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-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
EM Short Name
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RHyME2, Upper Mississippi River basin, USA | Chinook salmon value (household), Yaquina Bay, OR | Floral resources on landfill sites, United Kingdom | WMOSTsustainable water Danvers-Middleton, MA |
EM Full Name
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RHyME2 (Regional Hydrologic Modeling for Environmental Evaluation), Upper Mississippi River basin, USA | Economic value of Chinook salmon per household method, Yaquina Bay, OR | Floral resources on landfill sites, East Midlands, United Kingdom | WMOST sustainable water management initiative Danvers-Middleton, MA |
EM Source or Collection
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US EPA | US EPA | None | US EPA |
EM Source Document ID
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123 | 324 | 389 | 477 |
Document Author
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Tran, L. T., O’Neill, R. V., Smith, E. R., Bruins, R. J. F. and Harden, C. | Stephen J. Jordan, Timothy O'Higgins and John A. Dittmar | Tarrant S., J. Ollerton, M. L Rahman, J. Tarrant, and D. McCollin | United States EPA |
Document Year
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2013 | 2012 | 2013 | 2013 |
Document Title
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Application of hierarchy theory to cross-scale hydrologic modeling of nutrient loads | Ecosystem Services of Coastal Habitats and Fisheries: Multiscale Ecological and Economic Models in Support of Ecosystem-Based Management | Grassland restoration on landfill sites in the East Midlands, United Kingdom: An evaluation of floral resources and pollinating insects | Watershed Management Optimization Support Tool (WMOST) v1 User manual |
Document Status
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Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published |
Comments on Status
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Published journal manuscript | Published journal manuscript | Published journal manuscript | Published EPA report |
EM ID
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EM-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
Not applicable | Not applicable | Not applicable | https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NHEERL&dirEntryId=262280 | |
Contact Name
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Liem Tran | Stephen Jordan | Sam Tarrant | Naomi Detenbeck |
Contact Address
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Department of Geography, University of Tennessee, 1000 Phillip Fulmer Way, Knoxville, TN 37996-0925, USA | U.S. EPA, Gulf Ecology Div., 1 Sabine Island Dr., Gulf Breeze, FL 32561, USA | RSPB UK Headquarters, The Lodge, Sandy, Bedfordshire SG19 2DL, U.K. | NHEERL, Atlantic Ecology Division Narragansett, RI 02882 |
Contact Email
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ltran1@utk.edu | jordan.steve@epa.gov | sam.tarrant@rspb.org.uk | detenbeck.naomi@epa.gov |
EM ID
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EM-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
Summary Description
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ABSTRACT: "We describe a framework called Regional Hydrologic Modeling for Environmental Evaluation (RHyME2) for hydrologic modeling across scales. Rooted from hierarchy theory, RHyME2 acknowledges the rate-based hierarchical structure of hydrological systems. Operationally, hierarchical constraints are accounted for and explicitly described in models put together into RHyME2. We illustrate RHyME2with a two-module model to quantify annual nutrient loads in stream networks and watersheds at regional and subregional levels. High values of R2 (>0.95) and the Nash–Sutcliffe model efficiency coefficient (>0.85) and a systematic connection between the two modules show that the hierarchy theory-based RHyME2 framework can be used effectively for developing and connecting hydrologic models to analyze the dynamics of hydrologic systems." Two EMs will be entered in EPF-Library: 1. Regional scale module (Upper Mississippi River Basin) - this entry 2. Subregional scale module (St. Croix River Basin) | ABSTRACT:"Critical habitats for fish and wildlife are often small patches in landscapes, e.g., aquatic vegetation beds, reefs, isolated ponds and wetlands, remnant old-growth forests, etc., yet the same animal populations that depend on these patches for reproduction or survival can be extensive, ranging over large regions, even continents or major ocean basins. Whereas the ecological production functions that support these populations can be measured only at fine geographic scales and over brief periods of time, the ecosystem services (benefits that ecosystems convey to humans by supporting food production, water and air purification, recreational, esthetic, and cultural amenities, etc.) are delivered over extensive scales of space and time. These scale mismatches are particularly important for quantifying the economic values of ecosystem services. Examples can be seen in fish, shellfish, game, and bird populations. Moreover, there can be wide-scale mismatches in management regimes, e.g., coastal fisheries management versus habitat management in the coastal zone. We present concepts and case studies linking the production functions (contributions to recruitment) of critical habitats to commercial and recreational fishery values by combining site specific research data with spatial analysis and population models. We present examples illustrating various spatial scales of analysis, with indicators of economic value, for recreational Chinook (Oncorhynchus tshawytscha) salmon fisheries in the U.S. Pacific Northwest (Washington and Oregon) and commercial blue crab (Callinectes sapidus) and penaeid shrimp fisheries in the Gulf of Mexico. | ABSTRACT: "...Restored landfill sites are a significant potential reserve of semi-natural habitat, so their conservation value for supporting populations of pollinating insects was here examined by assessing whether the plant and pollinator assemblages of restored landfill sites are comparable to reference sites of existing wildlife value. Floral characteristics of the vegetation and the species richness and abundance of flower-visiting insect assemblages were compared between nine pairs of restored landfill sites and reference sites in the East Midlands of the United Kingdom, using standardized methods over two field seasons. …" AUTHOR'S DESCRIPTION: "The selection criteria for the landfill sites were greater than or equal to 50% of the site restored (to avoid undue influence from ongoing landfilling operations), greater than or equal to 0.5 ha in area and restored for greater than or equal to 4 years to allow establishment of vegetation. Comparison reference sites were the closest grassland sites of recognized nature conservation value, being designated as either Local Nature Reserves (LNRs) or Sites of Special Scientific Interest (SSSI)…All sites were surveyed three times each during the fieldwork season, in Spring, Summer, and Autumn. Paired sites were sampled on consecutive days whenever weather conditions permitted to reduce temporal bias. Standardized plant surveys were used (Dicks et al. 2002; Potts et al. 2006). Transects (100 × 2m) were centered from the approximate middle of the site and orientated using randomized bearing tables. All flowering plants were identified to species level… A “floral cover” method to represent available floral resources was used which combines floral abundance with inflorescence size. Mean area of the floral unit from above was measured for each flowering plant species and then multiplied by their frequencies." "Insect pollinated flowering plant species composition and floral abundance between sites by type were represented by non-metric multidimensional scaling (NMDS)...This method is sensitive to showing outliers and the distance between points shows the relative similarity (McCune & Grace 2002; Ollerton et al. 2009)." (This data is not entered into ESML) | ABSTRACT: "The Watershed Management Optimization Support Tool (WMOST) is intended to be used as a screening tool as part of an integrated watershed management process such as that described in EPA’s watershed planning handbook (EPA 2008).1 The objective of WMOST is to serve as a public-domain, efficient, and user-friendly tool for local water resources managers and planners to screen a widerange of potential water resources management options across their watershed or jurisdiction for costeffectiveness as well as environmental and economic sustainability (Zoltay et al 2010). Examples of options that could be evaluated with the tool include projects related to stormwater, water supply, wastewater and water-related resources such as Low-Impact Development (LID) and land conservation. The tool is intended to aid in evaluating the environmental and economic costs, benefits, trade-offs and co-benefits of various management options. In addition, the tool is intended to facilitate the evaluation of low impact development (LID) and green infrastructure as alternative or complementary management options in projects proposed for State Revolving Funds (SRF). WMOST is a screening model that is spatially lumped with a daily or monthly time step. The model considers water flows but does not yet consider water quality. The optimization of management options is solved using linear programming. The target user group for WMOST consists of local water resources managers, including municipal water works superintendents and their consultants. This document includes a presentation of a case study appling WMOST to the Danvers-Middleton, MA sustainable water management initiative. |
Specific Policy or Decision Context Cited
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Not reported | None identified | None identified | Not applicable |
Biophysical Context
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No additional description provided | Yaquina Bay estuary | No additional description provided | None |
EM Scenario Drivers
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No scenarios presented | No scenarios presented | No scenarios presented |
None ?Comment:Not presented with scenarios, but the model was run with multiple scenarios for costs related to varying instream minimum flows and provided the associated costs for each run. |
EM ID
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EM-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
Method Only, Application of Method or Model Run
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Method + Application | 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 | New or revised model | New or revised model | Application of existing model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
EM ID
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EM-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
Document ID for related EM
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Doc-123 | Doc-324 | None | Doc-477 |
EM ID for related EM
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None | EM-603 | EM-397 | EM-709 | None |
EM Modeling Approach
EM ID
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EM-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
EM Temporal Extent
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1987-1997 | 2003-2008 | 2007-2008 | Not applicable |
EM Time Dependence
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time-stationary | time-stationary | time-stationary | time-dependent |
EM Time Reference (Future/Past)
