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
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                    EM ID
                
                
             
           
     
                            
                                
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                        ? | EM-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
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                    EM Short Name
                
             
           
     
                            
                            
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                        ? | Evoland v3.5 (bounded growth), Eugene, OR, USA | EnviroAtlas-Nat. filtration-water | EnviroAtlas - Natural biological nitrogen fixation | Pollination ES, Central French Alps | Fish species habitat value, Tampa Bay, FL, USA | Birds in estuary habitats, Yaquina Estuary, WA, USA | InVEST water yield, Hood Canal, WA, USA | i-Tree Hydro v4.0 | Mangrove development, Tampa Bay, FL, USA | FORCLIM v2.9, Santiam watershed, OR, USA | ARIES carbon, Puget Sound Region, USA | InVEST crop pollination, California, USA | InVEST (v1.004) sediment retention, Indonesia | InVESTv3.0 Nutrient retention, Guánica Bay | Yasso07 v1.0.1, Switzerland | Floral resources on landfill sites, United Kingdom | WESP Method | C sequestration in grassland restoration, England | 
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                    EM Full Name
                
                
             
           
     
                            
                                
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                        ? | Evoland v3.5 (with urban growth boundaries), Eugene, OR, USA | US EPA EnviroAtlas - Natural filtration (of water by tree cover); Example is shown for Durham NC and vicinity, USA | US EPA EnviroAtlas - BNF (Natural biological nitrogen fixation), USA | Pollination ecosystem service estimated from plant functional traits, Central French Alps | Fish species habitat value, Tampa Bay, FL, USA | Bird use of estuarine habitats, Yaquina Estuary, WA, USA | InVEST (Integrated Valuation of Envl. Services and Tradeoffs) water yield, Hood Canal, WA, USA | i-Tree Hydro v4.0 (default data option) | Mangrove wetland development, Tampa Bay, FL, USA | FORCLIM (FORests in a changing CLIMate) v2.9, Santiam watershed, OR, USA | ARIES (Artificial Intelligence for Ecosystem Services) Carbon Storage and Sequestration, Puget Sound Region, Washington, USA | InVEST crop pollination, California, USA | InVEST (Integrated Valuation of Environmental Services and Tradeoffs v1.004) sediment retention, Sumatra, Indonesia | InVEST (Integrated Valuation of Environmental Services and Tradeoffs)v3.0 Nutrient retention, Guánica Bay, Puerto Rico, USA | Yasso07 v1.0.1 forest litter decomposition, Switzerland | Floral resources on landfill sites, East Midlands, United Kingdom | Method for the Wetland Ecosystem Services Protocol (WESP) | Carbon sequestration in grassland diversity restoration, England | 
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                    EM Source or Collection
                
             
           
     
                            
                            
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                        ? | Envision | US EPA | EnviroAtlas | i-Tree ? Comment:EnviroAtlas uses an application of the i-Tree Hydro model. | US EPA | EnviroAtlas | EU Biodiversity Action 5 | US EPA | US EPA | InVEST | i-Tree | USDA Forest Service | US EPA | US EPA | ARIES | InVEST | InVEST | US EPA | InVEST | None | None | None | None | 
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                    EM Source Document ID
                
             
           
     | 47 ? Comment:Doc 183 is a secondary source for the Evoland model. | 223 | 262 ? Comment:EnviroAtlas maps BNF based on a correlation with AET modeled by Cleveland et al. 1999, and modified by land use (% natural vs. ag/developed) within each HUC. AET was modeled using climate and land use parameters (equation from Sanford and Selnick 2013). For full citations of these related models, see below, "Document ID for related EM. | 260 | 187 | 275 | 205 | 198 | 97 | 23 ? Comment:Related document ID 22 is a secondary source providing tree species specific parameters in appendix. | 302 | 279 | 309 | 338 | 343 | 389 | 390 | 396 | 
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                    Document Author
                
                
             
           
     
                            
                                
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                        ? | Guzy, M. R., Smith, C. L. , Bolte, J. P., Hulse, D. W. and Gregory, S. V. | US EPA Office of Research and Development - National Exposure Research Laboratory | US EPA Office of Research and Development - National Exposure Research Laboratory | Lavorel, S., Grigulis, K., Lamarque, P., Colace, M-P, Garden, D., Girel, J., Pellet, G., and Douzet, R. | Fulford, R., Yoskowitz, D., Russell, M., Dantin, D., and Rogers, J. | Frazier, M. R., Lamberson, J. O. and Nelson, W. G. | Toft, J. E., Burke, J. L., Carey, M. P., Kim, C. K., Marsik, M., Sutherland, D. A., Arkema, K. K., Guerry, A. D., Levin, P. S., Minello, T. J., Plummer, M., Ruckelshaus, M. H., and Townsend, H. M. | USDA Forest Service | Osland, M. J., Spivak, A. C., Nestlerode, J. A., Lessmann, J. M., Almario, A. E., Heitmuller, P. T., Russell, M. J., Krauss, K. W., Alvarez, F., Dantin, D. D., Harvey, J. E., From, A. S., Cormier, N. and Stagg, C.L. | Busing, R. T., Solomon, A. M., McKane, R. B. and Burdick, C. A. | Bagstad, K.J., Villa, F., Batker, D., Harrison-Cox, J., Voigt, B., and Johnson, G.W. | Lonsdorf, E., Kremen, C., Ricketts, T., Winfree, R., Williams, N., and S. Greenleaf | Bhagabati, N. K., Ricketts, T., Sulistyawan, T. B. S., Conte, M., Ennaanay, D., Hadian, O., McKenzie, E., Olwero, N., Rosenthal, A., Tallis, H., and Wolney, S. | Amelia Smith, Susan Harrell Yee, Marc Russell, Jill Awkerman and William S. Fisher | Didion, M., B. Frey, N. Rogiers, and E. Thurig | Tarrant S., J. Ollerton, M. L Rahman, J. Tarrant, and D. McCollin | Adamus, P. R. | 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 | 
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                    Document Year
                
                
             
           
     
                            
                                
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                        ? | 2008 | 2013 | 2013 | 2011 | 2016 | 2014 | 2013 | Not Reported | 2012 | 2007 | 2014 | 2009 | 2014 | 2017 | 2014 | 2013 | 2016 | 2011 | 
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                    Document Title
                
             
           
     
                            
