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-94 | EM-617 |
EM-863 ![]() |
EM Short Name
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Reduction in pesticide runoff risk, Europe | RBI Spatial Analysis Method | SLAMM, Tampa Bay, FL, USA |
EM Full Name
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Reduction in pesticide runoff risk, Europe | Rapid Benefit Indicator (RBI) Spatial Analysis Toolset Method | SLAMM (sea level affecting marshes model), Tampa Bay, Florida, USA |
EM Source or Collection
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None | None | None |
EM Source Document ID
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255 | 367 |
415 ?Comment:Secondary sources: Documents 412 and 413. |
Document Author
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Lautenbach, S., Maes, J., Kattwinkel, M., Seppelt, R., Strauch, M., Scholz, M., Schulz-Zunkel, C., Volk, M., Weinert, J. and Dormann, C. | Bousquin, J., Mazzotta M., and W. Berry | Sherwood, E. T. and H. S. Greening |
Document Year
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2012 | 2017 | 2014 |
Document Title
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Mapping water quality-related ecosystem services: concepts and applications for nitrogen retention and pesticide risk reduction | Rapid Benefit Indicators (RBI) Spatial Analysis Toolset - Manual. | Potential impacts and management implications of climate change on Tampa Bay estuary critical coastal habitats |
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 EPA report | Published journal manuscript |
EM ID
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EM-94 | EM-617 |
EM-863 ![]() |
Not applicable | Not applicable | http://warrenpinnacle.com/prof/SLAMM/index.html com/prof/SLAMM/index.html | |
Contact Name
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Sven Lautenbach | Justin Bousquin | Edward T. Sherwood |
Contact Address
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Department of Computational Landscape Ecology, Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany | US EPA, Office of Research and Development, National health and environmental Effects Lab, Gulf Ecology Division, Gulf Breeze, FL 32561 | Tampa Bay Estuary Program, 263 13th Avenue South, St. Petersburg, FL 33701, USA |
Contact Email
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sven.lautenbach@ufz.de | bousquin.justin@epa.gov | esherwood@tbep.org |
EM ID
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EM-94 | EM-617 |
EM-863 ![]() |
Summary Description
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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." | AUTHOR DESCRIPTION: "The Rapid Benefits Indicators (RBI) approach consists of five steps and is outlined in Assessing the Benefits of Wetland Restoration – A Rapid Benefits Indicators Approach for Decision Makers, hereafter referred to as the “guide.” The guide presents the assessment approach, detailing each step of the indicator development process and providing an example application in the “Step in Action” pages. The spatial analysis toolset is intended to be used to analyze existing spatial information to produce metrics for many of the indicators developed in that guide. This spatial analysis toolset manual gives directions on the mechanics of the tool and its data requirements, but does not detail the reasoning behind the indicators and how to use results of the assessment; this information is found in the guide. " | ABSTRACT: "The Tampa Bay estuary is a unique and valued ecosystem that currently thrives between subtropical and temperate climates along Florida’s west-central coast. The watershed is considered urbanized (42 % lands developed); however, a suite of critical coastal habitats still persists. Current management efforts are focused toward restoring the historic balance of these habitat types to a benchmark 1950s period. We have modeled the anticipated changes to a suite of habitats within the Tampa Bay estuary using the sea level affecting marshes model (SLAMM) under various sea level rise (SLR) scenarios. Modeled changes to the distribution and coverage of mangrove habitats within the estuary are expected to dominate the overall proportions of future critical coastal habitats. Modeled losses in salt marsh, salt barren, and coastal freshwater wetlands by 2100 will significantly affect the progress achieved in ‘‘Restoring the Balance’’ of these habitat types over recent periods…" |
Specific Policy or Decision Context Cited
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European Commission Water Framework Directive (WFD, Directive 2000/60/EC) | None identified | None identified |
Biophysical Context
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Not applicable | wetlands | No additional description provided |
EM Scenario Drivers
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No scenarios presented | N/A | Varying sea level rise (baseline - 2m), and two habitat adaption strategies |
EM ID
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EM-94 | EM-617 |
EM-863 ![]() |
Method Only, Application of Method or Model Run
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Method + Application | Method Only | Method + Application (multiple runs exist) View EM Runs |
New or Pre-existing EM?
