EcoService Models Library (ESML)
loading
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
em.detail.idHelp
?
|
EM-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
EM Short Name
em.detail.shortNameHelp
?
|
Wetland shellfish production, Gulf of Mexico, USA | Yasso07 - SOC, Loess Plateau, China | WESP Method | WESP: Urban Stormwater Treatment, ID, USA | Neighborhood greenness and health, FL, USA |
EM Full Name
em.detail.fullNameHelp
?
|
Wetland shellfish production, Gulf of Mexico, USA | Yasso07 - Land Use Effects on Soil Organic Carbon Stocks in the Loess Plateau, China | Method for the Wetland Ecosystem Services Protocol (WESP) | WESP: Urban Stormwater Treament, ID, USA | Neighborhood greenness and chronic health conditions in Medicare beneficiaries, Miami-Dade County, Florida, USA |
EM Source or Collection
em.detail.emSourceOrCollectionHelp
?
|
US EPA ?Comment:Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science |
None | None | None | None |
EM Source Document ID
|
324 | 344 | 390 |
393 ?Comment:Additional data came from electronic appendix provided by author Chris Murphy. |
417 |
Document Author
em.detail.documentAuthorHelp
?
|
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 | Adamus, P. R. | Murphy, C. and T. Weekley | Brown, S. C., J. Lombard, K. Wang, M. M. Byrne, M. Toro, E. Plater-Zyberk, D. J. Feaster, J. Kardys, M. I. Nardi, G. Perez-Gomez, H. M. Pantin, and J. Szapocznik |
Document Year
em.detail.documentYearHelp
?
|
2012 | 2015 | 2016 | 2012 | 2016 |
Document Title
em.detail.sourceIdHelp
?
|
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 | Manual for the Wetland Ecosystem Services Protocol (WESP) v. 1.3. | Measuring outcomes of wetland restoration, enhancement, and creation in Idaho-- Assessing potential functions, values, and condition in a watershed context. | Neighborhood greenness and chronic health conditions in Medicare beneficiaries |
Document Status
em.detail.statusCategoryHelp
?
|
Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published |
Comments on Status
em.detail.commentsOnStatusHelp
?
|
Published journal manuscript | Published journal manuscript | Published report | Published report | Published journal manuscript |
EM ID
em.detail.idHelp
?
|
EM-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
Not applicable | http://en.ilmatieteenlaitos.fi/yasso-download-and-support |
http://people.oregonstate.edu/~adamusp/WESP/ ?Comment:This is an Excel spreadsheet calculator |
Not applicable | Not applicable | |
Contact Name
em.detail.contactNameHelp
?
|
Stephen J. Jordan | Xing Wu | Paul R. Adamus | Chris Murphy | Scott C. Brown |
Contact Address
|
U.S. Environmental Protection Agency, Gulf Ecology Division, 1 Sabine Island Drive, Gulf Breeze, FL 32561, USA | Chinese Academy of Sciences, Beijing 100085, China | 6028 NW Burgundy Dr. Corvallis, OR 97330 | Idaho Dept. Fish and Game, Wildlife Bureau, Habitat Section, Boise, ID | Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14th Street, Clinical Research Building (CRB), Room 1065, Miami FL 33136 |
Contact Email
|
jordan.steve@epa.gov | xingwu@rceesac.cn | adamus7@comcast.net | chris.murphy@idfg.idaho.gov | sbrown@med.miami.edu |
EM ID
em.detail.idHelp
?
|
EM-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
Summary Description
em.detail.summaryDescriptionHelp
?