                            
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                        ? | Policy research using agent-based modeling to assess future impacts of urban expansion into farmlands and forests | EnviroAtlas - Featured Community | EnviroAtlas - National | Using plant functional traits to understand the landscape distribution of multiple ecosystem services | Habitat and recreational fishing opportunity in Tampa Bay: Linking ecological and ecosystem services to human beneficiaries | Intertidal habitat utilization patterns of birds in a Northeast Pacific estuary | From mountains to sound: modelling the sensitivity of dungeness crab and Pacific oyster to land–sea interactions in Hood Canal,WA | i-Tree Hydro User's Manual v. 4.0 | Ecosystem development after mangrove wetland creation: plant–soil change across a 20-year chronosequence | Forest dynamics in Oregon landscapes: evaluation and application of an individual-based model | From theoretical to actual ecosystem services: mapping beneficiaries and spatial flows in ecosystem service assessments | Modelling pollination services across agricultural landscapes | Ecosystem services reinforce Sumatran tiger conservation in land use plans | Linking ecosystem services supply to stakeholder concerns on both land and sea: An example from Guanica Bay watershed, Puerto Rico | Validating tree litter decomposition in the Yasso07 carbon model | Grassland restoration on landfill sites in the East Midlands, United Kingdom: An evaluation of floral resources and pollinating insects | Manual for the Wetland Ecosystem Services Protocol (WESP) v. 1.3. | Additional carbon sequestration benefits of grassland diversity restoration | 
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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 | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | 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 on US EPA EnviroAtlas website | Published on US EPA EnviroAtlas website | Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript | Webpage | Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript | Published report | Published journal manuscript | 
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                    EM ID
                
             
           
     
                            
                            
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                        ? | EM-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
| http://evoland.bioe.orst.edu/ ? Comment:Software is likely available. | https://www.epa.gov/enviroatlas | https://www.epa.gov/enviroatlas | Not applicable | Not applicable | Not applicable | https://www.naturalcapitalproject.org/invest/ | http://www.itreetools.org | Not applicable | Not applicable | http://aries.integratedmodelling.org/ | http://www.naturalcapitalproject.org/models/crop_pollination.html | https://www.naturalcapitalproject.org/invest/ | http://www.naturalcapitalproject.org/invest/ | http://en.ilmatieteenlaitos.fi/yasso-download-and-support | Not applicable | http://people.oregonstate.edu/~adamusp/WESP/ ? Comment:This is an Excel spreadsheet calculator | Not applicable | |
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                    Contact Name
                
                
             
           
     
                            
                                
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                        ? | Michael R. Guzy | EnviroAtlas Team | EnviroAtlas Team ? Comment:Additional contact: Jana Compton, EPA | Sandra Lavorel | Richard Fulford | M. R. Frazier ? Comment:Present address: M. R. Frazier National Center for Ecological Analysis and Synthesis, 735 State St. Suite 300, Santa Barbara, CA 93101, USA | J.E. Toft | Not applicable | Michael Osland | Richard T. Busing | Ken Bagstad | Eric Lonsdorf | Nirmal K. Bhagabati | Susan H. Yee | Markus Didion ? Comment:Tel.: +41 44 7392 427 | Sam Tarrant | Paul R. Adamus | Gerlinde B. De Deyn | 
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                    Contact Address
                
             
           
     | Oregon State University, Dept. of Biological and Ecological Engineering | Not reported | Not reported | Laboratoire d’Ecologie Alpine, UMR 5553 CNRS Université Joseph Fourier, BP 53, 38041 Grenoble Cedex 9, France | USEPA Gulf Ecology Division, Gulf Breeze, FL 32561 | Western Ecology Division, Office of Research and Development, U.S. Environmental Protection Agency, Pacific coastal Ecology Branch, 2111 SE marine Science Drive, Newport, OR 97365 | The Natural Capital Project, Stanford University, 371 Serra Mall, Stanford, CA 94305-5020, USA | Not applicable | U.S. Environmental Protection Agency, Gulf Ecology Division, gulf Breeze, FL 32561 | U.S. Geological Survey, 200 SW 35th Street, Corvallis, Oregon 97333 USA | Geosciences and Environmental Change Science Center, US Geological Survey | Conservation and Science Dept, Linclon Park Zoo, 2001 N. Clark St, Chicago, IL 60614, USA | The Nature Conservancy, 1107 Laurel Avenue, Felton, CA 95018 | U.S. Environmental Protection Agency, Gulf Ecology Division, Gulf Breeze, FL 32561, USA | Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903 Birmensdorf, Switzerland | RSPB UK Headquarters, The Lodge, Sandy, Bedfordshire SG19 2DL, U.K. | 6028 NW Burgundy Dr. Corvallis, OR 97330 | Dept. of Terrestrial Ecology, Netherlands Institute of Ecology, P O Box 40, 6666 ZG Heteren, The Netherlands | 
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                    Contact Email
                
             
           
     | Not reported | enviroatlas@epa.gov | enviroatlas@epa.gov | sandra.lavorel@ujf-grenoble.fr | Fulford.Richard@epa.gov | frazier@nceas.ucsb.edu | jetoft@stanford.edu | Not applicable | mosland@usgs.gov | rtbusing@aol.com | kjbagstad@usgs.gov | ericlonsdorf@lpzoo.org | nirmal.bhagabati@wwfus.org | yee.susan@epa.gov | markus.didion@wsl.ch | sam.tarrant@rspb.org.uk | adamus7@comcast.net | g.dedeyn@nioo.knaw.nl; gerlindede@gmail.com | 
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                    EM ID
                
             
           
     
                            
                            
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                        ? | EM-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
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                    Summary Description
                
                
             
           
     
                            
                                
