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-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | EM-735   | 
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                    EM Short Name
                
             
           
     
                            
                            
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                        ? | EnviroAtlas-Nat. filtration-water | Fodder crude protein content, Central French Alps | Fish species habitat value, Tampa Bay, FL, USA | Birds in estuary habitats, Yaquina Estuary, WA, USA | Value of Habitat for Shrimp, Campeche, Mexico | InVEST water yield, Hood Canal, WA, USA | Mangrove development, Tampa Bay, FL, USA | FORCLIM v2.9, Santiam watershed, OR, USA | Biological pest control, Uppland Province, Sweden | Wetland shellfish production, Gulf of Mexico, USA | Decrease in erosion (shoreline), St. Croix, USVI | Yasso07 v1.0.1, Switzerland | Coastal protection in Belize | SolVES, Bridger-Teton NF, WY | Floral resources on landfill sites, United Kingdom | Northern Shoveler recruits, CREP wetlands, IA, USA | WESP Method | Pollinators on landfill sites, United Kingdom | C sequestration in grassland restoration, England | 
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                    EM Full Name
                
                
             
           
     
                            
                                
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                        ? | US EPA EnviroAtlas - Natural filtration (of water by tree cover); Example is shown for Durham NC and vicinity, USA | Fodder crude protein content, Central French Alps | Fish species habitat value, Tampa Bay, FL, USA | Bird use of estuarine habitats, Yaquina Estuary, WA, USA | Value of Habitat for Shrimp, Campeche, Mexico | InVEST (Integrated Valuation of Envl. Services and Tradeoffs) water yield, Hood Canal, WA, USA | Mangrove wetland development, Tampa Bay, FL, USA | FORCLIM (FORests in a changing CLIMate) v2.9, Santiam watershed, OR, USA | Biological control of agricultural pests by natural predators, Uppland Province, Sweden | Wetland shellfish production, Gulf of Mexico, USA | Decrease in erosion (shoreline) by reef, St. Croix, USVI | Yasso07 v1.0.1 forest litter decomposition, Switzerland | Coastal Protection provided by Coral, Seagrasses and Mangroves in Belize: | SolVES, Social Values for Ecosystem Services, Bridger-Teton National Forest, WY | Floral resources on landfill sites, East Midlands, United Kingdom | Northern Shoveler duck recruits, CREP (Conservation Reserve Enhancement Program) wetlands, Iowa, USA | Method for the Wetland Ecosystem Services Protocol (WESP) | Pollinating insects on landfill sites, East Midlands, United Kingdon | Carbon sequestration in grassland diversity restoration, England | 
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                    EM Source or Collection
                
             
           
     
                            
                            
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                        ? | US EPA | EnviroAtlas | i-Tree ? Comment:EnviroAtlas uses an application of the i-Tree Hydro model. | EU Biodiversity Action 5 | US EPA | US EPA | None | InVEST | US EPA | US EPA | None | US EPA ? Comment:Marine and Coastal Fisheries: Dynamics, Management, and Ecosystem Science | US EPA | None | InVEST | None | None | None | None | None | None | 
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                    EM Source Document ID
                
             
           
     | 223 | 260 | 187 | 275 | 227 | 205 | 97 | 23 ? Comment:Related document ID 22 is a secondary source providing tree species specific parameters in appendix. | 299 | 324 | 335 | 343 | 350 | 369 | 389 | 372 ? Comment:Document 373 is a secondary source for this EM. | 390 | 389 | 396 | 
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                    Document Author
                
                
             
           
     
                            
                                
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                        ? | 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. | Barbier, E. B., and Strand, I. | 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. | 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. | Jonsson, M., Bommarco, R., Ekbom, B., Smith, H.G., Bengtsson, J., Caballero-Lopez, B., Winqvist, C., and Olsson, O. | Stephen J. Jordan, Timothy O'Higgins and John A. Dittmar | Yee, S. H., Dittmar, J. A., and L. M. Oliver | Didion, M., B. Frey, N. Rogiers, and E. Thurig | Guannel, G., Arkema, K., Ruggiero, P., and G. Verutes | Sherrouse, B.C., Semmens, D.J., and J.M. Clement | Tarrant S., J. Ollerton, M. L Rahman, J. Tarrant, and D. McCollin | Otis, D. L., W. G. Crumpton, D. Green, A. K. Loan-Wilsey, R. L. McNeely, K. L. Kane, R. Johnson, T. Cooper, and M. Vandever | Adamus, P. R. | Tarrant S., J. Ollerton, M. L Rahman, J. Tarrant, and D. McCollin | 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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                        ? | 2013 | 2011 | 2016 | 2014 | 1998 | 2013 | 2012 | 2007 | 2014 | 2012 | 2014 | 2014 | 2016 | 2014 | 2013 | 2010 | 2016 | 2013 | 2011 | 
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                        ? | EnviroAtlas - Featured Community | 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 | Valuing mangrove-fishery linkages: A case study of Campeche, Mexico | From mountains to sound: modelling the sensitivity of dungeness crab and Pacific oyster to land–sea interactions in Hood Canal,WA | 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 | Ecological production functions for biological control services in agricultural landscapes | Ecosystem Services of Coastal Habitats and Fisheries: Multiscale Ecological and Economic Models in Support of Ecosystem-Based Management | Comparison of methods for quantifying reef ecosystem services: A case study mapping services for St. Croix, USVI | Validating tree litter decomposition in the Yasso07 carbon model | The Power of Three: Coral Reefs, Seagrasses and Mangroves Protect Coastal Regions and Increase Their Resilience | An application of Social Values for Ecosystem Services (SolVES) to three national forests in Colorado and Wyoming | Grassland restoration on landfill sites in the East Midlands, United Kingdom: An evaluation of floral resources and pollinating insects | Assessment of environmental services of CREP wetlands in Iowa and the midwestern corn belt | Manual for the Wetland Ecosystem Services Protocol (WESP) v. 1.3. | Grassland restoration on landfill sites in the East Midlands, United Kingdom: An evaluation of floral resources and pollinating insects | 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 | Peer reviewed and published | 
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                    Comments on Status
                
