**Implementing the Strategic Habitat Conservation (SHC) Framework within
the St. Joseph Watershed in Michigan, Ohio, and Indiana**

*A Case Study from the FWS/USGS Structured Decision Making Workshop:
Strategic Habitat Conservation -- Region 3*

*January 14-18, 2008, LaCrosse, WI, USA*

Authors: Barbara Hosler[^1], Jean Cochrane[^2], Mike Estey[^3], Jennifer
Szymanski[^4], James Boase[^5], Jeff Finn[^6], Richard Geboy[^7], Jim
Hazelman[^8], Jeff Kiefer[^9], Bruce Kingsbury[^10], T.J. Miller[^11],
Donna C. Brewer[^12], Anthony Starfield[^13]

# Decision Problem

The primary factor limiting the Copperbelly Water Snake (CWS) population
has been identified as habitat loss and fragmentation. Several Priority
1 recovery actions in the CWS draft recovery plan involve the
conservation of habitat complexes sufficient for CWS recovery, such as
identifying focal management areas, developing guidelines for habitat
restoration and enhancement, working with landowners and agency land
managers, and developing and implementing habitat conservation programs.
Our challenge is to determine how to create the landscape to meet the
population objectives for the CWS within existing constraints and to
reverse the population decline in the next five years.

# Background

## Legal, regulatory, and political context

The Northern Distinct Population Segment (NDPS) of the CWS is federally
listed as threatened under the Endangered Species Act of 1973, as
amended. The CWS is found primarily on private lands with the exception
of the Lake La Su An State Wildlife Area in Ohio. The Ohio Department of
Natural Resources (ODNR) manages the area for fishing and grassland
birds. A Draft Recovery Plan for CWS was issued in September of 2007.
Critical habitat has not been designated for this species.

*Ecological context*

The CWS NDPS occurs in the St. Joseph River watershed (Lake Erie
drainage) in the tri-state area of Michigan, Indiana, and Ohio. The CWS
is associated with shallow wetlands, such as scrub-shrub, emergent, and
margins of open water, within an upland forest matrix. The snakes use
scrub-shrub wetlands for basking and forage for amphibians in shallow
wetlands. The CWS is a vagile species, inhabiting a large home range (15
hectares) for a water snake. The CWS requires a diversity of
wetlands---different types of palustrine wetlands as well as ephemeral
wetlands of varying depths. The snake utilizes uplands as travel
corridors and also as foraging habitat in summer if their ephemeral
wetlands are dry. The CWS hibernates in crayfish burrows in forested
wetlands. The primary threat to CWS is habitat loss and fragmentation.

# Decision Structure

Because of its precipitous population decline, the CWS was already
established as a Region 3 priority species. For several reasons,
including existing cross-programmatic cooperation, the St. Joseph
watershed was selected as a focal area for SHC in the region. Thus, our
decision structure began from this point, with a focal species
pre-selected and an emphasis on the Service's Partners for Fish and
Wildlife (PFW) program.

Our decision structure evolved over the course of the workshop, based on
choices made to get prototypes started and to focus our work further.
For example, the PFW program lacks a standard method for differentiating
amongst habitat restoration projects for the CWS, as well as targeting
the areas which would most likely enhance CWS populations. Hence, part
of our decision structure focused on the PFW program actions and
specific alternatives. In addition, we agreed to use the population
objectives from the draft Recovery Plan, but also to set a concrete goal
of reversing the population decline within the next five years.
Ultimately, our decision structure involved the development of three
tools/models to assist the PFW program and to meet the population
objectives for the CWS.

## Alternative actions

Potential restoration activities could occur 1) on private lands around
known locations of CWS populations, 2) on private lands without recent
records of CWS, and 3) on public land with known locations of CWS.

## Objectives 

1)  At least one population of CWS exceeds 1,000 adults. In addition,
    five geographically distinct populations of CWS are more than 500
    individuals, or three metapopulations have a total population size
    of 3,000 with none less than 500.

2)  The NDPS of CWS is stable or increasing in the next five years.

## Predictive model

We developed three models/tools:

1)  a GIS-based, spatially explicit habitat model to predict CWS
    occurrence and prioritize restoration activities based on biology of
    CWS and geography of the St. Joseph watershed;

2)  a decision matrix for the PFW program, directly tied to the GIS
    model, but also incorporating the most important economical and
    practical parameters to PFW biologists; and

3)  a stochastic demographic population model for CWS to test our
    population objectives, i.e., will 1,000 individuals provide a
    probability of extinction \<10% for 100 years?

