EcoService Models Library (ESML)
loading
Compare EMs
Which comparison is best for me?EM Variables by Variable Role
One quick way to compare ecological models (EMs) is by comparing their variables. Predictor variables show what kinds of influences a model is able to account for, and what kinds of data it requires. Response variables show what information a model is capable of estimating.
This first comparison shows the names (and units) of each EM’s variables, side-by-side, sorted by variable role. Variable roles in ESML are as follows:
- Predictor Variables
- Time- or Space-Varying Variables
- Constants and Parameters
- Intermediate (Computed) Variables
- Response Variables
- Computed Response Variables
- Measured Response Variables
EM Variables by Category
A second way to use variables to compare EMs is by focusing on the kind of information each variable represents. The top-level categories in the ESML Variable Classification Hierarchy are as follows:
- Policy Regarding Use or Management of Ecosystem Resources
- Land Surface (or Water Body Bed) Cover, Use or Substrate
- Human Demographic Data
- Human-Produced Stressor or Enhancer of Ecosystem Goods and Services Production
- Ecosystem Attributes and Potential Supply of Ecosystem Goods and Services
- Non-monetary Indicators of Human Demand, Use or Benefit of Ecosystem Goods and Services
- Monetary Values
Besides understanding model similarities, sorting the variables for each EM by these 7 categories makes it easier to see if the compared models can be linked using similar variables. For example, if one model estimates an ecosystem attribute (in Category 5), such as water clarity, as a response variable, and a second model uses a similar attribute (also in Category 5) as a predictor of recreational use, the two models can potentially be used in tandem. This comparison makes it easier to spot potential model linkages.
All EM Descriptors
This selection allows a more detailed comparison of EMs by model characteristics other than their variables. The 50-or-so EM descriptors for each model are presented, side-by-side, in the following categories:
- EM Identity and Description
- EM Modeling Approach
- EM Locations, Environments, Ecology
- EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system
EM Descriptors by Modeling Concepts
This feature guides the user through the use of the following seven concepts for comparing and selecting EMs:
- Conceptual Model
- Modeling Objective
- Modeling Context
- Potential for Model Linkage
- Feasibility of Model Use
- Model Certainty
- Model Structural Information
Though presented separately, these concepts are interdependent, and information presented under one concept may have relevance to other concepts as well.
EM Identity and Description
EM ID
em.detail.idHelp
?
|
EM-103 | EM-130 |
EM Short Name
em.detail.shortNameHelp
?
|
Birds in estuary habitats, Yaquina Estuary, WA, USA | KINEROS2, River Ravna watershed, Bulgaria |
EM Full Name
em.detail.fullNameHelp
?
|
Bird use of estuarine habitats, Yaquina Estuary, WA, USA | KINEROS (Kinematic runoff and erosion model) v2, River Ravna watershed,Bulgaria |
EM Source or Collection
em.detail.emSourceOrCollectionHelp
?
|
US EPA | EU Biodiversity Action 5 |
EM Source Document ID
|
275 |
248 ?Comment:Document 277 is also a source document for this EM |
Document Author
em.detail.documentAuthorHelp
?
|
Frazier, M. R., Lamberson, J. O. and Nelson, W. G. | Nedkov, S., Burkhard, B. |
Document Year
em.detail.documentYearHelp
?
|
2014 | 2012 |
Document Title
em.detail.sourceIdHelp
?
|
Intertidal habitat utilization patterns of birds in a Northeast Pacific estuary | Flood regulating ecosystem services - Mapping supply and demand, in the Etropole municipality, Bulgaria |
Document Status
em.detail.statusCategoryHelp
?
|
Peer reviewed and published | Peer reviewed and published |
Comments on Status
em.detail.commentsOnStatusHelp
?
|
Published journal manuscript | Published journal manuscript |
EM ID
em.detail.idHelp
?
|
EM-103 | EM-130 |
Not applicable | http://www.tucson.ars.ag.gov/agwa/ | |
Contact Name
em.detail.contactNameHelp
?