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                        ? | **Note: A more recent version of this model exists. See Related EMs below for links to related models/applications.** ABSTRACT: "Spatially explicit agent-based models can represent the changes in resilience and ecological services that result from different land-use policies…This type of analysis generates ensembles of alternate plausible representations of future system conditions. User expertise steers interactive, stepwise system exploration toward inductive reasoning about potential changes to the system. In this study, we develop understanding of the potential alternative futures for a social-ecological system by way of successive simulations that test variations in the types and numbers of policies. The model addresses the agricultural-urban interface and the preservation of ecosystem services. The landscape analyzed is at the junction of the McKenzie and Willamette Rivers adjacent to the cities of Eugene and Springfield in Lane County, Oregon." AUTHOR'S DESCRIPTION: "Two general scenarios for urban expansion were created to set the bounds on what might be possible for the McKenzie-Willamette study area. One scenario, fish conservation, tried to accommodate urban expansion, but gave the most weight to policies that would produce resilience and ecosystem services to restore threatened fish populations. The other scenario, unconstrained development, reversed the weighting. The 35 policies in the fish conservation scenario are designed to maintain urban growth boundaries (UGB), accommodate human population growth through increased urban densities, promote land conservation through best-conservation practices on agricultural and forest lands, and make rural land-use conversions that benefit fish. In the unconstrained development scenario, 13 policies are mainly concerned with allowing urban expansion in locations desired by landowners. Urban expansion in this scenario was not constrained by the extent of the UGB, and the policies are not intended to create conservation land uses." | The Natural Filtration model has been used to create coverages for several US communities. An example for Durham, NC is shown in this entry. METADATA ABSTRACT: "This EnviroAtlas dataset presents environmental benefits of the urban forest in 193 block groups in Durham, North Carolina... runoff effects are calculated for each block group using i-Tree models (www.itreetools.org), local weather data, pollution data, EPA provided city boundary and land cover data, and U.S. Census derived block group boundary data. This dataset was produced by the US Forest Service to support research and online mapping activities related to EnviroAtlas." METADATA DESCRIPTION: "The i-Tree Hydro model estimates the effects of tree and impervious cover on hourly stream flow values for a watershed (Wang et al 2008). i-Tree Hydro also estimates changes in water quality using hourly runoff estimates and mean and median national event mean concentration (EMC) values. The model was calibrated using hourly stream flow data to yield the best fit between model and measured stream flow results… After calibration, the model was run a number of times under various conditions to see how the stream flow would respond given varying tree and impervious cover in the watershed… The term event mean concentration (EMC) is a statistical parameter used to represent the flow-proportional average concentration of a given parameter during a storm event. EMC data is used for estimating pollutant loading into watersheds. The response outputs were calculated as kg of pollutant per square meter of land area for pollutants. These per square meter values were multiplied by the square meters of land area in the block group to estimate the effects at the block group level." METADATA DESCRIPTION PARAPHRASED: Changes in water quality were estimated for the following pollutants (entered as separate runs); total suspended solids (TSS), total phosphorus, soluble phosphorus, nitrites and nitrates, total Kjeldahl nitrogen (TKN), biochemical oxygen demand (BOD5), chemical oxygen demand (COD5), and copper. "Reduction in annual runoff (census block group)" variable data was derived from the EnviroAtlas water recharge coverage which used the i-Tree Hydro model. | DATA FACT SHEET: "This EnviroAtlas national map displays the rate of biological nitrogen (N) fixation (BNF) in natural/semi-natural ecosystems within each watershed (12-digit HUC) in the conterminous United States (excluding Hawaii and Alaska) for the year 2006. These data are based on the modeled relationship of BNF with actual evapotranspiration (AET) in natural/semi-natural ecosystems. The mean rate of BNF is for the 12-digit HUC, not to natural/semi-natural lands within the HUC." "BNF in natural/semi-natural ecosystems was estimated using a correlation with actual evapotranspiration (AET). This correlation is based on a global meta-analysis of BNF in natural/semi-natural ecosystems. AET estimates for 2006 were calculated using a regression equation describing the correlation of AET with climate and land use/land cover variables in the conterminous US. Data describing annual average minimum and maximum daily temperatures and total precipitation at the 2.5 arcmin (~4 km) scale for 2006 were acquired from the PRISM climate dataset. The National Land Cover Database (NLCD) for 2006 was acquired from the USGS at the scale of 30 x 30 m. BNF in natural/semi-natural ecosystems within individual 12-digit HUCs was modeled with an equation describing the statistical relationship between BNF (kg N ha-1 yr-1) and actual evapotranspiration (AET; cm yr–1) and scaled to the proportion of non-developed and non-agricultural land in the 12-digit HUC." EnviroAtlas maps BNF based on a correlation with AET modeled by Cleveland et al. 1999, and modified by land use (% natural vs. ag/developed) within each HUC. AET was modeled using climate and land use parameters (equation from Sanford and Selnick 2013). For full citations of these related models, see below, "Document ID for related EM." | 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 pollination ecosystem service map was a simple sums 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 pollination ecosystem services are based on stakeholders’ perceptions, given positive (+1) or negative (-1) contributions." | ABSTRACT: "Estimating value of estuarine habitat to human beneficiaries requires that we understand how habitat alteration impacts function through both production and delivery of ecosystem goods and services (EGS). Here we expand on the habitat valuation technique of Bell (1997) with an estimate of recreational angler willingness-to-pay combined with estimates of angler effort, fish population size, and fish and angler distribution. Results suggest species-specific fishery value is impacted by angler interest and stock status, as the most targeted fish (spotted seatrout) did not have the highest specific value (fish−1). Reduced population size and higher size at capture resulted in higher specific value for common snook. Habitat value estimated from recreational fishing value and fish-angler distributions supported an association between seagrass and habitat value, yet this relationship was also impacted by distance to access points. This analysis does not provide complete valuation of habitat as it considers only one service (fishing), but demonstrates a methodology to consider functional equivalency of all habitat features as a part of a habitat mosaic rather than in isolation, as well as how to consider both EGS production and delivery to humans (e.g., anglers) in any habitat valuation, which are critical for a transition to ecosystem management." | AUTHOR'S DESCRIPTION: "To describe bird utilization patterns of intertidal habitats within Yaquina estuary, Oregon, we conducted censuses to obtain bird species and abundance data for the five dominant estuarine intertidal habitats: Zostera marina (eelgrass), Upogebia (mud shrimp)/ mudflat, Neotrypaea (ghost shrimp)/sandflat, Zostera japonica (Japanese eelgrass), and low marsh. EPFs were developed for the following metrics of bird use: standardized species richness; Shannon diversity; and density for the following four groups: all birds, all birds excluding gulls, waterfowl (ducks and geese), and shorebirds." | InVEST Water Yield and Scarcity Model Please note: This ESML entry describes a specific, published application of an InVEST model. Different versions (e.g. different tiers) or more recent versions of this model may be available at the InVEST website. AUTHOR'S DESCRIPTION: "We modelled discharge and total nitrogen for the 153 perennial sub- watersheds in Hood Canal based on spatial variation in hydrological factors, land and water use, and vegetation.To do this, we reparame-terized a set of fresh water models available in the InVEST tool (Tallis and Polasky, 2009; Kareiva et al., 2011)… We modelled discharge using the InVESTWater Yield and Scarcity model. The model estimates discharge for user-defined subwatersheds based on the average annual precipitation, annual reference evapotranspiration, and a correction factor for vegetation type, soil depth, plant available water content, land use and land cover, root depth, elevation, saturated hydraulic conductivity, and consumptive water use" (2) | ABSTRACT: "i-Tree Hydro is the first urban hydrology model that is specifically designed to model vegetation effects and to be calibrated against measured stream flow data. It is designed to model the effects of changes in urban tree cover and impervious surfaces on hourly stream flows and water quality at the watershed level." AUTHOR'S DESCRIPTION: "The purpose of i-Tree Hydro is to simulate hourly changes in stream flow (and water quality) given changes in tree and impervious cover in the watershed. The following is an overview of the process: 1) Determine your watershed of analysis and stream gauge station. i-Tree Hydro works on a watershed basis with the watershed determined as the total drainage area upstream from a measured stream gauge. Stream gauge availability varies. 