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-880 ![]() |
EM-1011 | EM-1012 |
EM Short Name
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Human well-being index, Pensacola Bay, Florida | WMOST method | CMAQ community multiscale air quality model |
EM Full Name
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Human well-being index (HWBI), Pensacola Bay, Florida | 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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US EPA | US EPA | US EPA |
EM Source Document ID
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418 | 477 | 478 |
Document Author
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Yee, S.H., Paulukonis, E., Simmons, C., Russell, M., Fullford, R., Harwell, L., and L.M. Smith | United States EPA | Byun, D.W. and J.K.S. Ching |
Document Year
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2021 | 2013 | 1999 |
Document Title
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Projecting effects of land use change on human well being through changes in ecosystem services | 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 |
Comments on Status
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Published journal manuscript | Published EPA report | Published EPA report |
EM ID
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EM-880 ![]() |
EM-1011 | EM-1012 |
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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Susan Yee | Naomi Detenbeck | D. W. BYUN |
Contact Address
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Gulf Ecosystem Measurement and Modeling Division, Center for Environmental Measurement and Modeling, US Environmental Prntection Agency, Gulf Breeze, FL 32561, USA | 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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yee.susan@epa.gov | detenbeck.naomi@epa.gov | bdx@hpcc.epa.gov |
EM ID
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EM-880 ![]() |
EM-1011 | EM-1012 |
Summary Description
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ABSTRACT: "Changing patterns of land use, temperature, and precipitation are expected to impact ecosystem se1vices, including water quality and quantity, buffering of extreme events, soil quality, and biodiversity. Scenario ana lyses that link such impacts on ecosystem se1vices to human well-being may be valuable in anticipating potential consequences of change that are meaningful to people living in a community. Ecosystem se1vices provide munerous benefits to community well-being, including living standards, health, cultural fulfillment, education, and connection to nature. Yet assessments of impacts of ecosystem se1vices on human well-being have largely focused on human health or moneta1y benefits (e.g. market values). This study applies a human well-being modeling framework to demonsffate the potential impacts of alternative land use scenarios on multi-faceted components of human well-being through changes in ecosystem se1vices (i.e., ecological benefits functions). The modeling framework quantitatively defines these relationships in a way that can be used to project the influence of ecosystem se1vice flows on indicators of human well-being, alongside social se1vice flows and economic se1vice flows. Land use changes are linked to changing indicators of ecosystem se1vices through the application of ecological production functions. The approach is demonstrated for two future land use scenarios in a Florida watershed, representing different degrees of population growth and environmental resource protection. Increasing rates of land development were almost universally associated with declines in ecosystem se1vices indicators and associated indicators of well-being, as natural ecosystems were replaced by impe1vious surfaces that depleted the ability of ecosystems to buffer air pollutants, provide habitat for biodiversity, and retain rainwater. Scenarios with increases in indicators of ecosystem se1vices, however, did not necessarily translate into increases in indicators of well-being, due to cova1ying changes in social and economic se1vices indicators. The approach is broadly ffansferable to other communities or decision scenarios and se1ves to illustrate the potential impacts of changing land use on ecosystem se1vices and human well-being. " | 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 | None provided |
Biophysical Context
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N/A | None | NA |
EM Scenario Drivers
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N/A | None | NA |
EM ID
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EM-880 ![]() |
EM-1011 | EM-1012 |
Method Only, Application of Method or Model Run
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Method + Application (multiple runs exist) View EM Runs | 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 |
Related EMs (for example, other versions or derivations of this EM) described in ESML
EM ID
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EM-880 ![]() |
EM-1011 | EM-1012 |
Document ID for related EM
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None | None | None |
EM ID for related EM
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EM-882 | None | EM-1019 | EM-1020 | EM-1021 |
EM Modeling Approach
EM ID
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EM-880 ![]() |
EM-1011 | EM-1012 |
EM Temporal Extent
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2010 | Not applicable | Not applicable |
EM Time Dependence
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time-stationary | time-dependent | time-dependent |
EM Time Reference (Future/Past)
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Not applicable |
Not applicable ?Comment:method description |
Not applicable |
EM Time Continuity
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Not applicable | discrete | continuous |
EM Temporal Grain Size Value
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Not applicable | 1 | Not applicable |
EM Temporal Grain Size Unit
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Not applicable | Month | Not applicable |
EM ID
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EM-880 ![]() |
EM-1011 | EM-1012 |
Bounding Type
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Geopolitical | Not applicable | Geopolitical |
Spatial Extent Name
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Pensacola Bay Region | Not applicable | United States |
Spatial Extent Area (Magnitude)
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100-1000 km^2 | Not applicable | >1,000,000 km^2 |
EM ID
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EM-880 ![]() |
EM-1011 | EM-1012 |
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) |
Spatial Grain Type
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area, for pixel or radial feature | Not applicable | grid cells |
Spatial Grain Size
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county | Not applicable | 32km |
EM ID
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EM-880 ![]() |
EM-1011 | EM-1012 |
EM Computational Approach
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Analytic | Numeric | Analytic |
EM Determinism
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deterministic | deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-880 ![]() |
EM-1011 | EM-1012 |
Model Calibration Reported?
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Unclear | Not applicable | Not applicable |
Model Goodness of Fit Reported?
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Not applicable | Not applicable |
Yes ?Comment:For particulate matter goodness of fit |
Goodness of Fit (metric| value | unit)
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None | None |
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Model Operational Validation Reported?
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No | Not applicable | Yes |
Model Uncertainty Analysis Reported?
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Yes | Not applicable | Unclear |
Model Sensitivity Analysis Reported?
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Yes | Not applicable | Unclear |
Model Sensitivity Analysis Include Interactions?
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Unclear | Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-880 ![]() |
EM-1011 | EM-1012 |
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None |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-880 ![]() |
EM-1011 | EM-1012 |
None | None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-880 ![]() |
EM-1011 | EM-1012 |
Centroid Latitude
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30.05 | Not applicable | 38.79 |
Centroid Longitude
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-87.61 | Not applicable | 106.53 |
Centroid Datum
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WGS84 | Not applicable | WGS84 |
Centroid Coordinates Status
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Estimated | Not applicable | Estimated |
EM ID
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EM-880 ![]() |
EM-1011 | EM-1012 |
EM Environmental Sub-Class
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Terrestrial Environment (sub-classes not fully specified) | Terrestrial Environment (sub-classes not fully specified) | Atmosphere |
Specific Environment Type
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Mixed | watershed | Land-sea-air interface |
EM Ecological Scale
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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-880 ![]() |
EM-1011 | EM-1012 |
EM Organismal Scale
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Not applicable | Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-880 ![]() |
EM-1011 | EM-1012 |
None Available | 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-880 ![]() |
EM-1011 | EM-1012 |
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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-880 ![]() |
EM-1011 | EM-1012 |
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None |
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