Optimization of Salt Marsh Management at the 

Stewart B. McKinney National Wildlife Refuge, 

Connecticut, Through Use of Structured Decision Making

Open-File Report 2020–1139

U.S. Department of the Interior

U.S. Geological Survey
Cover. Photograph of salt marsh habitat at Great Meadows Unit, Stewart B. McKinney National Wildlife 

Refuge, in Stratford, Connecticut; photograph by Kristina Vagos, U.S. Fish and Wildlife Service.
Optimization of Salt Marsh Management at 

the Stewart B. McKinney National Wildlife 

Refuge, Connecticut, Through Use of 

Structured Decision Making

By Laurel E. Low, Hilary A. Neckles, James E. Lyons, Jessica L. Nagel, 

Susan C. Adamowicz, Toni Mikula, Kristina Vagos, and Richard Potvin

Prepared in cooperation with the U.S. Fish and Wildlife Service

Open-File Report 2020–1139

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

DAVID BERNHARDT, Secretary

U.S. Geological Survey

James F. Reilly II, Director

U.S. Geological Survey, Reston, Virginia: 2020

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U.S. Fish and Wildlife Service.

Suggested citation:

Low, L.E., Neckles, H.A., Lyons, J.E., Nagel, J.L., Adamowicz, S.C., Mikula, T., Vagos, K., and Potvin, R., 2020, 

Optimization of salt marsh management at the Stewart B. McKinney National Wildlife Refuge, Connecticut, through 

use of structured decision making: U.S. Geological Survey Open-File Report 2020–1139, 28 p., https://doi.org/

10.3133/ofr20201139.

ISSN 2331-1258 (online)
iii

Acknowledgments

Ward Feurt, Ryan Kleinert, Kathleen O’Brien, and Bri Benvenuti of the U.S. Fish and Wildlife 

Service (FWS) provided exceptional hospitality at the Rachel Carson National Wildlife Refuge, 

Maine, for the 2018 structured decision-making workshop, which included participants from 

six additional national wildlife refuges. Nathan Bush of the FWS generated the mapping data 

used in this report, and Jackie Olson of the U.S. Geological Survey expertly prepared the maps. 

Insight from Shimon Anisfeld of Yale University and technical reviews by Rachel Katz of the 

FWS and Bill Thompson of the National Park Service greatly improved the quality of this report. 

At the time of publication, data supporting this study have not been published by the U.S. Fish 

and Wildlife Service.

v

Contents

Acknowledgments........................................................................................................................................iii

Abstract...........................................................................................................................................................1

Introduction.....................................................................................................................................................1

Purpose and Scope ..............................................................................................................................5

Description of Study Area ...................................................................................................................5

Regional Structured Decision-Making Framework .................................................................................6

Application to the Stewart B. McKinney National Wildlife Refuge .......................................................7

Results of Constrained Optimization ...........................................................................................................8

Considerations for Optimizing Salt Marsh Management ......................................................................14

References Cited..........................................................................................................................................16

Appendix 1. Regional Influence Diagrams ...........................................................................................18

Appendix 2. Utility Functions for the Stewart B. McKinney National Wildlife Refuge .................25

Figures

1. Map showing national wildlife refuges and national wildlife refuge complexes 

of the U.S. Fish and Wildlife Service where salt marsh integrity was assessed 

from 2012 to 2016 using the regional monitoring protocol .....................................................2

2. Salt marsh management units at the Stewart B. McKinney National Wildlife 

Refuge in Connecticut ..................................................................................................................3

3. Graph showing predicted total management benefit of various portfolios, 

expressed as weighted utilities, relative to total cost at the Stewart B. 

McKinney National Wildlife Refuge in Connecticut .............................................................13

4. Graph showing predicted management benefit for individual performance 

metrics from implementation of the management actions included in portfolio 9 

compared with the baseline “no-action” portfolio at the Stewart B. McKinney 

National Wildlife Refuge in Connecticut .................................................................................15

Tables

1. Objectives hierarchy for salt marsh management decision problems ................................7

2. Participants in workshop convened at the Rachel Carson National Wildlife 

Refuge, Maine, to apply a regional framework for optimizing salt marsh 

management decisions to six national wildlife refuges in January 2018 ............................8

3. Possible management actions for achieving objectives within 2 marsh 

management units at Stewart B. McKinney National Wildlife Refuge, 

Connecticut, estimated costs over 5 years, and predicted outcomes expressed 

relative to performance metrics .................................................................................................9

4. Normalized predicted outcomes and estimated total management benefits of 

possible management actions within 2 marsh management units at the Stewart 

B. McKinney National Wildlife Refuge, Connecticut ............................................................11

5. Actions included in various management portfolios to maximize the total 

management benefits subject to increasing cost constraints at the Stewart B. 

McKinney National Wildlife Refuge, Connecticut .................................................................14
vi

Conversion Factors

International System of Units to U.S. customary units

Multiply By To obtain

meter (m) 3.281 foot (ft)

kilometer (km) 0.6214 mile (mi)

square meter (m2) 0.0002471 acre

hectare (ha) 2.471 acre

Datum

Vertical coordinate information is referenced to the North American Vertical Datum of 1988 

(NAVD 88).

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).

Elevation, as used in this report, refers to distance above the vertical datum.

Abbreviations

FWS U.S. Fish and Wildlife Service

NWR national wildlife refuge

NWRS National Wildlife Refuge System

USGS U.S. Geological Survey
Optimization of Salt Marsh Management at the 

Stewart B. McKinney National Wildlife Refuge, 

Connecticut, Through Use of Structured Decision Making

By Laurel E. Low,1 Hilary A. Neckles,2 James E. Lyons,2 Jessica L. Nagel,2 Susan C. Adamowicz,3 Toni Mikula,3

Kristina Vagos,3 and Richard Potvin3

Abstract

Structured decision making is a systematic, transparent 

process for improving the quality of complex decisions by 

identifying measurable management objectives and feasible 

management actions; predicting the potential consequences 

of management actions relative to the stated objectives; and 

selecting a course of action that maximizes the total benefit achieved and balances tradeoffs among objectives. The 

U.S. Geological Survey, in cooperation with the U.S. Fish and 

Wildlife Service, applied an existing, regional framework for 

structured decision making to develop a prototype tool for 

optimizing tidal marsh management decisions at the Stewart 

B. McKinney National Wildlife Refuge in Connecticut. 

Refuge biologists, refuge managers, and research scientists 

identified multiple potential management actions to improve 

the ecological integrity of two marsh management units within 

the refuge and estimated the outcomes of each action in terms 

of performance metrics associated with each management 

objective. Value functions previously developed at the regional 

level were used to transform metric scores to a common 

utility scale, and utilities were summed to produce a single 

score representing the total management benefit that would be 

accrued from each potential management action. Constrained 

optimization was used to identify the set of management 

actions, one per marsh management unit, that would maximize total management benefits at different cost constraints 

at the refuge scale. Results indicated that, for the objectives 

and actions considered here, total management benefits may 

increase consistently up to approximately $1,190,000, but 

that further expenditures may yield diminishing return on 

investment. Management actions in optimal portfolios at total 

costs less than $1,190,000 included controlling avian predators in both management units, managing stormwater on 

lands adjacent to one marsh management unit, and removing 

1Yale University.

2U.S. Geological Survey.

3U.S. Fish and Wildlife Service.

a tide gate and breaching a dike to improve tidal flow in the 

other marsh management unit. The management benefits were 

derived from expected increases in the numbers of spiders (as 

an indicator of trophic health) and tidal marsh obligate birds, 

and an expected decrease in the use of herbicides to control 

invasive vegetation. The prototype presented here provides a 

framework for decision making at the Stewart B. McKinney 

National Wildlife Refuge that can be updated as new data and 

information become available. Insights from this process may 

also be useful to inform future habitat management planning at 

the refuges.

Introduction

The National Wildlife Refuge System (NWRS) protects 

extensive salt marsh acreage in the northeastern United States. 

Much of this habitat has been degraded by a succession of 

human activities since the time of European settlement (Gedan 

and others, 2009), and accelerated rates of sea-level rise 

exacerbate these effects (Gedan and others, 2011; Kirwan and 

Megonigal, 2013). Therefore, strategies to restore and enhance 

the ecological integrity of national wildlife refuge (NWR) salt 

marshes are regularly considered. Management may include 

such activities as reestablishing natural hydrology, augmenting 

or excavating sediments to restore marsh elevation, controlling invasive species, planting native vegetation, minimizing 

shoreline erosion, and remediating contaminant problems. 

