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-71 | EM-260 | EM-1011 | EM-1012 |
EM Short Name
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Community flowering date, Central French Alps | Coral taxa and land development, St.Croix, VI, USA | WMOST method | CMAQ community multiscale air quality model |
EM Full Name
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Community weighted mean flowering date, Central French Alps | Coral taxa richness and land development, St.Croix, Virgin Islands, USA | Watershed Management Optimization Support Tool (WMOST) v1 method | Science Algorithms of the EPA Models-3 Community Multi-scale Air Quality (CMAQ) Modeling System |
EM Source or Collection
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EU Biodiversity Action 5 | US EPA | US EPA | US EPA |
EM Source Document ID
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260 | 96 | 477 | 478 |
Document Author
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Lavorel, S., Grigulis, K., Lamarque, P., Colace, M-P, Garden, D., Girel, J., Pellet, G., and Douzet, R. | Oliver, L. M., Lehrter, J. C. and Fisher, W. S. | United States EPA | Byun, D.W. and J.K.S. Ching |
Document Year
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2011 | 2011 | 2013 | 1999 |
Document Title
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Using plant functional traits to understand the landscape distribution of multiple ecosystem services | Relating landscape development intensity to coral reef condition in the watersheds of St. Croix, US Virgin Islands | Watershed Management Optimization Support Tool (WMOST) v1 User manual | Science Algorithms of the EPA Models-3 Community Multi-scale Air Quality (CMAQ) Modeling System. |
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 EPA report | Published EPA report |
EM ID
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EM-71 | EM-260 | EM-1011 | EM-1012 |
Not applicable | Not applicable | https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NHEERL&dirEntryId=262280 | https://github.com/USEPA/CMAQ/blob/main/DOCS/Users_Guide/README.md | |
Contact Name
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Sandra Lavorel | Leah Oliver | Naomi Detenbeck | D. W. BYUN |
Contact Address
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Laboratoire d’Ecologie Alpine, UMR 5553 CNRS Université Joseph Fourier, BP 53, 38041 Grenoble Cedex 9, France | National Health and Environmental Research Effects Laboratory | NHEERL, Atlantic Ecology Division Narragansett, RI 02882 | Atmospheric Modeling Division National Exposure Research Laboratory U.S. Environmental Protection Agency Research Triangle Park, NC 27711 |
Contact Email
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sandra.lavorel@ujf-grenoble.fr | leah.oliver@epa.gov | detenbeck.naomi@epa.gov | bdx@hpcc.epa.gov |
EM ID
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EM-71 | EM-260 | EM-1011 | EM-1012 |
Summary Description
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ABSTRACT: "Here, we propose a new approach for the analysis, mapping and understanding of multiple ES delivery in landscapes. Spatially explicit single ES models based on plant traits and abiotic characteristics are combined to identify ‘hot’ and ‘cold’ spots of multiple ES delivery, and the land use and biotic determinants of such distributions. We demonstrate the value of this trait-based approach as compared to a pure land-use approach for a pastoral landscape from the central French Alps, and highlight how it improves understanding of ecological constraints to, and opportunities for, the delivery of multiple services." AUTHOR'S DESCRIPTION: "Community-weighted mean date of flowering onset was modelled using mixed models with land use and abiotic variables as fixed effects (LU + abiotic model) and year as a random effect…and modelled for each 20 x 20 m pixel using GLM estimated effects for each land use category and estimated regression coefficients with abiotic variables." | AUTHOR'S DESCRIPTION: "In this exploratory comparison, stony coral condition was related to watershed LULC and LDI values. We also compared the capacity of other potential human activity indicators to predict coral reef condition using multivariate analysis." (294) | 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 user guide and presentation of two case studies as examples of how to apply WMOST. Theoretical documentation is provided in a separate report (EPA/600/R-13/151). " | Models-3 is a flexible software system that provides a user-interface framework for CMAQ air quality modeling applications and tools for analysis, management of model input/output, and visualization of data. The Models-3 framework relies on two modeling systems to provide the meteorological and emissions data needed for air quality modeling. With this data, the Models-3 CMAQ modeling system can be used for urban and regional scale air quality simulation of tropospheric ozone, acid deposition, visibility, and particulate matter (PM2.5 and PM10). The meteorological and emissions modeling systems that are provided with the current release of Models-3 will be described in this document. However, CMAQ is designed as an open system where alternative models can be used to generate the data. |
Specific Policy or Decision Context Cited
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None identified | Not applicable | Not applicable | None provided |
Biophysical Context
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Elevation ranges from 1552 to 2442 m, on predominantly south-facing slopes | nearshore; <1.5 km offshore; <12 m depth | None | NA |
EM Scenario Drivers
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No scenarios presented | Not applicable | None | NA |
EM ID
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EM-71 | EM-260 | EM-1011 | EM-1012 |
Method Only, Application of Method or Model Run
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Method + Application | Method + Application | Method Only | Method + Application |
New or Pre-existing EM?
