EcoService Models Library (ESML)
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Which comparison is best for me?EM Variables by Variable Role
One quick way to compare ecological models (EMs) is by comparing their variables. Predictor variables show what kinds of influences a model is able to account for, and what kinds of data it requires. Response variables show what information a model is capable of estimating.
This first comparison shows the names (and units) of each EM’s variables, side-by-side, sorted by variable role. Variable roles in ESML are as follows:
- Predictor Variables
- Time- or Space-Varying Variables
- Constants and Parameters
- Intermediate (Computed) Variables
- Response Variables
- Computed Response Variables
- Measured Response Variables
EM Variables by Category
A second way to use variables to compare EMs is by focusing on the kind of information each variable represents. The top-level categories in the ESML Variable Classification Hierarchy are as follows:
- Policy Regarding Use or Management of Ecosystem Resources
- Land Surface (or Water Body Bed) Cover, Use or Substrate
- Human Demographic Data
- Human-Produced Stressor or Enhancer of Ecosystem Goods and Services Production
- Ecosystem Attributes and Potential Supply of Ecosystem Goods and Services
- Non-monetary Indicators of Human Demand, Use or Benefit of Ecosystem Goods and Services
- Monetary Values
Besides understanding model similarities, sorting the variables for each EM by these 7 categories makes it easier to see if the compared models can be linked using similar variables. For example, if one model estimates an ecosystem attribute (in Category 5), such as water clarity, as a response variable, and a second model uses a similar attribute (also in Category 5) as a predictor of recreational use, the two models can potentially be used in tandem. This comparison makes it easier to spot potential model linkages.
All EM Descriptors
This selection allows a more detailed comparison of EMs by model characteristics other than their variables. The 50-or-so EM descriptors for each model are presented, side-by-side, in the following categories:
- EM Identity and Description
- EM Modeling Approach
- EM Locations, Environments, Ecology
- EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system
EM Descriptors by Modeling Concepts
This feature guides the user through the use of the following seven concepts for comparing and selecting EMs:
- Conceptual Model
- Modeling Objective
- Modeling Context
- Potential for Model Linkage
- Feasibility of Model Use
- Model Certainty
- Model Structural Information
Though presented separately, these concepts are interdependent, and information presented under one concept may have relevance to other concepts as well.
Compare Criteria:
Show Criteria
Hide CriteriaEM Identity and Description
EM Identification
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EM ID
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EM-91 | EM-103 | EM-154 |
EM-321 
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EM-605
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EM-1018 |
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EM Short Name
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RHyME2, Upper Mississippi River basin, USA | Birds in estuary habitats, Yaquina Estuary, WA, USA | Mangrove development, Tampa Bay, FL, USA | Erosion prevention by vegetation, Portel, Portugal | VELMA v2.0, Ohio, USA | WMOSTsustainable water Danvers-Middleton, MA |
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EM Full Name
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RHyME2 (Regional Hydrologic Modeling for Environmental Evaluation), Upper Mississippi River basin, USA | Bird use of estuarine habitats, Yaquina Estuary, WA, USA | Mangrove wetland development, Tampa Bay, FL, USA | Soil erosion prevention provided by vegetation cover, Portel municipality, Portugal | Visualizing Ecosystems for Land Management Assessments (VELMA) v2.0, Shayler Crossing watershed, Ohio, USA | WMOST sustainable water management initiative Danvers-Middleton, MA |
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EM Source or Collection
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US EPA | US EPA | US EPA | EU Biodiversity Action 5 | US EPA | US EPA |
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EM Source Document ID
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123 | 275 | 97 | 281 |
359 ?Comment:Document #366 is a supporting document for this EM. McKane et al. 2014, VELMA Version 2.0 User Manual and Technical Documentation. |
477 |
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Document Author
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Tran, L. T., O’Neill, R. V., Smith, E. R., Bruins, R. J. F. and Harden, C. | Frazier, M. R., Lamberson, J. O. and Nelson, W. G. | 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. | Guerra, C.A., Pinto-Correia, T., Metzger, M.J. | Hoghooghi, N., H. E. Golden, B. P. Bledsoe, B. L. Barnhart, A. F. Brookes, K. S. Djang, J. J. Halama, R. B. McKane, C. T. Nietch, and P. P. Pettus | United States EPA |
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Document Year
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2013 | 2014 | 2012 | 2014 | 2018 | 2013 |
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Document Title
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Application of hierarchy theory to cross-scale hydrologic modeling of nutrient loads | Intertidal habitat utilization patterns of birds in a Northeast Pacific estuary | Ecosystem development after mangrove wetland creation: plant–soil change across a 20-year chronosequence | Mapping soil erosion prevention using an ecosystem service modeling framework for integrated land management and policy | Cumulative effects of low impact development on watershed hydrology in a mixed land-cover system | Watershed Management Optimization Support Tool (WMOST) v1 User manual |
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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 |
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Comments on Status