# Decision Analysis

We developed the following three tools at the workshop as prototypes to
test our concepts. Although preliminary, these early prototypes were
useful in showing how these approaches could be used and why they are
worth pursuing.

[Restoration Model]{.underline}

The first goal of the habitat restoration model was to identify areas
that satisfy all needs of the CWS within the existing landscape. We
located patches where habitat needs are met and identified habitat
complexes comprised of patches of suitable habitat and safe connecting
corridors. Then we added constraints of barriers**,** such as roads, to
display the habitat complex extent, now and in future. An example of
this map is shown in Figure 1.

The second goal was to identify potential restoration areas and their
restoration requirements. We used soils maps to identify areas suitable
for wetland restoration and National Wetland Inventory maps, in
conjunction with aerial photographs, to locate existing wetlands that
are lacking the surrounding forest matrix necessary for the CWS.

The third goal was to rank the potential restoration sites in terms of
their value to recovery of the CWS. This will require running
simulations of the model, adding restored habitat to identify which
sites provide the greatest improvement to the existing habitat
complexes. This will generate a landscape map, depicting recovery
values. With this in place, we can overlay property boundaries onto the
recovery value landscape to indicate the relative value of each parcel
for CWS recovery.

[PFW Decision Matrix]{.underline}

To assist the PFW program biologists, we developed a ranking system to
differentiate amongst PFW projects for the CWS across the tri-state
area. In selecting restoration sites, PFW biologists need to consider
not only biological aspects, but also economical and practical
(real-world) parameters. We utilized the SMART (Simple Multi Attribute
Ranking Technique) tool for development of the decision matrix. The
matrix includes seven attributes, which were weighted based on factors
that are most important in differentiating amongst potential CWS habitat
restoration projects. We then used hypothetical projects that could be
encountered in private lands work, with various combinations of
restorable habitats (e.g., large wetland, small wetland complex, wetland
and tree planting, tree planting only, etc.), to conduct a sensitivity
analysis on the various attributes and their weightings to insure that
the output of the decision tool made sense from a biological, as well as
a programmatic, standpoint.

The decision matrix, with hypothetical projects, is presented in
Table 1. The seven attributes are described below:

CWS Score -- The CWS attribute was considered the most heavily weighted
attribute but was not an absolute driver of the ranking process.

Lag Time -- We included this attribute to differentiate amongst those
projects that provide an immediate functional benefit (e.g., wetland
restoration or tree planting in an agricultural field) versus those
projects where the functional benefit is delayed (e.g., tree planting in
sod).

Total Cost/Acre -- Using total cost per acre allowed us to weight
projects within and amongst different habitats equally.

Difficulty -- This attribute could be viewed as the most subjective
attribute; therefore, we classified the most common obstacles we face as
PFW biologists, recognizing the types of obstacles may vary across
states.

Priority Species -- Examples include other federally listed endangered
and/or threatened species, migratory birds, and non-trust resource
species (e.g., state listed species).

Cost Share -- This is a measure of the proportion of the cost of a
project that the landowner bears.

Agreement Duration -- Restorations conducted under the PFW program
require the landowner to agree to maintain the restored habitat for a
certain length of time, usually 10-15 years. Longer agreements were
weighted more heavily.

[Stochastic Demographic Population Model]{.underline}

One of our population objectives from the draft Recovery Plan is 1,000
adult CWS. The purpose of developing the population model was to test
whether a population of 1,000 individuals would provide a probability of
extinction less than 10% for 100 years. The analytical approach we
utilized depended on CWS expert opinion to populate the model. We used a
stable age-structure to set the initial population and then evaluated
the model behavior. We later added catastrophic events, such as drought,
to the model. A graph of our model output is shown in Figure 2.

The model variables are as follows:

-   P = Proportion of adults breeding - sample from an equal
    distribution

-   R = Proportion of reproductively mature females giving birth -
    sample from an equal distribution

-   F = Number of young per female - sample from an equal distribution

-   A = Adult survival rate - sample from an equal distribution

-   Sn = Neonate survival rate age 0 - sample from an equal distribution

-   Sji = Juvenile survival rate age 1 to 3 - sample from an equal
    distribution

```{=html}
<!-- -->
```
-   First age of breeding age = 3yrs

-   Maximum age of breeding = 7yrs.