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New or revised model | New or revised model | 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-71 | EM-260 | EM-1011 | EM-1012 |
Document ID for related EM
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Doc-260 | Doc-269 | None | None | None |
EM ID for related EM
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EM-65 | EM-66 | EM-68 | EM-69 | EM-70 | EM-79 | EM-80 | EM-81 | EM-82 | EM-83 | None | None | EM-1019 | EM-1020 | EM-1021 |
EM Modeling Approach
EM ID
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EM-71 | EM-260 | EM-1011 | EM-1012 |
EM Temporal Extent
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2007-2008 | 2006-2007 | Not applicable | Not applicable |
EM Time Dependence
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time-stationary | time-stationary | time-dependent | time-dependent |
EM Time Reference (Future/Past)
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Not applicable | Not applicable |
Not applicable ?Comment:method description |
Not applicable |
EM Time Continuity
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Not applicable | Not applicable | discrete | continuous |
EM Temporal Grain Size Value
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Not applicable | Not applicable | 1 | Not applicable |
EM Temporal Grain Size Unit
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Not applicable | Not applicable | Month | Not applicable |
EM ID
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EM-71 | EM-260 | EM-1011 | EM-1012 |
Bounding Type
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Physiographic or Ecological | Physiographic or Ecological | Not applicable | Geopolitical |
Spatial Extent Name
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Central French Alps | St.Croix, U.S. Virgin Islands | Not applicable | United States |
Spatial Extent Area (Magnitude)
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10-100 km^2 | 10-100 km^2 | Not applicable | >1,000,000 km^2 |
EM ID
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EM-71 | EM-260 | EM-1011 | EM-1012 |
EM Spatial Distribution
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spatially distributed (in at least some cases) | spatially lumped (in all cases) | spatially lumped (in all cases) | spatially distributed (in at least some cases) |
Spatial Grain Type
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area, for pixel or radial feature | Not applicable | Not applicable | grid cells |
Spatial Grain Size
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20 m x 20 m | Not applicable | Not applicable | 32km |
EM ID
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EM-71 | EM-260 | EM-1011 | EM-1012 |
EM Computational Approach
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Analytic | Analytic | Numeric | Analytic |
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-71 | EM-260 | EM-1011 | EM-1012 |
Model Calibration Reported?
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No | Yes | Not applicable | Not applicable |
Model Goodness of Fit Reported?
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Yes | Yes | Not applicable |
Yes ?Comment:For particulate matter goodness of fit |
Goodness of Fit (metric| value | unit)
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None |
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Model Operational Validation Reported?
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No | No | Not applicable | Yes |
Model Uncertainty Analysis Reported?
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No | Yes | Not applicable | Unclear |
Model Sensitivity Analysis Reported?
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No | No | Not applicable | Unclear |
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-71 | EM-260 | EM-1011 | EM-1012 |
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None | None |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-71 | EM-260 | EM-1011 | EM-1012 |
None |
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None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-71 | EM-260 | EM-1011 | EM-1012 |
Centroid Latitude
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45.05 | 17.75 | Not applicable | 38.79 |
Centroid Longitude
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6.4 | -64.75 | Not applicable | 106.53 |
Centroid Datum
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WGS84 | NAD83 | Not applicable | WGS84 |
Centroid Coordinates Status
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Provided | Estimated | Not applicable | Estimated |
EM ID
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EM-71 | EM-260 | EM-1011 | EM-1012 |
EM Environmental Sub-Class
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Agroecosystems | Grasslands | Near Coastal Marine and Estuarine | Terrestrial Environment (sub-classes not fully specified) | Atmosphere |
Specific Environment Type
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Subalpine terraces, grasslands, and meadows. | stony coral reef | watershed | Land-sea-air interface |
EM Ecological Scale
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Not applicable | Ecological scale is finer than that of the Environmental Sub-class | Ecological scale is finer than that of the Environmental Sub-class | Not applicable |
Scale of differentiation of organisms modeled
EM ID
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EM-71 | EM-260 | EM-1011 | EM-1012 |
EM Organismal Scale
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Community | Guild or Assemblage | Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-71 | EM-260 | EM-1011 | EM-1012 |
None Available |
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None Available | 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-71 | EM-260 | EM-1011 | EM-1012 |
None |
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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-71 | EM-260 | EM-1011 | EM-1012 |
None |
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None |
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