct burying of intertidal 

habitat (Vulnerability Assessment Workshop, pers. comm., 2014) and the inability to migrate 

inland in response to rising sea levels due to the loss and burying of potential habitat further 

landward (Largier et al. 2010). 

254
II. Sensitivity to disturbance regimes

Disturbance regimes identified: wind, disease, storms, flooding, and extreme heat events 

Overall species sensitivity to disturbance regimes: High

• Confidence of workshop participants: Moderate

Additional participant comments

Though there are no documented diseases that directly impact sea palm, the ecological dynamics 

of the rocky intertidal may be greatly altered by disease, including the sea star wasting syndrome 

that could effectively eliminate the major predator of the California mussel, sea palm’s greatest 

competitor for space.

Supporting literature

Wind and extreme heat events

Wind and heat events often work together to exacerbate the negative effects of desiccation on sea 

palm microscopic stages (Hutto 2011) and on the bleaching and mortality of adult individuals 

(Nielsen et al. 2006). 

Storms

Increased storm intensity and frequency will bring enhanced wave intensity to the rocky 

intertidal habitat, impacting the ecological dynamics of intertidal organisms, including the sea 

palm (see wave action section above). 

Flooding 

Flooding from sea level rise and increased storm activity will submerge sea palm which has been 

shown to cause declines in growth and reproductive output, likely due to lower average light 

levels (Nielsen et al. 2006). 

III. Dependencies 

Species dependence on one or more sensitive habitat types: Moderate

• Confidence of workshop participants: Moderate 

• Sensitive habitats: available substrate in the highly exposed, mid-high rocky intertidal 

zone, including bare rock, turf algae, and mussel beds 

Species dependence on specific prey or forage species: Low

• Confidence of workshop participants: High 

Other critical dependencies: wave disturbance

• Degree of dependence: High

• Confidence of workshop participants: High 

Specialization of species (1=generalist; 5=specialist): 5

• Confidence of workshop participants: High 

Supporting literature

There is some indication that the most suitable substrate type for settlement and growth of the 

microscopic stages varies by environmental stressor, with bare rock being most suitable in areas 

of high wave action, and algal turfs being most suitable in areas exposed to high heat and 

255
desiccation events (Hutto 2011). Wave disturbance was identified as a critical dependency for 

the species due to its role in the removal of competitors (specifically, the California mussel) for 

space in the highly crowded intertidal environment (Dayton 1973, Paine 1988). 

IV. Sensitivity and exposure to non-climate stressors Non-climate stressors identified (score4

, confidence5): harvest (5, high) 

Overall species sensitivity to non-climate stressors: High

• Confidence of workshop participants: High

Overall current exposure to non-climate stressors: Low-moderate

• Confidence of workshop participants: Low

Supporting literature

Harvest

It is unknown how much harvest of sea palm occurs throughout the region, though commercial 

harvest of this species is reportedly increasing in California due to a growing market for edible 

seaweeds and is unregulated and unmanaged at this time (Thompson et al. 2010). Sea palm 

contributes 45% of commercial seaweed harvest, and is vulnerable to overexploitation due to the 

species’ limited dispersal, the location of its reproductive material on the harvested fronds, and 

small, localized populations that are at risk of extinction if spore production is limited 

(Thompson et al. 2010). Thompson et al. (2010) found highly variable responses to harvest of 

sea palm fronds based on the time of year of harvest, though harvest in general resulted in a 38% 

reduction in recruitment and a reduction of population size by 40-50%. The authors suggest that 

management action be taken to protect this species from overexploitation. 

V. Other sensitivities: none identified 

Adaptive Capacity

I. Extent, Status, and Dispersal Ability

Geographic extent of the species (1=endemic; 5=transboundary): 5

• Confidence of workshop participants: High

Population status of the species (1=endangered; 5=robust): 5

• Confidence of workshop participants: High

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 2

• Confidence of workshop participants: High

Dispersal ability of the species: Low-Moderate

• Confidence of workshop participants: High

Maximum annual dispersal distance: >100km

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

256
• Confidence of workshop participants: High

Supporting literature

This species exhibits a transcontinental geographic extent along much of the west coast of North 

America from British Columbia to Central California (Abbott and Hollenberg 1976). Population 

persistence of the sea palm is limited by the low dispersal capabilities of the microscopic spores 

(Dayton 1973, Paine 1988), with most dispersal occurring over distances of 1-5 meters (Coyer et 

al. 1997), though fertile adults that are removed from the substrate by wave action may be able to 

travel great distances and colonize new areas. Populations, therefore, do not easily colonize new 

areas, are vulnerable to local extinction, and must rely on the persistence of established patches 

from year to year (Dayton 1973).

II. Intraspecific/Life History Diversity

Diversity of life history strategies: Moderate-High

• Confidence of workshop participants: High

Genetic diversity: unknown 

Behavioral plasticity: Low

• Confidence of workshop participants: Moderate

Phenotypic plasticity: Moderate

• Confidence of workshop participants: High

Overall degree of diversity/plasticity of the species: Moderate-High

• Confidence of workshop participants: High

Additional participant comments

Due to the nature of its biphasic life history, the sea palm has some flexibility in responding to 

environmental conditions and can reach reproductive age at various times based on 

environmental cues. Once grown, adults can form short and stout morphologies in response to 

heavy wave action, or grow tall and spindly when in a dense bed of other adults. Sea palms 

produce many offspring and have a shorter generation time, with spore release occurring just 

once during its annual life cycle, triggered by environmental cues. 

Supporting literature

Sudden growth and recruitment of the settled microscopic spores has been observed immediately 

following manual and natural removal of mussels (Dayton 1973, Blanchette 1998), suggesting 

that these stages may be able to “hunker down” under mussels and other algae until appropriate 

environmental conditions trigger sudden growth (Hutto 2011). Genetic analyses indicate 

inbreeding in the species (Kusumo et al. 2006) and genetic bottlenecks due to boom-bust cycles 

in natural abundance (Whitmer 2002). However, due to the plasticity in both morphology and 

stages/timing of life history, the species may exhibit greater adaptive capacity in response to 

climate impacts.

257
III. Management Potential

Value of species to people: Low-Moderate

• Confidence of workshop participants: Moderate

• Description of value: Low value attributed to its limited harvest, and moderate value 

attributed to its value to the research and management community as a protected species 

and the state alga.

Likelihood of managing or alleviating climate change impacts on species: Low-Moderate

• Confidence of workshop participants: Low

• Description of potential management options: The most likely way to manage or 

alleviate climate change impacts would be manage harvest levels, which are already very 

low, or to restore/recolonize areas after extreme storm events.

Supporting literature

There is currently little to no regulation of commercial harvest of sea palm, and as harvest 

increases rapidly in California, management recommendations include: (1) mandating the frond 

trimming method, (2) limiting collection to once a year, and (3) closing the commercial season 

before the onset of reproduction (Thompson et al. 2010). 

IV. Other adaptive capacity factors: none identified 

Exposure 

I. Future climate exposure6 Future climate and climate-driven changes identified (score7

, confidence8): changes in air 

temperature (5, high), changes in sea surface temperature (5, moderate -high), changes in 

precipitation (5, high), changes in salinity (5, moderate), decreased pH (5, high), sea level rise (5, 

high), increased flooding (3, moderate), altered currents and mixing (4, low- moderate), 

increased storminess (3, moderate), decreased dissolved oxygen (DO) levels (2, low), increased 

coastal erosion and runoff (2, moderate) 

Degree of exposure to future climate and climate-driven changes: Moderate-High

• Confidence of workshop participants: Moderate 

Literature Cited

Abbott, I.A. and G.J. Hollenberg. 1976. Marine algae of California. Stanford, California: Stanford University Press.

Blanchette, C.A. 1998. Seasonal patterns of disturbance influence recruitment of the sea palm, Postelsia 

palmaeformis. Journal of Experimental Marine Biology and Ecology 197: 1-14. 

Coyer, J.A., J.L. Olsen, W.T. Stam. 1997. Genetic variability and spatial separation in the sea palm Postelsia 

palmaeformis (Phaeophyceae) as assessed with M13 fingerprints and RAPDs. Journal of Phycology 

33:561-8.

6 Supporting literature for future exposure to climate factors is provided in the introduction. 7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

258
Dayton, P.K. 1973. Dispersion, dispersal, and persistence of the annual intertidal alga, Postelsia palmaeformis 

Ruprecht. Ecology 54: 433-438. 

Dayton, P.K. 1985. Ecology of Kelp Communities. Annual Review of Ecological Systematics 16:215-45.

Fredersdorf, J., R. Muller, S. Becker, C. Wiencke and K. Bischof. 2009. Interactive effects of radiation, temperature 

and salinity on different life history stages of the Arctic kelp Alaria esculenta (Phaeophyceae). Oecologia

160 (3): 483-92.

Holbrook, N.M., M.W. Denny, M.A.R. Koehl. 1991. Intertidal “trees”: consequences of aggregation on the 

mechanical and photosynthetic properties of sea palms Postelsia palmaeformis Ruprecht. Journal of 

Experimental Marine Biology and Ecology 146:39-67. 

Hurd, A.M. 1919. The Relation between the Osmotic Pressure of Nereocystis and the Salinity of the Water. In: 

Volume 2 of University of Washington Publications. Puget Sound Biological Station. Pp. 188-199.

Hutto, S.V. 2011. Differential recruitment of Postelsia palmaeformis across substrate types and potential 

facilitative effects of turfing algae. MS Thesis, Moss Landing Marine Laboratories.

Kusumo, H.T., C.A. Pfister, J.T. Wootton. 2006. Small-scale genetic structure in the sea palm Postelsia 

palmaeformis Ruprecht (Phaeophyceae). Marine Biology 149:731–742.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Nielsen, K.J., C.A. Blanchette, B.A. Menge and J. Lubchenco. 2006. Physiological snapshots reflect ecological 

performance of the sea palm, Postelsia palmaeformis (Phaeophyceae) across intertidal elevation and 

exposure gradients. Journal of Phycology 42: 548-559.

Norton, T.A. and G.R. South. 1969. Influence of reduced salinity on the distribution of two laminarian algae. Oikos 

20:320-26.

Paine, R.T. 1988. Habitat suitability and local population persistence of the sea palm Postelsia palmaeformis. 

Ecology 69:1787-1794.

Sauvageau, C. 1915. Sur la sexualité heterogamique d’une Laminaire (Saccorhiza bulbosa). Comptes Rendus de 

l’Académie des Sciences Paris 161:796–799.

Schiel, D.R. and M.S. Foster. 2006. The population biology of large brown seaweeds: ecological consequences of 

multiphase life histories in dynamic coastal environments. Annual Review of Ecology, Evolution and 

Systematics 37:343-72. 

Thompson, S.A., H. Knoll, C.A. Blanchette, K.J. Nielsen. 2010. Population consequence of biomass loss due to 

commercial collection of the wild seaweed Postelsia palmaeformis. Marine Ecology Progress Series 

413:17-31.

Whitmer, A.C. 2002. Population dynamics and genetics of the intertidal kelp Postelsia palmaeformis. PhD 

dissertation, University of Washington, Seattle, WA

259
Southern Sea Otter (Enhydra lutris nereis)1

Executive Summary The southern sea otter inhabits 

nearshore marine habitats, including 

kelp forests, bays, estuaries, and the 

exposed outer coast of central 

California, from Half Moon Bay to 

Point Conception, with a small 

population at the Channel Islands in Southern California. Key climate sensitivities identified by 

workshop participants include changes in precipitation, decreased pH and wave action and key 

non-climate sensitivities include pollution and poisons. The southern sea otter is a threatened 

subspecies, whose population exhibits a limited geographic extent within the state of California 

and is isolated and fragmented. The species exhibits low dispersal, with females rarely traveling 

more than 20 miles from their home range. Recovery of the subspecies from its lowest level of 

just 50 individuals has been very slow and tenuous. The southern sea otter has low genetic 

diversity due to population bottleneck resulting from overharvesting by the fur trade and lowmoderate phenotypic plasticity, but moderate-high behavioral plasticity. Some examples of 

diversity/plasticity in the species includes prey specialization dependent upon prey richness, and 

plasticity in the age of first reproduction dependent upon carrying capacity of the population. 

The societal value for the sea otter was rated as high due to its value as a charismatic megafauna 

species that often serves as an icon of coastal California, but the likelihood of managing or 

alleviating climate impacts was considered low-moderate. 

Sensitivity 

I. Sensitivity to climate and climate driven changes 

Climate and climate-driven changes identified (score2, confidence3): precipitation (4, moderate), 

pH (4, high), wave action (3, moderate), dynamic ocean conditions 

(currents/mixing/stratification) (2, moderate), coastal erosion (2, moderate), dissolved oxygen 

(DO) levels (2, moderate), salinity (1, low), sea surface temperature4

 (1, high) 

Climate and climate-driven changes that may benefit the species: sea surface temperature

• Description of benefit: Increased sea surface temperatures may expand the range of 

suitable habitat for the sea otter, though this is not supported by the literature. 

Overall species sensitivity to climate and climate-driven factors: Low-Moderate

• Confidence of workshop participants: Moderate 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

4 Reviewer noted that sea surface temperature is documented to have a strong negative effect on kelp forest habitat.

Southern Sea Otter Score Confidence 

Sensitivity 2 Low-Moderate 3 High

Exposure 4 Moderate-High 2 Moderate

Adaptive Capacity 2 Low-Moderate 2 Moderate

Vulnerability 3 Moderate 2 Moderate

260
Supporting literature

Literature review was conducted for those factors scoring 3 or higher, although the other 

sensitivities identified should also be considered. 

Precipitation

As extreme precipitation events are expected to increase with climate change, an enhanced 

potential for coastal erosion and run-off can also be expected (PWA 2009). Land-based run-off 

has been implicated as a source of the parasite Toxoplasma gondii, one of the more significant 

infectious diseases that impact sea otter health. Otters sampled near areas of maximal freshwater 

runoff were 3 times more likely to test positive to the parasite than otters in areas of low flow 

(Miller et al. 2002), with proximity to urban areas a key factor in exposure (Steve Lonhart, pers. 

comm., 2014). Enhanced coastal run-off was also associated with the increased likelihood of 

infection from multiple other bacterial pathogens (Miller et al. 2010). 

pH 

The expected acidification of coastal waters, especially in upwelling centers, may have a longterm cascading effect on sea otters by altering the health, size and abundance of its prey, which 

are calcifying invertebrates (Center for Biological Diversity 2014). In this region, where prey 

limitation is already a challenge (Tinker et al. 2008), a further reduction in the availability and 

abundance of prey, as well as the size of each individual prey item, may directly impact the 

energetics of sea otters, as they may have to expend more energy in finding additional prey items 

to meet their energy demands. Alternatively, otters may need to expend less energy in 

processing their calcified prey due to weakened shells, which may result in a benefit from 

reduced pH (Steve Lonhart, pers. comm., 2014). 

Wave Action

Enhanced wave action will likely impact the habitats that the sea otter relies on, including the 

kelp forest and nearshore habitats by impacting sediment redistribution and enhancing sand 

scour, forcing the movement of nearshore kelp forests into deeper water (Graham 1997) and 

creating greater intra-annual variability in kelp productivity and abundance (Graham et al. 1997). 

Wave action may potentially affect the availability and ease of extraction of sea otter prey, 

though there is no information available in the literature (Steve Lonhart, pers. comm., 2014), and 

may affect pup survival since females often leave pups in kelp beds while they forage (Sarah 

Allen, pers. comm. 2014). 

II. Sensitivity to changes in disturbance regimes

Disturbance regimes identified: disease, storms, and wind 

Overall species sensitivity to disturbance regimes: disease (5), storms (3), wind (2) 

• Confidence of workshop participants: disease (high), storms (moderate), wind (low) 

Supporting literature

Literature review was conducted for those factors scoring higher than 3, although the other 

sensitivities identified should also be considered. 

261
Disease

Disease is projected to increase with warming water temperatures, due to enhanced pathogen 

development and survival, as well as host susceptibility (Harvell et al. 2002). From 1998 to 

2003, disease was the leading cause of death in sea otters, accounting for 50% of the mortality 

when identified (SIMoN 2014). In a 2013 study of sea otter mortality, disease accounted for 

only 14% of full necropsies, though underlying disease is cited as being a potential cause for 

greater vulnerability to other causes of death, including shark bite, boat strike, and lesions 

(Miller et al. 2014). The most significant diseases affecting the sea otter include protozoal 

infections (Toxoplasma gondii and Sarcocystis neurona) that enter their habitat through 

freshwater output and whose eggs are found in cat feces (Miller et al. 2002). Other issues 

include infection by thorny headed worms, cardiomyopathy (a set of heart conditions with 

multiple causes), a variety of bacterial infections, and domoic acid poisoning from harmful algal 

blooms (SIMoN 2014). 

III. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score5, confidence6): pollution and poisons (5, high), predation 

(2, low), harvest of prey (2, low) 

Overall species sensitivity to non-climate stressors: Moderate-High

• Confidence of workshop participants: Low

Overall current exposure to non-climate stressors: Low-Moderate7

• Confidence of workshop participants: Moderate 

Supporting literature

Literature review was conducted for those factors scoring 3 or higher, although the other 

sensitivities identified should also be considered. Additional non-climate stressors identified that 

may be important to consider include harmful algal blooms which result in shellfish poisoning 

(Miller et al. 2010) and human fisheries interactions (Sarah Allen, pers. comm., 2014). 

Pollution and Poisons 

As a result of run-off, sea otters are highly exposed to a number of pollutants. Residues of the 

pesticide DDT and the organic pollutant PCB are found in sea otter tissues at concentrations high 

enough to kill other species in the same family, and those that died of infectious diseases had 

higher concentrations of tributyltin (a chemical in anti-fouling paint used on boat hulls), though 

this association does not prove a causal link (SIMoN 2014). Oil spills are also a significant 

danger to sea otters and one large spill in central California could decimate the entire southern 

subspecies (SIMoN 2014). Exposure can result in hypothermia by reducing the insulting 

qualities of the otter’s fur and can result in toxic levels of ingestion as otters constantly groom 

their fur in an attempt to remove oil (SIMoN 2014). One estimate reports the probability of 

death to be 50% for an otter that comes into contact with oil from a spill (USFWS 2003). 

Inhalation of aersols is also a significant toxin and causes mortality as occurred during the Exxon 

Valdez (Sarah Allen, pers. comm., 2014). 

5 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

6 Confidence level indicated by workshop participants. 7 Reviewer notes that exposure to pollution and poisons is very localized, and likely moderate to high.

262
IV. Dependencies

Species dependence on one or more sensitive habitat types: 

• Confidence of workshop participants: kelp (high), estuaries (moderate), nearshore (high) 

• Sensitive habitats species is dependent upon: kelp forests (4), estuaries/coastal lagoons

(2), and nearshore habitat (5)

Species dependence on specific prey or forage species: Low, feeds on a variety of benthic 

invertebrates

• Confidence of workshop participants: High 

Other critical dependencies: none identified

Specialization of species (1=generalist; 5=specialist): 28

• Confidence of workshop participants: High

V. Other sensitivities none identified

Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 3

• Confidence of workshop participants: High 

Population status of the species (1=endangered; 5=robust): 1

• Confidence of workshop participants: High 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 2

• Confidence of workshop participants: Moderate 

Dispersal ability of the species: Low-Moderate 

• Confidence of workshop participants: High 

Maximum annual dispersal distance: 1-5km 

• Confidence of workshop participants: High 

Supporting literature

The southern sea otter exhibits a fairly limited geographic extent from Half Moon Bay to Point 

Conception, especially when compared to its historical range which reached almost continuously 

from Baja California around the Pacific to Japan (SIMoN 2014). After rebounding from its 

lowest population level of just 50 individuals in the early 1900s, the threatened subspecies, now 

numbering around 2900 individuals (Hattfield and Tinker 2013), is showing a very sluggish 

recovery, which may be due to multiple factors including disease, predation, pollution (SIMoN 

2014), and human interaction (Sarah Allen, pers. comm., 2014). Movement of individuals varies 

greatly by sex, age, and location, with males traveling the furthest, around 200 miles from the 

8 One reviewer did not agree with this ranking, stating that many sea otter biologists would not consider the species 

to be a generalist. An additional reviewer noted that in general, sea otter diet is diverse, but individuals may be 

highly specialized.

263
peripheries of the range to reach the more female-dense center, whereas females make more 

frequent, short-range trips (rarely more than 20 miles) (SIMoN 2014). 

II. Intraspecific/Life history diversity

Diversity of life history strategies: Low-Moderate 

• Confidence of workshop participants: Low

Genetic diversity: Low

• Confidence of workshop participants: High 

Behavioral plasticity: Moderate-High

• Confidence of workshop participants: Moderate 

Phenotypic plasticity: Low-Moderate

• Confidence of workshop participants: Moderate 

Overall degree of diversity/plasticity of the species: Low-Moderate

• Confidence of workshop participants: Moderate 

Supporting literature

Due to the population bottleneck that occurred during the fur trade, which resulted in a southern 

subspecies of just 50 individuals, the genetic diversity of the southern sea otter is extremely low 

(Larson et al. 2012), which may make this species more vulnerable to change and lead to 

inbreeding depression. Sea otters show great diversity in behavior, however, that enables them 

to adapt to different environmental variables, including dietary polymorphism in response to a 

food-poor environment (Tinker et al. 2008). Plasticity has been observed as well, which gives 

the species an advantage, including plasticity in the age of first reproduction in the northern sea 

otter in response to the carrying capacity of the population (von Biela et al. 2009). The species is 

relatively long-lived (likely 20 years), which aids in adaptive capacity through behavioral 

changes, as evidenced by their use of tools, one of few mammal species to do so (Sarah Allen, 

pers. comm., 2014). Females take approximately 3 to 5 years to reach reproductive maturity and 

produce only one pup every 16 months with high maternal investment for one year following

(Vulnerability Assessment Workshop, pers. comm., 2014; Sarah Allen, pers. comm., 2014). Pup 

mortality is estimated to be around 45%. Sea otters have a polygamous mating system, and the 

health and survival of females is of greater importance for population recovery than that of males 

(Miller et al. 2014). 

III. Management potential

Value of species to people: High

• Confidence of workshop participants: High

• Description of value: value as a charismatic megafauna species that often serves as an 

icon of coastal California 

Likelihood of managing or alleviating climate change impacts on species: Low-Moderate

• Confidence of workshop participants: Moderate

• Description of possible management actions: no answer provided 

264
IV. Other Adaptive Capacity Factors

Critical factors not addressed that may affect species’ adaptive capacity: impact of predation, 

impacts to key prey, and factors that limit the ability of the species to migrate north and south 

along the coast

• Degree to which these factors affect the habitat’s adaptive capacity: High

• Confidence of workshop participants: Low

Exposure 

I. Future climate exposure9

Future climate and climate-driven changes identified (score10, confidence11): decreased pH (4, 

high), increased coastal erosion and runoff (4, moderate), changes in precipitation (3, moderate), 

increased storminess (3, moderate)12

Degree of exposure to future climate and climate-driven changes: Moderate-High

• Confidence of workshop participants: Moderate 

Additional participant comments

Increased coastal erosion and runoff, as well as changes in precipitation and increased 

storminess, may lead to increased exposure to land-based pollutants. 

Literature Cited

Center for Biological Diversity. 2014. Endangered Oceans - Species Profiles. Accessed June 2014. 

http://www.biologicaldiversity.org/campaigns/endangered_oceans/species_profiles.html.

Graham, M.H. 1997. Factors determining the upper limit of giant kelp, Macrocystis pyrifera, along the Monterey 

Peninsula, central California, USA. Journal of Experimental Marine Biology and Ecology 218:127-149.

Graham, M.H., Harrold, C, Lisin, S, Light, K, Watanabe, J, and M.S. Foster. 1997. Population dynamics of 

Macrocystis pyrifera along a wave exposure gradient. Marine Ecology Progress Series 148:269-279. 

Harvell, C.D., C.E. Mitchell, J.R. Ward, S. Altizer, A.P. Dobson, R.S. Ostfeld and M.D. Samuel. 2002. Climate 

warming and disease risks for terrestrial and marine biota. Science 296:2158-2162. 

Hattfield, B. and T. Tinker. 2013. Spring 2013 California Sea Otter Census Results. USGS Western Ecological 

Research Center.

Larson, S., R. Jameson, M. Etnier, T. Jones and R. Hall. 2012. Genetic diversity and population parameters of sea 

otters, Enhydra lutris, before fur trade extirpation from 1741–1911. PloS One 7 (3):e32205.

Miller, M. A., B. A. Byrne, S. S. Jang, E. M. Dodd, E. Dorfmeier, M. D. Harris, J. Ames, D. Paradies, K. Worcester 

and D. A. Jessup. 2010. Enteric bacterial pathogen detection in southern sea otters (Enhydra lutris nereis) 

is associated with coastal urbanization and freshwater runoff. Veterinary Research 41 (1):1-13.

Miller, M. A., E. Dodd, F. Batac, C. Young, M. D. Harris, J. Kunz and L. Henkel. 2014. Summary of Southern Sea

Otter Mortality Investigations in 2013. Santa Cruz, CA: California Department of Fish and Wildlife, Office 

Spill Prevention and Response.

Miller M.A., I.A. Gardner, C. Kreuder, D.M. Paradies, K.R. Worcester, D.A. Jessup, E. Dodd, M.D. Harris, J.A. 

9 Supporting literature for future exposure to climate factors is provided in the introduction.

10 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

11 Confidence level indicated by workshop participants. 12 Reviewer noted that sea surface temperature should be included as a future climate factor of importance due to its 

negative impact on important biogenic habitat, kelp beds.

265
Ames, A.E. Packham, P.A. Conrad. 2002. Coastal freshwater runoff is a risk factor for Toxoplasma 

gondii infection of southern sea otters (Enhydra lutris nereis). International Journal for Parasitology 

32:997-1006.

Phil William & Associates, Ltd (PWA). 2009. California Coastal Erosion Response to Sea Level Rise – Analysis 

and Mapping. Report to the Pacific Institute funded by the California Ocean Protection Council. 

http://www.pwa-ltd.com/about/news-CoastalErosion/PWA_OPC_Methods_final.pdf. 

Sanctuary Integrated Monitoring Network (SIMoN). 2014. Special Status Species: Southern (California) Sea Otter 

(Enhydra lutris nereis). Accessed June 2014. 

http://www.sanctuarysimon.org/monterey/sections/specialSpecies/sea_otter.php.

Tinker, M. T., G. Bentall and J. A. Estes. 2008. Food limitation leads to behavioral diversification and dietary 

specialization in sea otters. Proceedings of the National Academy of Sciences 105 (2):560-565.

U.S. Fish and Wildlife Service (2003) Final Revised Recovery Plan for the Southern Sea Otter (Enhydra lutris 

nereis). Portland, Oregon.

von Biela, V. R., V. A. Gill, J. L. Bodkin and J. M. Burns. 2009. Phenotypic plasticity in age at first reproduction of 

female northern sea otters (Enhydra lutris kenyoni). Journal of Mammalogy 90 (5):1224-1231.

266
Surface Nesters: Brandt’s Cormorant (Phalacrocorax penicillatus) 

and Common Murre (Uria aalge)

1

Executive Summary Brandt’s cormorants and common 

murres are resident seabirds in the 

study area, and are characterized by 

nesting on open surfaces and diving 

for prey. Key climate sensitivities

identified by workshop participants 

for these species includes extreme 

weather conditions, sea surface 

temperature, and dynamic ocean conditions (currents/mixing/stratification). Key non-climate 

sensitivities include aircraft and vessels, recreation, invasive species, harvest, and pollution and 

poisons. Brandt’s cormorants and common murres occur along the Pacific Coast of North 

America and have almost continuous population connectivity. The study area contains the 

southern-most colonies for these species in the Pacific, and populations are relatively stable 

and/or increasing. Brandt’s cormorants and common murres are highly dependent on undisturbed 

breeding habitat on coastal cliffs, offshore rocks, and islands. Common murres have fairly low 

reproductive potential, reproducing only once per year and having few chicks, whereas Brandt’s 

cormorants have greater reproductive potential than any other local seabird. These species 

exhibit some behavioral foraging diversity (i.e., foraging in different areas and on different 

species). Brandt’s cormorants and common murres likely have a low to low-moderate societal 

value (depending on the segment of society) and a low likelihood for managing or alleviating 

climate impacts. Continuing to mitigate disturbance via aerial, vessel, and public access 

restrictions may reduce cumulative stressors on these species. 

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): extreme weather events (5, 

high), dynamic ocean conditions (currents/mixing/stratification) (3, moderate), sea surface 

temperature (3, moderate), air temperature (2, moderate), salinity (2, low), dissolved oxygen 

(DO) levels (2, low), pH (2, low), coastal erosion (2, moderate), precipitation (1, moderate), sea 

level rise (1, high), wave action (1, moderate) 

Climate and climate-driven changes that may benefit the species: no answer provided 

Overall species sensitivity to climate and climate-driven factors: Low-Moderate

• Confidence of workshop participants: Moderate 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Surface Nesters: 

Brandt’s Cormorant 

and Common Murre

Score Confidence

Sensitivity 4 Moderate-High 3 High

Exposure 3 Moderate 3 High

Adaptive Capacity 3 Moderate 2 Moderate

Vulnerability 3 Moderate 3 High

267
Additional participant comments

Surface nesting species, including the Brandt’s cormorant (Phalacrocorax penicillatus) and the 

common murre (Uria aalge), are mainly sensitive to any changes that affect their marine prey 

species or terrestrial breeding habitat, such as extreme weather conditions, sea surface 

temperatures, and currents/mixing/stratification. 

Supporting literature

Literature review was conducted for those factors scoring 3 or higher, although the other 

sensitivities identified should also be considered. 

Extreme Weather Conditions 

Extreme weather conditions can directly lead to mortality or breeding habitat disturbance of 

Brandt’s cormorants and common murres. For example, storms can increase the potential for 

breeding habitat inundation, especially in low-lying areas (Young et al. 2012). Shifts in largescale climatic forcings, such as the El Niño Southern Oscillation (ENSO), can also affect 

common murres and Brandt’s cormorants by intensifying storm conditions and/or affecting 

marine processes and food webs, leading to partial or complete colony abandonment (Manuwal 

et al. 2002). For example, the 1982-83 El Niño led to high mortality of common murres along the 

central California coast (USFWS 1995) and to population declines in the breeding population of 

Brandt’s cormorants on the Farallon Islands (Audobon Society 2014, Capitolo et al. 2014). 

Sea Surface Temperatures

Warmer sea surface temperatures can cause large thermoclines in the water column, increasing 

stratification, reducing ocean mixing and nutrient delivery to upper ocean photic zones and 

resulting in decreased primary productivity and impacts that echo up the food chain and affect 

foraging seabirds such as the common murre and Brandt’s cormorant (Young et al. 2012, 

Schmidt et al. 2014). For example, warmer sea surface temperatures have been correlated with 

decreased zooplankton abundance (Hill 1995, Roemmich and McGowan 1995), which can 

contribute to declines of key prey species, such as rockfish (Sebastes spp.) (Hill 1995), and affect 

the survival and reproductive success of diving piscivores (Young et al. 2012). Miller and 

Sydeman (2004) found that warmer sea surface temperatures correlated with decreased juvenile 

rockfish abundance in common murre diets. 

Water temperatures are influenced by both long- and short-term climate trends (Young et al. 

2012). For example, El Niño events and warm (positive) phases of the Pacific Decadal 

Oscillation (PDO) are often associated with warmer water temperatures, while La Niñas and cool 

(negative) phases of the PDO are associated with cooler water temperatures and higher 

productivity (Largier et al. 2010, Young et al. 2012). La Niña conditions from 1999-2000 are 

thought to have contributed to large population increases in Brandt’s cormorants in the Gulf of 

the Farallons (Capitolo et al. 2014). 

Dynamic ocean conditions (currents/mixing/stratification) 

Brandt’s cormorants and common murres forage on a variety of prey species delivered by the 

California Coastal Current and different upwelling zones (Briggs et al. 1988, Largier et al. 2010, 

Cornell Lab of Ornithology 2014), and reproduction timing is correlated with high prey 

availability (Manuwal et al. 2002). Changes in currents, wind, upwelling rates and timing, 

stratification, and ocean mixing can alter the delivery timing and availability of prey species, 

268
affecting survival and reproductive success of Brandt’s cormorants and common murres (Young 

et al. 2012). For example, upwelling may counteract rising sea surface temperatures and promote 

primary productivity (Largier et al. 2010), but intense upwelling could shift zooplankton to 

deeper waters (Pringle 2007), potentially decreasing food availability for diving seabirds if 

zooplankton and other forage fish end up below the maximum dive depths for these species 

(Largier et al. 2010). El Niño events can decrease upwelling and mixing, reducing nutrient 

delivery to photic zones and decreasing primary productivity, which can lead to food web 

collapses and negative impacts on seabird fitness and reproduction (Young et al. 2012). 

II. Sensitivities to disturbance regimes

Disturbance regimes identified: disease, storms, flooding, drought, intraspecific disturbance 

Overall species sensitivity to disturbance regimes: High

• Confidence of workshop participants: High 

Additional participant comments

Climate-driven changes in the distributions or behavioral activities of other species within the 

breeding ranges of common murres and Brandt’s cormorants could affect breeding success. 

Supporting literature

As colonial nesters, infectious disease can spread quickly and extensively amongst Brandt’s 

cormorants and common murres (Newman et al. 2004). Storms, especially those during breeding 

season and/or with large wave heights, can inundate breeding habitat and negatively impact 

breeding success (Young et al. 2012). Flooding of low-lying nesting habitat via sea level rise or 

storm surge can also reduce breeding success (Young et al. 2012). Drought may negatively 

impact the availability of native plant nesting material. In 2014, delayed rains meant extremely 

delayed onset of growth of Maritime goldfields (Lasthenia maritime), a key source of nesting 

material for Brandt’s Cormorant (Point Blue, unpublished data). There was enough just in time, 

but an extreme drought with no significant rain may be different.

Common murres and Brandt’s cormorants are sensitive to disturbance from other species, such 

as Western gulls (Larus occidentalis), Brown pelicans (Pelecanus occidentalis), common ravens 

(Corvus corax), and pinnipeds (Thayer et al. 1999, Warzybok et al. 2004, Apex Houston Trustee 

Council 2011). In addition, climate-driven expansion of competitors, such as the Humboldt 

Squid (Dosidicus gigas), could affect food availability and fitness of resident common murre and 

Brandt’s cormorant populations (Young et al. 2012). 

III. Dependencies

Species dependence on one or more sensitive habitat types: High (breeding habitat), Moderate 

(foraging habitat)

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: nearshore and offshore waters, cliffs, and 

rock islands 

Species dependence on specific prey or forage species: Moderate

• Confidence of workshop participants: High 

Other critical dependencies: timing of breeding and foraging availability

269
• Degree of dependence: High

• Confidence of workshop participants: High 

Specialization of species (1=generalist; 5=specialist): 3

• Confidence of workshop participants: High 

Additional participant comments

Common murres typically forage offshore. However, both species sometimes forage in areas 

outside their normal foraging grounds. 

Supporting literature

Brandt’s cormorants and common murres are colonial nesters, often nesting together on open 

surface areas (i.e., cliffs ledges, offshore rocks and islands) that are free of predators and human 

disturbance (Manuwal et al. 2002, Audobon Society 2014). Brandt’s cormorants typically forage 

nearshore, especially in areas with kelp beds (Cornell Lab of Ornithology 2014). Both species

exhibit some feeding diversity; for example, common murres feed on krill, schooling fish, and 

other aquatic prey (Apex Houston Trustee Council 2011), and Brandt’s cormorants feed on fish, 

squid, shrimp, and crabs (Audubon Society 2014, Cornell Lab of Ornithology 2014).

IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): invasive species (5, high), aircraft and 

vessels (5, high), pollution and poisons (5, high), recreation (4, high), harvest (3, high), energy 

production (2, high), land use change (2, high) 

Overall species sensitivity to non-climate stressors: Moderate-High

• Confidence of workshop participants: High 

Overall species exposure to non-climate stressors: Low

• Confidence of workshop participants: High

Additional participant comments

These stressors can make surface nesting species more vulnerable to climate stressors by 

affecting reproductive success and/or degrading habitat quality and food availability. Recreationrelated disturbance includes dogs, jet skis, kayaks, and unmanned aerial vehicles. 

Supporting literature

Literature review was conducted for those factors scoring 3 or higher, although the other 

sensitivities identified should also be considered. 

Invasive Species

Rodents, particularly house mice, were introduced to the Farallon Islands in the 19th century 

(USFWS 2013). Rodents change ecological relationships on islands (e.g., by eating native plants 

and invertebrates and/or by drawing in new predators), which can affect the availability and 

4

 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating 

high sensitivity and 1 indicating low sensitivity.

5

 Confidence level indicated by workshop participants.

270
quality of breeding habitat for surface nesting seabirds and/or increase rates of egg predation 

(USFWS 2013). Mice have apparently little impact on breeding murres and cormorants, but an 

introduction of rats on the Farallones could have disastrous consequences for these species 

(Russell Bradley, Point Blue, pers. comm., 2014). 

Aircraft and Vessels

Disturbance from aircraft and vessels can contribute to nest failure and/or stress Brandt’s 

cormorants and common murres, exacerbating their low reproductive potential. For example, 

disturbance during breeding season can lead to nest failure or colony desertion by Brandt’s 

cormorants (Audbon Society 2014); to prevent these issues, the Farallon Islands has established a 

300 foot special closure to protect seabirds from vessel disturbance during breeding season

(Audobon Society 2014). Aircraft disturbance, particularly helicopters, has also been 

documented to increase the frequency of adult murre flushing, especially when aircraft are flown 

less than 305 m above sea level (Rojek et al. 2007). Boat disturbance also contributed to nest 

failure in several central California common murre colonies, particularly when boats approached 

within 50 m of nesting colonies and remained there for extended periods of time (Rojek et al. 

2007). 

Pollution and Poisons 

Episodic pollution and poison events, such as oil spills, can kill Brandt’s cormorants and 

common murres and/or affect prey availability or habitat quality. For example, the 1986 oil spill 

from the Apex Houston killed approximately 6000 common murres from San Francisco to Big 

Sur (Siskin et al. 1993 cited in USFWS 1995) and led to the abandonment of several onshore 

breeding habitat areas (Takekawa et al. 1990, Swartzman and Carter 1991, Carter et al. 1992 

cited in USFWS 1995). 

Recreation

Similar to disturbance from airplanes or vessels, disturbance related to recreation can cause nest 

failure or colony abandonment, especially during times of low food availability (Young et al. 

2012). 

Harvest

Harvest of prey species can reduce food availability for common murres and Brandt’s 

cormorants. For example, increasing California sea lion (Zalophus californianus) populations 

and industrial fisheries may have reduced the number of young fish available for cormorant 

forage, slowing the recovery of Brandt’s cormorant populations within the study area (Audobon 

Society 2014, Capitolo et al. 2014). Future expansion of the groundfish fisheries could 

exacerbate this trend, warranting further study (Audobon Society 2014).

V. Other sensitivities

Other critical factors likely to influence the sensitivity of the species: El Niño-Southern 

Oscillations (ENSO)

• Degree to which these factors impact the sensitivity of the species to climate change: 

Moderate-High

• Confidence of workshop participants: High 

271
Adaptive Capacity 

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 5

• Confidence of workshop participants: High 

Population status of the species (1=endangered; 5=robust)6: BRCO: 3, COMO: 5 

• Confidence of workshop participants: High 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 4

• Confidence of workshop participants: Moderate 

Dispersal ability of the species: Moderate 

• Confidence of workshop participants: Moderate 

Maximum annual dispersal distance: >100km 

• Confidence of workshop participants: High 

Supporting literature

The study area contains the southern-most colonies for these species in the Pacific, and includes 

colonies that nest on cliffs and offshore rocks and islands (USFWS 1995, Apex Houston Trustee 

Council 2011, Cornell Lab of Ornithology 2014). Common murres are the most abundant 

breeding seabird in Central California (Apex Houston Trustee Council 2011), having rebounded 

from population lows in the late 1980s, with breeding colonies from Point Sur to Point Reyes 

and the largest breeding colony occurring in the Farallon Islands (Apex Houston Trustee Council 

2011). California hosts over 75% of the world’s population of breeding Brandt’s cormorants 

(Audobon Society 2014), and the Farallon Islands breeding colony is one of the largest in the 

world (Capitolo et al. 2014, USFWS 2014). Brandt’s cormorants have a diminished but generally 

stable population within the study region (Capitolo et al. 2014), with major declines in recent 

years at the Farallon Islands (Warzybok et al. 2012), though distributional shifts from islands to 

coastal communities may be occurring (Audobon Society 2014, Capitolo et al. 2014). These 

surface nesters are permanent residents in the study area, but do exhibit local movement. For 

example, Brandt’s cormorants will migrate from the Farallon Islands to the mainland, or wander 

south in winter to forage along the Mexican coastline (Audobon Society 2014, Capitolo et al. 

2014) or north up to British Columbia (Burles et al. 2008). 

II. Intraspecific/Life history diversity

Diversity of life history strategies6: BRCO: Low-Moderate, COMO: Moderate-High

• Confidence of workshop participants: Moderate 

Genetic diversity: Moderate

• Confidence of workshop participants: Low

Behavioral plasticity6: BRCO: Moderate, COMO: Low-Moderate 

• Confidence of workshop participants: Moderate 

Phenotypic plasticity6: BRCO: Moderate, COMO: Low-Moderate 

• Confidence of workshop participants: Moderate

6 BRCO = Brandt’s cormorant, COMO = common murre

272
Overall degree of diversity/plasticity of the species: BRCO: Moderate, COMO: Low-Moderate

• Confidence of workshop participants: Moderate 

Additional participant comments

Brandt’s cormorants have some plasticity in egg clutch size. 

Supporting literature

Brandt’s cormorants will forage in a diversity of habitats (i.e., nearshore, offshore, estuaries) 

(Audobon Society 2014). Brandt’s cormorants nest in large colonies. They have only one 

reproductive event per year, laying 1 to 4 eggs in a constructed nest, and take 2 to 4 years to 

reach reproductive maturity. However, the species can relay after failed breeding attempts, 

resulting in a second chance for reproductive success (Russell Bradley, Point Blue, pers. comm., 

2014). 

Common murres can dive deeper (up to 180 m; Piatt and Nettleship 1985) than some other 

seabirds in order to access prey (Oedekoven et al. 2001), which may increase their resilience to 

changes in currents, upwelling, and prey availability. Common murres have also been 

documented to shift their foraging zones in response to changes in the marine environment and 

prey availability (Oedekoven et al. 2001). However, common murres can carry only one fish at 

time when foraging for nestlings, which could lead to higher energetic costs and consequences if 

foraging distance and time requirements increase due to prey declines (Young et al. 2012). 

Common murres have only one reproductive event per year, but can relay after breeding failure 

and their breeding season lasts from late April to early August during times of peak food 

availability (Manuwal et al. 2002). Common murres breed and nest in large dense colonies. They 

lay one egg per year, and eggs are laid directly on the ground with no nest. After a short on-land 

rearing period, chicks are raised at sea by males (Manuwal et al. 2002). Common murres take 3-

5 years to reach reproductive maturity, and exhibit high fidelity to breeding sites, typically 

breeding at the site where they were born. 

III. Management potential

Value of species to people: Low-Moderate

• Confidence of workshop participants: High 

• Description of value: Low value to the general public, but moderate value to birders and 

nature enthusiasts. 

Likelihood of managing or alleviating climate change impacts on species: Low

• Confidence of workshop participants: High 

• Description of potential management options: no answer provided 

Supporting literature

Common murre populations are still recovering from significant population declines in the 

1980s, and recovery is currently being monitored and managed through the Common Murre 

Restoration Project7

, which includes re-establishment of common murre population at historical 

colony sites (i.e., Devil’s Slide Rock, San Pedro Rock) (USFWS 1995). Establishment of both 

7 http://www.fws.gov/sfbayrefuges/murre/index.htm

273
the Gulf of the Farallones and the Monterey Bay National Marine Sanctuaries helped reduce 

disturbance of murre and cormorant breeding colonies (Capitolo et al. 2014), and continuing to 

mitigate disturbance via aerial, vessel, and public access restrictions may reduce cumulative 

stressors on these species (Audobon Society 2014). 

IV. Other adaptive capacity factors: none identified 

Exposure 

I. Future climate exposure8

Future climate and climate-driven changes identified (score9, confidence10): altered currents and 

mixing (4, moderate), changes in air temperature (3, moderate), changes in sea surface 

temperature (3, moderate), increased storminess (3, moderate), changes in salinity (3, moderate), 

decreased dissolved oxygen (DO) levels (3, moderate), decreased pH (3, moderate), increased 

flooding (2, moderate), increased coastal erosion and runoff (2, moderate), changes in 

precipitation (2, moderate), sea level rise (1, moderate)

Degree of exposure to future climate and climate-driven changes: Moderate

• Confidence of workshop participants: Moderate 

Supporting literature

Climate change will likely have indirect impacts on surface nesting Brandt’s cormorants and 

common murres by affecting prey availability and habitat quality (Largier et al. 2010, Young et 

al. 2012). The nature of how some local seabird species, like Brandt’s Cormorants on the 

Farallones, have responded to changes in climate has itself changed in recent years (Schmidt et 

al. 2014). 

Literature Cited 

Apex Houston Trustee Council. 2011. Apex Houston Trustee Council Final Report. Available at: 

http://www.fws.gov/sfbayrefuges/murre/pdf/ApexHoustonFinalReport.pdf. 

Audobon Society. 2014. Brandt's Cormorant. Accessed June 2014. https://www.audubon.org/fieldguide/bird/brandts-cormorant. 

Briggs, K., D. Ainley, L. Spear, P. Adams and S. Smith. 1988. Distribution and diet of Cassin's Auklet and Common 

Murre in relation to central California upwellings. Proceedings of the International Ornithological 

Congress.

Burles, D. W., W. Szaniszlo and B. Wojtaszek. 2008. Sighting of Banded Brandt's Cormorant Phalacrocorax 

penicillatus on Haida Gwaii.

Capitolo, P. J., G. J. McChesney, H. R. Carter, M. W. Parker, L. E. Eigner and R. T. Golightly. 2014. Changes in 

breeding population sizes of Brandt’s Cormorants Phalacrocorax penicillatus in the Gulf of the Farallones, 

California, 1979–2006. Marine Ornithology 42:35-48.

Cornell Lab of Ornithology. 2014. Brandt's Cormorant. Accessed June 2014. 

http://www.allaboutbirds.org/guide/brandts_cormorant/lifehistory. 

Hill, D. K. 1995. Pacific warming unsettles ecosystems. Science 267:1911-1912.

8 Supporting literature for future exposure to climate factors is provided in the introduction.

9 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

10 Confidence level indicated by workshop participants.

274
Largier, J. L., B. S. Cheng and K. D. Higgason (editors). 2010. Report of a Joint Working Group of the Gulf of the 

Farallones and Cordell Bank National Marine Sanctuaries Advisory Councils.

Manuwal, D. A., H. R. Carter, T. S. Zimmerman and D. L. Orthmeyer. 2001. Biology and Conservation of the

Common Murre in California, Oregon, Washington, and British Columbia. Volume 1. Natural History and 

Population Trends. Washington, D.C.

Miller, A. K. and W. J. Sydeman. 2004. Rockfish response to low-frequency ocean climate change as revealed by 

the diet of a marine bird over multiple time scales. Marine Ecology Progress Series 281:207-216.

