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-321 ![]() |
EM-367 |
EM Short Name
em.detail.shortNameHelp
?
|
Erosion prevention by vegetation, Portel, Portugal | InVEST Coastal Blue Carbon |
EM Full Name
em.detail.fullNameHelp
?
|
Soil erosion prevention provided by vegetation cover, Portel municipality, Portugal | InVEST v3.0 Coastal Blue Carbon |
EM Source or Collection
em.detail.emSourceOrCollectionHelp
?
|
EU Biodiversity Action 5 | InVEST |
EM Source Document ID
|
281 | 310 |
Document Author
em.detail.documentAuthorHelp
?
|
Guerra, C.A., Pinto-Correia, T., Metzger, M.J. | Natural Capital Project |
Document Year
em.detail.documentYearHelp
?
|
2014 | 2014 |
Document Title
em.detail.sourceIdHelp
?
|
Mapping soil erosion prevention using an ecosystem service modeling framework for integrated land management and policy | Blue Carbon model - InVEST (v3.0) |
Document Status
em.detail.statusCategoryHelp
?
|
Peer reviewed and published | Documented, not peer reviewed |
Comments on Status
em.detail.commentsOnStatusHelp
?
|
Published journal manuscript | other |
EM ID
em.detail.idHelp
?
|
EM-321 ![]() |
EM-367 |
Not applicable | http://ncp-dev.stanford.edu/~dataportal/invest-releases/documentation/current_release/blue_carbon.html#running-the-model | |
Contact Name
em.detail.contactNameHelp
?
|
Carlos A. Guerra | Gregg Verutes |
Contact Address
|
Instituto de Ciências Agrárias e Ambientais Mediterrânicas, Universidade de Évora, Pólo da Mitra, Apartado 94, 7002-554 Évora, Portugal | Stanford University |
Contact Email
|
cguerra@uevora.pt | gverutes@stanford.edu |
EM ID
em.detail.idHelp
?
|
EM-321 ![]() |
EM-367 |
Summary Description
em.detail.summaryDescriptionHelp
?
|
ABSTRACT: "We present an integrative conceptual framework to estimate the provision of soil erosion prevention (SEP) by combining the structural impact of soil erosion and the social–ecological processes that allow for its mitigation. The framework was tested and illustrated in the Portel municipality in Southern Portugal, a Mediterranean silvo-pastoral system that is prone to desertification and soil degradation. The results show a clear difference in the spatial and temporal distribution of the capacity for ecosystem service provision and the actual ecosystem service provision." AUTHOR'S DESCRIPTION: "To begin assessing the contribution of SEP we need to identify the structural impact of soil erosion, that is, the erosion that would occur when vegetation is absent and therefore no ES is provided. It determines the potential soil erosion in a given place and time and is related to rainfall erosivity (that is, the erosive potential of rainfall), soil erodibility (as a characteristic of the soil type) and local topography. Although external drivers can have an effect on these variables (for example, climate change), they are less prone to be changed directly by human action. The actual ES provision reduces the total amount of structural impact, and we define the remaining impact as the ES mitigated impact. We can then define the capacity for ES provision as a key component to determine the fraction of the structural impact that is mitigated…Following the conceptual outline, we will estimate the SEP provided by vegetation cover using an adaptation of the Universal Soil Loss Equation (USLE)." | Please note: This ESML entry describes an InVEST model version that was current as of 2014. More recent versions may be available at the InVEST website. "InVEST Coastal Blue Carbon models the carbon cycle through a bookkeeping-type approach (Houghton, 2003). This approach simplifies the carbon cycle by accounting for storage in four main pools (aboveground biomass, belowground biomass, standing dead carbon and sediment carbon… Accumulation of carbon in coastal habitats occurs primarily in sediments (Pendleton et al., 2012). The model requires users to provide maps of coastal ecosystems that store carbon, such as mangroves and seagrasses. Users must also provide data on the amount of carbon stored in the four carbon pools and the rate of annual carbon accumulation in the sediments. If local information is not available, users can draw on the global database of values for carbon stocks and accumulation rates sourced from the peer-reviewed literature that is included in the model. If data from field studies or other local sources are available, these values should be used instead of those in the global database. The model requires land cover maps, which represent changes in human use patterns in coastal areas or changes to sea level, to estimate the amount of carbon lost or gained over a specified period of time. The model quantifies carbon storage across the land or seascape by summing the carbon stored in these four carbon pools. |
Specific Policy or Decision Context Cited
em.detail.policyDecisionContextHelp
?
|
None identified | None identified |
Biophysical Context
|
Open savannah-like forest of cork (Quercus suber) and holm (Quercus ilex) oaks, with trees of different ages randomly dispersed in changing densities, and pastures in the under cover. The pastures are mostly natural in a mosaic with patches of shrubs, which differ in size and the distribution depends mainly on the grazing intensity. Shallow, poor soils are prone to erosion, especially in areas with high grazing pressure. | Land use land class; habitat type |
EM Scenario Drivers
em.detail.scenarioDriverHelp
?
|
Different land management practices as represented by the comparison of different grazing intensities (i.e., livestock densities) in the whole study area and in three Civil Parishes within the study area | Land use land cover changes; habitat disturbance |
EM ID
em.detail.idHelp
?
