Accounting for Shifting Distributions and 

Changing Productivity in the Fishery 

Management Process: From Detection to 

Management Action 

Melissa A. Karp, Jay Peterson, Patrick D. Lynch, and Roger Griffis (editors) 

Charles Adams, Bill Arnold, Lewis Barnett, Yvonne deReynier, Jane 

DiCosimo, Kari Fenske, Sarah Gaichas, Anne Hollowed, Kirstin Holsman, 

Mandy Karnauskas, Donald Kobayashi, Andrew Leising, John Manderson, 

Michelle McClure, Wendy Morrison, Erin Schnettler, Andrew Thompson, Jim 

Thorson, John Walter, Annie Yau, Richard Methot, and Jason Link (contributors) 

U.S. Department of Commerce 

National Oceanic and Atmospheric Administration 

National Marine Fisheries Service 

NOAA Technical Memorandum NMFS-F/SPO-188

November 2018

Accounting for Shifting Distributions and Changing 

Productivity in the Fishery Management Process: 

From Detection to Management Action 

Melissa A. Karp, Jay Peterson, Patrick D. Lynch, and Roger Griffis (editors) 

Charles Adams, Bill Arnold, Lewis Barnett, Yvonne deReynier, Jane 

DiCosimo, Kari Fenske, Sarah Gaichas, Anne Hollowed, Kirstin Holsman, 

Mandy Karnauskas, Donald Kobayashi, Andrew Leising, John Manderson, 

Michelle McClure, Wendy Morrison, Erin Schnettler, Andrew Thompson, Jim 

Thorson, John Walter, Annie Yau, Richard Methot, and Jason Link (contributors) 

NOAA Technical Memorandum NMFS-F/SPO-188

November 2018

U.S. Department of Commerce

Wilbur L. Ross, Jr., Secretary 

National Oceanic and Atmospheric Administration 

RDML Tim Gallaudet, Ph.D., USN Ret., Acting NOAA Administrator 

National Marine Fisheries Service 

Chris Oliver, Assistant Administrator for Fisheries 
ii

Recommended citation: 

Karp, M. A., J. Peterson, P. D. Lynch, and R. Griffis (editors). Accounting for Shifting Distributions and Changing Productivity in the Fishery Management Process: From Detection to Management Action. 2018. U.S. Dept. of Commerce, NOAA. NOAA Technical Memorandum 

NMFS-F/SPO-188, 37 p. 

Copies of this report may be obtained from: 

Office of Science and Technology 

National Oceanic and Atmospheric Administration

1315 East-West Highway, F/ST

Silver Spring, MD 20910

Or online at: 

http://spo.nmfs.noaa.gov/tech-memos
iii

Contents

Executive Summary ......................................................................................................................................v

Acknowledgments.......................................................................................................................................vii

1.0 Introduction.............................................................................................................................................1

2.0 Climate Effects on Fish and Fisheries.....................................................................................................3

2.1 Shifting Distributions ........................................................................................................................3

2.2 Changing Productivity.......................................................................................................................4

3.0 Six Step Process: Challenges and Recommendations.............................................................................6

3.1 Detect and Anticipate Changes..........................................................................................................9

3.2 Understand Key Drivers of Changes.................................................................................................9

3.3 Evaluate Priorities and Risks........................................................................................................... 11

3.4 Conduct Assessments and Develop Forecasts................................................................................. 13

3.5 Communicate Scientific Advice to Management ............................................................................ 16

3.6 Manage Fisheries Under Changing Conditions............................................................................... 18

4.0 Conclusions........................................................................................................................................... 22

5.0 References............................................................................................................................................. 23

6.0 Appendix............................................................................................................................................... 27

A. Flexible survey design, Pacific sardine off the west coast of North America ................................. 27

B. Yellowfin sole (Limanda aspera) – “time-varying q” and “regime shift” ...................................... 28

C. Butterfish (Peprilus triacanthus) – thermal habitat availability...................................................... 29

D. Southern New England-Mid Atlantic yellowtail flounder (Limanda ferruginea) – cold pools and 

stock-recruitment relationship ......................................................................................................... 30

E. Quantifying risk from a change in ocean conditions: red-tide episodic event................................. 32

F. Alaska Climate Change Integrated Modeling (ACLIM) project..................................................... 33

G. Using comprehensive risk assessment to prioritize limited resources............................................. 35

H. Case study references...................................................................................................................... 36
iv

List of Figures 

Figure 1: Climate-ready fisheries management process ............................................................2

Figure 2: Conceptualization of interaction between the type of stock distributional change and changes to 

actual and apparent stock size ..........................................................................................4

Figure A1: Illustration of the multiple models and climate and fishing scenarios in the ACLIM project..33

List of Tables

Table 1: Recommendations and potential actions to increase capacity to detect and anticipate changes ....8

Table 2: Recommendations and potential actions to improve understanding of key drivers of change ....10

Table 3: Recommendations and potential actions to improve evaluations of risks and priorities ...........12

Table 4: Recommendations and potential actions to strengthen assessment and forecasting capabilities..15

Table 5: Recommendations and potential actions to improve communication of scientific advice on shifting distributions and changing productivity ........................................................................18

Table 6: Recommendations and potential actions to improve management of fisheries under changing 

conditions ...............................................................................................................21
v

Executive Summary 

Strong legislative mandates and investments in 

scientific programs have made the United States a 

world leader in sustainable fisheries management 

for seafood production, economic growth and outdoor recreation opportunities. NOAA Fisheries 

conducts targeted surveys, monitoring and research 

critical to tracking and understanding the physical, 

biological, and socio-economic conditions affecting fish stocks and fisheries. This information is essential for fisheries management and is used 

throughout the science-to-management process. 

However, changing climate and ocean conditions 

present new and growing challenges that affect the 

ability to understand and effectively manage fish 

stocks and fisheries. This report identifies the major challenges and possible solutions to addressing 

two of the main effects of changing climate and 

ocean conditions: shifts in stock distributions, and 

changing stock and ecosystem productivity. 

Shifts in stock distributions and/or stock and 

ecosystem productivity can have significant implications for effective fisheries management. Traditionally a stock’s life history parameters are assumed to be stationary, or constant, through time, 

and accurate estimates of these life history parameters are fundamental to establishing effective biological reference points. Changes in productivity 

can manifest through habitat alterations thereby affecting life history parameters, including growth, 

maturation rate, natural mortality, and stock-recruitment relationships. When productivity or distribution changes, the traditional assumption of stationarity is violated, with attendant implications for 

estimates of spawning stock biomass, biological 

reference points (e.g., maximum sustainable yield), 

and ultimately management actions, such as harvest 

recommendations and allocation decisions. Distributional shifts in response to changing climate and 

ocean conditions (e.g., temperature, habitat loss) 

can also alter the effectiveness of other management actions, such as time and area closures or bycatch reduction measures, as stocks may move out 

of designated protected areas and interact with different species and fishing gears. 

In recognition of the numerous challenges facing fisheries management under changing climate 

and ocean conditions, NOAA fisheries has called 

for increasing the production, delivery, and use of 

climate and environmental information to fulfill the 

agency’s living marine resource stewardship mandates. Addressing the growing challenges posed by 

changing conditions, and more formally including 

climate-informed decision making in the U.S. fisheries management process will require strengthening and adapting the current fisheries management 

framework, from improving detection and projection of changes, to better communication and use of 

climate-related information by resource managers. 

Incorporating climate-related information throughout the science-to-management process will help 

promote effective fisheries management in the face 

of current and projected changes in U.S. marine 

ecosystems. 

This effort identifies six key steps (detailed in 

the following table) in the science-to-management 

process needed to better account for and respond to 

climate impacts on fisheries. The report identifies 

the main challenges and limitations associated with 

each step, and provides corresponding recommendations to address these issues. Implementation of 

these steps and recommendations will increase the 

development and application of climate-related science to support sustainable fisheries management in 

a changing world. The steps and actions recommended are not prioritized, nor were resource requirements or specific timelines identified. The capacity to implement these recommendations varies 

by region, and some initial efforts are already underway in some areas. Regional discussions and 
vi

planning are warranted to identify priority actions

and determine how to implement these steps and 

recommendations. The six-step process and associated actions should be reviewed in each region to 

determine a feasible implementation scale given 

current knowledge and resources. This report is an 

important step towards implementing and integrating key national strategies and fulfilling NOAA 

Fisheries’ mission mandates in the face of changing 

climate and ocean conditions.

 Step Recommendations

1. Detect and anticipate changes

 Expand the spatial and temporal coverage of surveys and monitoring efforts through facilitating 

adaptive and flexible surveys, leveraging capacity of fishermen and other stakeholders, and expanding use of advanced sampling technologies

 Develop early warnings and indicators of change

 Facilitate coordination across jurisdictional boundaries to improve the integration of data streams 

and ability to track changes

2. Understand key 

drivers of change

 Design data collection and experimental approaches that evaluate fishery and survey catchability 

and selectivity in relation to ambient environmental and habitat conditions

 Direct more research towards process studies to examine and understand key drivers of stock dynamics

 Identify and address personnel and training needs to establish the staff capacity needed to address 

research needs

3. Evaluate risks and 

priorities 

 Identify and prioritize the species and regions that are at greatest risk from current and future climate change using Climate Vulnerability and Risk Assessments

 Use spatial analysis techniques and sensitivity analysis to identify and evaluate the relative importance and magnitude of distribution shifts and changes in productivity

4. Conduct assessments and develop forecasts

 Ensure that an ecosystem consideration component is included in the Terms of Reference for conducting and reviewing stock assessments

 Incorporate spatial, temporal, multispecies, and economic data into stock assessment and other analyses where appropriate

 Evaluate predictive skill associated with catch recommendations and other forecasts, and incorporate skill metrics into the characterization of uncertainty associated with scientific advice

 Entertain multiple hypotheses regarding mechanisms and drivers of change through use of multimodel approaches (e.g., ensemble modeling) when competing hypotheses cannot be reconciled

5. Communicate scientific advice 

 Develop standardized templates to report information on ecosystem dynamics, species distributions, 

and productivity to fishery managers 

 Facilitate communication among scientists, managers, and fisheries stakeholder groups through regular and open dialogue at workshops and/or debriefs to share and discuss issues and recommendations related to climate impacts on fisheries

 Include decision support tools in stock assessment reports to quantify and present tradeoffs, risks, 

and uncertainties associated with various plausible management scenarios and states of nature

6. Manage fisheries 

under changing 

conditions 

 Consider population resilience, age structure, and genetic diversity when making management decisions 

 Plan for future scenarios by using results from risk assessments and examining candidate management procedures using structured scenario planning, holistic ecosystem models, and/or Management 

Strategy Evaluation (MSE)

 Use distribution analyses and projections to plan in advance for emerging fisheries

 Evaluate time and area closures, adjusting where needed to reflect current and predicted distributions and habitat needs of managed stocks

 Develop harvest control rules that are responsive to, and account for, changing conditions
vii

Acknowledgments 

We would like to thank the Incorporating Climate and Ecosystem Information in Fisheries Management 

(ICE-FM) working group members for all their contributions to this work. We also would like to thank 

Kenric Osgood, Stephen Brown, Karyl Brewster-Geisz, and Jennifer Cudney for their constructive feedback on earlier versions of the document. 

1

1.0 Introduction 

Strong legislative mandates and investments in 

scientific programs have made the United States a 

world leader in sustainable fisheries management 

for seafood production, economic growth and outdoor recreation opportunities. NOAA Fisheries 

conducts targeted surveys, monitoring and research 

critical to tracking and understanding the physical, 

biological, and socio-economic conditions affecting fish stocks and fisheries management. However, changing climate and ocean conditions present a new and growing challenge affecting the ability of NOAA Fisheries and its management partners

to understand and manage for the effects of the 

physical environment on fish stocks and fisheries

(Figure 1).

In 2015, the NOAA Fisheries Climate Science 

Strategy (NCSS; Link et al. (eds.) 2015, Busch et 

al. 2016) was released to help increase the production, delivery, and use of climate-related information required to fulfill its mandates. Following 

this, the U.S. Government Accountability Office 

(GAO)1 worked with NOAA Fisheries to assess the 

agency’s efforts to develop actions the agency 

could take to incorporate climate information into

fishery management decisions. One of the GAO’s 

principal recommendations from that review was 

for NOAA Fisheries to develop guidance on incorporating climate information into the fishery management process. 

