{PAGE NAME} | {WEB AREA NAME}

EM Identity and Description

EM Identification (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
EM Short Name em.detail.shortNameHelp ?	Cultural ecosystem services, Bilbao, Spain	Coral taxa and land development, St.Croix, VI, USA	SAV occurrence, St. Louis River, MN/WI, USA	Reef density of P. argus, St. Croix, USVI	Arthropod flower preference, CA, USA	EcoSim II - method	CommunityViz, Albany county, Wyoming
EM Full Name em.detail.fullNameHelp ?	Cultural ecosystem services, Bilbao, Spain	Coral taxa richness and land development, St.Croix, Virgin Islands, USA	Predicting submerged aquatic vegetation occurrence, St. Louis River Estuary, MN & WI, USA	Relative density of Panulirus argus (on reef), St. Croix, USVI	Arthropod flower type preference, California, USA	EcoSim II - method	Wyoming Community Viz TM Partnership Phase I Pilot: Aquifer Protection and Community Viz TM in Albany County, Wyoming.
EM Source or Collection em.detail.emSourceOrCollectionHelp ?	None ? Comment: EU Mapping Studies	US EPA	US EPA	US EPA	None	None	*
EM Source Document ID	191	96	330	335	399	448	479 ? Comment: Published as a report by the University of Wyoming, but no record of peer review.
Document Author em.detail.documentAuthorHelp ?	Casado-Arzuaga, I., Onaindia, M., Madariaga, I. and Verburg P. H.	Oliver, L. M., Lehrter, J. C. and Fisher, W. S.	Ted R. Angradi, Mark S. Pearson, David W. Bolgrien, Brent J. Bellinger, Matthew A. Starry, Carol Reschke	Yee, S. H., Dittmar, J. A., and L. M. Oliver	Lundin, O., Ward, K.L., and N.M. Williams	Walters, C., Pauly, D., Christensen, V., and J.F. Kitchell	Lieske, S. N., Mullen, S., Knapp, M., & Hamerlinck, J. D.
Document Year em.detail.documentYearHelp ?	2013	2011	2013	2014	2018	2000	2003
Document Title em.detail.sourceIdHelp ?	Mapping recreation and aesthetic value of ecosystems in the Bilbao Metropolitan Greenbelt (northern Spain) to support landscape planning	Relating landscape development intensity to coral reef condition in the watersheds of St. Croix, US Virgin Islands	Predicting submerged aquatic vegetation cover and occurrence in a Lake Superior estuary	Comparison of methods for quantifying reef ecosystem services: A case study mapping services for St. Croix, USVI	Indentifying native plants for coordinated hanbitat manegement of arthroppod pollinators, herbivores and natural enemies	Representing density dependent consequences of life history strategies in aquatic ecostems: EcoSim II	Wyoming Community Viz TM Partnership Phase I Pilot: Aquifer Protection and Community Viz TM in Albany County, Wyoming
Document Status em.detail.statusCategoryHelp ?	*	*	*	*	Peer reviewed and published	*	Not peer reviewed but is published (explain in Comment)
Comments on Status em.detail.commentsOnStatusHelp ?	*	*	*	*	Published journal manuscript	*	Published report

Software and Access (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
EM Software Access info Exit em.detail.modelAccessInformationHelp ?	*	*	*	*	Not applicable	https://ecopath.org/downloads/	https://communityviz.com/
Contact Name em.detail.contactNameHelp ?	Izaskun Casado-Arzuaga	Leah Oliver	Ted R. Angradi	Susan H. Yee	Ola Lundin	Carl Walters	Scott Lieske
Contact Address	Plant Biology and Ecology Department, University of the Basque Country UPV/EHU, Campus de Leioa, Barrio Sarriena s/n, 48940 Leioa, Bizkaia, Spain	National Health and Environmental Research Effects Laboratory	U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Mid-Continent Ecology Division, 6201 Congdon Blvd., Duluth, MN 55804, USA	US EPA, Office of Research and Development, NHEERL, Gulf Ecology Division, Gulf Breeze, FL 32561, USA	Department of Ecology, Swedish Univ. of Agricultural Sciences, Uppsala, Sweden	Fisheries Centre, University of British Columbia, Vancouver, British Columbia, British Columbia, Canada, V6T 1Z4	Department of Agricultural & Applied Economics University of Wyoming, Laramie WY 82071
Contact Email	izaskun.casado@ehu.es	leah.oliver@epa.gov	angradi.theodore@epa.gov	yee.susan@epa.gov	ola.lundin@slu.se	c.walters@oceans.ubc.ca	lieske@uwyo.edu

