EcoService Models Library (ESML)
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Compare EMs
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.
EM Identity and Description
EM ID
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EM-260 |
EM-541 ![]() |
EM-889 |
EM Short Name
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Coral taxa and land development, St.Croix, VI, USA | InVEST fisheries, lobster, South Africa | HWB poor health, Great Lakes waterfront, USA |
EM Full Name
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Coral taxa richness and land development, St.Croix, Virgin Islands, USA | Integrated Valuation of Ecosystem Services and Trade-offs Fisheries, rock lobster, South Africa | Human well being indicator-poor health, Great Lakes waterfront, USA |
EM Source or Collection
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US EPA | InVEST | None |
EM Source Document ID
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96 |
349 ?Comment:Supplemented with the InVEST Users Guide fisheries. |
422 ?Comment:Has not been submitted to Journal yet, but has been peer reviewed by EPA inhouse and outside reviewers |
Document Author
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Oliver, L. M., Lehrter, J. C. and Fisher, W. S. | Ward, Michelle, Hugh Possingham, Johathan R. Rhodes, Peter Mumby | Ted R. Angradi, Jonathon J. Launspach, and Molly J. Wick |
Document Year
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2011 | 2018 | None |
Document Title
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Relating landscape development intensity to coral reef condition in the watersheds of St. Croix, US Virgin Islands | Food, money and lobsters: Valuing ecosystem services to align environmental management with Sustainable Development Goals | Human well-being and natural capital indictors for Great Lakes waterfront revitalization |
Document Status
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Peer reviewed and published | Peer reviewed and published | Peer reviewed but unpublished (explain in Comment) |
Comments on Status
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Published journal manuscript | Published journal manuscript | Journal manuscript submitted or in review |
EM ID
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EM-260 |
EM-541 ![]() |
EM-889 |
Not applicable | https://www.naturalcapitalproject.org/invest/ | Not applicable | |
Contact Name
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Leah Oliver | Michelle Ward | Ted Angradi |
Contact Address
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National Health and Environmental Research Effects Laboratory | ARC Centre of Excellence for Environmental Decisions, The University of Queensland, Brisbane, QLD 4072, Australia | USEPA, Center for Computational Toxicology and Ecology, Great Lakes Toxicology and Ecology Division, Duluth, MN 55804 |
Contact Email
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leah.oliver@epa.gov | m.ward@uq.edu.au | tedangradi@gmail.com |
EM ID
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EM-260 |
EM-541 ![]() |
EM-889 |
Summary Description
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AUTHOR'S DESCRIPTION: "In this exploratory comparison, stony coral condition was related to watershed LULC and LDI values. We also compared the capacity of other potential human activity indicators to predict coral reef condition using multivariate analysis." (294) | AUTHOR'S DESCRIPTION: "Here we develop a method for assessing future scenarios of environmental management change that improve coastal ecosystem services and thereby, support the success of the SDGs. We illustrate application of the method using a case study of South Africa’s West Coast Rock Lobster fishery within the Table Mountain National Park (TMNP) Marine Protected Area...We calculated the retrospective and current value of the West Coast Rock Lobster fishery using published and unpublished data from various sources and combined the market worth of landed lobster from recreational fishers, small-scale fisheries (SSF), large-scale fisheries (LSF) and poachers. Then using the InVEST tool, we combined data to build scenarios that describe possible futures for the West Coast Rock Lobster fishery (see Table 1). The first scenario, entitled ‘Business as Usual’ (BAU), takes the current situation and most up-to-date data to model the future if harvest continues at the existing rate. The second scenario is entitled ‘Redirect the Poachers’ (RP), which attempts to model implementation of strict management, whereby poaching is minimised from the Marine Protected Area and other economic and nutritional sources are made available through government initiatives. The third scenario, entitled ‘Large Scale Cutbacks’ (LSC), excludes large-scale fisheries from harvesting West Coast Rock Lobster within the TMNP Marine Protected Area." | ABSTRACT: "Revitalization of natural capital amenities at the Great Lakes waterfront can result from sediment remediation, habitat restoration, climate resilience projects, brownfield reuse, economic redevelopment and other efforts. Practical indicators are needed to assess the socioeconomic and cultural benefits of these investments. We compiled U.S. census-tract scale data for five Great Lakes communities: Duluth/Superior, Green Bay, Milwaukee, Chicago, and Cleveland. We downloaded data from the US Census Bureau, Centers for Disease Control and Prevention, Environmental Protection Agency, National Oceanic and Atmospheric Administration, and non-governmental organizations. We compiled a final set of 19 objective human well-being (HWB) metrics and 26 metrics representing attributes of natural and 7 seminatural amenities (natural capital). We rated the reliability of metrics according to their consistency of correlations with metric of the other type (HWB vs. natural capital) at the census-tract scale, how often they were correlated in the expected direction, strength of correlations, and other attributes. Among the highest rated HWB indicators were measures of mean health, mental health, home ownership, home value, life success, and educational attainment. Highest rated natural capital metrics included tree cover and impervious surface metrics, walkability, density of recreational amenities, and shoreline type. Two ociodemographic covariates, household income and population density, had a strong influence on the associations between HWB and natural capital and must be included in any assessment of change in HWB benefits in the waterfront setting. Our findings are a starting point for applying objective HWB and natural capital indicators in a waterfront revitalization context." |
Specific Policy or Decision Context Cited
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Not applicable | Future rock lobster fisheries management | None identified |
Biophysical Context
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nearshore; <1.5 km offshore; <12 m depth | No additional description provided | Waterfront districts on south Lake Michigan and south lake Erie |
EM Scenario Drivers
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Not applicable | Fisheries exploitation; fishing vulnerability (of age classes) | N/A |
EM ID
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EM-260 |
EM-541 ![]() |
EM-889 |
Method Only, Application of Method or Model Run
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Method + Application | Method + Application (multiple runs exist) View EM Runs | Method + Application |
New or Pre-existing EM?