In 2016, NOAA Fisheries released its Ecosystem-Based Fisheries Management (EBFM) Road 

Map2(Link et al., 2016) to ensure that NOAA Fisheries and its management partners; assess and account for major pressures affecting living marine 

resources and their habitats in the management pro-

 

1 https://www.gao.gov/products/GAO-16-827

2 https://www.fisheries.noaa.gov/topic/ecosystems#-

science

cess; execute the correct analytical level of assessment; address relevant ecosystem linkages; account

for ecosystem-level features and cumulative impacts; and ensure that the frequency and scope of 

living marine resource assessments align with the 

broader ecosystem and fishing community dynamics. In 2018, NOAA Fisheries released Implementing a Next Generation Stock Assessment Enterprise: An Update to the NOAA Fisheries Stock Assessment Improvement Plan3

(SAIP; Lynch et al.

2018). Building off the EBFM Road Map, the SAIP

emphasizes the development of more holistic and 

ecosystem-linked stock assessments. The priorities 

and directions defined in the NCSS, GAO review, 

EBFM Road Map, and SAIP created the impetus 

for this report.

This report focuses on two effects of changing 

ocean conditions that are particularly challenging 

for fisheries management: shifting species distributions, and changing productivity, at both the stock 

and ecosystem levels (Nye et al. 2009; Lenoir et al. 

2011; Pinsky et al. 2013; Lynch et al. 2015). Both 

shifting species distributions and changing productivity violate traditional stock assessment assumptions of stationarity, and have implications for estimates of spawning biomass, maximum sustainable 

yield, and for harvest recommendations and allocation. Distributional shifts in response to changing 

ocean conditions (e.g. temperature) can also alter 

the effectiveness of management measures, such as 

time and area closures or bycatch reduction 

measures, as species interact with different species 

and gears. Changes in productivity can manifest 

through habitat changes that affect a stock’s life history parameters, including growth, maturation rate, 

natural mortality, and stock-recruitment relationships. Not accounting for changes in a stock’s life 

history parameters can lead to significant error in 

estimates of stock biomass, biological reference 

3 https://www.fisheries.noaa.gov/feature-story/updated-stock-assessment-improvement-plan-buildspast-success
2
3

points, and maximum sustainable yield, which can 

affect not only stock status determinations, but also 

can affect sustainable catch recommendations and 

the achievability of rebuilding plans. Climate effects on species’ distributions and productivity pose 

major challenges to living marine resource management; however, accounting for these effectsin management decisions has remained limited. 

To understand and address these challenges, this 

report evaluates the fisheries management process 

from the capacity to detect and understand changes,

to communicating results to management and subsequent management actions (Figure 1). Recommendations are provided to address identified issues and ultimately increase the development and 

application of climate and ecosystem related science to support sustainable fishery management in 

a changing world. Section 2.0 of this report summarizes the effects of changing climate and ocean conditions on distributions and productivity of living 

marine resources. Section 3.0 describes key challenges and recommended actions under each of the

following six important steps or components of a

science-to-management process that is able to account for and respond to changing conditions:

1. Detect and anticipate changes

2. Understand key drivers of change 

3. Evaluate risks and priorities 

4. Conduct assessments and develop forecasts

5. Communicate scientific advice 

6. Manage fisheries under changing conditions 

Concluding thoughts are provided in Section 4.0, 

and references are provided in Section 5.0. An appendix provides case studies that illustrate how climate effects are being addressed in the fishery management process around the country. 

2.0 Climate Effects

on Fish and Fisheries

The potential effects of changing climate and 

ocean conditions are growing concerns for fishermen, managers, and coastal communities who rely 

on marine resources for food and economic security. The potential effects include increasing water 

temperature, ocean acidification, changes in atmospheric and ocean circulation, and more frequent and 

stronger weather events, and subsequent shifts in 

species distribution and productivity (IPCC 2014; 

The Royal Society 2005; Diaz and Rosenberg 2008; 

Hoegh-Guldberg et al. 2014; FAO 2016; Barange 

et al. 2010). The Intergovernmental Panel on Climate Change reported in 2014, there is “high confidence” that recent regional changes in ocean temperature have already had a “discernible impact” on 

some marine ecosystems and fisheries. Ocean temperatures are expected to increase an additional 2-

4

oC by the end of the century, increasing the effects

to fish stocks and fisheries (Hoegh-Guldberg et al. 

2014; IPCC 2014; Poloczanska et al. 2016). 

2.1 Shifting Distributions

A distribution shift refers to a permanent, or at 

least multi-decadal to centennial, shift in the spatial 

distribution of a species or stock from its traditional 

region or habitat, to a new region or habitat. These 

shifts are often considered a result of changing climate or ocean conditions; although other factors 

(e.g., fishing, habitat degradation, trophic dynamics) may also cause shifts in distribution. Such 

shifts violate traditional assumptions of stationarity

common to fish stock assessments, with attendant 

implications for estimates of spawning stock biomass, biological reference points, and ultimately 

harvest recommendations and allocation. Stocks 

are already on the move in response to oceanographic (e.g. temperature) and ecosystem (e.g. habitat loss, trophic dynamics) conditions (Nye et al. 

2009; Lenoir et al. 2011; Pinsky et al. 2013; Bell et 
4

al. 2014; Lynch et al. 2015; Poloczanka et al. 2016), 

highlighting the importance of this issue. 

How a distribution shift affects fish stock and 

resultant management actions depends on the type 

of shift that has occurred. Link et al. (2011) described the various scenarios of how stock distributions may respond to changing ocean conditions,

and the different effects those scenarios have on 

management advice. Two main effects on stocks 

are that the apparent stock size within a given area 

may be quite different from the actual stock size, 

and stock structure may change (Figure 2). Both situations can lead to misspecification of stock status. 

For example, if a stock shifts northward across defined stock boundaries, there would be an apparent 

decline in abundance in the area that it is leaving, 

and an apparent increase in abundance in the area 

to which it is moving, while the true stock abundance may remain constant. If a stock is moving 

into an area in which it was not previously found, 

there is a risk that a fishery may develop in the new 

area before an appropriate monitoring program and 

fishery management plan can be implemented 

(Link et al. 2011). 

Shifting species distributions also will have consequences for access to the fish, particularly when 

stocks shift across management jurisdictions (state, 

federal, or international). Thus, such shifts may 

have direct economic impacts on fishing communities (see Box 1: Shifting Distributions and the Allocation of Fishing Rights). Additionally, management tools, such as catch limits, time or spatial closures, may lose their effectiveness as species shift 

in or out of those regions. Interactions, both between species and with fishing gear, may change as 

a result of distribution shifts, which could affect the 

performance of bycatch reduction measures. Additionally, The Magnuson-Stevens Act, which governs federal fishery management in the U.S., states 

in its National Standard 3 that “to the extent practicable, an individual stock of fish shall be managed 

as a single unit throughout its range, and interrelated stocks of fish shall be managed as a unit or in 

close coordination”. Geographic shifts in distribution may therefore result in fundamental changes to 

the structure of regional fishery management Council’s fishery management plans, and perhaps to the 

Councils themselves. At a minimum such shifts will 

require increased cross-jurisdictional coordination 

to manage stocks as they shift, expand, or contract 

their ranges. 

2.2 Changing Productivity

Figure 2: Conceptualization of interaction between the type 

of stock distributional change and changes to actual and

apparent stock size. Each of the 8 vertical sets of 3-panels 

depicts the type of movement of a stock or stocks across an 

assumed stock boundary (horizontal black line, top panel), 

the actual stock size (middle panel), and the apparent stock 

size (bottom panel) Figure adapted from Link et al. 2011.
5

Productivity in a fisheries context refers to the 

total biomass of fish, or the amount of yield, that a 

stock can support for removal (i.e., by fishing). Climate, ocean, and ecosystem conditions can greatly 

affect fish stock productivity by affecting habitat 

suitability, ecosystem-level productivity and dynamics (e.g., predator-prey interactions), and a 

stock’s life history parameters, such as growth, 

maturation rate, natural mortality, and stock-recruitment relationships (Hare et al. 2010; Farley et 

al. 2016). For example, the recruitment of many 

cold-water and temperate species in the northwest 

Atlantic have been linked to the dynamics of the 

mid-Atlantic cold pool (Houghton et al. 1982, Miller et al. 2016). Warmer than average winter ocean 

temperatures cause Atlantic croaker recruitment to 

be higher than average (Hare et al. 2010), while Atlantic cod and Yellowtail flounder recruitment (Appendix D) is lower (Fogarty et al. 2008). These 

changes may occur concurrently with a stock’s distribution shift, but also may affect stocks that remain within their historical ranges.

When stock productivity changes, it directly affects the assessment and management process. Errors in estimated life history parameters can lead to 

significant differences in inferred stock productivity (Whitten et al. 2013; Audzijonyte et al. 2016) 

and biological reference points, including estimation of the maximum sustainable yield (MSY). The 

effects of changing climate and ocean conditions on 

stock productivity affects the management utility of 

biological reference points, which are linked to historic conditions. In recognition of environmental 

(climate and ocean) effects on productivity, the national standard guidelines of the MSA states that “if 

environmental changes affect the long-term productive capacity of the stock or stock complex, one 

 Allocation is defined by NOAA Fisheries as “a direct and deliberate distribution of the opportunity to 

participate in a fishery among identifiable, discrete 

user groups or individuals” (50 CFR 600.325; Morrison and Scott 2014). Allocation of fishery resources is 

one of the most challenging issues faced by fishery 

managers because of the economic value, history, and 

tradition associated with access to fishery resources 

and the perceptions of fairness that arise with allocation decisions. Allocation can be across jurisdictions 

(international, state, regional, etc.), across sectors 

(commercial, recreational, tribal, research, etc.), and 

within sectors (individual fishermen, gear types, etc.). 

To date, a large percentage of allocation decisions (80 

percent of commercial/recreational allocations and 89 

percent of catch share allocations) within the U.S. are 

based entirely or partially on

In 2016, NOAA Fisheries created an Allocation 

Policy to provide a mechanism to ensure that fisheries 

allocations are periodically evaluated and remain relevant to current conditions. The Policy defines roles 

and responsibilities for NOAA Fisheries and the eight 

regional fishery management Councils in reviewing allocations. The policy’s first procedural directive outlines three categories that may trigger a Council to initiate an allocation review: public interest, time, or indicators. The Councils plan to identify one or more triggers for each fishery with an allocation by August 

2019 (or as soon as practicable). The policy’s second 

procedural directive outlines recommended practices 

and factors to consider when reviewing and updating 

allocations, and includes sections on planning for future conditions and on considering if the distribution of 

the species has changed.

BOX 1

SHIFTING DISTRIBUTIONS AND THE ALLOCATION OF FISHING 

RIGHTS
6

or more components of the status determination criteria must be respecified.”

Changes in stock productivity may also affect 

the achievability of rebuilding plans if biological 

targets are no longer feasible under current or future 

conditions. Similar to the effect of shifting distributions, changing productivity may be unidirectional, 

so the affected stock would not be expected to return to its original state (as is expected with climate 

change). In other cases, productivity changes could 

occur in cycles that last for years to decades before 

shifting back to a previous productivity regime (as 

has been the case with decadal-scale climate and 

oceanographic oscillations). Therefore, NOAA 

Fisheries has developed, and should continue to improve, methods to detect and monitor for productivity changes, and evaluate whether biological reference points, status determination criteria, and harvest control rules reflect a stock’s current productivity regime and are responsive and robust to 

changing conditions. 

3.0 Six Step Process: 

Challenges and 

Recommendations 

This section goes through each of the six general 

steps involved in a climate-informed science-tomanagement system: (1) detect and anticipate

changes, (2) understand key drivers of changes, (3) 

evaluate risks and priorities, (4) conduct assessments and develop forecasts, (5) communicate advice to managers and stakeholders, and (6) manage 

fisheries under changing conditions. For each step 

the major challenges to accounting for shifting distributions and changing productivity are identified, 

followed by a description of recommendations to 

address those challenges. Recommendations and 

potential actions are summarized in a table at the 

end of each step’s section. Addressing the challenges at each step in the process will strengthen

NOAA Fisheries’ ability to account for and respond 

to changing climate and ocean conditions in the sustainable management of living marine resources. 

Given regional variability in the capacity to implement this process, and the fact that some efforts are 

already underway in some regions, the steps themselves are not prioritized. Regional planning groups 

should walk through each step and associated recommendations, evaluate current knowledge, and 

determine when, where and how these steps can be 

implemented to facilitate a more “climate-informed” science-to-management system. 

3.1 Detect and Anticipate Changes 

For U.S. fisheries management to effectively address species distribution shifts and changing 

productivity, scientists and managers need to be 

able to: determine that a change has occurred in the 

past; detect that a change is currently occurring; and

predict that a change is likely to occur in the near 

future. A crucial component of detecting changes is

tracking and monitoring shifts in oceanographic

conditions and stock characteristics in real-time. 

