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-102 |
EM-667 |
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EM Short Name
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Fish species habitat value, Tampa Bay, FL, USA | Alewife derived nutrients, Connecticut, USA |
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EM Full Name
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Fish species habitat value, Tampa Bay, FL, USA | Alewife derived nutrients in stream food web, Connecticut, USA |
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EM Source or Collection
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US EPA | None |
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EM Source Document ID
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187 | 384 |
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Document Author
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Fulford, R., Yoskowitz, D., Russell, M., Dantin, D., and Rogers, J. | Walters, A. W., R. T. Barnes, and D. M. Post |
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Document Year
em.detail.documentYearHelp
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2016 | 2009 |
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Document Title
em.detail.sourceIdHelp
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Habitat and recreational fishing opportunity in Tampa Bay: Linking ecological and ecosystem services to human beneficiaries | Anadromous alewives (Alosa pseudoharengus) contribute marine-derived nutrients to coastal stream food webs |
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Document Status
em.detail.statusCategoryHelp
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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 |
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EM ID
em.detail.idHelp
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EM-102 |
EM-667 |
| Not applicable | Not applicable | |
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Contact Name
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Richard Fulford | Annika W. Walters |
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Contact Address
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USEPA Gulf Ecology Division, Gulf Breeze, FL 32561 | Dept. of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06511, USA |
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Contact Email
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Fulford.Richard@epa.gov | annika.walters@yale.edu |
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EM ID
em.detail.idHelp
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EM-102 |
EM-667 |
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Summary Description
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ABSTRACT: "Estimating value of estuarine habitat to human beneficiaries requires that we understand how habitat alteration impacts function through both production and delivery of ecosystem goods and services (EGS). Here we expand on the habitat valuation technique of Bell (1997) with an estimate of recreational angler willingness-to-pay combined with estimates of angler effort, fish population size, and fish and angler distribution. Results suggest species-specific fishery value is impacted by angler interest and stock status, as the most targeted fish (spotted seatrout) did not have the highest specific value (fish−1). Reduced population size and higher size at capture resulted in higher specific value for common snook. Habitat value estimated from recreational fishing value and fish-angler distributions supported an association between seagrass and habitat value, yet this relationship was also impacted by distance to access points. This analysis does not provide complete valuation of habitat as it considers only one service (fishing), but demonstrates a methodology to consider functional equivalency of all habitat features as a part of a habitat mosaic rather than in isolation, as well as how to consider both EGS production and delivery to humans (e.g., anglers) in any habitat valuation, which are critical for a transition to ecosystem management." | ABSTRACT: "Diadromous fish are an important link between marine and freshwater food webs. Pacific salmon (Oncorhynchus spp.) strongly impact nutrient dynamics in inland waters and anadromous alewife (Alosa pseudoharengus) may play a similar ecological role along the Atlantic coast. The annual spawning migration of anadromous alewife contributes, on average, 1050 g of nitrogen and 120 g of phosphorus to Bride Brook, Connecticut, USA, through excretion and mortality each year... There was no significant effect of this nutrient influx on water chemistry, leaf decomposition, or periphyton accrual. Dam removal and fish ladder construction will allow anadromous alewife to regain access to historical freshwater spawning habitats, potentially impacting food web dynamics and nutrient cycling in coastal freshwater systems." |
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Specific Policy or Decision Context Cited
em.detail.policyDecisionContextHelp
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None identifed | None identified |
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Biophysical Context
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shallow bay (mean 3.7m), transition zone between warm temperate and tropical biogeographic provinces. Highly urbanized watershed | Alewife spawning runs typically occur Mid March - May. |
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EM Scenario Drivers
em.detail.scenarioDriverHelp
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No scenarios presented | No scenarios presented |
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EM ID
em.detail.idHelp
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EM-102 |
EM-667 |
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Method Only, Application of Method or Model Run
em.detail.methodOrAppHelp
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Method + Application (multiple runs exist) View EM Runs | Method + Application (multiple runs exist) View EM Runs |
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New or Pre-existing EM?
