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.

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Comparing:

EM-349
EM-368
EM-432
EM-446
EM-541
EM-701
EM-729
EM-735
EM-760
EM-887
EM-979

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EM Identity and Description

EM Identification

EM ID em.detail.idHelp ?	EM-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
EM Short Name em.detail.shortNameHelp ?	InVEST (v1.004) Carbon, Indonesia	InVEST - Water Yield (v3.0)	Nitrogen fixation rates, Guánica Bay, Puerto Rico	CRPI, St. Croix, USVI	InVEST fisheries, lobster, South Africa	Blue-winged Teal recruits, CREP wetlands, IA, USA	WESP: Urban Stormwater Treatment, ID, USA	C sequestration in grassland restoration, England	WESP: Marsh & wet meadow, ID, USA	VELMA v. 2.0 disturbance	Predicting ecosystem service values, Bangladesh
EM Full Name em.detail.fullNameHelp ?	InVEST (Integrated Valuation of Environmental Services and Tradeoffs version 1.004) carbon storage and sequestration, Sumatra, Indonesia	InVEST v3.0 Reservoir Hydropower Projection, aka Water Yield	Nitrogen fixation rates, Guánica Bay, Puerto Rico, USA	CRPI (Coral Reef Protection Index, St. Croix, USVI	Integrated Valuation of Ecosystem Services and Trade-offs Fisheries, rock lobster, South Africa	Blue-winged Teal duck recruits, CREP (Conservation Reserve Enhancement Program) wetlands, Iowa, USA	WESP: Urban Stormwater Treament, ID, USA	Carbon sequestration in grassland diversity restoration, England	WESP: Seasonally flooded marsh & wet meadow, Idaho, USA	VELMA (Visualizing Ecosystems for Land Management Assessment) version 2.0 disturbance	Future ecosystem service value modeling with land cover dynamics by using machine learning based Artificial Neural Network model for Jashore city, Bangladesh
EM Source or Collection em.detail.emSourceOrCollectionHelp ?	InVEST	InVEST	US EPA	US EPA	InVEST	None	None	None	None	US EPA	None
EM Source Document ID	309	311	338 ? Comment: WE received a draft copy prior to journal publication that was agency reviewed.	335	349 ? Comment: Supplemented with the InVEST Users Guide fisheries.	372 ? Comment: Document 373 is a secondary source for this EM.	393 ? Comment: Additional data came from electronic appendix provided by author Chris Murphy.	396	393 ? Comment: Additional data came from electronic appendix provided by author Chris Murphy.	366	457
Document Author em.detail.documentAuthorHelp ?	Bhagabati, N. K., Ricketts, T., Sulistyawan, T. B. S., Conte, M., Ennaanay, D., Hadian, O., McKenzie, E., Olwero, N., Rosenthal, A., Tallis, H., and Wolney, S.	Natural Capital Project	Amelia Smith, Susan Harrell Yee, Marc Russell, Jill Awkerman and William S. Fisher	Yee, S. H., Dittmar, J. A., and L. M. Oliver	Ward, Michelle, Hugh Possingham, Johathan R. Rhodes, Peter Mumby	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	Murphy, C. and T. Weekley	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	Murphy, C. and T. Weekley	McKane, R. B., A. Brookes, K. Djang, M. Stieglitz, A. G. Abdelnour, F. Pan, J. J. Halama, P. B. Pettus and D. L. Phillips	Morshed, S. R., Fattah, M. A., Haque, M. N., & Morshed, S. Y.
Document Year em.detail.documentYearHelp ?	2014	2015	2017	2014	2018	2010	2012	2011	2012	2014	2022
Document Title em.detail.sourceIdHelp ?	Ecosystem services reinforce Sumatran tiger conservation in land use plans	Water Yield: Reservoir Hydropower Production- InVEST (v3.0)	Linking ecosystem services supply to stakeholder concerns on both land and sea: An example from Guanica Bay watershed, Puerto Rico	Comparison of methods for quantifying reef ecosystem services: A case study mapping services for St. Croix, USVI	Food, money and lobsters: Valuing ecosystem services to align environmental management with Sustainable Development Goals	Assessment of environmental services of CREP wetlands in Iowa and the midwestern corn belt	Measuring outcomes of wetland restoration, enhancement, and creation in Idaho-- Assessing potential functions, values, and condition in a watershed context.	Additional carbon sequestration benefits of grassland diversity restoration	Measuring outcomes of wetland restoration, enhancement, and creation in Idaho-- Assessing potential functions, values, and condition in a watershed context.	VELMA Version 2.0 User Manual and Technical Documentation	Future ecosystem service value modeling with land cover dynamics by using machine learning based Artificial Neural Network model for Jashore city, Bangladesh
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	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	Web published	Published journal manuscript	Published journal manuscript	Published journal manuscript	Published report	Published report	Published journal manuscript	Published report	Published report	Published journal manuscript

