EcoService Models Library (ESML)
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Which comparison is best for me?EM Variables by Variable Role
One quick way to compare ecological models (EMs) is by comparing their variables. Predictor variables show what kinds of influences a model is able to account for, and what kinds of data it requires. Response variables show what information a model is capable of estimating.
This first comparison shows the names (and units) of each EM’s variables, side-by-side, sorted by variable role. Variable roles in ESML are as follows:
- Predictor Variables
- Time- or Space-Varying Variables
- Constants and Parameters
- Intermediate (Computed) Variables
- Response Variables
- Computed Response Variables
- Measured Response Variables
EM Variables by Category
A second way to use variables to compare EMs is by focusing on the kind of information each variable represents. The top-level categories in the ESML Variable Classification Hierarchy are as follows:
- Policy Regarding Use or Management of Ecosystem Resources
- Land Surface (or Water Body Bed) Cover, Use or Substrate
- Human Demographic Data
- Human-Produced Stressor or Enhancer of Ecosystem Goods and Services Production
- Ecosystem Attributes and Potential Supply of Ecosystem Goods and Services
- Non-monetary Indicators of Human Demand, Use or Benefit of Ecosystem Goods and Services
- Monetary Values
Besides understanding model similarities, sorting the variables for each EM by these 7 categories makes it easier to see if the compared models can be linked using similar variables. For example, if one model estimates an ecosystem attribute (in Category 5), such as water clarity, as a response variable, and a second model uses a similar attribute (also in Category 5) as a predictor of recreational use, the two models can potentially be used in tandem. This comparison makes it easier to spot potential model linkages.
All EM Descriptors
This selection allows a more detailed comparison of EMs by model characteristics other than their variables. The 50-or-so EM descriptors for each model are presented, side-by-side, in the following categories:
- EM Identity and Description
- EM Modeling Approach
- EM Locations, Environments, Ecology
- EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system
EM Descriptors by Modeling Concepts
This feature guides the user through the use of the following seven concepts for comparing and selecting EMs:
- Conceptual Model
- Modeling Objective
- Modeling Context
- Potential for Model Linkage
- Feasibility of Model Use
- Model Certainty
- Model Structural Information
Though presented separately, these concepts are interdependent, and information presented under one concept may have relevance to other concepts as well.
Compare Criteria:
Show Criteria
Hide CriteriaEM Identity and Description
EM Identification
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EM ID
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EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
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EM Short Name
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Retained rainwater, Guánica Bay, Puerto Rico | CRPI, St. Croix, USVI | Dickcissel density, CREP, Iowa, USA | WTP for a beach day, Massachusetts, USA | Recreational fishery index, USA |
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EM Full Name
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Retained rainwater, Guánica Bay, Puerto Rico, USA | CRPI (Coral Reef Protection Index, St. Croix, USVI | Dickcissel population density, CREP (Conservation Reserve Enhancement Program) wetlands, Iowa, USA | Willingness to pay (WTP) for a beach day, Barnstable, Massachusetts, USA | Recreational fishery index for streams and rivers, USA |
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EM Source or Collection
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US EPA | US EPA | None | US EPA | US EPA |
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EM Source Document ID
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338 | 335 | 372 | 386 | 414 |
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Document Author
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Amelia Smith, Susan Harrell Yee, Marc Russell, Jill Awkerman and William S. Fisher | Yee, S. H., Dittmar, J. A., and L. M. Oliver | Otis, D. L., W. G. Crumpton, D. Green, A. K. Loan-Wilsey, R. L. McNeely, K. L. Kane, R. Johnson, T. Cooper, and M. Vandever | Lyon, Sarina F., Nathaniel H. Merrill, Kate K. Mulvaney, and Marisa J. Mazzotta | Lomnicky. G.A., Hughes, R.M., Peck, D.V., and P.L. Ringold |
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Document Year
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2017 | 2014 | 2010 | 2018 | 2021 |
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Document Title
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Linking ecosystem services supply to stakeholder concerns on both land and sea: An example from Guanica Bay watershed, Puerto Rico | Comparison of methods for quantifying reef ecosystem services: A case study mapping services for St. Croix, USVI | Assessment of environmental services of CREP wetlands in Iowa and the midwestern corn belt | Valuing coastal beaches and closures using benefit transfer: An application to Barnstable, Massachusetts | Correspondence between a recreational fishery index and ecological condition for U.S.A. streams and rivers. |
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Document Status
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Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published |
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Comments on Status