2) Download national digital elevation data. Once the area and location of the watershed are known, digital elevation data are downloaded from the USGS for an area that encompasses the entire watershed. ArcGIS software is then used to create a digital elevation map and to determine the exact boundary for the watershed upstream from the gauge station location. 3) Determine cover attributes of the watershed and gather other required data. i-Tree Canopy and other sources can be used to determine the tree cover, shrub cover, impervious surface and other cover types. Information about other aspects of the watershed such as proportion of evergreen trees and shrubs, leaf area index, and a variety of hydrologic parameters must be collected. 4) Get started with Hydro. Once these input data are ready, they are loaded into Hydro to begin analysis. 5) Calibrate the model. The Hydro model contains an auto-calibration routine that tries to find the best fit between the stream flow predicted by the model and the stream flow measured at the stream gauge station given the various inputs. The model can also be manually calibrated to improve the fit by changing the parameters as needed. 6) Model new scenarios: Once the model is properly calibrated, tree and impervious cover parameters can be changed to illustrate the impact on stream flow and water quality." | ABSTRACT: "Mangrove wetland restoration and creation effortsare increasingly proposed as mechanisms to compensate for mangrove wetland losses. However, ecosystem development and functional equivalence in restored and created mangrove wetlands are poorly understood. We compared a 20-year chronosequence of created tidal wetland sites in Tampa Bay, Florida (USA) to natural reference mangrove wetlands. Across the chronosequence, our sites represent the succession from salt marsh to mangrove forest communities. Our results identify important soil and plant structural differences between the created and natural reference wetland sites; however, they also depict a positive developmental trajectory for the created wetland sites that reflects tightly coupled plant-soil development. Because upland soils and/or dredge spoils were used to create the new mangrove habitats, the soils at younger created sites and at lower depths (10–30 cm) had higher bulk densities, higher sand content, lower soil organic matter (SOM), lower total carbon (TC), and lower total nitrogen (TN) than did natural reference wetland soils. However, in the upper soil layer (0–10 cm), SOM, TC, and TN increased with created wetland site age simultaneously with mangrove forest growth. The rate of created wetland soil C accumulation was comparable to literature values for natural mangrove wetlands. Notably, the time to equivalence for the upper soil layer of created mangrove wetlands appears to be faster than for many other wetland ecosystem types. Collectively, our findings characterize the rate and trajectory of above- and below-ground changes associated with ecosystem development in created mangrove wetlands; this is valuable information for environmental managers planning to sustain existing mangrove wetlands or mitigate for mangrove wetland losses." | 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. It was then applied to simulate present and future (1990-2050) forest landscape dynamics of a watershed in the west Cascades. Various regimes of climate change and harvesting in the watershed were considered in the landscape application." AUTHOR'S DESCRIPTION: "Effects of different management histories on the landscape were incorporated using the land management (conservation, plan, or development trend) and forest age categories…the plan trend was an intermediate alternative, representing the continuation of current policies and trends, whereas the conservation and development trends were possible alternatives…Non-forested areas were given a forest age of zero; forested areas were assigned to one of eight forest age classes: >0-20 yr, 21-40 yr, 41-60 yr, 61-80 yr, 81-200 yr, 201-400 yr, and >600 yr in 1990…two climate change scenarios were used, representing lower and upper extremes projected by a set of global climate models: (1) minor warming with drier summers, and (2) major warming with wetter conditions…For the first scenario, temperature was increased by 0.5°C in 2025 and by 1.5°C in 2045. Precipitation from October to March was increased 2% in 2025 and decreased 2% in 2045. Precipitation from April to September was decreased 4% in 2025 and 7% in 2045. For the second scenario, temperature was by increased 2.6°C in 2025 and by 3.2°C in 2045. Precipitation from October to March was increased 18% in 2025 and 22% in 2045. Precipitation from April to September was increased 14% in 2025 and 9% in 2045. | ABSTRACT: "...new modeling approaches that map and quantify service-specific sources (ecosystem capacity to provide a service), sinks (biophysical or anthropogenic features that deplete or alter service flows), users (user locations and level of demand), and spatial flows can provide a more complete understanding of ecosystem services. Through a case study in Puget Sound, Washington State, USA, we quantify and differentiate between the theoretical or in situ provision of services, i.e., ecosystems’ capacity to supply services, and their actual provision when accounting for the location of beneficiaries and the spatial connections that mediate service flows between people and ecosystems... Using the ARtificial Intelligence for Ecosystem Services (ARIES) methodology we map service supply, demand, and flow, extending on simpler approaches used by past studies to map service provision and use." AUTHOR'S NOTE: "We quantified carbon sequestration and storage in vegetation and soils using Bayesian models (Bagstad et al. 2011) calibrated with Moderate-resolution Imaging Spectroradiometer Net Primary Productivity (MODIS GPP/NPP Project, http://secure.ntsg.umt. edu/projects/index.php/ID/ca2901a0/fuseaction/prohttp://www.whrc.org/ational Bwww.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/?cid=nrcs142p2_053627)vey Geographic Dahttp://www.geomac.gov/index.shtml)wps/portal/nrcs/detail/soils/survey/?cid=nrcs142p2_053627) soils data, respectively. By overlaying fire boundary polygons from the Geospatial Multi-Agency Coordination Group (GeoMAC, http://www.geomac.gov/index.shtml) we estimated carbon storage losses caused by wildfire, using fuel consumption coefficients from Spracklen et al. (2009) and carbon pool data from Smith et al. (2006). By incorporating the impacts of land-cover change from urbanization (Bolte and Vache 2010) within carbon models, we quantified resultant changes in carbon storage." | Please note: This ESML entry describes a specific, published application of an InVEST model. Different versions (e.g. different tiers) or more recent versions of this model may be available at the InVEST website. ABSTRACT: "Background and Aims: Crop pollination by bees and other animals is an essential ecosystem service. Ensuring the maintenance of the service requires a full understanding of the contributions of landscape elements to pollinator populations and crop pollination. Here, the first quantitative model that predicts pollinator abundance on a landscape is described and tested. Methods: Using information on pollinator nesting resources, floral resources and foraging distances, the model predicts the relative abundance of pollinators within nesting habitats. From these nesting areas, it then predicts relative abundances of pollinators on the farms requiring pollination services. Model outputs are compared with data from coffee in Costa Rica, watermelon and sunflower in California and watermelon in New Jersey–Pennsylvania (NJPA). Key Results: Results from Costa Rica and California, comparing field estimates of pollinator abundance, richness or services with model estimates, are