However, tracking changes and collecting data at 

the temporal and spatial scales necessary to provide 

real-time data and early warnings that a change may 

occur is challenging under current monitoring capacity. 

NOAA Fisheries typically relies on fishery-independent and fishery-dependent sources to collect 

data and monitor changes in oceanographic and biological variables. For stock abundance monitoring, survey and catch rate data are often standardized over space and time (e.g., conducted within the 

same region and season) to the historic range of the 

species or to a jurisdictional domain. Historically, 

standardized sampling and analysis results in reduced sampling bias and facilitates spatial and temporal comparisons, yet standardization may introduce error and/or bias if changes in physical and 

oceanographic features affect stock distributions or 

life history parameters. Additionally, many of the 
7

geostatistical techniques underlying spatial models 

rely on extensive and accurate spatial data (Berger 

et al. 2017), increasing the need for data collection 

programs that accurately capture the spatial structure and movements of stocks and coinciding ecosystem information.

Movement of stocks across survey or jurisdictional borders poses an additional challenge for detecting changes in a stock’s distribution or productivity. Surveys are not always consistent in design, 

timing, or gear type across jurisdictions. Survey inconsistency across regions can complicate the determination that productivity has changed, versus a 

species has shifted in or out of a region. It also 

makes it challenging to quantify the magnitude of 

changes in distribution or productivity. In fact, differences in survey design and methodology used to 

detect changes can have significant effects on the 

observed variability in the magnitude of stock distribution shifts in response to climate change 

(Brown et al. 2016).

Improvements and expansions in data collection, monitoring, and data-sharing programs are 

needed to develop early warnings and indicators 

that would help increase NOAA’s capacity to detect 

changes when they occur and anticipate changes 

before they occur. Inevitably, these improvements 

will need to be prioritized and phased-in accordingly. Recommended actions to increase NOAA 

Fisheries’ capacity to detect changes are described 

below and summarized in Table 1. 

Recommendations

 Develop early warnings and indicators of 

change using ecosystem or stock attributes 

that are relatively easy to track

Important variables for tracking changing oceanographic conditions may include temperature, dissolved oxygen, pH, salinity, stratification, sea surface height, and circulation patterns. These variables are likely to change with changing climatic 

conditions and are potential drivers of fish stock dynamics. Other attributes that are important to monitor include catch histories and composition, centers

of biomass, dispersion, guild or trophic structure, 

stock structure and connectivity, growth and sizeat-age, and recruitment patterns (Rec 1.1, Table 1). 

Additionally, changes in habitat suitability may 

cause stocks to shift out of and into new regions;

therefore, monitoring changes in important habitats 

(e.g. essential fish habitats) may serve as potential 

indicators and early warnings of change. A first step 

toward providing indicators of change is to analyze 

existing data for changes in the above mentioned 

attributes which could signal that a potential shift in 

distribution or productivity has occurred. Analysts 

can use and communicate this information to managers to provide initial indication that a change in 

the system has occurred.

 Expand the spatial and temporal coverage of 

surveys.

The SAIP (Lynch et al. 2018) recommends adjusting monitoring programs to track changes in 

species distributions, a recommendation reiterated 

here (Rec 1.2, Table 1). Facilitating survey flexibility and adaptability could greatly improve the detection and tracking of distribution shifts and 

changes in productivity, and ensure that the complete range of a stock is adequately sampled. Identifying how and when to adjust surveys should involve evaluating current survey domains and designs, particularly their relative abilities to detect 

changes and distinguish among changes in distributions, productivity, and abundance. Adapting surveys could involve both adjusting surveys in response to changing species behavior (e.g., Pacific 

sardine surveys, Appendix A) and expanding the 

spatial and temporal scope of surveys, which may 

be both a cost- and time-prohibitive endeavor in 

some regions. Therefore, the use of fishery catch 

data, citizen science, local ecological knowledge, 

and partnerships with fishermen should be encouraged to help expand the monitoring capacity of 
8

NOAA Fisheries and provide information to help 

inform decisions to adjust surveys.

 Use integrated ocean observing systems and 

advanced sampling technologies

NOAA recently developed the Integrated Ocean 

Observing System (IOOS)4, a national-regional 

partnership to maximize access to real-time data, 

generate information products, and improve habitat, ecosystem, and climate understanding. Fisheries monitoring and assessment teams could benefit 

from increasing coordination and use of the real-

 

4 https://ioos.noaa.gov/about/

time data collected through this observing system. 

This system could provide information needed to 

track large scale oceanographic conditions and indicators of change at temporal and spatial scales not 

adequately captured by traditional fishery-independent surveys (see Manderson et al. 2011; Kohut 

et al. 2012). Increased use of advanced sampling 

technologies, such as sail drones and autonomous 

vehicles, can also help expand the collection of fish 

stock and oceanographic data. 

 Facilitate coordination across jurisdictional 

boundaries. 

TABLE 1 

RECOMMENDATIONS AND POTENTIAL ACTIONS TO INCREASE CAPACITY TO DETECT AND ANTICIPATE CHANGES 

Recommendation Potential Actions

1.1 Develop indicators and early 

warning signs 

Utilize indicators and early warnings to 

detect and predict when stocks are exhibiting or may exhibit distribution or 

productivity changes

 Analyze survey and fishery catch data for changes in guild/trophic structure, 

species composition, location of catch, growth (e.g. catch-at-age), and recruitment patterns

 Monitor changes in habitats and ecosystems through dedicated and opportunistic collection of oceanographic variables such as pH, dissolved oxygen, 

temperature, salinity, and bottom type 

 Evaluate the scale and rate of stock structure changes and spatial patterns in 

recruitment on a regular basis through tagging studies and genetic analysis 

1.2 Expand spatial and temporal coverage of monitoring efforts 

Monitoring programs and surveys 

should be adjusted to track changes 

and reflect the current distribution and 

behavior of the stock 

 Facilitate survey adaptability and flexibility 

 Engage and leverage the capacity of fishermen and other stakeholders, and 

use “citizen science” data collected by stakeholders and fishermen to inform 

monitoring programs

 Use Ecosystem Status Reports to inform fish stock monitoring and assessments (e.g. to evaluate sampling designs and identify key stressors)

1.3 Use integrative ocean observing 

systems and advanced sampling technologies 

 Increase the use of real-time data collected through the Integrated Ocean Observing System (IOOS) to help track large scale oceanographic conditions 

and indicators of change

 Use and continue to develop advanced sampling technologies, such as sailing

drones and autonomous vehicles 

1.4 Facilitate coordination across jurisdictional boundaries

Research and survey efforts should be 

coordinated across regions and jurisdictions to facilitate integrating data 

streams and improve the ability to 

track changes

 Evaluate ongoing surveys to prioritize intercalibration work and standardization of surveys across adjacent regions

 Improve data-sharing through creation of publically available, machinereadable data warehousing that is compatible across NOAA regions and 

among data collection partners
9

Improving the coordination of research and survey efforts across regions and jurisdictions, including improved data-sharing across neighboring regions would improve each region’s ability to track

changes, as well as increase managers’ awareness

of the changes occurring in their, and neighboring,

jurisdictions (Rec. 1.3, Table 1). However, this relies on having good communication and sharing of 

information between managers and scientists both 

within and between jurisdictions (see Section 3.5 

for specific recommendations on improving communication). This information will be crucial for 

managers as they plan for future conditions and 

emerging fisheries (see Section 3.6)

3.2 Understand Key Drivers of Change

Not only is it important to identify that a change 

has occurred, but understanding the cause of the observed change is also key. For instance, an observed 

change in distribution or productivity could be related to a variety of factors, singly or in combination. These factors include natural variability in the 

system, changes in fishing practices, changing 

trophic dynamics and abundance of predators or 

prey, stock rebuilding plans, long-term environmental change, or some combination of drivers.

The driving factors will affect how managers 

should respond. 

Furthermore, understanding the underlying 

mechanisms of distributional and productivity 

changes may improve scientific advice and the ability to predict and develop forecasts of expected 

changes. For example, when stocks shift their distributions or movement patterns as a result of 

changing growth rates and/or oceanographic conditions, there can be resultant effects on the ‘availability’ (catchability, selectivity, sampling efficiency, etc.) of fish stocks to surveys or fisheries. 

This availability is important to quantify in stock 

assessments as it affects estimates of total abundance, productivity, and subsequently stock status 

and sustainable catch levels. Accounting for environmentally-driven and time-varying catchability 

and selectivity is therefore important, yet remains 

difficult due to limited mechanistic understanding.

Even when necessary data are available to provide information on key drivers of change, the time 

and personnel required to process and analyze these 

data can be a limiting factor. There are often an insufficient number of experts trained to work with 

the data, especially with regard to the zooplankton, 

secondary production, and food habits data that are 

useful for understanding changing stock and system 

productivity. The lack of trained personnel needed 

to process and work with the data in a timely manner can lead to a mismatch or lag between data collection and processing, resulting in not using the information in assessments to inform management 

decisions.

Therefore, increasing the collection of data (as

noted in the previous section), process-oriented research efforts, and staff capacity are crucial to inform mechanistic understanding of observed 

changes. Recommendations to improve NOAA 

Fisheries understanding of key drivers of change 

are described below and summarized in Table 2, 

with some additional specific potential actions. 

Recommendations

 Institute collection of oceanographic, habitat, 

and multispecies information on all standard 

surveys.

Collecting oceanographic, ecosystem, and habitat 

data concurrently with stock’s biological information can provide indicators and early warnings 

of change as mentioned in section 3.1. Better coordination of data collection can also improve scientists’ ability to determine potential drivers of 

change by matching up climate, ocean, and habitat 

conditions with resultant changes in stock dynamics.

Collecting multispecies and trophic information 

may help determine how different stocks respond to 
10

system-level changes. Some species may respond 

more strongly to changes in temperature while others respond more to changes in prey composition or 

habitat availability. Therefore, collecting a range of 

ecosystem data will provide necessary information 

to understand and evaluate various potential drivers 

of change (Rec 2.1, Table 2). 

 Evaluate stock availability to survey and fishing gear.

Data collection and experimental approaches 

should be designed to estimate catchability, availability, and selectivity in relation to ambient environmental and habitat conditions (Rec. 2.2, Table 2). 

Ways to evaluate these changes include paired 

acoustic-trawl surveys and video surveys of fish behavior around survey gear in concert with collecting environmental (habitat and oceanographic) information. Paired acoustic-trawl surveys can provide information on changes in vertical distribution 

of fish while enhanced sampling of fish behavior 

TABLE 2

RECOMMENDATIONS AND POTENTIAL ACTIONS TO IMPROVE UNDERSTANDING OF KEY DRIVERS OF CHANGE

Recommendation Potential Actions

2.1 Institute collection of oceanographic, ecosystem, and habitat information on all standard surveys.

Ensure that appropriate ecological observations are collected on all standard surveys, and where opportunities 

exist, to enable direct linkage between 

species and environmental information

 Measure oceanographic variables, such as dissolved oxygen, temperature, 

salinity, and depth as standard procedure on surveys

 Use acoustics and side-scan sonar to assess bottom and habitat type and 

zooplankton density

 Use satellite and on-board sampling to collect information on primary 

productivity

 Collect multi-species information, as a matter of sampling efficiency, but 

also to understand trophic dynamics

2.2 Evaluate stock availability to survey and fishing gears

Design data collection and experimental approaches to estimate catchability, selectivity, and efficiency in 

relation to ambient environmental 

and habitat conditions

 Invest in process-oriented projects to characterize changes in catchability, selectivity, and gear efficiency and understand relationships between 

those changes and oceanographic conditions

 Conduct paired acoustic-trawl sampling to estimate changes in vertical 

distribution

2.3 Identify key drivers of stock dynamics

Conduct interdisciplinary process-oriented research that integrates across 

the physical, biological, and socioeconomic disciplines

 Conduct experiments to evaluate environmental effects on organisms’ vital rates (i.e., growth, mortality, reproduction, etc.)

 Establish and maintain ageing programs and food habits labs in all regions

2.4 Identify and address personnel 

and training needs

Optimize staff capacity to address 

growing information challenges and 

needs

 Increase opportunities for scientific staff to receive training in topics such 

as plankton identification, gonad processing, genetic analysis, and diet 

analysis

 Adjust staff performance plans to include dedicated time for interacting 

with and developing analysis and reports for fisheries managers, and conducting mechanistic research, stock structure studies, and catchability 

and calibration experiments
11

around survey gear would allow for improved understanding of how fish behavior and interactions

with survey gear may change in response to changing environmental conditions. 

 Identify key drivers of stock dynamics.