Uncertainty stemming from incomplete knowledge of system 

status and imperfect understanding of ecosystem dynamics commonly hinders management predictions and consequent selection of the most effective management options. 

Consequently, tools for identifying appropriate assessment 

variables and evaluating tradeoffs among management objectives are valuable to inform marsh management decisions.

Structured decision making is a systematic approach to 

improving the quality of complex decisions that integrates 

assessment metrics into the decision process (Gregory and 

Keeney, 2002). This approach involves identifying measurable 

management objectives and potential management actions, 
2 Optimization of Salt Marsh Management at the Stewart B. McKinney National Wildlife Refuge, Connecticut

predicting management outcomes, and evaluating tradeoffs 

to choose a preferred alternative. From 2008 to 2012, the 

U.S. Geological Survey (USGS) and U.S. Fish and Wildlife 

Service (FWS) used structured decision making to develop a 

framework for optimizing management decisions for NWR 

salt marshes in the FWS Northeast Region (that is, salt 

marshes in the coastal region from Maine through Virginia). 

The structured decision-making steps were applied through 

successive “rapid prototyping” workshops, an iterative process in which relatively short periods of time are invested to 

continually improve the decision structure (Blomquist and 

others, 2010; Garrard and others, 2017). The decision framework includes regional management objectives addressing 

critical components of salt marsh ecosystems, and associated 

performance metrics for determining whether objectives are 

achieved (Neckles and others, 2015). The regional objectives 

structure served as the foundation for a consistent protocol for 

monitoring salt marsh integrity at these northeastern coastal 

refuges, in which the monitoring variables are linked explicitly to management goals (Neckles and others, 2013). From 

2012 to 2016, this protocol was used to conduct a baseline 

assessment of salt marsh integrity at all 17 refuges or refuge 

complexes in the FWS Northeast Region with salt marsh 

habitat (fig. 1).

The Stewart B. McKinney National Wildlife Refuge 

protects about 200 hectares (ha) of salt marsh bordering 

Long Island Sound in Stratford and Westbrook, Connecticut 

(fig. 2). The refuge’s salt marsh provides critical nesting and 

Lake Ontario

Lake Erie

Lake Huron

A T L A N T I C

O C E A N

RI

D.C.

Montpelier

Concord

Augusta

Albany

Trenton

Charleston

Richmond

Columbus

Dover

Buffalo

Baltimore

Philadelphia

Hartford

Providence

Boston

New York

ME

NH

MA

VT

CT

DE

MD

PA

NJ

NY

OH

WV

VA

NC

KY

Moosehorn

NWR

Maine Coastal

Islands NWR

Rachel Carson

NWR

Parker River NWR

Monomoy NWR

Stewart B. 

McKinney

NWR

Long Island NWR Complex

Fisherman Island NWR

Eastern Shore of Virginia NWR

Chincoteague NWR

Prime Hook NWR 

Cape May NWR

Bombay Hook NWR

Supawna Meadows NWR

Plum Tree

Island NWR

Edwin B. Forsythe NWR

Rhode Island

NWR Complex

CANADA

UNITED STATES

85° 80° 75° 70° 65°

45°

40°

Base map image copyright Esri Inc., 2017

Universal Transverse Mercator, zone 18N

North American Datum of 1983

0 100 200 300 MILES

0 100 200 300 KILOMETERS

EXPLANATION

National wildlife

Stewart B. refuge and name

McKinney NWR

Figure 1. National wildlife refuges and national wildlife refuge complexes of the U.S. Fish and Wildlife Service where salt marsh 

integrity was assessed from 2012 to 2016 using the regional monitoring protocol.
Introduction 3

Great Meadow

LONG

ISLAND

SOUND

Johnsons Creek

Yellow

Mill Channel

Lewis Gut

BRIDGEPORT

HARBOR

Stratford

East

Bridgeport

Newfield

IGOR SIKORSKY

MEMORIAL AIRPORT

EXPLANATION

Stewart B. McKinney National Wildlife Refuge

Fish and Wildlife Service managed area

U.S. Fish and Wildlife Service salt marsh

unit and name

Great

0 0.2 0.4 0.6 0.8 MILES

0 0.2 0.4 0.6 0.8 KILOMETERS

73°10' 73°09' 73°08'

41°

11'

41°

10'

41°

09'

Base map image copyright Esri Inc., 2017

Universal Transverse Mercator, Zone 18N

North American Datum of 1983

Stewart B. McKinney

National Wildlife Refuge

CONNECTICUT

NEW YORK

CONNECTICUT

NEW YORK

Stratford Bridgeport

Map

area

Hartford

A

B

A

MASSACHUSETTS

RI

A

Figure 2. Maps showing salt marsh management units at the Stewart B. McKinney National Wildlife Refuge in Connecticut. A, Great 

Meadows unit in Stratford, Connecticut, and B, Salt Meadow unit in Westbrook, Connecticut.
4 Optimization of Salt Marsh Management at the Stewart B. McKinney National Wildlife Refuge, Connecticut

Salt Meadow

LONG ISLAND

SOUND

DUCK ISLAND ROADS

WESTBROOK

HARBOR

Menunketesuck River

Patchogue River

Grove

Beach

EXPLANATION

Stewart B. McKinney National Wildlife Refuge

Fish and Wildlife Service managed area

U.S. Fish and Wildlife Service salt marsh

unit and name

Salt

0 0.25 0.5 MILES

0 0.25 0.5 KILOMETERS

72°29' 72°28'30" 72°28' 72°27'30"

41°

17'

30"

41°

17'

41°

16'

30"

41°

16'

Base map image copyright Esri Inc., 2017

Universal Transverse Mercator, Zone 18N

North American Datum of 1983

CONNECTICUT

NEW YORK

Clinton B

Stewart B. McKinney

National Wildlife Refuge

CONNECTICUT

NEW YORK

Hartford

A

B

MASSACHUSETTS

RI

Map

area

B

Figure 2. Maps showing salt marsh management units at the Stewart B. McKinney National Wildlife Refuge in Connecticut. A, Great 

Meadows unit in Stratford, Connecticut, and B, Salt Meadow unit in Westbrook, Connecticut.—Continued
Introduction 5

wintering habitat for birds of highest conservation priority, 

including saltmarsh sparrows and American black ducks, in 

the U.S. North American Bird Conservation Initiative’s bird 

conservation region for the New England and mid-Atlantic 

coast (Steinkamp, 2008; National Audubon Society, 2020a, b; 

U.S. North American Bird Conservation Initiative, 2020). The 

salt marsh also provides important foraging habitat for wading 

birds (such as Great and Snowy Egrets) during breeding and 

migratory seasons (National Audubon Society 2020a, b). The 

primary threats to this habitat are marsh loss, fragmentation, 

and degradation associated with increasing human activity 

within 1,000 meters (m) of the refuge boundary, spread of the 

invasive reed Phragmites australis (hereafter referred to as 

Phragmites), and marsh submergence associated with rising 

sea level (Potvin, 2017; National Audubon Society 2020a, b; 

S.C. Adamowicz and T. Mikula, FWS, unpub. data, 2017). 

Salt-marsh management goals for the refuge focus on maintaining, restoring, and enhancing critical habitat for breeding, 

migrating, and wintering birds. In this study, the regional 

structured decision-making framework was used to help prioritize salt marsh management options for the refuge.

Purpose and Scope

This report describes the application of the regional 

structured decision-making framework (Neckles and others, 

2015) to the Stewart B. McKinney National Wildlife Refuge. 

The regional framework was parameterized to local conditions 

through rapid prototyping, producing a decision model for 

the refuge that can be updated as new information becomes 

available. Included are a suite of potential management actions 

to achieve objectives in two marsh management units at the 

refuge (fig. 2), approximate costs for implementing each 

potential action, predictions for the outcome of each management action relative to individual management objectives, and 

results of constrained optimization to maximize management 

benefits subject to cost constraints. This decision structure can 

be used to understand how specific actions may contribute 

to achieving management objectives and identify an optimum combination of actions, or “management portfolio,” to 

maximize management benefits at the refuge scale for a range 

of potential budgets. The prototype presented here provides a 

framework for continually improving the quality of complex 

management decisions at the Stewart B. McKinney National 

Wildlife Refuge.