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Application of existing model | New or revised model | 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-94 | EM-617 |
EM-863 ![]() |
Document ID for related EM
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Doc-254 | Doc-256 ?Comment:Document 254 was also used as a source document for this EM |
None | Doc-412 | Doc-413 |
EM ID for related EM
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None | None | EM-857 |
EM Modeling Approach
EM ID
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EM-94 | EM-617 |
EM-863 ![]() |
EM Temporal Extent
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2000 | Not applicable | 2002-2100 |
EM Time Dependence
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time-stationary | time-stationary | time-stationary |
EM Time Reference (Future/Past)
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Not applicable | Not applicable | Not applicable |
EM Time Continuity
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Not applicable | Not applicable | Not applicable |
EM Temporal Grain Size Value
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Not applicable | Not applicable | Not applicable |
EM Temporal Grain Size Unit
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Not applicable | Not applicable | Not applicable |
EM ID
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EM-94 | EM-617 |
EM-863 ![]() |
Bounding Type
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Geopolitical | Not applicable | Watershed/Catchment/HUC |
Spatial Extent Name
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EU-27 | Not applicable | Tampa Bay estuary watershed |
Spatial Extent Area (Magnitude)
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>1,000,000 km^2 | Not applicable | 1000-10,000 km^2. |
EM ID
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EM-94 | EM-617 |
EM-863 ![]() |
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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area, for pixel or radial feature | area, for pixel or radial feature | area, for pixel or radial feature |
Spatial Grain Size
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10 km x 10 km | Not reported | 10 x 10 m |
EM ID
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EM-94 | EM-617 |
EM-863 ![]() |
EM Computational Approach
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Analytic | Analytic | Analytic |
EM Determinism
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deterministic | deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-94 | EM-617 |
EM-863 ![]() |
Model Calibration Reported?
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No | Not applicable | No |
Model Goodness of Fit Reported?
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No | Not applicable | No |
Goodness of Fit (metric| value | unit)
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None | None | None |
Model Operational Validation Reported?
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Yes | Not applicable | No |
Model Uncertainty Analysis Reported?
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No | Not applicable | No |
Model Sensitivity Analysis Reported?
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No | Not applicable | No |
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-94 | EM-617 |
EM-863 ![]() |
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None |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-94 | EM-617 |
EM-863 ![]() |
None | None |
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Centroid Lat/Long (Decimal Degree)
EM ID
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EM-94 | EM-617 |
EM-863 ![]() |
Centroid Latitude
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50.53 | Not applicable | 27.76 |
Centroid Longitude
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7.6 | Not applicable | -82.54 |
Centroid Datum
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WGS84 | Not applicable | WGS84 |
Centroid Coordinates Status
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Estimated | Not applicable | Estimated |
EM ID
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EM-94 | EM-617 |
EM-863 ![]() |
EM Environmental Sub-Class
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Rivers and Streams | Forests | Agroecosystems | Grasslands | Scrubland/Shrubland | Inland Wetlands | Inland Wetlands | Near Coastal Marine and Estuarine | Terrestrial Environment (sub-classes not fully specified) |
Specific Environment Type
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Streams and near upstream environments | Restored wetlands | Esturary and associated urban and terrestrial environment |
EM Ecological Scale
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Ecological scale is coarser 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-94 | EM-617 |
EM-863 ![]() |
EM Organismal Scale
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Not applicable | Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-94 | EM-617 |
EM-863 ![]() |
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-94 | EM-617 |
EM-863 ![]() |
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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-94 | EM-617 |
EM-863 ![]() |
None |
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None |