EM Description (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
Summary Description em.detail.summaryDescriptionHelp ?	ABSTRACT "This paper presents a method to quantify cultural ecosystem services (ES) and their spatial distribution in the landscape based on ecological structure and social evaluation approaches. The method aims to provide quantified assessments of ES to support land use planning decisions. A GIS-based approach was used to estimate and map the provision of recreation and aesthetic services supplied by ecosystems in a peri-urban area located in the Basque Country, northern Spain. Data of two different public participation processes (frequency of visits to 25 different sites within the study area and aesthetic value of different landscape units) were used to validate the maps. Three maps were obtained as results: a map showing the provision of recreation services, an aesthetic value map and a map of the correspondences and differences between both services. The data obtained in the participation processes were found useful for the validation of the maps. A weak spatial correlation was found between aesthetic quality and recreation provision services, with an overlap of the highest values for both services only in 7.2 % of the area. A consultation with decision-makers indicated that the results were considered useful to identify areas that can be targeted for improvement of landscape and recreation management."	AUTHOR'S DESCRIPTION: "In this exploratory comparison, stony coral condition was related to watershed LULC and LDI values. We also compared the capacity of other potential human activity indicators to predict coral reef condition using multivariate analysis." (294)	ABSTRACT: “Submerged aquatic vegetation (SAV) provides the biophysical basis for multiple ecosystem services in Great Lakes estuaries. Understanding sources of variation in SAV is necessary for sustainable management of SAV habitat. From data collected using hydroacoustic survey methods, we created predictive models for SAV in the St. Louis River Estuary (SLRE) of western Lake Superior. The dominant SAV species in most areas of the estuary was American wild celery (Vallisneria americana Michx.)…” AUTHOR’S DESCRIPTION: “The SLRE is a Great Lakes “rivermouth” ecosystem as defined by Larson et al. (2013). The 5000-ha estuary forms a section of the state border between Duluth, Minnesota and Superior, Wisconsin…In the SLRE, SAV beds are often patchy, turbidity varies considerably among areas (DeVore, 1978) and over time, and the growing season is short. Given these conditions, hydroacoustic survey methods were the best option for generating the extensive, high resolution data needed for modeling. From late July through mid September in 2011, we surveyed SAV in Allouez Bay, part of Superior Bay, eastern half of St. Louis Bay, and Spirit Lake…We used the measured SAV percent cover at the location immediately previous to each useable record location along each transect as a lag variable to correct for possible serial autocorrelation of model error. SAV percent cover, substrate parameters, corrected depth, and exposure and bed slope data were combined in Arc-GIS...We created logistic regression models for each area of the SLRE to predict the probability of SAV being present at each report location. We created models for the training data set using the Logistic procedure in SAS v.9.1 with step wise elimination (?=0.05). Plots of cover by depth for selected predictor values (Supplementary Information Appendix C) suggested that interactions between depth and other predictors were likely to be significant, and so were included in regression models. We retained the main effect if their interaction terms were significant in the model. We examined the performance of the models using the area under the receiver operating characteristic (AUROC) curve. AUROC is the probability of concordance between random pairs of observations and ranges from 0.5 to 1 (Gönen, 2006). We cross-validated logistic occurrence models for their ability to classify correctly locations in the validation (holdout) dataset and in the Superior Bay dataset… Model performance, as indicated by the area under the receiver operating characteristic (AUROC) curve was >0.8 (Table 3). Assessed accuracy of models (the percent of records where the predicted probability of occurrence and actual SAV presence or absence agreed) for split datasets was 79% for Allouez Bay, 86% for St. Louis Bay, and 78% for Spirit Lake."	