Newman, S. H., R. T. Golightly, E. N. Craig, H. R. Carter and C. Kreuder. 2004. The effects of petroleum exposure 

and rehabilitation on post-release survival, behavior, and blood health indices: A Common Murre (Uria 

aalge) case study following the Stuyvesant petroleum spill. Final Report. Oiled Wildlife Care Network, 

Wildlife Health Center, 1 Shields Avenue, School of Veterinary Medicine, University of California, Davis,

CA.

Oedekoven, C. S., D. G. Ainley and L. B. Spear. 2001. Variable responses of seabirds to change in marine climate: 

California Current, 1985-1994. Marine Ecology Progress Series 212:265-281.

Piatt, J. F. and D. N. Nettleship. 1985. Diving depths of four alcids. The Auk 102:293-297.

Pringle, J. M. 2007. Turbulence avoidance and the wind-driven transport of plankton in the surface Ekman layer. 

Continental Shelf Research 27 (5):670-678.

Roemmich, D. and J. McGowan. 1995. Climatic warming and the decline of zooplankton in the California Current. 

Science 267 (5202):1324-1326.

Rojek, N. A., M. W. Parker, H. R. Carter and G. J. McChesney. 2007. Aircraft and vessel disturbances to common 

murres Uria aalge at breeding colonies in central California, 1997-1999. Marine Ornithology 35 (1):61-69.

Schmidt, A. E., L. W. Botsford, J. M. Eadie, R. W. Bradley, E. Di Lorenzo and J. Jahncke. 2014. Non-stationary 

seabird responses reveal shifting ENSO dynamics in the northeast Pacific. Marine Ecology Progress Series

499:249-258.

Thayer, J. A., W. J. Sydeman, N. P. Fairman and S. G. Allen. 1999. Attendance and effects of disturbance on coastal 

Common Murre colonies at Point Reyes, California. Waterbirds 22 (1):130-139.

U.S. Fish and Wildlife Service (USFWS). 1995. Notice of Availability, Final Apex Houston Oil Spill Restoration 

Plan. Federal Register 60 (81):20739-20749.

U.S. Fish and Wildlife Service (USFWS). 2013. Farallon National Wildlife Refuge: South Farallon Islands Invasive 

House Mouse Eradication Project. Revised Draft Environmental Impact Statement. US Department of the 

Interior, Fish and Wildlife Service, Pacific Southwest Region.

U.S. Fish and Wildlife Service (USFWS). 2014. Seabirds of Farallon Islands. Accessed June 2014. 

http://www.fws.gov/refuge/farallon/wildlife_habitat/seabirds.html. 

Warzybok, P., R. Bradley and W. Sydeman. 2004. Population size and reproductive performance of seabirds on 

Southeast Farallon Island, 2003. Unpublished report to the U.S. Fish and Wildlife Service. PRBO 

Conservation Science, Petaluma, CA.

Warzybok, P. M., R. W. Berger and R. W. Bradley. 2012. Status of seabirds on southeast Farallon Island during the 

2012 breeding season. Unpublished report to the U.S. Fish and Wildlife Service. PRBO Conservation 

Science, Petaluma, CA.

Young, L., R. Suryan, D. Duffy and W. Sydeman. 2012. Climate change and seabirds of the California current and 

Pacific Islands ecosystems: Observed and potential impacts and management implications. Report to the 

US Fish and Wildlife Service, Region 1.

275
Tidewater Goby (Eucyclogobius newberryi)

1

Executive Summary The tidewater goby, a small fish species 

endemic to California, inhabits coastal 

lagoons, estuaries and marshes from 

Smith River, just south of the Oregon 

border, to northern San Diego County. 

The key climate sensitivity identified 

for the species by workshop participants is precipitation, and the key-non climate sensitivity is 

land use change. The endangered tidewater goby, though highly adapted and resilient to variable 

environmental conditions, has experienced significant population reductions due to habitat loss 

and degradation. The species is endemic to California, and patchily distributed. The species 

does not actively disperse, limiting its ability to colonize new areas, though flooding and 

nearshore transport results in passive dispersal down-coast up to 15 km. Because of this limited 

dispersal, genetic diversity is high among populations separated by unfavorable habitat, though 

little or no known behavioral or phenotypic plasticity exists for the species, so overall diversity is 

low-moderate. Societal value for the tidewater goby is moderate, with scientists and managers 

recognizing the species’ value, and potential for management is moderate, with managers having 

the ability to use land-use planning and regulations to improve goby habitat, thereby increasing 

its resilience to climate change impacts.

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): precipitation (4, moderate), 

pH (2, low), sea level rise (2, low), and coastal erosion (2, low) 

Climate and climate-driven changes that may benefit the species: sea level rise

• Description of benefit: Sea level rise could result in an increase of shallow water pool 

habitat, which would increase suitable habitat for the species. However, sea level rise 

may also transform pre-existing shallow water pools into deep water pools, thus 

decreasing available habitat. The overall impact of sea level rise on the tidewater goby 

will depend on specific local habitat conditions. 

Overall species sensitivity to climate and climate-driven factors: Moderate

• Confidence of workshop participants: Moderate 

Additional participant comments

The tidewater goby is highly sensitive to displacement from extreme storm events. However, 

extreme storm events may also assist in the nearshore dispersal of the species, enabling it to 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Tidewater Goby Score Confidence 

Sensitivity 3 Moderate 2 Moderate

Exposure 3 Moderate 2 Moderate

Adaptive Capacity 2 Low-Moderate 3 High

Vulnerability 3 Moderate 2 Moderate

276
recolonize nearby coastal lagoons. Extreme storm events may also result in a loss of aquatic 

vegetation thus reducing suitable habitat for the tidewater goby. 

Variability in precipitation impacts the tidewater goby in multiple ways by affecting streamflow 

and resulting lagoon dynamics. Gobies in general thrive in a system that is balanced with 

periodic heavy winter precipitation and consistent brackish conditions during dry months, but 

enhanced and prolonged periods of precipitation may negatively impact the species. If 

precipitation becomes more consistent and spread throughout the year, instead of the current 

Mediterranean pattern, lagoons would be open more often and would create less suitable habitat 

for gobies that rely on shallow sandy areas for spawning. 

Supporting literature

Literature review was conducted for those factors scoring 3 or higher, although the other 

sensitivities identified should also be considered. 

Precipitation

Gobies are highly sensitive to drought in smaller wetlands due to the loss of suitable habitat and 

thus fair better during wetter years that produce greater streamflow (Lafferty et al. 1999a). 

However, increased streamflow can result in breaching and scouring of lagoons, substantial 

salinity reduction, flooding and subsequent local population loss due to passive dispersal (which 

also has its benefits) (USFWS 2005). 

Additional comments provided after the vulnerability assessment workshop by Dr. Camm Swift, 

professor emeritus at the Natural History Museum of Los Angeles, indicate that the goby may 

also be somewhat sensitive to salinity, oxygen, wave action, currents/stratification and coastal 

erosion, though the species is generally recognized as being highly adapted to broad 

environmental conditions (Worcester and Lea 1996, USFWS 2005). Optimal conditions for 

tidewater gobies are in the lower one third of the salinity range and increased salinity is 

correlated with less robust habitat and diminished populations. Oxygen in the subsurface sandy 

substrate is critical for incubation of the eggs by the males in burrows. Wave action builds the 

sand berms that maintain the brackish lagoons optimal for tidewater gobies, and changes in the 

source direction of the waves could lead to deterioration of barrier berms and loss of lagoon 

habitat. Tidewater gobies do not tolerate much current and increases in current or tidal flows are 

detrimental. Stratification results in saline bottom water in lagoons that differentially absorb 

solar radiation which uses up oxygen leading to anoxic conditions low in the water column, 

driving brackish fauna like tidewater gobies into marginal shallows where they become 

vulnerable to predators. Coastal erosion can lead to fine sediments dominating lagoon 

substrates, in which tidewater gobies cannot dig breeding burrows. 

II. Sensitivities to disturbance regimes

Disturbance regimes identified: flooding 

Overall species sensitivity to disturbance regimes: Moderate-High

• Confidence of workshop participants: High 

277
Additional participant comments 

Flooding events can impact both the habitat and reproductive success of the tidewater goby. 

Though the tidewater goby thrives in the natural Mediterranean disturbance regime of relatively 

brief flooding and scouring of lagoons during winter months with stabilization and consistent 

brackish conditions during dry months, increased variability and intensity of precipitation events, 

and subsequent flooding, may negatively impact the species. Gobies may be displaced through 

nearshore dispersal mechanisms when their habitat is flooded (Lafferty et al. 1999b; though this 

may benefit the species by enabling colonization of new habitat) and increased flooding may also 

interfere with reproduction success because the species is a substrate-nester.

III. Dependencies

Species dependence on one or more sensitive habitat types: High

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: brackish water habitat, including coastal 

lagoons and upstream creek and river systems 

Species dependence on specific prey or forage species: Low-Moderate 

• Confidence of workshop participants: Moderate 

Other critical dependencies: relatively clear water for visual breeding and courtship activities in 

spring/early summer and oxygenated sandy substrate at least 4-6 inches deep for breeding 

burrows. 

• Degree of dependence: Moderate

• Confidence of workshop participants: no answer provided 

Specialization of species (1=generalist; 5=specialist): 2

• Confidence of workshop participants: Moderate 

IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): land use change (3, moderate) and 

invasive species (2, low) 

Overall species sensitivity to non-climate stressors: Low-Moderate

• Confidence of workshop participants: Low

Overall species exposure to non-climate stressors: no answer provided 

Supporting literature

Land-use change

Land-use practices such as conversion of coastal marsh to marinas, road and railway 

construction, freshwater diversion, grazing and agriculture, and flood control practices have all 

resulted in massive habitat loss and degradation throughout the goby’s range (Lafferty et al. 

1996). This has resulted in the extirpation of around half of the original populations, with most 

populations lost in Southern California and in the San Francisco Bay region (Swift et al. 1989). 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

278
Gobies use vegetated, shallow water habitats, and pre-existing development along the lagoon 

margins will preclude the ability of this habitat to expand as sea level rise causes lagoon water 

elevations to increase (Darren Fong, pers. comm., 2014). 

Invasive species

Goby populations have historically been locally extirpated following the introduction of invasive 

species, particularly large piscivorous fish, including the killifish, yellowfin goby, and squawfish 

(Leidy 1984, Brittan et al. 1970, Lafferty et al. 1999a). 

V. Other sensitivities: none identified

Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 1 

• Confidence of workshop participants: High 

Population status of the species (1=endangered; 5=robust): 1 

• Confidence of workshop participants: High 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 2

• Confidence of workshop participants: Moderate

Dispersal ability of the species: Low 

• Confidence of workshop participants: Moderate

Maximum annual dispersal distance: up to 15 km 

• Confidence of workshop participants: Moderate

Supporting literature

This species is endemic to California, and thus exhibits a limited geographic extent, from Smith 

River in Del Norte County to northern San Diego County (USFWS 2005). The population is 

endangered (though USFWS has proposed a downlisting to “threatened”; Darren Fong, pers. 

comm., 2014) and somewhat fragmented and patchy due to the persistence of unsuitable habitat 

along the coastline that separates suitable habitat (Lafferty et al. 1999a). Dispersal is low and 

limited to 10-15 km at most for adults; larvae and small juveniles are thought to be too sensitive 

to higher salinities to be able to disperse (according to unpublished research by Hellmair at 

Humboldt State, Camm Swift, pers. comm., 2014). Dispersal is passive and a result of flooding 

and longshore currents that transport individuals to suitable habitat to the south (Lafferty et al. 

1999b).

II. Intraspecific/Life history diversity

Diversity of life history strategies: Low

• Confidence of workshop participants: no answer provided 

Genetic diversity: High

• Confidence of workshop participants: no answer provided 

279
Behavioral plasticity: Low

• Confidence of workshop participants: no answer provided 

Phenotypic plasticity: Low-Moderate

• Confidence of workshop participants: no answer provided 

Overall degree of diversity/plasticity of the species: Low-Moderate

• Confidence of workshop participants: no answer provided 

The tidewater goby exhibits high genetic diversity due to its highly fragmented population, 

which is clearly the result of isolation and genetic drift (Earl et al. 2010). This work suggests 

that populations, especially in the southern range in northern San Diego County, are extremely 

divergent due to extensive isolation and may even represent a separate species (Earl et al. 2010). 

Genetic evidence indicates that populations throughout much of the range show extreme 

isolation and may be unlikely to recover from local extinction via dispersal from adjacent areas. 

This species also displays no known behavioral plasticity, and low-moderate phenotypic 

plasticity, mostly in subtle morphological features (Camm Swift, pers. comm., 2014). 

Gobies reproduce in successive cycles, spawn nearly year-round, can undergo more than 4 

reproductive events in a given year, and take 3-10 months to reach reproductive maturity, 

depending on the season (longer during colder temperatures) (Camm Swift, pers. comm., 2014). 

The tidewater goby exhibits a female-dominated breeding system, and males typically remain in 

one burrow and breed with successive females (Camm Swift, pers. comm., 2014). 

III. Management potential

Value of species to people: Moderate

• Confidence of workshop participants: Moderate 

• Description of value: endangered species and endemic to California

Likelihood of managing or alleviating climate change impacts on species: Moderate

• Confidence of workshop participants: Moderate

• Description of potential management options: the species has proven amenable to 

management when wetland and lagoon habitat has been improved and exotic predators 

removed or controlled 

Additional participant comments

There are generally good land-use planning and regulations in California to protect the natural 

fringe habitats around coastal lagoons and estuaries where this species is present, and support 

exists for protecting the species as it is considered endangered and endemic. 

IV. Other adaptive capacity factors: none identified 

Additional participant comments

Normally the species would be considered very adaptable to climate change under natural 

conditions, but the many constraints on the margins of wetlands and lagoons, the freshwater 

supply, and the presence of exotic species will complicate the species’ normally good abilities to 

adapt.

280
Exposure 

I. Future climate exposure6

Future climate and climate-driven changes identified (score7, confidence8): changes in 

precipitation (3, moderate) and increased flooding (3, moderate) 

Degree of exposure to future climate and climate-driven changes: Moderate

• Confidence of workshop participants: Moderate 

Additional participant comments

Potential areas of refugia from flooding include fringing wetlands (if present) of lagoons and 

creeks.

Literature Cited

Brittan, M.R., J.D. Hopkirk, J.D. Conners and M.Martin. 1970. Exposive spread of the oriental goby Acanthogobius 

flavimanus in the San Francisco Bay-Delta Region of California. Proceedings of the California Academy 

of Sciences 4(38):207-214.

Earl, D. A., K.D. Louie, C. Bardeleben, C.C. Swift, D.K. Jacobs. 2010. Rangewide microsatellite phylogeography of 

the endangered tidewater goby, Eucyclogobius newberryi (Teleostei: Gobiidae), a genetically subdivided 

coastal fish with limited marine dispersal. Conservation Genetics 11: 103-114. 

Lafferty, K.D., R.O. Swenson, and C.C. Swift. 1996. Threatened fishes of the world: Eucyclogobius newberryi

Girard, 1857 (Gobiidae). Environmental Biology of Fishes 46:254.

Lafferty, K.D., C.C. Swift, and R.F. Ambrose. 1999a. Extirpation and Recolonization in a Metapopulation of an

Endangered Fish, the Tidewater Goby. Conservation Biology 13(6): 1447-1453.

Lafferty, K.D., C.C. Swift, and R.F. Ambrose. 1999b. Postflood persistence and recolonization of endangered 

tidewater goby populations. North American Journal of Fisheries Management 19:618-622.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp.

Leidy, R.A. 1984. Distribution and ecology of stream fishes in the San Francisco Bay drainage. Hilgardia 52:1-175.

Swift, C.C., J.L. Nelson, C. Maslow, and T. Stein. 1989. Biology and distribution of the tidewater goby, 

Eucyclogobius newberryi (Pisces: Gobiidae) of California. Contributions in science 404. Natural History 

Museum of Los Angeles County, Los Angeles.

United States Fish and Wildlife Service (USFWS). 2005. Recovery Plan for the Tidewater Goby (Eucyclogobius 

newberryi). U.S. Fish and Wildlife Service, Portland,Oregon. 199 pp.

Worcester, K.R., and R.N. Lea. 1996. Observations on tidewater goby habitat utilization and laboratory 

maintenance during the California drought. Unpublished abstract from Symposium on tidewater goby, 

Southern California Academy of Sciences Annual Meeting at Loyola Marymount University May 3-4, 

1996.

6 Supporting literature for future exposure to climate factors is provided in the introduction. 7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

281
Western Snowy Plover (Charadrius alexandrinus nivosus)

1

Executive Summary The Western snowy plover is a 

federally threatened subspecies that 

breeds on coastal beaches from 

southern Washington to southern Baja 

California and relies on a variety of 

sensitive habitats, nesting in flat, open 

sandy areas just in front of coastal foredunes. Key climate sensitivities identified for the species 

by participants include sea level rise and coastal erosion/wave action, and key non-climate 

sensitivities include recreation, land use change, pollution and poisons, and invasive species. The 

Pacific coast population of the Western snowy plover exhibits a broad transcontinental 

geographic extent and a federally threatened population that is fragmented but likely connected 

due to high dispersal. The species exhibits some degree of reproductive plasticity, but limited 

genetic diversity and behavioral plasticity. The societal value for this species is complicated, 

with birders and some recreational users seeing great value in the species, though recreational 

use conflicts have caused some local opposition to conservation actions to protect the species 

from disturbance. Declines in abundance in recent decades are likely due to habitat loss, 

predation, and human disturbance, and the major future threat to the snowy plover from climate 

impacts is likely the loss of habitat and the inability for managers to address that loss on a large 

enough scale to maintain population abundance. Efforts to manage for human disturbance and 

predation have seen mixed results, but the population has yet to recover to previous levels. 

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): sea level rise (5, high), 

wave action (5, high), coastal erosion (5, high), precipitation (2, low), pH (1, low) 

Climate and climate-driven changes that may benefit the species: coastal erosion 

• Description of benefit: Coastal erosion could create additional habitat for the snowy 

plover 

Overall species sensitivity to climate and climate-driven factors: Moderate-High

• Confidence of workshop participants: Moderate

Additional participant comments

The snowy plover was identified as being highly sensitive to climate-driven factors primarily due 

to the loss of nesting habitat and subsequent reductions in reproductive success. Potential short1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Snowy Plover Score Confidence 

Sensitivity 4 Moderate-High 3 High

Exposure 4 Moderate-High 2 Moderate

Adaptive Capacity 3 Moderate 2 Moderate

Vulnerability 4 Moderate-High 2 Moderate

282
term benefits to the species may be realized through the creation of new habitat as a result of 

enhanced coastal erosion, though in the long-term, cumulative habitat loss is expected.

Supporting literature

Sea Level Rise

Rising sea level can contribute to habitat fragmentation and loss, resulting in a reduction of 

foraging and nesting areas for snowy plovers (Chu-Agor et al. 2012). Using geomorphological 

models, combined with metapopulation information for the snowy plover in Florida, AielloLammens et al. (2011) demonstrated that sea level rise will likely cause a decline in suitable 

habitat and carrying capacity for the snowy plover, increasing its risk of widespread decline and 

extinction. Habitat loss due to sea level rise for shorebirds in the San Francisco Bay region was 

estimated at upwards of 70%, exacerbated by seawalls and other structures that inhibit the 

migration of beach and dune habitat (Galbraith et al. 2002). 

As managers consider impacts of sea level rise to snowy plovers in their specific regions, 

different beach types and settings should be considered, as beach response to sea level rise and 

sand supply failure will not be uniform in terms of the resulting consequence for snowy plover 

habitat (Peter Baye, pers. comm., 2014). Steep, narrow, cliff-backed beaches are more 

vulnerable to losing critical backshore habitat, whereas high dune/paleo-dune backed beaches are 

buffered from backshore habitat loss and can migrate inland, indicating habitat resilience even 

with accelerating sea level rise (Peter Baye, pers. comm., 2014). Barrier beaches may actually 

become more suitable for snowy plovers, as accelerated sea level rise and increased storm 

intensity may increase wash-over, negatively impacting the European beachgrass (see “invasive 

species” section for more information) and creating more open space breeding habitat (Peter 

Baye, pers. comm., 2014). 

Coastal Erosion/Wave Action

These climate factors are considered together because they result in the same impacts to snowy 

plover population abundance. Intense winter storms, particularly during ENSO events, bring 

high wave energy that significantly alters beach profiles due to enhanced erosion (White and 

Allen 1999), negatively impacting snowy plover populations. During the 1997/1998 winter 

ENSO event, the snowy plover breeding population experienced a 10-30% range-wide decline 

(USFWS 2007) due to enhanced erosion from wave action that disrupted nesting habitat 

(Campbell 2013). 

II. Sensitivities to disturbance regimes

Disturbance regimes identified: wind, storms, and flooding 

Overall species sensitivity to disturbance regimes: High

• Confidence of workshop participants: High

Additional participant comments

Storms and flooding can result in the loss of a brood during the nesting season, and strong winds 

can bury nests. Enhanced wave energy may impact the back beach nesting habitat and enhance 

erosion, reducing breeding success. 

283
III. Dependencies

Species dependence on one or more sensitive habitat types: Moderate-High

• Confidence of workshop participants: Moderate 

• Sensitive habitats species is dependent upon: gravel bars, salt pans, and sandy beaches 

Species dependence on specific prey or forage species: Low4

• Confidence of workshop participants: Moderate 

Other critical dependencies: none identified 

Specialization of species (1=generalist; 5=specialist): 4

• Confidence of workshop participants: Moderate 

IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score5, confidence6): recreation (5, high), land use change (5, 

high), pollution and poisons (5, high), invasive species (4, high) 

Overall species sensitivity to non-climate stressors: High

• Confidence of workshop participants: High 

Overall species exposure to non-climate stressors: Moderate-High

• Confidence of workshop participants: High

Supporting literature

Though not identified by workshop participants, urban predators such as ravens and crows are an 

important limiting factor in breeding success at many sites (Dan Robinette, pers. comm., 2014), 

and may be a more significant threat to snowy plover populations than invasive species (Peter 

Baye, pers. comm., 2014). 

Recreation

The snowy plover breeding season, from March to September, coincides with the busiest and 

most popular recreational use of beaches (California State Parks 2014). Impacts from human 

disturbance, especially from off-leash dogs, can cause nest abandonment and loss of eggs and 

unfledged chicks. Beach visitors also often leave trash behind, which attracts opportunistic 

predators such as the American crow and striped skunk (California State Parks 2014). In a study 

conducted by the Golden Gate National Recreation Area at Ocean Beach, San Francisco, 90% of 

observed dogs were off-leash, with 19 dogs (6% of those observed) chasing at least 62 snowy 

plovers, and roaming dogs (50% of those observed) inadvertently disturbing another 100 birds in 

just 40 hours of observation (Hatch 1996). Plovers were also observed to be disturbed by sand 

excavation, people, helicopters, bicycles, vehicles and kites (Hatch 1996). 

4 Reviewer of this document noted that this may not be an accurate score for the snowy plover’s dependence on 

specific prey, as talitrid amphipods are a very specific and critical food source for the species. 5 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

6 Confidence level indicated by workshop participants.

284
Land Use Change 

The impact of land use change on snowy plovers is primarily through the introduction and 

exacerbation of predation by gulls, ravens, foxes, coyotes, dogs, feral cats, skunks and racoons 

that often follow human activity into snowy plover habitat (Campbell 2013; Vulnerability 

Assessment Workshop, pers. comm., 2014). Land use change (i.e., development, watershed 

alterations, livestock grazing and agriculture) may also disrupt sediment supply to plover habitat, 

and impact water quality in the region, resulting in high coliform, bacterial and toxic metal 

contamination (e.g., high mercury levels, ONMS 2010). Development and landscape irrigation 

on top of coastal cliffs that often back beaches and dunes in the study region can increase 

internal pore pressures of cliff materials, decreasing resilience and accelerating coastal erosion 

(Griggs and Patsch 2004), and beach grooming and nourishment can negatively impact brown 

algal wrack abundance, which will impact talitrid amphipods, an important prey for snowy 

plovers (Dan Robinette, pers. comm., 2014). 

Land use and development on barrier beaches may change as a response to accelerated sea level 

rise and increased storminess. These areas may become economically unsustainable due to 

increased failure of beach armoring and catastrophic storm damage, and revert to open space 

compatible with plover habitat and spontaneous plover recolonization/recovery (Peter Baye, 

pers. comm., 2014). 

Pollution and poisons 

Threats to snowy plovers from pollution and poisons include oil from offshore spills that can 

coat foraging and nesting habitat (Vulnerability Assessment Workshop, pers. comm., 2014; 

SIMoN 2014), decreasing food availability and causing harmful physiological effects (SIMoN 

2014), debris that can cause entanglement (which has been observed in abandoned monofilament 

fishing line, SIMoN 2014) and attraction of predators (Campbell 2013). Plovers may also be 

exposed to toxins such as heavy metals, and one study implicated the elevated concentration of 

mercury in the failure of eggs to hatch at Point Reyes National Seashore (Schwarzbach et al. 

2005). 

Invasive Species

Predation by introduced species has contributed to recent declines in snowy plover abundance, 

including the non-native Eastern red fox (California State Parks, 2014). Plovers prefer open, flat 

sand with sparse vegetation for nesting, and the invasive European beachgrass has decreased the 

availability of this habitat and changed the topography of the dunes, as well as created an 

impenetrable vegetative barrier for chicks between foraging and nesting areas (BLM 2014). 

Invertebrate densities are also lower in habitat dominated by European beachgrass as compared 

to native vegetation, limiting the foraging opportunities for plovers (BLM 2014). Management 

efforts by Point Reyes National Seashore show an increase in the number of plover chicks reared 

in areas immediately following removal of beachgrass (Campbell 2013). 

V. Other sensitivities: none identified 

285
Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 5

• Confidence of workshop participants: High 

Population status of the species (1=endangered; 5=robust): 2

• Confidence of workshop participants: High 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 3

• Confidence of workshop participants: Moderate 

Dispersal ability of the species: High 

• Confidence of workshop participants: High 

Maximum annual dispersal distance: >100km 

• Confidence of workshop participants: High 

Supporting literature

The Pacific coast population of the Western snowy plover exhibits a broad transcontinental 

geographic extent, from southern Washington to southern Baja California, Mexico and a 

federally threatened population. Declines in abundance in recent decades are due to habitat loss, 

predation, and human disturbance (California State Parks 2014). There are an estimated 2,400 

breeding adults in the Pacific coast population, which breed exclusively on coastal beaches (in 

contrast to the reproductively distinct inland population, SIMoN 2014). 

II. Intraspecific/Life history diversity

Diversity of life history strategies: Moderate

• Confidence of workshop participants: Moderate 

Genetic diversity: Low-Moderate

• Confidence of workshop participants: Moderate 

Behavioral plasticity: Low-Moderate

• Confidence of workshop participants: Low

Phenotypic plasticity: Low-Moderate 

• Confidence of workshop participants: Low

Overall degree of diversity/plasticity of the species: Low-Moderate 

• Confidence of workshop participants: Low

Additional participant comments

The species is able to produce a second clutch in any given year if the first reproductive attempt 

fails and can adapt the timing of reproduction somewhat based on environmental conditions. 

Limited behavioral adaptation has been exhibited in response to increased predation from ravens 

and cats, though there may be some degree of behavioral response to habitat loss through the use 

of other habitat types. There is likely very little genetic structure and diversity in the Pacific 

coast population due to high dispersal, and reduction of the population to just 2,000 individuals. 

286
Supporting literature

The species reproduces in successive cycles throughout its lifespan, becoming reproductively 

mature at a little less than a year (310 days, Moller 2006). Breeding occurs from March to 

September and parents incubate the eggs for 4 weeks, followed by a 4-week fledgling period 

(California State Parks 2014). 

III. Management potential

Value of species to people: Low-Moderate

• Confidence of workshop participants: Moderate 

• Description of value: Birders value the species, but most recreational users (especially 

dog owners) do not due to recreational use conflicts. 

Likelihood of managing or alleviating climate change impacts on species: Low-Moderate

• Confidence of workshop participants: High 

• Description of potential management options: Most beaches have no place to migrate and 

the management actions of beach nourishment and sediment supply may help, but will 

likely conflict with recreational uses (and can also negatively impact snowy plover prey). 

Protecting refugia has high likelihood of success, but there are limited opportunities to do 

this. 

Supporting literature

Despite intensive management measures at Point Reyes National Seashore, the snowy plover 

population there has not recovered to previous levels, declining from 50 individuals in 1987 to 

only 9 in 2012 (Campbell 2013). 

IV. Other adaptive capacity factors: none identified 

Exposure 

I. Future climate exposure7

Future climate and climate-driven changes identified (score8, confidence9): increased coastal 

erosion and runoff (5, high), increased flooding (5, moderate), sea level rise (5, high), increased 

storminess (5, high), decreased sediment supply (3, moderate), decreased pH (2, low), changes in 

precipitation (2, low) 

Degree of exposure to future climate and climate-driven changes: Moderate

• Confidence of workshop participants: Moderate 

7 Supporting literature for future exposure to climate factors is provided in the introduction.

8 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

9 Confidence level indicated by workshop participants.

287
Literature Cited

Aiello-Lammens, M.E., M.L. Chu-Agor, M. Convertino, R.A. Fischer, I. Linkov, and H.R. Akçakaya. 2011. The

impact of sea-level rise on Snowy Plovers in Florida: integrating geomorphological, habitat, and 

metapopulation models. Global Change Biology, 17: 3644–3654. 

Bureau of Land Management (BLM). 2014. Western Snowy Plover. Accessed August 20, 2014, from: 

http://www.blm.gov/ca/st/en/fo/arcata/western_snowy_plover.print.html. 

California State Parks. 2014. Snowy Plover Monitoring and Protection. Accessed August 20, 2014, from:

 http://www.parks.ca.gov/?page_id=21577.

Campbell, C. 2013. Monitoring Western Snowy Plovers at Point Reyes National Seashore, Marin County, 

California: 2012 annual report. Natural Resource Technical Report. NPS/SFAN/NRTR—2013/825. 

National ParkService. Fort Collins, Colorado. Published Report-2204673. Available 

at: http://www.sfnps.org/download_product/4526/0. 

Chu-Agora, M.L., R. Muñoz-Carpenaa, G.A. Kikera, M.E. Aiello-Lammensb, H.R. Akçakayab, M. Convertinoa, 

and I. Linkovc. 2012. Simulating the fate of Florida Snowy Plovers with sea-level rise: Exploring research 

and management priorities with a global uncertainty and sensitivity analysis perspective. Ecological 

Modeling 224(1): 33-47.

Galbraith, H., R. Jones, R. Park, J. Clough, S. Herrod-Julius, B. Harrington, and G. Page. 2002. Global climate 

change and sea level rise: potential losses of intertidal habitat for shorebirds. Waterbirds 25:173–183.

Griggs, G.B. and K.B. Patsch. 2004. California’s Coastal Cliffs and Bluffs. In: Formation, Evolution, and Stability 

of Coastal Cliffs – Status and Trends. U.S. Geological Survey Professional paper 1693. Pp. 53-64.

Hatch, D.A. 1996. Western snowy plover (a federally threatened species) wintering population and interaction with 

human activity on Ocean Beach, San Francisco, Golden Gate National Recreation Area, 1988 through 

1996. Golden Gate National Recreation Area US03062.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Moller, A.P. 2006. Sociality, age at first reproduction and senescence: comparative analyses of birds. Journal of 

Evolutionary Biology 19:682-689. 

Office of National Marine Sanctuaries (ONMS). 2010. Gulf of the Farallones National Marine Sanctuary Condition

Report. U.S. Department of Commerce, National Oceanic and Atmospheric Administration, Office 

of National Marine Sanctuaries, Silver Spring, MD. 97 pp.

Sanctuary Integrated Monitoring Network (SIMoN). 2014. Western Snowy Plover. Accessed August 20, 2014, 

from: http://sanctuarysimon.org/monterey/sections/specialSpecies/western_snowy_plover.php. 

Schwarzbach, S. E., M. Stephenson, T. Ruhlen, S. Abbott, G.W. Page, and D. Adams. 2005. Elevated mercury 

concentrations in failed eggs of Snowy Plovers at Point Reyes National Seashore. Marine Pollution Bulletin 

50: 1433–1456.

U.S. Fish and Wildlife Service (USFWS). 2007. Recovery plan for the Pacific coast population of the western 

snowy plover (Charadrius alexandrinus nivosus). In 2 volumes. U.S. Fish and Wildlife Service, 

Sacramento, Calfornia.

White, J. D., and S. G. Allen. 1999. Draft western snowy plover management plan. Point Reyes National Seashore 

 Unpublished Report, Point Reyes, California.

288
Widow Rockfish (Sebastes entomelas)1

Executive Summary Widow rockfish is a medium-sized, 

mid-water species important in both the 

recreational and commercial catches in 

California. The species occurs from 

Alaska to Baja California over highrelief substrata, most commonly at 

depths between 140 to 210 meters, though has been captured at depths from 24 to 549 meters. 

Key climate sensitivities identified by workshop participants for widow rockfish include 

dissolved oxygen, wave action, dynamic ocean conditions (currents/mixing/stratification) and 

pH. Key non-climate sensitivities include harvest and pollution/poisons. Widow rockfish 

exhibit a moderate to large geographic extent and a diminished, but generally stable, population 

that is nearly continuous. The center of distribution is British Columbia to Northern California. 

The range of larval dispersal is unknown, but some studies suggest that dispersal may be limited 

to less than 200 km. Widow rockfish exhibit overall moderate diversity due to moderate life 

history diversity and behavioral plasticity, including the ability to move out of areas experiencing 

unfavorable conditions, moderate-high genetic diversity, and moderate phenotypic plasticity, 

including the ability of females to spawn in response to favorable oceanographic conditions. The 

societal value for widow rockfish is moderate-high due to its harvest value, and because the 

population can be managed for harvest, the likelihood of managing or alleviating climate impacts 

was rated as moderate. If the fishery is managed to sustain healthy populations with increased 

genetic diversity, widow rockfish populations will be moderately able to withstand climate 

impacts.

Sensitivity 

I. Sensitivities to climate and climate-driven factors

Climate and climate-driven changes identified (score2, confidence3): dissolved oxygen (DO) 

levels (4, moderate), wave action (4, high), dynamic ocean conditions 

(currents/mixing/stratification) (4, high), pH (3, low) 

Climate and climate-driven changes that may benefit the species: no answer provided 

Overall species sensitivity to climate and climate-driven factors: Moderate-High

• Confidence of workshop participants: Moderate 

Additional participant comments 

Upwelling has a significant impact on larval and juvenile rockfish and the availability of food, 

which may drive population trends for the species. 

1 Refer to the introductory content of the results section on for an explanation of the format, layout and content of 

this summary report.

2 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

3 Confidence level indicated by workshop participants.

Widow Rockfish Score Confidence 

Sensitivity 3 Moderate 3 High

Exposure 3 Moderate 3 High

Adaptive Capacity 4 Moderate-High 3 High

Vulnerability 3 Moderate 3 High

289
Supporting literature

Oxygen

Significant changes to dissolved oxygen (DO) can result from a number of physical and 

biological processes, including circulation, ventilation, air-sea exchange, production and 

respiration (Keeling and Garcia 2002, Deutsch et al. 2005, Bograd et al. 2008). A decline in 

midwater oceanic DO is predicted due to enhanced stratification and reduced ventilation 

(Sarmiento et al. 1998, Keeling and Garcia 2002). Areas adjacent to upwelling centers like Point 

Arena are particularly susceptible to low DO levels as the upwelling process naturally delivers 

low oxygen water onto the continental shelf from the deep ocean (Largier et al. 2010). DO 

levels under 2 mg/L have been observed to negatively impact rockfish prey sources (NMFS 

2013), lead to mass mortality events (Palsson et al. 2008), and alter rockfish behavior and habitat 

use through movement to more tolerable conditions at shallower depths (Palsson et al. 2005). 

Though there is little information regarding habitat requirements of rockfish larvae, the larval 

stages of many other fish species are vulnerable to low DO (Boehlert and Morgan 1985, NMFS 

2013). 

Wave Action 

Wave action is expected to most impact rockfish larvae (Vulnerability Assessment Workshop, 

pers. comm., 2014). Larval rockfish are subject to oceanographic conditions after birth, drifting 

in ocean currents in generally the upper 80 meters of the water column and may remain in the 

plankton for up to five months (Love et al. 2002). 

Dynamic ocean conditions (currents/mixing/stratification) 

In this broad category of climate impacts, upwelling and El Niño processes were identified by 

workshop participants as being the most influential on the sensitivity of widow rockfish. Cury 

and Roy (1989) found that a moderate degree of upwelling is ideal for the species; if upwelling is 

too weak, ocean productivity is too low to support an abundant year class, but if upwelling is too 

strong and persistent, larvae are transported offshore beyond favorable recruitment habitats for 

settling juveniles. Turbulence effectively separates fish larvae from food patches, decreasing 

larval survival. El Niño conditions, which suppress upwelling, have been shown to negatively 

impact female rockfish fecundity and growth rates, and repeated exposure to El Niño events may 

result in delay of maturation age, which can result in the reduction of lifetime egg production 

(Harvey 2005). The number of El Niño events likely will not change, though the likelihood of 

super El Niños doubled from one every 20 years in the previous century to one every 10 years in 

the 21st century (Cai et al. 2013). Additionally, enhanced stratification is expected to decrease 

dissolved oxygen levels in midwater habitats (Sarmiento et al. 1998, Keeling and Garcia 2002), 

with important repercussions for rockfish (see oxygen section above). 

pH 

The direct effects of decreased pH on fishes within the study region are not well understood 

(Largier et al. 2010), though one study outside of the region documented the impact of lower pH 

levels on larval clownfish olfactory cues, which caused disorientation (Munday et al. 2009). 

Altered behavioral responses, in the form of increased time spent seeking refuge, have recently 

been documented in juvenile rockfish when exposed to lower pH waters (7.75; projected for the 

next century in California) for one week, with recovery of normal behavior taking 12 days after a 

return to seawater at a normal pH level. The cause was traced to altered ion concentration in the 

blood, which impacts the fish’s sensory system (Hamilton et al. 2013). 

290
II. Sensitivities to disturbance regimes

Disturbance regimes identified: wind

Overall species sensitivity to disturbance regimes: Moderate

• Confidence of workshop participants: Moderate 

Additional participant comments 

Changes in seasonal wind patterns can result in changes to localized upwelling, which is a 

critical process for maintaining food supply for juvenile and adult fish.

Supporting literature

Climate change is expected to impact the intensity of upwelling by altering wind stress, and 

upwelling that is too weak or too intense can have negative impacts on larval rockfish (Cury and 

Roy 1989, see Dynamic Ocean Conditions section above).

III. Dependencies

Species dependence on one or more sensitive habitat types: Moderate-High

• Confidence of workshop participants: High 

• Sensitive habitats species is dependent upon: pelagic water column for larvae, nearshore 

kelp forest habitat for juveniles, and deep reef habitat for adults 

Species dependence on specific prey or forage species: Low-Moderate 

• Confidence of workshop participants: High 

Other critical dependencies: Cold water/upwelling to support an abundant boreal food supply for 

juveniles 

• Degree of dependence: Moderate-High

• Confidence of workshop participants: Moderate

Specialization of species (1=generalist; 5=specialist): 2

• Confidence of workshop participants: Low-Moderate 

Additional participant comments 

El Niño events that push warmer waters northward can impact the food supply of juvenile fish. 

The species also does not recruit well during poor upwelling and El Niño events. 

Supporting literature

Widow rockfish feed on krill and copepods during the larval and pelagic juvenile stage, and a 

variety of gelatinous zooplankton, small pelagic crustaceans (including krill), and small fishes as 

adults (Adams 1987, AFSC 2014). 

291
IV. Sensitivity and current exposure to non-climate stressors

Non-climate stressors identified (score4, confidence5): harvest (4, high) and pollution (oil and 

dispersants) (4, high) 

Overall species sensitivity to non-climate stressors: Moderate-High

• Confidence of workshop participants: High 

Overall current exposure to non-climate stressors: Low

• Confidence of workshop participants: High

Additional participant comments

Local populations of widow rockfish that have been over-harvested will be more sensitive to 

climate impacts than healthy populations. 

Supporting literature

Harvest

Widow rockfish are the third most frequently caught scorpaenid in California’s commercial 

fishery, and are an important component of recreational landings (Starr et al. 2002), though 

recreational catch has been minimal in recent years (He et al. 2011). Total landings peaked in 

1981 and have declined since, due to reduced population and increased regulations (Starr et al. 

2002). The stock spawning biomass showed a steady decline between 1980 and 2001, at which 

point the stock began an increasing trend (He et al. 2011). Though the population was declared 

overfished in 2001, the latest stock assessment estimates the spawning biomass to be 51% of 

virgin spawning biomass and the population is now considered rebuilt (He et al. 2011) 

Pollution

Oil and dispersants were identified by workshop participants as potential sources of pollution 

that may impact widow rockfish, particularly the larval and juvenile stages. Over 6,000 

commercial vessels transit in and out of San Francisco Bay every year, with 5% of these as large 

cargo vessels that can carry up to one million gallons of bunker fuel (GFNMS 2008). All 

transiting vessels, including military, research and fishing vessels, carry crude oil or fuel, posing 

a potential risk to resources in the region (Largier et al. 2010). After the 1989 Exxon Valdez oil 

spill in Prince William Sound, Alaska, demersal rockfish species were the only fish species 

found dead in significant numbers, likely due to elevated hydrocarbon metabolites (Marty et al. 

2003), indicating they may be particularly vulnerable to oil spills. 

V. Other sensitivities: none identified 

4 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

sensitivity and 1 indicating low sensitivity.

5 Confidence level indicated by workshop participants.

292
Adaptive Capacity

I. Extent, status, and dispersal ability

Geographic extent of the species (1=endemic; 5=transboundary): 4

• Confidence of workshop participants: High 

Population status of the species (1=endangered; 5=robust): 3

• Confidence of workshop participants: Moderate 

Population connectivity of the species (1=isolated/fragmented; 5=continuous): 4

• Confidence of workshop participants: High 

Dispersal ability of the species: High 

• Confidence of workshop participants: High

Maximum annual dispersal distance: no answer provided 

Supporting literature

Workshop participants rated widow rockfish as having high dispersal capability based on the fact 

that larvae can remain in the plankton for up to five months (Love et al. 2002). Mobile, longlived species that have pelagic larvae typically are thought to have high dispersal, though few 

data exist for larval rockfish dispersal distance (Miller and Shanks 2004). However, recent 

studies on other rockfish species indicate dispersal distance may be less than previously thought 

for some species. Otolith microstructure and microchemistry were used to estimate larval 

dispersal for the black rockfish, which was found to be much more limited than models have 

projected, less than 120 km (Miller and Shanks 2004). Limited lifetime dispersal (between 100 

and 200 km) was also indicated for the Northern Rockfish based on significant genetic structure 

and isolation-by-distance relationships among 11 microsatellite loci (Gharrett et al. 2011).

II. Intraspecific/Life history diversity

Diversity of life history strategies: Moderate

• Confidence of workshop participants: Moderate 

Genetic diversity: Moderate-High

• Confidence of workshop participants: High 

Behavioral plasticity: Low-Moderate

• Confidence of workshop participants: Low

Phenotypic plasticity: Moderate

• Confidence of workshop participants: High 

Overall degree of diversity/plasticity of the species: Moderate

• Confidence of workshop participants: Moderate 

Additional participant comments

An example of phenotypic plasticity is the ability of females to spawn in response to favorable 

oceanographic conditions, increasing the likelihood of larval survival. 

293
Supporting literature

Behaviorally, the species may move to more favorable oceanographic conditions in response to a 

stressor (e.g. upwelled oxygen-poor water, Palsson et al. 2005). There is no evidence of separate 

genetic stocks of widow rockfish along its range, and the species is therefore treated from a 

management perspective as one stock (He et al. 2011). 

Females generally spawn from December to April in this region and live to around 60 years, 

becoming more fecund with age (AFSC 2014). Released larvae drift in ocean currents and 

exhibit a very high mortality rate, up to 70% in laboratory conditions (Canino and Francis 1989). 

III. Management potential

Value of species to people: Moderate-High

• Confidence of workshop participants: High 

• Description of value: Value for commercial and recreational fisheries.

Likelihood of managing or alleviating climate change impacts on species: Moderate

• Confidence of workshop participants: High 

• Description of potential management options: If harvest of the species is managed to 

sustain a genetically diverse population, it’s likely the species would have increased 

capacity to succeed in a changing environment. 

Additional participant comments

Though it will be difficult to manage the impacts of climate change on this species, human 

impacts, such as harvest levels, can be actively managed.

IV. Other adaptive capacity factors: none identified 

Exposure6

I. Future climate exposure

Future climate and climate-driven changes identified (score7, confidence8): altered currents and 

mixing (4, high), decreased pH (4, high), changes in sea surface temperature (3, high), increased 

storminess (3, moderate), decreased dissolved oxygen (DO) (2, moderate) 

Degree of exposure to future climate and climate-driven changes: Moderate

• Confidence of workshop participants: Moderate-High

Additional participant comments

Because the species range extends well north of the study region, the species may be able to seek 

refuge from warmer ocean temperatures in the northern stretches of its range. Sea surface 

temperature impacts stratification and ocean circulation patterns, influencing primary 

productivity and prey availability for rockfishes. 

6 Supporting literature for future exposure to climate factors is provided in the introduction.

7 For scoring methodology, see methods section. Factors were scored on a scale of 1-5, with 5 indicating high 

exposure and 1 indicating low exposure.

8 Confidence level indicated by workshop participants.

294
Literature Cited

Adams, P.B. 1987. The diet of widow rockfish Sebastes entomelas in northern California, pp. 37-41. In: W.H. 

Lenarz and D.R. Gunderson (eds.), Widow rockfish, proceedings of a workshop, Tiburon, California, 

December 11-12, 1980. NOAA Tech. Rep. NMFS 48.

Alaska Fisheries Science Center (AFSC). 2014. Widow Rockfish. National Marine Fisheries Service - NOAA 

Fisheries Accessed June 2014. http://www.afsc.noaa.gov/Rockfish-Game/description/widow.htm.

Boehlert, G. W. and J. B. Morgan 1985. Turbidity enhances feeding ability of larval Pacific herring (Clupea 

harengus pallasi). Hydrobiologia. Volume 123, pages 161 to 170.

Bograd, S. J., C. G. Castro, E. Di Lorenzo, D. M. Palacios, H. Bailey, W. Gilly and F. P. Chavez. 2008. Oxygen 

declines and the shoaling of the hypoxic boundary in the California Current. Geophysical Research Letters

35 (12).

Cai, W. S. Borlace, M. Lengaigne, P. van Rensch, M. Collins, G. Vecchi, A. Timmermann A. Santoso, M.J. 

McPhaden, L. Wu, M.H. England, G. Wang, E. Guilyardi, and F. Jin. 2013. Increasing Frequency of 

Extreme El Niño Events Due to Greenhouse Warming. Nature Climate Change 4: 111-16.

Canino, M., and R.C. Francis. 1989. Rearing of Sebastes larvae (Scorpaenidae) in static culture Fisheries Research 

Institute, University of Washington, School of Fisheries, Seattle, WA.

Cury, P. and C. Roy. 1989. Optimal environmental window and pelagic fish recruitment success in upwelling areas. 

Canadian Journal of Fisheries and Aquatic Sciences 46 (4):670-680.

Deutsch, C., S. Emerson and L. Thompson. 2005. Fingerprints of climate change in North Pacific oxygen. 

Geophysical Research Letters 32 (16).