             
           
     
                            
                            
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                        ? | Published on US EPA EnviroAtlas website | 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 journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript | Published report | Published report | Published journal manuscript | Published journal manuscript | 
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                    EM ID
                
             
           
     
                            
                            
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                        ? | EM-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | EM-735   | 
| https://www.epa.gov/enviroatlas | Not applicable | Not applicable | Not applicable | Not applicable | https://www.naturalcapitalproject.org/invest/ | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | http://en.ilmatieteenlaitos.fi/yasso-download-and-support | Not identified in paper | Not applicable | Not applicable | Not applicable | http://people.oregonstate.edu/~adamusp/WESP/ ? Comment:This is an Excel spreadsheet calculator | Not applicable | Not applicable | |
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                        ? | EnviroAtlas Team | 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 | E.B. Barbier | J.E. Toft | Michael Osland | Richard T. Busing | Mattias Jonsson | Stephen J. Jordan | Susan H. Yee | Markus Didion ? Comment:Tel.: +41 44 7392 427 | Greg Guannel | Benson Sherrouse | Sam Tarrant | David Otis | Paul R. Adamus | Sam Tarrant | Gerlinde B. De Deyn | 
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                    Contact Address
                
             
           
     | 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 | Environment Department, University of York, York YO1 5DD, UK | The Natural Capital Project, Stanford University, 371 Serra Mall, Stanford, CA 94305-5020, USA | U.S. Environmental Protection Agency, Gulf Ecology Division, gulf Breeze, FL 32561 | U.S. Geological Survey, 200 SW 35th Street, Corvallis, Oregon 97333 USA | Department of Ecology, Swedish University of Agricultural Sciences, PO Box 7044, SE-750 07 Uppsala, Sweden | U.S. Environmental Protection Agency, Gulf Ecology Division, 1 Sabine Island Drive, Gulf Breeze, FL 32561, USA | US EPA, Office of Research and Development, NHEERL, Gulf Ecology Division, Gulf Breeze, FL 32561, USA | Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903 Birmensdorf, Switzerland | The Nature Conservancy, Coral Gables, FL. USA | USGS, 5522 Research Park Dr., Baltimore, MD 21228, USA | RSPB UK Headquarters, The Lodge, Sandy, Bedfordshire SG19 2DL, U.K. | U.S. Geological Survey, Iowa Cooperative Fish and Wildlife Research Unit, Iowa State University | 6028 NW Burgundy Dr. Corvallis, OR 97330 | RSPB UK Headquarters, The Lodge, Sandy, Bedfordshire SG19 2DL, U.K. | Dept. of Terrestrial Ecology, Netherlands Institute of Ecology, P O Box 40, 6666 ZG Heteren, The Netherlands | 
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     | enviroatlas@epa.gov | sandra.lavorel@ujf-grenoble.fr | Fulford.Richard@epa.gov | frazier@nceas.ucsb.edu | Not reported | jetoft@stanford.edu | mosland@usgs.gov | rtbusing@aol.com | mattias.jonsson@slu.se | jordan.steve@epa.gov | yee.susan@epa.gov | markus.didion@wsl.ch | greg.guannel@gmail.com | bcsherrouse@usgs.gov | sam.tarrant@rspb.org.uk | dotis@iastate.edu | adamus7@comcast.net | sam.tarrant@rspb.org.uk | g.dedeyn@nioo.knaw.nl; gerlindede@gmail.com | 
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                        ? | EM-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | EM-735   | 
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                    Summary Description
                
                
             
           
     
                            
                                
