EcoService Models Library (ESML)
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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.
Compare Criteria:
Show Criteria
Hide CriteriaEM Identity and Description
EM Identification
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EM ID
em.detail.idHelp
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EM-80 | EM-654 |
EM-735 
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EM-774
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EM-843 |
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EM Short Name
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Agronomic ES and plant traits, Central French Alps | Forest recreation, Wisconsin, USA | C sequestration in grassland restoration, England | Plant-pollinator networks at reclaimed mine, USA | Mourning dove abundance, Piedmont region, USA |
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EM Full Name
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Agronomic ecosystem service estimated from plant functional traits, Central French Alps | Forest recreation, Wisconsin, USA | Carbon sequestration in grassland diversity restoration, England | Restoration of plant-pollinator networks at reclaimed strip mine, Ohio, USA | Mourning dove abundance, Piedmont ecoregion, USA |
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EM Source or Collection
em.detail.emSourceOrCollectionHelp
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EU Biodiversity Action 5 | None | None | None | None |
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EM Source Document ID
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260 | 376 | 396 | 397 | 405 |
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Document Author
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Lavorel, S., Grigulis, K., Lamarque, P., Colace, M-P, Garden, D., Girel, J., Pellet, G., and Douzet, R. | Qiu, J. and M. G. Turner | De Deyn, G. B., R. S. Shiel, N. J. Ostle, N. P. McNamara, S. Oakley, I. Young, C. Freeman, N. Fenner, H. Quirk, and R. D. Bardgett | Cusser, S. and K. Goodell | Riffel, S., Scognamillo, D., and L. W. Burger |
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Document Year
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2011 | 2013 | 2011 | 2013 | 2008 |
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Document Title
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Using plant functional traits to understand the landscape distribution of multiple ecosystem services | Spatial interactions among ecosystem services in an urbanizing agricultural watershed | Additional carbon sequestration benefits of grassland diversity restoration | Diversity and distribution of floral resources influence the restoration of plant-pollinator networks on a reclaimed strip mine | Effects of the Conservation Reserve Program on northern bobwhite and grassland birds |
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Document Status
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Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published |
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Comments on Status
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Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript |
Software and Access
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EM ID
em.detail.idHelp
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EM-80 | EM-654 |
EM-735
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EM-774
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EM-843 |
| Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | |
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Contact Name
em.detail.contactNameHelp
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Sandra Lavorel | Monica G. Turner | Gerlinde B. De Deyn |
Sarah Cusser ?Comment:Department of Evolution, Ecology, and Organismal Biology, Ohio State University, 318 West 12th Avenue, Columbus, OH 43202, U.S.A. |
Sam Riffell |
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Contact Address
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Laboratoire d’Ecologie Alpine, UMR 5553 CNRS Université Joseph Fourier, BP 53, 38041 Grenoble Cedex 9, France | Not reported | Dept. of Terrestrial Ecology, Netherlands Institute of Ecology, P O Box 40, 6666 ZG Heteren, The Netherlands | Department of Evolution, Ecology, and Behavior, School of Biological Sciences, The University of Texas at Austin, 100 East 24th Street Stop A6500, Austin, TX 78712-1598, U.S.A. | Department of Wildlife & Fisheries, Mississippi State University, Mississippi State, MS 39762, USA |
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Contact Email
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sandra.lavorel@ujf-grenoble.fr | turnermg@wisc.edu | g.dedeyn@nioo.knaw.nl; gerlindede@gmail.com | sarah.cusser@gmail.com | sriffell@cfr.msstate.edu |
EM Description
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EM ID
em.detail.idHelp
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EM-80 | EM-654 |
EM-735
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EM-774
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EM-843 |
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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." AUTHOR'S DESCRIPTION: "The Agronomic ecosystem service map is a simple sum of maps for relevant Ecosystem Properties (produced in related EMs) after scaling to a 0–100 baseline and trimming outliers to the 5–95% quantiles (Venables&Ripley 2002)…Coefficients used for the summing of individual ecosystem properties to agronomic ecosystem services are based on stakeholders’ perceptions, given positive or negative contributions." | AUTHOR'S DESCRIPTION (from Supporting Information): "Forest recreation service as a function of the amount of forest habitat, recreational opportunities provided, proximity to population center, and accessibility of the area. Several assumptions were made for this assessment approach: larger areas and places with more recreational opportunities would provide more recreational service; areas near large population centers would be visited and used more than remote areas; and proximity to major roads would increase access and thus recreational use of an area… we quantified forest recreation service for each 30-m grid cells using the equation below: FRSi = Ai Σ(Oppti + Popi +Roadi), where FRS is forest recreation score, A is the area of forest habitat, Oppt represents the recreation opportunities, Pop is the proximity to population centers, and Road stands for the distance to major roads. To simplify interpretation, we rescaled the original forest recreation score (ranging from 0 to 5,200) to a range of 0–100, with 0 representing no forest recreation service and 100 representing highest service. | ABSTRACT: "A major aim of European agri-environment policy is the management of grassland for botanical diversity conservation and restoration, together with the delivery of ecosystem services including soil carbon (C) sequestration. To test whether management for biodiversity restoration has additional benefits for soil C sequestration, we investigated C and nitrogen (N) accumulation rates in soil and C and N pools in vegetation in a long-term field experiment (16 years) in which fertilizer application and plant seeding were manipulated. In addition, the abundance of the legume Trifolium pratense was manipulated for the last 2 years. To unravel the mechanisms underlying changes in soil C and N pools, we also tested for effects of diversity restoration management on soil structure, ecosystem respiration and soil enzyme activities…" AUTHOR'S DESCRIPTION: "Measurements were made on 36 plots of 3 x 3 m comprising two management treatments (and their controls) in a long-term multifactorial grassland restoration experiment which have successfully increased plant species diversity, namely the cessation of NPK fertilizer application and the addition of seed mixtures…" | ABSTRACT: "Plant–pollinator mutualisms are one of the several functional relationships that must be reinstated to ensure the long-term success of habitat restoration projects. These mutualisms are unlikely to reinstate themselves until all of the resource requirements of pollinators have been met. By meeting these requirements, projects can improve their long-term success. We hypothesized that pollinator assemblage and structure and stability of plant–pollinator networks depend both on aspects of the surrounding landscape and of the restoration effort itself. We predicted that pollinator species diversity and network stability would be negatively associated with distance from remnant habitat, but that local floral diversity might rescue pollinator diversity and network stability in locations distant from the remnant. We created plots of native prairie on a reclaimed strip mine in central Ohio, U.S.A. that ranged in floral diversity and isolation from the remnant habitat. We found that the pollinator diversity declined with distance from the remnant habitat. Furthermore, reduced pollinator diversity in low floral diversity plots far from the remnant habitat was associated with loss of network stability. High floral diversity, however, compensated for losses in pollinator diversity in plots far from the remnant habitat through the attraction of generalist pollinators. Generalist pollinators increased network connectance and plant-niche overlap. Asa result, network robustness of high floral diversity plots was independent of isolation. We conclude that the aspects of the restoration effort itself, such as floral community composition, can be successfully tailored to incorporate the restoration of pollinators and improve success given a particular landscape context." | ABSTRACT:"The Conservation Reserve Program (CRP) has converted just over 36 million acres of cropland into potential wildlife habitat, primarily grassland. Thus, the CRP should benefit grassland songbirds, a group of species that is declining across the United States and is of conservation concern. Additionally, the CRP is an important part of multi-agency, regional efforts to restore northern bobwhite populations. However, comprehensive assessments of the wildlife benefits of CRP at regional scales are lacking. We used Breeding Bird Survey and National Resources Inventory data to assess the potential for the CRP to benefit northern bobwhite and other grassland birds with overlapping ranges and similar habitat associations. We built regression models for 15 species in seven different ecological regions. Forty-nine of 108 total models contained significant CRP effects (P < 0.05), and 48 of the 49 contained positive effects. Responses to CRP varied across ecological regions. Only eastern meadowlark was positively related to CRP in all the ecological regions, and western meadowlark was the only species never related to CRP. CRP was a strong predictor of bird abundance compared to other land cover types. The potential for CRP habitat as a regional conservation tool to benefit declining grassland bird populations should continue to be assessed at a variety of spatial scales. We caution that bird-CRP relations varied from region to region and among species. Because the NRI provides relatively coarse resolution information on CRP, more detailed information about CRP habitats (spatial arrangement, age of the habitat (time since planting), specific conservation practices used) should be included in future assessments to fully understand where and to what extent CRP can benefit grassland birds. " |
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Specific Policy or Decision Context Cited
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None identified | None identified | None identified | None identified | None reported |
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Biophysical Context
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Elevation ranges from 1552 to 2442 m, on predominantly south-facing slopes | No additional description provided | Lolium perenne-Cynosorus cristatus grassland; The soil is a shallow brown-earth (average depth 28 cm) over limestone of moderate-high residual fertility. | The site was surface mined for coal until the mid-1980s and soon after recontoured and seeded with a low diversity of non-native grasses and forbes. The property is grassland in a state of arrested succession, unable to support tree growth because of shallow, infertile soils. | Conservation Reserve Program lands left to go fallow |
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EM Scenario Drivers
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No scenarios presented | No scenarios presented | Additional benefits due to biodiversity restoration practices | No scenarios presented | N/A |
