THE DYNAMIC MARSH MANAGEMENT TOOL (DMMT) –OPTIMIZING COASTAL‐MARSH AND NATURAL‐RESOURCEPRESERVATION UNDER UNCERTAIN SEA‐LEVEL RISE
The Dynamic Marsh Management Tool integrates current model results, uncertainty analysis, and stakeholder values to estimate
cost‐per‐benefit ratios for alternative management strategies
Conservation planning and management under changing climate conditions, particularly sea level rise, can be complicated by thewealth of divergent data sets available and multiple policymaking goals. Because of this, prioritization of marsh‐management
strategies can be a difficult undertaking. Ideally, a manager could evaluate the relative benefits of adaptation strategies andmaximize wetland benefits while considering uncertainty both in future sea‐level rise, and dynamic marsh response. A modelingframework to evaluate the costs and benefits of management strategies while accounting for these uncertainties has beendeveloped (Figure 1, left).

Stakeholder
ValuesEcosystem Values
Defined for each Site
Quantitative and Qualitative
Utility
Functions

SLAMM Results for
Adaptive Strategies

Integrate
Relative Parcel
Value overTime

Adaptation Strategy
Costs by SiteCost‐Benefit Metric

FIGURE 1. SCHEMATIC OF DMMT AND A SPATIAL UNCERTAINTY ANALYSIS MAP USED (PERCENT LIKELIHOOD OF HABITAT CHANGE BY 2085)

The base data for the tool are high‐resolution uncertainty‐analysis results from the SLAMM model under multiple adaptive‐
management strategies (Figure 1 right). Adaptation strategies that have been simulated include:

thin‐layer sediment deposition of dredge material onto existing marshes,
upland land purchase and purchase of easements to allow marsh migration,
marsh habitat restoration to historic footprints (or new‐project footprints), andtidal‐amplitude restoration via culvert replacement.

Model results are combined with ecosystem‐valuation assessments from stakeholders that define a set of relative “wetlandbenefits.” Stakeholders enumerate site specific wetland benefits that can include nature‐centered benefits (such as nekton
habitat preservation) and human‐centered benefits (such as recreation and flood protection). Model results and stakeholder
values are then linked together using utility functions that characterize the relationship between defined wetland benefits andgeometric metrics such as “marsh type,” “marsh area,” marsh edge,” and “marsh width.” Expected‐values for each site’s wetland
benefits can then be projected into the future and compared to the estimated costs for each adaptation strategy (Figure 2).
Estimates of optimal marsh‐management strategies are produced, by maximizing the “wetlands benefits per estimated costs”
ratio.

SiteStrategy

UtilityComponents of Each Site's Utility, Defined by
Stakeholders then Integrated over Time

Utility at 'Udall's Cove, Queens' by Strategy over Time
16.00

6000

14.00

UtilityAggregated Utility from 2016 to 2100

General preservation of wetlands
Political/Cultural/Historic value

4000

Habitat connectivity / Frag
Nekton Habitat
Natural Areas for Underserved Communities

3000

Marsh Land Recreation
Undeveloped Dry Land Recreation

2000

Wetland Benefits per Year

Flood Vulnerability Reduction

5000

Phosphorus Sequestration

12.00
10.00

Strategy

Migr. All Dry

8.00

Migr. Undeveloped
No Migration

6.00

Restore to 1974
Thin Layer Depo.

4.00

Nitrogen Sequestration

1000

2.00

Carbon Sequestration

0.00
Udall's Cove, Pelham Bay Lemon Creek, Alley Creek,
QueensCove
Staten Island Queens

2016
2020
2024
2028
2032
2036
2040
20442048
2052
2056
2060
2064
2068
2072
2076
2080
2084
2088
2092
2096
2100

0W.T. Davis Idlewild Innerand OuterSiteYear

Site

Strategy

Estimated Wetland Benefits per Unit Cost (by Site and Adaptation Strategy)

Expected Value: Land Cover of 'Udall's Cove, Queens' Over Time: 'No Migration'

120.0

10
Migr. All Dry

9

Expected Value in Acres

876LandCoverFreshwater Non‐Tidal
5Freshwater Tidal
Transitional

4

Saltmarsh

32

Wetland Benefit per Millions of Dollars Spent

100.0

Migr. UndevelopedRestore to 1974
Thin Layer Depo.

80.0

60.0

40.0

20.0

10201620302044205820722086

21000.0Idlewild Inner and Outer Alley Creek, QueensYearLemon Creek, StatenIslandPelham Bay Cove

W.T. DavisUdall's Cove, Queens

FIGURE 2. UPPER LEFT: COMPONENTS OF MARSH WETLAND BENEFITS BY DEFINED STUDY AREA. UPPER RIGHT: EFFECTS OF ALTERNATIVE MANAGEMENTSTRATEGIES ON ONE DEFINED MARSH SYSTEM. LOWER LEFT: EXPECTED VALUE OF LAND COVER GIVEN UNCERTAIN SEA‐LEVEL RISE. LOWER RIGHT:COMPARITIVE BENEFITS PER ESTIMATED COST OF EACH ADAPTATION STRATEGY BY SITE STUDIED

This new tool has been applied in two different New York Counties (partnering with NYSERDA and NYC Parks) and is currently
being applied to a third county (partnering with NYSERDA and TNC) and Casco Bay in Maine (with Casco Bay Estuary Partnership).
The current New York State project has built on previously completed high‐resolution uncertainty analysis modeling (Clough,Polaczyk, and Propato, 2016 in Ecological Modeling).
Existing SLAMM model applications can be utilized as the base of the tool or new applications created with updated spatial datafor a reasonable cost. For more information on the DMMT including model results and New York City case studies, please visit
http://warrenpinnacle.com/prof/SLAMM/NYSERDA2015/DMMT.html. To learn more about applying DMMT for your study area,
please contact Jonathan Clough (jclough@warrenpinnacle.com) or Marco Propato (mpropato@warrenpinnacle.com) or call
Jonathan at 802‐496‐3476.
Other Projects Warren Pinnacle Consulting has recently been involved in include:

Modeling Effects of Sea‐Level Rise and Storm Surge on Roads and Infrastructure
Modeling Effects of Deepwater Horizon on Nearshore Environments (Blancher et. al 2017; Clough et al, 2017 accepted)
Creation of SLAMM version 6.7 including dynamic wave erosion (with ESA Associates and funding from TNC)
Creation of AQUATOX 3.2 with EPA funding (EPA release expected in 2017)