|
EM-321 ![]() |
EM-367 |
Method Only, Application of Method or Model Run
em.detail.methodOrAppHelp
?
|
Method + Application (multiple runs exist) View EM Runs | Method Only |
New or Pre-existing EM?
em.detail.newOrExistHelp
?
|
New or revised model | New or revised model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
EM ID
em.detail.idHelp
?
|
EM-321 ![]() |
EM-367 |
Document ID for related EM
em.detail.relatedEmDocumentIdHelp
?
|
Doc-282 | Doc-283 | Doc-284 | Doc-285 | None |
EM ID for related EM
em.detail.relatedEmEmIdHelp
?
|
None | None |
EM Modeling Approach
EM ID
em.detail.idHelp
?
|
EM-321 ![]() |
EM-367 |
EM Temporal Extent
em.detail.tempExtentHelp
?
|
January to December 2003 | Not applicable |
EM Time Dependence
em.detail.timeDependencyHelp
?
|
time-dependent | time-dependent |
EM Time Reference (Future/Past)
em.detail.futurePastHelp
?
|
future time | Not applicable |
EM Time Continuity
em.detail.continueDiscreteHelp
?
|
discrete | discrete |
EM Temporal Grain Size Value
em.detail.tempGrainSizeHelp
?
|
1 | 1 |
EM Temporal Grain Size Unit
em.detail.tempGrainSizeUnitHelp
?
|
Month | Year |
EM ID
em.detail.idHelp
?
|
EM-321 ![]() |
EM-367 |
Bounding Type
em.detail.boundingTypeHelp
?
|
Geopolitical | Not applicable |
Spatial Extent Name
em.detail.extentNameHelp
?
|
Portel municipality | Not applicable |
Spatial Extent Area (Magnitude)
em.detail.extentAreaHelp
?
|
100-1000 km^2 | Not applicable |
EM ID
em.detail.idHelp
?
|
EM-321 ![]() |
EM-367 |
EM Spatial Distribution
em.detail.distributeLumpHelp
?
|
spatially distributed (in at least some cases) | spatially distributed (in at least some cases) |
Spatial Grain Type
em.detail.spGrainTypeHelp
?
|
area, for pixel or radial feature | volume, for 3-D feature |
Spatial Grain Size
em.detail.spGrainSizeHelp
?
|
250 m x 250 m | user-specified |
EM ID
em.detail.idHelp
?
|
EM-321 ![]() |
EM-367 |
EM Computational Approach
em.detail.emComputationalApproachHelp
?
|
Analytic | Analytic |
EM Determinism
em.detail.deterStochHelp
?
|
deterministic | deterministic |
Statistical Estimation of EM
em.detail.statisticalEstimationHelp
?
|
|
|
EM ID
em.detail.idHelp
?
|
EM-321 ![]() |
EM-367 |
Model Calibration Reported?
em.detail.calibrationHelp
?
|
No | Not applicable |
Model Goodness of Fit Reported?
em.detail.goodnessFitHelp
?
|
No | Not applicable |
Goodness of Fit (metric| value | unit)
em.detail.goodnessFitValuesHelp
?
|
None | None |
Model Operational Validation Reported?
em.detail.validationHelp
?
|
No | Not applicable |
Model Uncertainty Analysis Reported?
em.detail.uncertaintyAnalysisHelp
?
|
No | Not applicable |
Model Sensitivity Analysis Reported?
em.detail.sensAnalysisHelp
?
|
No | Not applicable |
Model Sensitivity Analysis Include Interactions?
em.detail.interactionConsiderHelp
?
|
Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-321 ![]() |
EM-367 |
|
None |
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-321 ![]() |
EM-367 |
None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
em.detail.idHelp
?
|
EM-321 ![]() |
EM-367 |
Centroid Latitude
em.detail.ddLatHelp
?
|
38.3 | -9999 |
Centroid Longitude
em.detail.ddLongHelp
?
|
-7.7 | -9999 |
Centroid Datum
em.detail.datumHelp
?
|
WGS84 | Not applicable |
Centroid Coordinates Status
em.detail.coordinateStatusHelp
?
|
Estimated | Not applicable |
EM ID
em.detail.idHelp
?
|
EM-321 ![]() |
EM-367 |
EM Environmental Sub-Class
em.detail.emEnvironmentalSubclassHelp
?
|
Terrestrial Environment (sub-classes not fully specified) | Forests | Agroecosystems | Scrubland/Shrubland | Inland Wetlands | Near Coastal Marine and Estuarine |
Specific Environment Type
em.detail.specificEnvTypeHelp
?
|
Silvo-pastoral system | user specified |
EM Ecological Scale
em.detail.ecoScaleHelp
?
|
Ecological scale is coarser 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
em.detail.idHelp
?
|
EM-321 ![]() |
EM-367 |
EM Organismal Scale
em.detail.orgScaleHelp
?
|
Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-321 ![]() |
EM-367 |
None Available | None Available |
EnviroAtlas URL
EM-321 ![]() |
EM-367 |
Average Annual Precipitation | Carbon Storage by Tree Biomass |
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-321 ![]() |
EM-367 |
|
|
<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-321 ![]() |
EM-367 |
|
None |