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                        ? | 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. | ABSTRACT: "Here, we propose a new approach for the analysis, mapping and understanding of multiple ES delivery in landscapes. Spatially explicit single ES models based on plant traits and abiotic characteristics are combined to identify ‘hot’ and ‘cold’ spots of multiple ES delivery, and the land use and biotic determinants of such distributions. We demonstrate the value of this trait-based approach as compared to a pure land-use approach for a pastoral landscape from the central French Alps, and highlight how it improves understanding of ecological constraints to, and opportunities for, the delivery of multiple services. Vegetative height and leaf traits such as leaf dry matter content were response traits strongly influenced by land use and abiotic environment, with follow-on effects on several ecosystem properties (e.g., fodder crude protein content), and could therefore be used as functional markers of ES." AUTHOR'S DESCRIPTION: "Variation in fodder crude protein content was modelled using…traits community-weighted mean (CWM) and functional divergence (FD) and abiotic variables (continuous variables; trait + abiotic) following Diaz et al. (2007). …The comparison between this model and the land-use alone model identifies the need for site-based information beyond a land use or land cover proxy…Fodder crude protein for each pixel was calculated and mapped using model estimates...This step is critically novel as compared to a direct application of the model by Diaz et al. (2007) in that we explicitly modelled the responses of trait community-weighted means and functional divergences to environment prior to evaluating their effects on fodder protein content. Such an approach is the key to the explicit representation of functional variation across the landscape, as opposed to the use of unique trait values within each land use." | 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." | AUTHOR'S DESCRIPTION: "We assume throughout that shrimp harvesting occurs through open access management that yields production which is exported internationally, and we modify a standard open access fishery model to account explicitly for the effect of the mangrove area on carrying capacity and thus production.We derive the conditions determining the long-run equilibrium of the model, including the comparative static effects of a change in mangrove area, on this equilibrium. Through regressing a relationship between shrimp harvest, effort and mangrove area over time, we estimate parameters based on the combinations of the bioeconomic parameters of the model determining the comparative statics. By incorporating additional economic data, we are able to simulate an estimate of the effect of changes in mangrove area in Laguna de Terminos on the production and value of shrimp harvests in Campeche state." (153) | 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: "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: "We develop a novel, mechanistic landscape model for biological control of cereal aphids, explicitly accounting for the influence of landscape composition on natural enemies varying in mobility, feeding rates and other life history traits. Finally, we use the model to map biological control services across cereal fields in a Swedish agricultural region with varying landscape complexity. The model predicted that biological control would reduce crop damage by 45–70% and that the biological control effect would be higher in complex landscapes. In a validation with independent data, the model performed well and predicted a significant proportion of biological control variation in cereal fields. However, much variability remains to be explained, and we propose that the model could be improved by refining the mechanistic understanding of predator dynamics and accounting for variation in aphid colonization." | ABSTRACT: "We present concepts and case studies linking the production functions (contributions to recruitment) of critical habitats to commercial and recreational fishery values by combining site specific research data with spatial analysis and population models. We present examples illustrating various spatial scales of analysis, with indicators of economic value, for … commercial blue crab Callinectes sapidus and penaeid shrimp fisheries in the Gulf of Mexico." | ABSTRACT: "...We investigated and compared a number of existing methods for quantifying ecological integrity, shoreline protection, recreational opportunities, fisheries production, and the potential for natural products discovery from reefs. Methods were applied to mapping potential ecosystem services production around St. Croix, U.S. Virgin Islands. Overall, we found that a number of different methods produced similar predictions." AUTHOR'S DESCRIPTION: "A number of methods have been developed for linking biophysical attributes of reef condition, such as reef structural complexity, fish biomass, or species richness, to provisioning of ecosystem goods and services (Principe et al., 2012). We investigated the feasibility of using existing methods and data for mapping production of reef ecosystem goods and services. We applied these methods toward mapping potential ecosystem goods and services production in St. Croix, U.S. Virgin Islands (USVI)...For each of the five categories of ecosystem services, we chose a suite of models and indices for estimating potential production based on relative ease of implementation, consisting of well-defined parameters, and likely availability of input data, to maximize potential for transferability to other locations. For each method, we assembled the necessary reef condition and environmental data as spatial data layers for St. Croix (Table1). The coastal zone surrounding St. Croix was divided into 10x10 m grid cells, and production functions were applied to quantify ecosystem services provisioning in each grid cell...Shoreline protection as an ecosystem service has been defined in a number of ways including protection from shoreline erosion...and can thus be estimated as % Decrease in erosion due to reef = 1 - (Ho/H)^2.5 where Ho is the attenuated wave height due to the presence of the reef and H is wave height in the absence of the reef." | 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." | AUTHOR'S DESCRIPTION: "Natural habitats have the ability to protect coastal communities against the impacts of waves and storms, yet it is unclear how different habitats complement each other to reduce those impacts. Here, we investigate the individual and combined coastal protection services supplied by live corals on reefs, seagrass meadows, and mangrove forests during both non-storm and storm conditions, and under present and future sea-level conditions. Using idealized profiles of fringing and barrier reefs, we quantify the services supplied by these habitats using various metrics of inundation and erosion. We find that, together, live corals, seagrasses, and mangroves supply more protection services than any individual habitat or any combination of two habitats. Specifically, we find that, while mangroves are the most effective at protecting the coast under non-storm and storm conditions, live corals and seagrasses also moderate