Description of Study Area

The Stewart B. McKinney National Wildlife Refuge 

comprises 10 separate parcels along the coast of Connecticut 

(fig. 1). Two of the refuge’s parcels, the Great Meadows and 

Salt Meadow marsh management units, protect extensive salt 

marsh habitat along this highly developed shoreline and are 

the subject of this study. The Great Meadows marsh management unit (fig. 2A) in Stratford contains about 173 ha of salt 

marsh bounded on the northern side by industrial and commercial development and on the southern side by Lewis Gut, 

an embayment that is connected to Long Island Sound. Dikes 

interrupt tidal flow to the northern and northeastern reaches 

of the marsh management unit. Although the northeastern 

section of the marsh management unit is moderately ditched, 

the marsh management unit contains the largest segment of 

unditched high salt marsh in Connecticut (Potvin, 2017). The 

Salt Meadow marsh management unit (fig. 2B) in Westbrook 

contains about 25 ha of salt marsh along the Menunketesuck 

River. The majority of land within 150 m of the unit boundary 

is forest. The marsh management unit is bisected by a railroad bridge over the river that may restrict tidal flow. The salt 

marsh is heavily ditched throughout the entire Salt Meadow 

management unit. During summer 2012, average surfacewater salinities were about 27 parts per thousand (polyhaline 

as defined by Cowardin and others, 1979) within both marsh 

management units (S.C. Adamowicz and T. Mikula, FWS, 

unpub. data, 2017).
6 Optimization of Salt Marsh Management at the Stewart B. McKinney National Wildlife Refuge, Connecticut

Regional Structured Decision-Making 

Framework

A regional framework for assessing and managing salt 

marsh integrity at northeastern NWRs was developed through 

collaborative efforts of FWS regional and refuge managers 

and biologists, salt marsh research scientists, and structured 

decision-making experts. This process followed the discrete 

steps outlined by Hammond and others (1999) and Gregory 

and Keeney (2002):

1. Clarify the temporal and spatial scope of the management decision.

2. Define objectives and performance measures to evaluate 

whether objectives are achieved.

3. Develop alternative management actions for achieving 

objectives.

4. Estimate the consequences or likely outcomes of management actions in terms of the performance measures.

5. Evaluate the tradeoffs inherent in potential alternatives 

and select the optimum alternatives to maximize management benefits.

This sequence of steps was applied through successive 

workshops to refine the decision structure and incorporate 

newly available information. Initial development of the 

structured decision-making framework occurred during a 

week-long workshop in 2008 to define the decision problem, 

specify management objectives, and explore strategies available to restore and enhance salt marsh integrity. During 2008 

and 2009, workshop results were used to guide field tests of 

salt marsh monitoring variables (Neckles and others, 2013). 

Subsequently, in 2012, data and insights gained from these 

field tests were used in a two-part workshop to refine management objectives and develop the means for evaluating management outcomes (Neckles and others, 2015).

From the outset, FWS goals included development of 

an approach for consistent assessment of salt marsh integrity 

across all northeastern NWRs (fig. 1). Within this regional 

context, staff at a given refuge must periodically determine 

the best approaches for managing salt marshes to maximize 

habitat value while considering financial and other constraints. 

The salt marsh decision problem was thus defined as applying to individual NWRs over a 5-year planning horizon. The 

objectives for complex decisions can be organized into a 

hierarchy to help clarify what is most important to decision 

makers (Gregory and others, 2012). The hierarchy of objectives for salt marsh management decisions (table 1) was based 

explicitly on the conservation mission of the NWRS, which 

is upheld through management to “ensure that the biological 

integrity, diversity, and environmental health of the System 

are maintained for the benefit of present and future generations of Americans,” as mandated in the National Wildlife 

Refuge System Improvement Act of 1997 (16 U.S.C. §668dd 

note). Two fundamental objectives, or the overall goals for salt 

marsh management decisions, were drawn from this policy to 

maximize (1) biological integrity and diversity, and (2) environmental health, of salt marsh ecosystems. Participants in the 

prototyping workshops deconstructed these overall goals into 

low-level objectives relating to salt marsh structure and function and identified performance metrics to evaluate whether 

objectives are achieved (table 1). In addition, performance 

metrics were weighted to reflect the relative importance of 

each objective (Neckles and others, 2015).

The hierarchy of objectives for salt marsh management 

(table 1) provides the foundation for identifying possible management actions at individual NWRs and predicting management outcomes. Workshop participants developed preliminary 

influence diagrams (app. 1), or conceptual models relating 

management actions to responses by each performance metric 

(Conroy and Peterson, 2013), to guide this process. To allow 

metric responses to be aggregated into a single, overall performance score, participants also defined value functions relating 

salt marsh integrity metric scores to perceived management 

benefit on a common, unitless “utility” scale (Keeney and 

Raiffa, 1993). Stakeholder elicitation was used to determine 

the form of each value function relating the original metric 

scale to the utility scale, ranging from 0, representing the lowest management benefit, to 1, representing the highest benefit 

(app. 2). Neckles and others (2015) provided details regarding development of the structured decision-making framework and a case-study application to Prime Hook National 

Wildlife Refuge.
Application to the Stewart B. McKinney National Wildlife Refuge 7

Table 1. Objectives hierarchy for salt marsh management decision problems.

[Two fundamental objectives (overall goals of the decision problem) draw directly from National Wildlife Refuge System policy to maintain, restore, and 

enhance biological integrity, diversity, and environmental health within the refuge. These are broken down into low-level objectives focused on specific aspects 

of marsh structure and function. Values in parentheses are weights assigned to objectives, reflecting their relative importance. Weights on any branch of the 

hierarchy sum to one. The weight for each metric is the product of the weights from each level of the hierarchy leading to that metric. NA, not applicable; See 

also Neckles and others (2015)]

Objectives Performance metrics Unit of measurement

Maximize biological integrity and diversity1 (0.5)

Maximize cover of native vegetation 

(0.24)

Cover of native vegetation Percent

Maximize abundance and diversity of 

native nekton (0.18):

NA NA

 Maximize nekton abundance (0.50) Native nekton density Number per square meter

 Maximize nekton diversity (0.50) Native nekton species richness Number of native species

Maintain sustainable populations of 

obligate salt marsh breeding birds 

(0.20)

Abundance of four species of tidal marsh 

obligate birds (clapper rail, willet, saltmarsh 

sparrow, seaside sparrow)

Number per marsh management unit from 

call-broadcast surveys, summed across all 

sampling points in unit

Maximize use by nonbreeding wetland 

birds (0.20)

Abundance of American black duck as indicator speciesRelative abundance for refuge during wintering 

waterfowl season (low, medium, high)2

Maintain trophic structure (0.18) Density of spiders as indicator taxon Number per square meter

Maximize environmental health1 (0.5)

Maintain natural hydrology (0.44): NA NA

Maintain natural flooding regime 

(0.50)

Percent of time marsh surface is flooded relative to ideal reference systemAbsolute deviation from reference in percentage 

points

 Maintain natural salinity (0.50) Surface-water salinity relative to ideal reference systemAbsolute deviation from reference in parts per 

thousand

Maintain the extent of the marsh platform (0.44)Change in marsh surface elevation relative to 

sea-level rise

0=change in elevation is less than amount of sealevel rise; 1=change in elevation greater than 

or equal to amount of sea-level rise

Minimize use of herbicides (0.12) Rate of application 0=no herbicide applied; 1=herbicide applied

1Fundamental objectives of salt marsh management decisions.

2Relative abundance based on local knowledge.

Application to the Stewart B. 

McKinney National Wildlife Refuge

In January 2018, FWS regional biologists, biologists and 

managers from seven northeastern NWR administrative units 

and USGS and Yale University research scientists (table 2) 

participated in a 1.5-day rapid-prototyping workshop to apply 

the regional structured decision-making framework to the 

Maine Coastal Islands, Monomoy, Moosehorn, Parker River, 

Rachel Carson, and Stewart B. McKinney National Wildlife 

Refuges. Participants worked within refuge-specific small 

groups to focus on management issues at individual refuges. 

Plenary discussions of common patterns of salt marsh degradation, potential management strategies, and mechanisms 

of ecosystem response offered additional insights to enhance 

refuge-specific discussions.

Participants identified a range of possible management 

actions for achieving objectives within the Great Meadows 

and Salt Meadow marsh management units at the Stewart B. 

McKinney National Wildlife Refuge and estimated the total 

cost of implementation over a 5-year period; the specific 

years of implementation were not identified in this prototype. 

