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
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EM ID
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EM-374 | EM-432 |
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EM Short Name
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InVEST carbon storage and sequestration (v3.2.0) | Nitrogen fixation rates, Guánica Bay, Puerto Rico |
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EM Full Name
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InVEST v3.2.0 Carbon storage and sequestration | Nitrogen fixation rates, Guánica Bay, Puerto Rico, USA |
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EM Source or Collection
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InVEST | US EPA |
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EM Source Document ID
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315 |
338 ?Comment:WE received a draft copy prior to journal publication that was agency reviewed. |
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Document Author
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The Natural Capital Project | Amelia Smith, Susan Harrell Yee, Marc Russell, Jill Awkerman and William S. Fisher |
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Document Year
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2015 | 2017 |
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Document Title
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Carbon storage and sequestration - InVEST (v3.2.0) | Linking ecosystem services supply to stakeholder concerns on both land and sea: An example from Guanica Bay watershed, Puerto Rico |
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Document Status
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Peer reviewed and published | Peer reviewed and published |
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Comments on Status
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Website | Published journal manuscript |
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EM ID
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EM-374 | EM-432 |
| https://www.naturalcapitalproject.org/invest/ | Not applicable | |
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Contact Name
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The Natural Capital Project | Susan H. Yee |
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Contact Address
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371 Serra Mall Stanford University Stanford, CA 94305-5020 USA | U.S. Environmental Protection Agency, Gulf Ecology Division, Gulf Breeze, FL 32561, USA |
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Contact Email
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invest@naturalcapitalproject.org | yee.susan@epa.gov |
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EM ID
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EM-374 | EM-432 |
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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." | AUTHOR'S DESCRIPTION: " …In Guánica Bay watershed, Puerto Rico, deforestation and drainage of a large lagoon have led to sediment, contaminant, and nutrient transport into the bay, resulting in declining quality of coral reefs. A watershed management plan is currently being implemented to restore reefs through a variety of proposed actions…After the workshops, fifteen indicators of terrestrial ecosystem services in the watershed and four indicators in the coastal zone were identified to reflect the wide range of stakeholder concerns that could be impacted by management decisions. Ecosystem service production functions were applied to quantify and map ecosystem services supply in the Guánica Bay watershed, as well as an additional highly engineered upper multi-watershed area connected to the lower watershed via a series of reservoirs and tunnels,…” AUTHOR''S DESCRIPTION: "The U.S. Coral Reef Task Force (CRTF), a collaboration of federal, state and territorial agencies, initiated a program in 2009 to better incorporate land-based sources of pollution and socio-economic considerations into watershed strategies for coral reef protection (Bradley et al., 2016)...Baseline measures for relevant ecosystem services were calculated by parameterizing existing methods, largely based on land cover (Egoh et al., 2012; Martinez- Harms and Balvanera, 2012), with relevant rates of ecosystem services production for Puerto Rico, and applying them to map ecosystem services supply for the Guánica Bay Watershed...The Guánica Bay watershed is a highly engineered watershed in southwestern Puerto Rico, with a series of five reservoirs and extensive tunnel systems artificially connecting multiple mountainous sub-watersheds to the lower watershed of the Rio Loco, which itself is altered by an irrigation canal and return drainage ditch that diverts water through the Lajas Valley (PRWRA, 1948)...For each objective, a translator of ecosystem services production, i.e., ecological production function, was used to quantify baseline measurements of ecosystem services supply from land use/land cover (LULC) maps for watersheds across Puerto Rico...Two additional metrics, nitrogen fixation and rates of carbon sequestration into soil and sediment, were also calculated as potential measures of soil quality and agricultural productivity. Carbon sequestration and nitrogen fixation rates were assigned to each land cover class" |
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Specific Policy or Decision Context Cited
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None identified | None provided |
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Biophysical Context
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Not applicable | No additional description provided |
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EM Scenario Drivers
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Optional future scenarios for changed LULC and wood harvest | No scenarios presented |
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EM ID
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EM-374 | EM-432 |
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Method Only, Application of Method or Model Run
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Method Only | Method + Application |
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New or Pre-existing EM?
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New or revised model | Application of existing model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
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EM ID
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EM-374 | EM-432 |
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Document ID for related EM
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Doc-309 | None |
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EM ID for related EM
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EM-349 | None |
EM Modeling Approach
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EM ID
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EM-374 | EM-432 |
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EM Temporal Extent
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Not applicable | 1978 - 2009 |
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EM Time Dependence
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time-dependent | time-stationary |
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EM Time Reference (Future/Past)
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future time | Not applicable |
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EM Time Continuity
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discrete | Not applicable |
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EM Temporal Grain Size Value
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1 | Not applicable |
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EM Temporal Grain Size Unit
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Year | Not applicable |
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EM ID
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EM-374 | EM-432 |
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Bounding Type
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Not applicable | Watershed/Catchment/HUC |
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Spatial Extent Name
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Not applicable | Guanica Bay watershed |
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Spatial Extent Area (Magnitude)
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Not applicable | 100-1000 km^2 |
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EM ID
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EM-374 | EM-432 |
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EM Spatial Distribution
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spatially distributed (in at least some cases) | spatially distributed (in at least some cases) |
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Spatial Grain Type
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area, for pixel or radial feature | other (specify), for irregular (e.g., stream reach, lake basin) |
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Spatial Grain Size
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application specific | HUC |
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EM ID
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EM-374 | EM-432 |
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EM Computational Approach
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Analytic | Analytic |
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EM Determinism
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deterministic | deterministic |
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Statistical Estimation of EM
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EM ID
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EM-374 | EM-432 |
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Model Calibration Reported?
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Not applicable | No |
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Model Goodness of Fit Reported?
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Not applicable | No |
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Goodness of Fit (metric| value | unit)
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None | None |
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Model Operational Validation Reported?
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Not applicable | No |
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Model Uncertainty Analysis Reported?
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Not applicable | No |
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Model Sensitivity Analysis Reported?
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Not applicable | No |
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Model Sensitivity Analysis Include Interactions?
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Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
| EM-374 | EM-432 |
| None |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
| EM-374 | EM-432 |
| None | None |
Centroid Lat/Long (Decimal Degree)
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EM ID
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EM-374 | EM-432 |
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Centroid Latitude
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-9999 | 17.96 |
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Centroid Longitude
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-9999 | -67.02 |
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Centroid Datum
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Not applicable | WGS84 |
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Centroid Coordinates Status
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Not applicable | Estimated |
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EM ID
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EM-374 | EM-432 |
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EM Environmental Sub-Class
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Not applicable | Inland Wetlands | Forests | Agroecosystems | Created Greenspace | Grasslands | Scrubland/Shrubland | Barren |
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Specific Environment Type
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Terrestrial environments, but not specified for methods | Tropical terrestrial |
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EM Ecological Scale
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Not applicable | Ecological scale is finer than that of the Environmental Sub-class |
Scale of differentiation of organisms modeled
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EM ID
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EM-374 | EM-432 |
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EM Organismal Scale
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Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
| EM-374 | EM-432 |
| None Available | None Available |
EnviroAtlas URL
| EM-374 | EM-432 |
| GAP Ecological Systems, Carbon Storage by Tree Biomass, Hectares of cotton crops | Total Annual Reduced Nitrogen Deposition, The Watershed Boundary Dataset (WBD), Percent Impervious Area |
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-432 |
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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-432 |
| None |
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