Software and Access

EM ID em.detail.idHelp ?	EM-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
EM Software Access info Exit em.detail.modelAccessInformationHelp ?	https://www.naturalcapitalproject.org/invest/	https://www.naturalcapitalproject.org/invest/	Not applicable	Not applicable	https://www.naturalcapitalproject.org/invest/	Not applicable	Not applicable	Not applicable	Not applicable	https://www.epa.gov/water-research/visualizing-ecosystem-land-management-assessments-velma-model-20	Not applicable
Contact Name em.detail.contactNameHelp ?	Nirmal K. Bhagabati	Natural Capital Project	Susan H. Yee	Susan H. Yee	Michelle Ward	David Otis	Chris Murphy	Gerlinde B. De Deyn	Chris Murphy	Robert B. McKane	Syed Riad Morshed
Contact Address	The Nature Conservancy, 1107 Laurel Avenue, Felton, CA 95018	371 Serra Mall, Stanford University, Stanford, Ca 94305	U.S. Environmental Protection Agency, Gulf Ecology Division, Gulf Breeze, FL 32561, USA	US EPA, Office of Research and Development, NHEERL, Gulf Ecology Division, Gulf Breeze, FL 32561, USA	ARC Centre of Excellence for Environmental Decisions, The University of Queensland, Brisbane, QLD 4072, Australia	U.S. Geological Survey, Iowa Cooperative Fish and Wildlife Research Unit, Iowa State University	Idaho Dept. Fish and Game, Wildlife Bureau, Habitat Section, Boise, ID	Dept. of Terrestrial Ecology, Netherlands Institute of Ecology, P O Box 40, 6666 ZG Heteren, The Netherlands	Idaho Dept. Fish and Game, Wildlife Bureau, Habitat Section, Boise, ID	U.S. EPA, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Western Ecology Division, Corvallis, Oregon 97333	Department of Urban and Regional Planning, Khulna University of Engineering and Technology, Khulna, Bangladesh
Contact Email	nirmal.bhagabati@wwfus.org	invest@naturalcapitalproject.org	yee.susan@epa.gov	yee.susan@epa.gov	m.ward@uq.edu.au	dotis@iastate.edu	chris.murphy@idfg.idaho.gov	g.dedeyn@nioo.knaw.nl; gerlindede@gmail.com	chris.murphy@idfg.idaho.gov	mckane.bob@epa.gov	riad.kuet.urp16@gmail.com