the impact of waves and storms, thereby further reducing the vulnerability of coastal regions. Also, in addition to structural differences, the amount of service supplied by habitats in our analysis is highly dependent on the geomorphic setting, habitat location and forcing conditions: live corals in the fringing reef profile supply more protection services than seagrasses; seagrasses in the barrier reef profile supply more protection services than live corals; and seagrasses, in our simulations, can even compensate for the long-term degradation of the barrier reef. Results of this study demonstrate the importance of taking integrated and place-based approaches when quantifying and managing for the coastal protection services supplied by ecosystems." | [ABSTRACT: " "Despite widespread recognition that social-value information is needed to inform stakeholders and decision makers regarding trade-offs in environmental management, it too often remains absent from ecosystem service assessments. Although quantitative indicators of social values need to be explicitly accounted for in the decision-making process, they need not be monetary. Ongoing efforts to map such values demonstrate how they can also be made spatially explicit and relatable to underlying ecological information. We originally developed Social Values for Ecosystem Services (SolVES) as a tool to assess, map, and quantify nonmarket values perceived by various groups of ecosystem stakeholders.With SolVES 2.0 we have extended the functionality by integrating SolVES with Maxent maximum entropy modeling software to generate more complete social-value maps from available value and preference survey data and to produce more robust models describing the relationship between social values and ecosystems. The current study has two objectives: (1) evaluate how effectively the value index, a quantitative, nonmonetary social-value indicator calculated by SolVES, reproduces results from more common statistical methods of social-survey data analysis and (2) examine how the spatial results produced by SolVES provide additional information that could be used by managers and stakeholders to better understand more complex relationships among stakeholder values, attitudes, and preferences. To achieve these objectives, we applied SolVES to value and preference survey data collected for three national forests, the Pike and San Isabel in Colorado and the Bridger–Teton and the Shoshone in Wyoming. Value index results were generally consistent with results found through more common statistical analyses of the survey data such as frequency, discriminant function, and correlation analyses. In addition, spatial analysis of the social-value maps produced by SolVES provided information that was useful for explaining relationships between stakeholder values and forest uses. Our results suggest that SolVES can effectively reproduce information derived from traditional statistical analyses while adding spatially explicit, socialvalue information that can contribute to integrated resource assessment, planning, and management of forests and other ecosystems. | 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) | ABSTRACT: "Our initial primary objective (Progress Report I) was prediction of environmental services provided by the 27 Iowa Conservation Reserve Enhancement Program (CREP) wetland sites that had been completed by 2007 in the Prairie Pothole Region of northcentral Iowa. The sites contain 102.4 ha of wetlands and 377.4 ha of associated grassland buffers…" AUTHOR'S DESCRIPTION: "The first phase of the U.S. Fish and Wildlife Service task was to evaluate the contribution of the 27 approved sites to migratory birds breeding in the Prairie Pothole Region of Iowa. To date, evaluation has been completed for 7 species of waterfowl and 5 species of grassland birds. All evaluations were completed using existing models that relate landscape composition to bird populations. As such, the first objective was to develop a current land cover geographic information system (GIS) that reflected current landscape conditions including the incorporation of habitat restored through the CREP program. The second objective was to input landscape variables from our land cover GIS into models to estimate various migratory bird population parameters (i.e. the number of pairs, individuals, or recruits) for each site. Recruitment for the 27 sites was estimated for Mallards, Blue-winged Teal, Northern Shoveler, Gadwall, and Northern Pintail according to recruitment models presented by Cowardin et al. (1995). Recruitment was not estimated for Canada Geese and Wood Ducks because recruitment models do not exist for these species. Variables used to estimate recruitment included the number of pairs, the composition of the landscape in a 4-square mile area around the CREP wetland, species-specific habitat preferences, and species- and habitat-specific clutch success rates. Recruitment estimates were derived using the following equations: Recruits = 2*R*n where, 2 = constant based on the assumption of equal sex ratio at hatch, n = number of breeding pairs estimated using the pairs equation previously outlined, R = Recruitment rate as defined by Cowardin and Johnson (1979) where, R = H*Z*B/2 where, H = hen success (see Cowardin et al. (1995) for methods used to calculate H, which is related to land cover types in the 4-mile2 landscape around each wetland), Z = proportion of broods that survived to fledge at least 1 recruit (= 0.74 based on Cowardin and Johnson 1979), B = average brood size at fledging (= 4.9 based on Cowardin and Johnson 1979)." ENTERER'S COMMENT: The number of breeding pairs (n) is estimated by a separate submodel from this paper, and as such is also entered as a separate model in ESML (EM 632). | 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: "...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…In the first year of study, plants in flower and flower visitors were surveyed using the same transects as for the floral resources surveys. The transect was left undisturbed for 20 minutes following the initial plant survey to allow the flower visitors to return. Each transect was surveyed at a rate of approximately 3m/minute for 30 minutes. All insects observed to touch the sexual parts of flowers were either captured using a butterfly net and transferred into individually labeled specimen jars, or directly captured into the jars. After the survey was completed, those insects that could be identified in the field were recorded and released. The flower-visitor surveys were conducted in the morning, within 1 hour of midday, and in the afternoon to sample those insects active at different times. Insects that could not be identified in the field were collected as voucher specimens for later identification. Identifications were verified using reference collections and by taxon specialists. Relatively low capture rates in the first year led to methods being altered in the second year when surveying followed a spiral pattern from a randomly determined point on the sites, at a standard pace of 10 m/minute for 30 minutes, following Nielsen and Bascompte (2007) and Kalikhman (2007). Given a 2-m wide transect, an area of approximately 600m2 was sampled in each | 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
                                