# Uncertainty

Our uncertainty lies primarily with our knowledge of the biology and
habitat requirements of the CWS. Information about its habitat
preferences for hibernacula is lacking, and thus, a critical component
may be missing from our habitat model. The basics of its reproductive
biology, such as clutch size, are inferred from knowledge of the
southern CWS population and other water snake species. In all the
simulations of our population model, we were unable to drive the
population to extinction, indicating a potential problem in our model.

The uncertainty associated with our PFW decision tool is related to the
way the PFW program currently operates. In general, potential
restoration sites are not actively sought in a specific area; rather,
projects are dependent upon the voluntary initiative of private
landowners to contact the FWS if they are interested in a restoration
project. Thus, the sites that the decision tool evaluates may vary
greatly from one year to the next. Additionally, the highest priority
parcels for CWS may not have willing landowners; therefore, lower
quality sites might be the only ones that are available.

# Discussion

## Value of decision structuring

Our decision structuring will lead to greatly improved conservation and
management for the CWS. The habitat model will allow us to analyze
visually the CWS locations and types of habitat occupied, as well as
call attention to habitat-related questions for research. In addition,
the model will help us to prioritize potential restoration sites, track
completed restorations graphically, and evaluate the impact of
restorations on the overall habitat value of the landscape.

The population model, with some refinements, will test our population
objectives for CWS. The model can also be revised and updated as we
obtain new information about the CWS's biology and population
demographics. The model will also help us to understand research needs
and guide future investigations.

Development of the PFW decision tool represents a potential paradigm
shift in how the PFW program will operate in the St. Joseph watershed.
The decision matrix has called attention to the need to target
individual parcels for habitat restoration, based on the parcel's value
to CWS recovery. In addition, PFW biologists are discussing new ways to
allocate funding and biologists' time within the watershed to focus
restoration work, regardless of artificial boundaries, where our efforts
will provide the greatest benefit to CWS.

## Further development required

The habitat model needs refinement to make it more accurate and useful.
We still must complete a prototype with a scoring process for
suitability for CWS, including roads, wetland types, residential areas,
etc. We also intend to add decision support layers, such as parcels and
restoration potential by treatment options.

The PFW decision tool is ready to use once the CWS habitat score is
developed in the habitat model. With a tool in place to prioritize
restoration work for CWS, the PFW biologists could explore funding
distribution alternatives to support restoration work in CWS areas. We
also need to design an evaluation process for the PFW decision tool.
Ideally, we would be able to share the tool with other agencies, such as
the U.S. Department of Agriculture's Natural Resources Conservation
Service and Farm Service Agency, Michigan Department of Natural
Resources, and The Nature Conservancy, all of which also work with
private landowners within the St. Joseph watershed.

As with our habitat model, we still must refine and improve the
stochastic demographic model. Based on the outputs from this model, we
will examine the CWS population objective to insure that the extinction
risk is acceptable and then revise the population objective as needed.
In addition, we intend to perform a sensitivity analysis of the model to
identify management priorities and research needs.

## Prototyping process

Our team came to the workshop with an array of expectations as well as
familiarity with models and GIS. This diversity in our team quickly
became apparent when we attempted a rapid prototype of the CWS's
limiting factors and initial construction of a habitat model. We decided
to divide into two groups---the spatial modelers and the non-modelers.
Starting from different places as we did definitely delayed performance
of the group; however, once we split into smaller groups, our
productivity and enthusiasm escalated. As we became more comfortable
with the concept of rapid prototyping and could see progress in our
work, we eventually divided into three groups, which ultimately
developed the three models/decision tools discussed above. Although we
struggled initially with the lack of detail in our early prototypes, we
finally were able to try a prototype, react and assess, and then refine
it. In the end, we agreed to the value of rapid prototyping for
structuring our decision problems.

# Recommendations

The following bullets represent recommendations for implementing SHC
within Region 3 and utilizing structured decision making as a training
vehicle for SHC.

-   Need to increase capacity for modeling within Region 3

-   Share modeling capacity across FWS program boundaries

-   Consider assistance from USGS on modeling issues

-   Accountability measures---should be outcome-driven rather than
    output-based

-   Determine how to support outside expertise (e.g., University
    researchers)

-   Functional directory of expertise of people to pull in to solve
    problems

-   Bite off manageable sized pieces

-   Follow up to workshop to bring team back together

-   Break up workshop into smaller functional groups

# Literature Cited

Hammond JS, Keeney RL, Raiffa H. 1999. Smart Choices: A Practical Guide
to Making Better Life Decisions. Broadway Books, New York.

