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-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
EM Short Name
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Soil carbon content, Central French Alps | Coral and land development, St.Croix, VI, USA | FORCLIM v2.9, West Cascades, OR, USA | Seed mix for native plant establishment, IA, USA |
EM Full Name
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Soil carbon content, Central French Alps | Coral colony density and land development, St.Croix, Virgin Islands, USA | FORCLIM (FORests in a changing CLIMate) v2.9, West Cascades, OR, USA | Cost-effective seed mix design for native plant establishment, Iowa, USA |
EM Source or Collection
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EU Biodiversity Action 5 | US EPA | US EPA | None |
EM Source Document ID
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260 | 96 |
23 ?Comment:Related document ID 22 is a secondary source providing tree species specific parameters in appendix. |
394 |
Document Author
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Lavorel, S., Grigulis, K., Lamarque, P., Colace, M-P, Garden, D., Girel, J., Pellet, G., and Douzet, R. | Oliver, L. M., Lehrter, J. C. and Fisher, W. S. | Busing, R. T., Solomon, A. M., McKane, R. B. and Burdick, C. A. | Meissen, J. |
Document Year
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2011 | 2011 | 2007 | 2018 |
Document Title
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Using plant functional traits to understand the landscape distribution of multiple ecosystem services | Relating landscape development intensity to coral reef condition in the watersheds of St. Croix, US Virgin Islands | Forest dynamics in Oregon landscapes: evaluation and application of an individual-based model | Cost-effective seed mix design and first-year management |
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-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
Not applicable | Not applicable | Not applicable | Not applicable | |
Contact Name
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Sandra Lavorel | Leah Oliver | Richard T. Busing | Justin Meissen |
Contact Address
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Laboratoire d’Ecologie Alpine, UMR 5553 CNRS Université Joseph Fourier, BP 53, 38041 Grenoble Cedex 9, France | National Health and Environmental Research Effects Laboratory | U.S. Geological Survey, 200 SW 35th Street, Corvallis, Oregon 97333 USA | Tallgrass Prairie Center, University of Northern Iowa |
Contact Email
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sandra.lavorel@ujf-grenoble.fr | leah.oliver@epa.gov | rtbusing@aol.com | Not reported |
EM ID
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EM-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
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. Vegetative height and leaf traits such as leaf dry matter content were response traits strongly influenced by land use and abiotic environment, with follow-on effects on several ecosystem properties, and could therefore be used as functional markers of ES." AUTHOR'S DESCRIPTION: "Variation in soil carbon was modelled using…traits community-weighted mean (CWM) and functional divergence (FD) and abiotic variables (continuous variables; trait + abiotic) following Diaz et al. (2007). …The comparison between this model and the land-use alone model identifies the need for site-based information beyond a land use or land cover proxy…Soil carbon for each pixel was calculated and mapped using model estimates...This step is critically novel as compared to a direct application of the model by Diaz et al. (2007) in that we explicitly modelled the responses of trait community-weighted means and functional divergences to environment prior to evaluating their effects on soil carbon. Such an approach is the key to the explicit representation of functional variation across the landscape, as opposed to the use of unique trait values within each land use." | AUTHOR'S DESCRIPTION: "In this exploratory comparison, stony coral condition was related to watershed LULC and LDI values. We also compared the capacity of other potential human activity indicators to predict coral reef condition using multivariate analysis." (294) | ABSTRACT: "The FORCLIM model of forest dynamics was tested against field survey data for its ability to simulate basal area and composition of old forests across broad climatic gradients in western Oregon, USA. The model was also tested for its ability to capture successional trends in ecoregions of the west Cascade Range…The simulation of both stand-replacing and partial-stand disturbances across western Oregon improved agreement between simulated and actual data." AUTHOR'S DESCRIPTION: "An analysis of forest successional dynamics was performed on ecoregions 4a and 4b, which cover the south Santiam watershed area selected for intensive study. In each of these two ecoregions, a set of 20 simulated sites was compared to survey plot data summaries. Survey data were analysed by stand age class and simulations of corresponding ages. The statistical methods described…were applied in comparison of actual with simulated forest composition and total basal area by age class. Separate simulations were run with and without fire." | AUTHOR'S DESCRIPTION: "Restoring ecosystem services at scale requires executing conservation programs in a way that is resource and cost efficient as well as ecologically effective…Seed mix design is one of the largest determinants of project cost and ecological outcomes for prairie reconstructions. In particular, grass-to-forb seeding ratio affects cost since forb seed can be much more expensive relative to grass species (Prairie Moon Nursery 2012). Even for seed mixes with the same overall seeding rates, a mix with a low grass-to-forb seeding ratio is considerably more expensive than one with a high grass-to-forb ratio. Seeding rates for different plant functional groups that are too high or low may also adversely affect ecological outcomes…First-year management may also play a role in cost-effective prairie reconstruction. Post-agricultural sites where restoration typically occurs are often quickly dominated by fast-growing annual weeds by the time sown prairie seeds begin germinating (Smith et al. 2010)… Williams and others (2007) showed that prairie seedlings sown into established warm-season grasses were reliant on high light conditions created by frequently mowing tall vegetation in order to survive in subsequent years…Our objective was to compare native plant establishment and cost effectiveness with and without first-year mowing for three different seed mixes that differed in grass to forb ratio and soil type customization. With knowledge of plant establishment, cost effectiveness, and mowing management outcomes, conservation practitioners will be better equipped to restore prairie efficiently and successfully." |
Specific Policy or Decision Context Cited
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None identified | Not applicable | None Identified | Seed mix design and management practices for native plant restoration |
Biophysical Context