                                
                            
                            
                        ? | None identified | None identified | None identifed | None identified | None identified | Land use change | Not applicable | None identified | None identified | None identified | None identified | None identified | Future rock lobster fisheries management | None | None identified | None identified | None identified | None identified | None identified | 
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                    Biophysical Context
                
                
             
           
     | No additional description provided | Elevation ranges from 1552 to 2442 m, on predominantely 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 | Gulf of Mexico; mangrove-lagoon system | Not additional description provided | mangrove forest,Salt marsh, estuary, sea level, | No additional description provided | Spring-sown cereal croplands, where the bird chearry-oat aphid is a key aphid pest. The aphid colonizes the crop during late May and early June, depending on weather and location. The colonization phase is followed by a brief phase of rapid exponential population growth by wingless aphids, continuing until about the time of crop heading, in late June or early July. After heading, aphid populations usually decline rapidly in the crop due to decreased plant quality and migration to grasslands. The aphids are attacked by a complex of arthropod natural enemies, but parasitism is not important in the region and therefore not modelled here. | Estuarine environments and marsh-land interfaces | No additional description provided | Different forest types dominated by Norway Spruce (Picea abies), European Beech (Fagus sylvatica) and Sweet Chestnut (Castanea sativa). | barrier reef and fringing reef in nearshore coastal marine system | Rocky mountain conifer forests | No additional description provided | Prairie Pothole Region of Iowa | None | 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. | 
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                    EM Scenario Drivers
                
                
             
           
     
                            
                                
                                    em.detail.scenarioDriverHelp
                                
                                
                            
                            
                        ? | No scenarios presented | No scenarios presented | No scenarios presented | No scenarios presented | No scenarios presented | Future land use and land cover; climate change | Not applicable | Land Management (3); Climate Change (3) | No scenarios presented | Shellfish type; Changes to submerged aquatic vegetation (SAV) | 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). | Reef type, Sea level increase, storm conditions, seagrass conditions, coral conditions, vegetation types and conditions | N/A | No scenarios presented | No scenarios presented | N/A | No scenarios presented | Additional benefits due to biodiversity restoration practices | 
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | 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 | 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 ? Comment:Runs differentiated by scenario combination. | Method + Application | Method + Application (multiple runs exist)  	     View EM Runs ? Comment:Ten runs; blue crab and penaeid shrimp, each combined with five different submerged aquatic vegetation habitat areas. | Method + Application | Method + 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 + Application | Method + Application (multiple runs exist) View EM Runs | Method + Application | Method Only | Method + Application (multiple runs exist) View EM Runs | Method + Application (multiple runs exist) View EM Runs | 
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                    New or Pre-existing EM?
                
                
             
           
     
                            
                                
                                    em.detail.newOrExistHelp
                                
                                
                            
                            
                        ? | 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 | Application of existing model | New or revised model | New or revised model | Application of existing model | Application of existing model | New or revised model | New or revised model | 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
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                    EM ID
                
                
             
           
     
                            
                                
                                    em.detail.idHelp
                                
                                
                            
                            
                        ? | EM-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | EM-735   | 
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                    Document ID for related EM
                
                
             
           
     
                            
                                
                                    em.detail.relatedEmDocumentIdHelp
                                
                                
                            
                            
                        ? | Doc-198 | Doc-260 | Doc-269 | None | None | None | Doc-280 | Doc-307 | Doc-311 | Doc-338 | None | Doc-22 | Doc-23 ? Comment:Related document ID 22 is a secondary source providing tree species specific parameters in appendix. | None | None | Doc-335 | Doc-342 | Doc-344 | None | None | None | Doc-372 | Doc-373 | None | Doc-389 | None | 
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                    EM ID for related EM
                
