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-81 | EM-94 | EM-439 |
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EM Short Name
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Cultural ES and plant traits, Central French Alps | Reduction in pesticide runoff risk, Europe | WaSSI, Conterminous USA |
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EM Full Name
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Cultural ecosystem service estimated from plant functional traits, Central French Alps | Reduction in pesticide runoff risk, Europe | Water Supply Stress Index, Conterminous USA |
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EM Source or Collection
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EU Biodiversity Action 5 | None |
USDA Forest Service ?Comment:While the user guide on which model entry is based has not been peer reviewed, several peer reviewed journal articles describing this USA HUC8 version of WaSSI have been published. |
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EM Source Document ID
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260 | 255 | 341 |
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Document Author
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Lavorel, S., Grigulis, K., Lamarque, P., Colace, M-P, Garden, D., Girel, J., Pellet, G., and Douzet, R. | Lautenbach, S., Maes, J., Kattwinkel, M., Seppelt, R., Strauch, M., Scholz, M., Schulz-Zunkel, C., Volk, M., Weinert, J. and Dormann, C. | Peter Caldwell, Ge Sun, Steve McNulty, Jennifer Moore Myers, Erika Cohen, Robert Herring, Erik Martinez |
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Document Year
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2011 | 2012 | 2013 |
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Document Title
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Using plant functional traits to understand the landscape distribution of multiple ecosystem services | Mapping water quality-related ecosystem services: concepts and applications for nitrogen retention and pesticide risk reduction | WaSSI Ecosystem Services Model |
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Document Status
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Peer reviewed and published | Peer reviewed and published | Not peer reviewed but is published (explain in Comment) |
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Comments on Status
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Published journal manuscript | Published journal manuscript | While the user guide on which model entry is based has not been peer reviewed, several peer reviewed journal articles describing this USA HUC8 version of WaSSI have been published. |
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EM ID
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EM-81 | EM-94 | EM-439 |
| Not applicable | Not applicable | http://www.wassiweb.sgcp.ncsu.edu/ | |
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Contact Name
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Sandra Lavorel | Sven Lautenbach | Ge Sun |
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Contact Address
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Laboratoire d’Ecologie Alpine, UMR 5553 CNRS Université Joseph Fourier, BP 53, 38041 Grenoble Cedex 9, France | Department of Computational Landscape Ecology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany | Eastern Forest Environmental Threat Assessment Center, Southern Research Station, USDA Forest Service, 920 Main Campus Dr. Venture II, Suite 300, Raleigh, NC 27606 |
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Contact Email
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sandra.lavorel@ujf-grenoble.fr | sven.lautenbach@ufz.de | gesun@fs.fed.us |
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EM ID
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EM-81 | EM-94 | EM-439 |
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Summary Description
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ABSTRACT: "Here, we propose a new approach for the analysis, mapping and understanding of multiple ES delivery in landscapes. Spatially explicit single ES models based on plant traits and abiotic characteristics are combined to identify ‘hot’ and ‘cold’ spots of multiple ES delivery, and the land use and biotic determinants of such distributions. We demonstrate the value of this trait-based approach as compared to a pure land-use approach for a pastoral landscape from the central French Alps, and highlight how it improves understanding of ecological constraints to, and opportunities for, the delivery of multiple services." AUTHOR'S DESCRIPTION: "The Cultural ecosystem service map was a simple sum of maps for relevant Ecosystem Properties (produced in related EMs) after scaling to a 0–100 baseline and trimming outliers to the 5–95% quantiles (Venables&Ripley 2002)…Coefficients used for the summing of individual ecosystem properties to cultural ecosystem services were based on stakeholders’ perceptions, given positive or negative contributions." | AUTHOR'S DESCRIPTION: "We used a spatially explicit model to predict the potential exposure of small streams to insecticides (run-off potential – RP) as well as the resulting ecological risk (ER) for freshwater fauna on the European scale (Schriever and Liess 2007; Kattwinkel et al. 2011)...The recovery of community structure after exposure to insecticides is facilitated by the presence of undisturbed upstream stretches that can act as sources for recolonization (Niemi et al. 1990; Hatakeyama and Yokoyama 1997). In the absence of such sources for recolonization, the structure of the aquatic community at sites that are exposed to insecticides differs significantly from that of reference sites (Liess and von der Ohe 2005)...Hence, we calculated the ER depending on RP for insecticides and the amount of recolonization zones. ER gives the percentage of stream sites in each grid cell (10 × 10 km) in which the composition of the aquatic community deviated from that of good ecological status according to the WFD. In a second step, we estimated the service provided by the environment comparing the ER of a landscape lacking completely recolonization sources with that of the actual landscape configuration. Hence, the ES provided by non-arable areas (forests, pastures, natural grasslands, moors and heathlands) was calculated as the reduction of ER for sensitive species. The service can be thought of as a habitat provisioning/nursery service that leads to an improvement of ecological water quality." | AUTHORS DESCRIPTION: "WaSSI simulates monthly water and carbon dynamics at the Hydrologic Unit Code 8 level in the US. Three modules are integrated within the WaSSI model framework. The water balance module computes ecosystem water use, evapotranspiration and the water yield from each watershed. Water yield is sometimes referred to as runoff and can be thought of as the amount of streamflow at the outlet of each watershed due to hydrologic processes in each watershed in isolation without any flow contribution from upstream watersheds. The ecosystem productivity module simulates carbon gains and losses in each watershed or grid cell as functions of evapotranspiration. The water supply and demand module routes and accumulates the water yield through the river network according to topological relationships between adjacent watersheds, subtracts consumptive water use by humans from river flows, and compares water supply to water demand to compute the water supply stress index, or WaSSI." |
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Specific Policy or Decision Context Cited
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None identified | European Commission Water Framework Directive (WFD, Directive 2000/60/EC) | WaSSI can be used to project the regional effects of forest land cover change, climate change, and water withdrawals on river flows, water supply stress, and ecosystem productivity (i.e., carbon sequestration).WaSSI can be used to evaluate trade-offs among management strategies that influence multiple ecosystem services |
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Biophysical Context
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Elevations ranging from 1552 m to 2442 m, on predominantly south-facing slopes | Not applicable | Conterminous US |
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EM Scenario Drivers
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No scenarios presented | No scenarios presented |
No scenarios presented ?Comment:Model can be run from WaSSI website using a historic data set (1961 - 2010) or projections from various climate models representing different emissions scenarios and time periods from recent past to 2099. |
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EM ID
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EM-81 | EM-94 | EM-439 |
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Method Only, Application of Method or Model Run
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Method + Application | Method + Application | Method + Application |
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New or Pre-existing EM?