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Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript | Published EPA report |
Software and Access
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EM ID
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EM-91 | EM-103 | EM-154 |
EM-321
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EM-605
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EM-1018 |
| Not applicable | Not applicable | Not applicable | Not applicable | https://www.epa.gov/water-research/visualizing-ecosystem-land-management-assessments-velma-model-20 | https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NHEERL&dirEntryId=262280 | |
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Contact Name
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Liem Tran |
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 |
Michael Osland | Carlos A. Guerra | Heather Golden | Naomi Detenbeck |
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Contact Address
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Department of Geography, University of Tennessee, 1000 Phillip Fulmer Way, Knoxville, TN 37996-0925, USA | 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 | U.S. Environmental Protection Agency, Gulf Ecology Division, gulf Breeze, FL 32561 | Instituto de Ciências Agrárias e Ambientais Mediterrânicas, Universidade de Évora, Pólo da Mitra, Apartado 94, 7002-554 Évora, Portugal | National Exposure Research Laboratory, Office of Research and Development, US EPA, Cincinnati, OH 45268, USA | NHEERL, Atlantic Ecology Division Narragansett, RI 02882 |
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Contact Email
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ltran1@utk.edu | frazier@nceas.ucsb.edu | mosland@usgs.gov | cguerra@uevora.pt | Golden.Heather@epa.gov | detenbeck.naomi@epa.gov |
EM Description
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EM ID
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EM-91 | EM-103 | EM-154 |
EM-321
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EM-605
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EM-1018 |
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Summary Description
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ABSTRACT: "We describe a framework called Regional Hydrologic Modeling for Environmental Evaluation (RHyME2) for hydrologic modeling across scales. Rooted from hierarchy theory, RHyME2 acknowledges the rate-based hierarchical structure of hydrological systems. Operationally, hierarchical constraints are accounted for and explicitly described in models put together into RHyME2. We illustrate RHyME2with a two-module model to quantify annual nutrient loads in stream networks and watersheds at regional and subregional levels. High values of R2 (>0.95) and the Nash–Sutcliffe model efficiency coefficient (>0.85) and a systematic connection between the two modules show that the hierarchy theory-based RHyME2 framework can be used effectively for developing and connecting hydrologic models to analyze the dynamics of hydrologic systems." Two EMs will be entered in EPF-Library: 1. Regional scale module (Upper Mississippi River Basin) - this entry 2. Subregional scale module (St. Croix River Basin) | 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." | 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: "We present an integrative conceptual framework to estimate the provision of soil erosion prevention (SEP) by combining the structural impact of soil erosion and the social–ecological processes that allow for its mitigation. The framework was tested and illustrated in the Portel municipality in Southern Portugal, a Mediterranean silvo-pastoral system that is prone to desertification and soil degradation. The results show a clear difference in the spatial and temporal distribution of the capacity for ecosystem service provision and the actual ecosystem service provision." AUTHOR'S DESCRIPTION: "To begin assessing the contribution of SEP we need to identify the structural impact of soil erosion, that is, the erosion that would occur when vegetation is absent and therefore no ES is provided. It determines the potential soil erosion in a given place and time and is related to rainfall erosivity (that is, the erosive potential of rainfall), soil erodibility (as a characteristic of the soil type) and local topography. Although external drivers can have an effect on these variables (for example, climate change), they are less prone to be changed directly by human action. The actual ES provision reduces the total amount of structural impact, and we define the remaining impact as the ES mitigated impact. We can then define the capacity for ES provision as a key component to determine the fraction of the structural impact that is mitigated…Following the conceptual outline, we will estimate the SEP provided by vegetation cover using an adaptation of the Universal Soil Loss Equation (USLE)." | ABSTRACT: "Low Impact Development (LID) is an alternative to conventional urban stormwater management practices, which aims at mitigating the impacts of urbanization on water quantity and quality. Plot and local scale studies provide evidence of LID effectiveness; however, little is known about the overall watershed scale influence of LID practices. This is particularly true in watersheds with a land cover that is more diverse than that of urban or suburban classifications alone. We address this watershed-scale gap by assessing the effects of three common LID practices (rain gardens, permeable pavement, and riparian buffers) on the hydrology of a 0.94 km2 mixed land cover watershed. We used a spatially-explicit ecohydrological model, called Visualizing Ecosystems for Land Management Assessments (VELMA), to compare changes in watershed hydrologic responses before and after the implementation of LID practices. For the LID scenarios, we examined different spatial configurations, using 25%, 50%, 75% and 100% implementation extents, to convert sidewalks into rain gardens, and parking lots and driveways into permeable pavement. We further applied 20 m and 40 m riparian buffers along streams that were adjacent to agricultural land