                
             
           
     
                            
                                
                                    em.detail.relatedEmEmIdHelp
                                
                                
                            
                            
                        ? | EM-137 | EM-142 | EM-65 | EM-66 | EM-69 | EM-70 | EM-71 | EM-79 | EM-80 | EM-81 | EM-82 | EM-83 | None | None | EM-185 | EM-319 | EM-148 | EM-344 | EM-368 | EM-437 | None | EM-146 | EM-186 | EM-224 | None | EM-604 | EM-603 | EM-447 | EM-448 | EM-466 | EM-469 | EM-480 | EM-485 | None | EM-629 | EM-626 | EM-709 | EM-705 | EM-704 | EM-703 | EM-701 | EM-700 | EM-632 | EM-718 | EM-697 | None | 
EM Modeling Approach
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | EM-735   | 
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                    EM Temporal Extent
                
                
             
           
     
                            
                                
                                    em.detail.tempExtentHelp
                                
                                
                            
                            
                        ? | 1999-2010 | 2007-2009 | 2006-2011 | December 2007 - November 2008 | 1980-1990 | 2005-7; 2035-45 | 1990-2010 | 1990-2050 | 2009 | 1950 - 2050 | 2006-2007, 2010 | 1993-2013 | 2005-2013 | 2004-2008 | 2007-2008 | 1987-2007 | Not applicable | 2007-2008 | 1990-2007 | 
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                    EM Time Dependence
                
                
             
           
     
                            
                                
                                    em.detail.timeDependencyHelp
                                
                                
                            
                            
                        ? | 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-stationary | time-dependent | time-stationary | time-dependent | time-dependent | time-stationary | time-stationary | time-stationary | time-stationary | time-stationary | time-stationary | 
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                    EM Time Reference (Future/Past)
                
                
             
           
     
                            
                                
                                    em.detail.futurePastHelp
                                
                                
                            
                            
                        ? | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | future time | future time | Not applicable | future time | Not applicable | future time | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | 
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                    EM Time Continuity
                
                
             
           
     
                            
                                
                                    em.detail.continueDiscreteHelp
                                
                                
                            
                            
                        ? | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | continuous | discrete | Not applicable | discrete | Not applicable | discrete | discrete | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | 
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                    EM Temporal Grain Size Value
                
                
             
           
     
                            
                                
                                    em.detail.tempGrainSizeHelp
                                
                                
                            
                            
                        ? | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | 1 | Not applicable | Varies by Run | Not applicable | 1 | 1 | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | 
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                    EM Temporal Grain Size Unit
                
                
             
           
     
                            
                                
                                    em.detail.tempGrainSizeUnitHelp
                                
                                
                            
                            
                        ? | Not applicable | Not applicable | Not applicable | Not applicable | Year | Not applicable | Not applicable | Year | Not applicable | Year | Not applicable | Year | Second | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | 
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | EM-735   | 
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                    Bounding Type
                
             
           
     
                            
                            
                                em.detail.boundingTypeHelp
                            
                        ? | Geopolitical | Physiographic or Ecological | Physiographic or Ecological | Physiographic or ecological | Physiographic or Ecological | Watershed/Catchment/HUC | Physiographic or Ecological | Watershed/Catchment/HUC | Geopolitical | Physiographic or ecological | Physiographic or ecological | Geopolitical | Geopolitical | Geopolitical | Multiple unrelated locations (e.g., meta-analysis) | Multiple unrelated locations (e.g., meta-analysis) | Not applicable | Multiple unrelated locations (e.g., meta-analysis) | Other | 
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                    Spatial Extent Name
                
             
           
     
                            
                            
                                em.detail.extentNameHelp
                            
                        ? | Durham, NC and vicinity | Central French Alps | Tampa Bay | Yaquina Estuary (intertidal), Oregon, USA | Laguna de Terminos Mangrove system | Hood Canal | Tampa Bay | South Santiam watershed | Uppland province | Gulf of Mexico (estuarine and coastal) | Coastal zone surrounding St. Croix | Switzerland | Coast of Belize | National Park | East Midlands | CREP (Conservation Reserve Enhancement Program | Not applicable | East Midlands | Colt Park meadows, Ingleborough National Nature Reserve, northern England | 
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                    Spatial Extent Area (Magnitude)
                
             
           
     
                            
                            
                                em.detail.extentAreaHelp
                            
                        ? | 100-1000 km^2 | 10-100 km^2 | 1000-10,000 km^2. | 1-10 km^2 | 100-1000 km^2 | 100,000-1,000,000 km^2 | 100-1000 km^2 | 100-1000 km^2 | 10,000-100,000 km^2 | 10,000-100,000 km^2 | 100-1000 km^2 | 10,000-100,000 km^2 | 100-1000 km^2 | 1000-10,000 km^2. | 1000-10,000 km^2. | 10,000-100,000 km^2 | Not applicable | 1000-10,000 km^2. | <1 ha | 
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | EM-735   | 
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                    EM Spatial Distribution
                