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Published journal manuscript | Published journal manuscript | Published report | Published journal manuscript | Published journal manuscript |
Software and Access
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EM ID
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EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
| Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | |
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Contact Name
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Susan H. Yee | Susan H. Yee | David Otis | Kate K, Mulvaney | Gregg Lomnicky |
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Contact Address
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U.S. Environmental Protection Agency, Gulf Ecology Division, Gulf Breeze, FL 32561, USA | US EPA, Office of Research and Development, NHEERL, Gulf Ecology Division, Gulf Breeze, FL 32561, USA | U.S. Geological Survey, Iowa Cooperative Fish and Wildlife Research Unit, Iowa State University | Not reported | 200 SW 35th St., Corvallis, OR, 97333 |
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Contact Email
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yee.susan@epa.gov | yee.susan@epa.gov | dotis@iastate.edu | Mulvaney.Kate@EPA.gov | lomnicky.gregg@epa.gov |
EM Description
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EM ID
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EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
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Summary Description
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AUTHOR'S DESCRIPTION: "In total, 19 ecosystem services metrics were identified as relevant to stakeholder objectives in the Guánica Bay watershed identified during the 2013 Public Values Forum (Table 2)...Ecological production functions were applied to translate LULC measures of ecosystem condition to supply of ecosystem services…The volume of retained rainwater per unit area (in^3/in^2) includes both the maximum soil moisture retention and the initial abstraction of water before runoff due to infiltration, evaporation, or interception by vegetation…" | ABSTRACT: "...We investigated and compared a number of existing methods for quantifying ecological integrity, shoreline protection, recreational opportunities, fisheries production, and the potential for natural products discovery from reefs. Methods were applied to mapping potential ecosystem services production around St. Croix, U.S. Virgin Islands. Overall, we found that a number of different methods produced similar predictions." AUTHOR'S DESCRIPTION: "A number of methods have been developed for linking biophysical attributes of reef condition, such as reef structural complexity, fish biomass, or species richness, to provisioning of ecosystem goods and services (Principe et al., 2012). We investigated the feasibility of using existing methods and data for mapping production of reef ecosystem goods and services. We applied these methods toward mapping potential ecosystem goods and services production in St. Croix, U.S. Virgin Islands (USVI)...For each of the five categories of ecosystem services, we chose a suite of models and indices for estimating potential production based on relative ease of implementation, consisting of well-defined parameters, and likely availability of input data, to maximize potential for transferability to other locations. For each method, we assembled the necessary reef condition and environmental data as spatial data layers for St. Croix (Table1). The coastal zone surrounding St. Croix was divided into 10x10 m grid cells, and production functions were applied to quantify ecosystem services provisioning in each grid cell...Shoreline protection as an ecosystem service has been defined in a number of ways including protection from shoreline erosion, storm damage, or coastal inundation during extreme events (UNEP-WCMC (United Nations Environment Programme, World Conservation Monitoring Centre), 2006; WRI (World Resources Institute), 2009), but is often quantified as wave energy attenuation, an intermediate service that contributes to shoreline protection by reducing rates of erosion or coastal inundation (Principeet al., 2012)...An alternative index has been developed specifically for coral reefs, the Coral Reef Protection Index (CRPI), that accounts for the continuity of the reef and distance from shore in addition to reef habitat type (Burke et al., 2008): CRPI = ((Reef type + Reef distribution + Reef distance)/10) x 4 where the scaled magnitude of coastal protection due to each factor ranges from 0 (no protection) to 4 (very high protection; Table 2)." | ABSTRACT: "This final project report is a compendium of 3 previously submitted progress reports and a 4th report for work accomplished from August – December, 2009. Our initial primary objective (Progress Report I) was prediction of environmental services provided by the 27 Iowa Conservation Reserve Enhancement Program (CREP) wetland sites that had been completed by 2007 in the Prairie Pothole Region of northcentral Iowa. The sites contain 102.4 ha of wetlands and 377.4 ha of associated grassland buffers... With respect to wildlife habitat value, USFWS models predicted that the 27 wetlands would provide habitat for 136 pairs of 6 species of ducks, 48 pairs of Canada Geese, and 839 individuals of 5 grassland songbird species of special concern..." AUTHOR'S DESCRIPTION: "The migratory bird benefits of the 27 CREP sites were predicted for Dickcissel (Spiza americana)... Population estimates for these species were calculated using models developed by Quamen (2007) for the Prairie Pothole Region of Iowa (Table 3). The “neighborhood analysis” tool in the spatial analysis extension of ArcGIS (2008) was used to create landscape composition