EM Description

EM ID em.detail.idHelp ?	EM-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
Summary Description em.detail.summaryDescriptionHelp ?	Please note: This ESML entry describes a specific, published application of an InVEST model. Different versions (e.g. different tiers) or more recent versions of this model may be available at the InVEST website. ABSTRACT: "...Here we use simple spatial analyses on readily available datasets to compare the distribution of five ecosystem services with tiger habitat in central Sumatra. We assessed services and habitat in 2008 and the changes in these variables under two future scenarios: a conservation-friendly Green Vision, and a Spatial Plan developed by the Indonesian government..." AUTHOR'S DESCRIPTION: "We used a modeling tool, InVEST (Integrated Valuation of Environmental Services and Tradeoffs version 1.004; Tallis et al., 2010), to map and quantify tiger habitat quality and five ecosystem services. InVEST maps ecosystem services and the quality of species habitat as production functions of LULC using simple biophysical models. Models were parameterized using data from regional agencies, literature surveys, global databases, site visits and prior field experience (Table 1)... We mapped biomass carbon by assigning carbon values (in ton ha_1) for aboveground, belowground, and dead organic matter to each LULC class based on values from literature, as described in Tallis et al. (2010). We mapped soil carbon separately, as large quantities of carbon are stored in peat soil (Page et al., 2011). We estimated total losses in peat carbon over 50 years into the future scenarios, using reported annual emission rates for specific LULC transitions on peat (Uryu et al., 2008)...Although InVEST reports ecosystem services in biophysical units, its simple models are best suited to understanding broad patterns of spatial variation (Tallis and Polasky, 2011), rather than for precise quantification. Additionally, we lacked field measurements against which to calibrate our outputs. Therefore, we focused on relative spatial distribution across the landscape, and relative change to scenarios."	Please note: This ESML entry describes an InVEST model version that was current as of 2015. More recent versions may be available at the InVEST website. AUTHOR'S DESCRIPTION: "The InVEST Reservoir Hydropower model estimates the relative contributions of water from different parts of a landscape, offering insight into how changes in land use patterns affect annual surface water yield and hydropower production. Modeling the connections between landscape changes and hydrologic processes is not simple. Sophisticated models of these connections and associated processes (such as the WEAP model) are resource and data intensive and require substantial expertise. To accommodate more contexts, for which data are readily available, InVEST maps and models the annual average water yield from a landscape used for hydropower production, rather than directly addressing the affect of LULC changes on hydropower failure as this process is closely linked to variation in water inflow on a daily to monthly timescale. Instead, InVEST calculates the relative contribution of each land parcel to annual average hydropower production and the value of this contribution in terms of energy production. The net present value of hydropower production over the life of the reservoir also can be calculated by summing discounted annual revenues. The model runs on a gridded map. It estimates the quantity and value of water used for hydropower production from each subwatershed in the area of interest. It has three components, which run sequentially. First, it determines the amount of water running off each pixel as the precipitation less the fraction of the water that undergoes evapotranspiration. The model does not differentiate between surface, subsurface and baseflow, but assumes that all water yield from a pixel reaches the point of interest via one of these pathways. This model then sums and averages water yield to the subwatershed level. The pixel-scale calculations allow us to represent the heterogeneity of key driving factors in water yield such as soil type, precipitation, vegetation type, etc. However, the theory we are using as the foundation of this set of models was developed at the subwatershed to watershed scale. We are only confident in the interpretation of these models at the subwatershed scale, so all outputs are summed and/or averaged to the subwatershed scale. We do continue to provide pixel-scale representations of some outputs for calibration and model-checking purposes only. These pixel-scale maps are not to be interpreted for understanding of hydrological processes or to inform decision making of any kind.	AUTHOR'S DESCRIPTION: " …In Guánica Bay watershed, Puerto Rico, deforestation and drainage of a large lagoon have led to sediment, contaminant, and nutrient transport into the bay, resulting in declining quality of coral reefs. A watershed management plan is currently being implemented to restore reefs through a variety of proposed actions…After the workshops, fifteen indicators of terrestrial ecosystem services in the watershed and four indicators in the coastal zone were identified to reflect the wide range of stakeholder concerns that could be impacted by management decisions. Ecosystem service production functions were applied to quantify and map ecosystem services supply in the Guánica Bay watershed, as well as an additional highly engineered upper multi-watershed area connected to the lower watershed via a series of reservoirs and tunnels,…” AUTHOR''S DESCRIPTION: "The U.S. Coral Reef Task Force (CRTF), a collaboration of federal, state and territorial agencies, initiated a program in 2009 to better incorporate land-based sources of pollution and socio-economic considerations into watershed strategies for coral reef protection (Bradley et al., 2016)...Baseline measures for relevant ecosystem services were calculated by parameterizing existing methods, largely based on land cover (Egoh et al., 2012; Martinez- Harms and Balvanera, 2012), with relevant rates of ecosystem services production for Puerto Rico, and applying them to map ecosystem services supply for the Guánica Bay Watershed...The Guánica Bay watershed is a highly engineered watershed in southwestern Puerto Rico, with a series of five reservoirs and extensive tunnel systems artificially connecting multiple mountainous sub-watersheds to the lower watershed of the Rio Loco, which itself is altered by an irrigation canal and return drainage ditch that diverts water through the Lajas Valley (PRWRA, 1948)...For each objective, a translator of ecosystem services production, i.e., ecological production function, was used to quantify baseline measurements of ecosystem services supply from land use/land cover (LULC) maps for watersheds across Puerto Rico...Two additional metrics, nitrogen fixation and rates of carbon sequestration into soil and sediment, were also calculated as potential measures of soil quality and agricultural productivity. Carbon sequestration and nitrogen fixation rates were assigned to each land cover class"	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, storm damage, or coastal inundation during extreme events (UNEP-WCMC (United Nations Environment Programme, World Conservation Monitoring Centre), 2006; WRI (World Resources Institute), 2009), but is often quantified as wave energy attenuation, an intermediate service that contributes to shoreline protection by reducing rates of erosion or coastal inundation (Principeet al., 2012)...An alternative index has been developed specifically for coral reefs, the Coral Reef Protection Index (CRPI), that accounts for the continuity of the reef and distance from shore in addition to reef habitat type (Burke et al., 2008): CRPI = ((Reef type + Reef distribution + Reef distance)/10) x 4 where the scaled magnitude of coastal protection due to each factor ranges from 0 (no protection) to 4 (very high protection; Table 2)."	AUTHOR'S DESCRIPTION: "Here we develop a method for assessing future scenarios of environmental management change that improve coastal ecosystem services and thereby, support the success of the SDGs. We illustrate application of the method using a case study of South Africa’s West Coast Rock Lobster fishery within the Table Mountain National Park (TMNP) Marine Protected Area...We calculated the retrospective and current value of the West Coast Rock Lobster fishery using published and unpublished data from various sources and combined the market worth of landed lobster from recreational fishers, small-scale fisheries (SSF), large-scale fisheries (LSF) and poachers. Then using the InVEST tool, we combined data to build scenarios that describe possible futures for the West Coast Rock Lobster fishery (see Table 1). The first scenario, entitled ‘Business as Usual’ (BAU), takes the current situation and most up-to-date data to model the future if harvest continues at the existing rate. The second scenario is entitled ‘Redirect the Poachers’ (RP), which attempts to model implementation of strict management, whereby poaching is minimised from the Marine Protected Area and other economic and nutritional sources are made available through government initiatives. The third scenario, entitled ‘Large Scale Cutbacks’ (LSC), excludes large-scale fisheries from harvesting West Coast Rock Lobster within the TMNP Marine Protected Area."	