                
             
           
     
                            
                                
                                    em.detail.distributeLumpHelp
                                
                                
                            
                            
                        ? | 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) ? Comment:Computations at this pixel scale pertain to certain variables specific to Mobile Bay. | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially 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
                            
                        ? | 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 | other (specify), for irregular (e.g., stream reach, lake basin) | length, for linear feature (e.g., stream mile) | 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 | other (specify), for irregular (e.g., stream reach, lake basin) | area, for pixel or radial feature | 
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                    Spatial Grain Size
                
             
           
     
                            
                            
                                em.detail.spGrainSizeHelp
                            
                        ? | irregular | 20 m x 20 m | 1 km^2 | 0.87-104.29 ha | 1 km x 1 km | 30 m x 30 m | m^2 | 0.08 ha | 25 m x 25 m | 55.2 km^2 | 10 m x 10 m | 5 sites | 1 meter | 30m2 | multiple unrelated locations | multiple, individual, irregular sites | not reported | multiple unrelated locations | 3 m x 3 m | 
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | EM-735   | 
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                    EM Computational Approach
                
                
             
           
     
                            
                                
                                    em.detail.emComputationalApproachHelp
                                
                                
                            
                            
                        ? | 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 | Analytic | Numeric | Analytic | Numeric | Analytic | Numeric | Analytic | Numeric | Analytic | Analytic | Analytic | Analytic | Analytic | 
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                    EM Determinism
                
                
             
           
     
                            
                                
                                    em.detail.deterStochHelp
                                
                                
                            
                            
                        ? | deterministic | deterministic | deterministic | deterministic | deterministic | deterministic | deterministic | deterministic | deterministic | deterministic | deterministic | stochastic | deterministic | deterministic | deterministic | deterministic | deterministic | deterministic | stochastic | 
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                    Statistical Estimation of EM
                
             
           
     
                            
                            
                                em.detail.statisticalEstimationHelp
                            
                        ? | 
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | EM-735   | 
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                    Model Calibration Reported?
                
             
           
     
                            
                            
                                em.detail.calibrationHelp
                            
                        ? | Unclear | No | No | Unclear | Yes | Yes | No | No | No | Yes | Yes | No | No | No | Not applicable | Unclear | Not applicable | Not applicable | Not applicable | 
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                    Model Goodness of Fit Reported?
                
                
             
           
     
                            
                                
                                    em.detail.goodnessFitHelp
                                
                                
                            
                            
                        ? | No | Yes | No | No | Yes | No | No | No | No | No | No | No | No | Yes | Not applicable | No | Not applicable | Not applicable | Not applicable | 
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                    Goodness of Fit (metric| value | unit)
                
                
             
           
     
                            
                                
                                    em.detail.goodnessFitValuesHelp
                                
                                
                            
                            
                        ? | None | 
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                    Model Operational Validation Reported?
                
                
             
           
     
                            
                                
                                    em.detail.validationHelp
                                
                                
                            
                            
                        ? | Unclear | Yes | No | No | No | Yes | No | No | Yes | No | Yes | Yes | No ? Comment:Used the SWAN model (see below for referenece) with Generation 1 or 2 wind-wave formulations to validate the wave development portion of the model. Booij N, Ris RC, Holthuijsen LH. A third-generation wave model for coastal regions 1. Model description and validation. J Geophys Res. American Geophysical Union; 1999;104: 7649?7666. | No | Not applicable | No | No | Not applicable | No | 
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                    Model Uncertainty Analysis Reported?
                
                
             
           
     
                            
                                
                                    em.detail.uncertaintyAnalysisHelp
                                
                                
                            
                            
                        ? | Unclear | No | No | No | Yes | No | Yes | No | No | No | No | No | No | No | Not applicable | No | Not applicable | Not applicable | No | 
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                    Model Sensitivity Analysis Reported?
                
                
             
           
     
                            
                                
                                    em.detail.sensAnalysisHelp
                                
                                
                            
                            
                        ? | Unclear | No | No | No | Yes | Yes | Yes | No | Yes ? Comment:AUTHOR'S NOTE: "Varying aphid fecundity, overall predator abundances and attack rates affected the biological control effect, but had little influence on the relative differences between landscapes with high and low levels of biological control. The model predictions were more sensitive to changing the predators' landscape relations, but, with few exceptions, did not dramatically alter the overall patterns generated by the model." | No | No | No | No | No | Not applicable | 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 | Unclear | No | No | N/A | No | Not applicable | Not applicable | 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-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | EM-735   | 
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
| EM-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | EM-735   | 
| None | None | 
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 Comment:Realm: Tropical Atlantic Region: West Tropical Atlantic Province: Tropical Northwestern Atlantic Ecoregion: Floridian | None | None | 
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Centroid Lat/Long (Decimal Degree)
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | EM-735   | 
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                    Centroid Latitude
                