encouraging, explaining up to 80 % of variance among farms. However, the model did not predict observed pollinator abundances on NJPA, so continued model improvement and testing are necessary. The inability of the model to predict pollinator abundances in the NJPA landscape may be due to not accounting for fine-scale floral and nesting resources within the landscapes surrounding farms, rather than the logic of our model. Conclusions: The importance of fine-scale resources for pollinator service delivery was supported by sensitivity analyses indicating that the model's predictions depend largely on estimates of nesting and floral resources within crops. Despite the need for more research at the finer-scale, the approach fills an important gap by providing quantitative and mechanistic model from which to evaluate policy decisions and develop land-use plans that promote pollination conservation and service delivery. " | Please note: This ESML entry describes a specific, published application of an InVEST model. Different versions (e.g. different tiers) or more recent versions of this model may be available at the InVEST website. ABSTRACT: "...Here we use simple spatial analyses on readily available datasets to compare the distribution of five ecosystem services with tiger habitat in central Sumatra. We assessed services and habitat in 2008 and the changes in these variables under two future scenarios: a conservation-friendly Green Vision, and a Spatial Plan developed by the Indonesian government..." AUTHOR'S DESCRIPTION: "We used a modeling tool, InVEST (Integrated Valuation of Environmental Services and Tradeoffs version 1.004; Tallis et al., 2010), to map and quantify tiger habitat quality and five ecosystem services. InVEST maps ecosystem services and the quality of species habitat as production functions of LULC using simple biophysical models. Models were parameterized using data from regional agencies, literature surveys, global databases, site visits and prior field experience (Table 1)... The sediment retention model is based on the Universal Soil Loss Equation (USLE) (Wischmeier and Smith, 1978). It estimates erosion as ton y^-1 of sediment load, based on the energetic ability of rainfall to move soil, the erodibility of a given soil type, slope, erosion protection provided by vegetated LULC, and land management practices. The model routes sediment originating on each land parcel along its flow path, with vegetated parcels retaining a fraction of sediment with varying efficiencies, and exporting the remainder downstream. ...Although InVEST reports ecosystem services in biophysical units, its simple models are best suited to understanding broad patterns of spatial variation (Tallis and Polasky, 2011), rather than for precise quantification. Additionally, we lacked field measurements against which to calibrate our outputs. Therefore, we focused on relative spatial distribution across the landscape, and relative change to scenarios." | Please note: This ESML entry describes a specific, published application of an InVEST model. Different versions (e.g. different tiers) or more recent versions of this model may be available at the InVEST website. AUTHOR'S DESCRIPTION: "Nutrient retention was estimated by first calculating water yield and establishing the quantity of nitrogen or phosphorus retained by different land cover classes using a water purification model (InVEST 3.0.0; Tallis et al., 2013). Different land cover classes were assumed to have different capacities for retaining nutrients, depending on the efficiency of vegetation in removing either nitrogen or phosphorus and the rates of nitrogen or phosphorus loading." “Use of other models in conjunction with this model:Average runoff per pixel modeled here were derived from the InVEST Water Yield model" | ABSTRACT: "...We examined the validity of the litter decomposition and soil carbon model Yasso07 in Swiss forests based on data on observed decomposition of (i) foliage and fine root litter from sites along a climatic and altitudinal gradient and (ii) of 588 dead trees from 394 plots of the Swiss National Forest Inventory. Our objectives were to (i) examine the effect of the application of three different published Yasso07 parameter sets on simulated decay rate; (ii) analyze the accuracy of Yasso07 for reproducing observed decomposition of litter and dead wood in Swiss forests;…" AUTHOR'S DESCRIPTION: "Yasso07 (Tuomi et al., 2011a, 2009) is a litter decomposition model to calculate C stocks and stock changes in mineral soil, litter and deadwood. For estimating stocks of organic C in these pools and their temporal dynamics, Yasso07 (Y07) requires information on C inputs from dead organic matter (e.g., foliage and woody material) and climate (temperature, temperature amplitude and precipitation). DOM decomposition is modelled based on the chemical composition of the C input, size of woody parts and climate (Tuomi et al., 2011 a, b, 2009). In Y07 it is assumed that DOM consists of four compound groups with specific mass loss rates. The mass flows between compounds that are either insoluble (N), soluble in ethanol (E), in water (W) or in acid (A) and to a more stable humus compartment (H), as well as the flux out of the five pools (Fig. 1, Table A.1; Liski et al., 2009) are described by a range of parameters (Tuomi et al., 2011a, 2009)." "For this study, we used the Yasso07 release 1.0.1 (cf. project homepage). The Yasso07 Fortran source code was compiled for the Windows7 operating system. The statistical software R (R Core Team, 2013) version 3.0.1 (64 bit) was used for administrating theYasso07 simulations. The decomposition of DOM was simulated with Y07 using the parameter sets P09, P11 and P12 with the purpose of identifying a parameter set that is applicable to conditions in Switzerland. In the simulations we used the value of the maximum a posteriori point estimate (cf. Tuomi et al., 2009) derived from the distribution of parameter values for each set (Table A.1). The simulations were initialized with the C mass contained in (a) one litterbag at the start of the litterbag experiment for foliage and fine root litter (Heim and Frey, 2004) and (b) individual deadwood pieces at the time of the NFI2 for deadwood. The respective mass of C was separated into the four compound groups used by Y07. The simulations were run for the time span of the observed data. The result of the simulation was an annual estimate of the remaining fraction of the initial mass, which could then be compared with observed data." | ABSTRACT: "...Restored landfill sites are a significant potential reserve of semi-natural habitat, so their conservation value for supporting populations of pollinating insects was here examined by assessing whether the plant and pollinator assemblages of restored landfill sites are comparable to reference sites of existing wildlife value. Floral characteristics of the vegetation and the species richness and abundance of flower-visiting insect assemblages were compared between nine pairs of restored landfill sites and reference sites in the East Midlands of the United Kingdom, using standardized methods over two field seasons. …" AUTHOR'S DESCRIPTION: "The selection criteria for the landfill sites were greater than or equal to 50% of the site restored (to avoid undue influence from ongoing landfilling operations), greater than or equal to 0.5 ha in area and restored for greater than or equal to 4 years to allow establishment of vegetation. Comparison reference sites were the closest grassland sites of recognized nature conservation value, being designated as either Local Nature Reserves (LNRs) or Sites of Special Scientific Interest (SSSI)…All sites were surveyed three times each during the fieldwork season, in Spring, Summer, and Autumn. Paired sites were sampled on consecutive days whenever weather conditions permitted to reduce temporal bias. Standardized plant surveys were used (Dicks et al. 2002; Potts et al. 2006). Transects (100 × 2m) were centered from the approximate middle of the site and orientated using randomized bearing tables. All flowering plants were identified to species level… A “floral cover” method to represent available floral resources was used which combines floral abundance with inflorescence size. Mean area of the floral unit from above was measured for each flowering plant species and then multiplied by their frequencies." "Insect pollinated flowering plant species composition and floral abundance between sites by type were represented by non-metric multidimensional scaling (NMDS)...This method is sensitive to showing outliers and the distance between points shows the relative similarity (McCune & Grace 2002; Ollerton et al. 2009)." (This data is not entered into ESML) | 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."] | 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…" | 
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                    Specific Policy or Decision Context Cited
                