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…We broadly consider fisheries production to include harvesting of aquatic organisms as seafood for human consumption (NOAA (National Oceanic and Atmospheric Administration), 2009; Principe et al., 2012), as well as other non-consumptive uses such as live fish or coral for aquariums (Chan and Sadovy, 2000), or shells or skeletons for ornamental art or jewelry (Grigg, 1989; Hourigan, 2008). The density of key commercial fisheries species and the value of finfish can be associated with the relative cover of key benthic habitat types on which they depend (Mumby et al., 2008). For each grid cell, we estimated the contribution of coral reefs to fisheries production as the overall weighted average of relative magnitudes of contribution across habitat types within that grid cell: Relative fisheries production j = ΣiciMij where ci is the fraction of area within each grid cell for each habitat type i (dense, medium dense, or sparse seagrass, mangroves, sand, macroalgae, A. palmata, Montastraea reef, patch reef, and dense or sparse gorgonians),and Mij is the magnitude associated with each habitat for a given metric j: (1) density of the spiny lobster Panulirus argus"	ABSTRACT: " Plant species differed in attractiveness for each arthropod functional group. Floral area of the focal plant species positively affected honeybee, predator, and parasitic wasp attractiveness. Later bloom period was associated with lower numbers of parasitic wasps. Flower type (actinomorphic, composite, or zygomorphic) predicted attractiveness for honeybees, which preferred actinomorphic over composite flowers and for parasitic wasps, which preferred composite flowers over actinomorphic flowers. 4. Across plant species, herbivore, predator, and parasitic wasp abundances were positively correlated, and honeybee abundance correlated negatively to herbivore abundance. 5. Synthesis and applications. We use data from our common garden experiment to inform evidence-based selection of plants that support pollinators and natural enemies without enhancing potential pests. We recommend selecting plant species with a high floral area per ground area unit, as this metric predicts the abundances of several groups of beneficial arthropods. Multiple correlations between functionally important arthropod groups across plant species stress the importance of a multifunctional approach to arthropod habitat management. " Changes in arthropod abundance were estimated for flower type (entered as separate runs); Actinomorphic, Composite, Zygomorphic. 43 plant species evaluated included Amsinckia intermedia, Calandrinia menziesii, Nemophila maculata, Nemophila menziesii, Phacelia ciliata, Achillea millefolium, Collinsia heterophylla, Fagopyrum esculentum, Lasthenia fremontii, Lasthenia glabrata, Limnanthes alba, Lupinus microcarpus densiflorus, Lupinus succelentus, Phacelia californica, Phacelia campanularia, Phacelia tanacetifolia, Salvia columbariae, Sphaeralcea ambigua, Trifolium fucatum, Trifolium gracilentum, Antirrhinum conutum, Clarkia purpurea, Clarkia unguiculata, Clarkia williamsonii, Eriophyllum lanatum, Eschscholzia californica, Monardella villosa, Scrophularia californica, Asclepia eriocarpa, Asclepia fascicularis, Camissoniopsis Cheiranthifolia, Eriogonum fasciculatum, Gilia capitata, Grindelia camporum, Helianthus annuus, Lupinus formosus, Malacothrix saxatilis, Oenothera elata, Helianthus bolanderi, Helianthus californicus, Madia elegans, Trichostema lanceolatum, Heterotheca grandiflora."	