|
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." | Author Description: " The Wetland Ecosystem Services Protocol (WESP) is a standardized template for creating regionalized methods which then can be used to rapid assess ecosystem services (functions and values) of all wetland types throughout a focal region. To date, regionalized versions of WESP have been developed (or are ongoing) for government agencies or NGOs in Oregon, Alaska, Alberta, New Brunswick, and Nova Scotia. WESP also may be used directly in its current condition to assess these services at the scale of an individual wetland, but without providing a regional context for interpreting that information. Nonetheless, WESP takes into account many landscape factors, especially as they relate to the potential or actual benefits of a wetland’s functions. A WESP assessment requires completing a single three-part data form, taking about 1-3 hours. Responses to questions on that form are based on review of aerial imagery and observations during a single site visit; GIS is not required. After data are entered in an Excel spreadsheet, the spreadsheet uses science-based logic models to automatically generate scores intended to reflect a wetland’s ability to support the following functions: Water Storage and Delay, Stream Flow Support, Water Cooling, Sediment Retention and Stabilization, Phosphorus Retention, Nitrate Removal and Retention, Carbon Sequestration, Organic Nutrient Export, Aquatic Invertebrate Habitat, Anadromous Fish Habitat, Non-anadromous Fish Habitat, Amphibian & Reptile Habitat, Waterbird Feeding Habitat, Waterbird Nesting Habitat, Songbird, Raptor and Mammal Habitat, Pollinator Habitat, and Native Plant Habitat. For all but two of these functions, scores are given for both components of an ecosystem service: function and benefit. In addition, wetland Ecological Condition (Integrity), Public Use and Recognition, Wetland Sensitivity, and Stressors are scored. Scores generated by WESP may be used to (a) estimate a wetland’s relative ecological condition, stress, and sensitivity, (b) compare relative levels of ecosystem services among different wetland types, or (c) compare those in a single wetland before and after restoration, enhancement, or loss."] | 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. | ABSTRACT: "Introduction: Prior studies suggest that exposure to the natural environment may impact health. The present study examines the association between objective measures of block-level greenness (vegetative presence) and chronic medical conditions, including cardiometabolic conditions, in a large population-based sample of Medicare beneficiaries in Miami-Dade County, Florida. Methods: The sample included 249,405 Medicare beneficiaries aged >=65 years whose location (ZIP+4) within Miami-Dade County, Florida, did not change, from 2010 to 2011. Data were obtained in 2013 and multilevel analyses conducted in 2014 to examine relationships between greenness, measured by mean Normalized Difference Vegetation Index from satellite imagery at the Census block level, and chronic health conditions in 2011, adjusting for neighborhood median household income, individual age, gender, race, and ethnicity. Results: Higher greenness was significantly associated with better health, adjusting for covariates: An increase in mean block-level Normalized Difference Vegetation Index from 1 SD less to 1 SD more than the mean was associated with 49 fewer chronic conditions per 1,000 individuals, which is approximately similar to a reduction in age of the overall study population by 3 years. This same level of increase in mean Normalized Difference Vegetation Index was associated with a reduced risk of diabetes by 14%, hypertension by 13%, and hyperlipidemia by 10%. Planned post-hoc analyses revealed stronger and more consistently positive relationships between greenness and health in lower- than higher-income neighborhoods. Conclusions: Greenness or vegetative presence may be effective in promoting health in older populations, particularly in poor neighborhoods, possibly due to increased time outdoors, physical activity, or stress mitigation." |
Specific Policy or Decision Context Cited
em.detail.policyDecisionContextHelp
?
|
None identified | None | None identified | None identified | None identified |
Biophysical Context
|
Estuarine environments and marsh-land interfaces | Agricultural plain, hills, gulleys, forest, grassland, Central China | None | restored, enhanced and created wetlands | No additional description provided |
EM Scenario Drivers
em.detail.scenarioDriverHelp
?
|
Shellfish type; Changes to submerged aquatic vegetation (SAV) | Land use change | N/A | Sites, function or habitat focus | No scenarios presented |
EM ID
em.detail.idHelp
?
|
EM-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
Method Only, Application of Method or Model Run
em.detail.methodOrAppHelp
?
|
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 Only | Method + Application (multiple runs exist) View EM Runs | Method + Application |
New or Pre-existing EM?
em.detail.newOrExistHelp
?
|
New or revised model | Application of existing model | New or revised model | WESP - Urban Stormwater Treatment | New or revised model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
EM ID
em.detail.idHelp
?
|
EM-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
Document ID for related EM
em.detail.relatedEmDocumentIdHelp
?
|
None | Doc-343 | Doc-342 | None | Doc-390 | None |
EM ID for related EM
em.detail.relatedEmEmIdHelp
?
|
EM-604 | EM-603 | EM-466 | EM-467 | EM-480 | EM-485 | EM-718 | EM-718 | EM-734 | None |
EM Modeling Approach
EM ID
em.detail.idHelp
?
|
EM-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
EM Temporal Extent
em.detail.tempExtentHelp
?
|
1950 - 2050 | 1969-2011 | Not applicable | 2010-2011 | 2010-2011 |
EM Time Dependence
em.detail.timeDependencyHelp
?
|
time-dependent | time-dependent | time-stationary | time-dependent | time-stationary |
EM Time Reference (Future/Past)
em.detail.futurePastHelp
?
|
future time | past time | Not applicable | past time | Not applicable |
EM Time Continuity
em.detail.continueDiscreteHelp
?
|
discrete | discrete | Not applicable | Not applicable | Not applicable |
EM Temporal Grain Size Value
em.detail.tempGrainSizeHelp
?
|
Varies by Run | 1 | Not applicable | Not applicable | Not applicable |
EM Temporal Grain Size Unit
em.detail.tempGrainSizeUnitHelp
?
|
Year | Year | Not applicable | Not applicable | Not applicable |
EM ID
em.detail.idHelp
?
