EcoService Models Library (ESML)

Compare EMs

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:

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Comparing:

EM-91
EM-154
EM-321
EM-604
EM-605
EM-697
EM-1018

Add EM to Compare:

EM Identity and Description

EM Identification

EM ID em.detail.idHelp ?	EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
EM Short Name em.detail.shortNameHelp ?	RHyME2, Upper Mississippi River basin, USA	Mangrove development, Tampa Bay, FL, USA	Erosion prevention by vegetation, Portel, Portugal	Chinook salmon value (household), Yaquina Bay, OR	VELMA v2.0, Ohio, USA	Floral resources on landfill sites, United Kingdom	WMOSTsustainable water Danvers-Middleton, MA
EM Full Name em.detail.fullNameHelp ?	RHyME2 (Regional Hydrologic Modeling for Environmental Evaluation), Upper Mississippi River basin, USA	Mangrove wetland development, Tampa Bay, FL, USA	Soil erosion prevention provided by vegetation cover, Portel municipality, Portugal	Economic value of Chinook salmon per household method, Yaquina Bay, OR	Visualizing Ecosystems for Land Management Assessments (VELMA) v2.0, Shayler Crossing watershed, Ohio, USA	Floral resources on landfill sites, East Midlands, United Kingdom	WMOST sustainable water management initiative Danvers-Middleton, MA
EM Source or Collection em.detail.emSourceOrCollectionHelp ?	US EPA	US EPA	EU Biodiversity Action 5	US EPA	US EPA	None	US EPA
EM Source Document ID	123	97	281	324	359 ? Comment: Document #366 is a supporting document for this EM. McKane et al. 2014, VELMA Version 2.0 User Manual and Technical Documentation.	389	477
Document Author em.detail.documentAuthorHelp ?	Tran, L. T., O’Neill, R. V., Smith, E. R., Bruins, R. J. F. and Harden, C.	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.	Stephen J. Jordan, Timothy O'Higgins and John A. Dittmar	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	Tarrant S., J. Ollerton, M. L Rahman, J. Tarrant, and D. McCollin	United States EPA
Document Year em.detail.documentYearHelp ?	2013	2012	2014	2012	2018	2013	2013
Document Title em.detail.sourceIdHelp ?	Application of hierarchy theory to cross-scale hydrologic modeling of nutrient loads	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	Ecosystem Services of Coastal Habitats and Fisheries: Multiscale Ecological and Economic Models in Support of Ecosystem-Based Management	Cumulative effects of low impact development on watershed hydrology in a mixed land-cover system	Grassland restoration on landfill sites in the East Midlands, United Kingdom: An evaluation of floral resources and pollinating insects	Watershed Management Optimization Support Tool (WMOST) v1 User manual
Document Status em.detail.statusCategoryHelp ?	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
Comments on Status em.detail.commentsOnStatusHelp ?	Published journal manuscript	Published journal manuscript	Published journal manuscript	Published journal manuscript	Published journal manuscript	Published journal manuscript	Published EPA report

Software and Access

EM ID em.detail.idHelp ?	EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
EM Software Access info Exit em.detail.modelAccessInformationHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	https://www.epa.gov/water-research/visualizing-ecosystem-land-management-assessments-velma-model-20	Not applicable	https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NHEERL&dirEntryId=262280
Contact Name em.detail.contactNameHelp ?	Liem Tran	Michael Osland	Carlos A. Guerra	Stephen Jordan	Heather Golden	Sam Tarrant	Naomi Detenbeck
Contact Address	Department of Geography, University of Tennessee, 1000 Phillip Fulmer Way, Knoxville, TN 37996-0925, USA	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	U.S. EPA, Gulf Ecology Div., 1 Sabine Island Dr., Gulf Breeze, FL 32561, USA	National Exposure Research Laboratory, Office of Research and Development, US EPA, Cincinnati, OH 45268, USA	RSPB UK Headquarters, The Lodge, Sandy, Bedfordshire SG19 2DL, U.K.	NHEERL, Atlantic Ecology Division Narragansett, RI 02882
Contact Email	ltran1@utk.edu	mosland@usgs.gov	cguerra@uevora.pt	jordan.steve@epa.gov	Golden.Heather@epa.gov	sam.tarrant@rspb.org.uk	detenbeck.naomi@epa.gov