cover…" AUTHOR'S DESCRIPTION: "VELMA’s modeling domain is a three-dimensional matrix that includes information regarding surface topography, land use, and four soil layers. VELMA uses a distributed soil column framework to model the lateral and vertical movement of water and nutrients through the four soil layers. A soil water balance is solved for each layer. The soil column model is placed within a watershed framework to create a spatially distributed model applicable to watersheds (Figure 2, shown here with LID practices). Adjacent soil columns interact through down-gradient water transport. Water entering each pixel (via precipitation or flow from an adjacent pixel) can either first infiltrate into the implemented LID and the top soil layer, and then to the downslope pixel, or continue its downslope movement as the lateral surface flow. Surface and subsurface lateral flow are routed using a multiple flow direction method, as described in Abdelnour et al. [21]. A detailed description of the processes and equations can be found in McKane et al. [32], Abdelnour et al. [21], Abdelnour et al. [40]." | ABSTRACT: "The Watershed Management Optimization Support Tool (WMOST) is intended to be used as a screening tool as part of an integrated watershed management process such as that described in EPA’s watershed planning handbook (EPA 2008).1 The objective of WMOST is to serve as a public-domain, efficient, and user-friendly tool for local water resources managers and planners to screen a widerange of potential water resources management options across their watershed or jurisdiction for costeffectiveness as well as environmental and economic sustainability (Zoltay et al 2010). Examples of options that could be evaluated with the tool include projects related to stormwater, water supply, wastewater and water-related resources such as Low-Impact Development (LID) and land conservation. The tool is intended to aid in evaluating the environmental and economic costs, benefits, trade-offs and co-benefits of various management options. In addition, the tool is intended to facilitate the evaluation of low impact development (LID) and green infrastructure as alternative or complementary management options in projects proposed for State Revolving Funds (SRF). WMOST is a screening model that is spatially lumped with a daily or monthly time step. The model considers water flows but does not yet consider water quality. The optimization of management options is solved using linear programming. The target user group for WMOST consists of local water resources managers, including municipal water works superintendents and their consultants. This document includes a presentation of a case study appling WMOST to the Danvers-Middleton, MA sustainable water management initiative. |
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Specific Policy or Decision Context Cited
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Not reported | None identified | Not applicable | None identified | None identified | Not applicable |
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Biophysical Context
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No additional description provided | Estuarine intertidal, eelgrass, mudflat, sandflat and low marsh | mangrove forest,Salt marsh, estuary, sea level, | Open savannah-like forest of cork (Quercus suber) and holm (Quercus ilex) oaks, with trees of different ages randomly dispersed in changing densities, and pastures in the under cover. The pastures are mostly natural in a mosaic with patches of shrubs, which differ in size and the distribution depends mainly on the grazing intensity. Shallow, poor soils are prone to erosion, especially in areas with high grazing pressure. | The Shayler Crossing (SHC) watershed is a subwatershed of the East Fork Little Miami River Watershed in southwest Ohio, USA and falls within the Till Plains region of the Central Lowland physiographic province. The Till Plains region is a topographically young and extensive flat plain, with many areas remaining undissected by even the smallest stream. The bedrock is buried under a mantle of glacial drift 3–15 m thick. The Digital Elevation Model (DEM) has a maximum value of ~269 m (North American_1983 datum) within the watershed boundary (Figure 1). The soils are primarily the Avonburg and Rossmoyne series, with high silty clay loam content and poor to moderate infiltration. Average annual precipitation for the period, 1990 through 2011, was 1097.4 _ 173.5 mm. Average annual air temperature for the same period was 12 _C Mixed land cover suburban watershed. The primary land uses consist of 64.1% urban or developed area (including 37% lawn, 12% building, 6.5% street, 6.4% sidewalk, and 2.1% parking lot and driveway), 23% agriculture, and 13% deciduous forest. Total imperviousness covers approximately 27% of the watershed area. | None |
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EM Scenario Drivers
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No scenarios presented | No scenarios presented | Not applicable | Different land management practices as represented by the comparison of different grazing intensities (i.e., livestock densities) in the whole study area and in three Civil Parishes within the study area | Three types of Low Impact Development (LID) practices (rain gardens, permeable pavements, forested riparian buffers) applied a different conversion levels. |
None ?Comment:Not presented with scenarios, but the model was run with multiple scenarios for costs related to varying instream minimum flows and provided the associated costs for each run. |
EM Relationship to Other EMs or Applications
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EM ID
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EM-91 | EM-103 | EM-154 |
EM-321
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EM-605
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EM-1018 |
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Method Only, Application of Method or Model Run
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Method + Application | Method + Application | Method + Application | Method + Application (multiple runs exist) View EM Runs | Method + Application (multiple runs exist) View EM Runs | Method + Application |