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 = 2Rn 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 = HZB/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).	A wetland restoration monitoring and assessment program framework was developed for Idaho. The project goal was to assess outcomes of substantial governmental and private investment in wetland restoration, enhancement and creation. The functions, values, condition, and vegetation at restored, enhanced, and created wetlands on private and state lands across Idaho were retrospectively evaluated. Assessment was conducted at multiple spatial scales and intensities. Potential functions and values (ecosystem services) were rapidly assessed using the Oregon Rapid Wetland Assessment Protocol. Vegetation samples were analyzed using Floristic Quality Assessment indices from Washington State. We compared vegetation of restored, enhanced, and created wetlands with reference wetlands that occurred in similar hydrogeomorphic environments determined at the HUC 12 level.	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…"	A wetland restoration monitoring and assessment program framework was developed for Idaho. The project goal was to assess outcomes of substantial governmental and private investment in wetland restoration, enhancement and creation. The functions, values, condition, and vegetation at restored, enhanced, and created wetlands on private and state lands across Idaho were retrospectively evaluated. Assessment was conducted at multiple spatial scales and intensities. Potential functions and values (ecosystem services) were rapidly assessed using the Oregon Rapid Wetland Assessment Protocol. Vegetation samples were analyzed using Floristic Quality Assessment indices from Washington State. We compared vegetation of restored, enhanced, and created wetlands with reference wetlands that occurred in similar hydrogeomorphic environments determined at the HUC 12 level.	VELMA – Visualizing Ecosystems for Land Management Assessments - is a spatially distributed, eco-hydrological model that links a land surface hydrology model with a terrestrial biogeochemistry model for simulating the integrated responses of vegetation, soil, and water resources to interacting stressors. For example, VELMA can simulate how changes in climate and land use interact to affect soil water storage, surface and subsurface runoff, vertical drainage, evapotranspiration, vegetation and soil carbon and nitrogen dynamics, and transport of nitrate, ammonium, and dissolved organic carbon and nitrogen to water bodies. VELMA differs from other existing eco-hydrology models in its simplicity, flexibility, and theoretical foundation. The model has a user-friendly Graphics User Interface (GUI) for easy input of model parameter values. In addition, advanced visualization of simulation results can enhance understanding of results and underlying concepts. VELMA’s visualization and interactivity features are packaged in an open-source, open-platform programming environment (Java / Eclipse). The development team for VELMA version 2.0 includes Dr. Bob McKane and coworkers at the U.S. Environmental Protection Agency’s Western Ecology Division, Dr. Marc Stieglitz and coworkers at the Georgia Institute of Technology, and Dr. Feifei Pan at the University of North Texas. AUTHOR'S DESCRIPTION: "Understanding how disturbances such as harvest, fire and fertilization affect ecosystem services has been a major motivation in the development of VELMA. For example, how do disturbances such as forest harvest or the application of agronomic fertilizers affect hydrological and biogeochemical processes controlling water quality and quantity, carbon sequestration, production of greenhouse gases, etc.? Abdelnour et al. (2011, 2013) have already demonstrated the use of VELMA v1.0 to simulate the effects of forest clearcutting on ecohydrological processes that regulate a variety of ecosystem services. With the addition of a tissue-specific plant biomass (LSR) simulator and an enhanced GUI, VELMA v2.0 significantly expands the detail, flexibility, and ease of use for simulating disturbance effects. Currently available disturbance models include: - BurnDisturbanceModel, effects of fire. - GrazeDisturbanceModel, effects of grazing. - FertilizeLsrDisturbanceModel, effects of fertilizer applications. - HarvestLsrDisturbanceModel, effects of biomass harvest. Each of these disturbance models specifies where and when a disturbance event will occur. The Burn, Graze and Harvest models have options for specifying how much of each plant tissue and detritus pool (leaves, stems, roots) will be removed and where it goes (offsite and/or to a specified onsite C and N pools). The Fertilize model has options for applying nitrogen as ammonium, nitrate, urea and/or manure."	Land Use/Land Cover (LULC) provides provisional, supporting, cultural, and regulating ecosystem services that contribute to ecological environments, enhance human health and living, have economic advantages for sustaining living organisms. LULC transformation due to enormous urban expansion diminishing Ecosystem Services Values (ESVs) and discouraging sustainability. Though unplanned LULC transformation practice became more prevalent in developing countries, comprehensive assessment of LULC changes and their influences in ESVs are rarely attempted. This study aimed to illustrate and forecast the LULC changes and their influences on ESVs change in Jashore using remote sensing technologies. ESVs estimation and change analysis were conducted by utilizing -derived LULC data of the year 2000, 2010, and 2020 with the corresponding global value coefficients of each LULC type which are previously published. For simulating future LULC and ESVs, Land Change Modeler of TerrSet Geospatial Monitoring and Modeling Software was used in Multi-Layer Perceptron-Markov Chain and Artificial Neural Network method. The decline of agricultural land by 13.13% and waterbody by 5.79% has resulted in the reduction of total ESVs US$0.23 million (24.47%) during 2000–2020. The forecasted result shows that the built-up area will be dominant LULC in the future, and ESVs of provisioning and cultural services will be diminished by $0.107 million, $63400.3 by 2050 with the declination of agricultural, waterbody, vegetation, and vacant land covers. The study signifies the importance of a strategic rational land-use plan to strictly monitor and control the encroachment of built-up areas into vegetation, waterbodies, and agricultural land in addition to scientific mitigative policies for ensuring ecological sustainability.
Specific Policy or Decision Context Cited em.detail.policyDecisionContextHelp ?	This analysis provided input to government-led spatial planning and strategic environmental assessments in the study area. This region contains some of the last remaining forest habitat of the critically endangered Sumatran tiger, Panthera tigris sumatrae.	None identified	None provided	None identified	Future rock lobster fisheries management	None identified	None identified	None identified	None identified	None identified	N/A
Biophysical Context	Six watersheds in central Sumatra covering portions of Riau, Jambi and West Sumatra provinces. The Barisan mountain range comprises the western edge of the watersheds, while peat swamps predominate in the east.	None applicable	No additional description provided	No additional description provided	No additional description provided	Prairie Pothole Region of Iowa	restored, enhanced and created wetlands	Lolium perenne-Cynosorus cristatus grassland; The soil is a shallow brown-earth (average depth 28 cm) over limestone of moderate-high residual fertility.	restored, enhanced and created wetlands	No additional description provided	Jashore city, Bangladesh
EM Scenario Drivers em.detail.scenarioDriverHelp ?	Baseline year 2008, future LULC Sumatra 2020 Roadmap (Vision), future LULC Government Spatial Plan	N/A	No scenarios presented	No scenarios presented	Fisheries exploitation; fishing vulnerability (of age classes)	No scenarios presented	Sites, function or habitat focus	Additional benefits due to biodiversity restoration practices	Sites, function or habitat focus	No scenarios presented	No scenarios presented