U.S. Fish and Wildlife Service. 2007. Copperbelly Water Snake (*Nerodia*
*erythrogaster* *neglecta*) Draft Recovery Plan. Fort Snelling,
Minnesota. ix + 68 pp.

# Tables

<table style="width:100%;">
<colgroup>
<col style="width: 11%" />
<col style="width: 5%" />
<col style="width: 5%" />
<col style="width: 6%" />
<col style="width: 8%" />
<col style="width: 8%" />
<col style="width: 8%" />
<col style="width: 8%" />
<col style="width: 8%" />
<col style="width: 9%" />
<col style="width: 8%" />
<col style="width: 8%" />
</colgroup>
<tbody>
<tr class="odd">
<td colspan="4"><h1 id="section"></h1></td>
<td colspan="8"><h1
id="potential-cws-habitat-restoration-projects">Potential CWS Habitat
Restoration Projects</h1></td>
</tr>
<tr class="even">
<td><h1 id="attribute">Attribute</h1></td>
<td><h1 id="units">Units</h1></td>
<td><h1 id="goal">Goal</h1></td>
<td><h1 id="weight">Weight</h1></td>
<td><h1 id="multiple-wetlands">Multiple Wetlands</h1></td>
<td><h1 id="upland-forest">Upland Forest</h1></td>
<td><h1 id="large-wetland">Large Wetland</h1></td>
<td><h1 id="forest-and-wetland">Forest and Wetland</h1></td>
<td><h1 id="upland-forest-1">Upland Forest</h1></td>
<td><h1 id="small-wetland">Small Wetland</h1></td>
<td><h1 id="forest-and-wetland-1">Forest and Wetland</h1></td>
<td><h1 id="wetland-complex">Wetland Complex</h1></td>
</tr>
<tr class="odd">
<td><h1 id="cws-score">CWS score</h1></td>
<td><h1 id="section-1">1-10</h1></td>
<td><h1 id="max">max</h1></td>
<td><h1 id="section-2">65</h1></td>
<td><h1 id="section-3">65</h1></td>
<td><h1 id="section-4">0</h1></td>
<td><h1 id="section-5">32.5</h1></td>
<td><h1 id="section-6">16.25</h1></td>
<td><h1 id="section-7">32.5</h1></td>
<td><h1 id="section-8">8.125</h1></td>
<td><h1 id="section-9">48.75</h1></td>
<td><h1 id="section-10">24.375</h1></td>
</tr>
<tr class="even">
<td><h1 id="lag-time">Lag Time</h1></td>
<td><h1 id="section-11">0-1</h1></td>
<td><h1 id="min">min</h1></td>
<td><h1 id="section-12">10</h1></td>
<td><h1 id="section-13">10</h1></td>
<td><h1 id="section-14">0</h1></td>
<td><h1 id="section-15">10</h1></td>
<td><h1 id="section-16">10</h1></td>
<td><h1 id="section-17">0</h1></td>
<td><h1 id="section-18">10</h1></td>
<td><h1 id="section-19">10</h1></td>
<td><h1 id="section-20">10</h1></td>
</tr>
<tr class="odd">
<td><h1 id="total-costacre">Total cost/acre</h1></td>
<td><h1 id="section-21">$</h1></td>
<td><h1 id="min-1">min</h1></td>
<td><h1 id="section-22">5</h1></td>
<td><h1 id="section-23">0</h1></td>
<td><h1 id="section-24">4.565217</h1></td>
<td><h1 id="section-25">5</h1></td>
<td><h1 id="section-26">2.173913</h1></td>
<td><h1 id="section-27">3.913043</h1></td>
<td><h1 id="section-28">4.347826</h1></td>
<td><h1 id="section-29">3.26087</h1></td>
<td><h1 id="section-30">2.173913</h1></td>
</tr>
<tr class="even">
<td><h1 id="difficulty">Difficulty</h1></td>
<td><h1 id="section-31">1-5</h1></td>
<td><h1 id="min-2">min</h1></td>
<td><h1 id="section-32">5</h1></td>
<td><h1 id="section-33">0</h1></td>
<td><h1 id="section-34">5</h1></td>
<td><h1 id="section-35">2.5</h1></td>
<td><h1 id="section-36">2.5</h1></td>
<td><h1 id="section-37">3.75</h1></td>
<td><h1 id="section-38">5</h1></td>
<td><h1 id="section-39">2.5</h1></td>
<td><h1 id="section-40">2.5</h1></td>
</tr>
<tr class="odd">
<td><h1 id="priority-species">Priority Species</h1></td>
<td><h1 id="section-41">#</h1></td>
<td><h1 id="max-1">max</h1></td>
<td><h1 id="section-42">10</h1></td>
<td><h1 id="section-43">5</h1></td>
<td><h1 id="section-44">5</h1></td>
<td><h1 id="section-45">5</h1></td>
<td><h1 id="section-46">10</h1></td>
<td><h1 id="section-47">10</h1></td>
<td><h1 id="section-48">0</h1></td>
<td><h1 id="section-49">10</h1></td>
<td><h1 id="section-50">10</h1></td>
</tr>
<tr class="even">
<td><h1 id="cost-share">Cost Share</h1></td>
<td><h1 id="section-51">%</h1></td>
<td><h1 id="max-2">max</h1></td>
<td><h1 id="section-52">5</h1></td>
<td><h1 id="section-53">0</h1></td>
<td><h1 id="section-54">5</h1></td>
<td><h1 id="section-55">5</h1></td>
<td><h1 id="section-56">0</h1></td>
<td><h1 id="section-57">2</h1></td>
<td><h1 id="section-58">0</h1></td>
<td><h1 id="section-59">0</h1></td>
<td><h1 id="section-60">0</h1></td>
</tr>
<tr class="odd">
<td><h1 id="agreement-duration">Agreement Duration</h1></td>
<td><h1 id="section-61">#</h1></td>
<td><h1 id="max-3">max</h1></td>
<td><h1 id="section-62">5</h1></td>
<td><h1 id="section-63">0</h1></td>
<td><h1 id="section-64">1.25</h1></td>
<td><h1 id="section-65">1.25</h1></td>
<td><h1 id="section-66">1.25</h1></td>
<td><h1 id="section-67">1.25</h1></td>
<td><h1 id="section-68">0</h1></td>
<td><h1 id="section-69">5</h1></td>
<td><h1 id="section-70">1.25</h1></td>
</tr>
<tr class="even">
<td><h1 id="section-71"> </h1></td>
<td><h1 id="section-72"> </h1></td>
<td><h1 id="sum"> sum</h1></td>
<td><h1 id="section-73">105</h1></td>
<td><h1 id="section-74">0.761905</h1></td>
<td><h1 id="section-75">0.19824</h1></td>
<td><h1 id="section-76">0.583333</h1></td>
<td><h1 id="section-77">0.401656</h1></td>
<td><h1 id="section-78">0.508696</h1></td>
<td><h1 id="section-79">0.261646</h1></td>
<td><h1 id="section-80">0.757246</h1></td>
<td><h1 id="section-81">0.479037</h1></td>
</tr>
</tbody>
</table>

