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-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
EM Short Name
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InVEST carbon storage and sequestration (v3.2.0) | VELMA soil temperature, Oregon, USA | Waterfowl pairs, CREP wetlands, Iowa, USA | Vista land-sea planning submodel |
EM Full Name
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InVEST v3.2.0 Carbon storage and sequestration | VELMA (Visualizing Ecosystems for Land Management Assessments) soil temperature, Oregon, USA | Waterfowl pairs, CREP (Conservation Reserve Enhancement Program) wetlands, Iowa, USA | A technical guide to the integrated land-sea planning toolkit |
EM Source or Collection
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InVEST | US EPA | None | None |
EM Source Document ID
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315 | 317 | 372 | 473 |
Document Author
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The Natural Capital Project | Abdelnour, A., McKane, R. B., Stieglitz, M., Pan, F., and Chen, Y. | Otis, D. L., W. G. Crumpton, D. Green, A. K. Loan-Wilsey, R. L. McNeely, K. L. Kane, R. Johnson, T. Cooper, and M. Vandever | Crist, P., Madden, K., Varley, I., Eslinger, D., Walker, D., Anderson, A., Morehead, S. and Dunton, K., |
Document Year
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2015 | 2013 | 2010 | 2009 |
Document Title
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Carbon storage and sequestration - InVEST (v3.2.0) | Effects of harvest on carbon and nitrogen dynamics in a Pacific Northwest forest catchment | Assessment of environmental services of CREP wetlands in Iowa and the midwestern corn belt | Integrated Land-Sea Planning: A Technical Guide to the Integrated Land-Sea Planning Toolkit. |
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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Website | Published journal manuscript | Published report | Published report |
EM ID
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EM-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
https://www.naturalcapitalproject.org/invest/ | Bob McKane, VELMA Team Lead, USEPA-ORD-NHEERL-WED, Corvallis, OR (541) 754-4631; mckane.bob@epa.gov | Not applicable | https://repositories.lib.utexas.edu/bitstreams/3dee92a8-9373-4bcc-be25-eda74e81fabf/download | |
Contact Name
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The Natural Capital Project | Alex Abdelnour | David Otis |
Patrick Crist ?Comment:No contact information provided |
Contact Address
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371 Serra Mall Stanford University Stanford, CA 94305-5020 USA | Department of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0355, USA | U.S. Geological Survey, Iowa Cooperative Fish and Wildlife Research Unit, Iowa State University | None provided |
Contact Email
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invest@naturalcapitalproject.org | abdelnouralex@gmail.com | dotis@iastate.edu | patrick@planitfwd.com |
EM ID
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EM-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
Summary Description
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Please note: This ESML entry describes an InVEST model version that was current as of 2015. More recent versions may be available at the InVEST website. ABSTRACT: "Terrestrial ecosystems, which store more carbon than the atmosphere, are vital to influencing carbon dioxide-driven climate change. The InVEST model uses maps of land use and land cover types and data on wood harvest rates, harvested product degradation rates, and stocks in four carbon pools (aboveground biomass, belowground biomass, soil, dead organic matter) to estimate the amount of carbon currently stored in a landscape or the amount of carbon sequestered over time. Additional data on the market or social value of sequestered carbon and its annual rate of change, and a discount rate can be used in an optional model that estimates the value of this environmental service to society. Limitations of the model include an oversimplified carbon cycle, an assumed linear change in carbon sequestration over time, and potentially inaccurate discounting rates." AUTHOR'S DESCRIPTION: "A fifth optional pool included in the model applies to parcels that produce harvested wood products (HWPs) such as firewood or charcoal or more long-lived products such as house timbers or furniture. Tracking carbon in this pool is useful because it represents the amount of carbon kept from the atmosphere by a given product." | ABSTRACT: "We used a new ecohydrological model, Visualizing Ecosystems for Land Management Assessments (VELMA), to analyze the effects of forest harvest on catchment carbon and nitrogen dynamics. We applied the model to a 10 ha headwater catchment in the western Oregon Cascade Range where two major disturbance events have occurred during the past 500 years: a stand-replacing fire circa 1525 and a clear-cut in 1975. Hydrological and biogeochemical data from this site and other Pacific Northwest forest ecosystems were used to calibrate the