EM Relationship to Other EMs or Applications

EM ID em.detail.idHelp ?	EM-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
Method Only, Application of Method or Model Run em.detail.methodOrAppHelp ?	Method + Application (multiple runs exist) View EM Runs	Method Only	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 (multiple runs exist) View EM Runs	Method Only	Method + Application
New or Pre-existing EM? em.detail.newOrExistHelp ?	Application of existing model	New or revised model	Application of existing model	Application of existing model	Application of existing model	New or revised model	WESP - Urban Stormwater Treatment	New or revised model	New or revised model	New or revised model	New or revised model

Related EMs (for example, other versions or derivations of this EM) described in ESML

EM ID em.detail.idHelp ?	EM-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
Document ID for related EM em.detail.relatedEmDocumentIdHelp ?	Doc-315	Doc-307 \| Doc-280 \| Doc-338 \| Doc-205	None	None	None	Doc-372 \| Doc-373	Doc-390	None	Doc-390	Doc-13 \| Doc-317 \| Doc-366 \| Doc-359	None
EM ID for related EM em.detail.relatedEmEmIdHelp ?	EM-374	EM-437 \| EM-148 \| EM-344 \| EM-111	None	None	None	EM-705 \| EM-704 \| EM-703 \| EM-702 \| EM-700 \| EM-632	EM-718 \| EM-734	None	EM-718 \| EM-734 \| EM-743	EM-883 \| EM-884 \| EM-375 \| EM-379 \| EM-380 \| EM-605 \| EM-892	None