Gharrett, A. J., R. J. Riley and P. D. Spencer. 2011. Genetic analysis reveals restricted dispersal of northern rockfish 

along the continental margin of the Bering Sea and Aleutian Islands. Transactions of the American 

Fisheries Society 141 (2):370-382.

Gulf of the Farallones National Marine Sanctuary (GFNMS). 2008. Management Plan. 

http://farallones.noaa.gov/manage/plan.html. 

He, X., D. E. Pearson, E. J. Dick, J. C. Field, S. Ralston and A. D. MacCall. 2011. Status of the widow rockfish 

resource in 2011. Santa Cruz, CA: National Marine Fisheries Service, Southwest Fisheries Science Center.

Hamilton, T.J., Holcombe, A. and Tresguerres, M. 2013. CO2-induced ocean acidification increases anxiety in 

Rockfish via alteration of GABAA receptor functioning. Proceedings of the Royal Society B: Biological 

Sciences 281(1775).

Harvey, C.J. 2005. Effects of El Niño Events on Energy Demand and Egg Production of Rockfish (Scorpaenidae: 

Sebastes): A Bioenergetics Approach. Fishery Bulletin 103 (71):71-83.

Keeling, R. F. and H. E. Garcia. 2002. The change in oceanic O2 inventory associated with recent global warming. 

Proceedings of the National Academy of Sciences 99 (12):7848-7853.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp. 

Love, M. S., M. Yoklavich, and L. Thorstein. 2002. The rockfishes of the Northeast Pacific. University of California 

Press. 404 pages.

Marty, G.D., A. Hoffman, M.S. Okihiro, K. Hepler and D. Hanes. 2003. Retrospective analysis: bile hydrocarbons 

and histopathology of demersal rockfish in Prince William Sound, Alaska, after the Exxon Valdez oil spill. 

Marine Environmental Research 56(5): 569-584.

Miller, J. and A. Shanks. 2004. Evidence for limited larval dispersal in black rockfish (Sebastes melanops): 

implications for population structure and marine-reserve design. Canadian Journal of Fisheries and Aquatic 

Sciences 61 (9):1723-1735.

Munday, P.L, D.L. Dixson, J.M. Donelson, G.P. Jones, M.S. Pratchett, G.V. Devitsina, and K.B. Døving. 2009. 

Ocean acidification impairs olfactory discrimination and homing ability of a marine fish. Proceedings of 

the National Academy of Sciences 106:1848-1852. 

National Marine Fisheries Service (NMFS). 2013. Proposed Designation of Critical Habitat for the Distinct 

Population Segment of Yelloweye Rockfish, Canary Rockfish, and Bocaccio. Draft Biological Report. 

National Marine Fisheries Service, Northwest Region, Protected Resources Division.

Palsson, W. A., R. E. Pacunski and T. R. Parra. 2005. GASP! The response of marine fishes to water with low 

dissolved oxygen in southern Hood Canal, Washington. 2005 Puget Sound Georgia Basin Research 

Conference Proceedings.

295
Palsson, W. A., R. E. Pacunski, T. R. Parra, and J. Beam. 2008. The effects of hypoxia on marine fish populations in 

southern Hood Canal, Washington. American Fisheries Society Symposium. Volume 64, pages 255 to 280.

Sarmiento, J. L., T. M. Hughes, R. J. Stouffer and S. Manabe. 1998. Simulated response of the ocean carbon cycle to 

anthropogenic climate warming. Nature 393 (6682):245-249.

Starr, R. M., J. M. Cope and L. A. Kerr. 2002. Trends in Fisheries and Fishery Resources Associated with the 

Monterey Bay National Marine Sanctuary from 1981-2000. La Jolla, CA: California Sea Grant College 

Program, University of San Diego, California.

296
Carbon Storage and Sequestration1

 

Executive Summary 

California’s coastal wetlands provide 

carbon storage and sequestration 

through the accumulation and longterm storage of organic and inorganic 

carbon material via various biological 

and physical processes. Coastal 

wetlands in the United States sequester an estimated 5 Tg C yr-1, which accounts for 

approximately 1-2% of the carbon sink (Chmura et al. 2003). Coastal wetlands in the Northcentral California coastal region play an important role in mitigating the impacts of 

anthropogenic carbon emissions. Key climate sensitivities identified by workshop participants 

include sea level rise, extreme storm events, and sea surface temperature. Key non-climate 

sensitivities identified include pollution, land use change, recreation, and roads/armoring. Carbon 

storage can occur almost anywhere in the North-central California coastal region. Carbon storage 

and sequestration potential in the San Francisco Bay is likely high, and as such, any future policy 

decisions regarding this region may want to take this into consideration. Recently, attention has 

significantly increased on the establishment of national and global carbon markets. The 

establishment of such a market system could significantly increase the value of naturally 

occurring carbon storage and sequestration systems, and could incentivize the restoration, 

preservation, and maintenance of coastal wetland habitats. 

Sensitivity 

I. Sensitivity of ecosystem service components 

Sensitivity of the provision of the ecosystem service to climate and climate-driven changes: 

Low-Moderate

• Confidence of workshop participants: Moderate

Climate and climate-driven changes identified: sea level rise, storminess, and sea surface 

temperature

Climate and climate-driven changes that may benefit the provision of the ecosystem service: 

decreased ocean pH

• Description of benefit: Lower ocean pH, or more acidic waters, may be beneficial to sea

grass by increasing photosynthetic productivity, thus increasing carbon uptake and 

storage.

Additional participant comments

Upper marshlands will be more sensitive to drought conditions, while lower marshlands will be 

more sensitive to sea level rise. 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

Carbon Storage Score Confidence 

Sensitivity 3 Moderate 2 Moderate

Exposure 5 High 3 High

Adaptive Capacity 2 Low-Moderate 3 High

Vulnerability 4 Moderate-High 3 High

297
Supporting literature

Sea level rise

The impacts of sea level rise on carbon storage and sequestration in marine ecosystems will 

depend upon several factors including: vertical accretion rates (influenced by the deposition of 

inorganic sediments or the accumulation and burial of organic material), compaction and 

subsidence rates, and the ability of wetlands to expand and/or migrate. Rising sea levels may 

initially increase estuarine surface area and result in increased plant biomass production and 

sediment deposition, enhancing carbon storage in regional tidal marshes (DeLaune and White 

2012, South Bay Salt Pond Restoration Project 2015). However, rates of sea level rise that 

exceed the vertical accretion rate of sediment and organic material will eventually drown lowlying estuarine areas (Kirwan and Temmerman 2009, Mudd et al. 2009), reducing carbon storage 

by eliminating wetland habitat and by enhancing erosion of wetland soils that currently store 

significant carbon (DeLaune and White 2012). Coastal wetlands that are more dependent on 

organic accumulation rather than inorganic sediment deposition will likely be more impacted by 

rising sea levels (Stevenson et al. 1986, Stevenson and Kearney 2009). Salt marshes located in 

estuaries with low tidal ranges are expected to be more sensitive to rising sea levels due to 

decreased rates of sediment transport and vertical accretion (Simas et al. 2001). The impacts of 

rising sea levels may be negligible on coastal wetlands that are able to vertically accrete at rates 

that equal or exceed rates of sea level rise. 

Storminess

Climate change is expected to result in more frequent, extreme storm events with larger storm 

surges, higher winds, and increased short duration/high precipitation events, all of which will 

affect rates of sediment deposition and erosion (Simas et al. 2001) and overall wetland extent, 

influencing carbon storage potential (DeLaune and White 2012). Storm intensity and direction, 

wind and wave conditions, and local geomorphological conditions all influence the extent of 

storm impacts on coastal wetlands (Simas et al. 2001). For example, winter wave heights, driven 

by extra-tropical cyclones in the North Pacific, can be in excess of 8 m (Wingfield and Storlazzi 

2007), and large storm surges can kill wetland vegetation, increasing the likelihood of future 

erosion and associated carbon losses or transport of carbon-rich sediment to nearshore or shelf 

habitats (DeLaune and White 2012). Changes in wave height and direction can also expose 

previously sheltered areas to significant levels of erosion (Sallenger et al. 2002) and/or affect 

regional sediment transport and deposition processes (Scavia et al. 2002), which may have 

significant negative impacts to sensitive coastal wetland habitats and affect their ability to trap 

sediment and sequester carbon. 

Sea surface temperature

Changes in sea surface temperatures are greater in estuaries relative to changes along the outer 

coast, and an overall increase in water temperature may lead to increased growth and distribution 

of coastal wetlands (Scavia et al. 2002), enhancing the capacity for estuarine habitat to sequester 

carbon. However, soil carbon density declines with increased temperature, likely due to 

enhanced decay rates (Chmura et al. 2003). Increasing sea surface temperatures may also result 

in the range expansion of both native and non-native species into new areas (Williams and 

Grosholz 2008), which can impact long-term carbon storage and sequestration (see invasive 

species section below), and may impact the incidence of disease, estuarine circulation, dissolved 

oxygen (DO) levels, and key physiological processes in temperature-sensitive primary-producing 

298
estuarine species, potentially impacting the capacity for marsh and estuarine habitat to sequester 

carbon. 

II. Sensitivity to disturbance regimes

Disturbance regimes identified: flooding, wind, storms, and disease2

Overall sensitivity of the provision of the ecosystem service to disturbance regimes: Moderate

• Confidence of workshop participants: Moderate

Additional participant comments 

Flooding and storm disturbance regimes will impact both salt marshes and seagrasses, but wind 

and disease disturbance regimes may only impact seagrasses. 

Supporting literature

Wind 

Winds influence estuarine circulation, salinity structure, and flushing rates (residence times) 

(Geyer 1997). Estuarine circulation is inhibited by onshore winds, which may also increase 

salinity gradients and reduce flushing rates, while offshore winds may enhance flushing and 

outflow, and reduces alongshore salinity gradients (Geyer 1997). A well-flushed estuary is more 

robust, healthy, and resilient than a poorly flushed estuary, due to the inhibition of sedimentation 

and depleted dissolved oxygen (Wolanksi 2007), enhancing carbon sequestration capacity. 

Flooding 

Coastal wetlands are sensitive to changes in flooding patterns and sediment loading (Ramsar 

2002), which can impact vertical accretion rates. Although coastal wetlands are tolerant of 

periodic flooding, a flooding threshold likely exists, and longer flood durations and/or more 

frequent flooding can increase erosion and decrease organic plant contributions, accelerating 

wetland habitat deterioration (Kirwan and Megonigal 2013) and reducing current and future 

carbon storage (DeLaune and White 2012). 

III. Sensitivity and exposure to non-climate stressors Non-climate stressors identified: land use changes, overwater/underwater structures, coastal 

roads and armoring, invasive species, pollution and poisons, recreation, aquaculture, and 

dredging2 

Degree to which non-climate stressors affect the provision of the ecosystem service: ModerateHigh

• Confidence of workshop participants: High

Degree to which non-climate stressors affect the sensitivity of the provision of the ecosystem 

service to climate change: Moderate

• Confidence of workshop participants: Moderate

Additional participant comments

Excessive nutrient pollution may negatively impact seagrass through increases in epiphytic 

algae. Aquaculture can displace seagrass beds. Overwater/underwater structures increase 

2 Though peer-reviewed literature may exist, staff review was unable to locate supporting literature for this stressor. 

299
shading, which can negatively impact seagrass beds, and land use changes can negatively impact 

salt marshes.

Supporting literature

Land use changes

Reclamation, engineering, and urbanization have resulted in the loss of extensive areas of 

seagrass and salt marsh (Mcleod et al. 2011). Increased sedimentation from land use changes 

may result in the burying of vegetative habitat or increase the duration of estuary mouth closure. 

Freshwater diversions for agriculture and other human uses can result in hypersaline conditions, 

reduced estuarine circulation, or more persistent closures of estuary mouths due to reduced tidal 

prism (ONMS 2010), all of which can negatively impact vegetative habitats and long-term 

carbon storage and sequestration. 

Overwater/underwater structures

Overwater and underwater structures alter light regimes, wave energy, sediment and transport

processes, substrate, and water quality, which can limit plant growth and recruitment 

(Nightingale and Simenstad 2001), decreasing carbon storage potential. 

Coastal roads and armoring

Coastal armoring and road construction can prevent the inland migration or expansion of coastal 

wetland habitats in response to sea level rise. Where the inland border of coastal wetland habitats 

abuts roads, levees, or other armored structures, an accelerated loss of habitat may be expected 

(Dugan et al. 2008). Road construction and coastal armoring continues to be a problem in the 

study region, specifically in Bolinas Lagoon, Tomales Bay, and other areas of coastal 

development. Although the impacts of these structures are generally localized, they can be severe

as they can result in the conversion and loss of habitats that sequester carbon (ONMS 2010). 

Invasive species

Invasive and non-native species can cause changes in community species composition in coastal 

wetlands, which can result in changes to above-ground and below-ground carbon pools 

(Ehrenfeld 2003) and long-term carbon storage and sequestration. The net effect of invasive and 

non-native species on long-term carbon storage and sequestration will depend on numerous 

factors such as soil type, carbon mineralization rates, differences in root-to-shoot ratios, plant 

biomass, and productivity between native and invasive or non-native species (Ehrenfeld 2003). 

Pollution and poisons 

Coastal eutrophication, resulting from excess nutrient runoff from terrestrial sources, leads to 

increased epiphytic algae and macroalgae, which reduces available light for primary production. 

This can result in extensive loss of coastal vegetation, such as seagrass beds and saltmarshes

(Duarte 2002, Mcleod et al. 2011) that store and sequester carbon. 

IV. Other sensitivities: none identified

300
Adaptive Capacity 

I. Intrinsic value

Value of the ecosystem service to people: Low-Moderate 

• Confidence of workshop participants: Low

Degree to which people are willing to change their behavior to ensure provision of the ecosystem 

service: Low

• Confidence of workshop participants: High

Economic drivers that play a role in the management of the ecosystem service: Regulated carbon 

markets for carbon credits may drive efforts to more actively manage this ecosystem service.

Can the ecosystem service be accessed elsewhere, and how important is it to ensure provision of 

the ecosystem service in its current location(s): Carbon storage and sequestration can occur in a 

variety of terrestrial and marine locations. 

Additional participant comments

The deep sea has a very large capacity to store and sequester carbon. Currently there is only a 

limited awareness of the issue on a local level. The carbon storage and sequestration capacity in 

the region of interest is high if marshes in the San Francisco Bay are included. 

Supporting literature

Tidal marshes, seagrasses, and mangroves are identified by the Blue Carbon Initiative as the 

three coastal habitats that best accumulate, store, and sequester carbon (termed “blue carbon”; 

Howard et al. 2014). Restoration and conservation of these habitats could receive significant 

funding if blue carbon were included in market-based climate policy mechanisms, including 

regulated cap-and-trade; however, significant information needs exist, including scientific and 

economic analysis, and policy design and advocacy (Ullman et al. 2012). 

Past and ongoing management activities that have reduced impacts to the region’s estuaries and 

enhanced the health and resilience of carbon-sequestering coastal habitats include 

implementation of best management practices to reduce runoff, the closure and restoration of a 

mercury mine, the development of a vessel management plan to address illegal moorings in 

eelgrass, and the removal of abandoned vessels from Tomales Bay (ONMS 2010). Information 

on current management and restoration activities can be found for Bolinas Lagoon 

(http://farallones.noaa.gov/eco/bolinas/bolinas.html) and Tomales Bay 

(http://farallones.noaa.gov/eco/tomales/tomales.html).

II. Management potential

Rigidity / specificity of rules governing the provision of the ecosystem service or the areas that 

provide the ecosystem service: Moderate-High

• Confidence of workshop participants: Moderate

Conflicts with other services in the region: none 

Services that mutually benefit from the provision of the ecosystem service: food production 

(aquaculture)

301
Likelihood of managing or alleviating climate change impacts on the provision of the ecosystem 

service: The likelihood will depend on public support and the political will to fund restoration 

and management efforts. 

III. Other adaptive capacity factors: none identified

Additional participant comments

A good knowledge base currently exists for how to effectively restore mashes and seagrass beds. 

Exposure 

I. Future climate exposure3 

Degree to which the provision of the ecosystem service is likely to be affected by climate 

change: High

• Confidence of workshop participants: High 

Future climate and climate-driven changes identified: sea level rise, storminess, sea surface 

temperature, ocean pH, coastal erosion, and precipitation 

Literature Cited

Chmura, G. L., S. C. Anisfeld, D. R. Cahoon, and J. C. Lynch. 2003. Global carbon sequestration in tidal, saline 

 wetland soils, Global Biogeochemical Cycles 17(1111), doi:10.1029/2002GB001917, 4.

DeLaune, R.D. and J.R. White. 2012. Will coastal wetlands continue to sequester carbon in response to an increase 

in global sea level?: a case study of the rapidly subsiding Mississippi river deltaic plain. Climatic Change

110 (1-2):297-314.

Duarte, C.M. 2002. The future of seagrass meadows. Environ Conserv 29: 192-206.

Dugan, J.E., D.M. Hubbard, I. F. Rodil, D. L. Revell and S. Schroeter. 2008. Ecological effects of coastal armoring

 on sandy beaches. Marine Ecology 29: 160-170.

Ehrenfeld, J.G. 2003. Effects of Exotic Plant Invasions on Soil Nutrient Cycling Processes. Ecosystems 6(6): 503-

523. doi: 10.1007/s10021-002-0151-3.

Geyer, W.R. 1997. Influence of Wind on Dynamics and Flushing of Shallow Estuaries. Estuarine, Coastal and Shelf 

Science 44: 713-722.

Howard, J., S. Hoyt, K. Isensee, E. Pidgeon, M. Telszewski. (eds.) 2014. Coastal Blue Carbon: Methods for 

assessing carbon stocks and emissions factors in mangroves, tidal salt marshes, and seagrass meadows. 

Conservation International, Intergovernmental Oceanographic Commission of UNESCO, International 

Union for Conservation of Nature. Arlington, Virginia, USA.

Kirwan, M. L. and J. P. Megonigal. 2013. Tidal wetland stability in the face of human impacts and sea-level rise. 

Nature 504 (7478):53-60.

Kirwan, K. and S. Temmerman. 2009. Coastal marsh response to historical and future sea-level acceleration. 

Quarterly Science Reviews 28(17): 1801-1808.

Office of National Marine Sanctuaries (ONMS). 2010. Gulf of the Farallones National Marine Sanctuary Condition 

Report. U.S. Department of Commerce, National Oceanic and Atmospheric Administration, Office of 

National Marine Sanctuaries, Silver Spring, MD. 97 pp.

Mcleod, E., G.L. Chumra, S. Bouillon, R. Salm, M. Björk, C.M. Duarte, C.E. Lovelock, W.H. Schlesinger, and B.R. 

Silliman. 2011. A blueprint for blue carbon” toward an improved understanding of the role of vegetated 

coastal habitats in sequestering CO2. Front Ecol Environ 9(10): 552-560. doi: 10.1890/110004.

Mudd S.M., S.M. Howell, and J.T. Morris. 2009. Impact of dynamic feedbacks between sedimentation, sea-level 

3 Supporting literature for future exposure to climate factors is provided in the introduction.

302
rise, and biomass production on near-surface marsh stratigraphy and carbon accumulation. Estuarine, 

Coastal and Shelf Science 82:377-389.

Nightingale, B., and C.A. Simenstad. 2001. Overwater structures: marine issues. Washington State Transportation 

Commission. Seattle, Washington.

The Ramsar Convention on Wetlands (Ramsar). 2002. Climate Change and Wetlands: Impacts, Adaptation and 

Mitigation. Ramsar COP8 DOC. 11 Information Paper. Available at 

http://archive.ramsar.org/cda/es/ramsar-documents-standing-ramsar-cop8-doc-11/main/ramsar/1-31-

41%5E17764_4000_2__.

Sallenger, A.H., W. Krabill, J. Brock, R. Swift, S. Manizade, H. Stockdon. 2002. Sea-cliff erosion as a function of 

beach changes and extreme wave runup during the 1997-1008 El Nino. Marine Geology 187:279-97.

Scavia D., Field J.C., Boesch D.F., Buddemeier R.W., Burkett V., Cayan D.R., Fogarty M., Harwell 

M.A., Howart R.W., Mason C. 2002. Climate change impacts on U.S. coastal and marine 

ecosystems. Estuaries 25(2):149-64. 

Simas, T., J.P. Nunes, and J.G. Ferreira. 2001. Effects of global climate change on coastal salt marshes. Ecological 

Modeling 139: 1-15.

Stevenson, J. C., L. G. Ward, and M. S. Kearney. 1986. Vertical accretion in marshes with varying rates of sea level 

rise. Pages 241–259 in D. Wolf (ed.), Estuarine Variability. New York: Academic Press. 

Stevenson, J.C. and M.S. Kearney. 2009. Impacts of global climate change and sea level rise on tidal wetlands. In: 

Silliman, B.R., Grosholz, E.D. and Bertness, M.D. (eds). Human Impacts on Salt Marshes. Berkeley, CA: 

University of California Press. 

South Bay Salt Pond Restoration Project. 2015. Climate Change and Sea Level Rise. Accessed March 2015. 

http://www.southbayrestoration.org/climate/. 

Ullman, R., V. Bilbao-Bastida, G. Grimsditch. 2013. Including Blue Carbon in climate market mechanisms. Ocean 

and Coastal Management 83: 15-18.

Williams, S.L. and E.D. Grosholz. 2008. The invasive species challenge in estuarine and coastal environments: 

marrying management and science. Estuaries and Coasts 31(1): 3-20.

Wingfield, D.K. and C.D. Storlazzi. 2007. Variability in oceanographic and meteorologic forcing along Central 

California and its implications on nearshore processes. Journal of Marine Systems 68: 457-472.

Wolanksi, E. 2007. Estuarine Ecohydrology. Amsterdam, The Netherlands: Elsevier. 168 p.

303
Flood and Erosion Protection1

Executive Summary

Estuarine, beach, and dune coastal 

ecosystems provide natural protection 

against flooding and erosion from 

storms and storm surges to low-lying 

coastal areas. Key climate sensitivities 

identified by workshop participants 

include changes in precipitation, storm events, and sea level rise. Key non-climate sensitivities 

include land use change, overwater/underwater structures, roads/armoring, and sand mining. 

Coastal flood and erosion protection is primarily provided by two habitats, estuaries (salt 

marshes) and beaches and dunes. Given room to migrate and undisturbed supplies of naturally 

occurring sediment, these habitats are generally resilient and can respond to changing climatic 

conditions, although shifts may also occur in response to naturally occurring climatic variations. 

Attempts to manage and mitigate the erosion of cliffs and beach areas through the use of 

armoring and other measures disrupts the natural supply and transport of sediments critical for 

maintaining these habitats.

Sensitivity

I. Sensitivity of ecosystem service components Sensitivity of the provision of the ecosystem service to climate and climate-driven changes: High

• Confidence of workshop participants: High 

Climate and climate-driven changes identified: precipitation, storminess, coastal erosion and 

flooding, and sea level rise

Climate and climate-driven changes that may benefit the provision of the ecosystem service: 

none identified 

Additional participant comments

Sea level rise is drowning wetlands that have no room to move, and increased storm intensity is 

increasing erosion. 

Supporting literature

Precipitation

Changing patterns in precipitation will impact sediment deposition, river flows, erosion, and 

flooding. The seasonality of estuarine hydrology, including rainfall and water inflow from rivers 

into estuaries, influences the transport and deposition of sediments. Climate change may result in 

more frequent short duration/high precipitation events that may lead to increased frequency and 

severity of flooding events in estuaries. 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

Carbon Storage Score Confidence 

Sensitivity 5 High 3 High

Exposure 5 High 3 High

Adaptive Capacity 3 Moderate 3 High

Vulnerability 4 Moderate-High 3 High

304
Storminess / coastal erosion / flooding 

Climate change is expected to result in more frequent extreme storm events with larger storm 

surges, higher winds, and increased short duration/high precipitation events, all of which will 

affect rates of sediment deposition and erosion (Simas et al. 2001). Waves are the main driver of 

beach and dune erosion, but storm-driven winds can also impact beach and dune habitats by 

moving unconsolidated sediments (Scavia et al. 2002). Winter wave heights, driven by extratropical cyclones in the North Pacific, can be in excess of 8 m (Wingfield and Storlazzi 2007). 

Waves can erode shorelines, alter sediment transport and deposition processes (Scavia et al. 

2002), and may result in the inundation of beach and dune areas, forcing the landward retreat of 

these habitats and increasing the risk of coastal flooding (Storlazzi and Griggs 2000, Feagin et al. 

2005, Wingfield and Storlazzi 2007). Changes in wave height and direction, in response to both 

climate change and natural variability, will expose previously sheltered beaches to significant 

levels of erosion (Sallenger et al. 2002), which may increase the potential for localized flooding 

and erosion. 

Sea level rise

Sea level rise will allow waves and storm surges to penetrate further inland, making coastal areas 

more susceptible to flooding and erosion (Knowles and Cayan 2002, Faegin et al. 2005). Rising 

sea levels will result in increased tidal inundation and, when combined with higher storm surges, 

larger more energetic waves, and increased short duration/high precipitation events, will increase 

the vulnerability of low-lying coastal areas to flooding and erosion (Feenstra et al. 1998, Dolan 

and Walker 2004). 

Sea level rise can inundate beach and dune habitats, increasing rates of shoreline erosion and 

forcing the upland retreat of these habitats (Faegin et al. 2005). Beach and dune habitats could 

incur a reduction in areal extent and/or an increase in fragmentation, shifting from continuous 

habitat to narrower, steeper, and isolated pocket beaches where man-made or natural barriers 

block upland retreat (Largier et al. 2010). Sea level rise can also disrupt successional dynamics 

and degrade habitat quality by preventing the formation of mature coastal dune vegetation 

communities (Faegin et al. 2005). 

The impacts of sea level rise on coastal wetlands will depend upon several factors including 

vertical accretion rates, compaction rates, and the ability of wetlands to migrate. Coastal 

wetlands that vertically accrete at rates less than projected rates of sea level rise will eventually 

drown, resulting in the loss of vegetative habitat and a consequent reduction of flood and erosion 

protection (Largier et al. 2010, Ackerly et al. 2012). Coastal wetlands that are more dependent on 

organic accumulation rather than inorganic sediment deposition will likely be more impacted by 

rising sea levels (Stevenson et al. 1986, Stevenson and Kearney 2009). 

II. Sensitivity to disturbance regimes

Disturbance regimes identified: wind, flooding, and storms 

Overall sensitivity of the provision of the ecosystem service to disturbance regimes: ModerateHigh

• Confidence of workshop participants: High

305
Additional participant comments 

In general, habitats that provide flood and erosion protection are resilient and adequately provide 

this ecosystem service under normal storm conditions. However, these habitats may be unable to 

provide adequate flood and erosion protection due to projected future changes in the frequency 

and intensity of extreme storm events. 

Supporting literature

Wind 

Winds influence the formation and erosion of dunes and impact estuarine circulation, salinity 

structure, and flushing rates (residence times) (Geyer 1997). Estuarine circulation is inhibited by 

onshore winds, which may also increase salinity gradients and reduce flushing rates, while 

offshore winds may enhance flushing and outflow as well as alongshore salinity gradients (Geyer 

1997). Dunes, formed by the accumulation of sediments transported and deposited by winds, are 

sensitive to changes in prevailing wind patterns. Excessive winds can erode and destroy dunes, 

especially those composed of unconsolidated sediments (USGS 2014). 

Flooding 

Coastal wetlands are sensitive to changes in flooding patterns and sediment loading (Ramsar 

2002), which can impact vertical accretion rates. Although coastal wetlands are tolerant of

periodic flooding, a flooding threshold likely exists, and longer flood durations and/or more 

frequent flooding can increase erosion and decrease organic plant contributions, accelerating 

wetland habitat deterioration and reducing future flood protection (Kirwan and Megonigal 2013). 

Storms

Storms constantly reshape coastal wetlands and beach and dune habitats through erosive and 

depositional processes. Energetic winter storms tend to be more erosive. If beach erosion is 

severe enough, or waves are large enough, waves can wash over and erode dune areas (CERC 

1984). However, dunes may also be replenished by strong onshore winds, often associated with 

winter storms, through the transport and deposition of sand from beach areas onto dune areas. 

The overall impact of storms on beach and dune erosion will depend on specific 

geomorphological conditions, the intensity and direction of storms, as well as tides, currents, and 

other physical factors (Moran 2011). 

III. Sensitivity and exposure to non-climate stressors

Non-climate stressors identified: land use changes, overwater/underwater structures, coastal 

roads and armoring, and sand mining 

Degree to which non-climate stressors affect the provision of the ecosystem service: High

Confidence of workshop participants: High

Degree to which non-climate stressors affect the sensitivity of the provision of the ecosystem 

service to climate change: High

• Confidence of workshop participants: High

Additional participant comments

Land use changes have already destroyed much of this ecosystem service. Sand mining removes 

the sediment in the littoral cell. 

306
Supporting literature

Land use change

Land use change from dams, agriculture, coastal development and coastal infrastructure has 

significantly reduced the extent of coastal wetland and beach and dune habitats. For example, 

human development in the Central Bay from 1855-1979 destroyed significant tidal marsh and 

intertidal mudflat habitat, resulting in a 4% overall areal loss of these critical habitats in San 

Francisco Bay (Barnard et al. 2013). In addition, estuarine and coastal sediment regimes follow 

predictable patterns in relation to land use change, exhibiting a period of increased sedimentation 

associated with construction or activity, followed by reduced sediment supply as site and 

watershed management activities (e.g., dams, restoration projects) reduce streamflow variability 

and erosion potential (Barnard et al. 2013). Increased sedimentation from land use changes may

result in the burying of oyster and eelgrass habitat (ONMS 2010), undermining their ability to 

trap and stabilize sediment and dampen incoming wave force (Borsje et al. 2011). Alternatively, 

reduced sediment supply as a result of intensified upstream watershed management and/or 

sediment reduction projects can enhance the vulnerability of sediment-dependent habitats (e.g., 

coastal wetlands) to sea level rise (Knowles et al. 2010). Freshwater diversions for agriculture 

and other human uses can result in hypersaline conditions, slow circulation, and the persistent 

closing of estuary mouths due to reduced tidal prism (ONMS 2010), affecting wetland plant 

composition, habitat productivity, and ecosystem service provision (Watson and Byrne 2009). 

Overwater/underwater structures

Overwater and underwater structures can alter the supply and transport of sediment and impair 

the resiliency of estuary and beach/dune habitats. Dams, debris basins, and erosion reduction 

projects (e.g., installing riparian rip-rap) in upland watersheds can trap sediments and alter peak 

flows, which reduces sediment transport to estuary and beach/dune systems and can increase 

littoral cell sediment deficits and the potential for erosion (Willis and Griggs 2003, Slagel and 

Griggs 2008, Largier et al. 2010, Hestir et al. 2013), undermining the ability of these habitats to 

keep pace with sea level rise (Knowles 2010). For example, multiple dam projects on the 

Russian River reduced annual coarse-grained sediment supplies by more than 30% (Slagel and 

Griggs 2008). 

Coastal roads and armoring

Coastal armoring and road construction prevent the inland migration of estuaries and beach/dune 

habitats in response to sea level rise, increase passive erosion, and increase the sensitivity of 

estuaries and beach/dune habitats to climate and climate-driven factors. Where the inland border 

of these habitats abuts roads, levees, or other armored structures, an accelerated loss of habitat 

may be expected (Fletcher et al. 1997, Dugan et al. 2008). Passive erosion related to armoring or 

road structures can shift habitat zones down the beach profile by “drowning” upper beach areas, 

disproportionally degrading upper and mid-beach habitat (Dugan et al. 2008). These effects will 

become more pronounced with sea level rise as these structures interact with waves and tides. In 

addition, armoring can displace beach habitat, thus reducing beach extent (Dugan et al. 2008). 

Road construction and coastal armoring continues to be a problem in the study region, 

specifically in Bolinas Lagoon, Tomales Bay, and other areas of coastal development. Although 

the impacts of these structures are generally localized, they can be severe as they can result in the 

conversion and loss of habitats and increase erosion rates (ONMS 2010). Coastal armoring is 

projected to increase in the future, but beach nourishment is now being used more frequently as 

an alternative (Defeo et al. 2009).

307
Sand mining 

In general, open coastal and marine ecosystem sediment dynamics in north-central California are 

linked with anthropogenic activity within regional sediment-sheds, including sand mining, 

dredging, and aggregate mining (Barnard et al. 2013 and citations therein, Hein et al. 2013 and 

citations therein). Over the last century, the permanent removal of >200 million cubic meters of 

sediment from the San Francisco Bay is thought to have contributed to significant erosion of 

coastal beaches and the ebb tidal delta (Hein et al. 2013 and citations therein), undermining flood 

protection. Sand mining and aggregate mining are on-going activities, particularly in the Central 

Bay and Suisun Bay (Hanson et al. 2004, Barnard et al. 2013 and citations therein), and in 

combination with navigation-channel dredging, continue to affect sediment supply to estuarine 

and beach habitats within the study region (Barnard et al. 2013 and citations therein). 

In addition, studies of historical dune erosion rates, both during and after coastal sand mining 

operations along the southern Monterey shoreline, indicate that sand mining operations may lead 

to increased erosion of dunes (Thornton et al. 2006). Griggs and Savoy (1985) suggest that sand 

mining depletes shore-connected shoals, which protect the shoreline by dissipating the energy of 

winter waves, thus allowing more energetic winter waves to reach further onshore and increase 

dune erosion. However, dune erosion rates before and after sand mining operations were not 

statistically significant along the entire coastline, indicating that sand mining may not be the 

causal factor behind increased dune erosion (Thornton et al. 2006). 

IV. Other sensitivities

Other critical factors likely to influence the sensitivity of the provision of the ecosystem service: 

earthquakes and tsunamis2

• Confidence of workshop participants: High (if they occur)

• Confidence of workshop participants in the degree to which these factors influence the 

sensitivity of the ecosystem service provision: High (if they occur)

Adaptive Capacity

I. Intrinsic value

Value of the ecosystem service to people: High 

• Confidence of workshop participants: High 

Degree to which people are willing to change their behavior to ensure provision of the ecosystem 

service: Low-Moderate

• Confidence of workshop participants: High 

Economic drivers that play a role in the management of the ecosystem service: property values, 

infrastructure values, recreational value of beaches and wetlands, nursery value of wetland 

habitat, cultural value, and aesthetic value

Can the ecosystem service be accessed elsewhere, and how important is it to ensure provision of 

the ecosystem service in its current location(s): Because this ecosystem service cannot be 

2 Though peer-reviewed literature may exist, staff review was unable to locate supporting literature for this stressor.

308
accessed elsewhere for human benefit, it is very important that this ecosystem service continues 

to be provided in its current location. 

Additional participant comments

The habitats that contribute to the provision of flood and erosion protection also contribute to the 

provision of many other services that are valued by humans, such as recreational opportunities, 

nursery habitat for animals valued by humans, and cultural and aesthetic values. As such, the 

value of flood and erosion protection depends on the values of the many other services that are 

also provided by the habitats that provide flood and erosion protection. 

II. Management potential

Rigidity / specificity of rules governing the provision of the ecosystem service or the areas that 

provide the ecosystem service: Moderate

• Confidence of workshop participants: Moderate 

Conflicts with other services in the region: There are no perceived conflicts with other ecosystem 

services. 

Services that mutually benefit from the provision of the ecosystem service: recreation, water 

quality, habitat for beach and marsh flora and fauna 

Likelihood of managing or alleviating climate change impacts on the provision of the ecosystem 

service: The likelihood of managing or alleviating climate change impacts will depend on the 

degree of public awareness about current and future climate change impacts on the provision of 

the flood and erosion protection ecosystem service. Restoration of beaches, dunes, and coastal 

wetlands may mitigate the impacts of climate change on the provision of this service.

Additional participant comments

There are guidelines but no rules about the management of this service. A common response to 

coastal erosion and flooding is to utilize built infrastructure rather than maintaining natural 

infrastructure. An unintended consequence of using built infrastructure may be the degradation 

of the natural provision of flood and erosion protection. 

Supporting literature

Coastal habitat restoration and ecosystem engineering, commonly referred to as “living 

shorelines”, may bolster flood and erosion protection services in the face of climate change 

(Borsje et al. 2011, Coastal Conservancy 2012). Protecting, enhancing, and restoring habitats

(e.g., wetlands, oyster beds) and species (e.g., dune and beach vegetation) that provide these 

services reduces the demand for and stress on hard engineering solutions (e.g., seawalls), 

minimizing long-term costs and mitigating the inadvertent interactions of these structures with 

climate change stressors (e.g., inhibited wetland migration) (Borsje et al. 2011). Living shoreline 

initiatives are supported by both the California Climate Change Adaptation Strategy and the 

State Coastal Conservancy Climate Change Policy (Coastal Conservancy 2012). In addition, San 

Francisco Bay has an on-going living shorelines project which aims to evaluate different subtidal restoration techniques and their ability to maintain flood and erosion protection services and 

other habitat functions (San Francisco Bay Living Shorelines Project 2015). 

309
III. Other adaptive capacity factors

Other critical factors that may affect the provision of the ecosystem service: room to migrate

Degree to which these factors affect the provision of the ecosystem service: High

• Confidence of workshop participants: High

Additional participant comments

There is a currently a lot of built infrastructure along the coast. The locations where people are 

interested in the provision of the flood and erosion protection service are also the areas where 

there is limited room for habitats to migrate inland in response to climate change.

Exposure 

I. Future climate exposure3 

Degree of to which the provision of the ecosystem service is likely to be affected by climate 

change: High

• Confidence of workshop participants: High 

Future climate and climate-driven changes identified: sea surface temperature, air temperature, 

ocean pH, salinity, sea level rise, storminess, coastal erosion, and flooding 

Literature Cited

Ackerly, D. D., R. A. Ryals, W. K. Cornwell, S. R. Loarie, S. Veloz, K. D.Higgason, W. L. Silver, and T. E. 

Dawson. 2012. Potential Impacts of Climate Change on Biodiversity and Ecosystem Services in the San 

Francisco Bay Area. California Energy Commission. Publication number: CEC-500-2012- 037.

Barnard, P. L., D. H. Schoellhamer, B. E. Jaffe and L. J. McKee. 2013. Sediment transport in the San Francisco Bay 

coastal system: An overview. Marine Geology 345:3-17. 

Borsje, B. W., B. K. van Wesenbeeck, F. Dekker, P. Paalvast, T. J. Bouma, M. M. van Katwijk and M. B. de Vries. 

2011. How ecological engineering can serve in coastal protection. Ecological Engineering 37 (2):113-122.

Coastal Conservancy. 2012. The San Francisco Bay Living Shorelines: Nearshore Linkages Project. Available at 

http://www.sfbaylivingshorelines.org/Library/SFBayLivingShorelinesProjDes_052412.pdf. 

Coastal Engineering Research Center (CERC). 1984. Shore protection manual. US Government Printing Office, 

Washington, DC, 2 vols.

Defeo, O.A. McLachlan, D. Schoeman, T. Schlacher, J. Dugan, A. Jones, M. Lastra, F. Scapini. 2009. Threats to 

sandy beach ecosystems: a review. Estuar. Coastl. Shelf Sci. 81:1-12.

Dolan, A.H. and I.J. Walker. 2004. Understanding Vulnerability of Coastal Communities to Climate Change Related 

Risks. Journal of Coastal Research 39: 1316-1323. ISSN 0749-0208.

Dugan, J.E., D.M. Hubbard, I. F. Rodil, D. L. Revell and S. Schroeter. 2008. Ecological effects of coastal armoring 

on sandy beachesMarine Ecology 29: 160-170.

Feagin, R.A., D.J. Sherman, and W.E. Grant. 2005. Coastal erosion, global sea-level rise, and the loss of sand dune

plant habitats. Frontiers in Ecology and the Environment 7:359-364.

Feenstra, J.F., I Burton, J.B. Smith, and R.S.J. Tol. 1998. Handbook on Mthods for Climate Change Impact 

Assessment and Adaptation Strategies. Institute for Environmental Studies. United Nations Environment 

Programme.

Fletcher, C. H., R. A. Mullane, B. M. Richmond. 1997. Beach loss along armored shorelines on Oahu, Hawaiian 

Islands. Journal of Coastal Research 13: 209-215.

Geyer, W.R. 1997. Influence of Wind on Dynamics and Flushing of Shallow Estuaries. Estuarine, Coastal and Shelf 

Science 44: 713-722.

3 Supporting literature for future exposure to climate factors is provided in the introduction.

310
Griggs, G.B. and L.E. Savoy. 1985. Living with the California coast: Durham, North Carolina, Duke University 

Press, 393 p.

Hanson, C., Coil, J., Keller, B., Johnson, J., Taplin, J., Monroe, J., 2004. Assessment and Evaluation of the Effects 

of Sand Mining on Aquatic Habitat and Fishery Populations of Central San Francisco Bay and the 

Sacramento–San Joaquin Estuary. Hanson Environmental Inc. Available at: 

http:/www.hansonenvironmentalinc. com/reports.htm. 

Hein, J. R., K. Mizell and P. L. Barnard. 2013. Sand sources and transport pathways for the San Francisco Bay 

coastal system, based on X-ray diffraction mineralogy. Marine Geology 345:154-169.

Hestir, E. L., D. H. Schoellhamer, T. Morgan-King and S. L. Ustin. 2013. A step decrease in sediment concentration 

in a highly modified tidal river delta following the 1983 El Niño floods. Marine Geology 345:304-313.

Kirwan, M. L. and J. P. Megonigal. 2013. Tidal wetland stability in the face of human impacts and sea-level rise. 

Nature 504 (7478): 53-60.

Knowles, N. 2010. Potential inundation due to rising sea levels in the San Francisco Bay region. San Francisco 

Estuary and Watershed Science 8 (1).

Knowles, N. and D.R. Cayan. 2002. Potential effects of global warming on the Sacramento/San Joaquin watershed 

 and the San Francisco estuary. Geophysical Research Letters 29:1891.

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp.

Moran, J. 2011. Ocean Studies: Introduction to Oceanography, Third Edition. American Meteorological Society. 

Boston MA. 

Office of National Marine Sanctuaries (ONMS). 2010. Gulf of the Farallones National Marine Sanctuary Condition 

Report. U.S. Department of Commerce, National Oceanic and Atmospheric Administration, Office of 

National Marine Sanctuaries, Silver Spring, MD. 97 pp.

The Ramsar Convention on Wetlands (Ramsar). 2002. Climate Change and Wetlands: Impacts, Adaptation and 

Mitigation. Ramsar COP8 DOC. 11 Information Paper. Available at: 

http://archive.ramsar.org/cda/es/ramsar-documents-standing-ramsar-cop8-doc-11/main/ramsar/1-31-

41%5E17764_4000_2__.

Sallenger, A.H., W. Krabill, J. Brock, R. Swift, S. Manzinar, and H.F. Stockdon. 2002. Sea-Cliff erosion as a

function of beach changes and extreme wave run-up during the 1997-98 El Niño. Marine Geology 

187:279-297.

San Francisco Bay Living Shorelines Project. 2015. San Francisco Bay Living Shorelines Project. Accessed March 

2015. http://www.sfbaylivingshorelines.org/sf_shorelines_about.html.

Scavia, D, J.C. Field, D.F. Boesch, R.W. Buddemeier, V. Burkett, D.R. Cayan, M. Fogarty, M.A. Harwell. R.W. 

Howarth, C. Mason, D.J. Reed, T.C. Royer, A.H. Sallenger, J.G. Titus. 2002. Climate Change Impacts on 

U.S. Costal and Marine Ecosystems. Estuaries 25(2): 149-164.

Simas, T., J. Nunes and J. Ferreira. 2001. Effects of global climate change on coastal salt marshes. Ecological 

Modeling 139 (1):1-15.

Slagel, M. J. and G.B. Griggs. 2008. Cumulative Losses of Sand to the California Coast by Dam Impoundment.

 Journal of Coastal Research 24(3): 571-584.

Stevenson, J. C., L. G. Ward, and M. S. Kearney. 1986. Vertical accretion in marshes with varying rates of sea level 

rise. Pages 241–259 in D. Wolf (ed.), Estuarine Variability. New York: Academic Press. 

Stevenson, J.C. and M.S. Kearney. 2009. Impacts of global climate change and sea level rise on tidal wetlands. In: 

Silliman, B.R., Grosholz, E.D. and Bertness, M.D. (eds). Human Impacts on Salt Marshes. Berkeley, CA: 

University of California Press.

Storlazzi, C. and G. Griggs. 2000. Influence of El Niño-Southern Oscillation (ENSO) events on the evolution of

Central California's shoreline. GSA Bulletin 112 (2): 236-249.

Thornton, E. B., A. Sallenger, J.C. Sesto, L. Egley, T. McGee, and R. Parsons. 2006. Sand mining impacts on long- 

 term dune erosion in southern Monterey Bay. Marine Geology 229: 45-58.

United States Geological Survey (USGS). 2014. Coasts: Sand and Dunes. Accessed November 11 from: 

 http://geomaps.wr.usgs.gov/parks/coast/dunes/

Watson, E. B. and R. Byrne. 2009. Abundance and diversity of tidal marsh plants along the salinity gradient of the 

San Francisco Estuary: implications for global change ecology. Plant Ecology 205 (1):113-128.

Willis, C.M. and G.B. Griggs. 2003. Reductions in Fluvial Sediment Discharge by Coastal Dams in California and

implications for Beach Sustainability. Journal of Geology 111:167-182.

311
Wingfield, D.K. and C.D. Storlazzi. 2007. Variability in oceanographic and meteorologic forcing along Central 

California and its implications on nearshore processes. Journal of Marine Systems 68: 457-472.

312
Food Production1

Executive Summary

The marine and coastal areas of 

north-central California provide a 

variety of food products, including 

fish, crustaceans, mollusks, 

echinoderms, and some harvestable 

algae2. The impacts of climate and climate-driven changes on food production will likely vary 

widely between different seafood species and stocks, with impacts being both direct (e.g., altered 

physiology in response to warming water temperatures) and indirect (e.g., altered fishery 

productivity as prey availability shifts in response to climate changes such as pH and upwelling). 

Key climate sensitivities identified by workshop participants include sea surface temperature, 

pH, dynamic ocean conditions (currents/mixing/stratification), and salinity. Key non-climate 

stressors identified by workshop participants include recreation (fishing), aquaculture, harvest, 

and pollutions and poisons. Workshop participants evaluated food production to be of high 

societal value, but did not evaluate the likelihood of managing or alleviating climate impacts for 

this service. Supporting literature suggests that fisheries contribute significantly to local and state 

economies, but sustainable seafood initiatives have met with mixed success, and that marine 

protected areas can be used to meet multiple goals (e.g., harvest and stock protection), and shifts 

in fishing regulations could be used to better maintain seafood stocks in the future. 

Sensitivity 

I. Sensitivity of ecosystem service components

Sensitivity of the provision of the ecosystem service to climate and climate-driven changes: 

Moderate

• Confidence of workshop participants: Moderate

Climate and climate-driven changes identified: sea surface temperature, ocean pH, dynamic 

ocean conditions (currents/mixing/stratification), salinity

Climate and climate-driven changes that may benefit the provision of the ecosystem service: 

none provided 

• Description of benefits: The benefits of climate and climate-driven factors on food 

production will depend on individual species responses. 

Additional participant comments

Some species will be more impacted than others, as individual species will have different 

responses to climate and climate-driven changes. 

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

2 This assessment provides only a general synthesis of vulnerability information across all food species. For more 

detailed information on specific resources (e.g., anchovy, red abalone, blue rockfish), please see the specific species 

vulnerability assessments elsewhere in this report.