|
M. R. Frazier ?Comment:Present address: M. R. Frazier National Center for Ecological Analysis and Synthesis, 735 State St. Suite 300, Santa Barbara, CA 93101, USA |
David C. Goodrich |
Contact Address
|
Western Ecology Division, Office of Research and Development, U.S. Environmental Protection Agency, Pacific coastal Ecology Branch, 2111 SE marine Science Drive, Newport, OR 97365 | USDA - ARS Southwest Watershed Research Center, 2000 E. Allen Rd., Tucson, AZ 85719 |
Contact Email
|
frazier@nceas.ucsb.edu | agwa@tucson.ars.ag.gov |
EM ID
em.detail.idHelp
?
|
EM-103 | EM-130 |
Summary Description
em.detail.summaryDescriptionHelp
?
|
AUTHOR'S DESCRIPTION: "To describe bird utilization patterns of intertidal habitats within Yaquina estuary, Oregon, we conducted censuses to obtain bird species and abundance data for the five dominant estuarine intertidal habitats: Zostera marina (eelgrass), Upogebia (mud shrimp)/ mudflat, Neotrypaea (ghost shrimp)/sandflat, Zostera japonica (Japanese eelgrass), and low marsh. EPFs were developed for the following metrics of bird use: standardized species richness; Shannon diversity; and density for the following four groups: all birds, all birds excluding gulls, waterfowl (ducks and geese), and shorebirds." | ABSTRACT: "Floods exert significant pressure on human societies. Assessments of an ecosystem’s capacity to regulate and to prevent floods relative to human demands for flood regulating ecosystem services can provide important information for environmental management. In this study, the capacities of different ecosystems to regulate floods were assessed through investigations of water retention functions of the vegetation and soil cover. The use of the catchment based hydrologic model KINEROS and the GIS AGWA tool provided data about peak rivers’ flows and the capability of different land cover types to “capture” and regulate some parts of the water." AUTHOR'S DESCRIPTION: "KINEROS is a distributed, physically based, event model describing the processes of interception, dynamic infiltration, surface runoff and erosion from watersheds characterized by predominantly overland flow. The watershed is conceptualized as a cascade and the channels, over which the flow is routed in a top–down approach, are using a finite difference solution of the one-dimensional kinematic wave equations (Semmens et al., 2005). Rainfall excess, which leads to runoff, is defined as the difference between precipitation amount and interception and infiltration depth. The rate at which infiltration occurs is not constant but depends on the rainfall rate and the accumulated infiltration amount, or the available moisture condition of the soil. The AGWA tool is a multipurpose hydrologic analysis system addressed to: (1) provide a simple, direct and repeatable method for hydrologic modeling; (2) use basic, attainable GIS data; (3) be compatible with other geospatial basin-based environmental analysis software; and (4) be useful for scenario development and alternative future simulation work at multiple scales (Miller et al., 2002). AGWA provides the functionality to conduct the processes of modeling and assessment for…KINEROS." |
Specific Policy or Decision Context Cited
em.detail.policyDecisionContextHelp
?
|
None identified | None identified |
Biophysical Context
|
Estuarine intertidal, eelgrass, mudflat, sandflat and low marsh | Average elevation is 914 m. The mean annual temperatures gradually decrease from 9.5 to 2 degrees celcius as the elevation increases. The annual precipitation varies from 750 to 800 mm in the northern part to 1100 mm at the highest part of the mountains. Extreme preipitation is intensive and most often concentrated in certain parts of the catchment areas. Soils are represented by 5 main soil types - Cambisols, Rankers, Lithosols, Luvisols, ans Eutric Fluvisols. Most of the forest is deciduous, represented mainly by beech and hornbeam oak. |
EM Scenario Drivers
em.detail.scenarioDriverHelp
?
|
No scenarios presented | No scenarios presented |
EM ID
em.detail.idHelp
?
|
EM-103 | EM-130 |
Method Only, Application of Method or Model Run
em.detail.methodOrAppHelp
?
|
Method + Application | Method + Application |
New or Pre-existing EM?
em.detail.newOrExistHelp
?
|
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-103 | EM-130 |
Document ID for related EM
em.detail.relatedEmDocumentIdHelp
?
|
None |
Doc-277 | Doc-294 | Doc-249 | Doc-250 ?Comment:Document 277 is also a source document for this EM |
EM ID for related EM
em.detail.relatedEmEmIdHelp
?
|
None | EM-132 | EM-133 |
EM Modeling Approach
EM ID
em.detail.idHelp
?
|
EM-103 | EM-130 |
EM Temporal Extent
em.detail.tempExtentHelp
?