EM Modeling Approach

EM Relationship to Time

EM ID em.detail.idHelp ?	EM-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
EM Temporal Extent em.detail.tempExtentHelp ?	2008-2020	Not applicable	1978 - 2009	2006-2007, 2010	1986-2115	1987-2007	2010-2011	1990-2007	2010-2012	Not applicable	2000-2050
EM Time Dependence em.detail.timeDependencyHelp ?	time-stationary	time-dependent	time-stationary	time-stationary	time-dependent	time-stationary	time-dependent	time-stationary	time-dependent	time-dependent	time-dependent
EM Time Reference (Future/Past) em.detail.futurePastHelp ?	Not applicable	future time	Not applicable	Not applicable	future time	Not applicable	past time	Not applicable	past time	Not applicable	both
EM Time Continuity em.detail.continueDiscreteHelp ?	Not applicable	discrete	Not applicable	Not applicable	discrete	Not applicable	Not applicable	Not applicable	Not applicable	discrete	discrete
EM Temporal Grain Size Value em.detail.tempGrainSizeHelp ?	Not applicable	1	Not applicable	Not applicable	1	Not applicable	Not applicable	Not applicable	Not applicable	1	10
EM Temporal Grain Size Unit em.detail.tempGrainSizeUnitHelp ?	Not applicable	Year	Not applicable	Not applicable	Year	Not applicable	Not applicable	Not applicable	Not applicable	Day	Year

EM Spatial Extent

EM ID em.detail.idHelp ?	EM-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
Bounding Type em.detail.boundingTypeHelp ?	Watershed/Catchment/HUC	Not applicable	Watershed/Catchment/HUC	Physiographic or ecological	Geopolitical	Multiple unrelated locations (e.g., meta-analysis)	Multiple unrelated locations (e.g., meta-analysis)	Other	Multiple unrelated locations (e.g., meta-analysis)	Not applicable	Geopolitical
Spatial Extent Name em.detail.extentNameHelp ?	central Sumatra	Not applicable	Guanica Bay watershed	Coastal zone surrounding St. Croix	Table Mountain National Park Marine Protected Area	CREP (Conservation Reserve Enhancement Program	Wetlands in idaho	Colt Park meadows, Ingleborough National Nature Reserve, northern England	Wetlands in idaho	Not applicable	Jashore city, Bangladesh
Spatial Extent Area (Magnitude) em.detail.extentAreaHelp ?	100,000-1,000,000 km^2	Not applicable	100-1000 km^2	100-1000 km^2	100-1000 km^2	10,000-100,000 km^2	100,000-1,000,000 km^2	<1 ha	100,000-1,000,000 km^2	Not applicable	1000-10,000 km^2.

Spatial Distribution of Computations

EM ID em.detail.idHelp ?	EM-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
EM Spatial Distribution em.detail.distributeLumpHelp ?	spatially distributed (in at least some cases)	spatially distributed (in at least some cases) ? Comment: pixel is likely 30m x 30m	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 lumped (in all 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)
Spatial Grain Type em.detail.spGrainTypeHelp ?	area, for pixel or radial feature	area, for pixel or radial feature	other (specify), for irregular (e.g., stream reach, lake basin)	area, for pixel or radial feature	Not applicable	other (specify), for irregular (e.g., stream reach, lake basin)	Not applicable	area, for pixel or radial feature	Not applicable	area, for pixel or radial feature	map scale, for cartographic feature
Spatial Grain Size em.detail.spGrainSizeHelp ?	30 m x 30 m	Not specified	HUC	10 m x 10 m	Not applicable	multiple, individual, irregular sites	Not applicable	3 m x 3 m	Not applicable	user defined	30m

EM Structure and Computation Approach

EM ID em.detail.idHelp ?	EM-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
EM Computational Approach em.detail.emComputationalApproachHelp ?	Analytic	Numeric	Analytic	Analytic	Numeric	Analytic	Numeric	Analytic	Numeric	Numeric	Analytic
EM Determinism em.detail.deterStochHelp ?	deterministic	deterministic	deterministic	deterministic	deterministic	deterministic	deterministic	stochastic	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	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Machine learning