Food Production Score Confidence 

Sensitivity 4 Moderate-High 3 High

Exposure 4 Moderate-High 3 High

Adaptive Capacity 4 Moderate-High 2 Moderate

Vulnerability 3 Moderate 3 High

313
Supporting literature

North-central California marine and coastal zones produce a variety of food products available 

for commercial and recreational harvest. Commercially fished stocks include anchovy, sardine, 

sea urchin, Dungeness crab, shrimp, squid, halibut, mackerel, tuna, white seabass, sole, salmon, 

sablefish, and more (CDFW 2015a). Recreational fisheries include halibut, sturgeon, salmon, 

surfperch, rockfish, lingcod, greenlings, mussels, red abalone, and Dungeness crab, among others 

(CDFW 2015b). Harvestable algae, including giant and bull kelp, edible seaweed (common 

genera: Porphyra, Laminaria, and Monostrema) and agar-bearing marine algae are utilized for 

both commercial and non-commercial purposes (CDFW 2015c). There will likely be high 

variability in the response of marine food species and populations to climate and climate-driven 

changes (Sydeman and Thompson 2013); generalized impacts across species are summarized 

below, while more detailed information on particular resources can be found in the individual 

species summaries elsewhere in this report. 

Sea surface temperature

Warming sea surface temperatures can have direct effects on marine food species by affecting 

physiology, including metabolism and respiration (Botsford and Lawrence 2002, Sydeman and 

Thompson 2013). For example, warmer water can increase fish oxygen demand (Portner and 

Knust 2007), reduce energetic metabolic protein performance (Fields et al. 1999), and negatively 

affect respiration and growth for a variety of fish species (e.g., blue rockfish) (Largier et al. 

2010). Warming temperatures also indirectly affect marine food production by altering food 

webs and trophic interactions (Sydeman and Thompson 2013). For example, warmer sea surface 

temperatures increase water column stability and reduce nutrient delivery and primary 

productivity, which can have cascading trophic effects and influence fish reproduction and 

survival (Sydeman and Thompson 2013 and citations therein). Warmer water temperatures have 

been linked with negative impacts in Dungeness crab larvae (Botsford and Lawrence 2002) as 

well as reduced survival and recruitment in Chinook and coho salmon populations (Botsford and 

Lawrence 2002; Lindley et al. 2009), leading to recreational and commercial closures of these 

salmon fisheries in California (Sydeman and Thompson 2013). Warmer water temperatures can 

also facilitate range shifts, altering predator/prey dynamics and leading to compositional changes 

in fish communities (Sydeman and Thompson 2013). Shifts in the Pacific Decadal Oscillation 

(PDO) and the El Niño Southern Oscillation (ENSO) can drastically alter water temperatures 

(McPhaden 1999), influencing primary productivity and subsequently, seafood production (King 

2005, Overland et al. 2010, King et al. 2011, Sydeman and Thompson 2013).

pH 

Increased oceanic uptake of carbon dioxide (CO2) contributes to declines in ocean pH (Sydeman 

and Thompson 2013). Feely et al. (2008) show that pH is very low in upwelled waters along the 

coast of western North America, including in this study region. Low pH (i.e., “ocean 

acidification”) water, which has lower rates of calcium carbonate (CaCO3), can contribute to 

declines in calcification rates (Gazeau et al. 2007, Doney et al. 2009, Doney 2010, Gruber et al. 

2012) and can be corrosive to a wide variety of organisms, including mollusks (Guinotte and 

Fabry 2008) harvested for food, such as the California mussel (Mytilus californianus) (Gaylord 

et al. 2011). Lower pH has also been correlated with higher mortality of the Dungeness crab 

(Cancer magister) (Miller 2012). Declining pH can also affect fishery productivity by altering 

the availability of calcareous plankton, a key prey species (Sydeman and Thompson 2013). 

314
Dynamic ocean conditions (currents/mixing/stratification) 

The California Current is a dynamic ecosystem that varies geographically, seasonally, and 

temporally, supporting diverse ecosystems and many seafood species (Sydeman and Thompson 

2013 and citations therein). Fisheries productivity is tied to upwelling and subsequent water 

mixing (Huyer 1983, King et al. 2011, Thompson et al. 2012), with moderate levels of upwelling 

resulting in maximum fish productivity (Cury and Roy 1989, Hannah 2011). Upwelling is 

influenced by winds and current shifts related to shifts in ENSO or PDO regimes (Sydeman and 

Thompson 2013). For example, warmer currents associated with La Niña events can increase 

stratification, reducing nutrient delivery to the euphotic zone and affecting larger food webs 

(Sydeman and Thompson 2013). Increasing sea surface temperatures are also driving increased 

stratification (Sydeman and Thompson 2013); thermoclines have become stronger and deeper in 

offshore waters of the region (Palacios et al. 2004), impacting primary productivity (Roemmich 

and McGowan 1995) and trophic interactions. 

Salinity

Salinity can affect marine food production by directly impacting multiple fished species. Studies 

on the effect of salinity extremes (both high and low) indicate that, when combined with 

temperature stress, salinity can negatively impact rocky intertidal invertebrates (e.g., the 

California mussel) through increased embryonic mortality (Przeslawski et al. 2005, Deschaseaux 

et al. 2010) and decreased adult aerobic performance (Vajed Samiei et al. 2011). Salinity 

extremes can also negatively impact Pacific herring spawning and hatching (Taylor 1971, Reilly 

and Moore 1983).

II. Sensitivity to disturbance regimes

Disturbance regimes identified: wind, disease, storms, and harmful algal blooms (HABs) 

Overall sensitivity of the provision of the ecosystem service to disturbance regimes: ModerateHigh

• Confidence of workshop participants: no answer provided 

Additional participant comments

Changing wind patterns and storm frequency and intensity will particularly impact the fishing 

industry. The impacts of disease and HABs on food production will depend upon individual and 

cumulative species responses.

Supporting literature

Wind 

Wind patterns affect upwelling, which influences the health and productivity of a variety of 

valued seafood species and stocks (Sydeman and Thompson 2013 and citations therein). Wind 

can also desiccate rocky intertidal species (e.g., California mussel) (Bell 1995). 

Disease

Diseases (e.g., viruses, bacterial infections, worm infestations) can affect many important 

seafood species, including red abalone, shrimp, clams, crabs, and a variety of marine fishes, 

affecting survival, growth, recruitment and/or marketability (Jester et al. 2009, Lafferty et al. 

2015). For example, worms of the genus Carcinonemertes can infest Dungeness crabs and cause 

significant mortality in brooding eggs, reducing crab recruitment (Wickham et al. 1980). Marine 

diseases may increase with warming water temperatures due to enhanced pathogen development, 

315
survival, and dispersal, as well as new or increased host susceptibility (Friedman et al. 1997, 

Harvell et al. 2002, Raimondi et al. 2002, Largier et al. 2010). 

Storms

Winter storms have increased in intensity since 1950 (Bromirski et al. 2003). Harvest of 

available seafood can be limited by poor weather conditions and/or condense harvest activities to 

specific areas along the coastline (e.g., developed harbors, protected beaches) (Gleason et al. 

2010). 

Harmful algal blooms 

Harmful algal blooms (HABs) can have a variety of impacts on seafood species, including 

mortality, increased susceptibility to disease, depressed reproduction, habitat loss, and food web 

disruptions, among others (Burkholder 1998, Robinson and Graham 2014). Increases in HABs 

may be an indirect effect of warming ocean temperature (Burkholder 1998, Van Dolah 2005) or 

periods of warm water temperature (e.g., El Niño events; Burkholder 1998). Currently there have 

been no indications to suggest that water quality in the region is compromised due to HABs 

(CBNMS Condition Report 2009), although with the possible rise in ocean temperature the 

emergence and spread of HABs may increase (Largier et al. 2010). However, many other factors 

(e.g., nutrient inputs) influence the frequency, severity, and net effect of blooms on fisheries 

toxicity, making projections difficult (Anderson et al. 2002). 

III. Sensitivity and exposure to non-climate stressors

Non-climate stressors identified: recreation (fishing), aquaculture, harvest, pollutions and 

poisons 

Degree to which non-climate stressors affect the provision of the ecosystem service: ModerateHigh

• Confidence of workshop participants: High

Degree to which non-climate stressors affect the sensitivity of the provision of the ecosystem 

service to climate change: Moderate-High

• Confidence of workshop participants: Moderate

Additional participant comments

The effects of harvest activities will have the largest impact on food production. Regulatory 

changes in the current harvest levels will influence the sensitivity of food production to climate 

and climate-driven changes. 

Supporting literature

Recreation

Recreational fishing, even catch-and-release, can affect fish stocks and future food production. 

For example, high recreational fish catches during the 1980s were identified as the main driver of 

depleted near-shore California fisheries and lower catch rates in subsequent years (Schroeder and 

Love 2002). In addition, recreational anglers may unintentionally introduce invasive species, 

which can threaten biological communities already being impacted by climate change (e.g., fish 

stocks) (Monterey Bay National Marine Sanctuary (MBNMS) 2008). 

316
Aquaculture 

Many important finfish and shellfish species rely on eelgrass beds for nursery habitat (NOAA

2011), and aquaculture operations can displace, convert, or alter these and other important 

marine ecosystems (Diana 2009). Aquaculture can also facilitate disease transmission to wild 

stocks (Diana 2009); this is of particular concern with farmed abalone (Culver and Kuris 2000, 

Lafferty and Ben-Horin 2013). However, aquaculture is an expanding industry that contributes 

significantly to marine food production (Brander 2007). 

Harvest

Harvest affects age and population structures, which can affect future recruitment and fecundity 

(Schroeder and Love 2002, Sydeman and Thompson 2013). Depleted populations and 

populations with altered age/size distributions are generally more vulnerable to climate and 

climate-driven changes (Brander 2007, Sydeman and Thompson 2013). Fisheries harvest can 

also impact disease rates in both target and nontarget species and stocks by affecting species 

density and/or altering ecological relationships (Lafferty et al. 2015 and citations therein). 

Commercial kelp harvesting can also be detrimental for seafood species, as it destroys important 

habitat for juvenile fish species (CDFW 2008). 

Pollution and poisons 

Water pollution can impact the health of key seafood species (GFNMS 2008, MBNMS 2008, 

Largier et al. 2010). For example, degraded estuarine water quality can negatively affect 

harvested fish species that use estuaries as nurseries (Pendleton 2010). Pollution may include 

agricultural (inland and coastal) and urban runoff, vessel-based pollutants, legacy mining 

pollutants, sewage, and large particulates (e.g., plastic) (GFNMS 2008). In general, agricultural 

pollution sources are more influential within the boundaries of the sanctuary (GFNMS 2008), 

while urban runoff and sewage pollutants become increasingly significant from San Francisco 

southward (GFNMS 2008, Heal the Bay 2014). Coastal waters and estuaries are typically more 

vulnerable to water pollution impacts than open ocean areas within the study region (GFNMS 

2008). Higher coastal water pollutant levels are typically associated with rainfall and elevated 

runoff, which occur most frequently during cooler weather periods (November-March) (Heal the 

Bay 2014). 

IV. Other sensitivities: none identified

Adaptive Capacity

I. Intrinsic value

Value of the ecosystem service to people: High 

• Confidence of workshop participants: High

Degree to which people are willing to change their behavior to ensure provision of the ecosystem 

service: Low-Moderate

• Confidence of workshop participants: Moderate

Economic drivers that play a role in the management of the ecosystem service: The consumer 

cost of food is often the driving factor in the choice of seafood, which drives demand and harvest 

levels. 

317
Can the ecosystem service be accessed elsewhere, and how important is it to ensure provision of 

the ecosystem service in its current location(s): Yes, seafood can be accessed in numerous 

locations outside the North-central California coast and ocean regions, but fishing and 

aquaculture activities are culturally and economically important to numerous local communities 

in the region. 

Additional participant comments

Some efforts, such as Seafood Watch, are changing consumer choices and behaviors, but the 

majority of the population is not willing to switch to, or pay for, more sustainable choices of 

seafood. 

Supporting literature

In 2011, California fisheries were valued at roughly $200 million, with a majority of fished 

species being used for human food consumption (Sydeman and Thompson 2013). Demand for 

seafood is increasing globally, and is expected to continue to increase due to population growth 

(Owens 2008, Merino et al. 2012). However, there are an abundance of global fish markets 

(Brander 2007), and loss of recreational and commercial fisheries in the region would have 

significant impacts on both state and local economies (Pendleton 2010).

In response to declining fish stocks and ineffective policy solutions, market based strategies 

(e.g., eco-labeling) have been used to promote sustainable fisheries management and 

consumption (Owens 2008). Although these labeling efforts have met with localized success, 

they are undermined by unclear and/or unofficial seafood naming and labeling, (Jacquet and 

Polly 2007, 2008), consistent fish supply from non-participatory Asian markets (Jacquet and 

Polly 2007, 2008, Owens 2008), limited restaurant and aquaculture engagement (Owens 2008), 

and consumer perceptions and preferences (Hallstein and Villas-Boas 2009), among others. 

II. Management potential

Rigidity / specificity of rules governing the provision of the ecosystem service or the areas that 

provide the ecosystem service: High

• Confidence of workshop participants: High

Conflicts with other services in the region: Yes

• Conflicting services: non-consumptive uses and the maintenance of healthy habitats and 

ecosystems. There are also allocation conflicts between commercial and recreational 

fishing. 

Services that mutually benefit from the provision of the ecosystem service: tourism/recreational 

fishing 

Likelihood of managing or alleviating climate change impacts on the provision of the ecosystem 

service: no answer provided 

Additional participant comments

Reductions in current harvest levels could help buffer fish populations against climate change 

impacts. Increases in sustainable aquaculture and habitat protections, such as those enacted under 

the Marine Life Protection Act (MLPA) could help ensure the provision of food production in 

the region. 

318
Supporting literature

Interconnected marine reserves may help maintain healthy population age structures and 

recruitment (Berkeley et al. 2004). Balanced fishing strategies, particularly for those species 

whose fecundity increases with age, could also help buffer vulnerable stocks from the effects of 

climate change by reducing selectivity/removal impacts (Garcia et al. 2012). Recreational and 

commercial take regulations can be used to maintain long-term stock survival (CDFW 2015d), 

but can restrict food procurement intensity in the short-term. Cooperative, multi-jurisdictional 

management for wide-ranging species and/or species that are increasing in recreational value 

(e.g., Pacific halibut) will likely play an important role in maintaining viable populations for the 

future (CDFW 2015d). The California Department of Fish and Wildlife (2008) contends that 

protected marine areas can be tailored to allow both seafood population recovery and harvest. 

Aquaculture expansion will likely play a key role in meeting future seafood demand (Merino et 

al. 2012), particularly if sustainable methods are used more widely (Naylor et al. 2009). 

Marine food harvest can negatively affect other ecosystem services, including nutrient cycling 

and biodiversity (Brander 2007), particularly if practiced unsustainably. However, saltwater 

fishing is a major contributor to recreation and tourism in the study region (Pendleton 2010). 

III. Other adaptive capacity factors: none identified

Exposure 

I. Future climate exposure3

Degree of to which the provision of the ecosystem service is likely to be affected by climate 

change: Moderate-High

• Confidence of workshop participants: Moderate 

Future climate and climate-driven factors identified: changes in sea surface temperature, sea 

level rise, decreased pH, decreased dissolved oxygen (DO) levels, altered currents and mixing, 

changes in salinity, increased storminess

Supporting Literature

Sea surface temperature

Subtropical species (e.g., sardine) may increase with warmer ocean temperatures, while coldwater affiliate species (e.g., salmon, rockfish) may decline (Sydeman and Thompson 2013).

Currents/mixing/stratification

Enhanced upwelling may bolster cold-water affiliate stocks (e.g., salmon, rockfish) but 

negatively impact subtropical species (e.g., sardine) (Sydeman and Thompson 2013). Delayed 

upwelling could affect seafood production by disrupting or altering species phenology and 

juvenile survival (Logerwell et al. 2003, Snyder et al. 2003, Sydeman and Thompson 2013). 

3 Supporting literature for future exposure to climate factors is provided in the introduction.

319
Literature Cited 

Anderson, D. M., P. M. Glibert and J. M. Burkholder. 2002. Harmful algal blooms and eutrophication: nutrient 

sources, composition, and consequences. Estuaries 25 (4):704-726.

Bell, E. C. 1995. Environmental and morphological influences on thallus temperature and desiccation of the 

intertidal alga Mastocarpus papillatus Kützing. Journal of Experimental Marine Biology and Ecology 191 

(1):29-55.

Berkeley, S. A., M. A. Hixon, R. J. Larson and M. S. Love. 2004. Fisheries sustainability via protection of age 

structure and spatial distribution of fish populations. Fisheries 29 (8):23-32.

Botsford, L. and C. Lawrence. 2002. Patterns of co-variability among California Current chinook salmon, coho 

salmon, Dungeness crab, and physical oceanographic conditions. Progress in Oceanography 53 (2):283-

305.

Brander, K. M. 2007. Global fish production and climate change. Proceedings of the National Academy of Sciences

104 (50):19709-19714.

Bromirski, P. D., R. E. Flick and D. R. Cayan. 2003. Storminess variability along the California coast: 1858-2000.

Journal of Climate 16 (6):982-993.

Burkholder, J. M. 1998. Implications of harmful microalgae and heterotrophic dinoflagellates in management of 

sustainable marine fisheries. Ecological Applications 8 (sp1):S37-S62

California Department of Fish and Wildlife (CDFW). 2015a. Ocean Fishing. Accessed March 2015. 

http://www.dfg.ca.gov/marine/fishing.asp#commercial.

California Department of Fish and Wildlife (CDFW). 2015b. Current California Ocean Recreational Fishing 

Regulations. Accessed March 2015. http://www.dfg.ca.gov/marine/mapregs3.asp#other. 

California Department of Fish and Wildlife (CDFW). 2015c. Kelp and Other Marine Algae. Accessed March 2015. 

http://www.dfg.ca.gov/marine/kelp.asp. 

California Department of Fish and Wildlife (CDFW). 2015d. Pacific Halibut. Accessed March 2015. 

http://www.dfg.ca.gov/marine/pacifichalibut.asp.

California Department of Fish and Wildlife (CDFW). 2008. California Marine Life Protection Act: Master Plan for 

Marine Protected Areas.

Culver, C. S. and A. M. Kuris. 2000. The apparent eradication of a locally established introduced marine pest.

Biological Invasions 2 (3):245-253.

Cury, P. and C. Roy. 1989. Optimal environmental window and pelagic fish recruitment success in upwelling areas.

Canadian Journal of Fisheries and Aquatic Sciences 46 (4):670-680.

Deschaseaux, E. S., A. Taylor, W. A. Maher and A. Davis. 2010. Cellular responses of encapsulated gastropod 

embryos to multiple stressors associated with climate change. Journal of Experimental Marine Biology and 

Ecology 383 (2):130-136.

Diana, J. S. 2009. Aquaculture production and biodiversity conservation. Bioscience 59 (1):27-38.

Doney, S. C. 2010. The growing human footprint on coastal and open-ocean biogeochemistry. Science 328 

(5985):1512-1516.

Doney, S. C., V. J. Fabry, R. A. Feely and J. A. Kleypas. 2009. Ocean acidification: the other CO2 problem. Annual 

Review of Marine Science 1:169-192.

Feely, R. A., C. L. Sabine, J. M. Hernandez-Ayon, D. Ianson and B. Hales. 2008. Evidence for upwelling of 

corrosive acidified water onto the continental shelf. Science 320 (5882):1490-1492.

Fields, P.A., J.B. Graham, R.H. Rosenblatt, G.N. Somero. 1999. Effects of expected global climate change on 

marine faunas. Trends in Ecology and Evolution 8:361-367.

Friedman, C. S., M. Thomson, C. Chun, P. L. Haaker and R. P. Hedrick. 1997. Withering syndrome of the black 

abalone, Haliotis cracherodii (Leach): water temperature, food availability, and parasites as possible 

causes. Journal of Shellfish Research 16 (2):403-412.

Garcia, S., J. Kolding, J. Rice, M.-J. Rochet, S. Zhou, T. Arimoto, J. Beyer, L. Borges, A. Bundy and D. Dunn. 

2012. Reconsidering the consequences of selective fisheries. Science 335 (6072):1045-1047.

Garcia‐Reyes, M. and J. Largier. 2010. Observations of increased wind‐driven coastal upwelling off central 

California. Journal of Geophysical Research: Oceans (1978–2012) 115 (C4).

Gaylord, B., T. M. Hill, E. Sanford, E. A. Lenz, L. A. Jacobs, K. N. Sato, A. D. Russell and A. Hettinger. 2011. 

Functional impacts of ocean acidification in an ecologically critical foundation species. The Journal of 

Experimental Biology 214 (15):2586-2594.

Gazeau, F., C. Quiblier, J. M. Jansen, J. P. Gattuso, J. J. Middelburg and C. H. Heip. 2007. Impact of elevated CO2 

on shellfish calcification. Geophysical Research Letters 34 (7).

320
Gleason, M., S. McCreary, M. Miller-Henson, J. Ugoretz, E. Fox, M. Merrifield, W. McClintock, P. Serpa and K. 

Hoffman. 2010. Science-based and stakeholder-driven marine protected area network planning: A 

successful case study from north central California. Ocean & Coastal Management 53 (2):52-68.

Gruber, N., C. Hauri, Z. Lachkar, D. Loher, T. L. Frölicher and G.-K. Plattner. 2012. Rapid progression of ocean 

acidification in the California Current System. Science 337 (6091):220-223.

Guinotte, J. M. and V. J. Fabry. 2008. Ocean Acidification and Its Potential Effects on Marine Ecosystems. Annals 

New York Academy of Sciences 1134 (1):320-342. 

Gulf of the Farallones National Marine Sanctuary (GFNMS). 2008. GFNMS Management Plan.

Hallstein, E. and S. B. Villas-Boas. 2009. Are consumers color blind? An empirical investigation of a traffic light 

advisory for sustainable seafood. Department of Agricultural & Resource Economics, UC Berkeley, 

Working Paper Series. 

Hannah, R. W. 2011. Variation in the distribution of ocean shrimp (Pandalus jordani) recruits: links with coastal 

upwelling and climate change. Fisheries Oceanography 20 (4):305-313.

Harvell, C. D., C. E. Mitchell, J. R. Ward, S. Altizer, A. P. Dobson, R. S. Ostfeld and M. D. Samuel. 2002. Climate 

warming and disease risks for terrestrial and marine biota. Science 296 (5576):2158-2162.

Heal the Bay. 2014. 2013-2014 Annual Beach Report Card.

Huyer, A. 1983. Coastal upwelling in the California Current system. Progress in Oceanography 12 (3):259-284.

Jacquet, J. L. and D. Pauly. 2007. The rise of seafood awareness campaigns in an era of collapsing fisheries. Marine 

Policy 31 (3):308-313.

Jacquet, J. L. and D. Pauly. 2008. Trade secrets: renaming and mislabeling of seafood. Marine Policy 32 (3):309-

318.

Jester, R. J., K. A. Baugh and K. A. Lefebvre. 2009. Presence of Alexandrium catenella and paralytic shellfish 

toxins in finfish, shellfish and rock crabs in Monterey Bay, California, USA. Marine Biology 156 (3):493-

504.

King, J. R. 2005. Report of the study group on fisheries and ecosystem responses to recent regime shifts: Citeseer.

King, J. R., V. N. Agostini, C. J. Harvey, G. A. McFarlane, M. G. Foreman, J. E. Overland, E. Di Lorenzo, N. A. 

Bond and K. Y. Aydin. 2011. Climate forcing and the California Current ecosystem. ICES Journal of 

Marine Science: Journal du Conseil 68 (6):1199-1216.

Lafferty, K. D. and T. Ben-Horin. 2013. Abalone farm discharges the withering syndrome pathogen into the wild.

Frontiers in Microbiology 4:373.

Lafferty, K. D., C. D. Harvell, J. M. Conrad, C. S. Friedman, M. L. Kent, A. M. Kuris, E. N. Powell, D. Rondeau 

and S. M. Saksida. 2015. Infectious diseases affect marine fisheries and aquaculture economics. Annual 

Review of Marine Science 7:471-496.

Largier, J. L., B. S. Cheng and K. D. Higgason (editors). 2010. Report of a Joint Working Group of the Gulf of the 

Farallones and Cordell Bank National Marine Sanctuaries Advisory Councils. 

Lindley, S. T., C. B. Grimes, M. S. Mohr, W. T. Peterson, J. Stein, J. T. Anderson, L. W. Botsford, D. L. Bottom, C. 

A. Busack, T. K. Collier, J. Ferguson, J. C. Garza, A. M. Grover, D. G. Hankin, R. G. Kope, P. W. Lawson, 

A. Low, R. B. MacFarlane, K. Moore, M. Palmer-Zwahlen, F. B. Schwing, J. Smith, C. Tracy, R. Webb, B. 

K. Wells, and T. H. Williams. 2009. What caused the Sacramento River fall Chinook stock collapse? Prepublication report to the Pacific Fishery Management Council. 

Logerwell, E., N. Mantua, P. W. Lawson, R. Francis and V. Agostini. 2003. Tracking environmental processes in 

the coastal zone for understanding and predicting Oregon coho (Oncorhynchus kisutch) marine survival.

Fisheries Oceanography 12 (6):554-568.

McPhaden, M. J. 1999. Genesis and evolution of the 1997-98 El Niño. Science 283 (5404):950-954.

Mendelssohn, R. and F. Schwing. 2002. Common and uncommon trends in SST and wind stress in the California 

and Peru–Chile current systems. Progress in Oceanography 53 (2):141-162.

Mendelssohn, R., F. B. Schwing and S. J. Bograd. 2003. Spatial structure of subsurface temperature variability in 

the California Current, 1950–1993. Journal of Geophysical Research: Oceans (1978–2012) 108 (C3).

Merino, G., M. Barange, J. L. Blanchard, J. Harle, R. Holmes, I. Allen, E. H. Allison, M. C. Badjeck, N. K. Dulvy

and J. Holt. 2012. Can marine fisheries and aquaculture meet fish demand from a growing human 

population in a changing climate? Global Environmental Change 22 (4):795-806.

Miller, J. J. 2012. 100 days in hot water, tales from a sixth instar Dungeness crab (Cancer magister), ocean 

acidification impacts on early juvenile stages. Journal of Shellfish Research 31 (1):323-323.

Monterey Bay National Marine Sanctuary (MBNMS). 2008. Monterey Bay National Marine Sanctuary Final 

Management Plan.

National Oceanic and Atmospheric Administration (NOAA). 2011. Southern California Eelgrass Mitigation Policy.

321
Naylor, R. L., R. W. Hardy, D. P. Bureau, A. Chiu, M. Elliott, A. P. Farrell, I. Forster, D. M. Gatlin, R. J. Goldburg 

and K. Hua. 2009. Feeding aquaculture in an era of finite resources. Proceedings of the National Academy 

of Sciences 106 (36):15103-15110.

Office of National Marine Sanctuaries. 2009. Cordell Bank National Marine Sanctuary (CBNMS) Condition Report 

2009. Silver Spring, MD.

Overland, J. E., J. Alheit, A. Bakun, J. W. Hurrell, D. L. Mackas and A. J. Miller. 2010. Climate controls on marine 

ecosystems and fish populations. Journal of Marine Systems 79 (3):305-315.

Owens, C. M. 2008. Sustainable seafood labeling: An analysis of the marine stewardship council. Graduate School 

of International Relations and Pacific Studies., University of California, San Diego, IR/PS Case 07-02.

Palacios, D. M., S. J. Bograd, R. Mendelssohn and F. B. Schwing. 2004. Long‐term and seasonal trends in 

stratification in the California Current, 1950–1993. Journal of Geophysical Research: Oceans (1978–2012)

109 (C10).

Pendleton, L. H. 2010. The economic and market value of coasts and estuaries: what's at stake?

Portner, H.O. and R. Knust. 2007. Climate change affects marine fishes through the oxygen limitation of thermal 

tolerance. Science 315:95-97. 

Przeslawski, R., A. Davis and K. Benkendorff. 2005. Synergistic effects associated with climate change and the 

development of rocky shore molluscs. Global Change Biology 11 (3):515-522.

Raimondi, P., C. M. Wilson, R. E. Ambrose, J. M. Engle and T. Minchinton. 2002. Continued declines of black 

abalone along the coast of California: are mass mortalities related to El Niño events? Marine Ecology 

Progress Series 242:143-152.

Reilly, P.N. and T.O. Moore. 1983. Pacific herring, Clupea harengus pallasi , studies in San Francisco Bay, 

Monterey Bay, and the Gulf of the Farallones, July 1982 to March 1983. Calif. Fish Game Mar. Res. 

Admin. Rep. 83-5. 49 pp

Robinson, K. L. and W. M. Graham. 2014. Warming of subtropical coastal waters accelerates Mnemiopsis leidyi

growth and alters timing of spring ctenophore blooms. Marine Ecology Progress Series 502:105-115.

Roemmich, D. and J. McGowan. 1995. Climatic warming and the decline of zooplankton in the California Current.

Science 267 (5202):1324-1326.

Schroeder, D. M, and M. S. Love. 2002. Recreational fishing and marine fish populations in California. California 

Cooperative Oceanic Fisheries Investigations Report.

Snyder, M. A., L. C. Sloan, N. S. Diffenbaugh and J. L. Bell. 2003. Future climate change and upwelling in the 

California Current. Geophysical Research Letters 30 (15).

Sydeman, W., and S.A. Thompson. 2013. Potential Impacts of Climate Change on California’s Fish and Fisheries. 

Oakland, CA: Farallon Institute for Advanced Ecosystem Research. Literature Review.

Taylor, F.H.C. 1971. Variation in hatching success in Pacific herring Clupea pallasi eggs with water depth, 

temperature, salinity , and egg mass thickness. Rapp. P.-V. Reun. Cons. Int. Explor. Mer 160: 34- 41.

Thompson, S. A., W. J. Sydeman, J. A. Santora, B. A. Black, R. M. Suryan, J. Calambokidis, W. T. Peterson and S. 

J. Bograd. 2012. Linking predators to seasonality of upwelling: using food web indicators and path analysis 

to infer trophic connections. Progress in Oceanography 101 (1):106-120.

Van Dolah, F.M. 2005. Effects of harmful algal blooms. In: J. Reynolds III, W.F. Perrin, R.R. Reeves, S. 

Montgomery, and T.J. Ragen. Marine Mammal Research: Conservation beyond crisis. John Hopkins 

University Press, Baltimore, MD, USA.

Vajed Samiei, J., Novio Liñares, J.A., Abtahi, B. 2011. The Antagonistic Effect of Raised Salinity on the Aerobic 

Performance of a Rocky Intertidal Gastropod Nassarius deshayesianus (Issel, 1866) Exposed to Raised 

Water Temperature. Journal of the Persian Gulf 2(6): 29-36.

Wickham, D. E. 1980. Aspects of the life history of Carcinonemertes errans (Nemertea: Carcinonemertidae), an egg 

predator of the crab Cancer magister. The Biological Bulletin 159 (1):247-257.

322
Recreation and Tourism1

Executive Summary 

Coastal and marine areas in northcentral California provide a variety of 

land- and water-based recreational and 

tourism opportunities, and these 

activities are both highly valued by the 

public and significant contributors to 

California’s economy, although they at times conflict with other ecosystem services (e.g., water 

quality, food production). Climate change impacts (e.g., warming inland temperatures, sea level 

rise) can alter the demand, supply, and quality of tourism and recreation opportunities in coastal 

and marine areas. Impacts can be direct (e.g., reduced beach extent as a result of sea level rise) or 

indirect (e.g., reduced wildlife viewing opportunities as warmer water temperatures increase 

disease incidence). Key climate sensitivities identified by workshop participants include air and 

sea surface temperature, sea level rise, wave height, storm intensity, and prevailing wind 

patterns. Key non-climate sensitivities identified by participants include land use changes, 

harvest, aquaculture, pollution, and recreation impacts. Workshop participants indicated that 

recreation and tourism are of high societal value, but did not evaluate the likelihood of managing 

or alleviating climate impacts for this service. Supporting literature suggests that there may be 

significant opportunities for increased education and outreach surrounding recreation and 

tourism and coastal and marine resources. Other management options (e.g., beach nourishment) 

require advanced study to minimize negative impacts. 

Sensitivity 

I. Sensitivity of ecosystem service components Sensitivity of the provision of the ecosystem service to climate and climate-driven changes: 

Low-Moderate

• Confidence of workshop participants: High

Climate and climate-driven changes identified: air temperature, sea surface temperature, sea 

level rise, wave heights, prevailing wind patterns, storm intensity

Climate and climate-driven changes that may benefit the provision of the ecosystem service: 

wave heights, sea surface temperature, wind patterns

• Description of benefits: Increased wave heights could provide more opportunities for 

surfers, which could also increase tourism. Increases in sea surface temperature could 

make coastal and bay waters more conducive for swimming activities. Additionally, 

changes in sea surface temperature could result in changes to prevailing wind patterns, 

creating better conditions for sailing.

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

Recreation & 

Tourism

Score Confidence 

Sensitivity 3 Moderate 3 High

Exposure 4 Moderate-High 3 High

Adaptive Capacity 4 Moderate-High 3 High

Vulnerability 3 Moderate 3 High

323
Additional participant comments 

Climate and climate-driven changes could result in increased opportunities for some recreational 

activities, but may also cause more hazardous conditions for others, and could result in decreased 

use for some beach and water areas. 

Supporting literature

The marine and coastal areas of north-central California provide a variety of recreational and 

tourism opportunities, including but not limited to: beach access, hiking, surfing, swimming, 

sailing, kayaking, scuba diving, windsurfing, wildlife viewing, and fishing. However, a majority 

of current literature related to climate change and marine/coastal tourism and recreation focuses 

on ecosystem effects, while literature linking these effects to tourism and recreation sectors is 

less abundant, particularly when looking at activities outside of beach-based recreation (Moreno 

and Amelung 2009). 

Air temperature

Climate and weather play a significant role in determining vacation destinations (Amelung et al. 

2007, WTO and UNEP 2008, Moser et al. 2009), and increases in regional air temperature may

have primary effects on tourism and recreation by altering demand, travel plans, and visitation 

rates (Hall and Higham 2005, WTO and UNEP 2008). For example, warmer inland and urban 

temperatures may drive increased recreational demand in cooler coastal locations (Caldwell and 

Segall 2007). Temperature increases can also have secondary effects on tourism and recreation 

by altering environmental quality (Hall and Higham 2005, WTO and UNEP 2008). For example, 

vegetation shifts in response to changing temperature and precipitation regimes could affect 

scenic quality (Shaw and Loomis 2008). 

Sea level rise

Sea level rise can impact recreational and tourism opportunities (Caldwell and Segall 2007) by

affecting beach and wetland extent (Morris and Walls 2009). For example, sea level rise can 

increase rates of shoreline erosion, inundate current beaches (Feagin et al. 2005), and/or lead to 

net beach loss in areas experiencing passive erosion as a result of armoring (Largier et al. 2010). 

Alternatively, sea level rise may drive shifts in beach location (Morris and Walls 2009), 

particularly if beach and dune habitats have room to migrate inland (Yohe et al. 1999 cited in 

Morris and Walls 2009). Sea level rise also has implications for marine wetlands, as wetland loss 

may occur where inward migration is prevented by development, leading to loss of valuable 

fishing, waterbird hunting, and wildlife viewing opportunities (e.g., migratory birds) (Morris and 

Walls 2009). Loss of beach and wetland habitats also increases the vulnerability of other tourism 

and recreational areas and infrastructure to flooding and erosion from sea level rise and storm 

surges (WTO and UNEP 2008; for more information, see the Flooding and Erosion Ecosystem 

Service summary). 

Sea surface temperature

Shifts in sea surface and water column temperature affect fish stocks, including recreational fish 

stocks and species valued for diving and snorkeling (WTO and UNEP 2008, Sydeman and 

Thompson 2013). Warmer water temperatures may be detrimental to salmon and rockfish; for 

example, warming ocean temperatures linked with interannual (El Niño/La Niña), interdecadal 

(Pacific Decadal Oscillation), and quasi interdecadal (North Pacific Gyre Oscillation) variability 

have been documented to affect recreationally important fish species (e.g., salmon) in north324
central California (Cole 2000, Sydeman et al. 2013). Warming water temperatures may also 

facilitate marine pathogen expansion (Harvell et al. 2002; see discussion of disease below). 

Wave heights

Waves are seasonal drivers of beach and dune erosion and accretion (Storlazzi and Griggs 2000, 

Wingfield and Storlazzi 2007, Hapke et al. 2009, Barnard et al. 2013), affecting the extent of 

sandy shoreline area available for recreation and tourism. For example, Ocean Beach experiences 

severe erosion during winter storms with large wave heights (Barnard et al. 2011), but typically 

recovers sediments during lower wave-energy periods in summer and fall (Hansen and Barnard 

2010). Wave height varies according to many factors, including season, coastline orientation, 

local bathymetry, and storm climatology (Hapke et al. 2009). For example, El Niño periods 

typically feature larger waves that can cause significant erosion (Hapke et al. 2009). Waves can 

also increase coastal flooding and inundation, forcing the retreat of sandy shorelines further 

inland (Storlazzi and Griggs 2000, Wingfield and Storlazzi 2007). Changes in wave height and 

direction, in response to both climate change and natural variability, will expose previously 

sheltered beaches to significant levels of erosion (Sallenger et al. 2002). According to surveys of 

coastal visitors in Southern California, beach width is an important factor in determining beach 

visitation; respondents indicated that decreasing beach widths as a result of erosion would cause 

a 29% decrease in visitation relative to current levels (King 2001).

Storm intensity

Climate change is expected to result in more frequent extreme storm events with larger storm 

surges, higher winds, and increased short duration/high precipitation events, all of which will 

affect rates of sediment deposition and erosion (Simas et al. 2001) in common recreational areas 

(e.g., beaches, wetlands). For example, increasing storm intensity can interact with sea level rise 

to create larger wave heights that increase erosion and/or accretion along regional beaches 

(Moser and Tribbia 2006, Cayan et al. 2008), affecting the extent of areas available for 

recreation. Storm conditions also limit safe recreational access, and condense marine and coastal 

recreation to specific areas along the coastline (e.g., developed harbors, protected beaches) 

(Gleason et al. 2010). 

Prevailing wind patterns 

Wind, along with temperature and precipitation, likely plays a role in user preferences for 

recreation areas (e.g., acts a positive influence for wind-based activities, but as a negative 

influence for beach activities) (Moreno and Amelung 2009). Wind also affects upwelling, which 

influences the productivity of recreational and commercial fisheries (Sydeman and Thompson 

2013 and citations therein). 

II. Sensitivity to changes in disturbance regimes

Disturbance regimes identified: wind, disease, flooding, and storms

Overall sensitivity of the provision of the ecosystem service to disturbance regimes: ModerateHigh

• Confidence of workshop participants: Moderate

Additional participant comments 

Flooding and storms may reduce access to some recreational areas and may also adversely 

impact infrastructure that supports recreation and tourism. Outbreaks of shellfish disease may 

325
result in reduced visitation and usage of coastal areas where recreational harvesting of shellfish 

takes place.

Supporting literature

Disease

Marine diseases can both directly and indirectly affect recreation and tourism opportunities. 

Direct impacts include beach closures as a result of harmful algal blooms or high bacteria levels 

(Turbow et al. 2004, California Environmental Protection Agency 2015) and recreational fishery 

closures due to dinoflagellate blooms and high levels of paralytic shellfish toxins (Jester et al. 

2009, Lewitus et al. 2012). These toxins have been consistently present along the Marin County 

coast since 1999, and historic cases of human paralytic shellfish poisoning are most common 

along the central and northern California coast (Lewitus et al. 2012). Marine diseases can also 

indirectly affect recreation and tourism opportunities by affecting the health of iconic wildlife 

species (e.g., sea lions, seabirds, intertidal organisms) (Jester et al. 2009, Lafferty et al. 2015), 

degrading wildlife viewing quality and/or reducing wildlife viewing opportunities. For example, 

sea otters are a charismatic species that regularly draw land- and water-based viewers; however, 

they are sensitive to a variety of diseases and pathogens accumulated through shellfish 

intermediaries (Jessup et al. 2004). Marine disease may increase with warming water 

temperatures due to enhanced pathogen development, survival, and dispersal, as well as new or 

increased host susceptibility (Harvell et al. 2002). For example, heat-stressed hosts (e.g., 

seastars) may be more susceptible to infection (Harvell et al. 2002, White et al. 2014). 

Flooding 

Increased flooding as a result of sea level rise can inundate recreational areas (e.g., beaches, 

wetlands) and damage infrastructure and facilities used in tourism and recreation (IPCC 2007, 

Moreno and Amalung 2009). Increased freshwater flooding as a result of more frequent and/or 

severe extreme precipitation events can also damage cultural and historical assets valued for 

tourism, and/or recreational and tourism infrastructure (WTO and UNEP 2008). 

Storms

Please refer to the storm intensity discussion in the climate sensitivity section above. 

Wind 

Please refer to the wind discussion in the climate sensitivity section above. 

III. Sensitivity and exposure to non-climate stressors

Non-climate stressors identified: land use changes, aquaculture, harvest, pollution and poisons, 

recreation

Degree to which non-climate stressors affect the provision of the ecosystem service: LowModerate

• Confidence of workshop participants: Moderate

Degree to which non-climate stressors affect the sensitivity of the provision of the ecosystem 

service to climate change: Moderate-High

• Confidence of workshop participants: High

326
Additional participant comments 

Excessive nutrient pollution could negatively impact sea grass through increases in epiphytic 

algae. Aquaculture can displace sea grasses. Overwater/underwater structures increase shading, 

which can impact sea grass beds, and land use changes can negatively impact salt marshes.

Supporting literature

Land use changes

Land use changes can directly reduce natural habitat available for recreation and tourism, as well 

as exacerbate the impacts of climate change (e.g., flooding, erosion) (Nelson et al. 2013). For 

example, human development in the Central Bay from 1855-1979 destroyed significant tidal 

marsh and intertidal mudflat habitat, resulting in a 4% overall areal loss of these critical habitats 

in San Francisco Bay (Barnard et al. 2013) and increasing local flood vulnerability (Nelson et al. 

2013). Further, water management activities (e.g., dams, erosion mitigation projects) in upland 

river basins alter sediment supply and delivery to regional beach and wetland habitats, affecting 

their ability to keep pace with sea level rise (Knowles 2010), and thus, their availability for 

recreational and tourism use. 

Continued coastal development will likely drive increased demand for armoring (MBNMS

2008), which has implications for natural systems as well as recreation and tourism. For 

example, coastal armoring affects the scenic quality of the coastline (Stamski 2005), and can 

exacerbate beach erosion, affecting public access (Stamski 2005, Hanak and Moreno 2008). 

Aquaculture 

Many important recreational finfish and shellfish species rely on eelgrass beds for nursery 

habitat (NOAA 2011), and aquaculture operations can displace, convert, or alter these and other 

important marine ecosystems (Dianna 2009). Aquaculture can also facilitate disease transmission 

to wild stocks (Dianna 2009); this is of particular concern with farmed abalone (Colver and 

Kuris 2000, Lafferty and Ben-Horin 2013). 

Harvest

Fisheries harvest can impact disease rates in both target and nontarget species and stocks by 

affecting fish density and/or by altering ecological relationships (Lafferty et al. 2015 and 

citations therein). In addition to reducing fish stocks (Schroeder and Love 2002), harvest also

affects age and population structures, which can affect future recruitment (Sydeman and 

Thompson 2013), and subsequently, recreational opportunities. 

Pollution and poisons 

Water pollution can affect recreational access and the health of recreational users (MBNMS 

2008, Heal the Bay 2014), as well as impact the health of species valued by recreational users

(GFNMS 2008, MBNMS 2008). For example, degraded estuarine water quality can negatively 

affect recreational fish species that use estuaries as nurseries (Pendleton 2010), and runoff 

containing coliform bacteria can impair human health and has been linked with sea otter deaths 

(MBNMS 2008). Pollution may include agricultural (inland and coastal) and urban runoff, 

vessel-based pollutants, legacy mining pollutants, sewage, and large particulates (e.g., plastic)

(GFNMS 2008). In general, agricultural pollution sources are more influential within the 

boundaries of the sanctuary (GFNMS 2008), while urban runoff and sewage pollutants become 

increasingly significant from San Francisco southward (GFNMS 2008, Heal the Bay 2014). 

Coastal waters and estuaries are typically more vulnerable to water pollution impacts than open 

327
ocean areas within the study region (GFNMS 2008). Higher coastal water pollutant levels are 

typically associated with rainfall and elevated runoff, which occur most frequently during cooler 

weather periods (November-March), and are thus typically decoupled with peak beach demand, 

but can coincide with favorable surfing conditions (i.e., storm swell) (Heal the Bay 2014). Many 

public health agencies within the state recommend the public stay out of coastal water bodies for 

three days following rain events due to elevated pollutant levels in resultant runoff, though recent 

studies indicate that a five-day safety period may garner larger public health benefits (Heal the 

Bay 2014). Declines in regional precipitation and runoff in recent years have contributed to 

reduced water pollutant loads in monitored beach locations, and shifting climate conditions will 

continue to play a role in coastal water quality (Heal the Bay 2014) and subsequently, 

recreational access and safety. 

Recreation

Historic and current recreational use can affect future recreational quality and access, as well as 

exacerbate climate impacts. For example, high recreational fish catches during the 1980s were 

identified as the main driver of depleted near-shore California fisheries and lower catch rates in 

subsequent years (Schroeder and Love 2002). Similarly, trampling of tidepool areas can kill 

component species and degrade future recreational opportunities (MBNMS 2008, Smith et al. 

2008). In addition, recreational users may facilitate invasive species invasion and establishment, 

which can threaten biological communities already being impacted by climate change and/or 

exacerbate climate-driven changes in recreational areas (MBNMS 2008). For example, Chinese 

mitten crabs (Eriocheir sinensis) were likely introduced to the San Francisco Estuary in an 

attempt to establish a new recreational fishery (MBNMS 2008). However, this species 

exacerbates erosion by burrowing, acts as a secondary intermediate host for a pathogen that 

affects marine mammals and humans, and preys on juvenile salmon (MBNMS 2008), whose 

populations are already stressed by changing climatic conditions (Sydeman and Thompson 

2013). 

IV. Other sensitivities

Other critical factors likely to influence the sensitivity of the provision of the ecosystem service: 

population density 

• Confidence of workshop participants: Moderate-High

• Confidence of workshop participants in the degree to which these factors influence the 

sensitivity of the ecosystem service provision: High

Additional participant comments 

Increased population density may result in an increase in recreational usage of coastal areas, 

which if not managed properly, may adversely impact the overall experience of people using and 

visiting coastal areas.

Supporting literature

Increased overall use and demand of marine and coastal resources as a result of population 

growth could affect recreational quality, safety, and availability (Sivas and Caldwell 2008). 

California’s population is projected to grow 38% to include over 51 million residents by 2060, 

with Marin, San Mateo, and San Francisco counties projected to experience population increases 

of roughly 12%, 17%, and 77%, respectively (numbers relative to 2010 population estimates; 

California Department of Finance 2015). Population increases will likely drive increased 

328
visitation and crowding at regional beaches and other recreational areas, and crowding can be 

exacerbated by regional erosion and reduction in beach widths (King 2001). Surveys of beachgoers in other regions (e.g., Southern California) indicate that increased crowding would 

significantly deter coastal visitation; beach users in northern California likely exhibit the same 

preferences for less crowded recreational opportunities (King 2001). In addition to crowding and 

erosion concerns, traffic (i.e., the time it takes to reach a recreational destination) and 

competition for parking also significantly influence coastal visitation rates, and will be affected 

by population growth (King 2001). 