Potential actions to enhance salt marsh integrity ranged from 

targeted efforts that restore hydrologic connections, control 

predators, or protect shorelines to large-scale projects that alter 

marsh elevation or vegetation succession (table 3). Participants 

predicted the outcomes of each management action 5 years 

after initial implementation in terms of salt marsh integrity 

performance metrics. For most metrics, baseline conditions 

within each unit measured during the 2012–16 salt marsh 

integrity assessment (S.C. Adamowicz and T. Mikula, FWS, 

unpub. data, 2017) were used to predict the outcomes of a 

“no-action” alternative. Baseline conditions were estimated by 

using expert judgement for three metrics that lacked assessment data (abundance of American black ducks, density of 
8 Optimization of Salt Marsh Management at the Stewart B. McKinney National Wildlife Refuge, Connecticut

Table 2. Participants in workshop convened at the Rachel 

Carson National Wildlife Refuge, Maine, to apply a regional 

framework for optimizing salt marsh management decisions to six 

national wildlife refuges in January 2018.

[FWS, U.S. Fish and Wildlife Service; NWR, National Wildlife Refuge; 

USGS, U.S. Geological Survey]

Affiliation Participant

FWS NWR specialists

Maine Coastal Islands NWR Sara Williams

Monomoy NWR Matthew Hillman

Moosehorn NWR Maurice Mills

Moosehorn NWR Keith Ramos

Moosehorn NWR Ray Brown

Parker River NWR Nancy Pau

Parker River NWR Bill Peterson

Rachel Carson NWR Kathleen O’Brien

Rachel Carson NWR Ryan Kleinert

Rachel Carson NWR Bri Benvenuti

Stewart B. McKinney NWR Richard Potvin

Stewart B. McKinney NWR Kristina Vagos

FWS regional experts

Northeast Regional Office Rachel Katz

Northeast Regional Office Troy Wilson

Rachel Carson NWR Susan Adamowicz

Research scientists

USGS Patuxent Wildlife Research Center James Lyons

USGS Patuxent Wildlife Research Center Hilary Neckles

Yale School of Forestry and Environmental 

Studies

Laurel Low

spiders, change in marsh surface elevation relative to sea-level 

rise). Regional influence diagrams relating management strategies to outcomes aided in predicting consequences of management actions (app. 1). Although the influence diagrams incorporated the potential effects of stochastic processes, including 

weather, sea-level rise, herbivory, contaminant inputs, and 

disease, on management outcomes, no attempt was made to 

quantify these sources of uncertainty during rapid prototyping. 

Management predictions also inherently included considerable uncertainty surrounding the complex interactions among 

controlling factors and salt marsh ecosystem components.

Following the workshop, the potential management 

benefit of each salt marsh integrity performance metric was 

calculated by converting salt marsh integrity metric scores 

(table 3, workshop output) to weighted utilities (table 4) using 

regional value functions (app. 2). Weighted utilities were 

summed across all salt marsh integrity metrics for each action; 

this overall utility therefore represented the total management benefit, across all objectives, expected to accrue from a 

given management action (table 4). Constrained optimization 

(Conroy and Peterson, 2013) was used to find the management portfolio (the combination of actions, one action per 

marsh management unit) that maximizes the total management 

benefit across all units under varying cost scenarios for the 

entire the refuge. Constrained optimization using integer linear 

programming was implemented in the Solver tool in Microsoft 

Excel (Kirkwood, 1997).

Budget constraints were increased in $5,000 increments 

up to $25,000; in $25,000 increments up to $100,000; in 

$50,000 increments up to $400,000; in $100,000 increments 

up to $1 million; and in $500,000 increments thereafter. The 

upper limit to potential costs was not determined in advance; 

rather, it reflected the total estimated costs of the proposed 

management actions. A cost-benefit plot of the portfolios 

identified through the optimization analysis was used to 

identify the efficient frontier for resource allocation (Keeney 

and Raiffa, 1993), which is the set of portfolios that are not 

dominated by other portfolios at similar costs (or the set of 

portfolios with maximum total benefit for a similar cost). The 

cost-benefit plot also revealed the cost above which further 

expenditures would yield diminishing returns on investment. To exemplify use of the decision-making framework to 

understand how a given portfolio could affect specific management objectives, the refuge-scale management benefits for 

individual performance metrics were compared between one 

optimal portfolio and those predicted with no management 

action taken.

Results of Constrained Optimization

Management actions identified to improve marsh integrity at the Stewart B. McKinney National Wildlife Refuge 

included adding sediment to the marsh surface to increase 

elevation; restoring natural hydrology through breaching 

or removing dikes, removing tide gates, or restoring basin 

contours or tidal channels; controlling predators; and acquiring land to facilitate marsh migration into adjacent uplands 

(table 3). For costs ranging from $0 to $4.8 million, the estimated management benefits for individual actions across all 

metrics, measured as weighted utilities, ranged from 0.410 (for 

implementing no action in the Great Meadows marsh management unit) to 0.957 (for implementing thin layer deposition 

followed by vegetation planting in the Salt Meadow marsh 

management unit coupled with managing stormwater on 

adjacent lands), out of a maximum possible total management 

benefit of 1.0 (tables 3 and 4). In each marsh management 

unit, the alternative with both the lowest management benefit 

and lowest cost was the “no action” alternative (management 

action A).

Constrained optimization was applied to identify the 

optimal management portfolios over 5 years for a range of 

total costs to the refuge. As total cost increased from $0 (no 

action in either unit) to approximately $6.23 million, the 

total management benefit at the refuge scale increased from 
Results of Constrained Optimization 

9

Table 3. Possible management actions for achieving objectives within 2 marsh management units at Stewart B. McKinney National Wildlife Refuge, Connecticut, estimated costs over 5 years, and predicted outcomes expressed relative to performance metrics.[Potential management actions, costs, and predicted outcomes developed by workshop participants using expert judgement. Predicted consequences of management actions aided by influence diagrams (app. 1). %, percent; ppt, parts per thousand; TLD, thin layer deposition]

Management action

Estimated 

cost over 

5 years

(dollars)

Performance metrics

Native vegetation

(% cover)

Nekton Tidal marsh 

obligate 

birds

(summed 

number per 

point)

American 

black 

ducks

use1

Spider 

density

(number 

per square 

meter)

Hydrology Marsh surface elevation change 

relative to 

sea-level 

rise3

Herbicide 

application4

Density

(number 

of animals 

per square 

meter)

Species 

richness

(number)

Duration 

of surface 

flooding2

(%)

Surfacewater 

salinity2

(ppt)

Great Meadows

A. No action 0 98.4 90 7 1.1 2 1 58.63 0 0 1B. TLD 4,500,000 98.4 94.47 7 2 2 30 0 0 1 1C. TLD with planting 4,781,200 99.5 95 7 2 2 30 0 0 1 1D. Partial TLD 2,812,500 98.4 95 7 2 2 30 0 0 1 1E. Partial TLD with planting in partial 

area 2,988,250 98.7 95 7 2 2 30 0 0 1 1

F. Breach dike and recontour basin 15,000 99.5 110 7 1.37 2 1 55 0 0 0G. Remove tide gate 5,000 99.5 110 7 1.37 2 1 55 0 0 1H. Remove dike and recontour basin 15,000 99.5 110 7 1.6 2 1 55 0 0 1I. Move dikes 1,500 98.4 94.47 7 1.37 2 1 55 0 0 1J. Channels: stabilize banks 25,000 98.4 94.47 7 1.37 2 1 55 0 0 1K. Channels: create new 390,000 99.5 110 7 1.6 2 1 55 0 0 1L. Culverts: additional under road 240,000 98.4 110 7 1.6 2 1 55 2 0 1M. Marsh management for mosquitoes 65,000 99.5 110 7 1.6 2 1 55 0 0 0N. Stormwater management on adjacent lands 525,000 99 110 7 1.1 2 1 55 0 0 1O. Predator control 10,000 98.4 90 7 1.6 2 1 55 0 0 1P. Lessen wave action and sediment 

loss 1,000,000 98.4 94.47 7 1.37 2 1 55 0 0 1

Q. C+H+I 4,797,700 99.9 120 7 3 2 30 55 0 1 0
10 Optimization of Salt Marsh Management at the Stewart B. McKinney National Wildlife Refuge, Connecticut Table 3. Possible management actions for achieving objectives within 2 marsh management units at Stewart B. McKinney National Wildlife Refuge, Connecticut, estimated costs over 5 years, and predicted outcomes expressed relative to performance metrics.—Continued [Potential management actions, costs, and predicted outcomes developed by workshop participants using expert judgement. Predicted consequences of management actions aided by influence diagrams (app. 1). %, percent; ppt, parts per thousand; TLD, thin layer deposition] Management action Estimated cost over 