                
             
           
     
                            
                                
                                    em.detail.ddLatHelp
                                
                                
                            
                            
                        ? | 35.99 | 45.05 | 27.74 | 44.62 | 18.61 | 47.8 | 27.8 | 44.24 | 59.52 | 30.44 | 17.73 | 46.82 | 18.63 | 43.93 | 52.22 | 42.62 | Not applicable | 52.22 | 54.2 | 
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                    Centroid Longitude
                
                
             
           
     
                            
                                
                                    em.detail.ddLongHelp
                                
                                
                            
                            
                        ? | -78.96 | 6.4 | -82.57 | -124.06 | -91.55 | -122.7 | -82.4 | -122.24 | 17.9 | -87.99 | -64.77 | 8.23 | -88.22 | 110.24 | -0.91 | -93.84 | Not applicable | -0.91 | -2.35 | 
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                    Centroid Datum
                
                
             
           
     
                            
                                
                                    em.detail.datumHelp
                                
                                
                            
                            
                        ? | None provided | WGS84 | WGS84 | None provided | WGS84 | WGS84 | WGS84 | None provided | WGS84 | WGS84 | WGS84 | WGS84 | WGS84 | WGS84 | WGS84 | WGS84 | Not applicable | WGS84 | WGS84 | 
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                    Centroid Coordinates Status
                
                
             
           
     
                            
                                
                                    em.detail.coordinateStatusHelp
                                
                                
                            
                            
                        ? | Estimated | Provided | Estimated | Provided | Estimated | Estimated | Estimated | Provided | Estimated | Estimated | Estimated | Estimated | Estimated | Estimated | Estimated | Estimated | Not applicable | Estimated | Provided | 
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | EM-735   | 
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                    EM Environmental Sub-Class
                
                
             
           
     
                            
                                
                                    em.detail.emEnvironmentalSubclassHelp
                                
                                
                            
                            
                        ? | Rivers and Streams | Created Greenspace | Agroecosystems | Grasslands | Near Coastal Marine and Estuarine | Near Coastal Marine and Estuarine | Near Coastal Marine and Estuarine | Near Coastal Marine and Estuarine | Near Coastal Marine and Estuarine | Forests | Agroecosystems | Grasslands | Near Coastal Marine and Estuarine | Near Coastal Marine and Estuarine | Forests | Near Coastal Marine and Estuarine | Forests | Created Greenspace | Grasslands | Inland Wetlands | Agroecosystems | Grasslands | Inland Wetlands | Created Greenspace | Grasslands | Agroecosystems | Grasslands | 
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                    Specific Environment Type
                
                
             
           
     
                            
                                
                                    em.detail.specificEnvTypeHelp
                                
                                
                            
                            
                        ? | Urban areas including streams | Subalpine terraces, grasslands, and meadows | Habitat Zones (Low, Med, High, Optimal) around seagrass and emergent marsh | Estuarine intertidal | Mangrove | glacier-carved saltwater fjord | Created Mangrove wetlands | primarily Conifer Forest | Spring-sown cereal croplands and surrounding grassland and non-arable land | Submerged aquatic vegetation in estuaries and coastal lagoons | Coral reefs | forests | coral reefs | Montain forest | restored landfills and grasslands | Wetlands buffered by grassland within agroecosystems | Wetlands | restored landfills and grasslands | fertilized grassland (historically hayed) | 
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                    EM Ecological Scale
                
                
             
           
     
                            
                                
                                    em.detail.ecoScaleHelp
                                
                                
                            
                            
                        ? | Not applicable | Not applicable | 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 corresponds to 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 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 | Ecological scale corresponds to the Environmental Sub-class | 
Scale of differentiation of organisms modeled
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                    EM ID
                
             
           
     
                            
                            
                                em.detail.idHelp
                            
                        ? | EM-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | EM-735   | 
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                    EM Organismal Scale
                
                
             
           
     
                            
                                
                                    em.detail.orgScaleHelp
                                
                                
                            
                            
                        ? | Not applicable | Community | Species | Guild or Assemblage | Guild or Assemblage | Not applicable | Not applicable | Species | Individual or population, within a species | Species | Not applicable | Community | Guild or Assemblage | Not applicable | Individual or population, within a species | Individual or population, within a species | Not applicable | Individual or population, within a species | Community | 
Taxonomic level and name of organisms or groups identified
| EM-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | EM-735   | 
| None Available | None Available | 
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 | None Available | None Available | None Available | None Available | 
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 | 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-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | 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-51   | EM-68 | EM-102   | EM-103 | EM-106 | EM-111   | EM-154 | EM-208   | EM-303 | EM-397   | EM-449 | EM-467   | EM-542   | EM-628 | EM-697   | EM-702 | EM-706 | EM-709   | EM-735   | 
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