Adaptive Capacity

I. Intrinsic Value

Value of the ecosystem service to people: High 

• Confidence of workshop participants: High

Degree to which people are willing to change their behavior to ensure provision of the ecosystem 

service: Moderate-High

• Confidence of workshop participants: Moderate

Economic drivers that play a role in the management of the ecosystem service: Recreation and 

tourism are driven, to a large extent, by economics. 

Can the ecosystem service be accessed elsewhere, and how important is it to ensure provision of 

the ecosystem service in its current location(s): Yes. Because recreation and tourism have a large 

impact on the Northern California economy it is important that they do not shift to another 

location(s). 

Supporting literature

Coastal and marine recreation and tourism are major contributors to California’s economy 

(Dwight et al. 2007, Hanak and Moreno 2008), mirroring trends across the nation (Boesch et al. 

2000). For example, they contributed $11 billion to California’s gross domestic product in 2004 

(Hanak and Moreno 2008), and have increased in value while other marine industries have 

decreased (Sivas and Caldwell 2008). Further, coastal recreation is highly valued by California 

citizens, with roughly 72% of the population visiting the coast at least once per year (Public 

Policy Institute of California 2003 cited in Pendleton et al. 2006).

However, place-based recreational and tourism operations typically have a limited ability to shift 

in response to changing climate conditions (Hall and Higham 2005), especially in north-central 

coastal California where access is highly restricted by topography (e.g., rocky cliffs) (Gleason et 

al. 2010). Conversely, consumers have much higher mobility (Hall and Higham 2005), and shifts 

in recreation/tourism supply and price can lead to positive feedback loops of declining demand 

(Shaw and Loomis 2008, Morris and Walls 2009), underscoring the importance of maintaining 

current opportunities within the study region. 

329
II. Management Potential

Rigidity / specificity of rules governing the provision of the ecosystem service or the areas that 

provide the ecosystem service: Moderate

• Confidence of workshop participants: High

Conflicts with other services in the region: Yes

• Conflicting services: water quality, harvest (food production), research opportunities, 

biodiversity, and future energy production 

Services that mutually benefit from the provision of the ecosystem service: none 

Likelihood of managing or alleviating climate change impacts on the provision of the ecosystem 

service: none given

Additional participant comments 

Recreation and tourism services are probably the easiest of the ecosystem services to mitigate the 

impacts of climate change. New supporting infrastructure can be built, additional regulations can 

be put in place, and efforts to educate and encourage behavioral changes in people that reduce 

the impacts of increased tourism and recreation can be pursued. 

Supporting literature

Although north-central California tourism and recreational industries have limited ability to shift 

location in response to changing climate conditions (Hall and Higham 2005), there are 

opportunities to diversify and market new and/or adapted activities to better take advantage of 

current shoulder-season/low use periods and changing environmental conditions (Amelung et al. 

2007, WTO and UNEP 2008). In addition, there are many adaptation options to maintain 

recreational/tourism access and mitigate infrastructure vulnerability (WTO and UNEP 2008). For 

example, monitoring programs, live webcams and up-to-date webpages, and detailed coastal 

management plans can help distribute use impacts and relocate activities in response to shortterm perturbations (e.g., water quality related beach closures) (WTO and UNEP 2008). In 

addition, protecting and enhancing beach, wetland, and other nearshore ecosystems provides 

multiple benefits, as these locations are both used for recreational and tourism activities and 

protect critical tourism infrastructure from flooding, sea level rise, storm surge and other 

environmental changes (WTO and UNEP 2008). 

However, managing for recreational opportunities requires balancing with other management 

objectives. For example, beach nourishment can offset erosion loss occurring on some coastal 

beaches, but has environmental implications and constraints and is less feasible in areas 

experiencing high wave energy (Hanak and Moreno 2008). Similarly, tide pool access needs to 

balance visitor demand while protecting sensitive fauna that respond negatively to disturbance 

(Smith et al. 2008). Visitation and activity regulations can be used to mitigate recreational 

impacts, particularly in the face of population growth and increasing demand for coastal 

recreation, but regulation effectiveness will largely depend on enforcement and designing 

regulations to mitigate the most severe impacts (Smith et al. 2008). 

Some recreational and tourism activities conflict with other services; for example, high scuba 

diving use can undermine biodiversity and conservation (Davis and Tisdell 1995), pollution from 

recreational users (e.g., beach trash, fishing gear, motor oil) can impair water quality (Shealvy 

330
and Register 2007), and recreational fishing, even catch-and-release, can affect future harvest 

levels (Schroeder and Love 2002). 

III. Other adaptive capacity factors

Other critical factors that may affect the provision of the ecosystem service: Education of the 

general public, decision-makers, and regulators 

Degree to which these factors affect the provision of the ecosystem service: High

• Confidence of workshop participants: Moderate

Additional participant comments 

Future climate and climate-driven changes may result in an overall increase in the use of a 

limited number of areas, which in turn, could adversely impact wildlife and habitats that provide 

other important ecosystem services. Accordingly, education of the general public and decisionmakers will be very important to reduce the impacts of potential increases in recreation and 

tourism activities.

Supporting literature

Recreation and tourism can be used to increase education and awareness for marine and coastal 

issues. For example, federal and state agencies can coordinate with recreation providers and 

tourism operations to incorporate environmental education into their “on the water experiences” 

(MBNMS 2008). In addition, there are ample opportunities to increase education in coastal areas 

(e.g., beaches) (MBNMS 2008). 

Exposure 

I. Future climate exposure2

Degree of to which the provision of the ecosystem service is likely to be affected by climate 

change: Moderate-High

• Confidence of workshop participants: High 

Future climate and climate-driven changes identified: air temperature, sea surface temperature, 

sea level rise, wave heights, prevailing wind patterns, storm intensity

Literature Cited

Amelung, B., S. Nicholls and D. Viner. 2007. Implications of global climate change for tourism flows and 

seasonality. Journal of Travel Research 45 (3):285-296.

Barnard, P. L., J. Allan, J. E. Hansen, G. M. Kaminsky, P. Ruggiero and A. Doria. 2011. The impact of the 2009–10 

El Niño Modoki on US west coast beaches. Geophysical Research Letters 38 (13).

Barnard, P. L., D. H. Schoellhamer, B. E. Jaffe and L. J. McKee. 2013. Sediment transport in the San Francisco Bay 

coastal system: An overview. Marine Geology 345:3-17.

Boesch, D. F., J. C. Field and D. Scavia. 2000. The potential consequences of climate variability and change on 

coastal areas and marine resources: Report of the Coastal Areas and Marine Resources Sector Team, U.S. 

National Assessment of the Potential Consequences of Climate Variability and Change, U.S. Global 

2 Supporting literature for future exposure to climate factors is provided in the introduction.

331
Change Research Program. In NOAA Coastal Ocean Program Decision Analysis Series No. #21. Silver 

Springs, MD.

Caldwell, M. and C. H. Segall. 2007. No day at the beach: sea level rise, ecosystem loss, and public access along the 

California coast. Ecology LQ 34:533.

California Department of Finance. 2015. Report P-1: Summary Population Projections by Race/Ethnicity and by 

Major Age Groups. Report P-1 (County): State and County Total Population Projects, 2010-2060 (5-year 

increments). Accessed March 2015. http://www.dof.ca.gov/research/demographic/reports/projections/P-1/

California Environmental Protection Agency. 2015. California Beach Water Quality Information Page. Accessed 

March 2015. http://www.swrcb.ca.gov/water_issues/programs/beaches/beach_water_quality/.

Cayan, D. R., E. P. Maurer, M. D. Dettinger, M. Tyree and K. Hayhoe. 2008. Climate change scenarios for the 

California region. Climatic Change 87 (1):21-42.

Cole, J. 2000. Coastal sea surface temperature and coho salmon production off the north‐west United States. 

Fisheries Oceanography 9 (1):1-16.

Culver, C. S. and A. M. Kuris. 2000. The apparent eradication of a locally established introduced marine pest. 

Biological Invasions 2 (3):245-253.

Davis, D. and C. Tisdell. 1995. Recreational scuba-diving and carrying capacity in marine protected areas. Ocean & 

Coastal Management 26 (1):19-40.

Diana, J. S. 2009. Aquaculture production and biodiversity conservation. Bioscience 59 (1):27-38.

Dwight, R. H., M. V. Brinks, G. Sharavana-Kumar and J. C. Semenza. 2007. Beach attendance and bathing rates for 

Southern California beaches. Ocean & Coastal Management 50 (10):847-858.

Feagin, R. A., D. J. Sherman and W. E. Grant. 2005. Coastal erosion, global sea-level rise, and the loss of sand dune 

plant habitats. Frontiers in Ecology and the Environment 3 (7):359-364.

Gleason, M., S. McCreary, M. Miller-Henson, J. Ugoretz, E. Fox, M. Merrifield, W. McClintock, P. Serpa and K. 

Hoffman. 2010. Science-based and stakeholder-driven marine protected area network planning: A 

successful case study from north central California. Ocean & Coastal Management 53 (2):52-68.

Gulf of the Farallones National Marine Sanctuary (GFNMS). 2008. GFNMS Management Plan.

Hall, C. M. and J. E. Higham. 2005. Tourism, recreation, and climate change. Vol. 22: Channel View Publications.

Hanak, E. and G. Moreno. 2008. California coastal management with a changing climate. Climatic Change 111 

(1):45-73.

Hansen, J. E. and P. L. Barnard. 2010. Sub-weekly to interannual variability of a high-energy shoreline. Coastal 

Engineering 57 (11):959-972.

Hapke, C. J., D. Reid and B. Richmond. 2009. Rates and trends of coastal change in California and the regional 

behavior of the beach and cliff system. Journal of Coastal Research:603-615.

Harvell, C. D., C. E. Mitchell, J. R. Ward, S. Altizer, A. P. Dobson, R. S. Ostfeld and M. D. Samuel. 2002. Climate 

warming and disease risks for terrestrial and marine biota. Science 296 (5576):2158-2162.

Heal the Bay. 2014. 2013-2014 Annual Beach Report Card.

Intergovernmental Panel on Climate Change (IPCC). 2007. Summary for policy makers. In Climate Change 2007: 

Impacts, Adaptation, and Vulnerability. Contribution of the Working Group II to the Fourth Assessment 

Report of the Intergovernmental Panel on Climate Change, edited by M.L. Parry, O.F. Canziani, J.P. 

Palutikof, P.J. Van Der Linden and C.E. Handson. Cambridge, UK.

Jessup, D. A., M. Miller, J. Ames, M. Harris, C. Kreuder, P. A. Conrad and J. A. Mazet. 2004. Southern sea otter as 

a sentinel of marine ecosystem health. EcoHealth 1 (3):239-245.

Jester, R. J., K. A. Baugh and K. A. Lefebvre. 2009. Presence of Alexandrium catenella and paralytic shellfish 

toxins in finfish, shellfish and rock crabs in Monterey Bay, California, USA. Marine Biology 156 (3):493-

504.

King, P. G. 2001. Overcrowding and the Demand for Beaches in Southern California." A Report prepared for the 

Department of Boating and Waterways. 

Knowles, N. 2010. Potential inundation due to rising sea levels in the San Francisco Bay region. San Francisco 

Estuary and Watershed Science 8(1).

Lafferty, K. D. and T. Ben-Horin. 2013. Abalone farm discharges the withering syndrome pathogen into the wild. 

Frontiers in Microbiology 4:373.

Lafferty, K. D., C. D. Harvell, J. M. Conrad, C. S. Friedman, M. L. Kent, A. M. Kuris, E. N. Powell, D. Rondeau 

and S. M. Saksida. 2015. Infectious diseases affect marine fisheries and aquaculture economics. Annual 

Review of Marine Science 7:471-496.

Largier, J. L., B. S. Cheng and K. D. Higgason (editors). 2010. Report of a Joint Working Group of the Gulf of the 

Farallonesand Cordell Bank National Marine Sanctuaries Advisory Councils. 

332
Lewitus, A. J., R. A. Horner, D. A. Caron, E. Garcia-Mendoza, B. M. Hickey, M. Hunter, D. D. Huppert, R. M. 

Kudela, G. W. Langlois and J. L. Largier. 2012. Harmful algal blooms along the North American west 

coast region: History, trends, causes, and impacts. Harmful Algae 19:133-159.

Monterey Bay National Marine Sanctuary (MBNMS). 2008. Monterey Bay National Marine Sanctuary Final 

Management Plan.

Moreno, A. and B. Amelung. 2009. Climate change and coastal & marine tourism: review and analysis. Journal of 

Coastal Research (SI 56):1140-1144.

Morris, D. and M. A. Walls. 2009. Climate change and outdoor recreation resources. Washington, D.C.: Resources 

for the Future.

Moser, S., G. Franco, S. Pittiglio, W. Chou and D. Cayan. 2009. The future is now: an update on climate change 

science impacts and response options for California. California Energy Commission Public Interest Energy 

Research Program CEC-500-2008-071. 

Moser, S. C. and J. Tribbia. 2007. Vulnerability to inundation and climate change impacts in California: coastal 

managers' attitudes and perceptions. Marine Technology Society Journal 40 (4):35-44.

National Oceanic and Atmospheric Administration (NOAA). 2011. Southern California Eelgrass Mitigation Policy.

Nelson, E. J., P. Kareiva, M. Ruckelshaus, K. Arkema, G. Geller, E. Girvetz, D. Goodrich, V. Matzek, M. Pinsky 

and W. Reid. 2013

Pendleton, L. H. 2010. The economic and market value of coasts and estuaries: what's at stake?

Pendleton, L., J. Kildow and J. Rote. 2006. The non-market value of beach recreation in California. Shore and 

Beach 74 (2):34.

Sallenger, A. H., W. Krabill, J. Brock, R. Swift, S. Manzinar and H. F. Stockdon. 2002. Sea-Cliff erosion as a 

function of beach changes and extreme wave run-up during the 1997-98 El Niño. Marine Geology 187:279-

297.

Schroeder, D. M. and M. S. Love. 2002. Recreational fishing and marine fish populations in California. California 

Cooperative Oceanic Fisheries Investigations Report.

Shaw, D. and J. Loomis. 2008. Frameworks for Analyzing the Economic Effects of Climate Change on Outdoor 

Recreation and Selected Estimates. Climate Research 36 (3):259-69.

Sheavly, S. and K. Register. 2007. Marine debris & plastics: environmental concerns, sources, impacts and 

solutions. Journal of Polymers and the Environment 15 (4):301-305.

Simas, T., J. Nunes and J. Ferreira. 2001. Effects of global climate change on coastal salt marshes. Ecological 

Modeling 139 (1):1-15.

Sivas, D. A. and M. R. Caldwell. 2008. New Vision for California Ocean Governance: Comprehensive EcosystemBased Marine Zoning, A. Stanford Environmental Law Journal 27:209-270.

Smith, J. R., P. Fong and R. F. Ambrose. 2008. The impacts of human visitation on mussel bed communities along 

the California coast: are regulatory marine reserves effective in protecting these communities?. 

Environmental Management 41 (4):599-612.

Stamski, R. 2005. The Impacts of Coastal Protection Structures in California’s Monterey Bay National Marine 

Sanctuary. In Marine Sanctuary Conservation Series. 

Storlazzi, C. D. and G. B. Griggs. 2000. Influence of El Niño–Southern Oscillation (ENSO) events on the evolution 

of central California's shoreline. Geological Society of America Bulletin 112 (2):236-249.

Sydeman, W., and S.A. Thompson. 2013. Potential Impacts of Climate Change on California’s Fish and Fisheries. 

Oakland, CA: Farallon Institute for Advanced Ecosystem Research. Literature Review.

Sydeman, W. J., J. A. Santora, S. A. Thompson, B. Marinovic and E. D. Lorenzo. 2001. Climate change, 

reproductive performance and diet composition of marine birds in the southern California Current system, 

1969–1997. Progress in Oceanography 49 (1):309-329. 

Turbow, D., T. H. Lin and S. Jiang. 2004. Impacts of beach closures on perceptions of swimming-related health risk 

in Orange County, California. Marine Pollution Bulletin 48 (1):132-136.

White, T., M. Dethier and M. Eisenlord. 2014. The effects that diet, salinity and temperature contribute to Seastar 

Wasting Disease in Pycnopodia helianthoides and field surveying Pisaster ochraceus.

Wingfield, D. K. and C. D. Storlazzi. 2007. Spatial and temporal variability in oceanographic and meteorologic 

forcing along Central California and its implications on nearshore processes. Journal of Marine Systems 68 

(3):457-472.

World Tourism Organization (WTO) and United Nations Environement Programme (UNEP). 2008. Climate Change 

and Tourism: Responding to Global Challenges. Madrid, Spain.

333
Water Purification1

Executive Summary Water purification is a critically important ecosystem service provided by California coastal 

wetlands and filter-feeding organisms 

(e.g., oysters and mussels). Through 

various physical, biological, and 

chemical processes, wetlands and filterfeeding organisms purify surface and 

groundwater by trapping sediment, 

altering water chemistry, and removing pollutants such as metals, viruses, oils, pesticides and 

nutrients (e.g., nitrogen). The purified water supplied by California’s coastal wetlands supports 

numerous industries, recreational activities, and wildlife habitats, and supplies clean drinking 

water to many local communities by recharging groundwater supplies (Osmond et al. 1995). Key 

climate sensitivities identified by workshop participants include sea level rise, storm activity, and 

precipitation. Key non-climate sensitivities include land use change, pollution, and recreation. 

Water purification is highly valued by the general public, especially for recreational 

opportunities and for the health of harvested seafood. Restoration activities are critical in 

ameliorating the impacts of human-caused sedimentation, and management activities should 

focus on those areas with the greatest potential for recovery and resilience (including potential 

for inland migration and sufficient sedimentation to keep pace with sea level rise). Additionally, 

improved communication and collaboration among the multiple agencies responsible for 

managing water quality may help ensure the provision of this ecosystem service. 

Sensitivity 

I. Sensitivity of ecosystem service components Sensitivity of the provision of the ecosystem service to climate and climate-driven changes: 

Moderate-High

• Confidence of workshop participants: High 

Climate and climate-driven changes identified: ocean pH, sea level rise, dissolved oxygen levels, 

turbidity, storminess, coastal erosion, wave action, and circulation 

Climate and climate-driven changes that may benefit the provision of the ecosystem service: sea 

surface temperature

• Description of benefits: Increases in sea surface temperature may lead to increases in 

eelgrass. 

Additional participant comments 

Changes in large-scale circulation and assemblages of filter feeding organisms will impact the 

provision of the water purification ecosystem service.

1 Refer to the introductory content of the results section for an explanation of the format, layout and content of this 

summary report.

Water Purification Score Confidence 

Sensitivity 4 Moderate-High 3 High

Exposure 4 Moderate-High 3 High

Adaptive Capacity 3 Moderate 3 High

Vulnerability 3 Moderate 3 High

334
Supporting literature

Ocean pH

Filter-feeding animals, such as oysters and mussels, contribute significantly to the cleaning of 

water in coastal wetlands. These organisms exhibit sensitivity to changes in ocean pH; for 

example, lower ocean pH levels have been shown to cause decreased rates of calcification and

reduced rates of development in mussels and oysters (Talmage and Gobler 2009), as well as

decreased metabolism in mussels (Michealidis et al. 2005). Lower ocean pH levels have also 

been shown to increase oyster and mussel larval mortality and result in smaller-sized adults with 

reduced filtration capacity (Michealidis et al. 2005). 

Sea level rise

Coastal wetlands, which improve water quality by removing pollutants, trapping sediment, and 

altering water chemistry and nutrient levels through a variety of biological, physical, and 

chemical processes (Ecological Society of America 2015), are vulnerable to sea level rise. 

However, the overall vulnerability of wetlands and associated water purification services to sea 

level rise will depend upon several factors including vertical accretion rates (influenced by the 

deposition of inorganic sediments or the accumulation and burial of organic material), 

compaction and subsidence rates, and the ability of wetlands to expand and/or migrate. Rising 

sea levels may initially increase estuarine surface area and result in increased plant biomass 

production, potentially influencing water purification processes by slowing water velocity and 

facilitating mineral and organic particle deposition (Carter 1997). Conversely, rates of sea level 

rise that exceed the vertical accretion rate of sediment and organic material will eventually 

drown low-lying estuarine areas (Mudd et al. 2009, Kirwan and Temmerman 2009). Coastal 

wetland habitats that are unable to expand or migrate in response to rising sea levels because of 

natural barriers or man-made structures, or are unable to vertically accrete at a pace equal to, or 

greater than, the rate of sea level rise will eventually experience a decrease in biogenic habitat 

(Harley et al. 2006). Coastal wetlands that are more dependent on organic accumulation rather 

than inorganic sediment deposition will likely be more impacted by rising sea levels (Stevenson 

et al. 1986, Stevenson and Kearney 2009). Salt marshes located in estuaries with low tidal ranges 

are expected to be more sensitive to rising sea levels due to decreased rates of sediment transport 

and vertical accretion (Simas et al. 2001). The impacts of rising sea levels may be negligible on 

coastal wetlands that are able to vertically accrete at rates that equal or exceed rates of sea level 

rise.

Dissolved oxygen levels 

Dissolved oxygen (DO) is essential for many benthic organisms in coastal wetland habitats, 

including filter-feeding oysters. Low levels of DO can increase stress on adult oysters and may

increase mortality in juvenile oysters (Widdows et al. 1989). Extremely low levels of DO, or 

hypoxic conditions, can result in the loss of oysters and oyster reef habitat (Lenihan and Peterson 

1998). 

Circulation

Changes in coastal wetland circulation can impact dispersal and recruitment of marine 

organisms, and may result in reduced nutrient supplies with negative impacts on aquatic 

vegetation and filter-feeding organisms (Harley et al. 2006). 

335
Turbidity 

Increased turbidity will decrease the amount of light aquatic plants receive, reducing primary 

productivity. This may negatively impact filter-feeding animals, such as oysters, that depend on 

the oxygen generated by aquatic vegetation during primary production (NOAA 2012). 

Storminess / wave action / coastal erosion 

Climate change is expected to result in more extreme storm events with stronger winds, larger 

storm surges, and larger waves. Additionally, climate change may result in increased short 

duration/high precipitation events, which can increase the amount of pollution and sediment 

runoff. Changes in storm intensity may also result in changes to sediment transport and 

deposition processes (Simas, Nunes and Ferreira 2001), alter the timing of estuarine mouth 

opening and closing, increase soil and vegetation turnover, and increase water turbidity. The 

impact of these disturbances on vegetative habitats and filter-feeding organisms in coastal 

wetlands will depend upon specific storm and local geomorphological conditions (Simas, Nunes 

and Ferreira 2001). Winter waves, driven by extra-tropical cyclones in the North Pacific, can be 

in excess of 8 m (Wingfield and Storlazzi 2007) and erode shorelines and alter sediment 

transport and deposition processes (Scavia et al. 2002). Changes in wave height and direction 

will also expose previously sheltered areas to significant levels of erosion (Sallenger et al. 2002), 

which may have significant negative impacts on sensitive coastal wetland habitats. 

II. Sensitivity to disturbance regimes

Disturbance regimes identified: disease2, flooding, and storms 

Overall sensitivity of the provision of the ecosystem service to disturbance regimes: ModerateHigh

• Confidence of workshop participants: High

Additional participant comments 

Although the overall impact on the provision of the water purification ecosystem service will be 

high, local responses to climate and climate-driven changes will vary.

Supporting literature

Flooding 

Coastal wetlands are sensitive to changes in flooding patterns and sediment loading (Ramsar 

2002), which can impact vertical accretion rates. Although coastal wetlands are tolerant of 

periodic flooding, a flooding threshold likely exists, and longer flood durations and/or more 

frequent flooding can increase erosion and decrease organic plant contributions, accelerating 

wetland habitat deterioration (Kirwan and Megonigal 2013) and undermining the provision of 

water purification services. Additionally, although wetlands depend on surface water flows to 

deliver sediment from upstream watersheds, extended freshwater flooding can cause oxygen 

deficiencies that affect biological and biogeochemical functioning (Carter 1997). 

Storms

Storms constantly reshape coastal wetlands through erosive and depositional processes. 

Energetic winter storms tend to be more erosive. The overall impact of storms on coastal 

wetlands will depend on specific geomorphological conditions and the intensity and direction of 

2 Though peer-reviewed literature may exist, staff review was unable to locate supporting literature for this stressor. 

336
storms, as well as tides, currents, and other physical factors (Moran 2011). See discussion above 

under storminess/wave action/coastal erosion. 

III. Sensitivity and exposure to non-climate stressors

Non-climate stressors identified: land use changes, overwater/underwater structures, coastal 

roads and armoring, invasive species3, and pollution and poisons 

Degree to which non-climate stressors affect the provision of the ecosystem service: Moderate

• Confidence of workshop participants: Moderate

Degree to which non-climate stressors affect the sensitivity of the provision of the ecosystem 

service to climate change: Moderate-High

• Confidence of workshop participants: Moderate

Additional participant comments 

Land use changes, specifically the movement/expansion of wineries towards the coast in 

response to climate change and market forces, have had significant impacts on coastal wetlands 

and their ability to provide water purification services. Sea level rise and the resulting “coastal 

squeeze” will reduce the size of available coastal wetland habitat and reduce the overall capacity 

of coastal wetlands to provide this important ecosystem service. 

Supporting literature

Land use changes

Reclamation, engineering, and urbanization have resulted in the loss of extensive areas of 

seagrass and salt marsh (Mcleod et al. 2011). Increased sedimentation from land use changes 

may result in the burying of vegetative and oyster habitat, or increase the duration of estuary 

mouth closure. Freshwater diversions for agriculture and other human uses can result in

hypersaline conditions, reduced estuarine circulation, or more persistent closures of estuary 

mouths due to reduced tidal prism (ONMS 2010), all of which can negatively impact vegetative 

and oyster habitats. 

Overwater/underwater structures

Overwater and underwater structures alter light regimes, wave energy, sediment and transport 

processes, substrate, and water quality, which can limit plant growth and recruitment or result in 

altered plant assemblages (Nightingale and Simenstad 2001). 

Coastal roads and armoring 

Coastal armoring and road construction can prevent the inland migration or expansion of coastal 

wetland habitats in response to sea level rise. Where the inland border of coastal wetland habitats 

abuts roads, levees, or other armored structures, an accelerated loss of habitat may be expected 

(Fletcher et al. 1997, Dugan et al. 2008). Road construction and coastal armoring continue to 

affect the study region, specifically in Bolinas Lagoon, Tomales Bay, and other areas of coastal 

development. Although the impacts of these structures are generally localized, they can be severe

as they can result in the conversion and loss of habitat type and increase erosion rates (ONMS 

2010). 

3 Though peer-reviewed literature may exist, staff review was unable to locate supporting literature for this stressor. 

337
Pollution and poisons 

Coastal eutrophication, resulting from excess nutrient runoff from terrestrial sources, leads to 

lower DO levels, which may lead to increased stress and mortality in filter-feeding oysters and 

increased epiphytic algae and macroalgae. Increased epiphytic algae reduces available light for 

primary production, and can result in extensive loss of submerged aquatic vegetation (Duarte 

2002, Mcleod et al. 2011). 

IV. Other sensitivities: none identified

Adaptive Capacity

I. Intrinsic value

Value of the ecosystem service to people: High 

• Confidence of workshop participants: High

Degree to which people are willing to change their behavior to ensure provision of the ecosystem 

service: Moderate 

• Confidence of workshop participants: Moderate

Economic drivers that play a role in the management of the ecosystem service: recreational 

opportunities and health of locally produced seafood 

Can the ecosystem service be accessed elsewhere, and how important is it to ensure provision of 

the ecosystem service in its current location(s): There is limited access to clean water. Continued 

provision of this ecosystem service is critically important to numerous local communities in the 

region. 

Additional participant comments

Human intervention through increased bivalve aquaculture activities and restoration of coastal 

wetlands, will be needed to ensure the provision of water purification services in the future. 

II. Management potential

Rigidity / specificity of rules governing the provision of the ecosystem service or the areas that 

provide the ecosystem service: Moderate-High

• Confidence of workshop participants: High

Conflicts with other services in the region: none identified

Services that mutually benefit from the provision of the ecosystem service: food production and 

recreation

Likelihood of managing or alleviating climate change impacts on the provision of the ecosystem 

service: The likelihood will depend on public support and the political will to manage coastal 

wetlands as a “living shoreline”, including reducing coastal development and only approving 

aquaculture activities in appropriate locations.

338
Additional participant comments

There are currently an abundance of rules and regulations governing coastal wetlands from 

multiple management agencies with overlapping jurisdictions. Improved communication and 

collaboration between these agencies can help ensure the provision of the water purification 

ecosystem service. Coastal wetland restoration projects, such as the efforts in Bolinas Bay to 

ameliorate the impacts of human-caused sedimentation, are already successfully underway. 

Coastal wetlands that are bound by natural or man-made barriers, or have insufficient rates of 

sedimentation, may be unable to move/migrate in response to rising sea levels and changing 

climactic conditions. This could result in the loss of significant portions of the region’s coastal 

wetlands. Accordingly, it is critical that resource managers first identify coastal wetland areas 

with the highest adaptive capacities, and subsequently focus restoration and maintenance efforts 

on those areas. 

III. Other adaptive capacity factors Other critical factors that may affect the provision of the ecosystem service: sedimentation rates

Degree to which these factors affect the provision of the ecosystem service: High

• Confidence of workshop participants: no answer provided 

Additional participant comments 

Sedimentation rates that equal or exceed rates of sea level rise are required to maintain marsh 

plain areas and prevent the submersion of coastal wetland areas.

Exposure 

I. Future climate exposure4 

Degree of to which the provision of the ecosystem service is likely to be affected by climate 

change: Moderate-High

• Confidence of workshop participants: High 

Future climate and climate-driven changes identified: sea surface temperature, ocean pH, sea 

level rise, dissolved oxygen (DO) levels, turbidity, storm intensity, coastal erosion, wave action, 

and circulation

Additional participant comments

Restoration of coastal wetlands can help ensure the provision of this and other important 

ecosystem services in the future.

Literature Cited

Carter, V. 1997. Technical Aspects of Wetlands: Wetland Hydrology, Water Quality, and Associated Functions. 

United States Geological Survey Water Supply Paper 2425. 

Duarte, C.M. 2002. The future of seagrass meadows. Environ Conserv 29: 192-206.

Dugan, J.E., D.M. Hubbard, I. F. Rodil, D. L. Revell and S. Schroeter. 2008. Ecological effects of coastal armoring

 on sandy beaches. Marine Ecology 29: 160-170.

4 Supporting literature for future exposure to climate factors is provided in the introduction.

339
Fletcher, C. H., R. A. Mullane, B. M. Richmond. 1997. Beach loss along armored shorelines on Oahu, Hawaiian 

Islands. Journal of Coastal Research 13: 209-215.

Ecological Society of America (ESA). 2015. Water Purification Fact Sheet. Accessed March 2015. 

http://www.esa.org/ecoservices/comm/body.comm.fact.wate.html. 

Geyer, W.R. 1997. Influence of Wind on Dynamics and Flushing of Shallow Estuaries. Estuarine, Coastal and Shelf 

Science 44: 713-722.

Harley, C.D.G., A. Randall Hughes, K.M. Hultgren, B.G. Miner, C.J.B. Sorte, C.S. Thornber, L.F. Rodriguez, L. 

 Tomenek, and S.L. Williams. 2006. The impacts of climate change in coastal marine systems. Ecology

 Letters, 9: 228-241. doi: 10.1111/j.1461-0248.2005.00871.x 

Kirwan, M. L. and J. P. Megonigal. 2013. Tidal wetland stability in the face of human impacts and sea-level rise. 

Nature 504 (7478):53-60.

Kirwan, K. and S. Temmerman. 2009. Coastal marsh response to historical and future sea-level acceleration. 

Quarterly Science Reviews 28(17): 1801-1808. 

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and 

Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp.

Lenihan, H. and C.H. Peterson. 1998. How Habitat Degradation Through Fishery Disturbance Enhances Impacts Of 

 Hypoxia On Oyster Reefs. Ecological Applications 8(1): 128-140.

Mcleod, E., G.L. Chumra, S. Bouillon, R. Salm, M. Björk, C.M. Duarte, C.E. Lovelock, W.H. Schlesinger, and B.R. 

Silliman. 2011. A blueprint for blue carbon” toward an improved understanding of the role of vegetated 

coastal habitats in sequestering CO2. Front Ecol Environ 9(10): 552-560. doi: 10.1890/110004.

Michaelidis, B., C. Ouzounis, A. Paleras, and H.O. Pörtner. 2005. Effects of long-term moderate hypercapnia on 

 acid-base balance and growth rate in marine mussels Mytilus galloprovinciallis. Mar. Ecol. Prog. Ser. 293:

 109-118.

Moran, J. 2011. Ocean Studies: Introduction to Oceanography, Third Edition. American Meteorological Society. 

Boston MA. 

Mudd S.M., S.M. Howell, and J.T. Morris. 2009. Impact of dynamic feedbacks between sedimentation, sea-level 

rise, and biomass production on near-surface marsh stratigraphy and carbon accumulation. Estuarine, 

Coastal and Shelf Science 82:377-389.

National Oceanic and Atmospheric Administration (NOAA). 2012. Turbidity.

 http://oceanservice.noaa.goveducation/kits/estuaries/media/supp_estuar10e_turbinity.html. 

Nightingale, B., and C.A. Simenstad. 2001. OVERWATER STRUCTURES: MARINE ISSUES. Washington State 

Transportation Commission. Seattle, Washington.

Office of National Marine Sanctuaries (ONMS). 2010. Gulf of the Farallones National Marine Sanctuary Condition 

Report. U.S. Department of Commerce, National Oceanic and Atmospheric Administration, Office of 

National Marine Sanctuaries, Silver Spring, MD. 97 pp.

Osmond, D.L., D.E. Line, J.A. Gale, R.W. Gannon, C.B. Knott, K.A. Bartenhagen, M.H. Turner, S.W. Coffey, J. 

Spooner, J. Wells, J.C. Walker, L.L. Hargrove, M.A. Foster, P.D. Robillard, and D.W. Lehning. 1995. 

Values of wetlands. Available at http://www.water.ncsu.edu/watershedss/info/wetlands/values.html. 

The Ramsar Convention on Wetlands (Ramsar). 2002. Climate Change and Wetlands: Impacts, Adaptation and 

Mitigation. Ramsar COP8 DOC. 11 Information Paper. Available at 

http://archive.ramsar.org/cda/es/ramsar-documents-standing-ramsar-cop8-doc-11/main/ramsar/1-31-

41%5E17764_4000_2__

Sallenger, A.H., W. Krabill, J. Brock, R. Swift, S. Manizade, H. Stockdon. 2002. Sea-cliff erosion as a function of 

beach changes and extreme wave runup during the 1997-1008 El Nino. Marine Geology 187:279-97.

Scavia D., Field J.C., Boesch D.F., Buddemeier R.W., Burkett V., Cayan D.R., Fogarty M., Harwell M.A., Howart 

R.W., Mason C. 2002. Climate change impacts on U.S. coastal and marine ecosystems. Estuaries 

25(2):149-64. 

Simas, T., J.P. Nunes, and J.G. Ferreira. 2001. Effects of global climate change on coastal salt marshes. Ecological 

Modeling 139: 1-15.

Stevenson, J. C., L. G. Ward, and M. S. Kearney. 1986. Vertical accretion in marshes with varying rates of sea level 

rise. Pages 241–259 in D. Wolf (ed.), Estuarine Variability. New York: Academic Press. 

Stevenson, J.C. and M.S. Kearney. 2009. Impacts of global climate change and sea level rise on tidal wetlands. In: 

Silliman, B.R., Grosholz, E.D. and Bertness, M.D. (eds). Human Impacts on Salt Marshes. Berkeley, CA: 

University of California Press. 

Talmage, S.C. and C.J. Gobler. 2009. The effects of elevated carbon dioxide concentrations on the metamorphosis, 

340
size, and survival of larval hard clams (Mercenaria mercenaria), bay scallops (Argopecten irradians), and 

Eastern oysters (Crassostrea virginica). Limnology and Oceanography. 54(6): 2072-2080.

Widdows, J., R.E.I. Newell, and R. Mann. 1989. Effects of Hypoxia and Anoxia on Survival, Energy Metabolism, 

and Feeding of Oyster Larvae (Crassostrea virginica, Gmelin). Biological Bulletin, 177(1): 154-166.

Wingfield, D.K. and C.D. Storlazzi. 2007. Variability in oceanographic and meteorologic forcing along Central 

California and its implications on nearshore processes. Journal of Marine Systems 68: 457-472.

341
Conclusions and Next Steps

Marine resource managers realize the immediate threats of climate change to the resilience, 

health, and ecosystem services of the coastal and ocean places they protect, yet the resources to 

develop appropriate management options to prepare for and respond to a changing environment 

are limited (Gregg et al. 2011). This vulnerability assessment provides a foundation for 

understanding how and to what degree resources are threatened by climate change in the Northcentral California coast and ocean region, enabling resource managers and conservation planners 

to set management and planning priorities and more efficiently and effectively allocate resources

to respond to, plan, and manage for the impacts of climate change. 

Representatives from federal and state agencies, non-governmental organizations and academic 

institutions assessed the vulnerability of 44 species, habitats and ecosystem services to the 

impacts of climate change and non-climate stressors. Most resources were assessed as having 

moderate vulnerability, with a range from low-moderate to moderate-high vulnerability. 

Habitats and associated species and ecosystem services that exist at the land-sea interface 

(beaches and dunes, estuaries, and the rocky intertidal) were identified as being most vulnerable, 

and will likely be prioritized for the development of adaptive management recommendations. 

This report is the first step in the development of climate-smart adaptation strategies that can be 

feasibly implemented by managers to help ensure long-term viability of the resources they are 

mandated to protect, and represents the first phase of “Climate-Smart Adaptation for the Northcentral California Coast and Ocean.” The second phase of the project, initiated in early 2015, 

convenes a working group of the GFNMS Advisory Council of scientists and resource managers 

to 1) define distinct future climate scenarios for the study region and 2) develop prioritized 

adaptation action recommendations. Working group members will use this report and the 

Scenario Planning for Climate Change Adaptation guide (Moore et al. 2013) to define distinct 

scenarios for the study region based on the most uncertain and the most important (greatest 

impact) climatic and non-climatic drivers of change. Working Group members will meet and 

evaluate drivers of change that were identified in Phase 1 as contributors to focal resource 

vulnerability and rank those drivers by their relative uncertainty (in future direction and 

magnitude of change) and importance to management decisions. The working group will then 

select the top two or three most uncertain/impactful drivers and cross those drivers to create a set 

of plausible but also divergent scenarios to use in a scenario planning exercise. The working 

group will then name and describe each future scenario in preparation for the development of 

adaptation actions. Scenario planning is a successful and flexible approach to incorporate climate 

uncertainty into decision making to develop adaptation actions for multiple, plausible climate 

futures, and is especially useful when critical drivers of change are highly uncertain and cannot 

be controlled (Moore et al. 2013). Based on National Wildlife Federation and Point Blue 

Climate-Smart Conservation Principles, and using the developed scenarios as a framework, 

working group members will: 1) define criteria for prioritization of adaptation recommendations 

(e.g. feasibility, cost-effectiveness, climate-smart, collaborative, robustness across scenarios); 2) 

brainstorm potential management actions for each future scenario (in an iterative process, which 

may result in further revision of scenarios); 3) evaluate and prioritize brainstormed actions using 

defined criteria; and 4) determine a final set of recommended actions, linked to specific 

geographic locations within the study area. 

342
Recommendations from the working group will be forwarded to the GFNMS Advisory Council 

for approval, and the approved recommendations will then be forwarded to the GFNMS 

superintendent, as well as other coastal resource management agencies in the region for 

consideration in their current or future adaptation planning efforts, including the Point Reyes 

National Seashore, Golden Gate National Recreation Area, California State Parks, California 

Department of Fish and Wildlife, US Fish and Wildlife Service, and the Counties of San Mateo, 

San Francisco, Marin and Sonoma. GFNMS will then adopt a final set of climate-smart 

adaptation strategies based on the Sanctuary Advisory Council recommendations, and work with 

the project team to develop an adaptation implementation plan, including a summary of 

adaptation actions, implementation prioritization and schedule, estimated cost and potential 

funding sources, and potential partners. The Implementation Plan will be divided into three 

project initiation sections: 1) Near-term (less than 5 years to implement; 2) Mid-term (5-10 years 

to implement); and 3) Long-term (over 10 years to implement). GFNMS staff will immediately 

begin incorporating adaptation strategies into sanctuary management as resources allow. 

Immediate actions may include revising permit review criteria, additional analysis on climate 

change impacts incorporated into NEPA documents, and prioritization of restoration activities 

based on climate change impacts.

Potential ecological outcomes of integrating adaptation actions into natural resource management 

in the region include restoring habitats and using nature-based solutions to protect infrastructure 

such as the restoration of hydrologic function and floodplains in Bolinas Lagoon to provide for 

future wetland upland migration as well as flood and erosion control; seagrass restoration and 

protection in Tomales Bay to provide increased habitat, carbon storage and sequestration, 

improved water quality, and protection of shoreside infrastructure by reducing coastal erosion; 

and beach nourishment projects to protect coastal infrastructure. 

343
Literature Cited

Alin S.R., R.A. Feely, A.G. Dickson, J.M. Hernandez-Ayon, L.W. Juranek, M.D. Ohman, R. Goericke. 2012. 

Robust empirical relationships for estimating the carbonate system in the southern California Current System 

and application to CalCOFI hydrographic cruise data (2005-2011). Journal of Geophysical Research, 117.

Auad, G., A. Miller, and E. DiLorenzo. 2006. Long-term forecast of oceanic conditions in California and their 

biological implication. Journal of Geophysical Research 111: C09008.

Barnard, P. L., D. H. Schoellhamer, B. E. Jaffe and L. J. McKee. 2013. Sediment transport in the San Francisco Bay 

coastal system: An overview. Marine Geology 345:3-17.

Black, B.A., W.J. Sydeman, D.C. Frank, D. Griffin, D.W. Stahle, M. Garcia-Reyes, R.R. Rykaczewski, S.J. Bograd, 

W.T. Peterson. 2014. Six centuries of variability and extremes in a coupled marine-terrestrial ecosystem. 

Science 345(6203): 1498-1502.

Bograd, S., C. Castro, E. DiLorenzo, D. Palacios, H. Bailey, W. Gilly, and F. Chavez. 2008. Oxygen declines and 

the shoaling of the hypoxic boundary in the California Current. Geophysical Research Letters 35: L12607.

Cai, W. S. Borlace, M. Lengaigne, P. van Rensch, M. Collins, G. Vecchi, A. Timmermann A. Santoso, M.J. 

McPhaden, L. Wu, M.H. England, G. Wang, E. Guilyardi, F. Jin. 2013. Increasing Frequency of Extreme 

El Nino Events Due to Greenhouse Warming. Nature Climate Change 4: 111-16.

California Energy Commission (CEC). 2006. Our Changing Climate: Assessing the Risks to California. CEC-500-

2006-077, 16pp.

Callaway, J.C., V.T. Parker, M.C. Vasey and L.M. Schile. 2007. Emerging issues for the restoration of tidal marsh

ecosystems in the context of predicted climate change. Madrono. 54: 234-248.

Callaway, J. C., E. L. Borgnis, R. E. Turner and C. S. Milan. 2012. Carbon sequestration and sediment accretion in 

San Francisco Bay tidal wetlands. Estuaries and Coasts 35 (5):1163-1181.

Chan, F., J.A. Barth, J. Lubchenco, A. Kirinich, H. Weeks, W.T. Peterson and B.A. Menge. 2008. Emergence of

anoxia in the California Current large marine ecosystem. Science 319 (920) 

Dallas, K. L. and P. L. Barnard. 2011. Anthropogenic influences on shoreline and nearshore evolution in the San 

Francisco Bay coastal system. Estuarine, Coastal and Shelf Science 92 (1):195-204.

Department of Water Resources (DWR). 2006. Progress on Incorporating Climate Change into Planning and

Management of California’s Water Resources. Technical Memorandum Report. Sacramento, California.

http://baydeltaoffice.water.ca.gov/climatechange/reports.cfm. 

Deutsch, C., S. Emerson, and L. Thompson. 2005, Fingerprints of climate change in North Pacific oxygen. Geophys.

Res. Lett. 32. doi:10.1029/2005GL023190.

Di Lorenzo, E., N. Schneider, K.M. Cobb, P.J.S. Franks, K. Chhak, A.J. Miller, J.C. McWilliams, S.J. Bograd, H. 

Arango, E. Curchitser, T.M. Powell, P. Riviere. 2008. North Pacific Gyre Oscillation links ocean climate 

and ecosystem change, Geophys. Res. Lett., 35, L08607, doi:10.1029/2007GL032838.

Doney, S. C., V. J. Fabry, R. A. Feely, and J. A. Kleypas. 2009. Ocean acidification: The other CO2 problem. 

Annual Review of Marine Science 1:169-192. 

Ekstrom, J. A. and S. C. Moser. 2012. Climate Change Impacts, Vulnerabilities and Adaptation in San Francisco 

Bay: Synthesis. PIER Research Report, Sacramento, Publication # CEC-500-2012-071, 65pp. 

Enfield, D.B. and A.M. Mestas-Nunez. 1999. Multiscale variabilities in global sea surface temperatures and their

relationships with tropospheric climate patterns. Journal of Climate v. 12: 2719-2733.

Feely, R.A., C.L. Sabine, J.M. Hernandez-Ayon, D. Ianson, and B. Hales. 2008. Evidence for upwelling of corrosive 

"acidified" seawater onto the continental shelf. Science 320, 1490.

Fiedler, P. C. 2002. Environmental change in the eastern tropical Pacific Ocean: Review of ENSO and decadal 

variability. Marine Ecology Progress Series 244: 265-283. 

Ganju, N. K. and D. H. Schoellhamer. 2010. Decadal-timescale estuarine geomorphic change under future scenarios 

of climate and sediment supply. Estuaries and Coasts 33 (1):15-29.

Garcia-Reyes, M. and J. Largier. 2010. Observations of increased wind-driven coastal upwelling off central 

California. Journal of Geophysical Research: Oceans (1978–2012) 115: C4.

Gilly, W., U. Markaida, C. Baxter, B. Block, A. Boustany, L. Zeidberg, K. Reisenbichler, B. Robison, G. Bazzino,

and C. Salinas. 2006. Vertical and horizontal migrations by the jumbo squid Dosidicus gigas revealed by

electronic tagging. Marine Ecology Progress Series 324:1-17. 

Glick, P., B.A. Stein, and N.A. Edelson, editors. 2011. Scanning the Conservation Horizon: A Guide to 

Climate Change Vulnerability Assessment. National Wildlife Federation, Washington, D.C.

Gomez-Valdez, J. and G. Jeronimo. 2009. Upper mixed layer temperature and salinity variability in the tropical

boundary of the California Current, 1997-2007. Journal of Geophysical Research –Oceans, v. 114, C03012.

344
Graham, N.E. and H.F. Diaz. 2001. Evidence for intensification of North Pacific winter cyclones since 1948.

Bulletin of the American Meteorological Society 82:1869-1893.

Grantham, B. A., F. Chan, K. J. Nielsen, D. S. Fox, J. A. Barth, A. Huyer, J. Lubchenco and B. A. Menge. 2004.