5 years

(dollars)

Performance metrics

Native vegetation

(% cover)

Nekton Tidal marsh 

obligate 

birds

(summed 

number per 

point)

American 

black 

ducks

use1

Spider 

density

(number 

per square 

meter)

Hydrology Marsh surface elevation change 

relative to 

sea-level 

rise3

Herbicide 

application4

Density

(number 

of animals 

per square 

meter)

Species 

richness

(number)

Duration 

of surface 

flooding2

(%)

Surfacewater 

salinity2

(ppt)

Salt Meadow

A. No action 0 98 45.11 9 2.94 2 1 60.85 0 0 0B. TLD 1,125,000 98 45.11 9 3.5 2 30 0 0 1 0C. TLD with planting 1,195,300 99 45.11 9 3.5 2 30 0 0 1 0D. Stormwater management on adjacent lands 240,000 98 45.11 9 3.2 2 15 30 1 0 0E. Predator control 10,000 98 45.11 9 3 2 1 60.85 0 0 0F. Facilitate marsh migration 31,800 99 45.11 9 2.94 2 1 60.85 0 0 0G. C+D 1,435,300 99 45.11 9 3.6 2 30 0 1 1 0

1Relative abundance for refuge during wintering waterfowl season.2Measures absolute deviation from reference point representing ideal condition.3Measures change relative to sea-level rise: 0, lower than sea-level rise; 1, above sea-level rise.4Measures level of herbicide applied: 0, none applied; 1, some applied.
Results of Constrained Optimization 11

Table 4. Normalized predicted outcomes and estimated total management benefits of possible management actions within 2 marsh management units at the Stewart B. McKinney National Wildlife Refuge, Connecticut.[Numeric table entries are weighted utilities, which were calculated as raw utilities multiplied by objective weights. Unitless raw utilities were derived from metric scores (table 3) using existing regional value functions (app. 2). Objective weights for individual metrics were calculated as the product of the weights on the branch of the objectives hierarchy leading to each metric (table 1). The total management benefit for each action is the sum of weighted utilities across all performance metrics. TLD, thin layer deposition]

Management action

Performance metrics

Total 

management 

benefit

Native vegetation

Nekton Tidal 

marsh 

obligate 

birds

American 

black 

ducks

Spider 

density

Hydrology Marsh 

surface 

elevation 

change

Herbicide 

application Density Species richness Duration of surface flooding Surface- water salinity

Great Meadows

A. No action 0.119 0.040 0.035 0.031 0.075 0.000 0.000 0.110 0.000 0.000 0.410B. TLD 0.119 0.041 0.035 0.056 0.075 0.090 0.110 0.110 0.220 0.000 0.856C. TLD with planting 0.120 0.041 0.035 0.056 0.075 0.090 0.110 0.110 0.220 0.000 0.857D. Partial TLD 0.119 0.041 0.035 0.056 0.075 0.090 0.110 0.110 0.220 0.000 0.856E. Partial TLD with planting 

in partial area 0.120 0.041 0.035 0.056 0.075 0.090 0.110 0.110 0.220 0.000 0.856

F. Breach dike and recontour 

basin 0.120 0.044 0.035 0.038 0.075 0.000 0.000 0.110 0.000 0.060 0.482

G. Remove tide gate 0.120 0.044 0.035 0.038 0.075 0.000 0.000 0.110 0.000 0.000 0.422H. Remove dike and recontour basin 0.120 0.044 0.035 0.044 0.075 0.000 0.000 0.110 0.000 0.000 0.428I. Move dikes 0.119 0.041 0.035 0.038 0.075 0.000 0.000 0.110 0.000 0.000 0.419J. Channels: stabilize banks 0.119 0.041 0.035 0.038 0.075 0.000 0.000 0.110 0.000 0.000 0.419K. Channels: create new 0.120 0.044 0.035 0.044 0.075 0.000 0.000 0.110 0.000 0.000 0.428L. Culverts: additional under 

road 0.119 0.044 0.035 0.044 0.075 0.000 0.000 0.110 0.000 0.000 0.428

M. Marsh management for 

mosquitoes 0.120 0.044 0.035 0.044 0.075 0.000 0.000 0.110 0.000 0.060 0.488

N. Stormwater management 

on adjacent lands 0.120 0.044 0.035 0.031 0.075 0.000 0.000 0.110 0.000 0.000 0.414

O. Predator control 0.119 0.040 0.035 0.044 0.075 0.000 0.000 0.110 0.000 0.000 0.424P. Lessen wave action and 

sediment loss 0.119 0.041 0.035 0.038 0.075 0.000 0.000 0.110 0.000 0.000 0.419

Q. C+H+I 0.120 0.045 0.035 0.083 0.075 0.090 0.110 0.110 0.220 0.060 0.948
12 Optimization of Salt Marsh Management at the Stewart B. McKinney National Wildlife Refuge, Connecticut Table 4. Normalized predicted outcomes and estimated total management benefits of possible management actions within 2 marsh management units at the Stewart B. McKinney National Wildlife Refuge, Connecticut.—Continued [Numeric table entries are weighted utilities, which were calculated as raw utilities multiplied by objective weights. Unitless raw utilities were derived from metric scores (table 3) using existing regional value functions (app. 2). Objective weights for individual metrics were calculated as the product of the weights on the branch of the objectives hierarchy leading to each metric (table 1). The total management benefit for each action is the sum of weighted utilities across all performance metrics. TLD, thin layer deposition] Management action Performance metrics Total manage- ment benefit Native veg- etation Nekton Tidal marsh obligate birds American black ducks Spider density Hydrology Marsh surface elevation change Herbicide application Density Species richness Duration of surface flooding Surface- water salinity Salt Meadow A. No action 0.119 0.028 0.045 0.082 0.075 0.000 0.000 0.110 0.000 0.060 0.518 B. TLD 0.119 0.028 0.045 0.097 0.075 0.090 0.110 0.110 0.220 0.060 0.954 C. TLD with planting 0.120 0.028 0.045 0.097 0.075 0.090 0.110 0.110 0.220 0.060 0.954 D. Stormwater management on adjacent lands 0.119 0.028 0.045 0.089 0.075 0.045 0.037 0.110 0.000 0.060 0.607 E. Predator control 0.119 0.028 0.045 0.083 0.075 0.000 0.000 0.110 0.000 0.060 0.520 F. Facilitate marsh migration 0.120 0.028 0.045 0.082 0.075 0.000 0.000 0.110 0.000 0.060 0.519 G. C+D 0.120 0.028 0.045 0.100 0.075 0.090 0.110 0.110 0.220 0.060 0.957
Results of Constrained Optimization 13

0.928 to 1.905 (a 105 percent increase; table 5) out of a possible maximum of 2.0 (the maximum possible management 

benefit of 1.0 for any management action, summed across the 

two marsh management units). Graphical analysis showed 

a fairly consistent increase in management benefit as costs 

increased to $1.19 million (fig. 3, portfolio 9). Portfolio 9 

represented the turning point in the cost-benefit plot. As 

expenditures increased beyond the cost of portfolio 9, total 

management benefit continued to increase but at a lower rate, 

yielding diminishing returns on investment; there was very 

little gain in management benefit for expenditures greater than 

about $3.9 million (fig. 3, portfolio 14).

Several patterns emerged relative to management actions 

selected within the set of portfolios that yielded the greatest total management benefit per unit cost (table 5, portfolios 

2 through 9). The lowest-cost portfolios (total cost up to 

$250,000) always included predator control at one or the other 

of the marsh management units. In addition, portfolios at the 

Great Meadows marsh management unit included actions to 

restore hydrologic connections or integrated management 

for mosquito control, whereas portfolios at the Salt Meadow 

marsh management unit included primarily stormwater 

management on adjacent lands. In contrast, some management 

actions were never or rarely included in the portfolios yielding 

the greatest benefit per cost. For example, stormwater management on adjacent lands and adding culverts or channels were 

never selected for the Great Meadows marsh management 

unit, and facilitating marsh migration into the uplands was 

never selected for the Salt Meadow marsh management unit. 