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New or Pre-existing EM?
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New or revised model | New or revised model | New or revised model | New or revised model | New or revised model | Application of existing model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
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EM ID
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EM-91 | EM-103 | EM-154 |
EM-321
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EM-605
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EM-1018 |
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Document ID for related EM
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Doc-123 | None | None | Doc-282 | Doc-283 | Doc-284 | Doc-285 | Doc-13 | Doc-366 | Doc-477 |
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EM ID for related EM
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None | None | None | None | EM-375 | EM-377 | EM-378 | EM-884 | EM-883 | EM-887 | None |
EM Modeling Approach
EM Relationship to Time
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EM ID
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EM-91 | EM-103 | EM-154 |
EM-321
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EM-605
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EM-1018 |
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EM Temporal Extent
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1987-1997 | December 2007 - November 2008 | 1990-2010 | January to December 2003 | Jan 1, 2009 to Dec 31, 2011 | Not applicable |
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EM Time Dependence
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time-stationary | time-stationary | time-dependent | time-dependent | time-dependent | time-dependent |
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EM Time Reference (Future/Past)
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Not applicable | Not applicable | future time | future time | past time |
Not applicable ?Comment:method description |
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EM Time Continuity
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Not applicable | Not applicable | continuous | discrete | discrete | discrete |
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EM Temporal Grain Size Value
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Not applicable | Not applicable | Not applicable | 1 | 1 | 1 |
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EM Temporal Grain Size Unit
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Not applicable | Not applicable | Not applicable | Month | Day | Day |
EM Spatial Extent
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EM ID
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EM-91 | EM-103 | EM-154 |
EM-321
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EM-605
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EM-1018 |
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Bounding Type
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Watershed/Catchment/HUC | Physiographic or ecological | Physiographic or Ecological | Geopolitical | Watershed/Catchment/HUC | Watershed/Catchment/HUC |
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Spatial Extent Name
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Upper Mississippi River basin; St. Croix River Watershed | Yaquina Estuary (intertidal), Oregon, USA | Tampa Bay | Portel municipality | Shayler Crossing watershed, a subwatershed of the East Fork Little Miami River Watershed | Danvers-Middleton |
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Spatial Extent Area (Magnitude)
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100,000-1,000,000 km^2 | 1-10 km^2 | 100-1000 km^2 | 100-1000 km^2 | 10-100 ha | 10-100 km^2 |
Spatial Distribution of Computations
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EM ID
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EM-91 | EM-103 | EM-154 |
EM-321
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EM-605
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EM-1018 |
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EM Spatial Distribution
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spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially lumped (in all cases) |
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Spatial Grain Type
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NHDplus v1 | other (habitat type) | area, for pixel or radial feature | area, for pixel or radial feature | area, for pixel or radial feature | Not applicable |
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Spatial Grain Size
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NHDplus v1 | 0.87-104.29 ha | m^2 | 250 m x 250 m | 10m x 10m | Not applicable |
EM Structure and Computation Approach
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EM ID
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EM-91 | EM-103 | EM-154 |
EM-321
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EM-605
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EM-1018 |
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EM Computational Approach
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Numeric | Analytic | Analytic | Analytic | Numeric | Numeric |
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EM Determinism
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deterministic | deterministic | deterministic | deterministic | deterministic | deterministic |
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Statistical Estimation of EM
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Model Checking Procedures Used
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EM ID
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EM-91 | EM-103 | EM-154 |
EM-321
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EM-605
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EM-1018 |
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Model Calibration Reported?
