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
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EM ID
em.detail.idHelp
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EM-185 | EM-438 |
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EM Short Name
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Blue crabs and SAV, Chesapeake Bay, USA | InVESTv3.0 Nutrient retention, Guánica Bay |
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EM Full Name
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Blue crabs and submerged aquatic vegetation interaction, Chesapeake Bay, USA | InVEST (Integrated Valuation of Environmental Services and Tradeoffs)v3.0 Nutrient retention, Guánica Bay, Puerto Rico, USA |
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EM Source or Collection
em.detail.emSourceOrCollectionHelp
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None | US EPA | InVEST |
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EM Source Document ID
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292 ?Comment:Conference paper |
338 |
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Document Author
em.detail.documentAuthorHelp
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Mykoniatis, N. and Ready, R. | Amelia Smith, Susan Harrell Yee, Marc Russell, Jill Awkerman and William S. Fisher |
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Document Year
em.detail.documentYearHelp
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2013 | 2017 |
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Document Title
em.detail.sourceIdHelp
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Evaluating habitat-fishery interactions: The case of submerged aquatic vegetation and blue crab fishery in the Chesapeake Bay | Linking ecosystem services supply to stakeholder concerns on both land and sea: An example from Guanica Bay watershed, Puerto Rico |
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Document Status
em.detail.statusCategoryHelp
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Not formally documented | Peer reviewed and published |
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Comments on Status
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Conference proceedings | Published journal manuscript |
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EM ID
em.detail.idHelp
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EM-185 | EM-438 |
| Not applicable | http://www.naturalcapitalproject.org/invest/ | |
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Contact Name
em.detail.contactNameHelp
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Nikolaos Mykoniatis | Susan H. Yee |
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Contact Address
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Department of Agricultural Economics, Sociology and Education The Pennsylvania State University | U.S. Environmental Protection Agency, Gulf Ecology Division, Gulf Breeze, FL 32561, USA |
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Contact Email
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Not reported | yee.susan@epa.gov |
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EM ID
em.detail.idHelp
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EM-185 | EM-438 |
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Summary Description
em.detail.summaryDescriptionHelp
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ABSTRACT: "This paper investigates habitat-fisheries interaction between two important resources in the Chesapeake Bay: blue crabs and Submerged Aquatic Vegetation (SAV). A habitat can be essential to a species (the species is driven to extinction without it), facultative (more habitat means more of the species, but species can exist at some level without any of the habitat) or irrelevant (more habitat is not associated with more of the species). An empirical bioeconomic model that nests the essential-habitat model into its facultative-habitat counterpart is estimated. Two alternative approaches are used to test whether SAV matters for the crab stock. Our results indicate that, if we do not have perfect information on habitat-fisheries linkages, the right approach would be to run the more general facultative-habitat model instead of the essential- habitat one." | Please note: This ESML entry describes a specific, published application of an InVEST model. Different versions (e.g. different tiers) or more recent versions of this model may be available at the InVEST website. AUTHOR'S DESCRIPTION: "Nutrient retention was estimated by first calculating water yield and establishing the quantity of nitrogen or phosphorus retained by different land cover classes using a water purification model (InVEST 3.0.0; Tallis et al., 2013). Different land cover classes were assumed to have different capacities for retaining nutrients, depending on the efficiency of vegetation in removing either nitrogen or phosphorus and the rates of nitrogen or phosphorus loading." “Use of other models in conjunction with this model:Average runoff per pixel modeled here were derived from the InVEST Water Yield model" |
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Specific Policy or Decision Context Cited
em.detail.policyDecisionContextHelp
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Not applicable | Improving water quality |
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Biophysical Context
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Submerged Aquatic Vegetation (SAV), eelgrass | No additional description provided |
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EM Scenario Drivers
em.detail.scenarioDriverHelp
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Essential or Facultative habitat | No scenarios presented |
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EM ID
em.detail.idHelp
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EM-185 | EM-438 |
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Method Only, Application of Method or Model Run
em.detail.methodOrAppHelp
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Method + Application | Method + Application |
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New or Pre-existing EM?