ABSTRACT: " EcoSim II uses results from the Ecopath procedure for trophic mass-balance analysis to define biomass dynamics models for predicting temporal change in exploited ecosystems. Key populations can be repre- sented in further detail by using delay-difference models to account for both biomass and numbers dynamics. A major problem revealed by linking the population and biomass dynamics models is in representation of population responses to changes in food supply; simple proportional growth and reproductive responses lead to unrealistic predic- tions of changes in mean body size with changes in fishing mortality. EcoSim II allows users to specify life history mechanisms to avoid such unrealistic predictions: animals may translate changes in feed- ing rate into changes in reproductive rather than growth rates, or they may translate changes in food availability into changes in foraging time that in turn affects predation risk. These options, along with model relationships for limits on prey availabil- ity caused by predation avoidance tactics, tend to cause strong compensatory responses in modeled populations. It is likely that such compensatory responses are responsible for our inability to find obvious correlations between interacting trophic components in fisheries time-series data. But Eco- sim II does not just predict strong compensatory responses: it also suggests that large piscivores may be vulnerable to delayed recruitment collapses caused by increases in prey species that are in turn competitors/predators of juvenile piscivores "	The Wyoming Community VizTM Partnership was established in 2001 to promote the use of geographic information system-based planning support systems and related decision support technologies in community land-use planning and economic development activities in the State of Wyoming. Partnership members include several state agencies, local governments and several nongovernment organizations. Partnership coordination is provided by the Wyoming Rural Development Council. Research and technical support is coordinated by the Wyoming Geographic Information Science Center’s Spatial Decision Support System Research Program at the University of Wyoming. In June 2002, the Partnership initiated a three-phase plan to promote Community VizTM based planning support systems in Wyoming. Phase I of the Partnership plan was a “proof of concept” pilot project set in Albany County in southeastern Wyoming. The goal of the project was to demonstrate the application of Community VizTM to a Wyoming-specific issue (in this case, aquifer protection) and to determine potential challenges for broader adoption in terms of data requirements, computing infrastructure and technological expertise. The results of the Phase I pilot project are detailed in this report. Efforts are currently underway to secure funding for Phase II of the plan, which expands the use of Community VizTM into four additional Wyoming communities. Specific Phase II objectives are to expand the type and number of issues addressed by Community VizTM and increase the use of Community VizTM in the planning process. As a part of Phase II the Partnership will create a technical assistance network aimed at assisting communities with the technical challenges in applying the software to their planning issues. The third phase will expand the program to more communities in the state, maintain the technical assistance network, and monitor the impact of Community VizTM on the planning process.
Specific Policy or Decision Context Cited em.detail.policyDecisionContextHelp ?	Land management, ecosystem management, response to EU 2020 Biodiversity Strategy	Not applicable	None identified	None identified	None reported	None	None provided
Biophysical Context	Northern Spain; Bizkaia region	nearshore; <1.5 km offshore; <12 m depth	submerged aquatic vegetation	No additional description provided	Mediteranean climate	None, Ocean ecosystems	Groundwater recharge area, City of Laramie
EM Scenario Drivers em.detail.scenarioDriverHelp ?	No scenarios presented	Not applicable	No scenarios presented	No scenarios presented	Arthropod groups	N/A	Continuation of trends