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New or revised model | Application of existing model | New or revised model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
EM ID
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EM-260 |
EM-541 ![]() |
EM-889 |
Document ID for related EM
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None | None | Doc-422 |
EM ID for related EM
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None | None | EM-886 | EM-888 | EM-890 | EM-891 | EM-893 | EM-894 | EM-895 |
EM Modeling Approach
EM ID
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EM-260 |
EM-541 ![]() |
EM-889 |
EM Temporal Extent
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2006-2007 | 1986-2115 | 2022 |
EM Time Dependence
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time-stationary | time-dependent | time-stationary |
EM Time Reference (Future/Past)
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Not applicable | future time | Not applicable |
EM Time Continuity
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Not applicable | discrete | Not applicable |
EM Temporal Grain Size Value
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Not applicable | 1 | Not applicable |
EM Temporal Grain Size Unit
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Not applicable | Year | Not applicable |
EM ID
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EM-260 |
EM-541 ![]() |
EM-889 |
Bounding Type
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Physiographic or Ecological | Geopolitical | Geopolitical |
Spatial Extent Name
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St.Croix, U.S. Virgin Islands | Table Mountain National Park Marine Protected Area | Great Lakes waterfront |
Spatial Extent Area (Magnitude)
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10-100 km^2 | 100-1000 km^2 | 1000-10,000 km^2. |
EM ID
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EM-260 |
EM-541 ![]() |
EM-889 |
EM Spatial Distribution
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spatially lumped (in all cases) | spatially lumped (in all cases) | spatially lumped (in all cases) |
Spatial Grain Type
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Not applicable | Not applicable | Not applicable |
Spatial Grain Size
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Not applicable | Not applicable | Not applicable |
EM ID
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EM-260 |
EM-541 ![]() |
EM-889 |
EM Computational Approach
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Analytic | Numeric | Numeric |
EM Determinism
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deterministic | deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-260 |
EM-541 ![]() |
EM-889 |
Model Calibration Reported?
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Yes | No | No |
Model Goodness of Fit Reported?
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Yes | No | No |
Goodness of Fit (metric| value | unit)
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None | None |
Model Operational Validation Reported?
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No |
Yes ?Comment:A validation analysis was carried out running the model using data from 1880 to 2001, and then comparing the output for the adult population with the 2001 published data. |
No |
Model Uncertainty Analysis Reported?
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Yes | No | No |
Model Sensitivity Analysis Reported?
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No | No | Yes |
Model Sensitivity Analysis Include Interactions?
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Not applicable | Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-260 |
EM-541 ![]() |
EM-889 |
None | None |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-260 |
EM-541 ![]() |
EM-889 |
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None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-260 |
EM-541 ![]() |
EM-889 |
Centroid Latitude
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17.75 | -34.18 | 42.26 |
Centroid Longitude
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-64.75 | 18.35 | -87.84 |
Centroid Datum
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NAD83 | WGS84 | WGS84 |
Centroid Coordinates Status
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Estimated | Provided | Estimated |
EM ID
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EM-260 |
EM-541 ![]() |
EM-889 |
EM Environmental Sub-Class
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Near Coastal Marine and Estuarine | Near Coastal Marine and Estuarine | Terrestrial Environment (sub-classes not fully specified) |
Specific Environment Type
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stony coral reef | Rocky coast, mixed coast, sandy coast, rocky inshore, sandy inshore, rocky shelf and unconsolidated shelf | Lake Michigan & Lake Erie waterfront |
EM Ecological Scale
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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 |
Scale of differentiation of organisms modeled
EM ID
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EM-260 |
EM-541 ![]() |
EM-889 |
EM Organismal Scale
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Guild or Assemblage | Individual or population, within a species | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-260 |
EM-541 ![]() |
EM-889 |
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None Available |
EnviroAtlas URL
EM-260 |
EM-541 ![]() |
EM-889 |
None Available | Big game hunting recreation demand | Enabling Conditions |
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)
EM-260 |
EM-541 ![]() |
EM-889 |
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None |
<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>
(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
EM-260 |
EM-541 ![]() |
EM-889 |
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None |