Process-oriented research on the effects of changing environmental conditions, particularly temperature, on organism vital rates such as growth, mortality, larval survival, maturity, fecundity and recruitment is important across all regions (see Stawitz et al. 2015, Boldt et al. 2015, Thorson et al. 

2015b) (Rec 2.3, Table 2). Determining optimal 

management action under changing stock dynamics

is contingent on a stock’s life history (Thorson et al. 

2015b, Barbeaux and Hollowed 2017); therefore, 

analysis of factors affecting a stock’s vital rates 

throughout its life cycle should be prioritized to understand changes in productivity. Ageing programs 

and food habits labs are important for conducting 

much of this process research and should be supported in each region. 

 Identify and address personnel and training 

needs. 

Identifying and addressing personnel and training 

needs is essential to increasing staff capacity to confront the growing challenges facing fisheries management in a changing environment (Rec. 2.4, Table 2). Staff should be given opportunities and encouraged to: take training courses on topics such as 

plankton identification, gonad processing, and genetic analysis; interact with fisheries managers; and 

conduct research aimed at improving mechanistic 

understanding of changes.

3.3 Evaluate Priorities and Risks 

Not all observed changes warrant a response in 

the science-to-management process. Ideally the decision to expand a stock assessment to include climate and ecosystem information, and/or to take 

management action, will consider the degree of 

change observed, the degree to which a stock is 

likely to respond (e.g., the stock’s vulnerability to 

changing conditions), the relative importance of the 

stock, and if accounting for the change is likely to 

improve conservation and management overall. 

Recommended actions to help NOAA Fisheries 

evaluate risk and prioritize species for ecosystem 

considerations are provided below and corresponding specific potential actions are summarized in Table 3. 

Recommendations

 Evaluate the magnitude and relative importance of observed changes in distribution 

and productivity.

The development and use of spatial-temporal 

models for fishery survey data has been increasing 

in the United States. These statistical techniques facilitate evaluation of changes in a stock’s spatial 

distribution and incorporate spatial processes in 

stock assessments (e.g., Thorson et al. 2015a, 2016, 

Thorson and Wetzel 2015, Ianelli et al. 2016, Thorson and Barnett 2017). Assessment scientists 

should capitalize on advancements in geospatial 

statistics to help identify and evaluate the significance of distribution shifts and spatial changes in 

catch rates (Rec. 3.1, Table 3). Significant changes 

in either or both would provide support for including these factors in further analyses. 

Sensitivity analysis is another useful tool that can 

help determine when shifting distributions or 

changing productivity should be accounted for in,

and may improve, assessments and management 

advice. Sensitivity analyses are a routine part of 

stock assessments conducted to determine how 

modeling results are affected by perturbing the assumptions and uncertainties in the model (i.e., how 

“sensitive” is the model to these assumptions).

These analyses can help identify factors that influence stock productivity and distribution, when observed changes in productivity (e.g. growth, mortality, recruitment) or distribution (e.g. catchability) 

have a meaningful effect on the scientific advice, 
12

and when explicitly accounting for the change may 

be warranted. For instance, assessment scientists 

can use sensitivity analyses to answer questions 

such as, what percentage change in growth, recruitment, or size results in a measurable effect on inferred stock size, stock status, or catch advice. Results of these analyses can also inform the development of thresholds and triggers that indicate when 

changes are large enough to warrant a management 

response. 

 Prioritize species at risk. 

The 2018 update to the Stock Assessment Improvement Plan, Implementing a Next Generation 

Stock Assessment Enterprise, proposes a three-step 

process for deciding when and how to expand a 

stock assessment to include climate and ecosystem 

information. The first step involves identifying 

stocks that are highest priority for expanded assessments. This would include, for instance, stocks that 

are most vulnerable to climate or ecosystem impacts. Ecological risk assessments identify major 

threats facing groups of species and their relative 

vulnerabilities to those threats, and can be used to 

help prioritize species for expanded assessments

and/or management action. 

Several different forms of ecological risk assessments exist. Hobday et al. (2011) proposed a hierarchical (tiered) ecological risk assessment approach for looking at the effects of fishing on species and ecosystems. Holsman et al. (2017) expanded this approach to include assessment of risk 

due to any natural or anthropogenic pressure. In the 

tiered approach analysts work through sequential 

steps where species identified as “at risk” in Level 

1 analysis are further considered in Level 2 semiquantitative analysis, and species identified as “medium risk” or “high risk” at Level 2 are further evaluated using quantitative model-based approaches in 

Level 3 assessments. Therefore, the approach allows analysts to focus and prioritize time and resources developing quantitative assessments for 

only those species identified to be most at risk. Additionally, the Level 1 qualitative assessment can 

provide a rapid and computationally inexpensive 

screening tool to identify key pressures that may be 

TABLE 3

RECOMMENDATIONS AND POTENTIAL ACTIONS TO IMPROVE THE EVALUATION OF RISKS AND 

PRIORITIES 

Recommendation Potential Actions

3.1 Evaluate the magnitude and relative importance of distribution shifts 

and changes in productivity 

The magnitude and relative importance of an observed change 

should be evaluated prior to invoking a management response 

 Use spatial analysis techniques to identify and evaluate the magnitude 

and relative importance of distribution shifts as well as spatial changes in 

fishery catch rates

 Use sensitivity analyses to look at how accounting for climate change affects scientific advice and potential management responses

3.2 Prioritize species at risk 

Identify and prioritize the species 

and regions that are at greatest risk 

from current and future changes

 Apply the three-step process described in SAIP (Lynch et al. 2018) to prioritize stocks for ecosystem considerations

 Conduct comprehensive risk assessments and climate vulnerability assessments to inform assessment and management priorities, in addition 

to science and research needs [Appendix G]

 Run Tiered risk assessments (e.g. Hobday et al. 2011; Holsman et al. 

2017; Hare et al. 2016) to rapidly screen potential climate and ecosystem 

effects for hundreds of species and habitats 
13

affecting a wide range of species, habitats, activities, or social components and therefore be prioritized for more in-depth monitoring and analysis 

(Holsman et al. 2017). 

Climate vulnerability assessment, another form 

of ecological risk assessment, is specifically designed to identify and prioritize fish stocks of greatest risk from climate change (Link et al. 2015). Results from these various risk assessment approaches 

can help determine where to focus efforts for inclusion of climate and ecological information into the 

fishery science-to-management process (Rec. 3.2, 

Table 3). 

3.4 Conduct Assessments and 

Develop Forecasts

When there is a clear or anticipated effect of climate, ocean, and ecosystem conditions on fish dynamics, relying on fishing pressure as the sole, dynamic, extrinsic factor affecting fish populations 

may not be an effective management approach

(Keyl and Wolff 2008). However, accounting for 

changing conditions within a stock assessment can 

be quite challenging. Presently, most stock assessment models assume that model parameters (e.g. 

catchability, growth, mortality, recruitment) either 

remain constant over time and/or space, or vary according to random processes. However, climate-induced changes may create sudden shifts in system 

states, or gradual drift in underlying conditions (as 

opposed to variability about a mean value); therefore, assumptions about stationary or randomly varying parameters will be violated. Overall, to better 

account for distribution shifts and changing productivity, external drivers need to be considered in 

stock assessment models, particularly in relation to 

catchability and vital rate parameters. 

Catchability (Q) - Catchability or detectability relates to how susceptible an animal is to being caught or detected by fishing gear, including 

by fisheries and surveys. Surveys, fishery indices, and fishery assessments often assume that 

catchability for each fleet or survey is constant

over time. However, environmental changes are 

likely to alter the probability of capturing or encountering many species, leading to real changes 

in catchability. Not addressing these changes in 

catchability in stock assessment models can result in biased assessment results. Fortunately, 

mechanistic, process-oriented studies that explicitly account for changes in catchability as a 

function of oceanographic conditions are possible and can greatly benefit the assessment process, e.g. yellowfin sole (Appendix B) and butterfish (Appendix C).

Recruitment (R) – Changing temperature, pH, 

dissolved oxygen, and other ocean conditions 

can also have direct effects on production, or the 

number of recruits produced by a given spawning stock size. The mechanisms underlying these 

linkages are complex and involve multiple factors throughout early life history. Considerable 

progress has been made in understanding these 

complex processes through using coupled biophysical hindcast models that track single or 

multiple species through the first year of life 

(Rose et al. 2015). However, identifying how information from coupled models of the early life 

history can be indexed for use in stock assessments remains challenging.

Growth (G) – In addition to recruitment, understanding the rate at which individuals in a 

stock grow is important for estimating a stock’s 

productivity when size- or age-structured stock 

assessments are used. Growth is generally incorporated into stock assessments through the estimation of the relationship between size and age, 

often assumed to be constant through time. 

However, growth rates may change with changing environmental conditions. Bioenergetic 

models provide mechanistic explanations for 

how growth rates change as a function of diet, 
14

temperature, and other factor. These models can 

be valuable for evaluating how changes in 

growth can occur with environmental change 

(Holsman et al 2016). For example, growth rate 

is expected to increase with temperature to a certain point, then decline as temperature becomes 

too warm, leading to decline in aerobic performance (Audzijonyte et al. 2016). 

Natural Mortality (M) - Natural mortality is 

the rate at which fish die due to natural causes, 

i.e., causes other than fishing, and may also be 

affected by changing oceanographic conditions. 

These changes could be due to both episodic 

events, such as harmful algal blooms (Appendix 

E), heat waves, cold spells, and other extreme 

weather events that create short-term spikes or 

drops in mortality, or slower, longer term 

changes in climate and ocean conditions. Additionally, climate may affect the abundance, size, 

or metabolisms of species that interact with the 

focal species, indirectly affecting the natural 

mortality of the focal species. 

Despite the clear influence that oceanographic 

conditions can have on catchability and life history 

parameters, the value of including these effects in 

assessment models is often unclear, primarily because of limited understanding of the underlying 

mechanisms. Thus, the incorporation of ocean, climate, and ecosystem information in assessment 

models used for management advice is uncommon.

As mentioned previously, there are numerous potential negative consequences of not integrating

ocean and ecosystem information in the stock assessment models and/or advice to managers. Assessment scientists should explore ways to increase 

the incorporation of that information in assessments

and forecasts. Recommended actions for scientists 

to move toward that goal are described below and 

corresponding specific potential actions are summarized in Table 4. 

Recommendations

 Include ecosystem considerations in Terms of 

Reference in the stock assessment process.

To formalize the consideration of ecosystem drivers in a stock assessment, both the EBFM Road 

Map and the SAIP recommend that ecosystem considerations be included in stock assessment and assessment reviewer Terms of Reference (Link et al. 

2016; Lynch et al. 2018), a recommendation that is 

re-iterated in this report (Rec 4.1, Table 4). These 

considerations are likely best addressed when improvements to stock assessment methodology are 

being considered (e.g., during “research” or 

“benchmark” assessments). However, there is opportunity to evaluate hypotheses about climate-related effects on fish stocks during routine operational assessments, which may help establish research priorities. 

 Capitalize on advancements in spatiotemporal 

and physical-ecosystem-economic models. 

It has been historically challenging to account for 

shifts in stock distribution or productivity when 

multiple drivers are plausible (e.g., temperature vs 

age-structured dynamics, vs. fishing mortality, e.g., 

Thorson et al. 2017). However, advancements in 

spatiotemporal and spatially explicit models can 

help address this challenge by statistical modeling 

techniques that can test different hypotheses regarding plausible drivers of change in the ecosystem. 

These modeling approaches allow for improved incorporation of spatial, multispecies, and oceanographic dynamics in assessments and should be further explored and developed. 

 Evaluate model diagnostics and the predictive

skill of forecasts. 

Uncertainty in model forecasts can contribute to 

a lack of confidence in results from managers and 

stakeholders, limiting the use of potentially more 

accurate, but less certain, scientific advice. Therefore, there is a need for continued evaluation of the 

degree to which models with environmental and climate linkages are improvements over non-climate 
15

linked models. Practitioners should use various 

model diagnostics, including retrospective and sensitivity analyses, to evaluate the benefits and risks 

of including environmental covariates or time-varying parameters in models. Seasonal to decadal 

scale climate projections can be used to provide updates of predictive skill and inform forecasts formodels with mechanistic environmental linkages at 

scales relevant to fishery management (Tommasi et 

al. 2017). Additionally, regardless of whether environmental variables are included, the evaluation 

and quantification of model predictive skill should 

be a routine part of the stock assessment process.