variables (grass400, grass3200, hay400, hay3200, tree400) needed for model input (see Table 3 for variable definitions). Values for the species-specific relative abundance (bbspath) variable were acquired from Diane Granfors, USFWS HAPET office. The equations for each model were used to calculate bird density (birds/ha) for each 15-m2 pixel of the land coverage. Next, the “zonal statistics” tool in the spatial analyst extension of ArcGIS (ESRI 2008) was used to calculate the average bird density for each CREP buffer. A population estimate for each site was then calculated by multiplying the average density by the buffer size." Equation: DICK density = 1-1/1+e^(-6.811334 + 1.889878 * bbspath) * e^(-1.831015 + 0.0312571 * hay400) | ABSTRACT: "Each year, millions of Americans visit beaches for recreation, resulting in significant social welfare benefits and economic activity. Considering the high use of coastal beaches for recreation, closures due to bacterial contamination have the potential to greatly impact coastal visitors and communities. We used readily-available information to develop two transferable models that, together, provide estimates for the value of a beach day as well as the lost value due to a beach closure. We modeled visitation for beaches in Barnstable, Massachusetts on Cape Cod through panel regressions to predict visitation by type of day, for the season, and for lost visits when a closure was posted. We used a meta-analysis of existing studies conducted throughout the United States to estimate a consumer surplus value of a beach visit of around $22 for our study area, accounting for water quality at beaches by using past closure history. We applied this value through a benefit transfer to estimate the value of a beach day, and combined it with lost town revenue from parking to estimate losses in the event of a closure. The results indicate a high value for beaches as a public resource and show significant losses to the town when beaches are closed due to an exceedance in bacterial concentrations." AUTHOR'S DESCRIPTION: "We used existing studies in a meta-analysis to estimate appropriate benefit transfer values of consumer surplus per beach visit for Barnstable. The studies we include in the model are for beaches across the United States, allowing the metaregression model to be more broadly applicable to other beaches and for values to be adjusted based on appropriate site attributes...To identify relevant studies, we selected 25 studies of beach use and swimming from the Recreation Use Values Database (RUVD), where consumer surplus values are presented as value per day in 2016 dollars...We added beach length and history of closures to contextualize the model for our application by proxying water quality and site quality." Equation 1, page 11, provides the meta-regression. | ABSTRACT: [Sport fishing is an important recreational and economic activity, especially in Australia, Europe and North America, and the condition of sport fish populations is a key ecological indicator of water body condition for millions of anglers and the public. Despite its importance as an ecological indicator representing the status of sport fish populations, an index for measuring this ecosystem service has not been quantified by analyzing actual fish taxa, size and abundance data across the U.S.A. Therefore, we used game fish data collected from 1,561 stream and river sites located throughout the conterminous U.S.A. combined with specific fish species and size dollar weights to calculate site-specific recreational fishery index (RFI) scores. We then regressed those scores against 38 potential site-specific environmental predictor variables, as well as site-specific fish assemblage condition (multimetric index; MMI) scores based on entire fish assemblages, to determine the factors most associated with the RFI scores. We found weak correlations between RFI and MMI scores and weak to moderate correlations with environmental variables, which varied in importance with each of 9 ecoregions. We conclude that the RFI is a useful indicator of a stream ecosystem service, which should be of greater interest to the U.S.A. public and traditional fishery management agencies than are MMIs, which tend to be more useful for ecologists, environmentalists and environmental quality agencies.] |
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Specific Policy or Decision Context Cited
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Meeting water demands for agriculture and domestic purposes. | None identified | None identified | Economic value of protecting coastal beach water quality from contamination caused closures. | None identified |
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Biophysical Context
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No additional descriptions provided | No additional description provided | Prairie pothole region of north-central Iowa | Four separate beaches within the community of Barnstable | None |
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EM Scenario Drivers
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No scenarios presented | No scenarios presented | No scenarios presented | No scenarios presented | N/A |
EM Relationship to Other EMs or Applications
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EM ID
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EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
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Method Only, Application of Method or Model Run
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Method + Application | Method + Application | Method + Application | Method + Application | Method + Application |
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New or Pre-existing EM?