Upwelling-driven nearshore hypoxia signals ecosystem and oceanographic changes in the northeast Pacific.

Nature 429: 749-754. 

Gregg, R.M., L.J. Hansen, K.M. Feifel, J.L. Hitt, J.M. Kershner, A. Score, and J.R. Hoffman. 2011. The

State of Marine and Coastal Adaptation in North America: A Synthesis of Emerging Ideas. EcoAdapt, 

Bainbridge Island, WA.

Groisman, P., Knight, R. and T. Karl. 2001. Heavy precipitation and high streamflow in the contiguous United

States: trends in the 20th century. Bulletin of the American Meteorological Society 82: 219-246.

Gruber N, Hauri C, Lachkar Z, Loher D, Frolicher TL, Plattner GK. 2012. Rapid progression of ocean acidification 

in the California Current System. Science 337(220). 

Gulf of the Farallones National Marine Sanctuary (GFNMS) Final Management Plan. 2008. Volume II of 

IV. 451 pp.

Hamilton, T.J., Holcombe, A. and Tresguerres, M. 2013. CO2-induced ocean acidification increases anxiety in

 Rockfish via alteration of GABAA receptor functioning. Proceedings of the Royal Society B: Biological

 Sciences 281(1775). 

Hansen, L.J. and J.R. Hoffman, Climate Savvy: Adapting Conservation and Resource Management to a Changing 

 World. Washington, DC: Island Press.

Hauri C., N. Gruber, M. Vogt, S.C. Doney, R.A. Feely, Z. Lachkar, A. Leinweber, A.M.P. McDonnell, M. Munnich,

G.K. Plattner. 2013. Spatiotemporal variability and long-term trends of ocean acidification in the California 

Current System. Biogeosciences 10(1): 193-216.

Hartmann, D.L., A.M.G. Klein Tank, M. Rusticucci, L.V. Alexander, S. Brönnimann, Y. Charabi, F.J. Dentener, 

E.J. Dlugokencky, D.R. Easterling, A. Kaplan, B.J. Soden, P.W. Thorne, M. Wild and P.M. Zhai, 2013: 

Observations: Atmosphere and Surface. In: Climate Change 2013: The Physical Science Basis. 

Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on 

Climate Change [Stocker, T.F., D. Qin, G.-K. Plattner, M. Tignor, S.K. Allen, J. Boschung, A. Nauels, Y. 

Xia, V. Bex and P.M. Midgley (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New

York, NY, USA.

Hein, J. R., K. Mizell and P. L. Barnard. 2013. Sand sources and transport pathways for the San Francisco Bay 

coastal system, based on X-ray diffraction mineralogy. Marine Geology 345:154-169.

Hestir, E. L., D. H. Schoellhamer, T. Morgan-King and S. L. Ustin. 2013. A step decrease in sediment concentration 

in a highly modified tidal river delta following the 1983 El Niño floods. Marine Geology 345:304-313.

International Panel on Climate Change (IPCC). 2007. Summary for Policymakers. In: Climate Change 2007: 

Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the Fourth Assessment Report 

of the Intergovernmental Panel on Climate Change. Parry M.L., O.F. Canziani, J.P. Palutikof, P.J. van der 

Linden and C.E. Hanson (Eds.), Cambridge University Press, Cambridge, UK, 7-22.

International Panel on Climate Change (IPCC). 2014. Summary for policymakers. In: Climate Change 2014: 

Impacts,Adaptation, and Vulnerability. Part A: Global and Sectoral Aspects. Contribution of Working 

Group II to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change [Field, C.B., 

V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea,T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, 

R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L.White (eds.)]. 

Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp. 1-32.

Johnstone, J.A. and T.E. Dawson. 2010. Climate context and ecological implications of summer fog decline in the 

coast redwood region. Proceedings of the National Academy of Sciences, USA 107: 4533 – 4538.

Keeling, R.F. and H.E. Garcia. 2002. The change in oceanic O2 inventory associated with recent global warming. 

Proceedings of the National Academy of Sciences (PNAS) 99: 7848-7853.

Knowles, N. and D.R. Cayan. 2004. Elevational Dependence of Projected Hydrologic Changes in the San 

Francisco Estuary and Watershed. Climatic Change 62(1-3): 319-336.

Knowles, N. 2010. Potential inundation due to rising sea levels in the San Francisco Bay region. San Francisco 

Estuary and Watershed Science 8 (1).

Kim, J., Kim, T., Arritt, R. and N. Miller. 2002. Impacts of increased atmospheric CO2 on the Hydroclimate of the 

Western United States. Journal of Climate 15: 1926-1943.

Kiparsky, M. and P. Gleick. 2005. Climate change and California water resources: a survey and summary of the 

literature. California Water Plan Update, 2005. Sacramento, California. 55 pp

Largier, J.L., B.S. Cheng, and K.D. Higgason, editors. 2010. Climate Change Impacts: Gulf of the Farallones and

345
Cordell Bank National Marine Sanctuaries. Report of a Joint Working Group of the Gulf of the Farallones 

and Cordell Bank National Marine Sanctuaries Advisory Councils. 121pp.

Lebassi, B., J. Gonzalez, D. Fabris, E. Maurer, N. Miller, C. Milesi, P. Switzer, and R. Bornstein. 2009. Observed 

1948-2005 Cooling of summer daytime temperatures in coastal California. Journal of Climate 22:3558-

3573. 

Lischka, S., J. Budenbender, T. Boxhammer and U. Riebesell. Impact of ocean acidification and elevated 

temperatures on early juveniles of the polar shelled pteropod Limacina helicina: mortality, shell 

degradation, and shell growth. Biogeosciences Discussion 7: 8177-8214.

McGowan, J.A., D.R. Cayan, and L.M. Dorman. 1998. Climate‐ocean variability and ecosystem response in the

Northeast Pacific. Science 281:210‐217.

McPhaden, M. J., and D. Zhang. 2004. Pacific Ocean circulation rebounds. Geophys. Res. Lett. 31: L18301,

doi:10.1029/2004GL020727.

Meehl, G.A. and H. Teng. 2007. Multi-model changes in El Niño teleconnections over North America in a future

warmer climate. Clim. Dyn. 29:779–790, DOI 10.1007/s00382-007-0268-3.

Mendelssohn, R. and F.B. Schwing. 2002. Common and uncommon trends in SST and wind stress in California and

Peru-Chile current systems. Progress in Oceanography 53. p.141-162.

Moore, S.S., N.E. Seavy, and M. Gerhart. 2013. Scenario planning for climate change adaptation: A guidance for 

resource managers. Point Blue Conservation Science and California Coastal Conservancy. 

Mote, P.W., A.F. Hamlet, M.P. Clark, D.P. Lettenmaier. 2005. Declining mountain snowpack in western North

America. Bulletin of the American Meteorological Society 86:39-49.

Munday, P.L, D.L. Dixson, J.M. Donelson, G.P. Jones, M.S. Pratchett, G.V. Devitsina, and K.B. Døving. 2009.

Ocean acidification impairs olfactory discrimination and homing ability of a marine fish. Proceedings of

the National Academy of Sciences 106:1848-1852. 

National Oceanic and Atmospheric Administration (NOAA), National Ocean Service (NOS). July 2009.

http://tidesandcurrents.noaa.gov/sltrends/sltrends_station.shtml?stnid=9414290%20San%20Francisco,%20

CA. 

Palacios, D.M., S.J. Bograd, R. Mendelssohn, F.B. Schwing. 2004. Long-term and seasonal trends in stratification in 

the California Current, 1950-1993. Journal of Geophysical Research 109.

Phil William & Associates, Ltd (PWA). 2009. California Coastal Erosion Response to Sea Level Rise – Analysis

and Mapping. Report to the Pacific Institute funded by the California Ocean Protection 

Raven, R. and P.G. Falkowski. 1999. Oceanic sinks for atmospheric CO2. Plant, Cell and Environment 22:741-755. 

Roemmich, D. and J. McGowan. 1995. Climatic warming and the decline of zooplankton in the California Current. 

Science 267: 1324-26.

Sagarin, R.D., J.P. Barry, S.E. Gilman, C.H. Baxter. 1999. Climate-related change in an intertidal community over

short and long time scales. Ecological Monographs 69:465-490.

Sarmiento, J.L., T.M.C. Hughes, R.J. Stouffer, and S. Manabe. 1998. Simulated response of the ocean carbon cycle 

to the anthropogenic climate warming. Nature 393: 245-248.

Schoellhamer, D. H. 2011. Sudden clearing of estuarine waters upon crossing the threshold from transport to supply 

regulation of sediment transport as an erodible sediment pool is depleted: San Francisco Bay, 1999. 

Estuaries and Coasts 34 (5):885-899. 

Snyder, M., Bell, J., Sloan, L., Duffy, P. and B. Govindasamy. 2002. Climate responses to a doubling of 

atmospheric carbon dioxide for a climatically vulnerable region. Geophysical Research Letters 

29(11):10.1029/2001GL014431. 

Snyder, M.A., L.C. Sloan, N.S. Diffenbaugh, and J.L. Bell. 2003. Future climate change and upwelling in the

California Current. Geophysical Research Letters 30:1-4.

Snyder, M. A. and L. C. Sloan. 2005. Transient future climate over the western United States using a regional

climate model. Earth Interactions 9:1-21.

Stein, B.A., P. Glick, N. Edelson, and A. Staudt (eds.). 2014. Climate-Smart Conservation:Putting Adaptation 

Principles into Practice. National Wildlife Federation, Washington, D.C.

Stramma, L., G.C. Johnson, J. Sprintall, and V. Morholz. 2008. Expanding oxygen minimum 

zones in the tropical oceans. Science 320: 655-658.

Sydeman, W.J., M. Garcia-Reyes, D.S. Schoeman, R.R. Rykaczewski, S.A. Thompson, B.A. Black, S.J. Bograd. 

2014. Climate change and wind intensification in coastal upwelling ecosystems. Science 345(6192): 77-80.

Vecchi, G.A. and B.J. Soden. 2007. Global warming and the weakening of the tropical circulation. J. Climate 

20:4316-40.

Wolf, S.G., M.A. Snyder, W.J. Sydeman, D.F. Doaks, D.A. Croll. 2010. Predicting population consequences of 

346
ocean climate change for an ecosystem sentinel, the seabird Cassin’s auklet. Global Change Biology 

16:1923-35.

Zhang, X. D., J. E. Walsh, J. Zhang, U. S. Bhatt, and M. Ikeda, 2004: Climatology and interannual variability of 

Arctic cyclone activity: 1948–2002. J. Clim. 17: 2300–2317.

Report Photo and Figure Credits

Figure Description Credit

Cover photo, 

left

Sea Palm Sara Hutto, GFNMS

Cover photo, 

top

North-central California coastline GFNMS/Beach Watch

Cover Photo, 

bottom right

California Hydrocoral Steve Lonhart, MBNMS

Cover photo, 

bottom center

Black Oystercatcher GFNMS/Beach Watch

Figure 1 Sea Palm Sara Hutto, GFNMS

Figure 2 Rodeo Lagoon Flickr member GGNRA_Laura

Figure 3 Map of study region Tim Reed, GFNMS

Figure 4 Climate-Smart Conservation Cycle Glick et al. 2011

Figure 5 Vulnerability Assessment Methodology Sara Hutto, adapted from Jessi 

Kershner, EcoAdapt 

Figures 6-11 Vulnerability Assessment Results Jessi Kershner, EcoAdapt

347
Appendix A: Focal Resources Workshop agenda and participants

North-central California Coast and Ocean Climate-Smart Adaptation

Workshop 1: Focal Resources 

California Academy of Sciences

February 11, 2014 

9:30 am – 3:00 pm 

Time Subject

9:00 – 9:30 Sign-in and Coffee

• Attendees will select Habitat Assemblage Break-out Group to participate in at 

sign-in

9:30 – 9:40 Welcome

Terry Gosliner, Dean of Science and Research Collections, California Academy of 

Sciences and Maria Brown, Superintendent, Gulf of the Farallones National Marine 

Sanctuary (GFNMS) 

9:40 – 10:00 Project and Workshop Overview

Sara Hutto, GFNMS

10:00 – 10:20 Survey results: analysis, data, and orientation to materials

Sara Hutto, GFNMS

10:20 – 10:30 Break (reconvene in break-out groups)

10:30 – 11:55 Habitat Assemblage Break-out Groups 

• Complete worksheet as a group and develop recommendations for final focal 

resources

12:00 – 12:45

5 min for each 

group, 20 min 

for discussion

Reports from Break-out Groups

• Each group report their recommended habitats, species and ecosystem 

services

• Discuss proposed removals/additions to list

12:45 – 1:45 Lunch

1:45 – 2:15 Finalize focal resources

Sara Hutto, GFNMS

2:15 – 2:50 Planning for Workshop 2:

• Review of the vulnerability assessment process 

• Discuss information needs and available resources for the vulnerability 

assessments

Lara Hansen, EcoAdapt

2:50 – 3:00 Next Steps and Close-out

Sara Hutto, GFNMS

348
Participant Affiliation

Ben Becker Point Reyes National Seashore

Maria Brown Gulf of the Farallones National Marine Sanctuary

Amy Dean Farallones Marine Sanctuary Association

Meredith Elliott Point Blue Conservation Science

Rebecca Fris California Landscape Conservation Cooperative

Holly Gellerman California Department of Fish and Wildlife

Matt Gerhart California State Coastal Conservancy

Joel Gerwein California State Coastal Conservancy

Andrea Graffis California Landscape Conservation Cooperative

Denise Greig The Marine Mammal Center

Lara Hansen EcoAdapt

Eric Hartge Center for Ocean Solutions, Stanford University

Daphne Hatch Golden Gate National Recreation Area

Kelley Higgason Gulf of the Farallones National Marine Sanctuary

Dan Howard Cordell Bank National Marine Sanctuary

Sara Hutto Gulf of the Farallones National Marine Sanctuary

Jaime Jahncke Point Blue Conservation Science

Rebecca Johnson California Academy of Sciences

Suzanne Langridge Natural Capital Project

Dina Liebowitz California Ocean Science Trust

Dani Lipski Cordell Bank National Marine Sanctuary

Steve Lonhart Monterey Bay National Marine Sanctuary

Gerry McChesney US Fish and Wildlife Service

Steven Morgan UC Davis/Bodega Marine Lab

Hilary Papendick California Coastal Commission

Lorraine Parsons Point Reyes National Seashore

Karen Reyna Gulf of the Farallones National Marine Sanctuary

Jan Roletto Gulf of the Farallones National Marine Sanctuary

Claire Simeone The Marine Mammal Center

Jonathon Stillman UC Berkeley

Lisa Wooninck Office of National Marine Sanctuaries, West Coast Region

349
Appendix B: Vulnerability Assessment Workshop agenda and participants

North-central California Coast and Ocean Climate-Smart Adaptation

Workshop 2: Vulnerability Assessment 

Fort Mason 

June 10-11, 2014 

Tuesday, June 10th: 9:30 AM – 4:30 PM 

Introduction to Vulnerability Assessments and Climate Trends for the Region 

9:30 Welcome. Maria Brown, Gulf of the Farallones National Marine Sanctuary

9:35 – 9:40 Introduction to workshop goals and objectives. Sara Hutto, Gulf of the Farallones 

National Marine Sanctuary

9:40 – 9:45 Participant Introductions: name and affiliation

9:45 – 10:05 Presentation: Climate trends in the north-central California coast – historic and 

projected changes. Tom Suchanek, USGS. 

10:05 – 10:25 Presentation: Introduction to vulnerability assessments – foundational elements 

and key steps. Lara Hansen, EcoAdapt

10:25 – 10:35 Presentation: Introduction and orientation to vulnerability assessment worksheets. 

Jessi Kershner, EcoAdapt

10:50 – 12:30 Vulnerability Assessment Breakout Groups: Habitat type

Objectives for breakout groups: 

• Complete worksheets: sensitivity and exposure, adaptive capacity 

• Discuss overall vulnerability 

LUNCH: 12:30 – 1:30 PM 

1:30 – 1:50 Finish habitat vulnerability assessment

1:50 – 2:30 Breakout groups report back to share habitat vulnerability assessment findings 

with all participants and discuss rankings 

2:45 – 4:20 Vulnerability Assessment Breakout Groups: Species

 Objectives for breakout groups: 

• Complete worksheets: sensitivity and exposure, adaptive capacity

• Discuss overall vulnerability 

4:20 – 4:30 Wrap up and next day preview 

350
Wednesday, June 11th: 9:30 AM – 4:30 PM 

9:30 – 9:40 Opening comments and overview of day’s objectives. 

9:40 – 10:30 Finish species vulnerability assessment

10:45 – 11:30 Breakout groups report back to share species vulnerability assessment findings 

with all participants and discuss rankings 

11:30 – 12:30 Vulnerability Assessment Breakout Groups: Ecosystem Services

Objectives for breakout groups: 

• Complete worksheets: sensitivity, and exposure, adaptive capacity 

• Discuss overall vulnerability 

LUNCH: 12:30 – 1:30 PM 

1:30 – 2:15 Vulnerability Assessment Breakout Groups: Ecosystem Services

Objectives for breakout groups: 

• Complete worksheets: sensitivity, and exposure, adaptive capacity

• Discuss overall vulnerability 

2:15 – 3:00 Breakout groups report back to share human and economic vulnerability 

assessment findings with all participants and discuss rankings

3:15 – 4:15 Vulnerability Assessment Large Group Discussion: Management Decisions. 

Lara Hansen, EcoAdapt

4:15 – 4:30 Workshop wrap up and next steps 

Participant Affiliation Break-out groups

Ben Becker Point Reyes National Seashore Offshore

Russ Bradley Point Blue Conservation Science Cliffs

Maria Brown Gulf of the Farallones National 

Marine Sanctuary

Rocky Intertidal, Recreation 

and Tourism

Jennifer Brown Monterey Bay National Marine 

Sanctuary

Rocky Intertidal, Biodiversity

Meredith Elliott Point Blue Conservation Science

Darren Fong Golden Gate National Recreation 

Area

Carbon Storage and 

Sequestration

Holly Gellerman California Department of Fish and 

Wildlife

Cliffs, Recreation and 

Tourism

Doug George Applied Marine Sciences, Inc.

Joel Gerwein California State Coastal 

Conservancy

Beach and Dune, Carbon 

Storage and Sequestration

Andrea Graffis California Landscape Conservation 

Cooperative

351
Lara Hansen EcoAdapt Kelp Forest, Biodiversity

Eric Hartge Center for Ocean Solutions, 

Stanford University

Nearshore and Estuaries, 

Flood and Erosion Protection

Daphne Hatch Golden Gate National Recreation 

Area

Cliffs, Flood and Erosion 

Protection

Kelley Higgason Gulf of the Farallones National 

Marine Sanctuary

Cliffs

Dan Howard Cordell Bank National Marine 

Sanctuary

Offshore, Biodiversity

Sara Hutto Gulf of the Farallones National 

Marine Sanctuary

Rocky Intertidal

Jaime Jahncke Point Blue Conservation Science Offshore

Joanne Kerbavaz California State Parks Beach and Dune, Recreation 

and Tourism

Jessi Kershner EcoAdapt Carbon Storage and 

Sequestration

Kristy Kroeker UC Davis/Bodega Marine Lab Kelp Forest, Carbon Storage 

and Sequestration

Suzanne 

Langridge

UC Santa Cruz Nearshore and Estuaries

Dina Liebowitz California Ocean Science Trust Kelp Forest

Dani Lipski Cordell Bank National Marine 

Sanctuary

Offshore

Mary Matella California Coastal Commission Beach and Dune, Flood and 

Erosion Protection

Steven Morgan UC Davis/Bodega Marine Lab Rocky Intertidal

Tenaya Norris The Marine Mammal Center Nearshore and Estuaries

Paul Reilly California Department of Fish and 

Wildlife

Nearshore and Estuaries

Karen Reyna Gulf of the Farallones National 

Marine Sanctuary

Offshore

Jake Reynolds Gulf of the Farallones National 

Marine Sanctuary

Deb Schlafmann California Landscape Conservation 

Cooperative

Nearshore and Estuaries, 

Recreation and Tourism

Jonathon Stillman UC Berkeley Kelp Forest, Carbon Storage 

and Sequestration

Tom Suchanek US Geological Survey

Sam Veloz Point Blue Conservation Science Beach and Dune

Deb WilsonVandenburgCalifornia Department of Fish and 

Wildlife

Kelp Forest, Biodiversity

352
Appendix C: Contributors and Reviewers to assessment reports6

Focal Resource Contributor(s) Reviewer(s)

American Dune Grass Beaches and Dunes break-out 

group

Peter Baye (Ph.D., Botanist, 

unaffiliated)

Black Oystercatcher Kirsten Lindquist (Farallones 

Marine Sanctuary Association)

Kirsten Lindquist (Farallones 

Marine Sanctuary Association)

Black Rail Julian Wood (Point Blue

Conservation Science)

Laurie Hall (UC Davis)

Blue Rockfish Kelp forest break-out group Steve Lonhart (Monterey Bay 

National Marine Sanctuary)

Blue Whale Jaime Jahncke Meredith Elliot, Sarah Allen

(National Park Service)

California Mussel Rocky Intertidal break-out group Amy Dean (Farallones Marine 

Sanctuary Association)

Cassin’s Auklet Jaime Jahncke, Meredith Elliot, 

Russ Bradley, Bill Sydeman

(Farallon Institute)

Meredith Elliot

Cavity Nesters Cliffs break-out group Russ Bradley

Copepod Offshore break-out group Meredith Elliot

Coralline Algae Kelp forest break-out group Steve Lonhart (Monterey Bay 

National Marine Sanctuary)

Dune Grass Darren Fong and Camm Swift (

Professor Emeritus)

Peter Baye (Ph.D., Botanist, 

unaffiliated)

Gaper Clam Christy Juhasz (CDFW) Christy Juhasz (CDFW), Kirsten 

Ramey (CDFW), Peter Kalvass 

(CDFW)

CA Hydrocoral and 

Red sponge

Offshore break-out group Dani Lipski

Krill Offshore break-out group Meredith Elliot

Mole Crab Beaches and Dunes break-out 

group; Amy Dean (FMSA)

Dan Robinette (Point Blue 

Conservation Science)

Northern 

Anchovy/Pacific 

Sardine

Chelsea Protasio (CDFW)and 

Kirk Lynn (CDFW) 

Briana Brady (CDFW), Sarah 

Allen (NPS)

Ochre Sea Star Rocky Intertidal break-out group Amy Dean (Farallones Marine 

Sanctuary Association)

Olympia Oyster Ted Grosholz (UC Davis) Ted Grosholz (UC Davis)

Pacific Herring Nearshore break-out group Sarah Allen (NPS), Kirsten 

Ramey (CDFW), Ryan Bartling 

(CDFW)

Pteropod Jaime Jahncke, Meredith Elliot, 

Russ Bradley

Meredith Elliot

6 See participant list in Appendix B if affiliation is not listed

353
Red Abalone Kelp forest break-out group Steve Lonhart (Monterey Bay 

National Marine Sanctuary)

Sea Otter Nearshore break-out group Sarah Allen (NPS), Steve Lonhart

(Monterey Bay National Marine 

Sanctuary)

Sea Palm Rocky Intertidal break-out group Amy Dean (Farallones Marine 

Sanctuary Association)

Sea Urchins Kelp forest break-out group Steve Lonhart (Monterey Bay 

National Marine Sanctuary)

Snowy Plover Beaches and Dunes break-out 

group 

Dan Robinette (Point Blue 

Conservation Science), Peter 

Baye (Ph.D., Botanist, 

unaffiliated)

Surface Nesters Cliffs break-out group Russ Bradley

Tidewater Goby Darren Fong Ted Grosholz (UC Davis)

Widow Rockfish Offshore break-out group Dani Lipski

Kelp Forest Kelp forest break-out group Steve Lonhart (Monterey Bay 

National Marine Sanctuary)

Beaches and Dunes Beaches and dunes break-out 

group

Dan Robinette (Point Blue 

Conservation Science)

Benthic Shallow Banks Offshore break-out group Dani Lipski

Cliffs Cliffs break-out group Russ Bradley

Estuaries Nearshore break-out group Ted Grosholz (UC Davis)

Nearshore Nearshore break-out group Sarah Allen (NPS)

Pelagic Offshore break-out group Meredith Elliot

Rocky Intertidal Rocky Intertidal break-out group Amy Dean (Farallones Marine 

Sanctuary Association)

Flood and Erosion 

Protection

Flood and erosion protection 

break-out group

Daphne Hatch

Carbon Storage and 

Sequestration

Carbon storage and sequestration 

break-out group

Jessi Kershner

Food Production Food production break-out group Jessi Kershner

Water Purification Water purification break-out 

group

Jessi Kershner

Recreation and Tourism Recreation and tourism break-out 

group

Daphne Hatch

354
Appendix D: Vulnerability Assessment Scores

The following score tables provide vulnerability component scores and individual element scores 

assigned by workshop participants and assessment contributors for all 44 habitats, species, and 

ecosystem services considered as part of the Climate-Smart Adaptation Project for the Northcentral California Coast and Ocean. Score tables are listed in alphabetical order within resource 

categories, with habitat scores presented first, followed by species scores, and ecosystem 

services scores.

355
Beaches and Dunes – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 4 Moderate-High Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Factors

• Precipitation

• pH 

• Sea level rise

• Wave action

• Coastal erosion

• Sediment supply and movement 

• Wind

Overall: 4 Moderate-High

• 2 Low-Moderate 

• 1 Low

• 5 High 

• 5 High 

• 5 High 

• 5 High 

• 3 Moderate

Overall: 3 High

• 2 Moderate 

• 1 Low

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High

Disturbance Regimes

• Wind 

• Storms

Overall: 5 High Overall: 3 High

Non-Climate Stressors – Degree Stressor Affects

Sensitivity

• Roads/armoring 

• Recreation

• Invasive species

• Overwater/underwater structures

• Dredging

Overall: 4 Moderate-High

• 5 High 

• 3 Moderate 

• 3 Moderate 

• 4 Moderate-High

• 3 Moderate

Overall: 3 High

• 3 High

• 3 High

• 2 Moderate 

• 3 High

• 2 Moderate

Non-Climate Stressors – Current Exposure to Stressor

• Roads/armoring 

• Recreation

• Invasive species

• Overwater/underwater structures

• Dredging

Overall: 3 Moderate Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 2 Moderate 

• 2 Moderate

LOCAL

• 5 High 

• 5 High 

• 5 High 

• 5 High 

• 4 ModerateREGIONAL

• 2 Low-Moderate 

• 2 Low-Moderate 

• 2 Low-Moderate 

• 2 Low-Moderate 

• 2 Low-Moderate

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

356
Sensitivity Factor Sensitivity Evaluation Confidence

High

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 4 Moderate-High

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 High (Transcontinental) 3 High

Structural & Functional Integrity 3 Moderate (Altered but not degraded) 2 Moderate

Habitat Continuity 3 Moderate (Patchy across an area with some 

connectivity among patches)

2 Moderate

Habitat Resistance 2 Low-Moderate 2 Moderate

Habitat Recovery 3 Moderate 2 Moderate

Habitat Diversity – Physical/Topographical 2 Low-Moderate 2 Moderate

Habitat Diversity – Component Species 3 Moderate 2 Moderate

Habitat Diversity – Functional Groups 2 Low-Moderate 2 Moderate

Habitat Value 5 High 3 High

Likelihood of Managing or Alleviating Climate Impacts 3 Moderate 3 High

Other Adaptive Capacities

• Sediment Supply

Overall: 5 High Overall: 3 High

Overall Averaged Ranking (Adaptive Capacity)3: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 3 High

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Sea level rise

• Increased storminess

Overall: 5 High

• 5 High 

• 5 High

Overall: 3 High

• 3 High 

• 3 High

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above.

4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

357
Exposure Factor Exposure Evaluation Confidence

• Increased coastal erosion runoff

• Increased flooding 

• 5 High

• 3 Moderate 

• 3 High

• 1 Low

Overall Averaged Ranking (Exposure)3: 5 High

Overall Averaged Confidence (Exposure)4: 3 High

358
Cliffs – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Factors

• Air temperature

• Precipitation

• Salinity

• Sea level rise

• Wave action

• Coastal erosion

• Extreme weather events

Overall: 3 Moderate

• 2 Low-Moderate 

• 3 Moderate 

• 2 Low-Moderate 

• 3 Moderate 

• 4 Moderate-High

• 4 Moderate-High

• 5 High

Overall: 3 High

• 2 Moderate 

• 2 Moderate 

• 1 Low

• 3 High 

• 3 High 

• 3 High 

• 3 High

Disturbance Regimes

• Wind 

• Storms (wave height)

• Flooding 

• Drought

Overall: 4 Moderate-High Overall: 3 High

Non-Climate Stressors – Degree Stressor Affects

Sensitivity

• Land use change 

• Recreation

• Roads/Armoring 

• Invasive Species

• Urban Runoff 

• Overwater/underwater Structures

Overall: 3 Moderate

• 4 Moderate-High

• 2 Low-Moderate 

• 4 Moderate-High

• 2 Low-Moderate 

• 3 Moderate 

• 2 Low-Moderate

Overall: 3 High

• 3 High

• 3 High 

• 3 High 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate

Non-Climate Stressors – Current Exposure 

• Land use change 

Overall: 1 Low Overall: 1 Low

• 2 Moderate 

LOCAL

• 5 High (Urban); 2 

Low-Moderate 

REGIONAL

• 2 LowModerate

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

359
Sensitivity Factor Sensitivity Evaluation Confidence

• Recreation

• Roads/armoring 

• Invasive species

• Urban runoff 

• Overwater/underwater structures

(Rural)

• 3 Moderate (Urban); 

1 Low (Rural)

• 2 Moderate-Low 

(Urban); 1 Low 

(Rural)

• 1 Low

• 3 Moderate (Urban); 

1 Low (Rural)

• 2 Low-Moderate 

(Urban); 1 Low 

(Rural)

• 1 Low

• 1 Low

• 1 Low

• 1 Low

• 1 Low

• 3 High

• 3 High

• 3 High

• 2 Moderate 

• 2 Moderate 

Other Sensitivities

• Tsunami

• Earthquakes

Overall: 4 Moderate-High Overall: 2 Moderate

Overall Averaged Ranking (Sensitivity)3: 3 Moderate-High

Overall Averaged Confidence (Sensitivity)4: 2 Moderate

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 High (Transcontinental) 3 High

Structural & Functional Integrity 4 Moderate-High (Minor to moderate alterations) 3 High

Habitat Continuity 3 Moderate (Patchy across an area with some 

connectivity among patches)

3 High

Habitat Resistance 4 Moderate-High 2 Moderate

Habitat Recovery 2 Low-Moderate 2 Moderate

Habitat Diversity – Physical/Topographical 2 Low-Moderate 3 High

Habitat Diversity – Component Species 1 Low 3 High

Habitat Diversity – Functional Groups 1 Low 3 High

Habitat Value 4 Moderate-High 2 Moderate

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above.

4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

360
Likelihood of Managing or Alleviating Climate 

Impacts

2 Low-Moderate 2 Moderate

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 3 Moderate-High

Overall Averaged Confidence (Adaptive Capacity)4: 3 High

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Air temperature

• Change in precipitation

• Change in salinity

• Increased erosion runoff 

• Increased flooding 

• Increased sea level rise

• Increased storminess 

Overall: 2 Low-Moderate

• 1 Low

• 2 Low-Moderate 

• 1 Low

• 4 Moderate-High

• 2 Low-Moderate 

• 2 Low-Moderate 

• 4 Moderate-High

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

• 3 High 

• 3 High 

• 1 Low

• 2 Moderate 

• 3 High 

Overall Averaged Ranking (Exposure)3: 2 Low-Moderate

Overall Averaged Confidence (Exposure)4: 2 Moderate

361
Estuaries – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 4 Moderate-High Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Factors

• Air temperature

• Sea surface temperature

• Precipitation

• Salinity

• Oxygen 

• pH 

• Sea level rise

• Wave action

• Currents/mixing/stratification

• Coastal erosion

• Turbidity

Overall: 3 Moderate

• 3 Moderate 

• 4 Moderate-High

• 4 Moderate-High

• 2 Low Moderate

• 3 Moderate 

• 3 Moderate 

• 5 High

• 4 Moderate-High

• 2 Low Moderate

• 3 Moderate 

• 2 Low-Moderate

Overall: 3 High

• 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High

• 2 Moderate 

• 2 Moderate

Disturbance Regimes

• Storms

• Disease

• Flooding

Overall: 4 Moderate-High

• 4 Moderate-High

• 3 Moderate 

• 5 High

Overall: 3 High

• 3 High 

• 2 Moderate 

• 3 High

Non-Climate Stressors – Degree Stressor Affects

Sensitivity

• Land use change 

• Overwater/underwater structures

• Roads/armoring 

• Invasive & other problematic species

Overall: 5 High

• 5 High

• 4 Moderate-High

• 4 Moderate-High

• 4 Moderate-High

Overall: 3 High

• 3 High

• 3 High

• 3 High

• 3 High

Non-Climate Stressors – Current Exposure to Stressor Overall: 4 Moderate-High Overall: 3 High

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

362
Sensitivity Factor Sensitivity Evaluation Confidence

• Land use change 

• Overwater/underwater structures

• Roads/armoring 

• Invasive & other problematic species

LOCAL

• 4 Moderate-High

• 4 Moderate-High

• 4 Moderate-High

• 4 Moderate-High

REGIONAL

• 4 ModerateHigh

• 4 ModerateHigh

• Not Answered

• 4 ModerateHigh

• 3 High 

• 3 High 

• 3 High 

• 3 High 

Other Sensitivities

• Potential for restoration and resilience

• Public attention and awareness of issue

Overall: 5 High Overall: 3 High 

Overall Averaged Ranking (Sensitivity)3: 4 Moderate-High

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 High (Transcontinental) 3 High 

Structural & Functional Integrity 2 Low-Moderate (Somewhat degraded) 3 High 

Habitat Continuity 2 Low-Moderate (Somewhat isolated and/or 

fragmented, i.e. patchy)

3 High 

Habitat Resistance 1 Low 3 High 

Habitat Recovery 4 Moderate-High 3 High 

Habitat Diversity – Physical/Topographical 5 High 3 High 

Habitat Diversity – Component Species 5 High 3 High 

Habitat Diversity – Functional Groups 4 Moderate-High 2 Moderate 

Habitat Value 4 Moderate-High 3 High 

Likelihood of Managing or Alleviating Climate Impacts 3 Moderate 1 Low 

Other Adaptive Capacities

• Room to migrate

Overall: 5 High Overall: 3 High

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above.

4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

363
Overall Averaged Ranking (Adaptive Capacity)3

: 4 Moderate-High

Overall Averaged Confidence (Adaptive Capacity)4: 3 High

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Increased air temperature

• Changes in precipitation

• Increased sea surface temperature

• Increased coastal erosion/runoff

• Decreased pH

• Increased flooding 

• Decreased oxygen

• Sea level rise

• Increased storminess

Overall: 5 High

• 4 Moderate-High

• 5 High 

• 5 High 

• 5 High 

• 3 Moderate 

• 5 High 

• 3 Moderate 

• 4 Moderate-High

• 5 High

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 2 Moderate 

• 3 High 

• 2 Moderate 

• 2 Moderate 

• 3 High 

Overall Averaged Ranking (Exposure)3: 5 High

Overall Averaged Confidence (Exposure)4: 3 High 

364
Kelp Forests – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 2 Low-Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Factors

• Air temperature

• Sea surface temperature

• Precipitation

• Salinity

• Oxygen 

• pH 

• Sea level rise

• Wave action

• Currents/mixing/stratification

• Coastal erosion

• Turbidity

Overall: 3 Moderate

• 1 Low

• 4 Moderate-High

• 2 Low-Moderate 

• 5 High 

• 5 High 

• 3 Moderate 

• 2 Low-Moderate 

• 5 High 

• 2 Low-Moderate (local)

4 Moderate-High (large scale)

• 1 Low (chronic) 

2 Low-Moderate (acute)

• Not Answered

Overall: 3 High

• 3 High 

• 3 High 

• 2 Moderate 

• 3 High 

• 3 High 

• 2 Moderate 

• 1 Low

• 3 High

• 2 Moderate 

• 2 Moderate 

• Not Answered

Disturbance Regimes

• Disease

• Storms

Overall: 4 Moderate-High

• 2 Low-Moderate 

• 5 High

Overall: 2 Moderate

• 1 Low

• 3 High

Non-Climate Stressors – Degree Stressor Affects

Sensitivity

• Harvest algae/kelp

• Harvest grazers

• Harvest mid-trophic level organisms

• Pollution

• Oil spills

Overall: 3 Moderate

• 1 Low

• 2 Low-Moderate 

• 1 Low

• 5 High 

• 3 Moderate

Overall: 2 Moderate

• 3 High 

• 2 Moderate 

• 3 High 

• 3 High 

• 1 Low

Non-Climate Stressors – Current Exposure to Stressor Overall: 2 Low-Moderate Overall: 2 Moderate

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

365
Sensitivity Factor Sensitivity Evaluation Confidence

• Harvest algae/lelp

• Harvest grazers

• Harvest mid-trophic level organisms

• Pollution

• Oil spills

LOCAL

• 1 Low

• 3 Moderate 

• 3 Moderate 

• 4 ModerateHigh

• 1 Low

REGIONAL

• 1 Low

• 2 Low-Moderate 

• 3 Moderate 

• 1 Low

• 1 Low

• 3 Moderate 

• 2 Moderate 

• 3 Moderate 

• 2 Moderate 

• 1 Low

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 3 Moderate

Overall Averaged Confidence (Sensitivity)4: 2 Moderate

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 High (Transcontinental) 3 High

Structural & Functional Integrity 4 Moderate-High (Minor to moderate 

alterations)

3 High

Habitat Continuity 2 Low-Moderate (Somewhat isolated and/or 

fragmented, i.e. patchy)

3 High

Habitat Resistance 3 Moderate 2 Moderate

Habitat Recovery 4 Moderate-High 2 Moderate

Habitat Diversity – Physical/Topographical 5 High 3 High

Habitat Diversity – Component Species 5 High 3 High

Habitat Diversity – Functional Groups 5 High 3 High

Habitat Value 5 High 3 High

Likelihood of Managing or Alleviating Climate Impacts 2 Low-Moderate 2 Moderate

Other Adaptive Capacities

• Nutrients 

Overall: 3 Moderate Overall: 1 Low

Overall Averaged Ranking (Adaptive Capacity)3: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 3 High

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above.

4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

366
EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Sea surface temperature (chronic) 

• El Niño (increased sea surface temperature) 

• Decreased dissolved oxygen

• Increased storminess 

• Decreased pH

• Salinity

• Precipitation

• Flooding 

• Sea level rise

• Coastal erosion 

• Currents/mixing 

Overall: 2 Low-Moderate

• 1 Low

• 2 Low-Moderate 

• 2 Low-Moderate 

• 5 High 

• 5 High 

• 1 Low

• 1 Low

• 1 Low

• 5 High 

• 1 Low

• 4 Moderate-High

Overall: 3 High

• 2 Moderate 

• 1 Low

• 1 Low

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 2 Moderate 

Overall Averaged Ranking (Exposure)3: 2 Low-Moderate

Overall Averaged Confidence (Exposure)4: 3 High

367
Nearshore soft-bottom – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Factors

• Sea surface temperature

• Precipitation

• Salinity

• Oxygen 

• pH 

• Wave action

• Currents/mixing/stratification

• Coastal erosion

• Turbidity

Overall: 3 Moderate

• 3 Moderate 

• 2 Low-Moderate 

• 2 Low-Moderate 

• 2 Low-Moderate 

• 4 Moderate-High

• 4 Moderate-High

• 3 Moderate 

• 5 High 

• 4 Moderate-High

Overall: 2 Moderate

• 2 Moderate 

• 1 Low

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 3 High 

• 1 Low

• 3 High 

• 2 Moderate

Disturbance Regimes

• Wind 

• Disease

• Storms

Overall: 3 Moderate

• 3 Moderate 

• 3 Moderate 

• 4 Moderate-High

Overall: 3 High

• 2 Moderate 

• 2 Moderate 

• 3 High

Non-Climate Stressors – Degree Stressor Affects

Sensitivity

• Pollution and poisons 

• Energy production 

• Transportation 

• Land use change

Overall: 3 Moderate

• 4 Moderate-High

• 1 Low

• 2 Low-Moderate 

• 4 Moderate-High

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High

Non-Climate Stressors – Current Exposure to Stressor

• Pollution and poisons 

• Energy production 

• Transportation

Overall: 2 Low-Moderate Overall: 3 High

• 2 Moderate 

• 3 High 

• 3 High

LOCAL

• 4 Moderate-High

• 2 Low-Moderate 

• 2 Low-Moderate

REGIONAL

• 2 Low-Moderate 

• 1 Low

• 1 Low

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

368
Sensitivity Factor Sensitivity Evaluation Confidence

• Land use change • 2 Low-Moderate • 1 Low • 2 Moderate

Other Sensitivities

• Sea temperature at depth and mid-column

Overall: 3 Moderate Overall: 2 Moderate

Overall Averaged Ranking (Sensitivity)3: 3 Moderate

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 High(Transcontinental) 3 High

Structural & Functional Integrity 4 Moderate-High (Minor to moderate 

alterations)

3 High

Habitat Continuity 5 High (Continuous) 3 High

Habitat Resistance 4 Moderate-High 3 High

Habitat Recovery Not Answered 3 High

Habitat Diversity – Physical/Topographical 2 Low-Moderate 3 High

Habitat Diversity – Component Species 3 Moderate 3 High

Habitat Diversity – Functional Groups 3 Moderate 2 Moderate

Habitat Value 2 Low-Moderate 3 High

Likelihood of Managing or Alleviating Climate Impacts 2 Low-Moderate 3 High

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 3 High

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

369
EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Altered currents/mixing

• Increased sea surface temperature gradient 

• Increased coastal erosion and runoff

• Decreased pH

• Increased storminess

Overall: 4 Moderate-High

• 2 Low-Moderate 

• 4 Moderate-High

• 5 High 

• 5 High 

• 4 Moderate-High

Overall: 3 High

• 2 Moderate 

• 2 Moderate 

• 3 High 

• 3 High 

• 3 High 

Overall Averaged Ranking (Exposure)3: 4 Moderate-High

Overall Averaged Confidence (Exposure)4: 3 High

370
Offshore Rocky Reefs – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 2 Low-Moderate Overall Confidence2: 2 Moderate

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Factors

• Sea surface temperature

• Oxygen 

• pH 

• Currents/mixing/stratification

Overall: 3 Moderate

• 1 Low

• 5 High 

• 3 Moderate 

• 3 Moderate

Overall: 2 Moderate

• 1 Low

• 3 High 

• 1 Low

• 2 Moderate

Disturbance Regimes: none identified N/A N/A

Non-Climate Stressors – Degree Stressor Affects

Sensitivity

• Pollution

• Harvest (gear)

• Invasive species

Overall: 1 Low

• 1 Low

• 1 Low

• 3 Moderate

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

• 2 Moderate

Non-Climate Stressors – Current Exposure to Stressor

• Pollution

• Harvest (gear)

• Invasive species

Overall: 1 Low Overall: 2 Moderate

• 3 High 

• 1 Low

• 2 Moderate

LOCAL

• 1 Low

• 1 Low

• 1 Low

REGIONAL

• 1 Low

• 2 Low-Moderate 

• 2 Low-Moderate

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 2 Low-Moderate

Overall Averaged Confidence (Sensitivity)4: 2 Moderate

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity. 3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

371
ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 3 Moderate (Distribution within single state to 

two states)

3 High

Structural & Functional Integrity 3 Moderate (Altered but not degraded) 3 High

Habitat Continuity 1 Low (Isolated and/or fragmented) 3 High

Habitat Resistance Not Answered Not Answered

Habitat Recovery 2 Low-Moderate 3 High

Habitat Diversity – Physical/Topographical 2 Low-Moderate 3 High

Habitat Diversity – Component Species 4 Moderate-High 3 High

Habitat Diversity – Functional Groups 4 Moderate-High 3 High

Habitat Value 4 Moderate-High 2 Moderate

Likelihood of Managing or Alleviating Climate Impacts 1 Low 3 High

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 3 High

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Sea surface temperature

• Oxygen 

• Decreased pH

• Currents/mixing/stratification

Overall: 2 Low-Moderate

• 1 Low

• 2 Low-Moderate 

• 4 Moderate-High

• 2 Low-Moderate 

Overall: 2 Moderate

• 1 Low

• 1 Low

• 3 High 

• 2 Moderate 

Overall Averaged Ranking (Exposure)3: 2 Low-Moderate

Overall Averaged Confidence (Exposure)4: 2 Moderate

372
Pelagic Water Column – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Factors

• Air temperature

• Sea surface temperature

• Precipitation

• Salinity

• Oxygen 

• pH 

• Currents/mixing/stratification

• Turbidity

• Upwelling

Overall: 3 Moderate

• 2 Low-Moderate 

• 3 Moderate 

• 3 Moderate 

• 1 Low

• 4 Moderate-High

• 4 Moderate-High

• 5 High 

• Not Answered

• 5 High

Overall: 3 High

• 2 Moderate 

• 3 High 

• 3 High 

• 2 Moderate 

• 3 High 

• 2 Moderate 

• 3 High 

• Not Answered

• 3 High

Disturbance Regimes

• Wind 

• Storms

Overall: 5 High Overall: 3 High

Non-Climate Stressors – Degree Stressor Affects

Sensitivity

• Harvest

• Pollution

Overall: 1 Low

• 1 Low

• 1 Low

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate

Non-Climate Stressors – Current Exposure to Stressor

• Harvest

• Pollution

Overall: 1 Low Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

LOCAL

• 1 Low

• 1 Low

REGIONAL

• 2 Low-Moderate 

• 1 Low

Other Sensitivities

• Noise

Overall: 3 Moderate Overall: 1 Low

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

373
Overall Averaged Ranking (Sensitivity)3

: 3 Moderate

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 High (Transcontinental) 3 High

Structural & Functional Integrity 4 Moderate-High (Minor to moderate 

alterations)

3 High

Habitat Continuity 5 High (Continuous) 3 High

Habitat Resistance Not Answered Not Answered

Habitat Recovery 4 Moderate-High 3 High

Habitat Diversity – Physical/Topographical 1 Low 3 High

Habitat Diversity – Component Species 4 Moderate-High 3 High

Habitat Diversity – Functional Groups 4 Moderate-High 3 High

Habitat Value 5 High 3 High

Likelihood of Managing or Alleviating Climate Impacts 1 Low 3 High

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 4 Moderate-High

Overall Averaged Confidence (Adaptive Capacity)4: 3 High

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Air temperature

• Sea temperature

• Precipitation

• Salinity

• Oxygen 

• pH 

• Currents/mixing/stratification

Overall: 4 Moderate-High

• 5 High 

• 5 High 

• 2 Low-Moderate 

• 1 Low

• 5 High 

• 5 High 

• 5 High

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above.

