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-363 ![]() |
EM Short Name
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InVEST (v1.004) water purification, Indonesia |
EM Full Name
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InVEST (Integrated Valuation of Environmental Services and Tradeoffs v1.004) water purification (nutrient retention), Sumatra, Indonesia |
EM Source or Collection
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InVEST |
EM Source Document ID
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309 |
Document Author
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Bhagabati, N. K., Ricketts, T., Sulistyawan, T. B. S., Conte, M., Ennaanay, D., Hadian, O., McKenzie, E., Olwero, N., Rosenthal, A., Tallis, H., and Wolney, S. |
Document Year
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2014 |
Document Title
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Ecosystem services reinforce Sumatran tiger conservation in land use plans |
Document Status
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Peer reviewed and published |
Comments on Status
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Published journal manuscript |
EM ID
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EM-363 ![]() |
https://www.naturalcapitalproject.org/invest/ | |
Contact Name
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Nirmal K. Bhagabati |
Contact Address
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The Nature Conservancy, 1107 Laurel Avenue, Felton, CA 95018 |
Contact Email
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nirmal.bhagabati@wwfus.org |
EM ID
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EM-363 ![]() |
Summary Description
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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. ABSTRACT: "...Here we use simple spatial analyses on readily available datasets to compare the distribution of five ecosystem services with tiger habitat in central Sumatra. We assessed services and habitat in 2008 and the changes in these variables under two future scenarios: a conservation-friendly Green Vision, and a Spatial Plan developed by the Indonesian government..." AUTHOR'S DESCRIPTION: "We used a modeling tool, InVEST (Integrated Valuation of Environmental Services and Tradeoffs version 1.004; Tallis et al., 2010), to map and quantify tiger habitat quality and five ecosystem services. InVEST maps ecosystem services and the quality of species habitat as production functions of LULC using simple biophysical models. Models were parameterized using data from regional agencies, literature surveys, global databases, site visits and prior field experience (Table 1)... Our nutrient retention model estimates nitrogen and phosphorus loading (kg y^-1), leading causes of water pollution from fertilizer application and other activities, using the export coefficient approach of Reckhow et al. (1980). The model routes nutrient runoff from each land parcel downslope along the flow path, with some of the nutrient that originated upstream being retained by the parcel according to its retention efficiency. For assessing variation within the same LULC map (2008 and each scenario), we compared sediment and nutrient retention across the landscape. However, for assessing change to scenarios, we compared sediment and nutrient export between the relevant LULC maps, as the change in export (rather than in retention) better reflects the change in service experienced downstream. ...Although InVEST reports ecosystem services in biophysical units, its simple models are best suited to understanding broad patterns of spatial variation (Tallis and Polasky, 2011), rather than for precise quantification. Additionally, we lacked field measurements against which to calibrate our outputs. Therefore, we focused on relative spatial distribution across the landscape, and relative change to scenarios." |
Specific Policy or Decision Context Cited
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This analysis provided input to government-led spatial planning and strategic environmental assessments in the study area. This region contains some of the last remaining forest habitat of the critically endangered Sumatran tiger, Panthera tigris sumatrae. |
Biophysical Context
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Six watersheds in central Sumatra covering portions of Riau, Jambi and West Sumatra provinces. The Barisan mountain range comprises the western edge of the watersheds, while peat swamps predominate in the east. |
EM Scenario Drivers
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Baseline year 2008, future LULC Sumatra 2020 Roadmap (Vision), future LULC Government Spatial Plan |
EM ID
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EM-363 ![]() |
Method Only, Application of Method or Model Run
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Method + Application (multiple runs exist) View EM Runs |
New or Pre-existing EM?
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Application of existing model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
EM ID
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EM-363 ![]() |
Document ID for related EM
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Doc-338 | Doc-205 |
EM ID for related EM
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EM-438 | EM-112 |
EM Modeling Approach
EM ID
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EM-363 ![]() |
EM Temporal Extent
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2008-2020 |
EM Time Dependence
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time-stationary |
EM Time Reference (Future/Past)
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Not applicable |
EM Time Continuity
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Not applicable |
EM Temporal Grain Size Value
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Not applicable |
EM Temporal Grain Size Unit
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Not applicable |
EM ID
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EM-363 ![]() |
Bounding Type
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Watershed/Catchment/HUC |
Spatial Extent Name
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central Sumatra |
Spatial Extent Area (Magnitude)
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100,000-1,000,000 km^2 |
EM ID
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EM-363 ![]() |
EM Spatial Distribution
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spatially distributed (in at least some cases) |
Spatial Grain Type
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area, for pixel or radial feature |
Spatial Grain Size
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30 m x 30 m |
EM ID
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EM-363 ![]() |
EM Computational Approach
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Analytic |
EM Determinism
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deterministic |
Statistical Estimation of EM
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EM ID
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EM-363 ![]() |
Model Calibration Reported?
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No |
Model Goodness of Fit Reported?
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No |
Goodness of Fit (metric| value | unit)
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None |
Model Operational Validation Reported?
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No |
Model Uncertainty Analysis Reported?
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No |
Model Sensitivity Analysis Reported?
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No |
Model Sensitivity Analysis Include Interactions?
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Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
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None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-363 ![]() |
Centroid Latitude
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0 |
Centroid Longitude
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102 |
Centroid Datum
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WGS84 |
Centroid Coordinates Status
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Provided |
EM ID
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EM-363 ![]() |
EM Environmental Sub-Class
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Inland Wetlands | Lakes and Ponds | Forests | Agroecosystems | Created Greenspace | Grasslands | Scrubland/Shrubland | Barren |
Specific Environment Type
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104 land use land cover classes |
EM Ecological Scale
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Ecological scale is finer than that of the Environmental Sub-class |
Scale of differentiation of organisms modeled
EM ID
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EM-363 ![]() |
EM Organismal Scale
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Community |
Taxonomic level and name of organisms or groups identified
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None Available |
EnviroAtlas URL
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Total Annual Nitrogen Deposition, The Watershed Boundary Dataset (WBD) |
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)
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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-363 ![]() |
None |