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Yes | Unclear | No | No | Yes | Unclear |
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Model Goodness of Fit Reported?
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Yes | No | No | No |
Yes ?Comment:Goodness of fit for calibrated (2009-2010) and observed streamflow. |
Unclear |
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Goodness of Fit (metric| value | unit)
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None | None | None | None | None |
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Model Operational Validation Reported?
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No | No | No | No | Yes | Not applicable |
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Model Uncertainty Analysis Reported?
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No | No | Yes | No | No | Not applicable |
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Model Sensitivity Analysis Reported?
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No ?Comment:Some model coefficients serve, by their magnitude, to indicate the proportional impact on the final result of variation in the parameters they modify. |
No | Yes | No | No | Not applicable |
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Model Sensitivity Analysis Include Interactions?
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Not applicable | Not applicable | No | Not applicable | Not applicable | Not applicable |
EM Locations, Environments, Ecology
Location of EM Application
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
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| EM-91 | EM-103 | EM-154 |
EM-321
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EM-605
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EM-1018 |
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None |
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
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| EM-91 | EM-103 | EM-154 |
EM-321
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EM-605
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EM-1018 |
| None |
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Comment:Realm: Tropical Atlantic Region: West Tropical Atlantic Province: Tropical Northwestern Atlantic Ecoregion: Floridian |
None | None | None |
Centroid Lat/Long (Decimal Degree)
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EM ID
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EM-91 | EM-103 | EM-154 |
EM-321
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EM-605
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EM-1018 |
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Centroid Latitude
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42.5 | 44.62 | 27.8 | 38.3 | 39.19 | 42.58 |
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Centroid Longitude
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-90.63 | -124.06 | -82.4 | -7.7 | -84.29 | -70.93 |
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Centroid Datum
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WGS84 | None provided | WGS84 | WGS84 | WGS84 | WGS84 |
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Centroid Coordinates Status
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Estimated | Provided | Estimated | Estimated | Provided | Estimated |
Environments and Scales Modeled
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EM ID
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EM-91 | EM-103 | EM-154 |
EM-321
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EM-605
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EM-1018 |
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EM Environmental Sub-Class
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Aquatic Environment (sub-classes not fully specified) | Rivers and Streams | Inland Wetlands | Terrestrial Environment (sub-classes not fully specified) | Agroecosystems | Atmosphere | Near Coastal Marine and Estuarine | Near Coastal Marine and Estuarine | Terrestrial Environment (sub-classes not fully specified) | Forests | Agroecosystems | Scrubland/Shrubland | Rivers and Streams | Ground Water | Forests | Agroecosystems | Created Greenspace | Terrestrial Environment (sub-classes not fully specified) |
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Specific Environment Type
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None | Estuarine intertidal | Created Mangrove wetlands | Silvo-pastoral system | Mixed land cover suburban watershed | watershed |
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EM Ecological Scale
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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 coarser 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 |
Scale and taxa of organisms modeled
Scale of differentiation of organisms modeled
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EM ID
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EM-91 | EM-103 | EM-154 |
EM-321
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EM-605
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EM-1018 |
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EM Organismal Scale
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Not applicable | Guild or Assemblage | Not applicable | Not applicable | Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
taxonomyHelp
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| EM-91 | EM-103 | EM-154 |
EM-321
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EM-605
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EM-1018 |
| None Available |
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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.detail.cicesHelp
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| EM-91 | EM-103 | EM-154 |
EM-321
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EM-605
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EM-1018 |
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None |
<a target="_blank" rel="noopener noreferrer" href="https://www.epa.gov/eco-research/national-ecosystem-services-classification-system-nescs-plus">National Ecosystem Services Classification System (NESCS) Plus</a>
fegs1Help
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(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
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| EM-91 | EM-103 | EM-154 |
EM-321
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EM-605
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EM-1018 |
| None |
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None |