                
             
           
     
                            
                                
                                    em.detail.policyDecisionContextHelp
                                
                                
                            
                            
                        ? | Authors Description: " By policy, we mean land management options that span the domains of zoning, agricultural and forest production, environmental protection, and urban development, including the associated regulations, laws, and practices. The policies we used in our SES simulations include urban containment policies…We also used policies modeled on agricultural practices that affect ecoystem services and capital…" | None identified | None Identified | None identified | None identifed | None identified | Land use change | None identified | Not applicable | None identified | None identified | None identified | This analysis provided input to government-led spatial planning and strategic environmental assessments in the study area. This region contains some of the last remaining forest habitat of the critically endangered Sumatran tiger, Panthera tigris sumatrae. | Improving water quality | None identified | None identified | None identified | None identified | 
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                    Biophysical Context
                
                
             
           
     | No additional description provided | No additional description provided | No additional description provided | Elevations ranging from 1552 m to 2442 m, on predominantly south-facing slopes | shallow bay (mean 3.7m), transition zone between warm temperate and tropical biogeographic provinces. Highly urbanized watershed | Estuarine intertidal, eelgrass, mudflat, sandflat and low marsh | Not additional description provided | No additional description provided | mangrove forest,Salt marsh, estuary, sea level, | No additional description provided | No additional description provided | No additional description provided | Six watersheds in central Sumatra covering portions of Riau, Jambi and West Sumatra provinces. The Barisan mountain range comprises the western edge of the watersheds, while peat swamps predominate in the east. | No additional description provided | Different forest types dominated by Norway Spruce (Picea abies), European Beech (Fagus sylvatica) and Sweet Chestnut (Castanea sativa). | No additional description provided | None | Lolium perenne-Cynosorus cristatus grassland; The soil is a shallow brown-earth (average depth 28 cm) over limestone of moderate-high residual fertility. | 
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                    EM Scenario Drivers
                
                
             
           
     
                            
                                
                                    em.detail.scenarioDriverHelp
                                
                                
                            
                            
                        ? | Five scenarios that include urban growth boundaries and various combinations of unconstrainted development, fish conservation, agriculture and forest reserves. ? Comment:Additional alternatives included adding agricultural and forest reserves, and adding or removing urban growth boundaries to the three main scenarios. | No scenarios presented | No scenarios presented | No scenarios presented | No scenarios presented | No scenarios presented | Future land use and land cover; climate change | No scenarios presented | Not applicable | Land Management (3); Climate Change (3) | No scenarios presented | No scenarios presented | Baseline year 2008, future LULC Sumatra 2020 Roadmap (Vision), future LULC Government Spatial Plan | No scenarios presented | No scenarios presented ? Comment:Yasso model simulations were run using 3 different parameter sets from: 1) Tuomi et al., 2009 (P09), 2) Tuomi et al., 2011 (P11), and 3) Rantakari et al., 2012 (P12). | No scenarios presented | N/A | Additional benefits due to biodiversity restoration practices | 
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
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                    Method Only, Application of Method or Model Run
                
                
             
           
     
                            
                                
                                    em.detail.methodOrAppHelp
                                
                                
                            
                            
                        ? | Method + Application (multiple runs exist) View EM Runs | Method + Application (multiple runs exist) View EM Runs | Method + Application | Method + Application | Method + Application (multiple runs exist) View EM Runs | Method + Application | Method + Application (multiple runs exist) View EM Runs | Method Only | Method + Application | Method + Application (multiple runs exist)  	     View EM Runs ? Comment:Runs differentiated by scenario combination. | Method + Application | Method + Application (multiple runs exist) View EM Runs | Method + Application (multiple runs exist) View EM Runs | Method + Application | Method + Application (multiple runs exist)  	     View EM Runs ? Comment:Yasso model simulations were run using 3 different parameter sets from: 1) Tuomi et al., 2009 (P09), 2) Tuomi et al., 2011 (P11), and 3) Rantakari et al., 2012 (P12). | Method + Application (multiple runs exist) View EM Runs | Method Only | Method + Application (multiple runs exist) View EM Runs | 
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                    New or Pre-existing EM?
                
                
             
           
     
                            
                                
                                    em.detail.newOrExistHelp
                                
                                
                            
                            
                        ? | New or revised model | Application of existing model | New or revised model | New or revised model | New or revised model | New or revised model | Application of existing model | New or revised model | New or revised model | Application of existing model | New or revised model | New or revised model | Application of existing model | Application of existing model | Application of existing 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
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                    EM ID
                
                
             
           
     
                            
                                
                                    em.detail.idHelp
                                
                                
                            
                            
                        ? | EM-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
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                    Document ID for related EM
                
                
             
           
     
                            
                                
                                    em.detail.relatedEmDocumentIdHelp
                                
                                
                            
                            
                        ? | Doc-47 | Doc-313 | Doc-314 ? Comment:Doc 183 is a secondary source for the Evoland model. | Doc-198 | Doc-346 | Doc-347 ? Comment:EnviroAtlas maps BNF based on a correlation with AET modeled by Cleveland et al. 1999, and modified by land use (% natural vs. ag/developed) within each HUC. AET was modeled using climate and land use parameters (equation from Sanford and Selnick 2013). For full citations of these related models, see below, "Document ID for related EM. | Doc-260 | None | None | Doc-280 | Doc-307 | Doc-311 | Doc-338 | Doc-190 | Doc-223 | None | Doc-22 | Doc-23 ? Comment:Related document ID 22 is a secondary source providing tree species specific parameters in appendix. | Doc-303 | Doc-305 | Doc-279 | Doc-338 | Doc-309 | Doc-205 | Doc-342 | Doc-344 | None | None | None | 
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                    EM ID for related EM
                
                
             
           
     
                            
                                
                                    em.detail.relatedEmEmIdHelp
                                
                                
                            
                            
                        ? | EM-333 | EM-369 | EM-137 | EM-142 | None | EM-65 | EM-66 | EM-68 | EM-69 | EM-70 | EM-71 | EM-79 | EM-80 | EM-81 | EM-83 | None | None | EM-148 | EM-344 | EM-368 | EM-437 | EM-109 | EM-142 | EM-51 | None | EM-146 | EM-186 | EM-224 | None | EM-340 | EM-339 | EM-435 | EM-363 | EM-112 | EM-466 | EM-469 | EM-480 | EM-485 | EM-709 | EM-718 | None | 
EM Modeling Approach
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
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                    EM Temporal Extent
                
                
             
           
     
                            
                                
                                    em.detail.tempExtentHelp
                                
                                
                            
                            
                        ? | 1990-2050 | 1999-2010 | 2006-2010 | Not reported | 2006-2011 | December 2007 - November 2008 | 2005-7; 2035-45 | Not applicable | 1990-2010 | 1990-2050 | 1950-2007 | 2001-2002 | 2008-2020 | 1980 - 2013 | 1993-2013 | 2007-2008 | Not applicable | 1990-2007 | 
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                    EM Time Dependence
                
                
             
           
     
                            
                                
                                    em.detail.timeDependencyHelp
                                
                                
                            