At both marsh management units, thin layer deposition was 

only selected when the available budget exceeded $1 million.

Examination of the refuge-scale metric responses to 

actions included in portfolio 9, which is the turning point in 

the cost-benefit plot (fig. 3), revealed how implementation 

could affect specific management objectives. The actions 

included were predicted to achieve large gains in the overall management benefits derived from density of spiders (as 

an indicator of trophic health), duration of flooding, and the 

capacity of marsh elevation to keep pace with sea-level rise 

and modest gains in the benefits derived from numbers of 

tidal marsh obligate birds and herbicide application (fig. 4). 

Ecologically, the combination of actions in portfolio 9 may 

result in an average 32 percent increase in tidal marsh obligate 

bird counts (averaged across both marsh management units), 

0.9

1.0

1.1

1.2

1.3

1.4

1.5

1.6

1.7

1.8

1.9

2.0

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0

Total management benefit [dimensionless]

Total cost, in millions of dollars

EXPLANATION

 1 Management portfolio—Actions and salt marsh units

that create each portfolio are listed in table 5

Frontier of most efficient resource allocation 

1817

15 16

14

1312 11

6

7

10 9 

8

1

2,3

4,5

Figure 3. Predicted total management benefit of various portfolios, expressed as weighted utilities, 

relative to total cost at the Stewart B. McKinney National Wildlife Refuge in Connecticut. Each 

portfolio (dot with number) represents a combination of two management actions, one per marsh 

management unit, as identified in table 5. The line represents the efficient frontier for resource 

allocation.
14 Optimization of Salt Marsh Management at the Stewart B. McKinney National Wildlife Refuge, Connecticut

Table 5. Actions included in various management portfolios to 

maximize the total management benefits subject to increasing 

cost constraints at the Stewart B. McKinney National Wildlife 

Refuge, Connecticut.

[Letter designations for actions refer to specific actions and are listed in tables 

3 and 4. Portfolios represent the combination of actions, one per marsh management unit, that maximized the total management benefit across all units, 

subject to a refuge-wide cost constraint. The management actions constituting individual portfolios were selected using constrained optimization. The 

total cost represents the sum of costs estimated for each action included in the 

portfolio. The maximum possible total management benefit for the refuge is 

2, derived as the maximum possible total management benefit of 1.0 for any 

management action within one management unit, summed across 2 units]

Portfolio

Marsh management 

unit Total cost 

(dollars)

Total manageGreat ment benefit

Meadows

Salt 

Meadow

1 A A 0 0.928

2 G A 5,000 0.940

3 O A 10,000 0.943

4 F E 25,000 1.002

5 M E 75,000 1.008

6 O D 250,000 1.032

7 F D 255,000 1.089

8 M D 305,000 1.095

9 M B 1,190,000 1.442

10 M C 1,260,300 1.442

11 M G 1,500,300 1.445

12 D D 3,052,500 1.464

13 E D 3,228,250 1.464

14 D B 3,937,500 1.810

15 D G 4,247,800 1.813

16 E G 4,423,550 1.813

17 Q C 5,993,000 1.903

18 Q G 6,233,000 1.905

53 percent decrease in the deviation of surface flooding from 

the ideal reference condition, and 1,450 percent increase in 

spider density (derived as the average difference between the 

predicted metric scores for the actions implemented in portfolio 9 and the “no-action” alternative; table 3). Implementation 

of actions in this portfolio was also predicted to improve the 

capacity for marsh elevation to keep pace with sea-level rise in 

the Salt Meadow marsh management unit and reduce application of herbicides in the Great Meadows marsh management 

unit. The management benefits predicted for portfolios 1 

through 8, at total costs up to $305,000, were derived primarily from expected improvements in surface-water drainage, 

presumed increases in densities of spiders and numbers of 

tidal marsh obligate birds, and reduced need for herbicide 

application (tables 3 and 4).

Considerations for Optimizing Salt 

Marsh Management

A regional structured decision-making framework for 

salt marshes on NWRs in the northeastern United States was 

applied by the USGS, in cooperation with the FWS, to develop 

a tool for optimizing management decisions at the Stewart 

B. McKinney National Wildlife Refuge. Use of the existing 

regional framework and a rapid-prototyping approach permitted NWR biologists and managers, FWS regional authorities, and research scientists to construct a decision model for 

the refuge within the confines of a 1.5-day workshop. This 

preliminary prototype provides a local framework for decision 

making while revealing information needs for future iterations. 

Insights from this process may also be useful to inform future 

habitat management planning at the refuge.

The suite of potential management actions and predicted 

outcomes included in this prototype (table 3) were based on 

current understanding of the Stewart B. McKinney National 

Wildlife Refuge salt marshes and hypothesized processresponse pathways (app. 1). Tidal flooding is the predominant physical control on the structure and function of salt 

marsh ecosystems (Pennings and Bertness, 2001), and there 

is widespread scientific effort to elucidate how salt marshes 

may respond to accelerating rates of sea-level rise and management strategies to enhance their sustainability (Kirwan 

and Megonigal, 2013; Roman, 2017). Many salt marshes 

throughout the northeastern United States are degraded by 

roads, dikes, railroads, or other obstructions to tidal flow, and 

salt marsh restoration frequently focuses on reestablishing 

tidal flow (Konisky and others, 2006; Roman and Burdick, 

2012). Actions to restore tidal exchange throughout the Great 

Meadows marsh management unit were predicted to improve 

overall management benefit for a relatively low cost. In 

contrast, thin-layer deposition of sediments to raise marsh 

elevation is increasingly proposed to enhance sustainability 

of salt marshes in the northeastern United States (Wigand 

and others, 2017) and was identified as a potential action to 

improve the integrity of both marsh management units at the 

Stewart B. McKinney National Wildlife Refuge with expected 

high total management benefit (table 4). However, the high 

cost of implementation restricted this option to the most costly 

portfolios (table 5, portfolios 9 through 18).

Multiple, interacting factors influence the long-term success of restoration actions in prolonging marsh integrity and 

improving marsh resilience (Roman, 2017). Future iterations 

of this decision model can incorporate improved understanding of both implementation costs and marsh responses to 

management actions. In addition, during construction of the 

regional decision model, lack of widely available data on rates 

of vertical marsh growth led to the adoption of a very coarse 

scale of measurement for change in marsh surface elevation 

relative to sea-level rise (table 1). In 2012, surface elevation 

tables (Lynch and others, 2015) were installed in each marsh 

management unit to obtain high-resolution measurements 
Considerations for Optimizing Salt Marsh Management 15

0 0.1 0.2 0.3

Native vegetation cover

Nekton density

Nekton species richness

Tidal marsh obligate 

breeding birds

American black ducks 

in winter

Spider density

Flooding duration

Surface-water salinity

Marsh surface 

elevation change

Herbicide application

 Refuge-scale management benefit, dimensionless

No action

Portfolio 9

EXPLANATION

Figure 4. Predicted management benefit at the refuge scale for individual performance metrics, 

expressed as weighted utilities, resulting from implementation of the management actions included 

in portfolio 9, in comparison to the management benefit from the baseline “no-action” portfolio, at 

the Stewart B. McKinney National Wildlife Refuge in Connecticut. Baseline (“no-action”) predicted 

management benefit for spider density, flooding duration, and marsh surface elevation change are 

zero. The actions included in each portfolio are listed in table 5.

of change in marsh surface elevation (S.C. Adamowicz and 

T. Mikula, FWS, unpub. data, 2017). Incorporating this information into subsequent iterations of this structured decisionmaking framework would likely improve predictions related 

to the potential for marsh surface elevation to keep pace with 

sea-level rise.

Results of constrained optimizations (table 5) based on 

the objectives, management actions, and predicted outcomes 

included in this prototype identified four areas in which to 

improve the utility of the prototype for refuge decision making. First, although increasing the rate of marsh elevation gain 

relative to sea-level rise is a primary management concern at 

the Stewart B. McKinney National Wildlife Refuge, enhancing elevation directly through sediment deposition may be 

cost prohibitive for these salt marshes. Therefore, alternative 

options to reduce the depth and duration of surface flooding, 

such as digging runnels to improve surface drainage, may be 

more feasible (Wigand and others, 2017). Additionally, testing targeted actions to mitigate effects of flooding on at-risk 

species, such as creation of floating islands as nesting sites for 

saltmarsh sparrows, may be useful (Benvenuti, 2016).