|
December 2007 - November 2008 | Not reported |
EM Time Dependence
em.detail.timeDependencyHelp
?
|
time-stationary | time-dependent |
EM Time Reference (Future/Past)
em.detail.futurePastHelp
?
|
Not applicable | future time |
EM Time Continuity
em.detail.continueDiscreteHelp
?
|
Not applicable | discrete |
EM Temporal Grain Size Value
em.detail.tempGrainSizeHelp
?
|
Not applicable | Not reported |
EM Temporal Grain Size Unit
em.detail.tempGrainSizeUnitHelp
?
|
Not applicable | Not reported |
EM ID
em.detail.idHelp
?
|
EM-103 | EM-130 |
Bounding Type
em.detail.boundingTypeHelp
?
|
Physiographic or ecological | Watershed/Catchment/HUC |
Spatial Extent Name
em.detail.extentNameHelp
?
|
Yaquina Estuary (intertidal), Oregon, USA | River Ravna watershed |
Spatial Extent Area (Magnitude)
em.detail.extentAreaHelp
?
|
1-10 km^2 | 10-100 km^2 |
EM ID
em.detail.idHelp
?
|
EM-103 | EM-130 |
EM Spatial Distribution
em.detail.distributeLumpHelp
?
|
spatially distributed (in at least some cases) | spatially distributed (in at least some cases) |
Spatial Grain Type
em.detail.spGrainTypeHelp
?
|
other (habitat type) | area, for pixel or radial feature |
Spatial Grain Size
em.detail.spGrainSizeHelp
?
|
0.87-104.29 ha | 25 m x 25 m |
EM ID
em.detail.idHelp
?
|
EM-103 | EM-130 |
EM Computational Approach
em.detail.emComputationalApproachHelp
?
|
Analytic | Numeric |
EM Determinism
em.detail.deterStochHelp
?
|
deterministic | deterministic |
Statistical Estimation of EM
em.detail.statisticalEstimationHelp
?
|
|
|
EM ID
em.detail.idHelp
?
|
EM-103 | EM-130 |
Model Calibration Reported?
em.detail.calibrationHelp
?
|
Unclear | Yes |
Model Goodness of Fit Reported?
em.detail.goodnessFitHelp
?
|
No | No |
Goodness of Fit (metric| value | unit)
em.detail.goodnessFitValuesHelp
?
|
None | None |
Model Operational Validation Reported?
em.detail.validationHelp
?
|
No | No |
Model Uncertainty Analysis Reported?
em.detail.uncertaintyAnalysisHelp
?
|
No | No |
Model Sensitivity Analysis Reported?
em.detail.sensAnalysisHelp
?
|
No | No |
Model Sensitivity Analysis Include Interactions?
em.detail.interactionConsiderHelp
?
|
Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-103 | EM-130 |
|
|
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-103 | EM-130 |
|
None |
Centroid Lat/Long (Decimal Degree)
EM ID
em.detail.idHelp
?
|
EM-103 | EM-130 |
Centroid Latitude
em.detail.ddLatHelp
?
|
44.62 | 42.8 |
Centroid Longitude
em.detail.ddLongHelp
?
|
-124.06 | 24 |
Centroid Datum
em.detail.datumHelp
?
|
None provided | WGS84 |
Centroid Coordinates Status
em.detail.coordinateStatusHelp
?
|
Provided | Estimated |
EM ID
em.detail.idHelp
?
|
EM-103 | EM-130 |
EM Environmental Sub-Class
em.detail.emEnvironmentalSubclassHelp
?
|
Near Coastal Marine and Estuarine | Rivers and Streams | Terrestrial Environment (sub-classes not fully specified) | Forests |
Specific Environment Type
em.detail.specificEnvTypeHelp
?
|
Estuarine intertidal | Primarily forested 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 |
Scale of differentiation of organisms modeled
EM ID
em.detail.idHelp
?
|
EM-103 | EM-130 |
EM Organismal Scale
em.detail.orgScaleHelp
?
|
Guild or Assemblage | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-103 | EM-130 |
|
None Available |
EnviroAtlas URL
EM-103 | EM-130 |
None Available | The National Hydrography Dataset (NHD), Average Annual Precipitation, Percent Impervious Area |
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-103 | EM-130 |
|
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-103 | EM-130 |
|
None |