EM Relationship to Other EMs or Applications
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EM ID
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EM-80 | EM-654 |
EM-735
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EM-774
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EM-843 |
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Method Only, Application of Method or Model Run
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Method + Application | Method + Application | Method + Application (multiple runs exist) View EM Runs | Method + Application (multiple runs exist) View EM Runs | Method + Application |
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New or Pre-existing EM?
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New or revised model | New or revised model | New or revised model | New or revised model | New or revised model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
em.detail.relatedEmHelp
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EM ID
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EM-80 | EM-654 |
EM-735
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EM-774
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EM-843 |
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Document ID for related EM
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Doc-260 | Doc-270 | None | None | None | Doc-405 |
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EM ID for related EM
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EM-65 | EM-66 | EM-68 | EM-69 | EM-70 | EM-71 | EM-79 | EM-81 | EM-82 | EM-83 | None | None | None | EM-831 | EM-838 | EM-839 | EM-840 | EM-841 | EM-842 | EM-844 | EM-845 | EM-846 | EM-847 |
EM Modeling Approach
EM Relationship to Time
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EM ID
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EM-80 | EM-654 |
EM-735
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EM-774
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EM-843 |
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EM Temporal Extent
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Not reported | 2000-2006 | 1990-2007 | 2009-2010 | 2008 |
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EM Time Dependence
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time-stationary | time-stationary | time-stationary | time-stationary | time-stationary |
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EM Time Reference (Future/Past)
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Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
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EM Time Continuity
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Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
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EM Temporal Grain Size Value
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Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
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EM Temporal Grain Size Unit
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Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
EM Spatial Extent
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EM ID
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EM-80 | EM-654 |
EM-735
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EM-774
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EM-843 |
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Bounding Type
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Physiographic or Ecological | Watershed/Catchment/HUC | Other | Physiographic or ecological | Physiographic or ecological |
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Spatial Extent Name
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Central French Alps | Yahara Watershed, Wisconsin | Colt Park meadows, Ingleborough National Nature Reserve, northern England | The Wilds | Piedmont Ecoregion |
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Spatial Extent Area (Magnitude)
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10-100 km^2 | 1000-10,000 km^2. | <1 ha | 1-10 km^2 | 100,000-1,000,000 km^2 |
Spatial Distribution of Computations
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EM ID
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EM-80 | EM-654 |
EM-735
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EM-774
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EM-843 |
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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) | spatially distributed (in at least some cases) | spatially lumped (in all cases) |
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Spatial Grain Type
em.detail.spGrainTypeHelp
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area, for pixel or radial feature | area, for pixel or radial feature | area, for pixel or radial feature | area, for pixel or radial feature | Not applicable |
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Spatial Grain Size
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20 m x 20 m | 30m x 30m | 3 m x 3 m | 10 m radius | Not applicable |
EM Structure and Computation Approach
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EM ID
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EM-80 | EM-654 |
EM-735
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EM-774
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EM-843 |
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EM Computational Approach
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Analytic | Analytic | Analytic | Analytic | Analytic |
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EM Determinism
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deterministic | deterministic | stochastic | deterministic | deterministic |
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Statistical Estimation of EM
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Model Checking Procedures Used
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EM ID
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EM-80 | EM-654 |
EM-735
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EM-774
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EM-843 |
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Model Calibration Reported?