EM Relationship to Other EMs or Applications

EM ID em.detail.idHelp ?	New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
Method Only, Application of Method or Model Run em.detail.methodOrAppHelp ?	Method + Application	Method + Application	Method + Application	Method + Application	Method + Application (multiple runs exist)	Method Only	Model Run Associated with a Specific EM Application
New or Pre-existing EM? em.detail.newOrExistHelp ?	New or revised model	New or revised model	New or revised model	Application of existing model	New or revised model	New or revised model	Continuation of trends

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

EM ID em.detail.idHelp ?	New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
Document ID for related EM em.detail.relatedEmDocumentIdHelp ?	None	None	None	None	None	None	Doc-473
EM ID for related EM em.detail.relatedEmEmIdHelp ?	None	None	None	None	None	EM-1055	None

EM Modeling Approach

EM Relationship to Time (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
EM Temporal Extent em.detail.tempExtentHelp ?	2000 - 2007	2006-2007	2010 - 2012	2006-2007, 2010	2015-2016	Not applicable	2050
EM Time Dependence em.detail.timeDependencyHelp ?	*	*	*	*	time-stationary	time-dependent	*
EM Time Reference (Future/Past) em.detail.futurePastHelp ?	*	*	*	*	Not applicable	both	*
EM Time Continuity em.detail.continueDiscreteHelp ?	*	*	*	*	Not applicable	discrete ? Comment: Modeller dependent	*
EM Temporal Grain Size Value em.detail.tempGrainSizeHelp ?	*	*	*	*	Not applicable	1	*
EM Temporal Grain Size Unit em.detail.tempGrainSizeUnitHelp ?	*	*	*	*	Not applicable	Day	*

EM spatial extent (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
Bounding Type em.detail.boundingTypeHelp ?	Geopolitical	Physiographic or Ecological	Physiographic or ecological	Physiographic or ecological	Point or points	Other	Watershed/Catchment/HUC
Spatial Extent Name em.detail.extentNameHelp ?	Bilbao Metropolitan Greenbelt	St.Croix, U.S. Virgin Islands	St. Louis River Estuary	Coastal zone surrounding St. Croix	Harry Laidlaw Jr. Honey Bee Research facility	Not applicable	Laramie City's aquifer protection area
Spatial Extent Area (Magnitude) em.detail.extentAreaHelp ?	100-1000 km^2	10-100 km^2	10-100 km^2	100-1000 km^2	<1 ha	Not applicable	10-100 km^2

Spatial Distribution of Computations (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
EM Spatial Distribution em.detail.distributeLumpHelp ?	spatially distributed (in at least some cases)	*	spatially distributed (in at least some cases) ? Comment: BH: Each individual transect?s data was parceled into location reports, and that each report?s ?quadrat? area was dependent upon the angle of the hydroacoustic sampling beam. The spatial grain is 0.07 m^2, 0.20 m^2 and 0.70 m^2 for depths of 1 meter, 2 meters and 3 meters, respectively.	spatially distributed (in at least some cases)	spatially lumped (in all cases)	*	*
Spatial Grain Type em.detail.spGrainTypeHelp ?	area, for pixel or radial feature	*	area, for pixel or radial feature	area, for pixel or radial feature	Not applicable	*	*
Spatial Grain Size em.detail.spGrainSizeHelp ?	2 m x 2 m	*	0.07 m^2 to 0.70 m^2	10 m x 10 m	Not applicable	*	*

EM Structure and Computation Approach (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
EM Computational Approach em.detail.emComputationalApproachHelp ?	Analytic	Analytic	Analytic	Analytic	Numeric	Analytic	*
EM Determinism em.detail.deterStochHelp ?	*	*	*	*	deterministic	*	*
Statistical Estimation of EM em.detail.statisticalEstimationHelp ?	None	*	*	*	Conventional (frequentist) statistics	*	*

Model Checking Procedures Used (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
Model Calibration Reported? em.detail.calibrationHelp ?	No	Yes	Yes	Yes	Not applicable	No	Unclear
Model Goodness of Fit Reported? em.detail.goodnessFitHelp ?	No	Yes	Yes	No	Not applicable	No	No
Goodness of Fit (metric\| value \| unit) em.detail.goodnessFitValuesHelp ?	*	R squared (taxa richness) \| 0.74 \| Not applicable p-value \| 0.0020 \| unitless	p-value \| <0.001 \| unitless Nagelkerke r2 \| 0.30-0.62 \| unitless	*	None	*	*
Model Operational Validation Reported? em.detail.validationHelp ?	Yes	No	Yes	Yes	Not applicable	*	Unclear
Model Uncertainty Analysis Reported? em.detail.uncertaintyAnalysisHelp ?	*	Yes	*	*	No	Not applicable	Unclear
Model Sensitivity Analysis Reported? em.detail.sensAnalysisHelp ?	*	*	*	*	No	Not applicable	Unclear
Model Sensitivity Analysis Include Interactions? em.detail.interactionConsiderHelp ?	*	*	*	*	Not applicable	*	*

EM Locations, Environments, Ecology

Location of EM Application (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

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

New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
Europe Spain	*	North America United States Minnesota Wisconsin	*	North America United States California	*	North America United States Wyoming