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Elevation ranges from 1552 to 2442 m, predominantly on south-facing slopes | nearshore; <1.5 km offshore; <12 m depth | West Cascade lowlands (4a), and west Cascade montane (4b) ecoregions | The soils underlying the study site are primarily poorly drained Clyde clay loams, with a minor component of somewhat poorly drained Floyd loams in the northwest (NRCS 2016). Topographically, the study site is level, and slopes do not exceed 5% grade. Land use prior to this experiment was agricultural, with corn and soybeans consistently grown in rotation at the site. |
EM Scenario Drivers
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No scenarios presented | Not applicable | Two scenarios modelled, forests with and without fire | No scenarios presented |
EM ID
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EM-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
Method Only, Application of Method or Model Run
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Method + Application | Method + Application |
Method + Application (multiple runs exist) View EM Runs ?Comment:Related document ID 22 is a secondary source providing tree species specific parameters in appendix. |
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 | New or revised model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
EM ID
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EM-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
Document ID for related EM
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Doc-260 | Doc-269 | None | Doc-22 | Doc-23 | Doc-395 |
EM ID for related EM
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EM-65 | EM-66 | EM-68 | EM-70 | EM-71 | EM-79 | EM-80 | EM-81 | EM-82 | EM-83 | None | EM-146 | EM-208 | EM-186 | EM-728 |
EM Modeling Approach
EM ID
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EM-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
EM Temporal Extent
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2007-2009 | 2006-2007 | >650 yrs | 2015-2017 |
EM Time Dependence
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time-stationary | time-stationary | time-dependent | time-dependent |
EM Time Reference (Future/Past)
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Not applicable | Not applicable | past time | Not applicable |
EM Time Continuity
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Not applicable | Not applicable | discrete | discrete |
EM Temporal Grain Size Value
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Not applicable | Not applicable | 1 | 1 |
EM Temporal Grain Size Unit
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Not applicable | Not applicable | Year | Year |
EM ID
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EM-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
Bounding Type
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Physiographic or Ecological | Physiographic or Ecological | Physiographic or ecological | Other |
Spatial Extent Name
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Central French Alps | St. Croix, U.S. Virgin Islands | West Cascades, Oregon | Iowa State University Northeast Research and Demonstration Farm |
Spatial Extent Area (Magnitude)
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10-100 km^2 | 10-100 km^2 | 100-1000 km^2 | <1 ha |
EM ID
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EM-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
EM Spatial Distribution
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spatially distributed (in at least some cases) | spatially lumped (in all 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 | Not applicable | area, for pixel or radial feature | area, for pixel or radial feature |
Spatial Grain Size
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20 m x 20 m | Not applicable | 0.08 ha | 20 ft x 28 ft |
EM ID
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EM-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
EM Computational Approach
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Analytic | Analytic | Numeric | Analytic |
EM Determinism
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deterministic | deterministic | deterministic | stochastic |
Statistical Estimation of EM
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EM ID
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EM-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
Model Calibration Reported?
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No | Yes | No | Not applicable |
Model Goodness of Fit Reported?
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Yes | Yes | No | Not applicable |
Goodness of Fit (metric| value | unit)
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None | None |
Model Operational Validation Reported?
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Yes | No | Yes | No |
Model Uncertainty Analysis Reported?
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No | Yes | No | Not applicable |
Model Sensitivity Analysis Reported?
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No | No | No | Not applicable |
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-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
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None |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
None |
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None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
Centroid Latitude
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45.05 | 17.75 | 44.24 | 42.93 |
Centroid Longitude
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6.4 | -64.75 | -122.24 | -92.57 |
Centroid Datum
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WGS84 | NAD83 | WGS84 | WGS84 |
Centroid Coordinates Status
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Provided | Estimated | Estimated | Provided |
EM ID
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EM-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
EM Environmental Sub-Class
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Agroecosystems | Grasslands | Near Coastal Marine and Estuarine | Forests | Agroecosystems | Grasslands |
Specific Environment Type
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Subalpine terraces, grasslands, and meadows. | stony coral reef | Primarily conifer forest | Research farm in historic grassland |
EM Ecological Scale
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Not applicable | 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 |
Scale of differentiation of organisms modeled
EM ID
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EM-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
EM Organismal Scale
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Community | Guild or Assemblage | Species | Community |
Taxonomic level and name of organisms or groups identified
EM-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
None Available |
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None Available |
EnviroAtlas URL
EM-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
None Available | None Available | GAP Ecological Systems, Average Annual Precipitation, U.S. EPA (Omernik) ecoregions | GAP Ecological Systems |
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-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
None |
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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-69 | EM-194 |
EM-224 ![]() |
EM-719 ![]() |
None |
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None |
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