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-788 ![]() |
EM-968 |
EM Short Name
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Wild bees over 26 yrs of restored prairie, IL, USA | EPA Stormwater Manamgement Model |
EM Full Name
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Wild bee community change over a 26 year chronosequence of restored tallgrass prairie, IL, USA | Storm Water Management Model User's Manual Version 5.2 |
EM Source or Collection
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None | US EPA |
EM Source Document ID
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401 | 452 |
Document Author
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Griffin, S. R, B. Bruninga-Socolar, M. A. Kerr, J. Gibbs and R. Winfree | Rossman, L. A., M., Simon |
Document Year
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2017 | 2022 |
Document Title
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Wild bee community change over a 26-year chronosequence of restored tallgrass prairie | Storm Water Management Model User's Manual Version 5.2 |
Document Status
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Peer reviewed and published | Not peer reviewed but is published (explain in Comment) |
Comments on Status
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Published journal manuscript | Published EPA report |
EM ID
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EM-788 ![]() |
EM-968 |
Not applicable | https://www.epa.gov/water-research/storm-water-management-model-swmm | |
Contact Name
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Sean R. Griffin | David Burden |
Contact Address
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Department of Ecology, Evolution, and Natural Resources, Rutgers University, New Brunswick, NJ 08901, U.S.A. | U.S. EPA Research Center for Environmental Solutions and Emergency Response (CESER) Mail Drop: 314 P.O. Box #1198 Ada, OK 74821-1198 |
Contact Email
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srgriffin108@gmail.com | burden.david@epa.gov |
EM ID
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EM-788 ![]() |
EM-968 |
Summary Description
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ABSTRACT: "Restoration efforts often focus on plants, but additionally require the establishment and long-term persistence of diverse groups of nontarget organisms, such as bees, for important ecosystem functions and meeting restoration goals. We investigated long-term patterns in the response of bees to habitat restoration by sampling bee communities along a 26-year chronosequence of restored tallgrass prairie in north-central Illinois, U.S.A. Specifically, we examined how bee communities changed over time since restoration in terms of (1) abundance and richness, (2) community composition, and (3) the two components of beta diversity, one-to-one species replacement, and changes in species richness. Bee abundance and raw richness increased with restoration age from the low level of the pre-restoration (agricultural) sites to the target level of the remnant prairie within the first 2–3 years after restoration, and these high levels were maintained throughout the entire restoration chronosequence. Bee community composition of the youngest restored sites differed from that of prairie remnants, but 5–7 years post-restoration the community composition of restored prairie converged with that of remnants. Landscape context, particularly nearby wooded land, was found to affect abundance, rarefied richness, and community composition. Partitioning overall beta diversity between sites into species replacement and richness effects revealed that the main driver of community change over time was the gradual accumulation of species, rather than one-to-one species replacement. At the spatial and temporal scales we studied, we conclude that prairie restoration efforts targeting plants also successfully restore bee communities." |
EPA Storm Water Management Model (SWMM) is a dynamic rainfall-runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas. The runoff component of SWMM operates on a collection of subcatchment areas that receive precipitation and generate runoff and pollutant loads. The routing portion of SWMM transports this runoff through a system of pipes, channels, storage/treatment devices, pumps, and regulators. SWMM tracks the quantity and quality of runoff generated within each subcatchment, and the flow rate, flow depth, and quality of water in each pipe and channel during a simulation period comprised of multiple time steps. Running under Windows, SWMM 5 provides an integrated environment for editing study area input data, running hydrologic, hydraulic and water quality simulations, and viewing the results in a variety of formats. These include color coded drainage area and conveyance system maps, time series graphs and tables, profile plots, and statistical frequency analyses. This user’s manual describes in detail how to run SWMM 5.2. It includes instructions on how to build a drainage system model, how to set various simulation options, and how to view results in a variety of formats. It also describes the different types of files used by SWMM and provides useful tables of parameter values. Detailed descriptions of the theory behind SWMM 5 and the numerical methods it employs can be found in a separate set of reference manuals. ?Comment:The variables used for this ESML entry were derived from the quick tutorial section of the SWMM manual. |
Specific Policy or Decision Context Cited
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None identified | NA |
Biophysical Context
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The Nachusa Grasslands consists of over 1,900 ha of restored prairie plantings, prairie remnants, and other habitats such as wetlands and oak savanna. The area is generally mesic with an average annual precipitation of 975 mm, and most precipitation occurs during the growing season. | NA |
EM Scenario Drivers
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No scenarios presented | NA |
EM ID
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EM-788 ![]() |
EM-968 |
Method Only, Application of Method or Model Run
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Method + Application (multiple runs exist) View EM Runs | Method Only |
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-788 ![]() |
EM-968 |
Document ID for related EM
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None | None |
EM ID for related EM
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None | EM-971 |
EM Modeling Approach
EM ID
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EM-788 ![]() |
EM-968 |
EM Temporal Extent
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1988-2014 | Not applicable |
EM Time Dependence
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time-stationary | time-dependent |
EM Time Reference (Future/Past)
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Not applicable | both |
EM Time Continuity
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Not applicable | continuous |
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-788 ![]() |
EM-968 |
Bounding Type
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Physiographic or ecological | No location (no locational reference given) |
Spatial Extent Name
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Nachusa Grasslands | Not applicable |
Spatial Extent Area (Magnitude)
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10-100 km^2 | Not applicable |
EM ID
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EM-788 ![]() |
EM-968 |
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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other (specify), for irregular (e.g., stream reach, lake basin) | area, for pixel or radial feature |
Spatial Grain Size
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Area varies by site | mm |
EM ID
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EM-788 ![]() |
EM-968 |
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-788 ![]() |
EM-968 |
Model Calibration Reported?
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No | Not applicable |
Model Goodness of Fit Reported?
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No | Not applicable |
Goodness of Fit (metric| value | unit)
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None | None |
Model Operational Validation Reported?
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No | Not applicable |
Model Uncertainty Analysis Reported?
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No | Not applicable |
Model Sensitivity Analysis Reported?
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No | Not applicable |
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-788 ![]() |
EM-968 |
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None |
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-788 ![]() |
EM-968 |
None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-788 ![]() |
EM-968 |
Centroid Latitude
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41.89 | Not applicable |
Centroid Longitude
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-89.34 | Not applicable |
Centroid Datum
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WGS84 | Not applicable |
Centroid Coordinates Status
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Provided | Not applicable |
EM ID
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EM-788 ![]() |
EM-968 |
EM Environmental Sub-Class
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Agroecosystems | Grasslands | Terrestrial Environment (sub-classes not fully specified) |
Specific Environment Type
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Restored prairie, prairie remnants, and cropland | User-defined catchments |
EM Ecological Scale
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Ecological scale corresponds to the Environmental Sub-class | Other or unclear (comment) |
Scale of differentiation of organisms modeled
EM ID
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EM-788 ![]() |
EM-968 |
EM Organismal Scale
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Species | Not applicable |
Taxonomic level and name of organisms or groups identified
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EM-968 |
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None Available |
EnviroAtlas URL
EM-788 ![]() |
EM-968 |
GAP Ecological Systems | None Available |
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-788 ![]() |
EM-968 |
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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-788 ![]() |
EM-968 |
None |
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