EM Description

EM ID em.detail.idHelp ?	EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
Summary Description em.detail.summaryDescriptionHelp ?	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)	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:"Critical habitats for fish and wildlife are often small patches in landscapes, e.g., aquatic vegetation beds, reefs, isolated ponds and wetlands, remnant old-growth forests, etc., yet the same animal populations that depend on these patches for reproduction or survival can be extensive, ranging over large regions, even continents or major ocean basins. Whereas the ecological production functions that support these populations can be measured only at fine geographic scales and over brief periods of time, the ecosystem services (benefits that ecosystems convey to humans by supporting food production, water and air purification, recreational, esthetic, and cultural amenities, etc.) are delivered over extensive scales of space and time. These scale mismatches are particularly important for quantifying the economic values of ecosystem services. Examples can be seen in fish, shellfish, game, and bird populations. Moreover, there can be wide-scale mismatches in management regimes, e.g., coastal fisheries management versus habitat management in the coastal zone. 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 recreational Chinook (Oncorhynchus tshawytscha) salmon fisheries in the U.S. Pacific Northwest (Washington and Oregon) and commercial blue crab (Callinectes sapidus) and penaeid shrimp fisheries in the Gulf of Mexico.	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: "...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: "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.
Specific Policy or Decision Context Cited em.detail.policyDecisionContextHelp ?	Not reported	Not applicable	None identified	None identified	None identified	None identified	Not applicable
Biophysical Context	No additional description provided	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.	Yaquina Bay estuary	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.	No additional description provided	None
EM Scenario Drivers em.detail.scenarioDriverHelp ?	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	No scenarios presented	Three types of Low Impact Development (LID) practices (rain gardens, permeable pavements, forested riparian buffers) applied a different conversion levels.	No scenarios presented	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

EM ID em.detail.idHelp ?	EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
Method Only, Application of Method or Model Run em.detail.methodOrAppHelp ?	Method + Application	Method + Application	Method + Application (multiple runs exist) View EM Runs	Method + Application	Method + Application (multiple runs exist) View EM Runs	Method + Application (multiple runs exist) View EM Runs	Method + Application
New or Pre-existing EM? em.detail.newOrExistHelp ?	New or revised model	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

EM ID em.detail.idHelp ?	EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
Document ID for related EM em.detail.relatedEmDocumentIdHelp ?	Doc-123	None	Doc-282 \| Doc-283 \| Doc-284 \| Doc-285	Doc-324	Doc-13 \| Doc-366	None	Doc-477
EM ID for related EM em.detail.relatedEmEmIdHelp ?	None	None	None	EM-603 \| EM-397	EM-375 \| EM-377 \| EM-378 \| EM-884 \| EM-883 \| EM-887	EM-709	None

EM Modeling Approach

EM Relationship to Time

EM ID em.detail.idHelp ?	EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
EM Temporal Extent em.detail.tempExtentHelp ?	1987-1997	1990-2010	January to December 2003	2003-2008	Jan 1, 2009 to Dec 31, 2011	2007-2008	Not applicable
EM Time Dependence em.detail.timeDependencyHelp ?	time-stationary	time-dependent	time-dependent	time-stationary	time-dependent	time-stationary	time-dependent
EM Time Reference (Future/Past) em.detail.futurePastHelp ?	Not applicable	future time	future time	Not applicable	past time	Not applicable	Not applicable ? Comment: method description
EM Time Continuity em.detail.continueDiscreteHelp ?	Not applicable	continuous	discrete	Not applicable	discrete	Not applicable	discrete
EM Temporal Grain Size Value em.detail.tempGrainSizeHelp ?	Not applicable	Not applicable	1	Not applicable	1	Not applicable	1
EM Temporal Grain Size Unit em.detail.tempGrainSizeUnitHelp ?	Not applicable	Not applicable	Month	Not applicable	Day	Not applicable	Day

