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-193 | EM-943 |
EM Short Name
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InVEST marine water quality, Hood Canal, WA, USA | Cultural ecosystem services, Bilbao, Spain | Visitation to natural areas, New England, USA |
EM Full Name
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InVEST (Integrated Valuation of Envl. Services and Tradeoffs) marine water quality, Hood Canal, WA, USA | Cultural ecosystem services, Bilbao, Spain | Estimating natural area use with cell phone data, Narragansett Beach, New England, USA |
EM Source or Collection
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InVEST |
None ?Comment:EU Mapping Studies |
US EPA |
EM Source Document ID
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205 | 191 | 436 |
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. | Casado-Arzuaga, I., Onaindia, M., Madariaga, I. and Verburg P. H. | Merrill, N.H., Atkinson, S.F., Mulvaney, K.K., Mazzotta, K.K., and J. Bousquin |
Document Year
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2013 | 2013 | 2020 |
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 | Mapping recreation and aesthetic value of ecosystems in the Bilbao Metropolitan Greenbelt (northern Spain) to support landscape planning | Using data derived from cellular phone locations to estimate visitation to natural areas: An application to water recreation in New England, USA |
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 journal manuscript | Published journal manuscript |
EM ID
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EM-131 | EM-193 | EM-943 |
https://www.naturalcapitalproject.org/invest/ | Not applicable | https://github.com/USEPA/Recreation_Benefits.git | |
Contact Name
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J.E. Toft | Izaskun Casado-Arzuaga | Nathaniel Merrill |
Contact Address
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Not reported | Plant Biology and Ecology Department, University of the Basque Country UPV/EHU, Campus de Leioa, Barrio Sarriena s/n, 48940 Leioa, Bizkaia, Spain | Atlantic Coastal Environmental Sciences Division, U.S. Environmental Protection Agency, Office of Research and Development, Center for Environmental Measurement and Modeling, Narragansett, Rhode Island, United States of America, |
Contact Email
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jetoft@stanford.edu | izaskun.casado@ehu.es | merrill.nathaniel@epa.gov |
EM ID
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EM-131 | EM-193 | EM-943 |
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) | ABSTRACT "This paper presents a method to quantify cultural ecosystem services (ES) and their spatial distribution in the landscape based on ecological structure and social evaluation approaches. The method aims to provide quantified assessments of ES to support land use planning decisions. A GIS-based approach was used to estimate and map the provision of recreation and aesthetic services supplied by ecosystems in a peri-urban area located in the Basque Country, northern Spain. Data of two different public participation processes (frequency of visits to 25 different sites within the study area and aesthetic value of different landscape units) were used to validate the maps. Three maps were obtained as results: a map showing the provision of recreation services, an aesthetic value map and a map of the correspondences and differences between both services. The data obtained in the participation processes were found useful for the validation of the maps. A weak spatial correlation was found between aesthetic quality and recreation provision services, with an overlap of the highest values for both services only in 7.2 % of the area. A consultation with decision-makers indicated that the results were considered useful to identify areas that can be targeted for improvement of landscape and recreation management." | ABSTRACT: "We introduce and validate the use of commercially available human mobility datasets based on cell phone locations to estimate visitation to natural areas. By combining this data with on-the-ground observations of visitation to water recreation areas in New England, we fit a model to estimate daily visitation for four months to more than 500 sites. The results show the potential for this new big data source of human mobility to overcome limitations in traditional methods of estimating visitation and to provide consistent information at policy-relevant scales. However, the data providers’ opaque and rapidly developing methods for processing locational information required a calibration and validation against data collected by traditional means to confidently reproduce the desired estimates of visitation. We found that with this calibration, the high-resolution information in both space and time provided by cell phone location-derived data creates opportunities for developing next-generation models of human interactions with the natural environment. " |
Specific Policy or Decision Context Cited
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Land use change | Land management, ecosystem management, response to EU 2020 Biodiversity Strategy | None identified |
Biophysical Context
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No additional description provided | Northern Spain; Bizkaia region | Natural area water bodies |
EM Scenario Drivers
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future land use and land cover; Climate change | No scenarios presented | N/A |
EM ID
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EM-131 | EM-193 | EM-943 |
Method Only, Application of Method or Model Run
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Method + Application (multiple runs exist) | Method + Application | Method + Application |
New or Pre-existing EM?