|
EM-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
Bounding Type
em.detail.boundingTypeHelp
?
|
Physiographic or ecological | Watershed/Catchment/HUC | Not applicable | Multiple unrelated locations (e.g., meta-analysis) | Geopolitical |
Spatial Extent Name
em.detail.extentNameHelp
?
|
Gulf of Mexico (estuarine and coastal) | Yangjuangou catchment | Not applicable | Wetlands in idaho | Miami-Dade County |
Spatial Extent Area (Magnitude)
em.detail.extentAreaHelp
?
|
10,000-100,000 km^2 | 1-10 km^2 | Not applicable | 100,000-1,000,000 km^2 | 1000-10,000 km^2. |
EM ID
em.detail.idHelp
?
|
EM-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
EM Spatial Distribution
em.detail.distributeLumpHelp
?
|
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 distributed (in at least some cases) | spatially lumped (in all cases) | spatially distributed (in at least some cases) |
Spatial Grain Type
em.detail.spGrainTypeHelp
?
|
area, for pixel or radial feature | area, for pixel or radial feature | area, for pixel or radial feature | Not applicable | other (specify), for irregular (e.g., stream reach, lake basin) |
Spatial Grain Size
em.detail.spGrainSizeHelp
?
|
55.2 km^2 | 30m x 30m | not reported | Not applicable | Census block |
EM ID
em.detail.idHelp
?
|
EM-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
EM Computational Approach
em.detail.emComputationalApproachHelp
?
|
Numeric | Numeric | Analytic | Numeric | Analytic |
EM Determinism
em.detail.deterStochHelp
?
|
deterministic | deterministic | deterministic | deterministic | deterministic |
Statistical Estimation of EM
em.detail.statisticalEstimationHelp
?
|
|
|
|
|
|
EM ID
em.detail.idHelp
?
|
EM-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
Model Calibration Reported?
em.detail.calibrationHelp
?
|
Yes | Yes | Not applicable | No | Not applicable |
Model Goodness of Fit Reported?
em.detail.goodnessFitHelp
?
|
No |
Yes ?Comment:For the year 2006 and 2011 |
Not applicable | No | No |
Goodness of Fit (metric| value | unit)
em.detail.goodnessFitValuesHelp
?
|
None |
|
None | None | None |
Model Operational Validation Reported?
em.detail.validationHelp
?
|
No | No | No | No | No |
Model Uncertainty Analysis Reported?
em.detail.uncertaintyAnalysisHelp
?
|
No | No | Not applicable | No | No |
Model Sensitivity Analysis Reported?
em.detail.sensAnalysisHelp
?
|
No | No | Not applicable | No | No |
Model Sensitivity Analysis Include Interactions?
em.detail.interactionConsiderHelp
?
|
Not applicable | 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-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
|
|
None |
|
|
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
|
None | None | None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
em.detail.idHelp
?
|
EM-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
Centroid Latitude
em.detail.ddLatHelp
?
|
30.44 | 36.7 | Not applicable | 44.06 | 25.64 |
Centroid Longitude
em.detail.ddLongHelp
?
|
-87.99 | 109.52 | Not applicable | -114.69 | -80.5 |
Centroid Datum
em.detail.datumHelp
?
|
WGS84 | WGS84 | Not applicable | WGS84 | WGS84 |
Centroid Coordinates Status
em.detail.coordinateStatusHelp
?
|
Estimated | Provided | Not applicable | Estimated | Estimated |
EM ID
em.detail.idHelp
?
|
EM-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
EM Environmental Sub-Class
em.detail.emEnvironmentalSubclassHelp
?
|
Near Coastal Marine and Estuarine | Terrestrial Environment (sub-classes not fully specified) | Agroecosystems | Inland Wetlands | Inland Wetlands | Created Greenspace |
Specific Environment Type
em.detail.specificEnvTypeHelp
?
|
Submerged aquatic vegetation in estuaries and coastal lagoons | Loess plain | Wetlands | created, restored and enhanced wetlands | urban neighborhood greenspace |
EM Ecological Scale
em.detail.ecoScaleHelp
?
|
Ecological scale is finer than that of the Environmental Sub-class | Ecological scale is finer than that of the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class | Ecological scale is finer than that of the Environmental Sub-class | Ecological scale is coarser than that of the Environmental Sub-class |
Scale of differentiation of organisms modeled
EM ID
em.detail.idHelp
?
|
EM-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
EM Organismal Scale
em.detail.orgScaleHelp
?
|
Species | Not applicable | Not applicable | Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
|
None Available | 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-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
|
|
|
|
|
<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-397 ![]() |
EM-469 | EM-706 |
EM-729 ![]() |
EM-876 |
|
None |
|
None |
|