4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

374
Exposure Factor Exposure Evaluation Confidence

• Upwelling • 5 High • 3 High

Overall Averaged Ranking (Exposure)3: 4 Moderate-High

Overall Averaged Confidence (Exposure)4: 3 High

375
Rocky Intertidal – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 2 Moderate

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Factors

• Air temperature

• Sea surface temperature

• Precipitation

• Salinity

• Oxygen 

• pH 

• Sea level rise

• Wave action

• Currents/mixing/stratification

• Coastal erosion

Overall: 4 Moderate-High

• 5 High

• 3 Moderate 

• 2 Low-Moderate 

• 5 High

• 2 Low-Moderate 

• 4 Moderate-High

• 3 Moderate 

• 5 High

• 3 Moderate 

• 4 Moderate-High

Overall: 2 Moderate

• 3 High

• 1 Low

• 1 Low

• 2 Moderate 

• 1 Low

• 1 Low

• 2 Moderate 

• 3 High

• 1 Low

• 1 Low

Disturbance Regimes

• Wind 

• Disease

• Storms

• Flooding 

• Extreme heat events

Overall: 5 High Overall: 2 Moderate

Non-Climate Stressors – Degree Stressor Affects

Sensitivity

• Land use change 

• Armoring 

• Pollution/oil spills

• Harvest

• Recreation/trampling 

• Invasives/species range expansions

Overall: 4 Moderate-High

• 3 Moderate 

• 4 Moderate-High

• 4 Moderate-High

• 3 Moderate 

• 4 Moderate-High

• 4 Moderate-High

Overall: 1 Low

• 1 Low

• 2 Moderate 

• 1 Low

• 1 Low

• 1 Low

• 2 Low

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

376
Sensitivity Factor Sensitivity Evaluation Confidence

• Boat groundings • 3 Moderate • 1 Low

Non-Climate Stressors – Current Exposure to Stressor

• Land use change 

• Armoring 

• Pollution/oil spills

• Harvest

• Recreation/trampling 

• Invasives/species range expansions

• Boat groundings

Overall: 4 Moderate-High Overall: 2 Moderate

• 1 Low

• 3 High 

• 1 Low

• 1 Low

• 2 Moderate 

• 1 Low

• 3 High

LOCAL

• 2 Low-Moderate 

• 5 High

• 4 Moderate-High

• 2 Low-Moderate 

• 4 Moderate-High

• 4 Moderate-High

• 5 High

REGIONAL

• 1 Low

• 1 Low

• 1 Low

• 1 Low

• 1 Low

• 1 Low

• 1 Low

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 4 Moderate-High

Overall Averaged Confidence (Sensitivity)4: 2 Moderate 

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 High (Transcontinental) 3 High

Structural & Functional Integrity 5 High (Pristine) 3 High

Habitat Continuity 3 Moderate (Patchy across an area with some 

connectivity among patches)

3 High

Habitat Resistance 2 Low-Moderate 2 Moderate

Habitat Recovery 5 High 3 High

Habitat Diversity – Physical/Topographical 4 Moderate-High 3 High

Habitat Diversity – Component Species 5 High 3 High

Habitat Diversity – Functional Groups 5 High 3 High

Habitat Value 4 Moderate-High 1 Low

Likelihood of Managing or Alleviating Climate Impacts 2 Low-Moderate 3 High

Other Adaptive Capacities: none identified N/A N/A

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above.

4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

377
Overall Averaged Ranking (Adaptive Capacity)3

: 4 Moderate-High

Overall Averaged Confidence (Adaptive Capacity)4: 3 High

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Increased air temperature

• Change in precipitation 

• Change in salinity

• Altered currents

• Increased water temperature

• Increased erosion

• Decreased pH

• Increased flooding/runoff 

• Sea level rise

• Increased storms

• Decreased oxygen

Overall: 4 Moderate-High

• 5 High

• 5 High

• 5 High

• 4 Moderate-High

• 5 High

• 3 Moderate 

• 5 High

• 3 Moderate 

• 5 High

• 3 Moderate 

• 2 Low-Moderate 

Overall: 2 Moderate

• 3 High

• 3 High

• 2 Moderate 

• 1 Low

• 2 Moderate 

• 2 Moderate 

• 3 High

• 2 Moderate 

• 3 High

• 2 Moderate 

• 1 Low

Overall Averaged Ranking (Exposure)3: 4 Moderate-High

Overall Averaged Confidence (Exposure)4: 2 Moderate 

378
American Dune Grass – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 4 Moderate-High Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Air temperature

• Precipitation

• Sea Level Rise

• Wave action

• Coastal erosion

• Other: Sediment Supply

Overall: 3 Moderate

• 1 Low

• 2 Low-Moderate 

• 4 Moderate-High

• 4 Moderate-High

• 4 Moderate-High

• 4 Moderate-High

Overall: 3 High

• 1 Low

• 2 Moderate 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

Disturbance Regimes

• Storms

Overall: 3 Moderate Overall: 2 Moderate

Dependencies

• Dependence on sensitive habitat types

o Dunes 

• Dependence on specific prey or forage species

• Other dependencies

o Sediment supply to keep up with SLR

• Generalist or specialist?

Overall: 4 Moderate-High

• 5 High 

• 1 Low

• 5 High 

• 5 (Specialist)

Overall: 3 High

• 3 High 

• 3 High 

• 2 Moderate 

• 3 High 

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Roads/armoring 

• Recreation

• Invasives

Overall: 4 Moderate-High

• 4 Moderate-High

• 3 Moderate 

• 5 High

Overall: 3 High

• 3 High 

• 2 Moderate 

• 3 High

Non-Climate Stressors – Current Exposure to Stressor Overall: 4 Moderate-High Overall: 3 High

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

379
Sensitivity Factor Sensitivity Evaluation Confidence

• Roads/armoring 

• Recreation

• Invasives

LOCAL

• 5 High 

• 5 High 

• 5 High 

REGIONAL

• 3 Moderate 

• 2 LowModerate

• 4 ModerateHigh

• 3 High 

• 3 High 

• 3 High 

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 4 Moderate-High

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 3 (Diminished but generally stable) 2 Moderate

Population Connectivity 1 (Isolated and/or fragmented) 3 High

Dispersal Ability 2 Low-Moderate 2 Moderate

Maximum Annual Dispersal Distance <1 km 1 Low

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 2 Low-Moderate

• 2 Low-Moderate 

• Not Answered

• N/A

• 3 Moderate

Overall: 1 Low

• 2 Moderate 

• Not Answered

• N/A

• 1 Low

Species Value 1 Low 3 High

Likelihood of Managing or Alleviating Climate Impacts 3 Moderate 2 Moderate

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 2 Low-Moderate

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

380
Overall Averaged Confidence (Adaptive Capacity)4

: 2 Moderate

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Increased coastal erosion and runoff 

• Increased storminess

• Sea level rise

• Sediment supply and movement

Overall: 5 High

• 5 High 

• 5 High 

• 5 High 

• 5 High

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High

Overall Averaged Ranking (Exposure)3: 5 High

Overall Averaged Confidence (Exposure)4: 3 High

381
Black Oyster Catcher – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 4 Moderate-High Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Air temperature

• Precipitation

• Sea level rise

• Wave action

• Coastal erosion

Overall: 4 Moderate-High

• 1 Low

• 4 Moderate-High

• 5 High 

• 5 High 

• 4 Moderate-High

Overall: 3 High

• 2 Moderate 

• 3 High 

• 3 High 

• 3 High 

• 2 Moderate 

Disturbance Regimes

• Wind 

• Storms

• Flooding

Overall: 5 High Overall: 3 High

Dependencies

• Dependence on sensitive habitat types

o Rocky intertidal 

• Dependence on specific prey or forage species

• Other dependencies: none identified

• Generalist or specialist?

Overall: 5 High

• 5 High 

• 4 Moderate-High 

• N/A

• 5 (Specialist)

Overall: High

• 3 High 

• 2 Moderate 

• N/A

• 3 High

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Land use change 

• Pollution and poisons 

• Recreation

Overall: 5 High

• 5 High 

• 4 Moderate-High

• 5 High

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

• 2 Moderate

Non-Climate Stressors – Current Exposure to Stressor

• Not Answered

Not Answered Not Answered

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

382
Sensitivity Factor Sensitivity Evaluation Confidence

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 5 High

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 3 (Diminished but generally stable) 2 Moderate

Population Connectivity 2 (Somewhat isolated and/or fragmented) 2 Moderate

Dispersal Ability Unknown 1 Low

Maximum Annual Dispersal Distance Not Answered Not Answered

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 1 Low

• 1 Low

• Not Answered

• 1 Low

• Not Answered

Overall: 3 High

• 3 High 

• Not Answered

• 2 Moderate 

• Not Answered

Species Value 5 High 2 Moderate

Likelihood of Managing or Alleviating Climate Impacts 3 Moderate 2 Moderate

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 2 Moderate

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

383
EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in precipitation 

• Increased coastal erosion and runoff 

• Increased flooding 

• Sea level rise

• Increased storminess

Overall: 5 High

• 4 Moderate-High

• 4 Moderate-High

• 5 High 

• 5 High 

• 5 High 

Overall: 3 High

• 2 Moderate 

• 2 Moderate 

• 3 High 

• 3 High 

• 3 High 

Overall Averaged Ranking (Exposure)3: 5 High

Overall Averaged Confidence (Exposure)4: 3 High

384
Black Rail – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 4 Moderate-High Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Precipitation

• Salinity

• Sea level rise

• Wave action

• Storm severity and frequency

Overall: 4 Moderate-High

• 3 Moderate 

• 4 Moderate-High

• 5 High 

• 2 Low-Moderate 

• 4 Moderate-High

Overall: 3 High

• 2 Moderate 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

Disturbance Regimes

• Storms

• Flooding

Overall: 5 High Overall: 2 Moderate

Dependencies

• Dependence on sensitive habitat types

o Tidal marsh

• Dependence on specific prey or forage species

• Other dependencies: none identified

• Generalist or specialist?

Overall: 3 Moderate

• 5 High 

• 2 Low-Moderate

• N/A

• 3 (Both generalist and specialist 

characteristics)

Overall: 3 High

• 3 High 

• 2 Moderate 

• N/A

• 2 Moderate 

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Pollution and poisons 

• Invasives

• Predation

• Land use change 

• Roads/armoring

Overall: 4 Moderate-High

• 4 Moderate-High

• 4 Moderate-High

• 5 High 

• 5 High 

• 3 Moderate

Overall: 3 High

• 2 Moderate 

• 3 High 

• 3 High 

• 3 High 

• 3 High

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

385
Sensitivity Factor Sensitivity Evaluation Confidence

Non-Climate Stressors – Current Exposure to Stressor

• Pollution and poisons 

• Invasives

• Predation

• Land use change 

• Roads/armoring 

Overall: 4 Moderate-High Overall: 3 High

• 2 Moderate 

• 3 High 

• 3 High 

• 3 High 

• 2 Moderate 

LOCAL

• 3 Moderate 

• 2 LowModerate

• 5 High 

• 5 High 

• 4 ModerateHigh

REGIONAL

• 3 Moderate 

• 2 LowModerate

• 5 High 

• 5 High 

• 4 ModerateHigh

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 4 Moderate-High

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 2 (Moderate to large geographic region within 

a single state)

3 High

Population Status 1 (Endangered) 3 High

Population Connectivity 2 (Somewhat isolated and/or fragmented) 3 High

Dispersal Ability 2 Low-Moderate 2 Moderate

Maximum Annual Dispersal Distance Not Answered Not Answered

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 1 Low

• 1 Low

• Not Answered

• Not Answered

• Not Answered

Overall: 2 Moderate

• 2 Moderate 

• Not Answered

• Not Answered

• Not Answered

Species Value 2 Low-Moderate 2 Moderate

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

386
Likelihood of Managing or Alleviating Climate Impacts 4 Moderate-High 2 Moderate

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 2 Low-Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 3 High 

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in precipitation

• Changes in salinity

• Increased flooding 

• Sea level rise

Overall: 2 Low-Moderate

• 1 Low

• 2 Low-Moderate 

• 3 Moderate 

• 3 Moderate

Overall: 3 High

• 2 Moderate 

• 3 High 

• 3 High 

• 3 High

Overall Averaged Ranking (Exposure)3: 2 Low-Moderate

Overall Averaged Confidence (Exposure)4: 3 High

387
Blue Rockfish – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Sea surface temperature

• Salinity

• Oxygen 

• pH 

• Dynamic ocean conditions 

(currents/mixing/stratification) 

• Other: Pacific Decadal Oscillation

Overall: 4 Moderate-High

• 3 Moderate 

• 4 Moderate-High

• 5 High 

• 4 Moderate-High

• 2 Low-Moderate 

• 4 Moderate-High

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

• 3 High 

• 1 Low

• 2 Moderate 

• 3 High

Disturbance Regimes

• Storms

• Disease

Overall: 4 Moderate-High Overall: 3 High

Dependencies

• Dependence on sensitive habitat types

o Kelp forest

o Nearshore

• Dependence on specific prey or forage species

• Other dependencies

o Lack of successful reproduction in El Niño 

years

o Lack of recruitment with poor upwelling 

• Generalist or specialist?

Overall: 3 Moderate

• 4 Moderate-High

• 2 Low-Moderate 

• 2 Low-Moderate 

• 3 (Both generalist and specialist 

characteristics)

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High 

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

388
Sensitivity Factor Sensitivity Evaluation Confidence

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Harvest

• Energy production 

• Pollution and poisons

Overall: 3 Moderate

• 4 Moderate-High

• 3 Moderate 

• 3 Moderate

Overall: 3 High

• 3 High 

• 2 Moderate 

• 2 Moderate

Non-Climate Stressors – Current Exposure to Stressor

• Harvest

• Energy production 

• Pollution and poisons 

Overall: 2 Low-Moderate Overall: 1 Low

• 3 High 

• 1 Low

• 1 Low

LOCAL

• 5 High 

• 1 Low

• 1 Low

REGIONAL

• 3 Moderate 

• 1 Low

• 2 LowModerate

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 3 Moderate

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 4 (Stable population at abundant levels) 3 High

Population Connectivity 5 (Continuous) 3 High

Dispersal Ability 4 Moderate-High 3 High

Maximum Annual Dispersal Distance 75-100 km 2 Moderate

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

389
Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 3 Moderate

• 3 Moderate 

• 4 Moderate-High

• 3 Moderate 

• 3 Moderate

Overall: 2 Moderate

• 3 High 

• 2 Moderate 

• 1 Low

• 2 Moderate

Species Value 4 Moderate-High 3 High

Likelihood of Managing or Alleviating Climate Impacts 2 Low-Moderate 1 Low

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 4 Moderate-High

Overall Averaged Confidence (Adaptive Capacity)4: 3 High 

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in sea surface temperature

• Decreased dissolved oxygen

• Changes in salinity

• Decreased pH

• Increased storminess

• El Niño events

Overall: 3 Moderate

• 2 Low-Moderate 

• 1 Low

• 1 Low

• 3 Moderate 

• 4 Moderate-High

• 5 High 

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 3 High

• 3 High

• 2 Moderate 

Overall Averaged Ranking (Exposure)3: 3 Moderate

Overall Averaged Confidence (Exposure)4: 2 Moderate

390
Blue Whale – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 4 Moderate-High Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Sea surface temperature

• Dynamic ocean conditions 

(currents/mixing/stratification)

Overall: 2 Low-Moderate

• 2 Low-Moderate 

• 2 Low-Moderate 

Overall: 1 Low

• 2 Moderate 

• 1 Low

Disturbance Regimes: none identified N/A N/A

Dependencies

• Dependence on sensitive habitat types

o Continental shelf

• Dependence on specific prey or forage species

• Other dependencies

o Less offspring in unfavorable conditions 

• Generalist or specialist?

Overall: 4 Moderate-High

• 2 Low-Moderate 

• 5 High 

• 3 Moderate 

• 5 (Specialist)

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Pollution and poisons 

• Human interactions 

• Anthropogenic noise

Overall: 5 High

• 5 High

• 5 High

• 5 High

Overall: 3 High

• 3 High

• 3 High

• 3 High

Non-Climate Stressors – Current Exposure to Stressor

• Pollution and poisons 

• Human interactions 

• Anthropogenic noise 

Overall: 5 High Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

LOCAL

• 5 High 

• 5 High 

• 5 High

REGIONAL

• 5 High 

• 5 High 

• 5 High

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 4 Moderate-High

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity. 3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 

391
Overall Averaged Confidence (Sensitivity)4

: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 1 (Endangered) 3 High

Population Connectivity Not Answered Not Answered

Dispersal Ability 5 High 3 High

Maximum Annual Dispersal Distance >100 km Not Answered

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Not Answered Not Answered

Species Value 5 High 3 High

Likelihood of Managing or Alleviating Climate Impacts 3 Moderate 2 Moderate

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 4 Moderate-High

Overall Averaged Confidence (Adaptive Capacity)4: 3 High 

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in sea surface temperature

• Altered currents and mixing

Overall: 5 High

• 5 High 

• 5 High 

Overall: 2 Moderate

• 3 High 

• 1 Low

Overall Averaged Ranking (Exposure)3: 5 High

Overall Averaged Confidence (Exposure)4: 2 Moderate

4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure. 

392
California Hydrocoral and Red Sponge – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Oxygen 

• pH 

• Dynamic ocean conditions 

(currents/mixing/stratification)

Overall: 3 Moderate

• 3 Moderate 

• 3 Moderate 

• 4 Moderate-High

Overall: 1 Low

• 1 Low

• 1 Low

• 3 High 

Disturbance regimes: none identified N/A N/A

Dependencies

• Dependence on sensitive habitat types

o Rocky substrate 

• Dependence on specific prey or forage species

• Other dependencies: none identified

• Generalist or specialist?

Overall: 3 Moderate

• 5 High 

• 2 Low-Moderate 

• N/A

• 3 (Both generalist and specialist 

characteristics)

Overall: 2 Moderate

• 3 High 

• 2 Moderate 

• N/A

• 1 Low

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Pollution and poisons 

• Harvest

• Invasive species

Overall: 5 High

• 4 Moderate-High

• 4 Moderate-High

• 5 High

Overall: 3 High

• 3 High 

• 3 High 

• 3 High

Non-Climate Stressors – Current Exposure to Stressor

• Pollution and poisons 

• Harvest

• Invasive species

Overall: 1 Low Overall: 3 High

• 3 High 

• 2 Moderate 

• 2 Moderate

LOCAL

• 1 Low

• 2 Low-Moderate 

• 1 Low

REGIONAL

• 1 Low

• 2 LowModerate 

• 1 Low

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

393
Sensitivity Factor Sensitivity Evaluation Confidence

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 3 Moderate 

Overall Averaged Confidence (Sensitivity)4: 2 Moderate

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 3 (Distribution within single state to two 

states)

3 High

Population Status 3 (Diminished but generally stable) 2 Moderate

Population Connectivity 3 (Patchy across an area with some 

connectivity among patches)

2 Moderate

Dispersal Ability 4 Moderate-High 3 High

Maximum Annual Dispersal Distance Not Answered Not Answered

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Not Answered Not Answered

Species Value 4 Moderate-High 3 High

Likelihood of Managing or Alleviating Climate Impacts 2 Low-Moderate 2 Moderate

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 3 High 

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

394
EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in sea surface temperature

• Decreased pH

• Altered currents and mixing

• Decreased dissolved oxygen

Overall: 3 Moderate

• 3 Moderate 

• 4 Moderate-High

• 3 Moderate 

• 2 Low-Moderate 

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 1 Low

Overall Averaged Ranking (Exposure)3: 3 Moderate

Overall Averaged Confidence (Exposure)4: 3 High

395
California Mussel – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Air temperature

• Sea surface temperature

• Precipitation

• Salinity

• Oxygen 

• pH 

• Sea level rise

• Wave action

• Dynamic ocean conditions 

(currents/mixing/stratification) 

• Coastal erosion

Overall: 4 Moderate-High

• 5 High 

• 3 Moderate 

• 2 Low-Moderate 

• 5 High 

• 2 Low-Moderate

• 4 Moderate-High

• 3 Moderate 

• 5 High 

• 3 Moderate 

• 4 Moderate-High

Overall: 2 Moderate

• 3 High 

• 1 Low

• 1 Low

• 2 Moderate 

• 1 Low

• 1 Low

• 2 Moderate 

• 3 High 

• 1 Low

• 1 Low

Disturbance Regimes

• Wind 

• Disease

• Storms

• Flooding 

• Extreme heat events

Overall: 5 High Overall: 2 Moderate

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

396
Sensitivity Factor Sensitivity Evaluation Confidence

Dependencies

• Dependence on sensitive habitat types

• Dependence on specific prey or forage species

• Other dependencies

o Mid-intertidal height of exposed rocky 

shores 

• Generalist or specialist?

Overall: 2 Low-Moderate

• 1 Low

• 1 Low

• 5 High 

• 3 (Both generalist and specialist 

characteristics)

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High 

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Land use change 

• Armoring 

• Pollution and poisons 

• Harvest

• Recreation

• Invasive species

• Boat groundings

Overall: 4 Moderate-High

• 3 Moderate 

• 4 Moderate-High

• 4 Moderate-High

• 3 Moderate 

• 4 Moderate-High

• 4 Moderate-High

• 3 Moderate

Overall: 1 Low

• 1 Low

• 2 Moderate 

• 1 Low

• 1 Low

• 1 Low

• 2 Moderate 

• 1 Low

Non-Climate Stressors – Current Exposure to Stressor

• Land use change 

• Armoring 

• Pollution/oil spills

• Harvest

• Recreation/trampling 

• Invasives/species range expansions

• Boat groundings 

Overall: 2 Low-Moderate Overall: 2 Moderate

• 1 Low

• 3 High 

• 1 Low

• 1 Low

• 2 Moderate 

• 1 Low

• 3 High 

LOCAL

• 2 Low-Moderate 

• 5 High 

• 4 Moderate-High

• 2 Low-Moderate

• 4 Moderate-High

• 4 Moderate-High

• 5 High

REGIONAL

• 1 Low

• 1 Low

• 1 Low

• 1 Low

• 1 Low

• 1 Low

• 1 Low

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 3 Moderate 

Overall Averaged Confidence (Sensitivity)4: 3 High

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 

397
ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 5 (Healthy and/or expanding) 3 High

Population Connectivity 5 (Continuous) 3 High

Dispersal Ability 5 High 3 High

Maximum Annual Dispersal Distance 50-100 km 3 High

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 2 Low-Moderate

• 1 Low

• 4 Moderate-High

• 1 Low

• 3 Moderate

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High

Species Value 3 Moderate 3 High

Likelihood of Managing or Alleviating Climate Impacts 2 Low-Moderate 3 High

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 3 High 

4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

398
EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in air temperature

• Changes in precipitation

• Changes in salinity

• Altered currents and mixing

• Changes in sea surface temperature

• Increased coastal erosion and runoff 

• Decreased pH

• Increased flooding 

• Sea level rise

• Increased storminess

• Decreased dissolved oxygen

Overall: 4 Moderate-High

• 5 High 

• 5 High 

• 5 High 

• 4 Moderate-High

• 5 High 

• 2 Low-Moderate

• 5 High 

• 3 Moderate 

• 5 High 

• 3 Moderate 

• 2 Low-Moderate

Overall: 2 Moderate

• 3 High 

• 3 High 

• 2 Moderate 

• 1 Low

• 2 Moderate 

• 2 Moderate 

• 3 High 

• 2 Moderate 

• 3 High 

• 2 Moderate 

• 1 Low

Overall Averaged Ranking (Exposure)3: 4 Moderate-High

Overall Averaged Confidence (Exposure)4: 2 Moderate

399
Cassin’s Auklet – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Air temperature

• Sea surface temperature

• Precipitation

• Salinity (for prey species)

• Oxygen (for prey species)

• pH (for prey species)

• Sea level rise

• Wave action

• Dynamic ocean conditions 

(currents/mixing/stratification) 

• Coastal erosion

• Other: Extreme Weather Events

Overall: 2 Low-Moderate

• 1 Low

• 3 Moderate 

• 1 Low

• 2 Low-Moderate 

• 2 Low-Moderate 

• 2 Low-Moderate 

• 2 Low-Moderate 

• 1 Low

• 3 Moderate 

• 2 Low-Moderate 

• 4 Moderate-High

Overall: 2 Moderate

• 2 Moderate 

• 3 High

• 3 High

• 1 Low

• 1 Low

• 1 Low

• 3 High

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 3 High

Disturbance Regimes

• Disease

• Storms

• Flooding 

• Drought

Overall: 4 Moderate-High Overall: 3 High

Dependencies

• Dependence on sensitive habitat types

o Breeding habitat (offshore, predator-free 

islands) 

o Feeding habitat (mid-water pelagic)

• Dependence on specific prey or forage species

Overall: 5 High

• 5 High

• 2 Low-Moderate3

• 4.5 High4

Overall: 3 High

• 3 High

• 3 High

• 3 High

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

3 Average of two submitted scores (1,3).

4 Average of two submitted scores (4,5).

400
Sensitivity Factor Sensitivity Evaluation Confidence

o Availability of krill

• Other dependencies

o Timing of breeding 

• Generalist or specialist?

• 5 High

• 4 (Mostly specialist)

• 3 High

• 3 High

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Fisheries

• Pollution

• Oil spills

• Invasives (rodents) 

• Invasives (plants)

• Energy production 

• Researcher disturbance

• Land use change

Overall: 2 Low-Moderate

• 2 Low-Moderate 

• 1 Low

• 5 High

• 5 High

• 1 Low

• 2 Low-Moderate 

• 1 Low

• 2 Low-Moderate

Overall: 2 Moderate

• 1 Low

• 2 Moderate 

• 3 High

• 3 High 

• 1 Low

• 3 High

• 2 Moderate 

• 3 High

Non-Climate Stressors – Current Exposure to Stressor

• Fisheries

• Pollution

• Oil spills

• Invasives (rodents)

• Invasives (plants)

• Energy production 

• Researcher disturbance

• Land use change

Overall: 1 Low Overall: 3 High

• 1 Low

• 2 Moderate 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 2 Moderate 

• 3 High

LOCAL

• 2 LowModerate

• 1 Low

• 2 LowModerate

• 1 Low

• 2 LowModerate

• 1 Low

• 1 Low

• 1 Low

REGIONAL

• 2 LowModerate

• 1 Low

• 2 LowModerate

• 1 Low

• Not 

Answered

• 1 Low

• Not 

Answered

• 1 Low

Other Sensitivities

• Climate impacts on krill and copepods 

• El Niño, major basin-scale oceanographic 

change

Overall: 5 High

• 5 High

• 4 Moderate-High

Overall: 3 High

• 3 High

• 3 High

401
Overall Averaged Ranking (Sensitivity)5

: 4 Moderate-High

Overall Averaged Confidence (Sensitivity)6: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 4.5 (Transcontinental)7 3 High

Population Status 3 (Diminished but generally stable)8 3 High

Population Connectivity 3.5 (Almost continuous)9 3 High

Dispersal Ability 3.5 Moderate-High9 2 Moderate

Maximum Annual Dispersal Distance >100 km 3 High

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 3 Moderate

• 3.5 Moderate-High9

• 2.5 Moderate10

• 3 Moderate8

• 3 Moderate8

Overall: 3 High

• 3 High 

• 2 Moderate11

• 2.5 High10

• 2.5 High10

Species Value 1.5 Low-Moderate12 2 Moderate

Likelihood of Managing or Alleviating Climate Impacts 1 Low 3 High

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)5: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)6: 3 High 

5 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 6 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure. 7 Average of two submitted scores (4,5). 8 Average of two submitted scores (2,4). 9 Average of two submitted scores (3,4). 10 Average of two submitted scores (2,3). 11 Average of two submitted scores (1,3). 12 Average of two submitted scores (1,2).

402
EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in air temperature

• Changes in precipitation

• Changes in salinity

• Altered currents and mixing

• Changes in sea surface temperature

• Increased coastal erosion and run-off 

• Decreased pH

• Increased flooding 

• Decreased dissolved oxygen

• Sea level rise

• Increased storminess 

Overall: 2 Low-Moderate

• 3 Moderate 

• 2 Low-Moderate 

• 3 Moderate 

• 4 Moderate-High

• 3 Moderate 

• 2 Low-Moderate 

• 3 Moderate 

• 2 Low-Moderate 

• 3 Moderate 

• 1 Low

• 2 Low-Moderate 

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

Overall Averaged Ranking (Exposure)5: 2 Low-Moderate

Overall Averaged Confidence (Exposure)6: 2 Moderate

403
Cavity Nesters: Ashy Storm Petrel (ASSP), Tufted Puffin (TUPU), Pigeon Guillemot (PIGU) – Overview of 

Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate (TUPU, PIGU), 4 Moderate-High (ASSP) Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Air temperature

• Sea surface temperature

• Precipitation

• Salinity

• Oxygen 

• pH 

• Sea level rise

• Wave action

• Dynamic ocean conditions 

(currents/mixing/stratification) 

• Coastal erosion

• Extreme weather conditions

Overall: 2 Low-Moderate

• 2 Low-Moderate 

• 3 Moderate 

• 1 Low

• 2 Low-Moderate 

• 2 Low-Moderate 

• 2 Low-Moderate 

• 1 Low

• 1 Low

• 3 Moderate 

• 2 Low-Moderate 

• 5 High

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 1 Low

• 1 Low

• 1 Low

• 3 High 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 3 High

Disturbance Regimes

• Disease

• Storms

• Flooding 

• Drought 

• Interspecific disturbance 

Overall: 5 High Overall: 3 High

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

404
Sensitivity Factor Sensitivity Evaluation Confidence

Dependencies

• Dependence on sensitive habitat types

o ASSP: Pelagic, surface

o TUPU: Pelagic, offshore foraging

o PIGU: Benthic, nearshore 

• Dependence on specific prey or forage species

• Other dependencies

o Timing of breeding 

o Foraging availability

• Generalist or specialist?

Overall: 4 Moderate-High

• Breeding habitat: 5 High; Feeding 

habitat: 3 Moderate

• 3 Moderate 

• 5 High 

• 3 (Both generalist and specialist 

characteristics)

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High 

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Aircraft/vessels

• Land use change 

• Pollution and poisons 

• Harvest

• Energy production 

• Recreation

• Invasive Species

Overall: 4 Moderate-High

• 3 Moderate 

• 2 Low-Moderate 

• 5 High 

• 3 Moderate 

• 2 Low-Moderate 

• 4 Moderate-High

• 5 High

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High

Non-Climate Stressors – Current Exposure to Stressor Overall: 1 Low Overall: 3 High

405
Sensitivity Factor Sensitivity Evaluation Confidence

• Aircraft/vessels

• Land use change 

• Pollution and poisons 

• Harvest

• Energy production 

• Recreation

• Invasive Species 

LOCAL

• 3 Moderate 

• 2 LowModerate

• 2 LowModerate

• 1 Low

• 1 Low

• 2 LowModerate

• 1 Low

REGIONAL

• 2 LowModerate

• 1 Low

• 2 Moderate 

• 1 Low

• 1 Low

• 1 Low

• 1 Low

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 3 Moderate

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent

o ASSP

o TUPU

o PIGU

• 2 (Moderate to large geographic region 

within a single state)

• 5 (Transcontinental) 

• 5 (Transcontinental)

• 3 High 

• 3 High 

• 3 High

Population Status

o ASSP

o TUPU

o PIGU

• 2 (Threatened)

• 5 (Healthy and/or expanding) 

• 5 (Healthy and/or expanding)

• 3 High 

• 3 High 

• 3 High

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

406
Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Population Connectivity

o ASSP

o TUPU

o PIGU

• 2 (Somewhat isolated and/or 

fragmented)

• 5 (Continuous)

• 5 (Continuous)

Not Answered

Dispersal Ability Not Answered Not Answered

Maximum Annual Dispersal Distance Not Answered Not Answered

Intraspecific/Life History Diversity

• Diversity of life history strategies

o ASSP

o TUPU

o PIGU

• Genetic diversity

o ASSP

o TUPU

o PIGU

• Behavioral plasticity

o ASSP

o TUPU

o PIGU

• Phenotypic plasticity

o ASSP

o TUPU

o PIGU

Overall: 2 Low-Moderate

• 1 Low

• 2 Low-Moderate 

• 3 Moderate 

• 3 Moderate 

• 3 Moderate 

• 3 Moderate 

• 2 Low-Moderate 

• 2 Low-Moderate 

• 2 Low-Moderate 

• 1 Low

• 2 Low-Moderate 

• 2 Low-Moderate

Overall: 3 High

• 3 High 

• 1 Low

• 2 Moderate 

• 2 Moderate 

Species Value

o ASSP

o TUPU

o PIGU

• 1 Low

• 4 Moderate-High

• 2 Low-Moderate

• 3 High 

• 3 High 

• 3 High

Likelihood of Managing or Alleviating Climate Impacts 1 Low 3 High

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 1 Low (ASSP); 3 Moderate (TUPU and PIGU)

407
Overall Averaged Confidence (Adaptive Capacity)4

: 3 High 

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in air temperature

• Changes in precipitation

• Changes in salinity

• Altered currents/mixing

• Changes in sea surface temperature

• Increased coastal erosion & runoff

• Decreased pH

• Increased flooding 

• Decreased dissolved oxygen

• Sea level rise

• Increased storminess

Overall: 2 Low-Moderate

• 2 Low-Moderate 

• 2 Low-Moderate 

• 3 Moderate 

• 4 Moderate-High

• 3 Moderate 

• 2 Low-Moderate 

• 3 Moderate 

• 2 Low-Moderate 

• 3 Moderate 

• 1 Low

• 3 Moderate

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate

Overall Averaged Ranking (Exposure)3: 2 Low-Moderate

Overall Averaged Confidence (Exposure)4: 2 Moderate

408
Boreal Copepods – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 2 Moderate

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Sea surface temperature

• Salinity

• Dynamic ocean conditions 

(currents/mixing/stratification)

Overall: 4 Moderate-High

• 4 Moderate-High

• 4 Moderate-High

• 4 Moderate-High

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

Disturbance Regimes

• Wind

Overall: 4 Moderate-High Overall: 3 High

Dependencies

• Dependence on sensitive habitat types

• Dependence on specific prey or forage species

• Other dependencies

o Ability to go into diapause

• Generalist or specialist?

Overall: 1 Low

• 1 Low

• 1 Low

• 2 Low-Moderate 

• 2 (Mostly generalist)

Overall: 2 Moderate

• 3 High 

• 1 Low

• 2 Moderate 

• 3 High

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Pollution and poisons

Overall: 1 Low

• 1 Low

Overall: 3 High

• 3 High

Non-Climate Stressors – Current Exposure to Stressor

• Pollution and poisons 

Overall: 1 Low Overall: 3 High

• 3 High 

LOCAL

• 1 Low

REGIONAL

• 1 Low

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 2 Low-Moderate

Overall Averaged Confidence (Sensitivity)4: 3 High

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above.

409
ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 3 (Distribution within single state to two states) 1 Low

Population Status 4 (Stable population at abundant levels) 1 Low

Population Connectivity 5 (Continuous) 1 Low

Dispersal Ability 5 High 1 Low

Maximum Annual Dispersal Distance >100 km 1 Low

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 2 Low-Moderate

• 2 Low-Moderate 

• 2 Low-Moderate

• 3 Moderate 

• 3 Moderate

Overall: 1 Low

• 1 Low

• 1 Low

• 2 Moderate 

• 2 Moderate

Species Value 1 Low 1 Low

Likelihood of Managing or Alleviating Climate Impacts 1 Low 2 Moderate

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 1 Low

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Altered currents and mixing

• Changes in salinity

• Changes in sea surface temperature

Overall: 5 High

• 5 High 

• 5 High 

• 5 High

Overall: 3 High

• 3 High 

• 3 High 

• 3 High

Overall Averaged Ranking (Exposure)3: 5 High

Overall Averaged Confidence (Exposure)4: 3 High 

4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

410
Coralline Algae – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Air temperature

• Sea surface temperature

• Precipitation

• Salinity

• pH 

• Coastal erosion

Overall: 3 Moderate

• 4 Moderate-High

• 4 Moderate-High

• 1 Low

• 2 Low-Moderate 

• 4 Moderate-High

• 2 Low-Moderate 

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 1 Low

• 2 Moderate 

• 3 High 

Disturbance Regimes

• Storms

Overall: 1 Low Overall: 2 Moderate

Dependencies

• Dependence on sensitive habitat types

o Rocky substrate 

• Dependence on specific prey or forage species

• Other dependencies

o Presence of grazers of competing algae

• Generalist or specialist?

Overall: 3 Moderate

• 5 High 

• 1 Low

• 4 Moderate-High

• 1 (Generalist)

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High 

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Nutrient pollution

Overall: 2 Low-Moderate

• 2 Low-Moderate

Overall: 2 Moderate

• 2 Moderate

Non-Climate Stressors – Current Exposure to Stressor

• Nutrient pollution 

Overall: 2 Low-Moderate Overall: 3 High

• 3 High 

LOCAL

• 3 Moderate 

REGIONAL

• 1 Low

Other Sensitivities: none identified N/A N/A

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

411
Overall Averaged Ranking (Sensitivity)3

: 2 Low-Moderate

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 5 (Healthy and/or expanding) 3 High

Population Connectivity 2 (Somewhat isolated/fragmented) 2 Moderate

Dispersal Ability 1 Low 2 Moderate

Maximum Annual Dispersal Distance 1-5 km 2 Moderate

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Behavioral plasticity

• Phenotypic plasticity 

Overall: 2 Low-Moderate

• 3 Moderate 

• 1 Low

• 2 Low-Moderate 

Overall: 3 High

• 2 Low-Moderate 

• 3 Moderate 

• 2 Moderate 

Species Value 1 Low 3 High

Likelihood of Managing or Alleviating Climate Impacts 2 Low-Moderate 3 High

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 2 Low-Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 3 High 

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in air temperature

• Changes in sea surface temperature

• Decreased pH

Overall: 3 Moderate

• 1 Low

• 3 Moderate 

• 5 High 

Overall: 3 High

• 3 High 

• 2 Moderate 

• 3 High 

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

412
Overall Averaged Ranking (Exposure)3

: 3 Moderate 

Overall Averaged Confidence (Exposure)4: 3 High

413
Gaper Clam – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 2 Moderate

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Air temperature

• Sea surface temperature

• Precipitation

• Salinity

• Oxygen 

• pH 

• Wave action

• Dynamic ocean conditions 

(currents/mixing/stratification) 

• Coastal erosion

Overall: 3 Moderate

• 3 Moderate 

• 4 Moderate-High

• 4 Moderate-High

• 2 Low-Moderate 

• 3 Moderate 

• 4 Moderate-High

• 3 Moderate 

• 2 Low-Moderate 

• 4 Moderate-High

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate

Disturbance Regimes

• Disease

• Storms

• Flooding

Overall: 3 Moderate Overall: 1 Low

Dependencies

• Dependence on sensitive habitat types

o Soft-bottom subtidal 

o Estuaries

• Dependence on specific prey or forage species

• Other dependencies: none identified

• Generalist or specialist?

Overall: 3 Moderate

• 5 High 

• 1 Low

• N/A

• 2 (Mostly generalist)

Overall: 3 High

• 3 High 

• 3 High 

• N/A

• 3 High 

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

414
Sensitivity Factor Sensitivity Evaluation Confidence

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Harvest

• Recreation

• Dredging 

• Overwater/underwater structures

• Pollutions and poisons

Overall: 3 Moderate

• 3 Moderate 

• 2 Low-Moderate 

• 3 Moderate 

• 3 Moderate 

• 5 High

Overall: 1 Low

• 1 Low

• 1 Low

• 1 Low

• 1 Low

• 2 Moderate

Non-Climate Stressors – Current Exposure to Stressor

• Harvest

• Recreation

• Dredging 

• Overwater/underwater structures

• Pollutions and poisons

Overall: 3 Moderate Overall: 1 Low

• 1 Low

• 1 Low

• 1 Low

• 1 Low 

• 2 Moderate 

LOCAL

• 4 ModerateHigh

• 2 LowModerate

• 3 Moderate 

• 3 Moderate 

• 2 LowModerate

REGIONAL

• 4 ModerateHigh

• 2 LowModerate

• 3 Moderate 

• 2 LowModerate

• 2 LowModerate

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 3 Moderate

Overall Averaged Confidence (Sensitivity)4: 2 Moderate

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 4 (Stable population at abundant levels) 2 Moderate

Population Connectivity 4 (Almost continuous) 2 Moderate

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

415
Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Dispersal Ability 2 Low-Moderate 2 Moderate

Maximum Annual Dispersal Distance Not Answered Not Answered

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 1 Low

• 2 Low-Moderate 

• 3 Moderate 

• 1 Low

• 1 Low

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 1 Low

Species Value 3 Moderate 3 High

Likelihood of Managing or Alleviating Climate Impacts 2 Low-Moderate 2 Moderate

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 3 High 

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Decreased pH

• Decreased dissolved oxygen

• Changes in sea surface temperature

• Changes in air temperature

• Increased coastal erosion and runoff 

• Increased flooding 

• Changes in precipitation

• Changes in salinity

• Increased storminess

Overall: 4 Moderate

• 4 Moderate-High

• 4 Moderate-High

• 4 Moderate-High

• 5 High 

• 5 High 

• 4 Moderate-High

• 4 Moderate-High

• 4 Moderate-High

• 3 Moderate 

Overall: 2 Moderate

• 2 Moderate 

• 3 High 

• 3 High 

• 3 High 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

Overall Averaged Ranking (Exposure)3: 4 Moderate-High

Overall Averaged Confidence (Exposure)4: 2 Moderate

416
Krill – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 2 Low-Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Sea surface temperature

• Dynamic ocean conditions 

(currents/mixing/stratification) 

Overall: 2 Low-Moderate

• 2 Low-Moderate 

• 3 Moderate 

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

Disturbance Regimes

• Wind

Overall: 3 Moderate Overall: 2 Moderate

Dependencies

• Dependence on sensitive habitat types

• Dependence on specific prey or forage species

• Other dependencies: none identified

• Generalist or specialist?

Overall: 1 Low

• 1 Low

• 1 Low

• N/A

• 2 (Mostly generalist)

Overall: 3 High

• 3 High 

• 2 Moderate 

• N/A

• 3 High

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Pollution and poisons

Overall: 1 Low

• 1 Low

Overall: 3 High

• 3 High

Non-Climate Stressors – Current Exposure to Stressor

• Pollution and poisons 

Overall: 1 Low Overall: 3 High

• 3 High 

LOCAL

• 1 Low

REGIONAL

• 1 Low

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 1 Low

Overall Averaged Confidence (Sensitivity)4: 3 High

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity. 3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

417
ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 4 (Stable population at abundant levels) 2 Moderate

Population Connectivity 5 (Continuous) 1 Low

Dispersal Ability 5 High 1 Low

Maximum Annual Dispersal Distance 25+ km 1 Low

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Not Answered Not Answered

Species Value 2 Low-Moderate 2 Moderate

Likelihood of Managing or Alleviating Climate Impacts 3 Moderate 3 High

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 4 Moderate-High

Overall Averaged Confidence (Adaptive Capacity)4: 2 Moderate

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Altered currents and mixing

• Changes in salinity

• Changes in sea surface temperature

Overall: 5 High

• 5 High 

• 5 High 

• 5 High

Overall: 3 High

• 3 High 

• 3 High 

• 3 High

Overall Averaged Ranking (Exposure)3: 5 High

Overall Averaged Confidence (Exposure)4: 3 High

418
Mole Crab – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Sea surface temperature

• Precipitation

• Salinity

• pH 

• Sea level rise

• Dynamic ocean conditions 

(currents/mixing/stratification) 

• Coastal erosion

• Harmful algal blooms 

Overall: 3 Moderate

• 1 Low

• 3 Moderate 

• 5 High 

• 3 Moderate 

• 2 Low-Moderate 

• 2 Low-Moderate 

• 3.5 Moderate-High3

• 2 Low-Moderate 

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

• 3 High 

• 2 Moderate 

• 1 Low

• 1 Low

• 2 Moderate 

• 1 Low

Disturbance Regimes

• Storms

• Flooding

Overall: 3 Moderate Overall: 2 Moderate

Dependencies

• Dependence on sensitive habitat types

• Dependence on specific prey or forage species

• Other dependencies

o Reproductive dependency 

• Generalist or specialist?

Overall: 1 Low

• 1 Low

• 1 Low

• 3 Moderate 

• 1 (Generalist)

Overall: 3 High

• 3 High 

• 3 High 

• 2 Moderate 

• 3 High 

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

3 Average of two submitted scores (5, 2)

419
Sensitivity Factor Sensitivity Evaluation Confidence

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Pollution and poisons 

• Roads/armoring 

• Land use change

Overall: 3 Moderate

• 2 Low-Moderate 

• 3 Moderate 

• 5 High

Overall: 3 High

• 2 Moderate 

• 2 Moderate 

• 3 High

Non-Climate Stressors – Current Exposure to Stressor

• Pollution and poisons 

• Roads/armoring 

• Land use change 

Overall: 1 Low Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

• Not Answered

LOCAL

• 2 LowModerate

• 1 Low

• Not Answered

REGIONAL

• 1 Low

• 1 Low

• Not Answered

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)4: 2 Low-Moderate

Overall Averaged Confidence (Sensitivity)5: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 5 (Healthy and/or expanding) 3 High

Population Connectivity 5 (Continuous) 3 High

Dispersal Ability 5 High 3 High

Maximum Annual Dispersal Distance Unknown N/A

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 3 Moderate

• 3 Moderate 

• 3 Moderate 

• 2 Low-Moderate 

• 4 Moderate-High

Overall: 1 Low

• 2 Moderate 

• 1 Low

• 1 Low

• 1 Low

4 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 5 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

420
Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Species Value 1 Low 3 High

Likelihood of Managing or Alleviating Climate Impacts 2 Low-Moderate 1 Low

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)4: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)5: 2 Moderate

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Increased coastal erosion and runoff 

• Decreased pH

• Sea level rise

• Changes in sea surface temperature

• Changes in precipitation

• Changes in salinity

• Increased storminess

• Altered currents and mixing

• Increased flooding 

Overall: 5 High

• 5 High 

• 5 High 

• 5 High 

• 5 High 

• 5 High 

• 5 High 

• 5 High 

• 5 High

• 3 Moderate 

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 2 Moderate 

Overall Averaged Ranking (Exposure)4: 5 High

Overall Averaged Confidence (Exposure)5: 3 High 

421
Northern Anchovy – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 2 Moderate

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Air temperature

• Sea surface temperature

• Precipitation

• Salinity

• Oxygen 

• pH 

• Dynamic ocean conditions 

(currents/mixing/stratification) 

• Coastal erosion

Overall: 4 Moderate-High

• 2 Low-Moderate 

• 5 High 

• 2 Low-Moderate 

• 3 Moderate 

• 4 Moderate-High

• 4 Moderate-High

• 5 High 

• 3 Moderate

Overall: 2 Moderate

• 2 Moderate 

• 3 High 

• 2 Moderate 

• 2 Moderate 

• 3 High 

• 1 Low

• 3 High 

• 1 Low

Disturbance Regimes

• Wind 

• Storms

Overall: 2 Low-Moderate Overall: 1 Low

Dependencies

• Dependence on sensitive habitat types

o Offshore/Pelagic water column

• Dependence on specific prey or forage species

• Other dependencies: none identified

• Generalist or specialist?

