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-93 |
EM-102 ![]() |
EM Short Name
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Stream nitrogen removal, Mississippi R. basin, USA | Fish species habitat value, Tampa Bay, FL, USA |
EM Full Name
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Stream nitrogen removal, Upper Mississippi, Ohio and Missouri River sub-basins, USA | Fish species habitat value, Tampa Bay, FL, USA |
EM Source or Collection
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US EPA | US EPA |
EM Source Document ID
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52 | 187 |
Document Author
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Hill, B. and Bolgrien, D. | Fulford, R., Yoskowitz, D., Russell, M., Dantin, D., and Rogers, J. |
Document Year
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2011 | 2016 |
Document Title
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Nitrogen removal by streams and rivers of the Upper Mississippi River basin | Habitat and recreational fishing opportunity in Tampa Bay: Linking ecological and ecosystem services to human beneficiaries |
Document Status
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Peer reviewed and published | Peer reviewed and published |
Comments on Status
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Published journal manuscript | Published journal manuscript |
EM ID
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EM-93 |
EM-102 ![]() |
Not applicable | Not applicable | |
Contact Name
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Brian Hill | Richard Fulford |
Contact Address
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Mid-Continent Ecology Division NHEERL, ORD. USEPA 6201 Congdon Blvd. Duluth, MN 55804, USA | USEPA Gulf Ecology Division, Gulf Breeze, FL 32561 |
Contact Email
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hill.brian@epa.gov | Fulford.Richard@epa.gov |
EM ID
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EM-93 |
EM-102 ![]() |
Summary Description
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ABSTRACT: "We used stream chemistry and hydrogeomorphology data from 549 stream and 447 river sites to estimate NO3–N removal in the Upper Mississippi, Missouri, and Ohio Rivers. We used two N removal models to predict NO3–N input and removal. NO3–N input ranged from 0.01 to 338 kg/km*d in the Upper Mississippi River to 0.01–54 kg/ km*d in the Missouri River. Cumulative river network NO3–N input was 98700–101676 Mg/year in the Ohio River, 85,961–89,288 Mg/year in the Upper Mississippi River, and 59,463–61,541 Mg/year in the Missouri River. NO3–N output was highest in the Upper Mississippi River (0.01–329 kg/km*d ), followed by the Ohio and Missouri Rivers (0.01–236 kg/km*d ) sub-basins. Cumulative river network NO3–N output was 97,499 Mg/year for the Ohio River, 84,361 Mg/year for the Upper Mississippi River, and 59,200 Mg/year for the Missouri River. Proportional NO3–N removal (PNR) based on the two models ranged from 0.01 to 0.28. NO3–N removal was inversely correlated with stream order, and ranged from 0.01 to 8.57 kg/km*d in the Upper Mississippi River to 0.001–1.43 kg/km*d in the Missouri River. Cumulative river network NO3–N removal predicted by the two models was: Upper Mississippi River 4152 and 4152 Mg/year, Ohio River 3743 and 378 Mg/year, and Missouri River 2,277 and 197 Mg/year. PNR removal was negatively correlated with both stream order (r = −0.80–0.87) and the percent of the catchment in agriculture (r = −0.38–0.76)." | 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." |
Specific Policy or Decision Context Cited
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Not applicable | None identifed |
Biophysical Context
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Agricultural landuse , 1st-10th order streams | shallow bay (mean 3.7m), transition zone between warm temperate and tropical biogeographic provinces. Highly urbanized watershed |
EM Scenario Drivers
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Not applicable | No scenarios presented |
EM ID
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EM-93 |
EM-102 ![]() |
Method Only, Application of Method or Model Run
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Method + Application | Method + Application (multiple runs exist) View EM Runs |
New or Pre-existing EM?
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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
EM ID
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EM-93 |
EM-102 ![]() |
Document ID for related EM
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Doc-154 | Doc-155 | None |
EM ID for related EM
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None | None |
EM Modeling Approach
EM ID
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EM-93 |
EM-102 ![]() |
EM Temporal Extent
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2000-2008 | 2006-2011 |
EM Time Dependence
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time-stationary | time-stationary |
EM Time Reference (Future/Past)
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Not applicable | Not applicable |
EM Time Continuity
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Not applicable | Not applicable |
EM Temporal Grain Size Value
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Not applicable | Not applicable |
EM Temporal Grain Size Unit
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Not applicable | Not applicable |
EM ID
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EM-93 |
EM-102 ![]() |
Bounding Type
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Watershed/Catchment/HUC | Physiographic or Ecological |
Spatial Extent Name
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Upper Mississippi, Ohio and Missouri River sub-basins | Tampa Bay |
Spatial Extent Area (Magnitude)
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>1,000,000 km^2 | 1000-10,000 km^2. |
EM ID
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EM-93 |
EM-102 ![]() |
EM Spatial Distribution
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spatially distributed (in at least some cases) | spatially distributed (in at least some cases) |
Spatial Grain Type
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length, for linear feature (e.g., stream mile) | area, for pixel or radial feature |
Spatial Grain Size
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1 km | 1 km^2 |
EM ID
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EM-93 |
EM-102 ![]() |
EM Computational Approach
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Analytic | Analytic |
EM Determinism
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deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-93 |
EM-102 ![]() |
Model Calibration Reported?
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No | No |
Model Goodness of Fit Reported?
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No | No |
Goodness of Fit (metric| value | unit)
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None | None |
Model Operational Validation Reported?
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No | No |
Model Uncertainty Analysis Reported?
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Yes | No |
Model Sensitivity Analysis Reported?
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Unclear | No |
Model Sensitivity Analysis Include Interactions?
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Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-93 |
EM-102 ![]() |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-93 |
EM-102 ![]() |
None |
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Centroid Lat/Long (Decimal Degree)
EM ID
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EM-93 |
EM-102 ![]() |
Centroid Latitude
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36.98 | 27.74 |
Centroid Longitude
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-89.13 | -82.57 |
Centroid Datum
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WGS84 | WGS84 |
Centroid Coordinates Status
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Estimated | Estimated |
EM ID
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EM-93 |
EM-102 ![]() |
EM Environmental Sub-Class
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Rivers and Streams | Near Coastal Marine and Estuarine |
Specific Environment Type
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Not applicable | Habitat Zones (Low, Med, High, Optimal) around seagrass and emergent marsh |
EM Ecological Scale
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Ecological scale corresponds to the Environmental Sub-class | Zone within an ecosystem |
Scale of differentiation of organisms modeled
EM ID
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EM-93 |
EM-102 ![]() |
EM Organismal Scale
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Not applicable | Species |
Taxonomic level and name of organisms or groups identified
EM-93 |
EM-102 ![]() |
None Available |
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EnviroAtlas URL
EM-93 |
EM-102 ![]() |
National Hydrography Dataset Plus (NHD PlusV2), Total Annual Reduced Nitrogen Deposition, Total Annual Nitrogen Deposition | Big game hunting recreation demand |
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-93 |
EM-102 ![]() |
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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-93 |
EM-102 ![]() |
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