EM Spatial Extent

EM ID em.detail.idHelp ?	EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
Bounding Type em.detail.boundingTypeHelp ?	Watershed/Catchment/HUC	Physiographic or Ecological	Geopolitical	Geopolitical	Watershed/Catchment/HUC	Multiple unrelated locations (e.g., meta-analysis)	Watershed/Catchment/HUC
Spatial Extent Name em.detail.extentNameHelp ?	Upper Mississippi River basin; St. Croix River Watershed	Tampa Bay	Portel municipality	Pacific Northwest	Shayler Crossing watershed, a subwatershed of the East Fork Little Miami River Watershed	East Midlands	Danvers-Middleton
Spatial Extent Area (Magnitude) em.detail.extentAreaHelp ?	100,000-1,000,000 km^2	100-1000 km^2	100-1000 km^2	>1,000,000 km^2	10-100 ha	1000-10,000 km^2.	10-100 km^2

Spatial Distribution of Computations

EM ID em.detail.idHelp ?	EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
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 lumped (in all cases)	spatially distributed (in at least some cases)	spatially distributed (in at least some cases)	spatially lumped (in all cases)
Spatial Grain Type em.detail.spGrainTypeHelp ?	NHDplus v1	area, for pixel or radial feature	area, for pixel or radial feature	Not applicable	area, for pixel or radial feature	other (specify), for irregular (e.g., stream reach, lake basin)	Not applicable
Spatial Grain Size em.detail.spGrainSizeHelp ?	NHDplus v1	m^2	250 m x 250 m	Not applicable	10m x 10m	multiple unrelated locations	Not applicable

EM Structure and Computation Approach

EM ID em.detail.idHelp ?	EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
EM Computational Approach em.detail.emComputationalApproachHelp ?	Numeric	Analytic	Analytic	Analytic	Numeric	Analytic	Numeric
EM Determinism em.detail.deterStochHelp ?	deterministic	deterministic	deterministic	deterministic	deterministic	deterministic	deterministic
Statistical Estimation of EM em.detail.statisticalEstimationHelp ?	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics

Model Checking Procedures Used

EM ID em.detail.idHelp ?	EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
Model Calibration Reported? em.detail.calibrationHelp ?	Yes	No	No	No	Yes	Not applicable	Unclear
Model Goodness of Fit Reported? em.detail.goodnessFitHelp ?	Yes	No	No	No	Yes ? Comment: Goodness of fit for calibrated (2009-2010) and observed streamflow.	Not applicable	Unclear
Goodness of Fit (metric\| value \| unit) em.detail.goodnessFitValuesHelp ?	R^2 \| 0.923 \| none Mean Square Error \| 25.1 \| %	None	None	None	None	None	None
Model Operational Validation Reported? em.detail.validationHelp ?	No	No	No	Yes	Yes	Not applicable	Not applicable
Model Uncertainty Analysis Reported? em.detail.uncertaintyAnalysisHelp ?	No	Yes	No	No	No	Not applicable	Not applicable
Model Sensitivity Analysis Reported? em.detail.sensAnalysisHelp ?	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.	Yes	No	No	No	Not applicable	Not applicable
Model Sensitivity Analysis Include Interactions? em.detail.interactionConsiderHelp ?	Not applicable	No	Not applicable	Not applicable	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])

EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
North America United States Indiana Illinois Missouri South Dakota Minnesota Idaho Wisconsin	North America United States Florida	Europe Portugal	North America United States Oregon Washington	North America United States Ohio	Europe United Kingdom	None

Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)

EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
None	Tropical Atlantic West Tropical Atlantic Tropical Northwestern Atlantic Floridian ? Comment: Realm: Tropical Atlantic Region: West Tropical Atlantic Province: Tropical Northwestern Atlantic Ecoregion: Floridian	None	Temperate North Pacific Northeast Pacific Cold Temperate Northeast Pacific Oregon, Washington, Vancouver Coast and Shelf	None	None	None

Centroid Lat/Long (Decimal Degree)

EM ID em.detail.idHelp ?	EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
Centroid Latitude em.detail.ddLatHelp ?	42.5	27.8	38.3	44.62	39.19	52.22	42.58
Centroid Longitude em.detail.ddLongHelp ?	-90.63	-82.4	-7.7	-124.02	-84.29	-0.91	-70.93
Centroid Datum em.detail.datumHelp ?	WGS84	WGS84	WGS84	WGS84	WGS84	WGS84	WGS84
Centroid Coordinates Status em.detail.coordinateStatusHelp ?	Estimated	Estimated	Estimated	Estimated	Provided	Estimated	Estimated

