EcoService Models Library (ESML)
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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
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EM ID
em.detail.idHelp
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EM-598 |
EM-729 |
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EM Short Name
em.detail.shortNameHelp
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DeNitrification-DeComposition simulation (DNDC) v.8.9 flux simulation, Ireland | WESP: Urban Stormwater Treatment, ID, USA |
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EM Full Name
em.detail.fullNameHelp
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DeNitrification-DeComposition simulation of N2O flux Ireland | WESP: Urban Stormwater Treament, ID, USA |
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EM Source or Collection
em.detail.emSourceOrCollectionHelp
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None | None |
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EM Source Document ID
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358 |
393 ?Comment:Additional data came from electronic appendix provided by author Chris Murphy. |
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Document Author
em.detail.documentAuthorHelp
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Abdalla, M., Yeluripati, J., Smith, P., Burke, J., Williams, M. | Murphy, C. and T. Weekley |
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Document Year
em.detail.documentYearHelp
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2010 | 2012 |
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Document Title
em.detail.sourceIdHelp
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Testing DayCent and DNDC model simulations of N2O fluxes and assessing the impacts of climate change on the gas flux and biomass production from a humid pasture | Measuring outcomes of wetland restoration, enhancement, and creation in Idaho-- Assessing potential functions, values, and condition in a watershed context. |
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Document Status
em.detail.statusCategoryHelp
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Peer reviewed and published | Peer reviewed and published |
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Comments on Status
em.detail.commentsOnStatusHelp
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Published journal manuscript | Published report |
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EM ID
em.detail.idHelp
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EM-598 |
EM-729 |
| http://www.dndc.sr.unh.edu | Not applicable | |
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Contact Name
em.detail.contactNameHelp
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M. Abdalla | Chris Murphy |
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Contact Address
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Dept. of Botany, School of Natural Science, Trinity College Dublin, Dublin2, Ireland | Idaho Dept. Fish and Game, Wildlife Bureau, Habitat Section, Boise, ID |
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Contact Email
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abdallm@tcd.ie | chris.murphy@idfg.idaho.gov |
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EM ID
em.detail.idHelp
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EM-598 |
EM-729 |
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Summary Description
em.detail.summaryDescriptionHelp
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Simulation models are one of the approaches used to investigate greenhouse gas emissions and potential effects of global warming on terrestrial ecosystems. DayCent which is the daily time-step version of the CENTURY biogeochemical model, and DNDC (the DeNitrification–DeComposition model) were tested against observed nitrous oxide flux data from a field experiment on cut and extensively grazed pasture located at the Teagasc Oak Park Research Centre, Co. Carlow, Ireland. The soil was classified as a free draining sandy clay loam soil with a pH of 7.3 and a mean organic carbon and nitrogen content at 0–20 cm of 38 and 4.4 g kg−1 dry soil, respectively. The aims of this study were to validate DayCent and DNDC models for estimating N2O emissions from fertilized humid pasture, and to investigate the impacts of future climate change on N2O fluxes and biomass production. Measurements of N2O flux were carried out from November 2003 to November 2004 using static chambers. Three climate scenarios, a baseline of measured climatic data from the weather station at Carlow, and high and low temperature sensitivity scenarios predicted by the Community Climate Change Consortium For Ireland (C4I) based on the Hadley Centre Global Climate Model (HadCM3) and the Intergovernment Panel on Climate Change (IPCC) A1B emission scenario were investigated. DNDC overestimated the measured flux with relative deviations of +132 and +258% due to overestimation of the effects of SOC. DayCent, though requiring some calibration for Irish conditions, simulated N2O fluxes more consistently than did DNDC. | 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. |
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Specific Policy or Decision Context Cited
em.detail.policyDecisionContextHelp
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climate change | None identified |
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Biophysical Context
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Agricultural field, Ann rainfall 824mm, mean air temp 9.4°C | restored, enhanced and created wetlands |
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EM Scenario Drivers
em.detail.scenarioDriverHelp
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fertilization | Sites, function or habitat focus |
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EM ID
em.detail.idHelp
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EM-598 |
EM-729 |
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Method Only, Application of Method or Model Run
em.detail.methodOrAppHelp
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Method + Application | Method + Application (multiple runs exist) View EM Runs |
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New or Pre-existing EM?