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

New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
*	Tropical Atlantic West Tropical Atlantic Tropical Southwestern Atlantic	*	Tropical Atlantic West Tropical Atlantic Tropical Northwestern Atlantic Eastern Caribbean	None	*	*

Centroid Lat/Long (Decimal Degree)

EM ID em.detail.idHelp ?	New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
Centroid Latitude em.detail.ddLatHelp ?	43.25	17.75	46.72	17.73	38.54	Not applicable	41.31
Centroid Longitude em.detail.ddLongHelp ?	-2.92	-64.75	-96.13	-64.77	-121.79	Not applicable	-105.46
Centroid Datum em.detail.datumHelp ?	*	NAD83	*	*	WGS84	Not applicable	*
Centroid Coordinates Status em.detail.coordinateStatusHelp ?	*	Estimated	Estimated	Estimated	Provided	Not applicable	Estimated

Environments and Scales Modeled (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
EM Environmental Sub-Class em.detail.emEnvironmentalSubclassHelp ?	Aquatic Environment (sub-classes not fully specified) \| Rivers and Streams \| Near Coastal Marine and Estuarine \| Terrestrial Environment (sub-classes not fully specified) \| Forests \| Agroecosystems \| Created Greenspace \| Grasslands \| Scrubland/Shrubland	Near Coastal Marine and Estuarine	Aquatic Environment (sub-classes not fully specified) \| Rivers and Streams \| Inland Wetlands \| Lakes and Ponds	Near Coastal Marine and Estuarine	Agroecosystems	Open Ocean and Seas	Ground Water \| Terrestrial Environment (sub-classes not fully specified)
Specific Environment Type em.detail.specificEnvTypeHelp ?	none	stony coral reef	Freshwater estuarine system	Coral reefs	Agricultural fields	Pelagic	watershed
EM Ecological Scale em.detail.ecoScaleHelp ?	Ecological scale is finer than that of the Environmental Sub-class	Ecological scale is finer than that of the Environmental Sub-class	*	Ecological scale is finer than that of the Environmental Sub-class	Ecological scale corresponds to the Environmental Sub-class	*	*

Organisms modeled (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

Scale of differentiation of organisms modeled

EM ID em.detail.idHelp ?	New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
EM Organismal Scale em.detail.orgScaleHelp ?	Not applicable	*	Not applicable	Species	Guild or Assemblage	Other (Comment) ? Comment: Varied levels of taxonomic order	Not applicable

Taxonomic level and name of organisms or groups identified

New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
*	Genus Acropora Porites spp. Diploria spp. Species Mycetophylia lamarckiana Mycetophylia ferox Montastrea cavernosa Dichocoenia stokesii Meandrina meandrites Agaricia tenuifolia Agaricia fragilis Montastrea annularis Agaricia agaricites Dendrogyra cylindricus Millepora complanata Montastrea faveolata Porites astreoides Montastrea franksii	*	Species Panulirus argus	other Honey bees Predators Wild bees Herbivores Parasitic wasps	other Whiting shrimp Whales Seals Cod Phytoplankton Mackerel Benthos Zooplankton Anchovy	*

EnviroAtlas URL

New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
Percent IUCN Status II, Percent GAP Status 1 & 2	None Available	Average Annual Precipitation	None Available	GAP Ecological Systems	Big game hunting recreation demand	Dasymetric Allocation of Population, Total Annual Reduced Nitrogen Deposition, Employment Rate

EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system

* Note that run information is shown only where run data differ from the "parent" entry shown at left

CICES v 4.3 - Common International Classification of Ecosystem Services (Section > Division > Group > Class)

New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
[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 Experiential use of plants, animals and land-/seascapes in different environmental settings Intellectual and representative interactions Aesthetic	[Non-ecosystem] Regulation & Maintenance by natural physical structures and processes Maintenance of physical, chemical, abiotic conditions By natural chemical and physical processes Not applicable	[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Lifecycle maintenance, habitat and gene pool protection Maintaining nursery populations and habitats	[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 Pollination and seed dispersal	[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	[Non-ecosystem] Regulation & Maintenance by natural physical structures and processes Mediation of waste, toxics and other nuisances By natural chemical and physical processes Not applicable [Ecosystem] Provisioning Materials Water Ground water for non-drinking purposes [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 Intellectual and representative interactions Aesthetic