Model Checking Procedures Used

EM ID em.detail.idHelp ?	EM-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
Model Calibration Reported? em.detail.calibrationHelp ?	No	Yes ? Comment: Annual Yield can be calibrated with actual yield based up 10 year average input data though this was an "optional" part of the model. Calibrate with total precipitation and potential evapotranspiration. Before the calibration process is commenced, the modelers suggest performing a sensitivity analysis with the observed runoff data to define the parameters that influence model outputs the most. The calibration can then focus on highly sensitive parameters followed by less sensitive ones.	No	Yes	No	Unclear	No	Not applicable	No	Not applicable	Yes
Model Goodness of Fit Reported? em.detail.goodnessFitHelp ?	No	Not applicable	No	No	No	No	No	Not applicable	No	Not applicable	Yes
Goodness of Fit (metric\| value \| unit) em.detail.goodnessFitValuesHelp ?	None	None	None	None	None	None	None	None	None	None	Accuracy assessment value \| 93.33-96.67 \| % Kappa statistic \| 0.9143-0.9577 \| N/A
Model Operational Validation Reported? em.detail.validationHelp ?	No	No	No	Yes	Yes ? Comment: A validation analysis was carried out running the model using data from 1880 to 2001, and then comparing the output for the adult population with the 2001 published data.	No	No	No	No	Not applicable	Yes
Model Uncertainty Analysis Reported? em.detail.uncertaintyAnalysisHelp ?	No	No	No	No	No	No	No	No	No	Not applicable	Unclear
Model Sensitivity Analysis Reported? em.detail.sensAnalysisHelp ?	No	Not applicable	No	No	No	No	No	No	No	Not applicable	Unclear
Model Sensitivity Analysis Include Interactions? em.detail.interactionConsiderHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	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-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
Asia Indonesia	None	North America U.S. Caribbean Territories	None	None	North America United States Iowa	North America United States Idaho	Europe United Kingdom	North America United States Idaho	None	Asia India

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

EM-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
None	None	None	Tropical Atlantic West Tropical Atlantic Tropical Northwestern Atlantic Eastern Caribbean	Temperate South Africa South Africa Benguela Namaqua	None	None	None	None	None	None

Centroid Lat/Long (Decimal Degree)

EM ID em.detail.idHelp ?	EM-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
Centroid Latitude em.detail.ddLatHelp ?	0	-9999	17.96	17.73	-34.18	42.62	44.06	54.2	44.06	Not applicable	23.95
Centroid Longitude em.detail.ddLongHelp ?	102	-9999	-67.02	-64.77	18.35	-93.84	-114.69	-2.35	-114.69	Not applicable	89.12
Centroid Datum em.detail.datumHelp ?	WGS84	Not applicable	WGS84	WGS84	WGS84	WGS84	WGS84	WGS84	WGS84	Not applicable	other
Centroid Coordinates Status em.detail.coordinateStatusHelp ?	Provided	Not applicable	Estimated	Estimated	Provided	Estimated	Estimated	Provided	Estimated	Not applicable	Provided

Environments and Scales Modeled

EM ID em.detail.idHelp ?	EM-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
EM Environmental Sub-Class em.detail.emEnvironmentalSubclassHelp ?	Inland Wetlands \| Lakes and Ponds \| Forests \| Agroecosystems \| Created Greenspace \| Grasslands \| Scrubland/Shrubland \| Barren	Rivers and Streams	Inland Wetlands \| Forests \| Agroecosystems \| Created Greenspace \| Grasslands \| Scrubland/Shrubland \| Barren	Near Coastal Marine and Estuarine	Near Coastal Marine and Estuarine	Inland Wetlands \| Agroecosystems \| Grasslands	Inland Wetlands	Agroecosystems \| Grasslands	Inland Wetlands	Terrestrial Environment (sub-classes not fully specified)	Terrestrial Environment (sub-classes not fully specified)
Specific Environment Type em.detail.specificEnvTypeHelp ?	104 land use land cover classes	Watershed	Tropical terrestrial	Coral reefs	Rocky coast, mixed coast, sandy coast, rocky inshore, sandy inshore, rocky shelf and unconsolidated shelf	Wetlands buffered by grassland within agroecosystems	created, restored and enhanced wetlands	fertilized grassland (historically hayed)	created, restored and enhanced wetlands	Terrestrial environment sub-classes	Urban city
EM Ecological Scale em.detail.ecoScaleHelp ?	Ecological scale is finer than that of the Environmental Sub-class	Not applicable	Ecological scale is finer than that of the Environmental Sub-class	Ecological scale is 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 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