TABLE 4

RECOMMENDATIONS AND POTENTIAL ACTIONS TO STRENGTHEN ASSESSMENT AND FORECASTING CAPABILITIES 

Recommendation Potential Actions

4.1 Include ecosystem considerations 

in Terms of Reference in the stock 

assessment process

Terminology should be included in 

assessment TOR, assessment reviewer TOR, and there should be an 

expectation that management bodies consider climate effects when developing their catch recommendations

 “Research” or “benchmark” stock assessment TORs should consider including the following text:

“Are there known or hypothesized:

1. Range shifts in the population

2. Changes in survey/fishery catch rates

3. Changes in productivity (e.g. growth, recruitment)

4. Episodic mortality events.”

4.2 Capitalize on advancement in spatial-temporal and physical-ecosystem-economic models

Spatial, oceanographic, multispecies, 

and economic data should be incorporated into stock assessments and 

other analyses where appropriate

 Utilize results from process-oriented research to understand environmental drivers of recruitment and other vital rates

 Develop stock assessment models and test hypotheses related to: (1) including environmental covariates as drivers of catchability and vital

rates, (2) changes to stock identification, characterization, or spatial dimensions, (3) regime shifts and extreme events (e.g., HABs), (4) climatedriven changes in trophic dynamics, and (5) forecast scenarios and prevailing environmental conditions. 

4.3 Evaluate model diagnostics and 

the predictive skill of forecasts

Selection of a final model, or set of 

models, should rely on comparing diagnostics and predictive skill of a 

plausible suite of models, including 

those with environmental linkages 

 Employ probabilistic model evaluation techniques, such as retrospective 

bias analyses, forecast skill metrics for developing forecast ensembles, 

residual analysis to visualize error

 Seasonal to decadal scale climate projections (Tommasi et al. 2017) can 

be used to provide rapid updates of predictive skill for models with environmental linkages, informing assumptions regarding uncertainty 

around longer-term projections

 Results of diagnostic and skill tests should be communicated to managers and stakeholders to document the decision process and to fully characterize uncertainty around the scientific advice

4.4 Develop a suite of plausible hypotheses regarding stock assessment 

models and use multi-model inference when there is not a clear single 

best model

 When conducting research and development of operational models, consider and evaluate multiple hypotheses, including competing hypothesis 

regarding environmental drivers.

 Develop scientific advice using multi-model inference or ensemble modeling techniques when a clear single best approach is not apparent.
16

 Develop a suite of plausible hypotheses regarding stock assessment models and use multimodel inference when there is not a clear single best model.

In cases where processes are not well understood, 

multiple hypotheses should be considered, wherein 

comparative assessments test alternative mechanistic formulations. Comparing diagnostics and predictive skill across a suite of plausible models can 

be helpful to determine which model, or suite of 

models, should form the basis of scientific advice. 

Results of these analyses should then be communicated to managers and stakeholders to document the 

decision process, and the results should be incorporated into the characterization of uncertainty around 

the final advice. Results from multiple models 

could also be potentially synthesized using multimodel and ensemble modeling techniques. Multimodel techniques are a useful tool that may enable 

assessment scientists to more fully evaluate alternative states of nature and mechanistic relationships 

to better characterize the uncertainty in the system 

and resultant forecasts (e.g., Ianelli et al. 2016; 

ACLIM project, Appendix F).

3.5 Communicate Scientific Advice 

to Management 

To facilitate informed management decisions 

that respond to a dynamic and changing environment, scientific information needs to be communicated effectively and efficiently. There are numerous potential negative consequences to making 

management decisions that do not adequately or accurately account for shifts in distributions or 

changes in productivity. However, information on 

shifting distributions and changing productivity is 

often not used in management decisions partially as 

a result of how the information is communicated to 

managers leading to a lack of clarity on when and 

how the information could be used to adjust management actions.

In the U.S., the manner by which ecosystem information is communicated to managers during the 

stock assessment process is not consistent across regions. In some cases, such as with the North Pacific, 

Western Pacific, and Pacific Fishery Management 

Councils (NPFMC, WPFMC, and PFMC, respectively), the information is presented in dedicated 

ecosystem considerations chapters and/or scenarios 

within stock assessment reports. In the Gulf of 

Mexico, New England, and Mid-Atlantic Fishery 

Management Councils (GMFMC, NEFMC, and 

MAFMC, respectively), as well as the PFMC, short 

State of the Ecosystem reports, structured by general management objectives have been presented. 

Stock assessment scientists also present ecosystem 

information to Councils’ Scientific and Statistical 

Committees (SSCs) during some regional SSC 

meetings. The lack of a standardized process or protocol for reporting on the ecosystem, including 

shifting stock distributions and productivity 

changes, hinders the ability to account for these 

changes during the stock assessment process. 

This highlights the need to re-evaluate how climate change and ecosystem information is communicated to managers, and to identify ways to improve the communication and operationalization of 

this information. The goal is to provide evidencebased information in a transparent process in which

management strategies are evaluated and the probable consequences of different management decisions under various states of nature are clearly 

demonstrated. Ensuring that environmental (climate and ecosystem) information, and how it may 

be used, is presented to managers and other stakeholders in a clear and understandable manner is a 

very important step towards this goal. Recommendations to improve the communication of climate 

and ecosystem information to inform management 

decisions are described below and specific potential 

actions are summarized in Table 5. 

Recommendations
17

 Standardize reporting and coordinate among 

ecosystem and stock assessment teams.

Routine reporting and using standardized templates to communicate information on ecosystem 

dynamics, species distributions, and productivity, 

would improve the communication and delivery of 

assessment results to managers (Rec 5.1, Table 5).

As part of this reporting, scientists should provide 

contextual information that changes are occurring 

with either positive or negative implications for 

management. Stock assessment and ecosystem science teams should work together to provide this 

contextual information in a coordinated fashion, 

drawing connections between ecosystem changes

and stock assessments where appropriate and highlighting potential drivers of change. These interdisciplinary teams should work with management 

partners to determine the best format and timing for 

presenting Ecosystem Status Reports and other information to managers. A national initiative is underway to create a generic template that communicates stock-specific ecosystem considerations, referred to as Assessment Profile, Ecosystem Considerations, and Socioeconomics (APECS; Lynch et 

al. 2018). These APECS will provide two-page 

summaries of the important ecosystem and stock 

assessment information, thereby serving as a useful 

tool to improve communication and comparison of 

results across stocks and regions.

 Use decision support tools to communicate assessment advice and associated uncertainties. 

Decision support tools (e.g., decision tables, decision trees) are useful to help communicate uncertainty, tradeoffs, and risks associated with various 

states of nature and management decisions (Rec 

5.2, Table 5; Appendix E). To the extent practicable, decision support tools should be included in assessment reports and provide action-oriented information (i.e., communicate effects of trade-offs regarding metrics decision-makers care about, such 

as catch limits, gear restrictions, time and area closures, all associated with a probabilistic risk of 

overfishing). Results from sensitivity analyses that 

evaluate the level of change that results in measurable effects on a stock (see Section 3.3) can be used 

to inform the decision points and thresholds used in 

decision trees. Additionally, maps of changes in 

current and future projected species distributions, 

as related to management jurisdictions, can be a 

useful decision-support tool. Providing such maps 

during the decision making process can improve 

communication about changes and uncertainties 

around those changes and contribute to more informed decision making. 

 Facilitate communication between scientists 

and managers. 

Communication among scientists, managers, and 

stakeholders should be multidirectional, whereby

all perspectives are heard and participants learn 

from each other. A critical component of this increased communication is regular engagement and 

coordination with managers and their various committees (e.g., Council SSCs, Plan Teams, and Advisory Panels) as well as with fisheries stakeholder 

groups (Rec. 5.3, Table 5). This can be achieved 

through regular and open dialogue at Council meetings, as well as workshops, and debriefs with stock 

and ecosystem assessment scientists. The goals of 

these engagements should include arrival at a clear 

understanding of whether there are action items or 

measures that managers should consider in response to changing systems. Additionally, establishing work teams that include NOAA Fisheries 

scientists who are monitoring and assessing a 

species’ changing distribution and NOAA Fisheries 

management and regulatory staff would help ensure 

that scientists are aware of spatial management programs affecting species, and that managers are 

aware of changing scientific information on stock 

distributions and habitat use. Increased dialogue 

among all parties and a more collaborative and 

transparent decision-making process are important 

in building trust and scientific understanding, especially given the uncertainty and complexity of the 
18

challenges posed by changing climate and ocean 

conditions.

3.6 Manage Fisheries under Changing 

Conditions 

Fisheries managers increasingly face the daunting challenge of determining appropriate responses 

to current and predicted changes in stock distribution and productivity. As discussed in section 2.0, 

changing climate and ocean conditions and the resultant effects on species distributions and productivity can have significant effects on management 

decisions, such as allocation, spatiotemporal closures, stock status determinations, and catch limits. 

For instance, allocation issues can arise as the proportion of a species across regions changes due to 

shifts in its distribution. Basing allocation decisions 

on historical catch rates by region may not be appropriate, especially in the case of emerging fisheries. Both the fishermen who historically had fished 

the species and fishermen in the region into which 

it expanded will want to claim allocation rights. 

Historic fisheries do not want to experience reductions in their allocation, and emerging fisheries 

want a new or increased share of the quota. 

Changing environmental and oceanographic 

conditions can also influence the identification of 

essential fish habitat (EFH) and the effectiveness of 

subsequent spatial management approaches by altering the distribution, spatial extent, and use of 

spawning, migration, and nursery habitats. Federal 

regulations specified in 50 CFR 600.815(a)(10) require that Councils review the EFH provisions of 

their fishery management plans (FMPs) and revise 

TABLE 5

RECOMMENDATIONS AND POTENTIAL ACTIONS TO IMPROVE COMMUNICATION OF SCIENTIFIC 

ADVICE ON SHIFTING DISTRIBUTIONS AND CHANGING PRODUCTIVITY 

Recommendation Potential Actions

5.1 Standardize reporting

Use standardized templates to report information on ecosystem dynamics, species distributions, and 

productivity

 Provide managers with maps of species distributions over time and by 

life stage

 Increase the use of Assessment Profile, Ecosystem Considerations, and 

Socioeconomics (APECS) to summarize key stock assessment advice

 Determine best format and timing for presenting Ecosystem Status Reports to inform management decisions

5.2 Use decision support tools

Quantify and present tradeoffs and 

risks associated with various states 

of nature and management scenarios

 Use decision tables to communicate the probabilistic risk of overfishing 

and other action-oriented information (e.g., fishing scenarios) associated with various states of nature and management scenarios 

 Develop and use decision trees to trigger specific management responses (e.g., if stock A moves X amount, revisit catch allocation procedure)

5.3 Facilitate communication between scientists and management 

partners

Create mechanisms for regular and 

open dialogue between scientists, 

managers, and all fisheries stakeholder groups to support transparent decision-making, and ensure that 

the appropriate data are collected 

and used 

 Conduct workshops where managers, scientists, and stakeholders discuss what information is needed to better inform decisions

 Engage with stakeholders and managers throughout the entire scienceto-management process

 Conduct regular debriefs with interdisciplinary groups (e.g. ecosystem 

teams, Council subcommittees, stock assessment teams) following 

stock assessments to help interpret patterns and develop action items 

and research priorities

 Form work teams between NOAA Fisheries scientists who analyze species distributions and NOAA Fisheries regulatory and management staff 

who implement spatial management programs
19

or amend those provisions as warranted based on 

available information, at least once every 5 years. 

However, this timeframe may be too long to adequately respond to changes. Therefore, regulatory 

regimes that manage through time and area closures 

to protect EFH or prohibit fishing during vulnerable 

parts of a stock’s life history (e.g. spawning and juvenile stages) can see mismatches or lags between 

when change occurs in the water and when management actions can be implemented through the 

Council process.

Catch limits in the U.S. are usually arrived at 

through the use of harvest control rules (HCRs) that 

adjust fishing mortality or catch as a function of 

stock status relative to benchmarks and often provides precautionary buffers to account for associated scientific and management uncertainty (Brunel 

et al. 2010). Stock status determinations and HCRs 

are often developed under the assumption of fixed, 

or stationary, biological reference points over time. 

Many HCRs perform poorly when environmental 

conditions change stock productivity and reference 

points such that the HCR gets incorrect information 

on the true status of the stock or is unresponsive to 

changes (A’mar et al. 2009, Brunel et al. 2010). 

Ideally, management should be prepared to 

quickly respond and adapt to naturally-induced and 

fishery-induced fluctuations to provide appropriate 

decisions on allocations, spatiotemporal closures, 

and catch advice. Strengthening and adapting the 

science enterprise to better detect, understand, assess, and communicate changes in the environment 

(Sections 3.1 – 3.5) inevitably will help managers

determine appropriate courses of action. Some recommended actions for managers to take are described below and summarized in Table 6. 