em.detail.newOrExistHelp
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Application of existing model | WESP - Urban Stormwater Treatment |
Related EMs (for example, other versions or derivations of this EM) described in ESML
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EM ID
em.detail.idHelp
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EM-598 |
EM-729 |
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Document ID for related EM
em.detail.relatedEmDocumentIdHelp
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None | Doc-390 |
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EM ID for related EM
em.detail.relatedEmEmIdHelp
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EM-593 | EM-718 | EM-734 |
EM Modeling Approach
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EM ID
em.detail.idHelp
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EM-598 |
EM-729 |
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EM Temporal Extent
em.detail.tempExtentHelp
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1961-1990 | 2010-2011 |
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EM Time Dependence
em.detail.timeDependencyHelp
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time-dependent | time-dependent |
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EM Time Reference (Future/Past)
em.detail.futurePastHelp
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both | past time |
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EM Time Continuity
em.detail.continueDiscreteHelp
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discrete | Not applicable |
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EM Temporal Grain Size Value
em.detail.tempGrainSizeHelp
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1 | Not applicable |
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EM Temporal Grain Size Unit
em.detail.tempGrainSizeUnitHelp
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Day | Not applicable |
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EM ID
em.detail.idHelp
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EM-598 |
EM-729 |
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Bounding Type
em.detail.boundingTypeHelp
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Point or points | Multiple unrelated locations (e.g., meta-analysis) |
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Spatial Extent Name
em.detail.extentNameHelp
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Oak Park Research centre | Wetlands in idaho |
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Spatial Extent Area (Magnitude)
em.detail.extentAreaHelp
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1-10 ha | 100,000-1,000,000 km^2 |
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EM ID
em.detail.idHelp
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EM-598 |
EM-729 |
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EM Spatial Distribution
em.detail.distributeLumpHelp
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spatially lumped (in all cases) | spatially lumped (in all cases) |
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Spatial Grain Type
em.detail.spGrainTypeHelp
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Not applicable | Not applicable |
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Spatial Grain Size
em.detail.spGrainSizeHelp
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Not applicable | Not applicable |
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EM ID
em.detail.idHelp
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EM-598 |
EM-729 |
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EM Computational Approach
em.detail.emComputationalApproachHelp
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Numeric | Numeric |
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EM Determinism
em.detail.deterStochHelp
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deterministic | deterministic |
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Statistical Estimation of EM
em.detail.statisticalEstimationHelp
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EM ID
em.detail.idHelp
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EM-598 |
EM-729 |
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Model Calibration Reported?
em.detail.calibrationHelp
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Yes | No |
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Model Goodness of Fit Reported?
em.detail.goodnessFitHelp
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Yes ?Comment:Actual value was not given, just that results were very poor. Simulation results were 258% of observed |
No |
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Goodness of Fit (metric| value | unit)
em.detail.goodnessFitValuesHelp
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None |
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Model Operational Validation Reported?
em.detail.validationHelp
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Yes | No |
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Model Uncertainty Analysis Reported?
em.detail.uncertaintyAnalysisHelp
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No | No |
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Model Sensitivity Analysis Reported?
em.detail.sensAnalysisHelp
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No | No |
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Model Sensitivity Analysis Include Interactions?
em.detail.interactionConsiderHelp
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Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
| EM-598 |
EM-729 |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
| EM-598 |
EM-729 |
| None | None |
Centroid Lat/Long (Decimal Degree)
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EM ID
em.detail.idHelp
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EM-598 |
EM-729 |
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Centroid Latitude
em.detail.ddLatHelp
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52.86 | 44.06 |
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Centroid Longitude
em.detail.ddLongHelp
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6.54 | -114.69 |
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Centroid Datum
em.detail.datumHelp
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None provided | WGS84 |
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Centroid Coordinates Status
em.detail.coordinateStatusHelp
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Provided | Estimated |
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EM ID
em.detail.idHelp
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EM-598 |
EM-729 |
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EM Environmental Sub-Class
em.detail.emEnvironmentalSubclassHelp
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Agroecosystems | Inland Wetlands |
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Specific Environment Type
em.detail.specificEnvTypeHelp
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farm pasture | created, restored and enhanced wetlands |
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EM Ecological Scale
em.detail.ecoScaleHelp
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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
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EM ID
em.detail.idHelp
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EM-598 |
EM-729 |
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EM Organismal Scale
em.detail.orgScaleHelp
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Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
| EM-598 |
EM-729 |
| None Available | None Available |
EnviroAtlas URL
| EM-598 |
EM-729 |
| GAP Ecological Systems, Average Annual Precipitation, Agricultural water use (million gallons/day) | Total Annual Reduced Nitrogen Deposition, Carbon Storage by Tree Biomass |
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-598 |
EM-729 |
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<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-598 |
EM-729 |
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None |
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