model. Model parameters were first calibrated to simulate the postfire buildup of ecosystem carbon and nitrogen stocks in plants and soil from 1525 to 1969, the year when stream flow and chemistry measurements were begun. Thereafter, the model was used to simulate old-growth (1969–1974) and postharvest (1975–2008) temporal changes in carbon and nitrogen dynamics…" AUTHOR'S DESCRIPTION: "The soil column model consists of three coupled submodels:...a soil temperature model [Cheng et al., 2010] that simulates daily soil layer temperatures from surface air temperature and snow depth by propagating the air temperature first through the snowpack and then through the ground using the analytical solution of the one-dimensional thermal diffusion equation" | ABSTRACT: "This final project report is a compendium of 3 previously submitted progress reports and a 4th report for work accomplished from August – December, 2009. Our initial primary objective (Progress Report I) was prediction of environmental services provided by the 27 Iowa Conservation Reserve Enhancement Program (CREP) wetland sites that had been completed by 2007 in the Prairie Pothole Region of northcentral Iowa. The sites contain 102.4 ha of wetlands and 377.4 ha of associated grassland buffers... With respect to wildlife habitat value, USFWS models predicted that the 27 wetlands would provide habitat for 136 pairs of 6 species of ducks, 48 pairs of Canada Geese, and 839 individuals of 5 grassland songbird species of special concern..." AUTHOR'S DESCRIPTION: "Number of duck pairs per site was estimated for 6 species of ducks: Mallard (Anas platyrhynchos), Blue-winged Teal (Anas discors), Northern Shoveler (Anas clypeata), Gadwall (Anas strepera), Northern Pintail (Anas acuta), and Wood Duck (Aix sponsa), using models developed by Cowardin et al. (1995). Pair abundance was based on wetland class (i.e., temporary, seasonal, semi-permanent, lake, or river), wetland size, and a set of species specific regression coefficients. All CREP wetlands were considered semi-permanent for this analysis; therefore only coefficients associated with the semipermanent wetland pair model were used in calculations. The general equation used to estimate the pairs per wetland was: Pairs = e (a + bx + α) * p where, e = mathematical constant ≈ 2.718, a = species specific regression coefficient a, b = species specific regression coefficient b, x = the natural log of wetland size, α = species specific alpha value, and p = proportion of the basin containing water (assumed to be 0.90 for this analysis)" | NatureServe Vista is a broad assessment and planning decision support tool focused on conservation of specific mapped features or “conservation elements.” It facilitates capturing spatial and non-spatial information and conservation requirements for elements, defining scenarios of land use, management, conservation, disturbance, etc., and evaluating the impacts of scenarios on the elements. Vista also contains powerful internal tools and interoperability with outside tools to facilitate mitigating site-level conflicts, offsite mitigation, and development of alternative scenarios. The primary objective (though not exclusive application) of the tool is to develop/mitigate alternative scenarios such that they meet explicit conservation goals for the elements. Vista can also support goal seeking for competing land uses while preventing development of scenarios that attempt to meet goals for conflicting things in the same place. The primary role of NatureServe Vista in this toolkit is to evaluate the impacts of land use scenarios on conservation elements in terrestrial, freshwater, and marine ecosystems. It does this through direct evaluation of land use scenarios from CommunityViz (augmented with other use, management, disturbance data) and interoperating with N-SPECT to evaluate water quality impacts on aquatic/marine elements. |
Specific Policy or Decision Context Cited
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None identified | None identified | None identified | None provided |
Biophysical Context
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Not applicable | Basin elevation ranges from 430 m at the stream gauging station to 700 m at the southeastern ridgeline. Near stream and side slope gradients are approximately 24o and 25o to 50o, respectively. The climate is relatively mild with wet winters and dry summer. Mean annual temperature is 8.5 oC. Daily temperature extremes vary from 39 oC in the summer to -20 oC in the winter. | Prairie pothole region of north-central Iowa | Not applicable |
EM Scenario Drivers
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Optional future scenarios for changed LULC and wood harvest | No scenarios presented | No scenarios presented | No scenarios presented |
EM ID
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EM-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
Method Only, Application of Method or Model Run
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Method Only | Method + Application | Method + Application (multiple runs exist) View EM Runs | Method Only |
New or Pre-existing EM?