National Ecosystem Services Classification System (NESCS) Plus

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

New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
Near Coastal Marine/Estuarine (113) Composite (8) Presence of environmental class/subclass Site Characteristic Indicator Scapes: views, sounds and scents of land, sea, sky or a combination Site Characteristic Indicator Forests (21) Composite (8) Presence of environmental class/subclass Site Characteristic Indicator Scapes: views, sounds and scents of land, sea, sky or a combination Site Characteristic Indicator Grasslands (23) Composite (8) Presence of environmental class/subclass Site Characteristic Indicator Scapes: views, sounds and scents of land, sea, sky or a combination Site Characteristic Indicator Scrubland/Shrubland (24) Composite (8) Presence of environmental class/subclass Site Characteristic Indicator Scapes: views, sounds and scents of land, sea, sky or a combination Site Characteristic Indicator	Near Coastal Marine/Estuarine (113) Fauna (4) Invertebrates Quality Indicator	*	Near Coastal Marine/Estuarine (113) Fauna (4) Fish Stock Indicator	Agroecosystems (22) Fauna (4) Pollinators Stock Indicator	Open Oceans and Seas (114) Fauna (4) Fish Flow Indicator	Groundwater Water (3) Liquid water Flow Indicator

EM Variable Names (and Units)

* Note that for runs, variable name is displayed only where data for that variable differed by run AND those differences were reported in the source document. Where differences occurred but were not reported, the variable is not listed. Click on variable name to view details.

To view run information for variables, select any variable below or view run data for all variables.

Predictor

EM ID em.detail.idHelp ?	New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
Driving Variables (and Units) em.detail.drivingVariableHelp ?	Climbing sites mapped location (Not applicable) Coastline mapped location (Not applicable) Cycling paths mapped location (Not applicable) Density of mountain summits (km^-2) Elevation (m) Land use/land cover class (Not applicable) Natural protected areas, mapped location (Not applicable) Perceived value of different landscape units (Not applicable) Quality of bathing water (Not applicable) Recreational areas, mapped location (Not applicable) Routes of geological interest (Not applicable)	Land development intensity index (LDI) (Not applicable) Percent of land use classes in watersheds with a land development intensity index =1.0 (%) Station depth (meters)	Bed slope (%) Depth (water) (m) Directional fetch distance (km) Directional mean monthly wind velocity (Not reported) Directional percent frequency (wind) (%) Fractal dimension (bed) (unitless) Lag SAV presence/absence (Not applicable)	Habitat type class (Not applicable)	None	Adult class (Not applicable) Adult food consumption (Not reported) Biomass immigration rate (Not reported) Emigration rate (Not reported) Fishing mortality rate (Not reported) Fleet size dynamics (unitless) Group type (Not applicable) Juvenile body weight (Not reported) Juvenile class (unitless) Net growth efficiency (Not reported) Non predation mortality/metabolic rate (Not reported) Number of adults (No.) Number of juveniles age a (No.) Number of juveniles at age 0 produced at month t (No.) Number of juveniles at the start of month (No.) Predator biomass j (Not reported) Predator effective search rate (unitless) Prey biomass I (Not reported) Total food consumption by juveniles (Not reported)	Albany county study area boundary (Not reported) City annual budget data ($) Common land use list (Not reported) Distances from residential parcels to recreational trail access (miles) Existing development (Not reported) Existing land use or zoning data (Not reported) Guidelines for future land use/zoning (Not reported) Number of vehicle trips taken (trips) Population projections (Not reported) Property, sales, and lodging tax data ($) Proportion of land development to open space seen from observation points (NA) Roads/infrastructure (Not reported) Species distribution GIS data (Not reported) Topography (Not reported) Vehicle miles traveled (miles) Water consumption data (millions of gallons) Water quality data (nitrate levels) (ppm)
Constant or Factor Variables (and Units) em.detail.constantFactorVariableHelp ?	None	Coefficient on percent of land use classes with a LDI = 1.0 (Not applicable) Coefficient on station depth (Not applicable)	Coefficient on bed slope (unitless) Coefficient on depth (unitless) Coefficient on depth x REI (unitless) Coefficient on depth x bed slope (unitless) Coefficient on depth x fractal dimension (unitless) Coefficient on fractal dimension (bed) (unitless) Coefficient on lag SAV P/A (unitless) Coefficient on relative exposure index (wind) (unitless) Intercept (unitless)	Relative magnitude of density of Panulirus argus for each habitat type (Not applicable)	Flower type (Not applicable)	Age at graduation to the adult pool (months) Density dependent catchability (unitless) Feeding time adjust rate [0,1] (unitless) Fraction of other mortality sensitive to changes in feeding time (unitless) Juvenile growth efficiency (unitless) Juvenile growth rate ( not reported) Maximum relative Production/Biomass (P/B) (unitless) Maximum relative feeding time (Not reported) Predator effect on feeding time [0,1] (unitless) Prey vulnerability parameter 1 (unitless) Prey vulnerability parameter 2 (unitless) QBmax/QBo (for handing time) [>1] (unitless) Slope (metabolism) (Not reported) Switching power parameter [0,2] (unitless) von Bertalanffy growth parameter (unitless)	*