Recommendations

 Consider population resilience, age structure, 

and genetic diversity when making management decisions.

One of the most basic tools available to help build 

stock resilience to climate change is simply complying with the MSA’s requirement to prevent 

overfishing, prevent stocks from being overfished, 

and rebuild overfished stocks. Since 1996, 44 fish 

stocks have been rebuilt in the United States, benefitting marine ecosystems and fishing communities. 

Managers can also strengthen the adaptive capacity and resilience of stocks by protecting and enhancing the age structure and genetic diversity of a 

population. Genetic adaptation to climate change 

may be necessary, and management should aim to 

increase or preserve current genetic diversity as this 

provides the building blocks needed to adapt to a 

changing environment. Similarly, stocks that have 

maintained their age structure are more resilient to 

environmental change. Large females tend to have 

larger, healthier, and more abundant eggs (Planque 

et al. 2010). Large females also tend to spawn over 

a longer time period and depth gradient (Rouyer et 

al. 2011), and removal of these older fish can result 

in the loss of historical migration and spawning areas (Planque et al. 2010). Thus, removing large females can decrease the variety of conditions experienced by eggs and larvae, reducing the likelihood 

that some eggs and larvae encounter environmental 

conditions beneficial to growth and adaptation.

 Evaluate management action under potential 

future scenarios. 

Managers should be able to proactively explore 

and plan for various future scenarios and evaluate 

the impacts and risks associated with different management actions under those scenarios (Rec 6.1, Table 6). Tools that can aid managers in this endeavor 

include: structured scenario planning, holistic ecosystem models, climate vulnerability and risk assessments, and management strategy evaluations 

(MSEs). 

Structured scenario planning is a strategic planning method used to help visualize how alternative 

plausible futures might emerge, explore potential 

ways to prepare for those alternative futures, and 
20

evaluate how different actions or strategies would 

play out under the different plausible futures. Risk 

assessments and climate vulnerability assessments 

(CVAs; Morrison et al. 2015, Holsman et al. 2017)

previously mentioned in Section 4 of this report can 

be useful tools to inform management actions by 

identifying species and ecosystems at most risk, and 

therefore in need of additional data, analyses, and 

management action (see Section 4 for more detail; 

Holsman et al. 2017). CVAs5are ongoing for finfish and invertebrate species nationwide, and are 

being expanded to address protected species. Managers should call for and use the results of such 

analyses to help prioritize limited resources for future actions [See Appendix G].

MSEs can be used to test the efficacy of various 

alternative management options in achieving predetermined management objectives. These analyses 

can be used to evaluate the robustness of alternative 

strategies under various states of nature (i.e., different climate change scenarios) by including climate 

change signals in developing alternative operating 

models. 

 Plan for emerging fisheries. 

The MSA provides an adaptive tool intended to 

give Councils better notification of, and potentially 

more authority over, emerging fisheries. Section 

305(a) of the MSA requires that each Council develop a list of fisheries and gears used within its geographic area of authority. No person or vessel may 

employ fishing gear or engage in a fishery not included on this list without giving 90 days advance 

written notice to the appropriate Council, or to the 

Secretary of Commerce, where appropriate. This 

MSA provision is intended to give Councils time to 

develop, or ask the Secretary to develop, emergency regulations to address new fisheries as they 

arise to prevent the new fishery from compromising 

the effectiveness of conservation and management 

 

5 https://www.fisheries.noaa.gov/national/climate/climate-vulnerability-assessment

efforts under the MSA. A prudent and rudimentary

management action to address potential movement 

of new species into fishery management areas 

would be for each Council to review and update its 

list of authorized fisheries and gear (Rec 6.2, Table 

6).

When Councils prepare for emerging fisheries, 

they should develop and document a process for

making allocation decisions when stocks change 

their distributions (Rec. 6.2, Table 6). A literature 

review (Morrison and Termini 2016) provides the 

following suggestions. Managers can negotiate prearranged management responses that articulate a set 

of indicators and responses to follow when adjusting allocations (Miller and Munro 2004). For example, allocations could be based on the proportional 

distribution of the stock across regions in a given 

year (Bailey et al. 2013. Additionally, Councils can 

use early warnings and spatial distribution projections to help identify species that may shift across 

jurisdictional boundaries to help prepare for potential emerging fisheries. 

 Evaluate time and area closures. 

Changing ocean and climate conditions may require more responsive and dynamic fisheries management. In dynamic ocean management near realtime biological, oceanographic, social and/or economic data (See section 3.1) are used to evaluate 

and adjust temporal and spatial management actions to better align with changes of the resources 

being managed (Maxwell et al. 2015, Hazen et al. 

2018). The early warnings and indicators of change 

described in section 3.1 and distribution maps described in section 3.5 will be extremely important 

to enable such responsive ocean management. How 

a more dynamic and responsive management system would fit under the current MSA framework 

may need to be evaluated; however, in general, a

combination of traditional and more responsive 
21

TABLE 6

RECOMMENDATIONS AND POTENTIAL ACTIONS TO IMPROVE MANAGEMENT OF FISHERIES 

UNDER CHANGING CONDITIONS

Recommendation Potential Actions 

6.1 Consider population resilience, 

age structure, and genetic diversity 

when making management decisions 

Managers should consider the resilience and adaptive capacity of stocks 

when making management decisions. 

 Continue to comply with MSA’s requirement to prevent overfishing, prevent stocks from being overfished, and rebuild overfished stocks

 Protect and enhance the age structure and genetic diversity of a population 

6.2 Evaluate management actions under potential future scenarios 

Explore and plan for various future 

scenarios and evaluate impacts of different management actions under 

those scenarios

 Conduct structured scenario planning exercises to identify future scenarios and potential management options

 As MSEs are conducted on harvest policies, include scenarios related to 

possible future climate-induced changes in species distributions and 

productivity, and use MSEs for more comprehensive analysis of management scenarios and associated risks and tradeoffs 

 Where possible, evaluate single species catch recommendations (ACLs) 

using a climate-linked ecosystem model (e.g. Atlantis) to assess potential integrated and cumulative impacts of management

6.3 Plan for emerging fisheries

Councils should develop plans for 

how to respond to and coordinate 

with neighboring jurisdictions when 

distributions are shifting across management boundaries

 Evaluate current permitting systems for flexibility to account for shifting distributions and changes in productivity

 Update and provide detailed descriptions of current fisheries and gears 

approved under MSA section 305(a).

 Utilize early warning indicators and coordinate with neighboring jurisdictions to identify species which may shift into our out of a particular 

jurisdiction 

 Develop joint agreements between jurisdictions that describe the response to shifting distributions

6.4 Evaluate time and area closures

Adjust closures to reflect a stock’s 

current range, habitat needs, and phenology

 Use species and habitat distribution maps, and results of habitat suitability models to evaluate effectiveness of current and future conservation area boundaries 

 Use early warnings and indicators of ecosystem change to inform seasonal closures, gear restrictions, or bycatch reduction strategies, etc.

 Facilitate collaboration between scientists and managers to develop 

management grids and spatial metrics that could inform decisions related to allocations, spatial management, and jurisdictions

6.5 Develop adaptive Harvest Control 

Rules

Harvest control rules should be designed to be robust or responsive to 

changing ecosystems

 Design simulation-tested harvest control rules robust to climate-related 

uncertainty by incorporating this uncertainty into the buffer (catch reduction; e.g. P*) used to set catch limits that prevent overfishing

 Develop and use decision trees (ideally through research and simulation) to help determine how, and at what scale, an environmental or 

ecosystem driver should adjust a harvest policy

 Consider empirical management procedure-based harvest control rules 

that rely on simple, attainable, and responsive measures of living marine resource dynamics, particularly where mechanistic understanding 

is lacking
22

management procedures would potentially increase 

the speed and effectiveness of management decisions and their outcomes (Maxwell et al. 2015).

 Develop adaptive and responsive harvest control rules. 

Developing HCRs that account for uncertainty 

and known changes in environmental conditions affecting productivity may increase the successful 

management of fish stocks influenced by environmental forcing (Rec 6.4, Table 6). Examples of 

HCRs that are adaptive or robust to changing conditions could take several forms. One possible approach is for a Council to adjust its risk policy to 

respond to concerns about changing ecosystems in 

determining its acceptable level of risk of overfishing. The benefit of this approach is that it can be 

used in cases in which a climate-induced effect on 

a stock is likely, but underlying mechanisms are not 

yet understood. As an example, if a standard control 

rule allows for a 40% chance of overfishing, then 

for stocks with high climate vulnerability scores, 

perhaps 35% is more appropriate. 

Alternatively, HCRs that operate on empirical 

management procedures, such as indices of abundance, which implicitly and directly account for 

changing productivity may also be useful management considerations. Perhaps the most challenging 

and information intensive method is to explicitly 

estimate regime shifts or dynamic biological reference points, environmentally-driven stock-recruitment relationships, and forecasts that account for

changes in stock or ecosystem productivity. Generally, these mechanistic approaches require relatively long time series of reliable observations to facilitate an acceptable level of prediction skill. They 

may require an FMP amendment, which could take 

up to a year to implement and perhaps another stock 

assessment cycle to conclude.

4.0 Conclusions 

Changing climate and ocean conditions are affecting the Nation’s managed fisheries in ways that 

are not routinely addressed in the science-to-management process. Traditional methods and assumptions used in the fishery management process need 

to be adapted to ensure effective stewardship of living marine resources. This involves addressing the 

challenges and gaps identified in this report – from 

detecting and understanding changes to analyzing 

and communicating results to the relevant decisionmakers. 

There are a variety of opportunities to consider 

and address changing ocean conditions in the science-to-fisheries management process. This report 

identifies six key steps and specific, actionable recommendations for how NOAA Fisheries and its 

partners can better prepare for and address climate 

effects on fish stocks and fisheries. The recommendations and related actions are intended to be applied broadly to support the full range of fishery 

management decisions in each region. However,

resource and other limitations may require assessing how best to implement the recommendations in each region. NOAA Fisheries should partner with Councils and regional stakeholders to 

identify the most effective approach for implementing these recommendations in their region. This paper includes general recommendations and proposed actions to facilitate those discussions.

Faced with shifting species distributions and 

changing productivity, NOAA Fisheries, Councils 

and Interstate Commissions should explore future 

scenarios, plan for emerging fisheries, re-evaluate 

their spatial and temporal management procedures 

and develop responsive harvest control rules. Ultimately, all management approaches that account 

for changes in the environment as they occur depend on data collected from survey and monitoring 

efforts and process-oriented research. It is im-
23

portant that basic agency activities adapt to changing data needs to differentiate between changes in 

abundance and shifts in distribution or productivity. 

Opportunities exist to make better use of the current 

data collections, as well as to efficiently expand 

data collection through standardizing the type and 

frequency of data collected on existing surveys to 

allow better comparison across jurisdictions. Other 

key opportunities include leveraging the capacity of 

fishermen and citizen science programs, operationalizing advanced sampling technologies that can 

collect information at appropriate temporal and spatial scales, and using electronic technologies to 

more efficiently collect fishery-dependent data. 

Each step in the science-to-management process 

benefits from close collaboration and communication among scientists, managers, and stakeholders. 

Regularly scheduled workshops, debriefs, meetings, or other mechanisms to allow open dialogue 

and engagement between scientists and managers,

are essential for effective communication and collaboration. For instance, developing processes that 

allow scientists to provide timely information on 

ecosystem dynamics and species distributions to 

appropriate Council bodies can be important to inform management decisions. Regular meetings

would also provide scientists with feedback from 

managers to help prioritize the types of analyses 

and evaluations that would be most beneficial to 

sustainable fisheries management. 

The recommendations identified in this report, if 

enacted at appropriate regional and national levels, 

will better equip NOAA Fisheries to prepare for and 

respond to changing climate and ocean conditions, 

and thereby improving stewardship of the nation’s 

living marine resources.

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pollock in the Bering Sea. Fish and Fisheries, 8(6): 

1073–1084. https://doi.org/0.1111/faf.12225

Tommasi, D., Stock, C. A., Pegion, K., Vecchi, G. A., 

Methot, R. D., Alexander, M. A., and Checkley, D.

M. 2017. Improved management of small pelagic 

fisheries through seasonal climate prediction. Ecological Applications, 27(2), 378-388, 

https://doi.org/10.1002/eap.1458

Whitten, A. R., Klaer, N. L., Tuck, G. N., and Day, R.