em.detail.newOrExistHelp
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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
em.detail.idHelp
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EM-102 |
EM-667 |
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Document ID for related EM
em.detail.relatedEmDocumentIdHelp
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None | Doc-383 |
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EM ID for related EM
em.detail.relatedEmEmIdHelp
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None | EM-661 | EM-665 | EM-666 | EM-672 | EM-674 | EM-673 |
EM Modeling Approach
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EM ID
em.detail.idHelp
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EM-102 |
EM-667 |
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EM Temporal Extent
em.detail.tempExtentHelp
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2006-2011 | 1979-2009 |
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EM Time Dependence
em.detail.timeDependencyHelp
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time-stationary | time-stationary |
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EM Time Reference (Future/Past)
em.detail.futurePastHelp
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Not applicable | Not applicable |
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EM Time Continuity
em.detail.continueDiscreteHelp
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Not applicable | Not applicable |
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EM Temporal Grain Size Value
em.detail.tempGrainSizeHelp
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Not applicable | Not applicable |
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EM Temporal Grain Size Unit
em.detail.tempGrainSizeUnitHelp
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Not applicable | Not applicable |
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EM ID
em.detail.idHelp
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EM-102 |
EM-667 |
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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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Tampa Bay | Bride Brook |
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Spatial Extent Area (Magnitude)
em.detail.extentAreaHelp
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1000-10,000 km^2. | 1-10 ha |
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EM ID
em.detail.idHelp
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EM-102 |
EM-667 |
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EM Spatial Distribution
em.detail.distributeLumpHelp
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spatially distributed (in at least some cases) | spatially lumped (in all cases) |
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Spatial Grain Type
em.detail.spGrainTypeHelp
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area, for pixel or radial feature | Not applicable |
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Spatial Grain Size
em.detail.spGrainSizeHelp
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1 km^2 | Not applicable |
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EM ID
em.detail.idHelp
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EM-102 |
EM-667 |
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EM Computational Approach
em.detail.emComputationalApproachHelp
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Analytic | Analytic |
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EM Determinism
em.detail.deterStochHelp
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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-102 |
EM-667 |
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Model Calibration Reported?
em.detail.calibrationHelp
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No |
Yes ?Comment:The fish counter (for alewife numbers) was calibrated. |
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Model Goodness of Fit Reported?
em.detail.goodnessFitHelp
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No | 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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No | No |
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Model Uncertainty Analysis Reported?
em.detail.uncertaintyAnalysisHelp
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No | No |
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Model Sensitivity Analysis Reported?
em.detail.sensAnalysisHelp
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No | No |
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Model Sensitivity Analysis Include Interactions?
em.detail.interactionConsiderHelp
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Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
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EM-102 |
EM-667 |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
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EM-102 |
EM-667 |
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Centroid Lat/Long (Decimal Degree)
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EM ID
em.detail.idHelp
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EM-102 |
EM-667 |
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Centroid Latitude
em.detail.ddLatHelp
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27.74 | 41.32 |
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Centroid Longitude
em.detail.ddLongHelp
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-82.57 | -72.24 |
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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 | Provided |
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EM ID
em.detail.idHelp
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EM-102 |
EM-667 |
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EM Environmental Sub-Class
em.detail.emEnvironmentalSubclassHelp
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Near Coastal Marine and Estuarine | Rivers and Streams |
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Specific Environment Type
em.detail.specificEnvTypeHelp
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Habitat Zones (Low, Med, High, Optimal) around seagrass and emergent marsh | Coastal stream |
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EM Ecological Scale
em.detail.ecoScaleHelp
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Zone within an ecosystem | Ecological scale corresponds to the Environmental Sub-class |
Scale of differentiation of organisms modeled
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EM ID
em.detail.idHelp
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EM-102 |
EM-667 |
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EM Organismal Scale
em.detail.orgScaleHelp
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Species | Individual or population, within a species |
Taxonomic level and name of organisms or groups identified
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EM-102 |
EM-667 |
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EnviroAtlas URL
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EM-102 |
EM-667 |
| Big game hunting recreation demand | The National Hydrography Dataset (NHD) |
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-102 |
EM-667 |
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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)
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EM-102 |
EM-667 |
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