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-131 | EM-260 | EM-970 | EM-1011 |
EM Short Name
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InVEST marine water quality, Hood Canal, WA, USA | Coral taxa and land development, St.Croix, VI, USA | Air quality regulation, Lisbon | WMOST method |
EM Full Name
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InVEST (Integrated Valuation of Envl. Services and Tradeoffs) marine water quality, Hood Canal, WA, USA | Coral taxa richness and land development, St.Croix, Virgin Islands, USA | Modeling the provision of air-quality regulation ecosystem service provided by urban green spaces using lichens as ecological indicators | Watershed Management Optimization Support Tool (WMOST) v1 method |
EM Source or Collection
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InVEST | US EPA | None | US EPA |
EM Source Document ID
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205 | 96 | 454 | 477 |
Document Author
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Toft, J. E., Burke, J. L., Carey, M. P., Kim, C. K., Marsik, M., Sutherland, D. A., Arkema, K. K., Guerry, A. D., Levin, P. S., Minello, T. J., Plummer, M., Ruckelshaus, M. H., and Townsend, H. M. | Oliver, L. M., Lehrter, J. C. and Fisher, W. S. | Matos, P., Vieira, J., Rocha, B., Branquinho, C., & Pinho, P. | United States EPA |
Document Year
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2013 | 2011 | 2019 | 2013 |
Document Title
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From mountains to sound: modelling the sensitivity of dungeness crab and Pacific oyster to land–sea interactions in Hood Canal,WA | Relating landscape development intensity to coral reef condition in the watersheds of St. Croix, US Virgin Islands | Modeling the provision of air-quality regulation ecosystem service provided by urban green spaces using lichens as ecological indicators | 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-131 | EM-260 | EM-970 | EM-1011 |
https://www.naturalcapitalproject.org/invest/ | Not applicable | Not applicable | https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NHEERL&dirEntryId=262280 | |
Contact Name
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J.E. Toft | Leah Oliver | Pedro Pinho | Naomi Detenbeck |
Contact Address
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Not reported | National Health and Environmental Research Effects Laboratory | N/A | NHEERL, Atlantic Ecology Division Narragansett, RI 02882 |
Contact Email
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jetoft@stanford.edu | leah.oliver@epa.gov | ppinho@fc.ul.pt | detenbeck.naomi@epa.gov |
EM ID
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EM-131 | EM-260 | EM-970 | EM-1011 |
Summary Description
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Marine Water Quality Model. Please note: This ESML entry describes a specific, published application of an InVEST model. Different versions (e.g. different tiers) or more recent versions of this model may be available at the InVEST website. AUTHOR'S DESCRIPTION: "We used outputs from the freshwater models as inputs to the marine water quality model.We adapted a box model that has been successfully applied in Puget Sound (Babson et al., 2006; Sutherland et al., 2011) to simulate seasonal and interannual variations in salinity, water temperature, and nitrates in the Canal." (p. 4) | 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) | The UN Sustainable Development Goals states that urban air pollution must be tackled to create more inclusive, safe, resilient and sustainable cities. Urban green infrastructures can mitigate air pollution, but a crucial step to use this knowledge into urban management is to quantify how much air-quality regulation can green spaces provide and to understand how the provision of this ecosystem service is affected by other environmental factors. Considering the insufficient number of air quality monitoring stations in cities to monitor the wide range of natural and anthropic sources of pollution with high spatial resolution, ecological indicators of air quality are an alternative cost-effective tool. The aim of this work was to model the supply of air-quality regulation based on urban green spaces characteristics and other environmental factors. For that, we sampled lichen diversity in the centroids of 42 urban green spaces in Lisbon, Portugal. Species richness was the best biodiversity metric responding to air pollution, considering its simplicity and its significative response to the air pollutants concentration data measured in the existent air quality monitoring stations. Using that metric, we then created a model to estimate the supply of air quality regulation provided by green spaces in all green spaces of Lisbon based on the response to the following environmental drivers: the urban green spaces size and its vegetation density. We also used the unexplained variance of this model to map the background air pollution. Overall, we suggest that management should target the smallest urban green spaces by increasing green space size or tree density. The use of ecological indicators, very flexible in space, allow the understanding and the modeling of the provision of air-quality regulation by urban green spaces, and how urban green spaces can be managed to improve air quality and thus improve human well-being and cities resilience. | 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). " |
Specific Policy or Decision Context Cited
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Land use change | Not applicable | None identified | Not applicable |
Biophysical Context
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No additional description provided | nearshore; <1.5 km offshore; <12 m depth | Green spaces in Lisbon, Portugal | None |
EM Scenario Drivers
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future land use and land cover; Climate change | Not applicable | No scenarios presented | None |
EM ID
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EM-131 | EM-260 | EM-970 | EM-1011 |
Method Only, Application of Method or Model Run
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Method + Application (multiple runs exist) | Method + Application | Method + Application | Method Only |
New or Pre-existing EM?