Scale and taxa of organisms modeled

Scale of differentiation of organisms modeled

EM ID em.detail.idHelp ?	EM-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
EM Organismal Scale em.detail.orgScaleHelp ?	Community	Not applicable	Not applicable	Community	Individual or population, within a species	Individual or population, within a species	Not applicable	Community	Not applicable	Not applicable	Not applicable

Taxonomic level and name of organisms or groups identified

EM-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
None Available	None Available	None Available	None Available	Species West Coast Rock Lobster (Jasus lalandii)	Species Blue-winged teal (Anas discors)	None Available	None Available	None Available	None Available	None Available

EnviroAtlas URL

EM-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
The Watershed Boundary Dataset (WBD)	Average Annual Precipitation, Agricultural water use (million gallons/day), The Watershed Boundary Dataset (WBD)	Total Annual Reduced Nitrogen Deposition, The Watershed Boundary Dataset (WBD), Percent Impervious Area	None Available	Big game hunting recreation demand	Acres of Land Enrolled in the Conservation Reserve Program (CRP)	Total Annual Reduced Nitrogen Deposition, Carbon Storage by Tree Biomass	None Available	Total Annual Reduced Nitrogen Deposition, Carbon Storage by Tree Biomass	Carbon storage by tree biomass (kg/m2), Ecosystem Markets: Imperiled Species and Habitats	GAP Ecological Systems

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-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Atmospheric composition and climate regulation Global climate regulation by reduction of greenhouse gas concentrations	[Ecosystem] Provisioning Materials Water Surface water for non-drinking purposes	[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Soil formation and composition Decomposition and fixing processes	[Ecosystem] Regulation & Maintenance Mediation of flows Liquid flows Flood protection	[Ecosystem] Provisioning Nutrition Biomass Wild animals and their outputs	[Ecosystem] Provisioning Nutrition Biomass Wild animals and their outputs	[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Lifecycle maintenance, habitat and gene pool protection Maintaining nursery populations and habitats Water conditions Chemical condition of freshwaters Mediation of flows Liquid flows Flood protection Hydrological cycle and water flow maintenance Mass flows Mass stabilisation and control of erosion rates Mediation of waste, toxics and other nuisances Mediation by biota Filtration/sequestration/storage/accumulation by micro-organisms, algae, plants, and animals	[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Atmospheric composition and climate regulation Global climate regulation by reduction of greenhouse gas concentrations	[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Lifecycle maintenance, habitat and gene pool protection Maintaining nursery populations and habitats Water conditions Chemical condition of freshwaters Mediation of flows Liquid flows Flood protection Hydrological cycle and water flow maintenance Mass flows Mass stabilisation and control of erosion rates Mediation of waste, toxics and other nuisances Mediation by biota Filtration/sequestration/storage/accumulation by micro-organisms, algae, plants, and animals	[Ecosystem] Provisioning Materials Biomass Fibres and other materials from plants, algae and animals for direct use or processing	[Ecosystem] Provisioning Nutrition Biomass Cultivated crops Energy Biomass-based energy sources Plant-based resources Materials Biomass Fibres and other materials from plants, algae and animals for direct use or processing [Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Lifecycle maintenance, habitat and gene pool protection Maintaining nursery populations and habitats Mediation of flows Liquid flows Hydrological cycle and water flow maintenance Mass flows Mass stabilisation and control of erosion rates Mediation of waste, toxics and other nuisances Mediation by ecosystems Filtration/sequestration/storage/accumulation by ecosystems [Ecosystem] Cultural Spiritual, symbolic and other interactions with biota, ecosystems, and land-/seascapes [environmental settings] Spiritual and/or emblematic Sacred and/or religious Physical and intellectual interactions with biota, ecosystems, and land-/seascapes [environmental settings] Physical and experiential interactions Experiential use of plants, animals and land-/seascapes in different environmental settings

<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-349	EM-368	EM-432	EM-446	EM-541	EM-701	EM-729	EM-735	EM-760	EM-887	EM-979
None	Rivers and Streams (111) Water (3) Liquid water Stock Indicator	Agroecosystems (22) Soil (2) Specific types of soil Quality Indicator	Near Coastal Marine/Estuarine (113) Composite (8) Regulation of extreme events Extreme Event Indicator	Near Coastal Marine/Estuarine (113) Fauna (4) Invertebrates Stock Indicator	Wetlands (12) Fauna (4) Duck Stock Indicator	None	None	None	None	Scrubland/Shrubland (24) Composite (8) Regulation of extreme events Site Indicator Urban/Surburban (27) Composite (8) Presence of environmental class/subclass Site Indicator

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EM Locations, Environments, Ecology

Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])

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

Centroid Lat/Long (Decimal Degree)

Scale of differentiation of organisms modeled

Taxonomic level and name of organisms or groups identified

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)