W. 2013. Accounting for cohort-specific variable 

growth in fisheries stock assessments: a case study 

from south-eastern Australia. Fisheries Research,

142, 27–36.
27

6.0 Appendix 

A. Flexible survey design, Pacific sardine off the west coast of North America

Pacific sardine (Sardinops sagax) are an important component of the coastal pelagic species (CPS) assemblage off the west coasts of Vancouver Island, Canada, the United States, and Baja California, Mexico. Sardine have a high caloric value per gram, tend to be preferred forage of many higher trophic level 

animals, and can greatly affect the reproductive success of predators (e.g., sea lions, McClatchie et al. 

2016). Due to their high nutritional content, sardine are also economically valuable and harvested in the 3 

countries primarily as a reduction fishery. 

Sardine abundance varies massively at decadal scales (Zwolinski and Demer 2012). Sardine were very 

abundant in the 1930’s and 1940’s, but crashed in the 1950’s to near non-detection levels decimating the 

economies of many coastal towns. Sardine abundances resurged in the 1980’s and 1990’s, and harvest resumed in the U.S. and Canada in the 1990s. Stock sizes declined in recent years and the commercial directed fishery was closed in 2016. Given the volatility and importance of Pacific sardine, estimating stock 

sizes and setting harvest guidelines is a major goal of NOAA Fisheries. Estimating stock size is complicated by sardine life history. During the spring, sardine generally congregate and spawn off central and 

southern California. In summer, larger individuals often migrate north to Oregon, Washington, and Canada to feed in these productive waters. Because sardine distributions have always been a moving target, 

NOAA Fisheries has developed sampling protocols that may be flexible enough to accommodate climateinduced shifting distributions. Sardine presence is well-predicted by satellite-derived measurements of sea 

surface temperature, chlorophyll a, and sea surface altitude, and relationships hold regardless of season or 

sardine spawning condition (Zwolinski et al. 2011). As such, NOAA Fisheries is able to define optimal, 

good, bad, and unsuitable sardine habitat (Zwolinski et al. 2011). 

NOAA Fisheries conducts annual assessments of sardine stocks in the U.S. and Canada using acoustic-trawl (AT) sampling. AT methods involve searching for acoustic signals of CPS along predetermined 

transects during the day when CPS schools are at depth and then returning to locations where CPS were 

acoustically detected at night when they rise to the surface. Surface trawls are then run at night to evaluate 

which species characterized an acoustic signal. The sample frame and transect allocation is determined 

prior to the survey based on habitat classification based on the satellite-derived measurements. Greater 

sampling effort is apportioned in optimal and good than bad and unsuitable habitats. Stock estimates are 

then calculated within each habitat type in order to minimize overall CV. In a changing climate, it is possible that sardine and other CPS distributions will shift north. It is unlikely, however, that habitat suitability will change. Because sardine sampling is based on dynamic habitat rather than a fixed location, this 

type of design should remain viable in the future. 
28

B. Yellowfin sole (Limanda aspera) – “time-varying q” and “regime shift” 

Yellowfin sole are found along the Pacific coast of North America from British Columbia, Canada, to 

the Chukchi Sea, and south along the Asian Pacific coast to the South Korean coast in the Sea of Japan. 

They are the most abundant flatfish species in the eastern Bering Sea, and one of the largest flatfish fisheries in the world (BSAI SAFE report, 2011). Similar to many other fish species, bottom water temperature has been linked to changes in behavior and was addressed in several ways in the latest benchmark 

assessment. 

The relationship between bottom water temperature and survey biomass was first explored in the 2001 

assessment (Wilderbuer and Nichol 2001). In the 2011 benchmark assessment (Wilderbuer et al. 2011),

this relationship was further explored by evaluating how bottom water temperature affects the catchability 

of yellowfin sole in the survey trawl. During cold years catchability and herding behavior are thought to 

decrease as fish become less active, and inshore migration timing may change, both of which may alter 

their availability to the survey area, impacting the survey estimates of stock biomass. To address this, 

catchability (q) was modeled as q = e-a +βT, where e

-a

is the time-independent estimate of q, and e

-βT represents the time-varying (annual) q. The time-varying component is hypothesized to respond to the metabolic aspect of herding or distribution (availability) which can vary annually with bottom water temperature (Wilderbuer et al. 2011). 

In addition to including a time-varying q based on bottom water temperature, new to this assessment 

was the examination of a “regime-shift” which occurred in 1977. They evaluated three different time-series to determine the stock-recruitment relationship: (1) full time series, 1955-2005, (2) pre-regime shifts, 

1955-1977, and (3) post-regime shift, 1978-2005. These three time-series result in very different estimates 

of long-term sustainability of the stock. When scenario 1 or 2 were used, the stock was much more productive at low spawning stock biomass, which resulted in an FMSY 1.2 times greater than the F35%, and relatively low BMSY. Using the post-regime shift time series (scenario 3) resulted in lower FMSY and higher BMSY. 

Additionally, using time series scenarios 1 or 2 estimated FMSY with less uncertainty; thus, the buffer between OFL and ABC would be smaller compared to scenario 3. However, if the stock was productive at 

low stock sizes in the past because of non-density dependent causes, such as environmental conditions, 

then fishing at high levels and reducing biomass to low levels could prove detrimental to the sustainability of the stock if the environmental conditions resultant productivity has changed in the recent (post1977) period. Given the uncertainty in the stock-recruitment-environment relationship the panel ultimately went with the precautionary characterization of productivity and used scenario 3, the post-regime 

shift time series, to calculate biological reference points and determine stock status. 
29

C. Butterfish (Peprilus triacanthus) – thermal habitat availability

Butterfish are considered a single stock throughout their range from Cape Hatteras to the Gulf of 

Maine, and are managed by the Mid-Atlantic Fishery Management Council. The most recent benchmark 

assessment conducted in 2014 included a TOR to “undertake novel approaches to investigate the impact 

of the environment on the available butterfish habitat and therefore butterfish availability in the NEFSC 

fall offshore survey over time”. There was concern that recent changes in ocean temperature may have 

caused a shift in species range and migration dynamics that could affect survey catchability. 

In the 2014, assessment a thermal niche model coupled with regional hindcast of bottom water temperatures was used to create a habitat-based estimate of availability (pH) as the proportion of thermal habitat 

for butterfish available in the Northwest Atlantic sampled during the survey. More details on the modeling process can be found in the assessment report (NEFSC 2014), but a summary of the methods is presented here. The habitat-based availability index was developed in five steps. The first step was to develop a debiased bottom temperature hindcast for fishery independent surveys from 1973-2012. Daily 

bottom temperatures were hindcast using the Regional Ocean Modeling System (ROMS) numerical ocean 

circulation model (NEFSC 2014), and debiased using Mid-Atlantic Bight Ocean Climatological and Hydrographic Analysis (MOCHA). The daily bottom temperatures from the ROMS were interpolated onto 

the MOCHA grid. The second step was to develop a thermal niche response to temperature. This involved 

some data mining for an underlying temperature-survey catch response using a generalized additive 

model (GAM). The base GAM used swept area as an offset, with a bottom water temperature spline, and 

survey, season, and year as factors to estimate catch. Temperature explained 32% of the variance in catch. 

The closest known parametric temperature response function (The Johnson and Lewin response function) 

implied by the GAM was selected and fit to the data using maximum likelihood techniques. The third step 

was to evaluate the thermal niche model and projections of thermal habitat suitability using in situ temperature and catch data collected before 2008 and not included in the calibration. The model performed 

well, despite producing some false negatives. The fourth step was then to calculate a habitat availability 

index with uncertainty by using daily regional hindcasts of thermal habitat suitability sampled in the region during the survey periods. The final step was to evaluate the model based estimates of butterfish 

availability to the surveys by comparing them to empirical estimations (NEFSC 2014). 

Assessment reviewers noted that this method was innovative and took a rigorous approach to understanding butterfish habitat preferences, particularly in the context of how those preferences may affect 

survey catchability (q). In the assessment model, catchability was parameterized as the product of available thermal habitat surveyed and an empirical estimate of net efficiency. The catchability estimate enabled more realistic scaling of butterfish population size than in previous assessments (NEFSC 2014). 

However, the time-varying estimate of availability was ultimately rejected by the review panel in favor of 

a more parsimonious time-series mean, although the thermal habitat suitability index was retained for use 

in future sensitivity analysis. 
30

D. Southern New England-Mid Atlantic yellowtail flounder (Limanda ferruginea) 

– cold pools and stock-recruitment relationship

Yellowtail flounder is a small-mouthed flatfish (pleuronectid) found along the U.S. east coast. Historically, distribution of the Southern New England-Mid Atlantic yellowtail stock (hereafter referred to as the 

Southern New England stock) ranged from the Chesapeake Bay, but more recently from southern New 

England, to southern Labrador, Canada. There are three discrete stocks, or management units, for this species: Southern New England, Georges Bank, and Cape Cod/Gulf of Maine. The most recent benchmark 

assessment of the Southern New England stock in 2012 explored the use of an environmentally explicit

stock-recruitment model based on the observed relationship between yellowtail recruitment and the midAtlantic cold pool, but did not successfully resolve the relationship between the cold-pool and the recent 

poor recruitment of the stock. 

The recruitment of many cold-water and temperate species in the northwest Atlantic has been linked to 

the dynamics of the mid-Atlantic cold pool (Houghton et al. 1982, Miller et al. 2016). The linkage between Southern New England yellowtail flounder (YTF) recruitment and ocean temperatures has been 

hypothesized since the mid-1950s when Taylor et al. (1957) first proposed that the decline in southern 

New England yellowtail flounder in the 1940s was related to increasing ocean temperature. It was not until 2005, however, when Sullivan et al. (2005) made the connection between YTF recruitment and cold 

pool dynamics based on observations that YTF almost exclusively settle in the cold pool during summer. 

The 2012 YTF benchmark assessment explored this relationship between recruitment and cold pool 

index by developing an alternative run of the stock assessment base model which modelled the cold pool 

index as a covariate in the Beverton-Holt stock-recruit relationship estimated internally within the stock 

assessment ASAP model. The cold pool index was negatively correlated with the variation in YTF recruitment as the cold pool index decreases (i.e., larger and colder pool) the predicted recruitment increases (NEFSC, 2012). The environmentally-explicit Beverton-Holt models that included the cold pool 

index tended to fit the data better than those based on spawning stock biomass SSB alone (NEFSC 2012; 

Miller et al. 2016). However, the inclusion of the cold pool index did not explain the step-like decline in 

YTF that occurred around 1990, and thus was ultimately not used in the final model. Instead, to determine 

biological reference points, two different recruitment scenarios were evaluated to account for this potential change in the ‘prevailing environmental conditions’ and the uncertainty in the causal mechanisms behind it. The first scenario used age-1 recruitment from 1990-2010, representing the “recent” period, recognizing the potential environmentally driven drop in productivity after 1990. The second scenario used 

the entire age-1 recruitment time series from 1973-2010, with “two stanzas” of recruitment determined by 

whether spawning stock biomass is either above or below 4,319 mt. This scenario is based on an alternate 

hypothesis that the low-recruitment may be due to a decrease in spawning stock biomass. The biomass 

reference points and conclusions regarding the overfished status of the stock depended greatly on the recruitment scenario employed. Spawning stock biomass at maximum sustainable yield (SSBmsy) and MSY 

were much lower under the “recent” low-recruitment scenario compared to the “two stanza” scenario, 

which lead to the conclusion that the stock was not overfished and that the stock had rebuilt. 
31

Neither scenario could be ruled out with certainty; therefore, the panel suggested using a weight of evidence (Krimsky 2005) approach to decide whether a species productivity shift had occurred. The following criteria were considered (SARC 54 Panel Summary Report): 

● A long period of observed above or below recruitment;

● A long period of above or below average recruitment residuals should be observed that cannot be corrected by simple re-specification of the stock-recruitment relationship;

● Error in estimated model inputs, such as total catch, abundance indices or catch age/size composition can be ruled out as a cause; and 

● A plausible mechanism has been found that is based on environmental or ecological conditions. 

The panel concluded that the weight of evidence appeared to support the notion of “recent” reduced 

recruitment of the stock. Although it was concluded that the stock was not overfished, and overfishing 

was not occurring, the biomass stock status determination remained uncertain due to the lack of strong 

evidence to support the mechanisms related to the changes in the stock productivity.
32

E. Quantifying risk from a change in ocean conditions: red-tide episodic event

In the Gulf of Mexico, harmful algal blooms of the dinoflagellate Karenia brevis are responsible for 

major episodic mortality events of fish, such as red grouper (Epinephelus morio). Studies conducted since 

2013 have been effective at quantifying red tide severity, understanding the effects of red tide mortality 

on groupers and on species which interact with groupers, improving fits to abundance indices, and refining estimation of management benchmarks (SEDAR 2014, 2015). However, questions remained on 

whether the management system was robust to red tide mortality events. Therefore, in 2014, the Gulf of 

Mexico Fishery Management Council passed a motion to “...evaluate the current red grouper harvest control rule to determine if it is robust to possible future changes in intensity and frequency of episodic 

events of non-fishing mortality” (GMFMC 2014). In response to management concerns, simulation testing was conducted to determine potential responses to these mortality events under two different harvest 

control rule designs; a reactive control rule which altered catch limits in response to red tide event occurrence and an unresponsive, yet precautionary catch limit aimed at buffering against future natural mortality events.