Intermediate

EM ID em.detail.idHelp ?	New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
Intermediate (Computed) Variables (and Units) em.detail.intermediateVariableHelp ?	None	None	Relative exposure index (wind) (unitless)	Fraction of area within each grid cell for each habitat type (%)	None	Adult biomass (kg) Total mortality rate of adult pool (Not reported) Total mortality rate of juvenile pool (not reported) Trophic flow (biomass/time)	*

Response

EM ID em.detail.idHelp ?	New or revised model	New or revised model	New or revised model	Application of existing model	EM-779	New or revised model	Continuation of trends
Observed Response Variables (and Units) em.detail.observedResponseHelp ?	None	Coral taxa richness (No. taxa m^-2)	Submerged aquatic vegetation (SAV) occurrence (%)	None	Herbivores (No. ind./30 sec.) Honey bees (No. ind./60 sec.) Parasitic wasps (No. ind./30 sec.) Predators (No. ind./30 sec.) Wild bees (No. ind./60 sec.)	None	*
Computed Response Variables (and Units) em.detail.computedResponseHelp ?	Aesthetic quality of the landscape (Not applicable) Recreation provision index (Not applicable)	None	Submerged aquatic vegetation (SAV) probability (%)	Relative density of Panulirus argus (unitless)	None	Biomass change rate (kg/time)	Cost of community services (millions of dollars) Local tax revenues (millions of dollars) Quantity of water (millions of gallons) Recreation access (Miles to trail) Riparian area impacted (Acres) Traffic impacts (Vehicle miles traveled) Visual impact (Not reported) Water quality (nitrate levels) (ppm) Wildlife habitat (acres)

US EPA

EcoService Models Library (ESML)

View Runs

: Arthropod flower type preference, California, USA (EM-779)

EM Identity and Description

Comment:

Comment:

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

EM Modeling Approach

Comment:

Comment:

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

Comment:

Taxonomic level and name of organisms or groups identified

EnviroAtlas URL

EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system

* Note that run information is shown only where run data differ from the "parent" entry shown at left

CICES v 4.3 - Common International Classification of Ecosystem Services (Section > Division > Group > Class)

National Ecosystem Services Classification System (NESCS) Plus

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

EM Variable Names (and Units)

* Note that for runs, variable name is displayed only where data for that variable differed by run AND those differences were reported in the source document. Where differences occurred but were not reported, the variable is not listed. Click on variable name to view details.

Predictor

Intermediate

Response