                            
                        ? | time-dependent | time-stationary ? Comment:The underlying i-Tree Hydro model, used to generate the annual flows for which EMCs were ultimately applied, operated on an hourly timestep. The final annual flow parameter however is time stationary. | time-stationary | time-stationary | time-stationary | time-stationary | time-stationary | time-dependent | time-dependent | time-dependent | time-stationary | time-stationary | time-stationary | time-dependent | time-dependent | time-stationary | time-stationary | time-stationary | 
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                    EM Time Reference (Future/Past)
                
                
             
           
     
                            
                                
                                    em.detail.futurePastHelp
                                
                                
                            
                            
                        ? | future time | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | future time | future time | Not applicable | Not applicable | Not applicable | other or unclear (comment) | future time | Not applicable | Not applicable | Not applicable | 
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                    EM Time Continuity
                
                
             
           
     
                            
                                
                                    em.detail.continueDiscreteHelp
                                
                                
                            
                            
                        ? | discrete | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | discrete | continuous | discrete | Not applicable | Not applicable | Not applicable | discrete | discrete | Not applicable | Not applicable | Not applicable | 
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                    EM Temporal Grain Size Value
                
                
             
           
     
                            
                                
                                    em.detail.tempGrainSizeHelp
                                
                                
                            
                            
                        ? | 2 | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | 1 | Not applicable | 1 | Not applicable | Not applicable | Not applicable | 1 | 1 | Not applicable | Not applicable | Not applicable | 
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                    EM Temporal Grain Size Unit
                
                
             
           
     
                            
                                
                                    em.detail.tempGrainSizeUnitHelp
                                
                                
                            
                            
                        ? | Year | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Hour | Not applicable | Year | Not applicable | Not applicable | Not applicable | Year | Year | Not applicable | Not applicable | Not applicable | 
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
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                    Bounding Type
                
             
           
     
                            
                            
                                em.detail.boundingTypeHelp
                            
                        ? | Geopolitical | Geopolitical | Geopolitical | Physiographic or Ecological | Physiographic or Ecological | Physiographic or ecological | Watershed/Catchment/HUC | Not applicable | Physiographic or Ecological | Watershed/Catchment/HUC | Physiographic or ecological | Other | Watershed/Catchment/HUC | Watershed/Catchment/HUC | Geopolitical | Multiple unrelated locations (e.g., meta-analysis) | Not applicable | Other | 
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                    Spatial Extent Name
                
             
           
     
                            
                            
                                em.detail.extentNameHelp
                            
                        ? | Junction of McKenzie and Willamette Rivers, adjacent to the cities of Eugene and Springfield, Lane Co., Oregon, USA | Durham, NC and vicinity | counterminous United States | Central French Alps | Tampa Bay | Yaquina Estuary (intertidal), Oregon, USA | Hood Canal | Not applicable | Tampa Bay | South Santiam watershed | Puget Sound Region | Agricultural landscape, Yolo County, Central Valley | central Sumatra | Guanica Bay Study Area | Switzerland | East Midlands | Not applicable | Colt Park meadows, Ingleborough National Nature Reserve, northern England | 
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                    Spatial Extent Area (Magnitude)
                
             
           
     
                            
                            
                                em.detail.extentAreaHelp
                            
                        ? | 10-100 km^2 | 100-1000 km^2 | >1,000,000 km^2 | 10-100 km^2 | 1000-10,000 km^2. | 1-10 km^2 | 100,000-1,000,000 km^2 | Not applicable | 100-1000 km^2 | 100-1000 km^2 | 10,000-100,000 km^2 | 1000-10,000 km^2. | 100,000-1,000,000 km^2 | 1000-10,000 km^2. | 10,000-100,000 km^2 | 1000-10,000 km^2. | Not applicable | <1 ha | 
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
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                    EM Spatial Distribution
                
                
             
           
     
                            
                                
                                    em.detail.distributeLumpHelp
                                
                                
                            
                            
                        ? | spatially distributed (in at least some cases) ? Comment:Spatial grain for computations is comprised of 16,005 polygons of various size covering 7091 ha. | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) ? Comment:Watersheds (12-digit HUCs). | 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 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 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 distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | 
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                    Spatial Grain Type
                
             
           
     
                            
                            
                                em.detail.spGrainTypeHelp
                            
                        ? | area, for pixel or radial feature | other (specify), for irregular (e.g., stream reach, lake basin) | other (specify), for irregular (e.g., stream reach, lake basin) | area, for pixel or radial feature | area, for pixel or radial feature | other (habitat type) | area, for pixel or radial feature | area, for pixel or radial feature | area, for pixel or radial feature | area, for pixel or radial feature | area, for pixel or radial feature | area, for pixel or radial feature | area, for pixel or radial feature | area, for pixel or radial feature | other (specify), for irregular (e.g., stream reach, lake basin) | other (specify), for irregular (e.g., stream reach, lake basin) | area, for pixel or radial feature | area, for pixel or radial feature | 
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                    Spatial Grain Size
                
             
           
     
                            
                            
                                em.detail.spGrainSizeHelp
                            
                        ? | varies | irregular | irregular | 20 m x 20 m | 1 km^2 | 0.87-104.29 ha | 30 m x 30 m | 30 x 30 m | m^2 | 0.08 ha | 200m x 200m | 30 m x 30 m | 30 m x 30 m | 30 m x 30 m | 5 sites | multiple unrelated locations | not reported | 3 m x 3 m | 
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
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                    EM Computational Approach
                
                
             
           
     
                            
                                
                                    em.detail.emComputationalApproachHelp
                                
                                
                            
                            
                        ? | Numeric | Analytic ? Comment:The underlying i-Tree Hydro model, used to generate the annual flows for which EMCs were ultimately applied, was numeric. The final parameter however did not require iteration. | Analytic | Analytic | Analytic | Analytic | Analytic | Numeric | Analytic | Numeric | Analytic | Analytic | Analytic | Numeric | Numeric | Analytic | Analytic | Analytic | 
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                    EM Determinism
                
                
             
           
     
                            
                                
                                    em.detail.deterStochHelp
                                
                                
                            
                            
                        ? | stochastic | deterministic | deterministic | deterministic | deterministic | deterministic | deterministic | deterministic | deterministic | deterministic | stochastic | deterministic | deterministic | deterministic | stochastic | deterministic | deterministic | stochastic | 
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                    Statistical Estimation of EM
                
             
           
     
                            
                            
                                em.detail.statisticalEstimationHelp
                            
                        ? | 
 Comment:Agent based modeling results in response indices. | 
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
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                    Model Calibration Reported?
                
             
           
     
                            
                            
                                em.detail.calibrationHelp
                            
                        ? | Unclear | Unclear | No | No | No | Unclear | Yes | Not applicable | No | No | Yes | Unclear | No | No | No | Not applicable | Not applicable | Not applicable | 
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                    Model Goodness of Fit Reported?
                