Second, actions to minimize marsh loss through stabilizing channel banks or lessening wave action were excluded 

from the optimal portfolios. Deconstructing the objective of 

maintaining the extent of the marsh platform into subordinate 

objectives and performance metrics related to both horizontal and vertical gains and losses of marsh substrate may help 

focus decision making on erosion of marsh edges.

Third, although implementing integrated marsh management for mosquito control, which is a comprehensive 

approach to restoring tidal hydrology and reducing mosquitoes 

(Rochlin and others, 2012), was predicted to enhance abundance of nekton and tidal marsh obligate birds and reduce 

application of herbicide for Phragmites control at the Great 

Meadows unit (table 3), the regional environmental health 

objectives included in this prototype did not accommodate a 

potential additional benefit of reducing or eliminating use of 

insecticides to control mosquitoes. The mosquito management 

plan for the Great Meadows unit emphasized that to minimize 

use of insecticides on the refuge, hydrologic restoration should 

be employed where possible to decrease mosquito production (Potvin, 2017). In the future, including an objective in 
16 Optimization of Salt Marsh Management at the Stewart B. McKinney National Wildlife Refuge, Connecticut

the decision model related to minimizing insecticides would 

incorporate the effect of integrated marsh management on total 

pesticide use, including herbicides and insecticides, into the 

total management benefits.

Finally, the constrained optimizations analyzed in this 

report were based on approximations of management costs. 

As salt marsh management is undertaken around the region, 

a detailed list of actual expenses can be compiled, including 

staff time for project planning as well as materials, equipment, 

contracts, and staff time for implementation. This will allow 

future iterations of the decision model to include more accurate cost estimates.

The prototype model for the Stewart B. McKinney 

National Wildlife Refuge provides a useful tool for decision 

making that can be updated in the future with new data and 

information. The spatial and temporal variability inherent in 

parameter estimates were not quantified during rapid prototyping. Previously, preliminary sensitivity analysis revealed 

little effect of incorporating ecological variation in abundance 

of marsh-obligate breeding birds on the optimal solutions for 

Prime Hook National Wildlife Refuge (Neckles and others, 

2015). This lends confidence to use of this framework for 

decision making; however, including probability distributions 

for each performance metric in the decision model could be a 

high priority for future prototypes. Future monitoring of salt 

marsh integrity performance metrics will be useful to refine 

baseline parameter estimates and to determine the background 

rate of change in the absence of management actions; feedback from measured responses to management actions around 

the region will help reduce uncertainties surrounding management predictions. The structured decision-making framework 

applied here to the Stewart B. McKinney National Wildlife 

Refuge is based on a hierarchy of regional objectives and 

regional value functions relating performance metrics to perceived management benefits. It will be important to ensure that 

subsequent iterations reflect evolving management objectives 

and desired outcomes. Elements of the decision model could 

be further adapted, for example through differential weighting of objectives or altered value functions, to reflect specific, 

local management goals and mandates. Future optimization analyses that use this framework could also incorporate 

additional constraints on action selection, such as ensuring 

that particular actions within individual marsh management 

units are included in optimal management portfolios, to further 

tailor the model to refuge-specific needs.

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W.G., and Adamowicz, S.C., 2015, Use of structured decision making to identify monitoring variables and management priorities for salt marsh ecosystems: Estuaries 

and Coasts, v. 38, no. 4, p. 1215–1232. [Also available at 

https://doi.org/10.1007/s12237-014-9822-5.]

Pennings, S.C., and Bertness, M.D., 2001, Salt marsh communities, in Bertness, M.D., Gaines, S.D., and Hay, M.E., eds., 

Marine community ecology: Sunderland, Mass., Sinauer 

Associates, p. 289–316.

Potvin, R.A., 2017, Mosquito management plan and final 

environmental assessment for the Great Meadows Unit at 

Stewart B. McKinney National Wildlife Refuge: U.S. Fish 

and Wildlife Service, 315 p., accessed July 6, 2020, at 

https://ecos.fws.gov/ServCat/DownloadFile/146860?

Reference=98175.

Rochlin, I., James-Pirri, M.J., Adamowicz, S.C., Wolfe, R.J., 

Capotosto, P., Dempsey, M.E., Iwanejko, T., and Ninivaggi, 

D.V., 2012, Integrated marsh management (IMM)—A new 

perspective on mosquito control and best management 

practices for salt marsh restoration: Wetlands Ecology and 

Management, v. 20, no. 3, p. 219–232. [Also available at 

https://doi.org/10.1007/s11273-012-9251-9.]

Roman, C.T., 2017, Salt marsh sustainability—Challenges 

during an uncertain future: Estuaries and Coasts, v. 40, 

no. 3, p. 711–716. [Also available at https://doi.org/10.1007/

s12237-016-0149-2.]

 Roman, C.T., and Burdick, D.M., eds., 2012, Tidal marsh 

restoration—A synthesis of science and practice: 

Washington, D.C., Island Press, 406 p.

Steinkamp, M., 2008, New England/mid-Atlantic coast 

bird conservation region (BCR 30) implementation plan: 

Atlantic Coast Joint Venture final plan, 251 p., accessed 

August 15, 2018, at https://www.acjv.org/BCR_30/BCR30_

June_23_2008_final.pdf.

U.S. North American Bird Conservation Initiative, 2020, 

Bird conservation regions: U.S. North American Bird 

Conservation Initiative web page, accessed July 6, 2020, at 

https://nabci-us.org/resources/bird-conservation-regions/.

Wigand, C., Ardito, T., Chaffee, C., Ferguson, W., Paton, 

S., Raposa, K., Vandemoer, C., and Watson, E., 2017, A 

climate change adaptation strategy for management of 

coastal marsh systems: Estuaries and Coasts, v. 40, no. 3, 

p. 682–693. [Also available at https://doi.org/10.1007/

s12237-015-0003-y.]
18 Optimization of Salt Marsh Management at the Stewart B. McKinney National Wildlife Refuge, Connecticut

Appendix 1. Regional Influence Diagrams

The influence diagrams (following the style of prototype diagrams in Neckles and others, 2015) in this appendix (figs. 1.1–1.8) relate possible management strategies to 

performance metrics. Shapes represent elements of decisions, 

as follows: rectangles for actions, rectangles with rounded 

corners for deterministic factors, ovals for stochastic events, 

and hexagons for consequences expressed as a performance 

metric.

Trap or deposit

sediment

Restore

topography: fill

ditches, create

pools and channels

Restore tidal

flooding

Reduce upland

runoff

Control invasive

species

Plant native

species

Elevation

Soil oxygen

Soil salinity

Nutrient

availability

Physical

disturbance

Plant growth rate

Community

composition

Percent cover

of native species

Herbivory

Flood frequency,

duration, depth

Disease

Figure 1.1. Influence diagram used to estimate percent cover of native vegetation in response to implementing certain management 

actions.
Appendix 1. Regional Influence Diagrams 19

Predation

Marsh surface

elevation

Environmental

contaminants

Structure and

dynamics of

native nekton

community

Exotic species

Native nekton

density and species

richness

Restore native vegetation

buffer along upper

marsh edge

Reduce excess nutrient

enrichment from 

watershed

Restore natural hydrology

Eliminate contaminant

sources

Water chemistry/water quality

(temperature, salinity, dissolved

oxygen, suspended sediments)

Flood frequency,

duration, and depth

Native marsh vegetation

Figure 1.2. Influence diagram used to estimate nekton density and species richness in response to implementing certain management 

actions.
20 Optimization of Salt Marsh Management at the Stewart B. McKinney National Wildlife Refuge, Connecticut

Control predators

Maintain or restore

natural hydrology

Maintain or restore

native vegetation

communities

Acquire salt marsh

habitat

Remove barriers to

allow for marsh

transgression

Mitigate contaminant

loads

Predation

Flooding

Native vegetation

cover

Patch size

Contaminants

Severe

weather

Sea-level

rise

Abundance of tidal

marsh obligate

breeding birds

Figure 1.3. Influence diagram used to estimate abundance of tidal marsh obligate breeding birds in response to implementing certain 

management actions.
Appendix 1. Regional Influence Diagrams 21

Restore tidal flow

Plant native

vegetation

Plug ditches

Excavate fill

Integrated marsh

management

Apply herbicides to

invasive species

Available native

vegetation cover

Available animal food

Abundance of

American black

ducks

Winter weather

Winter survival and

spring recruitment

Available plant food Annual population size

Figure 1.4. Influence diagram used to estimate abundance of American black ducks in winter, as indicator species for nonbreeding 

wetland birds, in response to implementing certain management actions.
22 Optimization of Salt Marsh Management at the Stewart B. McKinney National Wildlife Refuge, Connecticut