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Application of existing 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-131 | EM-260 | EM-970 | EM-1011 |
Document ID for related EM
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None | None | None | None |
EM ID for related EM
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None | None | None | None |
EM Modeling Approach
EM ID
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EM-131 | EM-260 | EM-970 | EM-1011 |
EM Temporal Extent
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varies by run, see runs for values | 2006-2007 | 2015-2018 | 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 | Month |
EM ID
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EM-131 | EM-260 | EM-970 | EM-1011 |
Bounding Type
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Physiographic or ecological | Physiographic or Ecological | Physiographic or ecological | Not applicable |
Spatial Extent Name
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Hood Canal | St.Croix, U.S. Virgin Islands | Urban green spaces in Lisbon | Not applicable |
Spatial Extent Area (Magnitude)
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100-1000 km^2 | 10-100 km^2 | 100-1000 km^2 | Not applicable |
EM ID
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EM-131 | EM-260 | EM-970 | EM-1011 |
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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other (specify), for irregular (e.g., stream reach, lake basin) | Not applicable | map scale, for cartographic feature | Not applicable |
Spatial Grain Size
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Not reported | Not applicable | N/A | Not applicable |
EM ID
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EM-131 | EM-260 | EM-970 | EM-1011 |
EM Computational Approach
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Analytic | 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-131 | EM-260 | EM-970 | EM-1011 |
Model Calibration Reported?
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No | Yes | Yes | Not applicable |
Model Goodness of Fit Reported?
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No | Yes | Yes | Not applicable |
Goodness of Fit (metric| value | unit)
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None |
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None |
Model Operational Validation Reported?
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No | No | No | Not applicable |
Model Uncertainty Analysis Reported?
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No | Yes | No | Not applicable |
Model Sensitivity Analysis Reported?
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No | No | Unclear | 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-131 | EM-260 | EM-970 | EM-1011 |
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None |
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None |
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-131 | EM-260 | EM-970 | EM-1011 |
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None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-131 | EM-260 | EM-970 | EM-1011 |
Centroid Latitude
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47.8 | 17.75 | 38.75 | Not applicable |
Centroid Longitude
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-122.7 | -64.75 | 9.8 | Not applicable |
Centroid Datum
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NAD83 | NAD83 | None provided | Not applicable |
Centroid Coordinates Status
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Estimated | Estimated | Estimated | Not applicable |
EM ID
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EM-131 | EM-260 | EM-970 | EM-1011 |
EM Environmental Sub-Class
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Near Coastal Marine and Estuarine | Near Coastal Marine and Estuarine | Created Greenspace | Terrestrial Environment (sub-classes not fully specified) |
Specific Environment Type
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glacier-carver saltwater fjord | stony coral reef | Green spaces in Lisbon, Portugal | watershed |
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 | 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-131 | EM-260 | EM-970 | EM-1011 |
EM Organismal Scale
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Not applicable | Guild or Assemblage | Guild or Assemblage | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-131 | EM-260 | EM-970 | EM-1011 |
None Available |
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None Available |
EnviroAtlas URL
EM-131 | EM-260 | EM-970 | EM-1011 |
None Available | None Available | Green Space per Capita | National Hydrography Dataset Plus (NHD PlusV2), Wetlands and Streams, Agricultural water use (million gallons/day) |
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-131 | EM-260 | EM-970 | EM-1011 |
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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-131 | EM-260 | EM-970 | EM-1011 |
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None |