Table 1. Private Lands Decision Matrix

# Figures

![](media/image1.png){width="6.625in" height="5.753472222222222in"}

Figure 1. Forest and wetland component within 500m of each other, with
roads

![](media/image2.wmf){width="5.995138888888889in"
height="3.6659722222222224in"}

[^1]: USFWS, East Lansing Field Office, East Lansing, MI, USA,
    barbara_hosler@fws.gov

[^2]: Contracting biologist, Grand Marais, MN, USA

[^3]: USFWS, HAPET Office, Bismarck, ND, USA

[^4]: USFWS, Ecological Services, Onalaska, WI, USA

[^5]: USFWS, Alpena National Fish & Wildlife Conservation Office,
    Waterford, MI, USA

[^6]: USFWS, Ottawa National Wildlife Refuge, Oak Harbor, OH, USA

[^7]: USFWS, Bloomington Field Office, Bloomington, IN, USA

[^8]: USFWS, Michigan Private Lands Office, East Lansing, MI, USA

[^9]: USFWS, Indiana Private Lands Office, Bloomington, IN, USA

[^10]: Indiana-Purdue University, Department of Biology, Fort Wayne, IN,
    USA

[^11]: USFWS, Ecological Services, Fort Snelling, MN, USA

[^12]: USFWS, National Conservation Training Center, Shepherdstown, WV,
    USA

[^13]: Univ. MN-Retired