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-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
EM Short Name
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Landscape importance for crops, Europe | Wetland shellfish production, Gulf of Mexico, USA | Yasso07 - SOC, Loess Plateau, China | WESP: Urban Stormwater Treatment, ID, USA |
EM Full Name
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Landscape importance for crop-based production, Europe | Wetland shellfish production, Gulf of Mexico, USA | Yasso07 - Land Use Effects on Soil Organic Carbon Stocks in the Loess Plateau, China | WESP: Urban Stormwater Treament, ID, USA |
EM Source or Collection
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EU Biodiversity Action 5 |
US EPA ?Comment:Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science |
None | None |
EM Source Document ID
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228 | 324 | 344 |
393 ?Comment:Additional data came from electronic appendix provided by author Chris Murphy. |
Document Author
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Haines-Young, R., Potschin, M. and Kienast, F. | Stephen J. Jordan, Timothy O'Higgins and John A. Dittmar | Wu, Xing, Akujarvi, A., Lu, N., Liski, J., Liu, G., Want, Y, Holmberg, M., Li, F., Zeng, Y., and B. Fu | Murphy, C. and T. Weekley |
Document Year
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2012 | 2012 | 2015 | 2012 |
Document Title
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Indicators of ecosystem service potential at European scales: Mapping marginal changes and trade-offs | Ecosystem Services of Coastal Habitats and Fisheries: Multiscale Ecological and Economic Models in Support of Ecosystem-Based Management | Dynamics of soil organic carbon stock in a typical catchment of the Loess Plateau: comparison of model simulations with measurement | Measuring outcomes of wetland restoration, enhancement, and creation in Idaho-- Assessing potential functions, values, and condition in a watershed context. |
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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Published journal manuscript | Published journal manuscript | Published journal manuscript | Published report |
EM ID
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EM-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
Not applicable | Not applicable | http://en.ilmatieteenlaitos.fi/yasso-download-and-support | Not applicable | |
Contact Name
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Marion Potschin | Stephen J. Jordan | Xing Wu | Chris Murphy |
Contact Address
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Centre for Environmental Management, School of Geography, University of Nottingham, NG7 2RD, United Kingdom | U.S. Environmental Protection Agency, Gulf Ecology Division, 1 Sabine Island Drive, Gulf Breeze, FL 32561, USA | Chinese Academy of Sciences, Beijing 100085, China | Idaho Dept. Fish and Game, Wildlife Bureau, Habitat Section, Boise, ID |
Contact Email
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marion.potschin@nottingham.ac.uk | jordan.steve@epa.gov | xingwu@rceesac.cn | chris.murphy@idfg.idaho.gov |
EM ID
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EM-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
Summary Description
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ABSTRACT: "The study focuses on the EU-25 plus Switzerland and Norway, and develops the methodology proposed by Kienast et al. (2009), which uses expert-and literature-driven modelling methods. The methods are explored in relation to mapping and assessing … “Crop-based production” . . . The potential to deliver services is assumed to be influenced by (a) land-use, (b) net primary production, and (c) bioclimatic and landscape properties such as mountainous terrain." AUTHOR'S DESCRIPTION: "The analysis for "Crop-based production" maps all the areas that are important for food crops produced through commercial agriculture." | ABSTRACT: "We present concepts and case studies linking the production functions (contributions to recruitment) of critical habitats to commercial and recreational fishery values by combining site specific research data with spatial analysis and population models. We present examples illustrating various spatial scales of analysis, with indicators of economic value, for … commercial blue crab Callinectes sapidus and penaeid shrimp fisheries in the Gulf of Mexico." | ABSTRACT: "Land use changes are known to significantly affect the soil C balance by altering both C inputs and losses. Since the late 1990s, a large area of the Loess Plateau has undergone intensive land use changes during several ecological restoration projects to control soil erosion and combat land degradation, especially in the Grain for Green project. By using remote sensing techniques and the Yasso07 model, we simulated the dynamics of soil organic carbon (SOC) stocks in the Yangjuangou catchment of the Loess Plateau. The performance of the model was evaluated by comparing the simulated results with the intensive field measurements in 2006 and 2011 throughout the catchment. SOC stocks and NPP values of all land use types had generally increased during our study period. The average SOC sequestration rate in the upper 30 cm soil from 2006 to 2011 in the Yangjuangou catchment was approximately 44 g C m-2 yr-1, which was comparable to other studies in the Loess Plateau. Forest and grassland showed a more effective accumulation of SOC than the other land use types in our study area. The Yasso07 model performed reasonably well in predicting the overall dynamics of SOC stock for different land use change types at both the site and catchment scales. The assessment of the model performance indicated that the combination of Yasso07 model and remote sensing data could be used for simulating the effect of land use changes on SOC stock at catchment scale in the Loess Plateau." | A wetland restoration monitoring and assessment program framework was developed for Idaho. The project goal was to assess outcomes of substantial governmental and private investment in wetland restoration, enhancement and creation. The functions, values, condition, and vegetation at restored, enhanced, and created wetlands on private and state lands across Idaho were retrospectively evaluated. Assessment was conducted at multiple spatial scales and intensities. Potential functions and values (ecosystem services) were rapidly assessed using the Oregon Rapid Wetland Assessment Protocol. Vegetation samples were analyzed using Floristic Quality Assessment indices from Washington State. We compared vegetation of restored, enhanced, and created wetlands with reference wetlands that occurred in similar hydrogeomorphic environments determined at the HUC 12 level. |
Specific Policy or Decision Context Cited
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None identified | None identified | None | None identified |
Biophysical Context
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No additional description provided | Estuarine environments and marsh-land interfaces | Agricultural plain, hills, gulleys, forest, grassland, Central China | restored, enhanced and created wetlands |
EM Scenario Drivers
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No scenarios presented | Shellfish type; Changes to submerged aquatic vegetation (SAV) | Land use change | Sites, function or habitat focus |
EM ID
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EM-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
Method Only, Application of Method or Model Run
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Method + Application |
Method + Application (multiple runs exist) View EM Runs ?Comment:Ten runs; blue crab and penaeid shrimp, each combined with five different submerged aquatic vegetation habitat areas. |
Method + Application | Method + Application (multiple runs exist) View EM Runs |
New or Pre-existing EM?