em.detail.newOrExistHelp
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Application of existing model | Application of existing model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
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EM ID
em.detail.idHelp
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EM-185 | EM-438 |
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Document ID for related EM
em.detail.relatedEmDocumentIdHelp
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Doc-227 | Doc-309 | Doc-205 |
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EM ID for related EM
em.detail.relatedEmEmIdHelp
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EM-106 | EM-363 | EM-112 |
EM Modeling Approach
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EM ID
em.detail.idHelp
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EM-185 | EM-438 |
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EM Temporal Extent
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1993-2011 | 1980 - 2013 |
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EM Time Dependence
em.detail.timeDependencyHelp
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time-dependent | time-dependent |
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EM Time Reference (Future/Past)
em.detail.futurePastHelp
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past time | other or unclear (comment) |
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EM Time Continuity
em.detail.continueDiscreteHelp
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discrete | discrete |
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EM Temporal Grain Size Value
em.detail.tempGrainSizeHelp
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1 | 1 |
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EM Temporal Grain Size Unit
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Year | Year |
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EM ID
em.detail.idHelp
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EM-185 | EM-438 |
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Bounding Type
em.detail.boundingTypeHelp
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Physiographic or ecological | Watershed/Catchment/HUC |
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Spatial Extent Name
em.detail.extentNameHelp
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Chesapeake Bay | Guanica Bay Study Area |
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Spatial Extent Area (Magnitude)
em.detail.extentAreaHelp
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10,000-100,000 km^2 | 1000-10,000 km^2. |
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EM ID
em.detail.idHelp
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EM-185 | EM-438 |
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EM Spatial Distribution
em.detail.distributeLumpHelp
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spatially lumped (in all cases) | spatially distributed (in at least some cases) |
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Spatial Grain Type
em.detail.spGrainTypeHelp
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Not applicable | area, for pixel or radial feature |
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Spatial Grain Size
em.detail.spGrainSizeHelp
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Not applicable | 30 m x 30 m |
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EM ID
em.detail.idHelp
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EM-185 | EM-438 |
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EM Computational Approach
em.detail.emComputationalApproachHelp
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Analytic | Numeric |
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EM Determinism
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deterministic | deterministic |
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Statistical Estimation of EM
em.detail.statisticalEstimationHelp
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EM ID
em.detail.idHelp
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EM-185 | EM-438 |
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Model Calibration Reported?
em.detail.calibrationHelp
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Yes | No |
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Model Goodness of Fit Reported?
em.detail.goodnessFitHelp
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Yes | No |
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Goodness of Fit (metric| value | unit)
em.detail.goodnessFitValuesHelp
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None | None |
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Model Operational Validation Reported?
em.detail.validationHelp
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Yes | No |
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Model Uncertainty Analysis Reported?
em.detail.uncertaintyAnalysisHelp
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Yes | No |
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Model Sensitivity Analysis Reported?
em.detail.sensAnalysisHelp
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Yes | No |
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Model Sensitivity Analysis Include Interactions?
em.detail.interactionConsiderHelp
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Yes | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
| EM-185 | EM-438 |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
| EM-185 | EM-438 |
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None |
Centroid Lat/Long (Decimal Degree)
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EM ID
em.detail.idHelp
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EM-185 | EM-438 |
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Centroid Latitude
em.detail.ddLatHelp
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36.99 | 17.97 |
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Centroid Longitude
em.detail.ddLongHelp
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-75.95 | -66.93 |
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Centroid Datum
em.detail.datumHelp
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WGS84 | WGS84 |
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Centroid Coordinates Status
em.detail.coordinateStatusHelp
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Estimated | Estimated |
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EM ID
em.detail.idHelp
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EM-185 | EM-438 |
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EM Environmental Sub-Class
em.detail.emEnvironmentalSubclassHelp
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None | Aquatic Environment (sub-classes not fully specified) | Inland Wetlands | Near Coastal Marine and Estuarine | Open Ocean and Seas | Forests | Agroecosystems | Created Greenspace | Scrubland/Shrubland | Barren |
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Specific Environment Type
em.detail.specificEnvTypeHelp
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Yes | 13 LULC were used |
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EM Ecological Scale
em.detail.ecoScaleHelp
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Yes | Ecological scale is finer than that of the Environmental Sub-class |
Scale of differentiation of organisms modeled
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EM ID
em.detail.idHelp
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EM-185 | EM-438 |
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EM Organismal Scale
em.detail.orgScaleHelp
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Yes | Not applicable |
Taxonomic level and name of organisms or groups identified
| EM-185 | EM-438 |
| None Available | None Available |
EnviroAtlas URL
| EM-185 | EM-438 |
| None Available | Total Annual Reduced Nitrogen Deposition, The Watershed Boundary Dataset (WBD) |
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-185 | EM-438 |
| None |
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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>
(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
| EM-185 | EM-438 |
| None | None |
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