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Application of existing 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-193 | EM-943 |
Document ID for related EM
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None | None | None |
EM ID for related EM
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None | None | None |
EM Modeling Approach
EM ID
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EM-131 | EM-193 | EM-943 |
EM Temporal Extent
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varies by run, see runs for values | 2000 - 2007 | 2017 |
EM Time Dependence
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time-stationary | time-stationary | time-dependent |
EM Time Reference (Future/Past)
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Not applicable | Not applicable | past time |
EM Time Continuity
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Not applicable | Not applicable | discrete |
EM Temporal Grain Size Value
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Not applicable | Not applicable | 1 |
EM Temporal Grain Size Unit
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Not applicable | Not applicable | Day |
EM ID
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EM-131 | EM-193 | EM-943 |
Bounding Type
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Physiographic or ecological | Geopolitical | Point or points |
Spatial Extent Name
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Hood Canal | Bilbao Metropolitan Greenbelt | Cape Cod |
Spatial Extent Area (Magnitude)
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100-1000 km^2 | 100-1000 km^2 | 1000-10,000 km^2. |
EM ID
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EM-131 | EM-193 | EM-943 |
EM Spatial Distribution
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spatially distributed (in at least some cases) | 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 | other (specify), for irregular (e.g., stream reach, lake basin) |
Spatial Grain Size
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Not reported | 2 m x 2 m | water feature edge (beach) |
EM ID
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EM-131 | EM-193 | EM-943 |
EM Computational Approach
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Analytic | Analytic | Numeric |
EM Determinism
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deterministic | deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-131 | EM-193 | EM-943 |
Model Calibration Reported?
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No | No | Yes |
Model Goodness of Fit Reported?
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No | No |
Yes ?Comment:Random forest model performance statistics |
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 | Yes | Yes |
Model Uncertainty Analysis Reported?
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No | No | Unclear |
Model Sensitivity Analysis Reported?
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No | No | Yes |
Model Sensitivity Analysis Include Interactions?
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Not applicable | Not applicable | Unclear |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-131 | EM-193 | EM-943 |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-131 | EM-193 | EM-943 |
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None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-131 | EM-193 | EM-943 |
Centroid Latitude
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47.8 | 43.25 | 41.72 |
Centroid Longitude
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-122.7 | -2.92 | -70.29 |
Centroid Datum
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NAD83 | WGS84 | WGS84 |
Centroid Coordinates Status
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Estimated | Provided | Estimated |
EM ID
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EM-131 | EM-193 | EM-943 |
EM Environmental Sub-Class
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Near Coastal Marine and Estuarine | Aquatic Environment (sub-classes not fully specified) | Rivers and Streams | Near Coastal Marine and Estuarine | Terrestrial Environment (sub-classes not fully specified) | Forests | Agroecosystems | Created Greenspace | Grasslands | Scrubland/Shrubland | Lakes and Ponds | Near Coastal Marine and Estuarine |
Specific Environment Type
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glacier-carver saltwater fjord | none | beaches |
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 is finer than that of the Environmental Sub-class |
Scale of differentiation of organisms modeled
EM ID
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EM-131 | EM-193 | EM-943 |
EM Organismal Scale
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Not applicable | Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-131 | EM-193 | EM-943 |
None Available | None Available | None Available |
EnviroAtlas URL
EM-131 | EM-193 | EM-943 |
None Available | Percent IUCN Status II, Percent GAP Status 1 & 2 | Average Annual Precipitation |
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-193 | EM-943 |
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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-131 | EM-193 | EM-943 |
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