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New or revised model | New or revised model | Application of existing model | WESP - Urban Stormwater Treatment |
Related EMs (for example, other versions or derivations of this EM) described in ESML
EM ID
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EM-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
Document ID for related EM
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Doc-231 | Doc-228 | None | Doc-343 | Doc-342 | Doc-390 |
EM ID for related EM
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EM-119 | EM-120 | EM-121 | EM-162 | EM-164 | EM-165 | EM-122 | EM-123 | EM-124 | EM-125 | EM-166 | EM-170 | EM-171 | EM-604 | EM-603 | EM-466 | EM-467 | EM-480 | EM-485 | EM-718 | EM-734 |
EM Modeling Approach
EM ID
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EM-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
EM Temporal Extent
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2000 | 1950 - 2050 | 1969-2011 | 2010-2011 |
EM Time Dependence
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time-stationary | time-dependent | time-dependent | time-dependent |
EM Time Reference (Future/Past)
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Not applicable | future time | past time | past time |
EM Time Continuity
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Not applicable | discrete | discrete | Not applicable |
EM Temporal Grain Size Value
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Not applicable | Varies by Run | 1 | Not applicable |
EM Temporal Grain Size Unit
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Not applicable | Year | Year | Not applicable |
EM ID
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EM-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
Bounding Type
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Geopolitical | Physiographic or ecological | Watershed/Catchment/HUC | Multiple unrelated locations (e.g., meta-analysis) |
Spatial Extent Name
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The EU-25 plus Switzerland and Norway | Gulf of Mexico (estuarine and coastal) | Yangjuangou catchment | Wetlands in idaho |
Spatial Extent Area (Magnitude)
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>1,000,000 km^2 | 10,000-100,000 km^2 | 1-10 km^2 | 100,000-1,000,000 km^2 |
EM ID
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EM-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
EM Spatial Distribution
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spatially distributed (in at least some cases) |
spatially distributed (in at least some cases) ?Comment:Computations at this pixel scale pertain to certain variables specific to Mobile Bay. |
spatially distributed (in at least some cases) | spatially lumped (in all 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 | Not applicable |
Spatial Grain Size
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1 km x 1 km | 55.2 km^2 | 30m x 30m | Not applicable |
EM ID
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EM-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
EM Computational Approach
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Logic- or rule-based | Numeric | Numeric | Numeric |
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-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
Model Calibration Reported?
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No | Yes | Yes | No |
Model Goodness of Fit Reported?
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No | No |
Yes ?Comment:For the year 2006 and 2011 |
No |
Goodness of Fit (metric| value | unit)
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None | None |
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None |
Model Operational Validation Reported?
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Yes | No | No | No |
Model Uncertainty Analysis Reported?
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No | No | No | No |
Model Sensitivity Analysis Reported?
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No | No | No | No |
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-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
None |
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None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
Centroid Latitude
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50.53 | 30.44 | 36.7 | 44.06 |
Centroid Longitude
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7.6 | -87.99 | 109.52 | -114.69 |
Centroid Datum
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WGS84 | WGS84 | WGS84 | WGS84 |
Centroid Coordinates Status
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Estimated | Estimated | Provided | Estimated |
EM ID
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EM-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
EM Environmental Sub-Class
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Terrestrial Environment (sub-classes not fully specified) | Near Coastal Marine and Estuarine | Terrestrial Environment (sub-classes not fully specified) | Agroecosystems | Inland Wetlands |
Specific Environment Type
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Not applicable | Submerged aquatic vegetation in estuaries and coastal lagoons | Loess plain | created, restored and enhanced wetlands |
EM Ecological Scale
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Ecological scale is finer 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 | Ecological scale is finer than that of the Environmental Sub-class |
Scale of differentiation of organisms modeled
EM ID
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EM-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
EM Organismal Scale
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Not applicable | Species | Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
None Available |
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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-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
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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-99 |
EM-397 ![]() |
EM-469 |
EM-729 ![]() |
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None | None |