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New or revised model | Application of existing model |
Application of existing model ?Comment:. |
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-81 | EM-94 | EM-439 |
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Document ID for related EM
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None |
Doc-254 | Doc-256 ?Comment:Document 254 was also used as a source document for this EM |
None |
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EM ID for related EM
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EM-65 | EM-66 | EM-68 | EM-69 | EM-70 | EM-71 | EM-79 | EM-80 | EM-82 | EM-83 | None | None |
EM Modeling Approach
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EM ID
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EM-81 | EM-94 | EM-439 |
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EM Temporal Extent
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Not reported | 2000 | 1961-2009 |
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EM Time Dependence
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time-stationary | time-stationary | time-dependent |
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EM Time Reference (Future/Past)
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Not applicable | Not applicable | future time |
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EM Time Continuity
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Not applicable | Not applicable | discrete |
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EM Temporal Grain Size Value
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Not applicable | Not applicable | 1 |
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EM Temporal Grain Size Unit
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Not applicable | Not applicable | Month |
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EM ID
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EM-81 | EM-94 | EM-439 |
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Bounding Type
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Physiographic or Ecological | Geopolitical | Watershed/Catchment/HUC |
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Spatial Extent Name
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Central French Alps | EU-27 | All 8-digit hydrologic unit codes (HUC-8) in the conterminous USA |
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Spatial Extent Area (Magnitude)
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10-100 km^2 | >1,000,000 km^2 | >1,000,000 km^2 |
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EM ID
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EM-81 | EM-94 | EM-439 |
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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) |
spatially distributed (in at least some cases) ?Comment:Spatial grain for computations is the HUC-8. A HUC-12 version is under development. Spatial grain for computations is comprised of 16,005 polygons of various size covering 7091 ha. |
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Spatial Grain Type
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area, for pixel or radial feature | 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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20 m x 20 m | 10 km x 10 km | Computations are at the 8-digit HUC scale. MostHUC-8 watersheds are within a range of 800-8000 km^2 (500-5000 mi^2) in size. |
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EM ID
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EM-81 | EM-94 | EM-439 |
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EM Computational Approach
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Analytic | Analytic | Numeric |
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EM Determinism
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deterministic | deterministic | deterministic |
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Statistical Estimation of EM
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EM ID
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EM-81 | EM-94 | EM-439 |
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Model Calibration Reported?
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No | No | No |
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Model Goodness of Fit Reported?
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No | No | No |
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Goodness of Fit (metric| value | unit)
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None | None | None |
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Model Operational Validation Reported?
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No | Yes | No |
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Model Uncertainty Analysis Reported?
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No | No | No |
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Model Sensitivity Analysis Reported?
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No | No | No |
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Model Sensitivity Analysis Include Interactions?
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Not applicable | Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
| EM-81 | EM-94 | EM-439 |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
| EM-81 | EM-94 | EM-439 |
| None | None | None |
Centroid Lat/Long (Decimal Degree)
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EM ID
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EM-81 | EM-94 | EM-439 |
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Centroid Latitude
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45.05 | 50.53 | 39.83 |
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Centroid Longitude
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6.4 | 7.6 | -98.58 |
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Centroid Datum
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WGS84 | WGS84 | WGS84 |
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Centroid Coordinates Status
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Provided | Estimated | Estimated |
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EM ID
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EM-81 | EM-94 | EM-439 |
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EM Environmental Sub-Class
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Agroecosystems | Grasslands | Rivers and Streams | Forests | Agroecosystems | Grasslands | Scrubland/Shrubland |
Lakes and Ponds ?Comment:Watershed model represents all land areas, major streams and rivers. Since leaf area index, LAI, is an important variable, forests, created greenspaces (e.g., urban forests) and scrub/shrub subclasses are included. |
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Specific Environment Type
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Subalpine terraces, grasslands, and meadows. | Streams and near upstream environments | Not applicable |
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EM Ecological Scale
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Ecological scale is coarser than that of the Environmental Sub-class | Ecological scale is coarser than that of the Environmental Sub-class |
Ecological scale is coarser than that of the Environmental Sub-class ?Comment:Terrestrial characteristics are aggregated at a broad (HUC-8) scale; different types of aquatic sub-classes are not differentiated. |
Scale of differentiation of organisms modeled
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EM ID
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EM-81 | EM-94 | EM-439 |
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EM Organismal Scale
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Community | Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
| EM-81 | EM-94 | EM-439 |
| None Available | None Available | 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-81 | EM-94 | EM-439 |
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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-81 | EM-94 | EM-439 |
| None | None |
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