Environments and Scales Modeled

EM ID em.detail.idHelp ?	EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
EM Environmental Sub-Class em.detail.emEnvironmentalSubclassHelp ?	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	Terrestrial Environment (sub-classes not fully specified) \| Forests \| Agroecosystems \| Scrubland/Shrubland	Near Coastal Marine and Estuarine \| Terrestrial Environment (sub-classes not fully specified)	Rivers and Streams \| Ground Water \| Forests \| Agroecosystems \| Created Greenspace	Created Greenspace \| Grasslands	Terrestrial Environment (sub-classes not fully specified)
Specific Environment Type em.detail.specificEnvTypeHelp ?	None	Created Mangrove wetlands	Silvo-pastoral system	Yaquina Bay estuary and ocean	Mixed land cover suburban watershed	restored landfills and grasslands	watershed
EM Ecological Scale em.detail.ecoScaleHelp ?	Ecosystem	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	Ecological scale corresponds to 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

EM ID em.detail.idHelp ?	EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
EM Organismal Scale em.detail.orgScaleHelp ?	Not applicable	Not applicable	Not applicable	Other (multiple scales)	Not applicable	Individual or population, within a species	Not applicable

Taxonomic level and name of organisms or groups identified

EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
None Available	Species Laguncularia racemosa Avicennia germinans Rhizophora mangle Spartina alterniflora	None Available	Species Chinook salmon (Onchorhyncus tshawytscha)	None Available	Species Rhinanthus minor Picris echioides Lotus corniculatus Cardamine flexuosa Ranunculus acris Ranunculus bulbosus Stellaria graminea Trifolium dubium Picris hieracioides Ranunculus repens Trifolium repens Galium verum Cirsium arvense	None Available

EnviroAtlas URL

EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
The National Hydrography Dataset (NHD), National Hydrography Dataset Plus (NHD PlusV2), Average Annual Precipitation, Total Annual Reduced Nitrogen Deposition, Total Annual Nitrogen Deposition, The Watershed Boundary Dataset (WBD)	None Available	Average Annual Precipitation	Dasymetric Allocation of Population	Average Annual Precipitation, Average Annual Daily Potential Wind Energy	GAP Ecological Systems	National Hydrography Dataset Plus (NHD PlusV2), Wetlands and Streams, Agricultural water use (million gallons/day), Water supply from NID reservoirs (million gallons)

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-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Water conditions Chemical condition of freshwaters	[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Soil formation and composition Decomposition and fixing processes Atmospheric composition and climate regulation Global climate regulation by reduction of greenhouse gas concentrations Lifecycle maintenance, habitat and gene pool protection Pollination and seed dispersal	[Ecosystem] Regulation & Maintenance Mediation of flows Mass flows Buffering and attenuation of mass flows Mass stabilisation and control of erosion rates	[Ecosystem] Cultural Physical and intellectual interactions with biota, ecosystems, and land-/seascapes [environmental settings] Physical and experiential interactions Physical use of land-/seascapes in different environmental settings	[Ecosystem] Regulation & Maintenance Mediation of flows Liquid flows Flood protection	[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Lifecycle maintenance, habitat and gene pool protection Maintaining nursery populations and habitats	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>

(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)

EM-91	EM-154	EM-321	EM-604	EM-605	EM-697	EM-1018
None	Near Coastal Marine/Estuarine (113) Flora (5) Trees Stock Indicator Seaweed Stock Indicator Composite (8) Regulation of extreme events Quality Indicator	Forests (21) Soil (2) Specific types of soil Flow Indicator Scrubland/Shrubland (24) Soil (2) Specific types of soil Flow Indicator Agroecosystems (22) Soil (2) Specific types of soil Flow Indicator	Near Coastal Marine/Estuarine (113) Fauna (4) Fish Site Indicator	Rivers and Streams (111) Water (3) Liquid water Flow Indicator	None	None

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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)

<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)