Overall: 3 Moderate

• 4 Moderate-High

• 3 Moderate 

• N/A

• 3 (Both generalist and specialist 

characteristics)

Overall: 3 High

• 3 High 

• 2 Moderate 

• N/A

• 2 Moderate 

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Harvest

• Pollution and poisons

Overall: 4 Moderate-High

• 5 High 

• 2 Low-Moderate

Overall: 3 High

• 3 High 

• 2 Moderate

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

422
Sensitivity Factor Sensitivity Evaluation Confidence

Non-Climate Stressors – Current Exposure to Stressor

• Harvest

• Pollution and poisons 

Overall: 1 Low Overall: 3 High

• 2 Moderate 

• 3 High 

LOCAL

• 1 Low

• 1 Low

REGIONAL

• 1 Low

• 1 Low

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 3 Moderate

Overall Averaged Confidence (Sensitivity)4: 2 Moderate

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 3 (Diminished but generally stable) 1 Low

Population Connectivity 3 (Patchy across an area with some 

connectivity among patches)

3 High

Dispersal Ability 3 Moderate 2 Moderate

Maximum Annual Dispersal Distance 50-75 km 1 Low

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 4 Moderate-High

• 3 Moderate 

• 5 High 

• 3 Moderate 

• 3 Moderate

Overall: 1 Low

• 1 Low

• 3 High 

• 1 Low

• 1 Low

Species Value 4 Moderate-High 3 High

Likelihood of Managing or Alleviating Climate Impacts 2 Low-Moderate 2 Moderate

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 2 Moderate

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure. 

423
EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in sea surface temperature

• Decreased dissolved oxygen

• Changes in salinity

• Decreased pH

• Increased storminess

• Altered currents and mixing

• Increased coastal erosion and runoff 

Overall: 3 Moderate

• 5 High 

• 4 Moderate-High

• 3 Moderate 

• 4 Moderate-High

• 2 Low-Moderate

• 2 Low-Moderate 

• 3 Moderate 

Overall: 2 Moderate

• 3 High 

• 3 High 

• 2 Moderate 

• 1 Low

• 1 Low

• 1 Low

• 1 Low

Overall Averaged Ranking (Exposure)3: 3 Moderate

Overall Averaged Confidence (Exposure)4: 2 Moderate

424
Ochre Sea Star – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Air temperature

• Sea surface temperature

• Precipitation

• Salinity

• Oxygen 

• pH 

• Sea level rise

• Wave action

• Dynamic ocean conditions 

(currents/mixing/stratification) 

• Coastal erosion

Overall: 3 Moderate

• 5 High 

• 3 Moderate 

• 2 Low-Moderate 

• 5 High 

• 2 Low-Moderate 

• 2 Low-Moderate 

• 3 Moderate 

• 5 High 

• 3 Moderate 

• 4 Moderate-High

Overall: 2 Moderate

• 3 High 

• 1 Low

• 1 Low

• 2 Moderate 

• 1 Low

• 1 Low

• 2 Moderate 

• 3 High 

• 1 Low

• 1 Low

Disturbance Regimes

• Wind 

• Disease

• Storms

• Flooding 

• Extreme heat events

Overall: 5 High Overall: 2 Moderate

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

425
Sensitivity Factor Sensitivity Evaluation Confidence

Dependencies

• Dependence on sensitive habitat types

• Dependence on specific prey or forage species

o CA Mussel

• Other dependencies

o Hard substrate

• Generalist or specialist?

Overall: 2 Low-Moderate

• 1 Low

• 1 Low

• 5 High 

• 2 (Mostly generalist)

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Disease

• Recreation

Overall: 3 Moderate

• 5 High 

• 1 Low

Overall: 3 High

• 3 High 

• 3 High

Non-Climate Stressors – Current Exposure to Stressor

• Disease 

• Recreation

Overall: 3 Moderate Overall: 3 High

• 3 High 

• 3 High 

LOCAL

• 3 Moderate 

• 4 ModerateHigh

REGIONAL

• 5 High 

• 1 Low

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 3 Moderate

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 5 (Healthy and/or expanding) 3 High

Population Connectivity 5 (Continuous) 3 High

Dispersal Ability 5 High 3 High

Maximum Annual Dispersal Distance 50-100 km 1 Low

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

426
Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 2 Low-Moderate

• 1 Low

• 4 Moderate-High

• 3 Moderate 

• 2 Low-Moderate

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High

Species Value 3 Moderate 1 Low

Likelihood of Managing or Alleviating Climate Impacts 2 Low-Moderate 1 Low

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 4 Moderate-High

Overall Averaged Confidence (Adaptive Capacity)4: 3 High 

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in air temperature

• Changes in precipitation

• Changes in salinity

• Altered currents and mixing

• Changes in sea surface temperature

• Increased coastal erosion and runoff 

• Decreased pH

• Increased flooding 

• Sea level rise

• Increased storminess

• Decreased dissolved oxygen

Overall: 4 Moderate-High

• 5 High 

• 5 High 

• 5 High 

• 4 Moderate-High

• 5 High 

• 3 Moderate 

• 5 High 

• 3 Moderate 

• 5 High 

• 3 Moderate 

• 2 Low-Moderate 

Overall: 2 Moderate

• 3 High 

• 3 High 

• 2 Moderate 

• 1 Low

• 2 Moderate 

• 2 Moderate 

• 3 High 

• 2 Moderate 

• 3 High 

• 2 Moderate 

• 1 Low

Overall Averaged Ranking (Exposure)3: 4 Moderate-High

Overall Averaged Confidence (Exposure)4: 2 Moderate

427
Olympia Oyster – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Air temperature

• Sea surface temperature

• Precipitation

• Salinity

• Oxygen 

• pH 

• Wave action

• Currents/mixing/stratification

• Coastal erosion

• Other: Sedimentation from runoff and currents

Overall: 3 Moderate

• 2 Low-Moderate 

• 2 Low-Moderate 

• 5 High 

• 5 High 

• 3 Moderate 

• 3 Moderate 

• 2 Low-Moderate 

• 2 Low-Moderate 

• 3 Moderate 

• 3 Moderate

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 3 High

Disturbance Regimes

• Storms

• Flooding

Overall: 5 High Overall: 3 High

Dependencies

• Dependence on sensitive habitat types

o Hard substrate to gravel in estuaries

• Dependence on specific prey or forage species

• Other dependencies: none identified

• Generalist or specialist?

Overall: 2 Low-Moderate

• 3 Moderate 

• 1 Low

• N/A

• 3 (Both generalist and specialist 

characteristics)

Overall: 3 High

• 3 High 

• 3 High 

• N/A

• 3 High 

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

428
Sensitivity Factor Sensitivity Evaluation Confidence

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Pollution and poisons 

• Dredging 

• Invasive and other problematic species

Overall: 5 High

• 3 Moderate 

• 5 High 

• 5 High

Overall: 3 High

• 2 Moderate 

• 2 Moderate 

• 3 High

Non-Climate Stressors – Current Exposure to Stressor

• Pollution and poisons 

• Dredging 

• Invasive and other problematic species

Overall: 3 Moderate Overall: 3 High

• 2 Moderate 

• 2 Moderate 

• 3 High 

LOCAL

• 3 Moderate 

• 2 LowModerate

• 5 High

REGIONAL

• 2 LowModerate

• 2 LowModerate

• 3 Moderate

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 3 Moderate

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 3 (Diminished but generally stable) 3 High

Population Connectivity 2 (Somewhat isolated and/or fragmented) 3 High

Dispersal Ability 3 Moderate 3 High

Maximum Annual Dispersal Distance 5-25 km 2 Moderate

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

429
Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 2 Low-Moderate

• 2 Low-Moderate 

• 3 Moderate 

• 1 Low

• 3 Moderate

Overall: 3 High

• 2 Moderate 

• 2 Moderate 

• 3 High 

• 3 High

Species Value 5 High 3 High

Likelihood of Managing or Alleviating Climate Impacts 2 Low-Moderate 2 Moderate

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 3 High 

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Decreased pH

• Changes in sea surface temperature

• Changes in air temperature

• Increased coastal erosion & runoff

• Increased flooding 

• Changes in precipitation

• Changes in salinity

• Increased storminess

Overall: 5 High

• 4 Moderate-High

• 4 Moderate-High

• 4 Moderate-High

• 4 Moderate-High

• 5 High 

• 5 High 

• 5 High 

• 3 Moderate

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 2 Moderate

Overall Averaged Ranking (Exposure)3: 5 High

Overall Averaged Confidence (Exposure)4: 3 High

430
Pacific Herring – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 2 Moderate

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Air temperature

• Sea surface temperature

• Precipitation

• Salinity

• Oxygen 

• pH 

• Dynamic ocean conditions 

(currents/mixing/stratification)

Overall: 3 Moderate

• 2 Low-Moderate 

• 4 Moderate-High

• 3 Moderate 

• 4 Moderate-High

• 2 Low-Moderate 

• 3 Moderate 

• 3 Moderate 

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

Disturbance Regimes

• Storms

• Flooding

Overall: 3 Moderate Overall: 2 Moderate

Dependencies

• Dependence on sensitive habitat types

o Estuaries

• Dependence on specific prey or forage species

• Other dependencies: none identified

• Generalist or specialist?

Overall: 3 Moderate

• 5 High 

• 2 Low-Moderate 

• N/A

• 3 (Both generalist and specialist 

characteristics)

Overall: 2 Moderate

• 3 High 

• 1 Low

• N/A

• 2 Moderate 

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Harvest

Overall: 1 Low

• 1 Low

Overall: 3 High

• 3 High

Non-Climate Stressors – Current Exposure to Stressor Overall: 1 Low Overall: 3 High

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

431
Sensitivity Factor Sensitivity Evaluation Confidence

• Harvest

LOCAL

• 1 Low

REGIONAL

• 1 Low • 3 High 

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 2 Low-Moderate

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 4 (Moderate to large geographic area) 2 Moderate

Population Status 3 (Diminished but generally stable) 2 Moderate

Population Connectivity 3 (Patchy across an area with some 

connectivity among patches)

2 Moderate

Dispersal Ability 5 High 2 Moderate

Maximum Annual Dispersal Distance 25-50 km 1 Low

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 3 Moderate

• 2 Low-Moderate 

• 3 Moderate 

• 3 Moderate 

• 3 Moderate

Overall: 1 Low

• 1 Low

• 2 Moderate 

• 1 Low

• 1 Low

Species Value 1 Low 3 High

Likelihood of Managing or Alleviating Climate Impacts 2 Low-Moderate 2 Moderate

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 2 Moderate

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

432
EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in precipitation

• Coastal erosion and runoff 

• Changes in salinity

• Decreased pH

• Increased storminess

• Changes in sea surface temperature

Overall: 4 Moderate-High

• 3 Moderate 

• 3 Moderate 

• 4 Moderate-High

• 4 Moderate-High

• 4 Moderate-High

• 4 Moderate-High

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

Overall Averaged Ranking (Exposure)3: 4 Moderate-High

Overall Averaged Confidence (Exposure)4: 2 Moderate

433
Pacific Sardine – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 2 Moderate

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Sea surface temperature

• Salinity

• Oxygen 

• pH 

• Dynamic ocean conditions 

(currents/mixing/stratification)

Overall: 4 Moderate-High

• 5 High 

• 3 Moderate 

• 4 Moderate-High

• 4 Moderate-High

• 5 High 

Overall: 3 High

• 3 High 

• 2 Moderate 

• 3 High 

• 1 Low

• 3 High 

Disturbance Regimes

• Wind 

• Storms

Overall: 2 Low-Moderate Overall: 1 Low

Dependencies

• Dependence on sensitive habitat types

o Offshore/Pelagic water column

• Dependence on specific prey or forage species

• Other dependencies: none identified

• Generalist or specialist?

Overall: 4 Moderate-High

• 5 High 

• 3 Moderate 

• N/A

• 3 (Both generalist and specialist 

characteristics)

Overall: 3 High

• 3 High 

• 2 Moderate 

• N/A

• 2 Moderate 

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Harvest

• Pollution and poisons 

Overall: 4 Moderate-High

• 5 High 

• 2 Low-Moderate 

Overall: 3 High

• 3 High 

• 2 Moderate 

Non-Climate Stressors – Current Exposure to Stressor Overall: 1 Low Overall: 3 High

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

434
Sensitivity Factor Sensitivity Evaluation Confidence

• Harvest

• Pollution and poisons

LOCAL

• 1 Low

• 1 Low

REGIONAL

• 1 Low

• 1 Low

• 2 Moderate 

• 3 High

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 3 Moderate

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 3 (Diminished but generally stable) 2 Moderate

Population Connectivity 3 (Patchy across an area with some 

connectivity among patches)

3 High

Dispersal Ability 5 High 3 High

Maximum Annual Dispersal Distance >100 km 3 High

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 4 Moderate-High

• 3 Moderate 

• 5 High 

• 3 Moderate 

• 3 Moderate

Overall: 1 Low

• 1 Low

• 3 High 

• 1 Low

• 1 Low

Species Value 5 High 3 High

Likelihood of Managing or Alleviating Climate Impacts 3 Moderate 2 Moderate

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 4 Moderate-High

Overall Averaged Confidence (Adaptive Capacity)4: 2 Moderate

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

435
EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in sea surface temperature

• Decreased dissolved oxygen

• Changes in salinity

• Decreased pH

• Increased storminess

• Altered currents and mixing

Overall: 3 Moderate

• 5 High 

• 4 Moderate-High

• 3 Moderate 

• 4 Moderate-High

• 2 Low-Moderate 

• 2 Low-Moderate 

Overall: 2 Moderate

• 3 High 

• 3 High 

• 2 Moderate 

• 1 Low

• 1 Low

• 1 Low

Overall Averaged Ranking (Exposure)3: 3 Moderate

Overall Averaged Confidence (Exposure)4: 2 Moderate

436
Pteropod – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 4 Moderate-High Overall Confidence2: 2 Moderate

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• pH 

• Dynamic ocean conditions 

(currents/mixing/stratification)

Overall: 5 High

• 5 High 

• 4 Moderate-High

Overall: 3 High

• 3 High 

• 3 High 

Disturbance Regimes: none identified N/A N/A

Dependencies

• Dependence on sensitive habitat types

• Dependence on specific prey or forage species

• Other dependencies: none identified

• Generalist or specialist?

Overall: 3 Moderate

• 2 Low-Moderate 

• 4 Moderate-High

• N/A

• 4 (Mostly specialist)

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

• N/A

• 2 Moderate 

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Not Answered

Not Answered Not Answered

Non-Climate Stressors – Current Exposure to Stressor

• Not Answered

Not Answered Not Answered

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 4 Moderate-High 

Overall Averaged Confidence (Sensitivity)4: 2 Moderate

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

437
ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 4 (Stable population at abundant levels) 1 Low

Population Connectivity 5 (Continuous) 2 Moderate

Dispersal Ability 4 Moderate-High 2 Moderate

Maximum Annual Dispersal Distance >100 km 2 Moderate

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 1 Low

• 2 Low-Moderate 

• 3 Moderate 

• 1 Low

• 1 Low

Overall: 1 Low

• 2 Moderate 

• 2 Moderate 

• 1 Low

• 1 Low

Species Value 1 Low 3 High

Likelihood of Managing or Alleviating Climate Impacts 1 Low 3 High

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 2 Moderate

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Altered currents and mixing

• Decreased pH

Overall: 5 High

• 5 High 

• 5 High 

Overall: 3 High

• 3 High 

• 3 High 

Overall Averaged Ranking (Exposure)3: 5 High

Overall Averaged Confidence (Exposure)4: 3 High

438
Red Abalone – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Air temperature

• Sea surface temperature

• Salinity

• Oxygen 

• pH 

• Sea level rise

• Wave action

• Dynamic ocean conditions 

(currents/mixing/stratification) 

• Coastal erosion

Overall: 4 Moderate-High

• 5 High 

• 4 Moderate-High

• 4 Moderate-High

• 5 High 

• 5 High 

• 2 Low-Moderate 

• 3 Moderate

• 3 Moderate 

• 2 Low-Moderate

Overall: 3 High

• 3 High 

• 3 High 

• 2 Moderate 

• 3 High 

• 2 Moderate 

• 1 Low

• 3 High 

• 3 High 

• 3 High

Disturbance Regimes

• Disease

• Storms

• Harmful Algal Blooms

Overall: 5 High Overall: 3 High

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

439
Sensitivity Factor Sensitivity Evaluation Confidence

Dependencies

• Dependence on sensitive habitat types

o Rocky intertidal 

o Rocky reef

o Kelp forest

• Dependence on specific prey or forage species

• Other dependencies

o The allee effect

• Generalist or specialist?

Overall: 4 Moderate-High

• 4 Moderate-High

• 2 Low-Moderate 

• 5 High 

• 3 (Both generalist and specialist 

characteristics)

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High 

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Harvest

• Pollution and poisons 

• Invasive and other problematic species

Overall: 3 Moderate

• 5 High 

• 3 Moderate 

• 2 Low-Moderate

Overall: 1 Low

• 3 High 

• 1 Low

• 1 Low

Non-Climate Stressors – Current Exposure to Stressor

• Harvest

• Pollution and poisons 

• Invasive and other problematic species

Overall: 2 Low-Moderate Overall: 3 High

• 3 High 

• 2 Moderate 

• 3 High 

LOCAL

• 5 High 

• 3 Moderate 

• 1 Low

REGIONAL

• 3 Moderate 

• 1 Low

• 1 Low

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 4 Moderate-High

Overall Averaged Confidence (Sensitivity)4: 3 High

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

440
ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 3 (Diminished but generally stable) 2 Moderate

Population Connectivity 2 (Somewhat isolated and/or fragmented) 3 High

Dispersal Ability 1 Low 3 High

Maximum Annual Dispersal Distance 5-25 km 2 Moderate

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity 

Overall: 2 Low-Moderate

• 3 Moderate 

• Not Answered

• 2 Low-Moderate 

• 1 Low

Overall: 3 High

• 2 Moderate

• Not Answered

• 2 Moderate 

• 3 High 

Species Value 5 High 3 High

Likelihood of Managing or Alleviating Climate Impacts 3 Moderate 2 Moderate

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 3 High 

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in sea surface temperature

• Decreased pH

• Decreased dissolved oxygen

• Changes in air temperature

• Changes in salinity

• Sea level rise

• Changes in precipitation

Overall: 3 Moderate

• 1 Low

• 5 High 

• 3 Moderate 

• 5 High 

• 1 Low

• 5 High 

• 1 Low

Overall: 3 High

• 2 Moderate 

• 3 High 

• 2 Moderate 

• 3 High 

• 3 High 

• 3 High 

• 3 High

441
 Overall Averaged Ranking (Exposure)3

: 3 Moderate

 Overall Averaged Confidence (Exposure)4: 3 High

442
Sea Palm – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 4 Moderate-High Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Air temperature

• Sea surface temperature

• Precipitation

• Salinity

• Oxygen 

• pH 

• Sea level rise

• Wave action

• Dynamic ocean conditions 

(currents/mixing/stratification) 

• Coastal erosion

Overall: Moderate-High

• 5 High 

• 3 Moderate 

• 2 Low-Moderate 

• 5 High 

• 2 Low-Moderate 

• 4 Moderate-High

• 3 Moderate 

• 5 High 

• 3 Moderate 

• 4 Moderate-High 

Overall: 2 Moderate

• 3 High 

• 1 Low

• 1 Low

• 2 Moderate 

• 1 Low

• 1 Low

• 2 Moderate 

• 3 High 

• 1 Low

• 1 Low

Disturbance Regimes

• Wind 

• Disease

• Storms

• Flooding 

• Extreme heat events

Overall: 5 High Overall: 2 Moderate

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

443
Sensitivity Factor Sensitivity Evaluation Confidence

Dependencies

• Dependence on sensitive habitat types

o Coralline algae turfs

• Dependence on specific prey or forage species

• Other dependencies

o Wave disturbance to remove competitors 

• Generalist or specialist?

Overall: 4 Moderate-High

• 3 Moderate 

• 1 Low

• 5 High 

• 5 (Specialist)

Overall: 3 High

• 2 Moderate 

• 3 High 

• 3 High 

• 3 High

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Harvest

Overall: 5 High

• 5 High

Overall: 3 High

• 3 High

Non-Climate Stressors – Current Exposure to Stressor

• Harvest

Overall: 2 Low-Moderate Overall: 1 Low

• 1 Low

LOCAL

• 3 Moderate 

REGIONAL

• 1 Low

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 4 Moderate-High

Overall Averaged Confidence (Sensitivity)4: 3 High 

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 5 (Healthy and/or expanding) 3 High

Population Connectivity 2 (Somewhat isolated and/or fragmented) 3 High

Dispersal Ability 2 Low-Moderate 3 High

Maximum Annual Dispersal Distance <1km, >100km 3 High

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

444
Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 3 Moderate

• 4 Moderate-High

• Not Answered

• 1 Low

• 3 Moderate

Overall: 2 Moderate

• 3 High 

• 1 Low

• 2 Moderate 

• 3 High

Species Value 2 Low-Moderate 2 Moderate

Likelihood of Managing or Alleviating Climate Impacts 2 Low-Moderate 1 Low

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 3 High 

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in air temperature

• Changes in precipitation

• Changes in salinity

• Altered currents and mixing

• Changes in sea surface temperature

• Coastal erosion and runoff 

• Decreased pH

• Increased flooding 

• Sea level rise

• Increased storminess

• Decreased dissolved oxygen

Overall: 4 Moderate-High

• 5 High 

• 5 High 

• 5 High 

• 4 Moderate-High

• 5 High 

• 2 Low-Moderate 

• 5 High 

• 3 Moderate 

• 5 High 

• 3 Moderate 

• 2 Low-Moderate

Overall: 2 Moderate

• 3 High 

• 3 High 

• 2 Moderate 

• 1 Low

• 2 Moderate 

• 2 Moderate 

• 3 High 

• 2 Moderate 

• 3 High 

• 2 Moderate 

• 1 Low

Overall Averaged Ranking (Exposure)3: 4 Moderate-High

Overall Averaged Confidence (Exposure)4: 2 Moderate 

445
Sea Urchin, Red and Purple – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 2 Moderate

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Air temperature

• Sea surface temperature

• Oxygen 

• pH 

• Dynamic ocean conditions 

(currents/mixing/stratification)

Overall: 4 Moderate-High

• 4 Moderate-High

• 3 Moderate 

• 4 Moderate-High

• 4 Moderate-High

• 4 Moderate-High

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

Disturbance Regimes

• Disease

• Storms

Overall: 4 Moderate-High Overall: 3 High

Dependencies

• Dependence on sensitive habitat types

o Rocky reef

o Rocky intertidal 

o Kelp forest

• Dependence on specific prey or forage species

o Algae

• Other dependencies: none identified

• Generalist or specialist?

Overall: 3 Moderate

• 5 High 

• 1 Low

• N/A

• 2 (Mostly generalist)

Overall: 3 High

• 3 High 

• 3 High 

• N/A

• 3 High 

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Harvest

• Pollution and poisons

Overall: 4 Moderate-High

• 3 Moderate 

• 5 High

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate

Non-Climate Stressors – Current Exposure to Stressor Overall: 3 Moderate Overall: 2 Moderate

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

446
Sensitivity Factor Sensitivity Evaluation Confidence

• Harvest

• Pollution and poisons 

LOCAL

• 4 Moderate-High

• 4 Moderate-High

REGIONAL

• 1 Low

• 1 Low

• 2 Moderate 

• 2 Moderate 

Other Sensitivities

• Trophic relationships with predators 

Overall: 4 Moderate-High Overall: 2 Moderate

Overall Averaged Ranking (Sensitivity)3: 3 Moderate

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 4 (Stable population at abundant levels) 1 Low

Population Connectivity 5 (Continuous) 2 Moderate

Dispersal Ability 5 High 3 High

Maximum Annual Dispersal Distance >100 km 3 High

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 2 Low-Moderate

• 1 Low

• 5 High 

• 2 Low-Moderate 

• 1 Low

Overall: 3 High

• 3 High 

• 2 Moderate 

• 3 High 

• 3 High

Species Value 4 Moderate-High 3 High

Likelihood of Managing or Alleviating Climate Impacts 1 Low 2 Moderate

Other Adaptive Capacities

• Bottleneck during larval settlement

• Climate effects on recruitment success and larval 

survival

Overall: 4 Moderate-High Overall: 1 Low

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

447
Overall Averaged Ranking (Adaptive Capacity)3

: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 3 High 

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in air temperature

• Changes in sea surface temperature

• Decreased pH

• Decreased dissolved oxygen

• Increased storminess

• Altered currents and mixing

Overall: 2 Low-Moderate

• 2 Low-Moderate 

• 1 Low

• 4 Moderate-High

• 4 Moderate-High

• 2 Low-Moderate

• 1 Low

Overall: 2 Moderate

• 3 High 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 1 Low 

• 1 Low

Overall Averaged Ranking (Exposure)3: 2 Low-Moderate

Overall Averaged Confidence (Exposure)4: 2 Moderate

448
Southern Sea Otter – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 2 Moderate

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Sea surface temperature

• Precipitation

• Salinity

• Oxygen 

• pH 

• Wave action

• Dynamic ocean conditions 

(currents/mixing/stratification) 

• Coastal erosion

Overall: 2 Low-Moderate

• 1 Low

• 4 Moderate-High

• 1 Low

• 2 Low-Moderate 

• 4 Moderate-High

• 3 Moderate 

• 2 Low-Moderate

• 2 Low-Moderate

Overall: 2 Moderate

• 3 High 

• 2 Moderate 

• 1 Low

• 2 Moderate 

• 3 High 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate

Disturbance Regimes

• Wind 

• Disease

• Storms

Overall: 3 Moderate

• 2 Low-Moderate 

• 5 High 

• 3 Moderate

Overall: 2 Moderate

• 1 Low

• 3 High 

• 2 Moderate

Dependencies

• Dependence on sensitive habitat types

o Kelp

o Estuaries

o Nearshore

• Dependence on specific prey or forage species

• Other dependencies: none identified

• Generalist or specialist?

Overall: 2 Low-Moderate

• 4 Moderate-High

• 2 Low-Moderate 

• 5 High 

• 1 Low

• N/A 

• 2 (Mostly generalist)

Overall: 3 High

• 3 High 

• 2 Moderate 

• 3 High 

• 3 High 

• N/A

• 3 High 

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

449
Sensitivity Factor Sensitivity Evaluation Confidence

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Predation

• Pollution and poisons 

• Harvest

Overall: 4 Moderate-High

• 2 Low-Moderate 

• 5 High 

• 2 Low-Moderate

Overall: 1 Low

• 1 Low

• 3 High 

• 1 Low

Non-Climate Stressors – Current Exposure to Stressor

• Predation

• Pollution and poisons 

• Harvest

Overall: 2 Low-Moderate Overall: 2 Moderate

• 3 High 

• 2 Moderate 

• 1 Low

LOCAL

• 4 Moderate-High

• 2 Low-Moderate

• 1 Low

REGIONAL

• 2 Low-Moderate

• 2 Low-Moderate

• 1 Low

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 2 Low-Moderate

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 3 (Distribution within single state to two 

states)

3 High

Population Status 1 (Endangered) 3 High

Population Connectivity 2 (Somewhat isolated and/or fragmented) 2 Moderate

Dispersal Ability 2 Low-Moderate 3 High

Maximum Annual Dispersal Distance 1-5 km 3 High

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

450
Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 2 Low-Moderate

• 2 Low-Moderate 

• 1 Low

• 4 Moderate-High

• 2 Low-Moderate

Overall: 2 Moderate

• 1 Low

• 3 High 

• 2 Moderate 

• 2 Moderate

Species Value 5 High 3 High

Likelihood of Managing or Alleviating Climate Impacts 2 Low-Moderate 2 Moderate

Other Adaptive Capacities

• Hunting and predation 

• Impacts to key prey

• Ability to migrate north and south along the coast

Overall: 3 Moderate Overall: 1 Low

Overall Averaged Ranking (Adaptive Capacity)3: 2 Low-Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 2 Moderate

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in precipitation

• Decreased pH

• Increased storminess

• Increased coastal erosion and runoff 

Overall: 4 Moderate-High

• 3 Moderate 

• 4 Moderate-High

• 3 Moderate 

• 4 Moderate-High

Overall: 2 Moderate

• 2 Moderate 

• 3 High 

• 2 Moderate 

• 2 Moderate 

Overall Averaged Ranking (Exposure)3: 4 Moderate-High

Overall Averaged Confidence (Exposure)4: 2 Moderate

451
Surface Nesters: Brandt’s Cormorant and Common Murre – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Air temperature

• Sea surface temperature

• Precipitation

• Salinity

• Dissolved oxygen

• pH 

• Sea level rise

• Wave action

• Dynamic ocean conditions 

(currents/mixing/stratification) 

• Coastal erosion

• Extreme weather events

Overall: 2 Low-Moderate

• 2 Low-Moderate

• 3 Moderate 

• 1 Low

• 2 Low-Moderate

• 2 Low-Moderate

• 2 Low-Moderate

• 1 Low

• 1 Low

• 3 Moderate 

• 2 Low-Moderate

• 5 High

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 1 Low

• 1 Low

• 1 Low

• 3 High 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 3 High

Disturbance Regimes

• Disease

• Storms

• Flooding 

• Drought 

• Disturbance

Overall: 5 High Overall: 3 High

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

452
Sensitivity Factor Sensitivity Evaluation Confidence

Dependencies

• Dependence on sensitive habitat types

o Breeding habitat

o Foraging habitat 

• Dependence on specific prey or forage species

• Other dependencies

o Timing of breeding 

o Foraging availability

• Generalist or specialist?

Overall: 4 Moderate-High

• 5 High 

• 3 Moderate 

• 3 Moderate 

• 5 High 

• 3 (Both generalist and specialist 

characteristics)

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Land use change 

• Pollution and poisons 

• Harvest

• Energy production 

• Recreation

• Invasive species

• Aircraft and vessels

Overall: 4 Moderate-High

• 2 Low-Moderate

• 5 High 

• 3 Moderate 

• 2 Low-Moderate

• 4 Moderate-High

• 5 High 

• 5 High

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High

Non-Climate Stressors – Current Exposure to Stressor

• Land use change 

• Pollution and poisons 

• Harvest

• Energy production 

• Recreation

• Invasives

• Aircraft/vessels

Overall: 1 Low Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High 

• 3 High

LOCAL

• 2 LowModerate

• 2 LowModerate

• 1 Low

• 1 Low

• 2 LowModerate

• 1 Low

• 3 Moderate

REGIONAL

• 1 Low

• 2 Moderate 

• 1 Low

• 1 Low

• 1 Low

• 1 Low

• 2 Moderate

453
Sensitivity Factor Sensitivity Evaluation Confidence

Other Sensitivities

• El Niño

Overall: 4 Moderate-High Overall: 3 High

Overall Averaged Ranking (Sensitivity)3: 4 Moderate-High

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status

o Brandt’s Cormorant 

o Common Murre 

3 (Diminished but generally stable)

5 (Healthy and/or expanding) 

3 High 

3 High 

Population Connectivity 4 (Almost continuous) 2 Moderate

Dispersal Ability 3 Moderate 2 Moderate

Maximum Annual Dispersal Distance >100 km 3 High

Intraspecific/Life History Diversity

• Diversity of life history strategies

o Brandt’s Cormorant 

o Common Murre 

• Genetic diversity

o Brandt’s Cormorant 

o Common Murre 

• Behavioral plasticity

o Brandt’s Cormorant 

o Common Murre 

• Phenotypic plasticity 

o Brandt’s Cormorant 

o Common Murre 

Overall: 3 Moderate

• 4 Moderate-High

• 2 Low-Moderate

• 3 Moderate 

• 3 Moderate 

• 3 Moderate 

• 2 Low-Moderate

• 3 Moderate 

• 2 Low-Moderate

Overall: 2 Moderate

• 3 High 

• 3 High 

• 1 Low

• 1 Low

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

454
Species Value 2 Low-Moderate 3 High

Likelihood of Managing or Alleviating Climate Impacts 1 Low 3 High

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 3 High 

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in air temperature

• Changes in precipitation

• Changes in salinity 

• Altered currents and mixing

• Changes in sea surface temperature

• Increased coastal erosion & runoff

• Decreased pH

• Increased flooding 

• Decreased dissolved oxygen

• Sea level rise

• Increased storminess

Overall: 3 Moderate

• 3 Moderate 

• 2 Low-Moderate

• 3 Moderate 

• 4 Moderate-High

• 3 Moderate 

• 2 Low-Moderate

• 3 Moderate 

• 2 Low-Moderate

• 3 Moderate 

• 1 Low

• 3 Moderate 

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

• 2 Moderate 

Overall Averaged Ranking (Exposure)3: 3 Moderate

Overall Averaged Confidence (Exposure)4: 2 Moderate

455
Tidewater Goby – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 2 Moderate

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Precipitation

• pH 

• Sea level rise

• Coastal erosion

Overall: 2 Low-Moderate

• 4 Moderate-High

• 2 Low-Moderate 

• 2 Low-Moderate 

• 2 Low-Moderate 

Overall: 1 Low

• 2 Moderate 

• 1 Low

• 1 Low

• 1 Low

Disturbance Regimes

• Flooding

Overall: 4 Moderate-High Overall: 3 High

Dependencies

• Dependence on sensitive habitat types

o Brackish water (Coastal Lagoons and 

Upstream in creek/river systems) 

• Dependence on specific prey or forage species

• Other dependencies

o Clear water for breeding

o Oxygenated sandy substrate for burrow 

o Nearby populations 

• Generalist or specialist?

Overall: 3 Moderate

• 5 High 

• 2 Low-Moderate 

• 3 Moderate 

• 2 (Mostly generalist)

Overall: 3 High

• 3 High 

• 2 Moderate 

• Not Answered

• 2 Moderate

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Land use change 

• Invasive and other problematic species

Overall: 2 Low-Moderate

• 3 Moderate 

• 2 Low-Moderate

Overall: 1 Low

• 2 Moderate 

• 1 Low

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

456
Sensitivity Factor Sensitivity Evaluation Confidence

Non-Climate Stressors – Current Exposure to Stressor

• Land use change 

• Invasive and other problematic species

Not Answered Not Answered

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 3 Moderate

Overall Averaged Confidence (Sensitivity)4: 2 Moderate

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 1 (Endemic) 3 High

Population Status 1 (Endangered) 3 High

Population Connectivity 2 (Somewhat isolated and/or fragmented, i.e. 

patchy)

2 Moderate

Dispersal Ability 1 Low 2 Moderate

Maximum Annual Dispersal Distance 5-25 km, documented up to 15 km 2 Moderate

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 2 Low-Moderate

• 1 Low

• 5 High 

• 1 Low

• 2 Low-Moderate

Not Answered

Species Value 3 Moderate 2 Moderate

Likelihood of Managing or Alleviating Climate Impacts 3 Moderate 2 Moderate

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 2 Low-Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 3 High 

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

457
EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in precipitation

• Increased flooding 

Overall: 3 Moderate

• 3 Moderate 

• 3 Moderate

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate

Overall Averaged Ranking (Exposure)3: 3 Moderate

Overall Averaged Confidence (Exposure)4: 2 Moderate

458
Western Snowy Plover – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 4 Moderate-High Overall Confidence2: 2 Moderate

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Changes

• Precipitation

• pH 

• Sea level rise

• Wave action

• Coastal erosion

Overall: 4 Moderate-High

• 2 Low-Moderate 

• 1 Low

• 5 High 

• 5 High 

• 5 High 

Overall: 2 Moderate

• 1 Low

• 1 Low

• 3 High 

• 3 High 

• 3 High 

Disturbance Regimes

• Wind 

• Storms

• Flooding

Overall: 5 High Overall: 3 High

Dependencies

• Dependence on sensitive habitat types

o Gravel bars

o Salt pans

• Dependence on specific prey or forage species

• Other dependencies: none identified

• Generalist or specialist?

Overall: 3 Moderate

• 4 Moderate-High

• 1 Low

• N/A

• 4 (Mostly specialist)

Overall: 2 Moderate

• 2 Moderate 

• 2 Moderate 

• N/A

• 2 Moderate 

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Recreation

• Invasive and other problematic species

• Land use change 

• Pollution and poisons

Overall: 5 High

• 5 High 

• 4 Moderate-High

• 5 High

• 5 High

Overall: 3 High

• 3 High 

• 3 High 

• 3 High 

• 3 High

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

459
Sensitivity Factor Sensitivity Evaluation Confidence

Non-Climate Stressors – Current Exposure to Stressor

• Recreation

• Invasive and other problematic species

• Land use change 

• Pollution and poisons 

Overall: 4 Moderate-High Overall: 3 High

• 3 High 

• 3 High 

• 2 Moderate 

• 3 High 

LOCAL

• 5 High 

• 5 High 

• 5 High 

• 5 High 

REGIONAL

• 4 Moderate-High

• 4 Moderate-High

• 4 Moderate-High

• 1 Low

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 4 Moderate-High

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Geographic Extent 5 (Transcontinental) 3 High

Population Status 2 (Threatened) 3 High

Population Connectivity 3 (Patchy across an area with some 

connectivity among patches)

2 Moderate

Dispersal Ability 5 High 3 High

Maximum Annual Dispersal Distance >100 km 3 High

Intraspecific/Life History Diversity

• Diversity of life history strategies

• Genetic diversity

• Behavioral plasticity

• Phenotypic plasticity

Overall: 2 Low-Moderate

• 3 Moderate 

• 2 Low-Moderate 

• 2 Low-Moderate 

• 2 Low-Moderate

Overall: 1 Low

• 2 Moderate 

• 2 Moderate 

• 1 Low

• 1 Low

Species Value 2 Low-Moderate 2 Moderate

Likelihood of Managing or Alleviating Climate Impacts 2 Low-Moderate 3 High

Other Adaptive Capacities: none identified N/A N/A

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, or exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

460
Overall Averaged Ranking (Adaptive Capacity)3

: 3 Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 2 Moderate

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Changes in precipitation

• Increased coastal erosion and runoff 

• Increased flooding 

• Sea level rise

• Increased storminess

• Decreased pH

• Decreased sediment supply

Overall: 4 Moderate-High

• 2 Low-Moderate 

• 5 High 

• 5 High 

• 5 High 

• 5 High 

• 2 Low-Moderate 

• 3 Moderate 

Overall: 2 Moderate

• 1 Low

• 3 High 

• 2 Moderate 

• 3 High 

• 3 High 

• 1 Low

• 2 Moderate 

Overall Averaged Ranking (Exposure)3: 4 Moderate-High

Overall Averaged Confidence (Exposure)4: 2 Moderate

461
Carbon Storage and Sequestration – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 4 Moderate-High Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Factors

• Sea level rise

• Storm events 

• Sea surface temperature

Overall: 2 Low-Moderate Overall: 2 Moderate

Disturbance Regimes

• Wind 

• Disease

• Flooding 

• Storms

Overall: 3 Moderate Overall: 2 Moderate

Non-Climate Stressors – Current Exposure to Stressor 

• Land use change 

• Overwater/underwater structures

• Recreation

• Aquaculture 

• Roads/armoring 

• Invasive and other problematic species

• Pollution and poisons 

• Dredging

Overall: 4 Moderate-High Overall: 3 High

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

462
Sensitivity Factor Sensitivity Evaluation Confidence

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Land use change 

• Overwater/underwater structures

• Recreation

• Aquaculture 

• Roads/armoring 

• Invasive and other problematic species

• Pollution and poisons 

• Dredging 

Overall: 3 Moderate Overall: 2 Moderate

Other Sensitivities: none identified N/A N/A

Overall Averaged Ranking (Sensitivity)3: 3 Moderate 

Overall Averaged Confidence (Sensitivity)4: 2 Moderate 

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Service Value 2 Low-Moderate 1 Low

Societal Willingness to Change Behavior 1 Low 3 High

Rigidity/Specificity of Service Management 4 (Rules are specific with some space for 

interpretation)

2 Moderate

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 2 Low-Moderate

Overall Averaged Confidence (Adaptive Capacity)4: 3 High

 

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, and exposure evaluation columns above. 4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

463
EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Sea level rise

• Storms

• Sea surface temperature

• pH 

• Increased erosion

• Precipitation changes (extreme events)

Overall: 5 High Overall: 3 High

Overall Averaged Ranking (Exposure)3: 5 High

Overall Averaged Confidence (Exposure)4: 3 High

464
Flood and Erosion Protection – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 4 Moderate-High Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Factors

• Increased precipitation

• Increased storminess

• Increased coastal erosion

• Increased flooding 

• Sea level rise

• Increased storm events

Overall: 5 High Overall: 3 High

Disturbance Regimes

• Wind 

• Flooding 

• Storms

Overall: 4 Moderate-High Overall: 3 High

Non-Climate Stressors – Current Exposure to Stressor 

• Land use change 

• Overwater/underwater structures

• Roads/armoring 

• Other: sand mining

Overall: 5 High Overall: 3 High

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Land use change

• Overwater/underwater structures

• Roads/armoring 

• Other: sand mining

Overall: 5 High Overall: 3 High

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

465
Sensitivity Factor Sensitivity Evaluation Confidence

Other Sensitivities

• Earthquakes

• Tsunamis

Overall: 5 High Overall: 3 High

Overall Averaged Ranking (Sensitivity)3: 5 High

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Service Value 5 High 3 High

Societal Willingness to Change Behavior 2 Low-Moderate 3 High

Rigidity/Specificity of Service Management 3 (Rules are moderately specific) 2 Moderate

Other Adaptive Capacities

• Habitat migration

Overall: 5 High Overall: 3 High

Overall Averaged Ranking (Adaptive Capacity)3: 4 Moderate-High

Overall Averaged Confidence (Adaptive Capacity)4: 3 High

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Sea surface temperature

• Air temperature

• Sea level rise

• Increased erosion

• Storminess 

• Increased flooding 

• Changes in salinity

Overall: 5 High Overall: 3 High

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, and exposure evaluation columns above.

4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

466
Overall Averaged Ranking (Exposure)3

: 5 High

Overall Averaged Confidence (Exposure)4: 3 High

467
Food Production – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Factors

• Sea surface temperature

• pH 

• Oxygen 

• Currents/mixing/stratification

• Salinity

Overall: 3 Moderate Overall: 2 Moderate

Disturbance Regimes

• Wind 

• Disease

• Storms

Overall: 4 Moderate-High Not Answered

Non-Climate Stressors – Current Exposure to Stressor 

• Recreation

• Aquaculture 

• Harvest

• Pollution and poisons

Overall: 4 Moderate-High Overall: 3 High

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Recreation

• Aquaculture 

• Harvest

• Pollution and poisons

Overall: 4 Moderate-High Overall: 2 Moderate

Other Sensitivities

• Regulatory changes in harvest levels

Overall: 4 Moderate-High Overall: 3 High

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

468
Overall Averaged Ranking (Sensitivity)3

: 4 Moderate-High

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Service Value 5 High 3 High

Societal Willingness to Change Behavior 2 Low-Moderate 2 Moderate

Rigidity/Specificity of Service Management 5 (Rules are very specific) 3 High

Other Adaptive Capacities

• World fishery demand reduction 

• Increase sustainable aquaculture

• Habitat protections

Overall: 3 Moderate Overall: 2 Moderate

Overall Averaged Ranking (Adaptive Capacity)3: 4 Moderate-High

Overall Averaged Confidence (Adaptive Capacity)4: 3 High

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Sea surface temperature

• pH 

• Oxygen 

• Currents/mixing/stratification

• Salinity

• Wind/storms

Overall: 4 Moderate-High Overall: 2 Moderate

Overall Averaged Ranking (Exposure)3: 4 Moderate-High

Overall Averaged Confidence (Exposure)4: 2 Moderate

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, and exposure evaluation columns above.

4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

469
Recreation and Tourism – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Factors

• Warmer inland temperatures

• Increased wave height

• Increased storminess

• Sea surface temperature

• Increased wind 

• Sea level rise

Overall: 2 Low-Moderate Overall: 3 High

Disturbance Regimes

• Wind 

• Disease

• Flooding 

• Storms

Overall: 4 Moderate-High Overall: 2 Moderate

Non-Climate Stressors – Current Exposure to Stressor 

• Land use change 

• Aquaculture 

• Harvest

• Pollution and poisons

Overall: 2 Low-Moderate Overall: 2 Moderate

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Land use change 

• Aquaculture 

• Harvest

• Pollution and poisons

Overall: 4 Moderate-High Overall: 3 High

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

470
Sensitivity Factor Sensitivity Evaluation Confidence

Other Sensitivities

• Population density

Overall: 4 Moderate-High Overall: 3 High

Overall Averaged Ranking (Sensitivity)3: 3 Moderate 

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Service Value 5 High 3 High

Societal Willingness to Change Behavior 4 Moderate-High 2 Moderate

Rigidity/Specificity of Service Management 3 (Rules are moderately specific) 3 High

Other Adaptive Capacities

• Education of the public

Overall: 5 High Overall: 2 Moderate

Overall Averaged Ranking (Adaptive Capacity)3: 5 High

Overall Averaged Confidence (Adaptive Capacity)4: 3 High

EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Warmer inland temperatures

• Increased wave height

• Increased storminess

• Sea surface temperature

• Increased wind 

• Sea level rise

Overall: 4 Moderate-High Overall: 3 High

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, and exposure evaluation columns above.

4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

471
Overall Averaged Ranking (Exposure)3

: 4 Moderate-High

Overall Averaged Confidence (Exposure)4: 3 High

472
Water Purification – Overview of Vulnerability Component Evaluations 

Overall Vulnerability Ranking1: 3 Moderate Overall Confidence2: 3 High

SENSITIVITY

Sensitivity Factor Sensitivity Evaluation Confidence

Sensitivities to Climate & Climate-Driven Factors

• pH 

• Sea level rise

• Precipitation

• Dissolved oxygen

• Turbidity

• Storm activity

• Coastal erosion (wave action) 

• Circulation

Overall: 5 High Overall: 3 High

Disturbance Regimes

• Wind 

• Flooding 

• Storms

Overall: 5 High Overall: 3 High

Non-Climate Stressors – Current Exposure to Stressor 

• Land use change 

• Recreation

• Aquaculture 

• Harvest

• Pollution and poisons 

• Dredging 

• Other: shipping

Overall: 3 Moderate Overall: 2 Moderate

1 Overall vulnerability is calculated according to the following formula: Vulnerability = Sensitivity * (0.5*Exposure) * (1/Adaptive Capacity). 2 Overall confidence is an average of the overall averaged confidences for sensitivity, exposure, and adaptive capacity.

473
Sensitivity Factor Sensitivity Evaluation Confidence

Non-Climate Stressors – Degree Stressor Affects 

Sensitivity

• Land use change 

• Recreation

• Aquaculture 

• Harvest

• Pollution and poisons 

• Dredging 

• Other: shipping

Overall: 4 Moderate-High Overall: 2 Moderate

Other Sensitivities

• Desalination brine 

• Agricultural land use

• Dredging practices

Overall: 2 Low-Moderate Overall: 2 Moderate

Overall Averaged Ranking (Sensitivity)3: 4 Moderate-High

Overall Averaged Confidence (Sensitivity)4: 3 High

ADAPTIVE CAPACITY

Adaptive Capacity Factor Adaptive Capacity Evaluation Confidence

Service Value 5 High 3 High

Societal Willingness to Change Behavior 3 Moderate 2 Moderate

Rigidity/Specificity of Service Management 4 (Rules are specific with some space for 

interpretation)

2 Moderate

Other Adaptive Capacities: none identified N/A N/A

Overall Averaged Ranking (Adaptive Capacity)3: 4 Moderate-High

Overall Averaged Confidence (Adaptive Capacity)4: 3 High

 

3 Overall averaged ranking is an average of the sensitivity, adaptive capacity, and exposure evaluation columns above.

4 Overall averaged confidence is an average of the confidence column for sensitivity, adaptive capacity, or exposure.

474
EXPOSURE

Exposure Factor Exposure Evaluation Confidence

Future Climate Exposure Factors

• Sea temperature

• pH 

• Sea level rise

• Precipitation

• Dissolved oxygen

• Turbidity

• Storm activity

• Coastal erosion (wave action) 

• Circulation

Overall: 4 Moderate-High Overall: 3 High

Overall Averaged Ranking (Exposure)3: 4 Moderate-High

Overall Averaged Confidence (Exposure)4: 3 High

475