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New or revised model | 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-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
Document ID for related EM
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Doc-309 | Doc-13 | Doc-317 | None | Doc-473 |
EM ID for related EM
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EM-349 | EM-375 | EM-380 | EM-884 | EM-883 | EM-887 | EM-705 | EM-703 | EM-702 | EM-701 | EM-700 | EM-1003 | EM-1005 | EM-1007 | EM-1008 |
EM Modeling Approach
EM ID
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EM-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
EM Temporal Extent
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Not applicable | 1969-2008 | 2002-2007 | Not applicable |
EM Time Dependence
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time-dependent | time-dependent | time-stationary | time-dependent |
EM Time Reference (Future/Past)
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future time | future time | Not applicable | Not applicable |
EM Time Continuity
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discrete | discrete | Not applicable | other or unclear (comment) |
EM Temporal Grain Size Value
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1 | 1 | Not applicable | Not applicable |
EM Temporal Grain Size Unit
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Year | Day | Not applicable | Not applicable |
EM ID
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EM-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
Bounding Type
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Not applicable | Watershed/Catchment/HUC | Multiple unrelated locations (e.g., meta-analysis) | Not applicable |
Spatial Extent Name
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Not applicable | H. J. Andrews LTER WS10 | CREP (Conservation Reserve Enhancement Program) wetland sites | Not applicable |
Spatial Extent Area (Magnitude)
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Not applicable | 10-100 ha | 1-10 km^2 | Not applicable |
EM ID
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EM-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
EM Spatial Distribution
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spatially distributed (in at least some cases) |
spatially distributed (in at least some cases) ?Comment:See below, grain includes vertical, subsurface dimension. |
spatially distributed (in at least some cases) | other or unclear (comment) |
Spatial Grain Type
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area, for pixel or radial feature | volume, for 3-D feature | other (specify), for irregular (e.g., stream reach, lake basin) | Not applicable |
Spatial Grain Size
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application specific | 30 m x 30 m surface pixel and 2-m depth soil column | multiple, individual, irregular shaped sites | Not applicable |
EM ID
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EM-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
EM Computational Approach
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Analytic | Numeric | Analytic | 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-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
Model Calibration Reported?
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Not applicable | No | Unclear | Not applicable |
Model Goodness of Fit Reported?
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Not applicable | No | No | Not applicable |
Goodness of Fit (metric| value | unit)
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None | None | None | None |
Model Operational Validation Reported?
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Not applicable | No | Unclear | Not applicable |
Model Uncertainty Analysis Reported?
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Not applicable | No | No | Not applicable |
Model Sensitivity Analysis Reported?
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Not applicable | No | No | 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-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
None |
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None |
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
None | None | None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
Centroid Latitude
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-9999 | 44.25 | 42.62 | Not applicable |
Centroid Longitude
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-9999 | -122.33 | -93.84 | Not applicable |
Centroid Datum
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Not applicable | WGS84 | WGS84 | Not applicable |
Centroid Coordinates Status
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Not applicable | Provided | Estimated | Not applicable |
EM ID
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EM-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
EM Environmental Sub-Class
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Not applicable | Forests | Inland Wetlands | Agroecosystems | Grasslands | Not applicable |
Specific Environment Type
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Terrestrial environments, but not specified for methods | 400 to 500 year old forest dominated by Douglas-fir (Pseudotsuga menziesii), western hemlock (Tsuga heterophylla), and western red cedar (Thuja plicata). | Wetlands buffered by grassland set in agricultural land | None |
EM Ecological Scale
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Not applicable | Ecological scale is finer than that of the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class |
Scale of differentiation of organisms modeled
EM ID
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EM-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
EM Organismal Scale
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Not applicable | Not applicable | Species | Community |
Taxonomic level and name of organisms or groups identified
EM-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
None Available | None Available |
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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-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
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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-374 | EM-379 |
EM-632 ![]() |
EM-1006 |
None | None |
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None |