Management concerns revolved around determining (1) what the trade-offs are for different management approaches in terms of maintaining sustainable fisheries; (2) what considerations, if any, arise when 

mortality changes during stock rebuilding; and (3) how do precautionary approaches affect catches. Simulation tests were conducted focused on two components of the two harvest control rule designs: (1) decision-making reactivity and (2) the level of precautionary catch reduction used to buffer against episodic 

natural mortality events. The simulations tested several variants of each design considering different precautionary ACL reductions and decision frequencies (e.g., fixed 5-year intervals vs. 5-year reactive intervals where an ACL is newly calculated after a red tide mortality event). HCR performance was measured 

in terms of (1) avoiding minimum biomass, calculated as the frequency of years in a simulation run where 

biomass was greater than (1-M)/BMSY, and (2) achieving optimum catch, calculated as the percentage of 

years in a simulation run where catches were greater than 0.75MSY. Simulations of management strategies were analyzed, and the performance outcomes were presented in the form of a decision tree. Presenting results in the form of decision trees enabled managers and stakeholders to play-out risk-averse or riskprone approaches to HCR selection in circumstances where episodic natural mortality increases either 

materialize or fail to materialize. Overall, precautionary ACL reductions had a greater effect on management performance than did decision reactivity; however, in both cases there was a tradeoff between 

avoiding minimum biomass levels and achieving optimum catch. Reactive HCRs were also less likely to 

result in timely stock recovery compared with the precautionary ACL HCRs. Precautionary ACL reductions were also found to protect against multiple stochastic events (e.g., recruitment fluctuations and episodic natural morality events) that may be impacting a stock simultaneously. 

This study highlights how MSE and structured management guidance can address uncertainty about 

future occurrences in episodic natural mortality events and can support rationale contrasts of management 

performance across a variety of scenarios (Harford et al. submitted).
33

F. Alaska Climate Change Integrated Modeling (ACLIM) project 

The Alaska Climate Change Integrated Modeling (ACLIM) project represents a comprehensive, collaborative effort to characterize and project climate-driven changes to the Bering Sea ecosystem, from 

physics to fishing communities, and to understand how different fisheries management approaches might 

help promote adaptation to climate-driven changes and long-term sustainability in fish and shellfish populations. ACLIM strives to evaluate fishery management strategies under 10+ different climate change scenarios (spanning high and low CO2 futures) in the Bering Sea. It connects research on scaling of climate 

models, climate-enhanced biological models, and socio-economic and harvest scenarios (Figure 

A1). ACLIM is a multi-year, interdisciplinary project, involving collaboration among 19 physical oceanographers, ecosystem modelers, socioeconomic researchers, and fishery management analysts from 

NOAA Alaska Fisheries Science Center (AFSC), NOAA Pacific Marine Environmental Lab (PMEL), 

and the University of Washington. A major focus of the project is to quantify scenario, parameter, and 

structural uncertainty through a multi-model projection suite which will aid in evaluating the performance 

of resource management strategies under different future scenarios.

Figure A1. Illustration of the multiple models and climate and fishing scenarios in the ACLIM project.
34

ACLIM uses output from global climate and earth system models (CGM and ESM, respectively) to 

project future boundary conditions for a regional ocean model. Dynamically coupled, regionally 

downscaled projections of the biogeochemistry of the eastern Bering Sea ecosystems are used to project 

the future of fish and fisheries in a region. Projections of the distribution, production and abundance of 

fish are used to estimate the future distribution and yield of commercial fisheries using a suite of population dynamics models with different levels of complexity. The approach of ACLIM is to integrate results 

from the diverse multi-model projection suite to provide a reasonable range of representative futures (with 

sufficient contrast in scenarios) that can be used to evaluate short- and long- term implications of management actions under future climate change. ACLIM is specifically designed to help NOAA Fisheries assess 

the science capacity and approaches needed in other regions to deliver and use projections of climate impacts on fisheries in management. 

Operationalized ACLIM

AFSC has been moving towards operationalizing ACLIM. An operationalized ACLIM framework 

would be employed every 5 years (or more frequently if needed) to provide climate ready fisheries management advice. The generalized ACLIM approach for a new climate assessment is as follows: (1) global 

climate projections will be downloaded and used for initial and boundary conditions of regional high-resolution three-dimensional coupled physical circulation and lower trophic productivity models (ROMSNPZ); (2) ROMS-NPZ models will be coupled to biological models (e.g., climate-enhanced stock assessment and/or climate-enhanced food web models); (3) with input from stakeholders and fisheries management councils, various harvest and management scenarios will be used to iteratively develop and refine 

management strategy evaluations (MSEs). This will enhance the global assessment of climate impacts on 

the world’s oceans as well as regional management actions to ensure climate resilience for the Bering Sea 

ecosystem and the ~$2 billion/yr fishery industry it supports. 

Identifying harvest strategies that perform well under non-stationary environmental conditions is a 

challenging endeavor (Szuwalski and Hollowed 2016). The proposed iterative ACLIM framework conducted on a ~5 year cycle is modeled after the highly successful annual stock assessment cycle in the region; the approach will ensure that fisheries management decisions account for climate-driven changes to 

fish production and distribution and that climate-ready fisheries management in the region reflects the 

most recent global climate and carbon emission projections and best available ecosystem and socioeconomic science. Results include projections of biological and physical conditions, species distribution and 

abundance, and fisheries harvest under various climate and management combinations. Initial results are 

regularly presented to fisheries managers, fishery dependent communities and other non-governmental 

organizations to seek feedback on the relative realism of proposed management and fisher responses to 

changing fish production. The suite of Representative Fishery Pathways are modified based on this input. 

Final results of the assessment will be distributed in the form of a climate assessment document and presented to regional stakeholders and fisheries councils in order to inform management decisions and 

tradeoff analyses under short- term and long-term variable conditions and contrasting ecological assumptions (inherent in each model). 
35

G. Using comprehensive risk assessment to prioritize limited resources

Comprehensive risk analysis may be a useful tool to help Councils and other management bodies prioritize which actions to take with respect to incorporating climate and ecosystem factors into fisheries 

management. In 2016, the Mid Atlantic Fishery Management Council conducted a risk assessment in 

which sensitivity to climate driven distribution shifts and productivity shifts were considered along with 

single species status, food web, habitat, economic, social, and management factors to identify species and 

ecosystems at most risk due to changing climatic conditions (Gaichas et al. 2016). 

For this risk assessment the Council selected a set of risk elements which are aspects that may threaten 

the ability to achieve Council social, biological, and economic objectives. The risk elements were evaluated at the managed species or sector level, or ecosystem region. Categorization for each risk element was 

evaluated using an associated set of indicators. Five risk element groups were identified: 

 Ecological (assessment performance, fishing and biomass status, food web interactions (predator and prey), ecosystem productivity, climate, distribution shifts, estuarine habitat, offshore 

habitat);

 Economic (commercial/recreational revenue, commercial fishery resilience (revenue diversity), commercial fishery resilience (shoreside support));

 Social (fleet resilience, social-cultural) ;

 Food production (commercial, recreational); and 

 Management (control, interactions, other ocean uses, regulatory complexity, discards, allocation).

Each sub-category within a risk element category was evaluated and the species or ecosystem given a 

risk score (low, low-moderate, moderate-high, high). The risk categorization for each subcategory was

then summarized for each species, sector, and/or ecosystem and used to identify species, sectors, or ecosystems at most risk, and therefore highest priority for monitoring and management action. Information 

necessary to conduct the evaluations came from a multitude of sources. Ecological data came from 

NEFSC trawl surveys, food habits databases, remote sensing (e.g., satellites), and climate vulnerability 

analysis. Social and economic data were obtained from Quarterly Census and Employment and Wages 

statistics from the U.S. Census Bureau, Fisheries Economics of the US compiled by NMFS, and the 

NOAA Fisheries Community Social Vulnerability Indicators. Commercial and recreational seafood landings data were used to assess commercial and recreational seafood production. This effort is still in its initial stages; therefore, the risk assessments’ benefits to management are still unclear. 
36

H. Case study references 

Gaichas, S. K., Seagraves, R. J., Coakley, J. M., DePiper, G. S., Guida, V. G., Hare, J. A., Rago, P. J., and

Wilberg, M. J. 2016. A Framework for Incorporating Species, Fleet, Habitat, and Climate Interactions into Fishery Management. Frontiers in Marine Science, 3(105), 

https://doi.org/10.3389/fmars.2016.00105

GMFMC. 2014. Gulf of Mexico Fishery Management Council motions report June 23-27, 2014,

Key Largo FL.

Harford, W. J., Gruss, A., Schirripa, M. J., Karnauskas, M. submitted. Designing harvest control rules to 

respond to episodic natural mortality increases. 

Houghton, R. W., Schlitz, R., Beardsley, R. C., Butman, B., and Chamberlin, J. L. 1982. The Middle Atlantic Bight cold pool: evolution of the temperature structure during summer 1979. Journal of Physical Oceanography 12:1019–1029.

Krimsky, S. 2005. The weight of scientific evidence in policy and law. Am. J. PublicHealth 95 (Suppl. 1), 

S1.

McClatchie, S., Field, J., Thompson, A. R., Gerrodette, T., Lowry, M., Fiedler, P. C., Watson, W., Nieto,

K. M., Vetter, R. D. 2016. Food limitation of sea lion pups and the decline of forage off central and 

southern California. Royal Society Open Science 3: 150628

Miller, T. J., Hare, J. A., and Alade, L. A. 2016. A state-space approach to incorporating environmental 

effects on recruitment in an age-structured assessment model with an application to southern New 

England yellowtail flounder. Canadian Journal of Fisheries and Aquatic Sciences 73:1261-1270.

NEFSC. 2012. 54th Northeast Regional Stock Assessment Workshop (54th SAW) Assessment Report. 

NEFSC Ref Doc 12-18. 600 p.

NEFSC. 2014. 58th Northeast Regional Stock Assessment Workshop (58th SAW) Assessment Report. 

NEFSC Ref Doc 14-04. 784 p.

SEDAR. 2014. Stock assessment report: Gulf of Mexico Gag. Gulf of Mexico Fishery

Management Council. SEDAR 33.

SEDAR. 2015. Stock assessment report: Gulf of Mexico Red Grouper. Gulf of Mexico Fishery

Management Council. SEDAR 42.

Sullivan, M. C., Cowen, R. K., and Steves, B. P. 2005. Evidence for atmosphere–ocean forcing of yellowtail flounder (Limanda ferruginea) recruitment in the Middle Atlantic Bight. Fisheries Oceanography 

14:386–399

Szuwalski, C. S. and Hollowed, A. B. 2016. Climate change and non-stationary population processes in 

fisheries management. ICES Journal of Marine Science, 73(5), 1297-1305, 

https://doi.org/10.1093/icesjms/fsv229

Taylor, C. C., Bigelow, H. B., and Graham, H. W. 1957. Climatic trends and the distribution of marine 

animals in New England. Fishery Bulletin 57:293–345

Wilderbuer, T. K. and Nichol, D. 2001. Yellowfin sole. In Stock Assessment and Fishery Evaluation 

Document for Groundfish Resources in the Bering Sea/Aleutian Islands Region as Projected for 

2004, chapter 4. North Pacific Fishery Management Council, P. O. Box 103136, Anchorage, AK

99510 

Wilderbuer, T. K., Nichol D., Ianelli, J. 2011. Yellowfin sole. In Stock Assessment and Fishery Evaluation Document for Groundfish Resources in the Bering Sea/Aleutian Islands Region as Projected for 
37

2012, chapter 4. North Pacific Fishery Management Council, P. O. Box 103136, Anchorage, AK 

99510 

Zwolinski, J. P., Emmett, R. L., and Demer, D. A. 2011. Predicting habitat to optimize sampling of Pacific sardine (Sardinops sagax) ICES Journal of Marine Science 68: 687-879

Zwolinski, J. P., and Demer, D. A. 2012. A cold oceanographic regime with high exploitation rates in the 

Northeast Pacific forecasts a collapse of the sardine stock. Proceedings of the National Academy of 

Sciences of the United States of America 109: 4175-4180