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Not applicable | Not applicable | Not applicable |
Not applicable ?Comment:method description |
EM Time Continuity
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Not applicable | Not applicable | Not applicable | discrete |
EM Temporal Grain Size Value
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Not applicable | Not applicable | Not applicable | 1 |
EM Temporal Grain Size Unit
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Not applicable | Not applicable | Not applicable | Day |
EM ID
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EM-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
Bounding Type
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Watershed/Catchment/HUC | Geopolitical | Multiple unrelated locations (e.g., meta-analysis) | Watershed/Catchment/HUC |
Spatial Extent Name
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Upper Mississippi River basin; St. Croix River Watershed | Pacific Northwest | East Midlands | Danvers-Middleton |
Spatial Extent Area (Magnitude)
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100,000-1,000,000 km^2 | >1,000,000 km^2 | 1000-10,000 km^2. | 10-100 km^2 |
EM ID
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EM-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
EM Spatial Distribution
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spatially distributed (in at least some cases) | spatially lumped (in all cases) | spatially distributed (in at least some cases) | spatially lumped (in all cases) |
Spatial Grain Type
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NHDplus v1 | Not applicable | other (specify), for irregular (e.g., stream reach, lake basin) | Not applicable |
Spatial Grain Size
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NHDplus v1 | Not applicable | multiple unrelated locations | Not applicable |
EM ID
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EM-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
EM Computational Approach
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Numeric | Analytic | Analytic | Numeric |
EM Determinism
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deterministic | deterministic | deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
Model Calibration Reported?
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Yes | No | Not applicable | Unclear |
Model Goodness of Fit Reported?
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Yes | No | Not applicable | Unclear |
Goodness of Fit (metric| value | unit)
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None | None | None |
Model Operational Validation Reported?
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No | Yes | Not applicable | Not applicable |
Model Uncertainty Analysis Reported?
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No | No | Not applicable | Not applicable |
Model Sensitivity Analysis Reported?
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No ?Comment:Some model coefficients serve, by their magnitude, to indicate the proportional impact on the final result of variation in the parameters they modify. |
No | Not applicable | Not applicable |
Model Sensitivity Analysis Include Interactions?
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Not applicable | Not applicable | Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
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None |
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
None |
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None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
Centroid Latitude
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42.5 | 44.62 | 52.22 | 42.58 |
Centroid Longitude
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-90.63 | -124.02 | -0.91 | -70.93 |
Centroid Datum
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WGS84 | WGS84 | WGS84 | WGS84 |
Centroid Coordinates Status
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Estimated | Estimated | Estimated | Estimated |
EM ID
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EM-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
EM Environmental Sub-Class
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Aquatic Environment (sub-classes not fully specified) | Rivers and Streams | Inland Wetlands | Terrestrial Environment (sub-classes not fully specified) | Agroecosystems | Atmosphere | Near Coastal Marine and Estuarine | Terrestrial Environment (sub-classes not fully specified) | Created Greenspace | Grasslands | Terrestrial Environment (sub-classes not fully specified) |
Specific Environment Type
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None | Yaquina Bay estuary and ocean | restored landfills and grasslands | watershed |
EM Ecological Scale
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Ecosystem | Ecological scale is finer than that of the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class | Ecological scale is finer than that of the Environmental Sub-class |
Scale of differentiation of organisms modeled
EM ID
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EM-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
EM Organismal Scale
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Not applicable | Other (multiple scales) | Individual or population, within a species | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
None Available |
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None Available |
EnviroAtlas URL
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-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
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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-91 | EM-604 |
EM-697 ![]() |
EM-1018 |
None |
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None | None |