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No | No | Not applicable | Not applicable | Yes |
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Model Goodness of Fit Reported?
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No | No | Not applicable | Not applicable | No |
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Goodness of Fit (metric| value | unit)
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None | None | None | None | None |
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Model Operational Validation Reported?
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No | No | No | Yes | No |
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Model Uncertainty Analysis Reported?
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No | No | No | Yes | No |
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Model Sensitivity Analysis Reported?
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No | No | No | No | Yes |
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Model Sensitivity Analysis Include Interactions?
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Not applicable | Not applicable | Not applicable | Not applicable | Unclear |
EM Locations, Environments, Ecology
Location of EM Application
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
em.detail.relationToSpaceTerrestrialHelp
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| EM-80 | EM-654 |
EM-735
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EM-774
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EM-843 |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
em.detail.relationToSpaceMarineHelp
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| EM-80 | EM-654 |
EM-735
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EM-774
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EM-843 |
| None | None | None | None | None |
Centroid Lat/Long (Decimal Degree)
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EM ID
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EM-80 | EM-654 |
EM-735
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EM-774
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EM-843 |
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Centroid Latitude
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45.05 | 43.1 | 54.2 | 39.82 | 36.23 |
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Centroid Longitude
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6.4 | -89.4 | -2.35 | -81.75 | -81.9 |
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Centroid Datum
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WGS84 | WGS84 | WGS84 | WGS84 | WGS84 |
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Centroid Coordinates Status
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Provided | Provided | Provided | Provided | Estimated |
Environments and Scales Modeled
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EM ID
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EM-80 | EM-654 |
EM-735
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EM-774
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EM-843 |
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EM Environmental Sub-Class
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Agroecosystems | Grasslands | Rivers and Streams | Inland Wetlands | Lakes and Ponds | Forests | Agroecosystems | Created Greenspace | Grasslands | Agroecosystems | Grasslands | Grasslands | Grasslands |
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Specific Environment Type
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Subalpine terraces, grasslands, and meadows. | Mixed environment watershed of prairie converted to predominantly agriculture and urban landscape | fertilized grassland (historically hayed) | Grassland | grasslands |
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EM Ecological Scale
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Ecological scale is coarser than that of the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class |
Scale and taxa of organisms modeled
Scale of differentiation of organisms modeled
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EM ID
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EM-80 | EM-654 |
EM-735
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EM-774
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EM-843 |
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EM Organismal Scale
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Community | Not applicable | Community | Species | Species |
Taxonomic level and name of organisms or groups identified
taxonomyHelp
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| EM-80 | EM-654 |
EM-735
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EM-774
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EM-843 |
| None Available | None Available | None Available |
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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.detail.cicesHelp
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| EM-80 | EM-654 |
EM-735
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EM-774
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EM-843 |
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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>
fegs1Help
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(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
fegs2Help
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| EM-80 | EM-654 |
EM-735
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EM-774
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EM-843 |
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None | None | None |
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