                
             
           
     
                            
                                
                                    em.detail.goodnessFitHelp
                                
                                
                            
                            
                        ? | No | No | No | No | No | No | No | Not applicable | No | No | No | No | No | No | No | Not applicable | Not applicable | Not applicable | 
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                    Goodness of Fit (metric| value | unit)
                
                
             
           
     
                            
                                
                                    em.detail.goodnessFitValuesHelp
                                
                                
                            
                            
                        ? | None | None | None | None | None | None | None | None | None | None | None | None | None | None | None | None | None | None | 
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                    Model Operational Validation Reported?
                
                
             
           
     
                            
                                
                                    em.detail.validationHelp
                                
                                
                            
                            
                        ? | No | Unclear | No | No | No | No | Yes | Not applicable | No | No | No | Yes ? Comment:Performed just for "Total pollinator abundance service score". | No | No | Yes | Not applicable | No | No | 
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                    Model Uncertainty Analysis Reported?
                
                
             
           
     
                            
                                
                                    em.detail.uncertaintyAnalysisHelp
                                
                                
                            
                            
                        ? | No | Unclear | No | No | No | No | No | Not applicable | Yes | No | No | No | No | No | No | Not applicable | Not applicable | No | 
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                    Model Sensitivity Analysis Reported?
                
                
             
           
     
                            
                                
                                    em.detail.sensAnalysisHelp
                                
                                
                            
                            
                        ? | No ? Comment:Sensitivity analysis performed for agent values only. | Unclear | No | No | No | No | Yes | Not applicable | Yes | No | No | No | No | No | No | Not applicable | Not applicable | No | 
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                    Model Sensitivity Analysis Include Interactions?
                
             
           
     
                            
                            
                                em.detail.interactionConsiderHelp
                            
                        ? | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | No | Not applicable | No | N/A | Not applicable | Not applicable | Not applicable | 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-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
| EM-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
| None | None | None | None | 
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 Comment:Realm: Tropical Atlantic Region: West Tropical Atlantic Province: Tropical Northwestern Atlantic Ecoregion: Floridian | None | None | None | None | None | None | None | None | None | 
Centroid Lat/Long (Decimal Degree)
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
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                    Centroid Latitude
                
                
             
           
     
                            
                                
                                    em.detail.ddLatHelp
                                
                                
                            
                            
                        ? | 44.11 | 35.99 | 39.5 | 45.05 | 27.74 | 44.62 | 47.8 | -9999 | 27.8 | 44.24 | 48 | 38.7 | 0 | 17.97 | 46.82 | 52.22 | Not applicable | 54.2 | 
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                    Centroid Longitude
                
                
             
           
     
                            
                                
                                    em.detail.ddLongHelp
                                
                                
                            
                            
                        ? | -123.09 | -78.96 | -98.35 | 6.4 | -82.57 | -124.06 | -122.7 | -9999 | -82.4 | -122.24 | -123 | -121.8 | 102 | -66.93 | 8.23 | -0.91 | Not applicable | -2.35 | 
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                    Centroid Datum
                
                
             
           
     
                            
                                
                                    em.detail.datumHelp
                                
                                
                            
                            
                        ? | WGS84 | None provided | WGS84 | WGS84 | WGS84 | None provided | WGS84 | Not applicable | WGS84 | None provided | WGS84 | WGS84 | WGS84 | WGS84 | WGS84 | WGS84 | Not applicable | WGS84 | 
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                    Centroid Coordinates Status
                
                
             
           
     
                            
                                
                                    em.detail.coordinateStatusHelp
                                
                                
                            
                            
                        ? | Estimated | Estimated | Estimated | Provided | Estimated | Provided | Estimated | Not applicable | Estimated | Provided | Estimated | Estimated | Provided | Estimated | Estimated | Estimated | Not applicable | Provided | 
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
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                    EM Environmental Sub-Class
                
                
             
           
     
                            
                                
                                    em.detail.emEnvironmentalSubclassHelp
                                
                                
                            
                            
                        ? | Rivers and Streams | Forests | Agroecosystems | Created Greenspace | Rivers and Streams | Created Greenspace | Terrestrial Environment (sub-classes not fully specified) | Agroecosystems | Grasslands | Near Coastal Marine and Estuarine | Near Coastal Marine and Estuarine | Near Coastal Marine and Estuarine | Rivers and Streams | Ground Water | Created Greenspace | Near Coastal Marine and Estuarine | Forests | Inland Wetlands | Terrestrial Environment (sub-classes not fully specified) | Forests | Atmosphere | Terrestrial Environment (sub-classes not fully specified) | Agroecosystems | Inland Wetlands | Lakes and Ponds | Forests | Agroecosystems | Created Greenspace | Grasslands | Scrubland/Shrubland | Barren | Aquatic Environment (sub-classes not fully specified) | Inland Wetlands | Near Coastal Marine and Estuarine | Open Ocean and Seas | Forests | Agroecosystems | Created Greenspace | Scrubland/Shrubland | Barren | Forests | Created Greenspace | Grasslands | Inland Wetlands | Agroecosystems | Grasslands | 
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                    Specific Environment Type
                
                
             
           
     
                            
                                
                                    em.detail.specificEnvTypeHelp
                                
                                
                            
                            
                        ? | Agricultural-urban interface at river junction | Urban areas including streams | Terrestrial | Subalpine terraces, grasslands, and meadows. | Habitat Zones (Low, Med, High, Optimal) around seagrass and emergent marsh | Estuarine intertidal | glacier-carved saltwater fjord | Urban watersheds | Created Mangrove wetlands | primarily Conifer Forest | Terrestrial environment surrounding a large estuary | Cropland and surrounding landscape | 104 land use land cover classes | 13 LULC were used | forests | restored landfills and grasslands | Wetlands | fertilized grassland (historically hayed) | 
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                    EM Ecological Scale
                
                
             
           
     
                            
                                
                                    em.detail.ecoScaleHelp
                                
                                
                            
                            
                        ? | Ecological scale is finer than that of the Environmental Sub-class | Not applicable | Ecological scale is finer than that of the Environmental Sub-class | Ecological scale is coarser than that of the Environmental Sub-class | Zone within an ecosystem | 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 | 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 | Ecological scale is finer 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 of differentiation of organisms modeled
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
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                    EM Organismal Scale
                
                
             
           
     
                            
                                
                                    em.detail.orgScaleHelp
                                
                                
                            
                            
                        ? | Not applicable | Not applicable | Not applicable | Community | Species | Guild or Assemblage | Not applicable | Community | Not applicable | Species | Not applicable | Species | Community | Not applicable | Community | Individual or population, within a species | Not applicable | Community | 
Taxonomic level and name of organisms or groups identified
| EM-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
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 | None Available | None Available | None Available | 
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 | None Available | None Available | 
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 | None Available | 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-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
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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-12   | EM-51   | EM-63 | EM-82 | EM-102   | EM-103 | EM-111   | EM-137 | EM-154 | EM-208   | EM-317 | EM-338   | EM-359   | EM-438 | EM-467   | EM-697   | EM-706 | EM-735   | 
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