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Application of existing model | Application of existing model |
Application of existing model ?Comment:Models developed by Quamen (2007). |
New or revised model | New or revised model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
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EM ID
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EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
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Document ID for related EM
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None | None | Doc-372 | Doc-386 | Doc-387 | None |
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EM ID for related EM
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None | None | EM-652 | EM-650 | EM-649 | EM-648 | EM-684 | EM-685 | EM-683 | EM-686 | None |
EM Modeling Approach
EM Relationship to Time
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EM ID
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EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
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EM Temporal Extent
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2006 - 2012 | 2006-2007, 2010 | 1992-2007 | July 1, 2011 to June 31, 2016 | 2013-2014 |
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EM Time Dependence
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time-stationary | time-stationary | time-stationary | time-stationary | time-dependent |
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EM Time Reference (Future/Past)
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Not applicable | Not applicable | Not applicable | Not applicable | past time |
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EM Time Continuity
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Not applicable | Not applicable | Not applicable | Not applicable | discrete |
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EM Temporal Grain Size Value
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Not applicable | Not applicable | Not applicable | Not applicable | 1 |
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EM Temporal Grain Size Unit
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Not applicable | Not applicable | Not applicable | Not applicable | Year |
EM Spatial Extent
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EM ID
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EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
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Bounding Type
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Watershed/Catchment/HUC | Physiographic or ecological | Multiple unrelated locations (e.g., meta-analysis) | Physiographic or ecological | Geopolitical |
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Spatial Extent Name
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Guanica Bay watershed | Coastal zone surrounding St. Croix | CREP (Conservation Reserve Enhancement Program) wetland sites | Barnstable beaches (Craigville Beach, Kalmus Beach, Keyes Memorial Beach, and Veteran’s Park Beach) | United States |
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Spatial Extent Area (Magnitude)
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1000-10,000 km^2. | 100-1000 km^2 | 1-10 km^2 | 10-100 ha | >1,000,000 km^2 |
Spatial Distribution of Computations
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EM ID
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EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
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EM Spatial Distribution
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spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) |
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Spatial Grain Type
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area, for pixel or radial feature | area, for pixel or radial feature | other (specify), for irregular (e.g., stream reach, lake basin) | length, for linear feature (e.g., stream mile) | length, for linear feature (e.g., stream mile) |
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Spatial Grain Size
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30 m x 30 m | 10 m x 10 m | multiple, individual, irregular shaped sites | by beach site | stream reach (site) |
EM Structure and Computation Approach
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EM ID
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EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
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EM Computational Approach
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Analytic | Analytic | Analytic | Analytic | Analytic |
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EM Determinism
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deterministic | deterministic | deterministic | deterministic | deterministic |
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Statistical Estimation of EM
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Model Checking Procedures Used
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EM ID
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EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
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Model Calibration Reported?
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No | Yes | Unclear | Yes | No |
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Model Goodness of Fit Reported?
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No | No | No | Yes | No |
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Goodness of Fit (metric| value | unit)
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None | None | None |
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None |
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Model Operational Validation Reported?
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No | Yes | Unclear | No | No |
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Model Uncertainty Analysis Reported?
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No | No | No | No | No |
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Model Sensitivity Analysis Reported?
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No | No | No |
Yes ?Comment:p-values of <0.05 and <0.01 provided for regression coefficient explanatory variables. |
No |
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Model Sensitivity Analysis Include Interactions?
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Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
EM Locations, Environments, Ecology
Location of EM Application
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
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| EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
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None |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
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| EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
| None |
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None |
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None |
Centroid Lat/Long (Decimal Degree)
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EM ID
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EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
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Centroid Latitude
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17.96 | 17.73 | 42.62 | 41.64 | 36.21 |
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Centroid Longitude
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-67.02 | -64.77 | -93.84 | -70.29 | -113.76 |
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Centroid Datum
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WGS84 | WGS84 | WGS84 | WGS84 | WGS84 |
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Centroid Coordinates Status
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Estimated | Estimated | Estimated | Estimated | Estimated |
Environments and Scales Modeled
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EM ID
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EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
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EM Environmental Sub-Class
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Inland Wetlands | Forests | Agroecosystems | Grasslands | Scrubland/Shrubland | Barren | Near Coastal Marine and Estuarine | Inland Wetlands | Agroecosystems | Grasslands | Near Coastal Marine and Estuarine | Rivers and Streams |
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Specific Environment Type
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13 LULC were used | Coral reefs | Grassland buffering inland wetlands set in agricultural land | Saltwater beach | reach |
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EM Ecological Scale
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Ecological scale is finer than that of the Environmental Sub-class | Ecological scale is finer than that of the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class | Ecological scale is finer than that of the Environmental Sub-class |
Scale and taxa of organisms modeled
Scale of differentiation of organisms modeled
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EM ID
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EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
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EM Organismal Scale
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Not applicable | Community | Species | Not applicable | Guild or Assemblage |
Taxonomic level and name of organisms or groups identified
taxonomyHelp
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| EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
| None Available | None Available |
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None Available | None Available |
EnviroAtlas URL
| EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
| The Watershed Boundary Dataset (WBD) | None Available | GAP Ecological Systems | None Available | None Available |
EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system
CICES v 4.3 - Common International Classification of Ecosystem Services (Section > Division > Group > Class)
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| EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
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<a target="_blank" rel="noopener noreferrer" href="https://www.epa.gov/eco-research/national-ecosystem-services-classification-system-nescs-plus">National Ecosystem Services Classification System (NESCS) Plus</a>
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(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
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| EM-428 | EM-446 | EM-651 | EM-682 | EM-862 |
| None |
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