Weather

Disease

Density of

spiders

Population

abundance from

prior year

Plant buffer of

native vegetation

Plant community

Bird predators

Area of open water

relative to marsh area

Apply herbicide

to invasive plants

Apply pesticides

Control stormwater

Fill ditches

Create pools

Adjust surface

contours

Add perimeter

ditch

Add radial ditch

Restore tidal flow

Figure 1.5. Influence diagram used to estimate density of spiders, as indicator of trophic health, in response to implementing certain 

management actions.
Appendix 1. Regional Influence Diagrams 23

Plant vegetation

Marsh elevation

Ditch density

Freshwater

input

Tidal exchange

with bay or ocean

Tidal creek

density

Deposit dredge spoil

Trap sediment

Apply herbicide

to Phragmites

Divert freshwater

Increase culvert size

Excavate channels

Manipulate hydrologic

connections for

mosquito control

Sea-level rise

Percent of time

marsh surface

is flooded

Salinity of

surface water

Figure 1.6. Influence diagram used to estimate percent of time marsh surface is flooded and salinity of marsh surface water in 

response to implementing certain management actions.
24 Optimization of Salt Marsh Management at the Stewart B. McKinney National Wildlife Refuge, Connecticut

Control herbivore

populations

Excavate ditches

Increase culvert size

Add sediment

Herbivory

Soil salinity

Flood frequency,

duration, depth

Sedimentation

rate

River discharge

Subsidence

Storms

Fire

Vegetation density

Subsurface

organic

accumulation

Change in elevation

relative to sea-level rise

Sea-level rise

Figure 1.7. Influence diagram used to estimate change in elevation of the marsh surface relative to sea-level rise in response to 

implementing certain management actions.

Apply herbicide

Plant growth

rate

Invasive

patch size

Volume of

herbicide

applied for

management

Figure 1.8. Influence diagram used to estimate volume of 

herbicide that would be applied if decision was made to use 

chemical control for removing unwanted vegetation.

Reference Cited

Neckles, H.A., Lyons, J.E., Guntenspergen, G.R., Shriver, 

W.G., and Adamowicz, S.C., 2015, Use of structured decision making to identify monitoring variables and management priorities for salt marsh ecosystems: Estuaries 

and Coasts, v. 38, no. 4, p. 1215–1232. [Also available at 

https://doi.org/10.1007/s12237-014-9822-5.]
Appendix 2. Utility Functions for the Stewart B. McKinney National Wildlife Refuge 25

Appendix 2. Utility Functions for the Stewart B. McKinney National 

Wildlife Refuge

Utilities [u(x)] are derived as monotonically increasing, 

monotonically decreasing, or step functions over the range of 

performance metric x. In the functions in figures 2.1 through 

2.10, x, Low, High, and ρ are expressed in performance metric 

units; Low and High represent the endpoints of the given 

metric range for the Stewart B. McKinney National Wildlife 

Refuge; and ρ represents a shape parameter derived by stakeholder elicitation (Neckles and others, 2015). Break points in 

step functions were also derived by stakeholder elicitation.

0 20 40 60 80 100

0

0.2

0.4

0.6

0.8

1

Utility [dimensionless]

Native vegetation, in percent cover

( )

( )

( )

1

1

x Low

High Low

e u x

e

ρ

ρ

− −

− −

− =

−

where

Low = 0

High = 100

ρ = 50

Figure 2.1. Native vegetation at the Stewart B. McKinney National Wildlife Refuge, Connecticut.

0.00

0.20

0.40

0.60

0.80

1.00

0 20 40 60 80 100 120

Utility [dimensionless]

Nekton density, in number of animals per square meter

( )

( )

( )

1

1

x Low

High Low

e u x

e

ρ

ρ

− −

− −

− =

−

where 

Low = 0

High= 120

ρ = 60

Figure 2.2. Native nekton density at the Stewart B. McKinney National Wildlife Refuge, Connecticut.
26 Optimization of Salt Marsh Management at the Stewart B. McKinney National Wildlife Refuge, Connecticut

where

Low = 0

High = 9

( ) x Low u x High Low

− = −

0.0

0.2

0.4

0.6

0.8

1.0

0 2 4 6 8 10

Utility [dimensionless]

Nekton richness, in number of species

Figure 2.3. Native nekton species richness at the Stewart B. McKinney National Wildlife Refuge, Connecticut.

where

Low = 0

High = 3.6

( ) x Low u x High Low

− = −

0.0

0.2

0.4

0.6

0.8

1.0

0 1 2 3 4

Utility [dimensionless]

Birds, summed number per point

Figure 2.4. Tidal marsh obligate birds at the Stewart B. McKinney National Wildlife Refuge, Connecticut.

Low Medium High

0

0.2

0.4

0.6

0.8

1

Utility [dimensionless]

Ducks, relative abundance during winter

If x = Low, then u(x) = 0

If x = Medium, then u(x) = 0.75

If x = High, then u(x) = 1

Figure 2.5. American black ducks at the Stewart B. McKinney National Wildlife Refuge, Connecticut.
Appendix 2. Utility Functions for the Stewart B. McKinney National Wildlife Refuge 27

0

0.2

0.4

0.6

0.8

1

0 15 30

Utility [dimensionless]

Spiders, number per square meter

If x ≤ 15, then ( ) 1 0.5

14

x u x − = ×

If x > 15, then ( ) 15 0.5 (0.5

15

x u x − = + × )

Figure 2.6. Marsh spiders at the Stewart B. McKinney National Wildlife Refuge, Connecticut.

0 10 20 30 40 50 60 70 80 90 100

0

0.2

0.4

0.6

0.8

1

Percent of time (absolute deviation from reference)

Utility [dimensionless]

If x ≤ 10, then u(x) = 1

If x ≥ 40, then u(x) = 0

If 10 < x < 40, then ( ) 10 1

30

x u x − = −

Figure 2.7. Duration of surface flooding at the Stewart B. McKinney National Wildlife Refuge, Connecticut.

If x ≤ 10, then u(x) = 1

If x ≥ 25, then u(x) = 0

If 10 < x < 25, then ( ) 10 1

15

x u x − = −

0

0.2

0.4

0.6

0.8

1

0 10 20 30 40

Utility [dimensionless]

Salinity, in parts per thousand (absolute deviation from reference) 

Figure 2.8. Salinity of surface water at the Stewart B. McKinney National Wildlife Refuge, Connecticut.
28 Optimization of Salt Marsh Management at the Stewart B. McKinney National Wildlife Refuge, Connecticut

0 1

0

0.2

0.4

0.6

0.8

1

Utility [dimensionless]

Marsh surface elevation change relative to sea-level rise

( ) x Low u x High Low

− = −

where 

Low = 0, lower than

sea-level rise

High = 1, above 

sea-level rise

Figure 2.9. Change in marsh surface elevation relative to sea-level rise at the Stewart B. McKinney National Wildlife Refuge, 

Connecticut.

0

0.2

0.4

0.6

0.8

1

0 0.2 0.4 0.6 0.8 1

Utility [dimensionless]

Herbicide, in pints

( ) High x u x High Low

− = −

where 

Low = 0

High = 1

Figure 2.10. Application of herbicides at the Stewart B. McKinney National Wildlife Refuge, Connecticut.

Reference Cited

Neckles, H.A., Lyons, J.E., Guntenspergen, G.R., Shriver, 

W.G., and Adamowicz, S.C., 2015, Use of structured decision making to identify monitoring variables and management priorities for salt marsh ecosystems: Estuaries 

and Coasts, v. 38, no. 4, p. 1215–1232. [Also available at 

https://doi.org/10.1007/s12237-014-9822-5.]
For more information, contact:

U.S. Geological Survey

Director, Patuxent Wildlife Research Center

12100 Beech Forest Road

Laurel, MD 20708-4039

https://www.usgs.gov/centers/pwrc

Publishing support provided by the

Pembroke Publishing Service Center
Low and others—Optimization of Salt Marsh Management at the Stewart B. McKinney National Wildlife Refuge, Connecticut—OFR 2020–1139

ISSN 2331-1258 (online)

https://doi.org/10.3133/ofr20201139