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
EM ID
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EM-466 |
EM-605 ![]() |
EM Short Name
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Yasso 15 - soil carbon model | VELMA v2.0, Ohio, USA |
EM Full Name
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Yasso 15 - soil carbon | Visualizing Ecosystems for Land Management Assessments (VELMA) v2.0, Shayler Crossing watershed, Ohio, USA |
EM Source or Collection
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None | US EPA |
EM Source Document ID
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342 ?Comment:Webpage pdf users manual for model. |
359 ?Comment:Document #366 is a supporting document for this EM. McKane et al. 2014, VELMA Version 2.0 User Manual and Technical Documentation. |
Document Author
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Repo, A., Jarvenpaa, M., Kollin, J., Rasinmaki, J. and Liski, J. | Hoghooghi, N., H. E. Golden, B. P. Bledsoe, B. L. Barnhart, A. F. Brookes, K. S. Djang, J. J. Halama, R. B. McKane, C. T. Nietch, and P. P. Pettus |
Document Year
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2016 | 2018 |
Document Title
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Yasso 15 graphical user-interface manual | Cumulative effects of low impact development on watershed hydrology in a mixed land-cover system |
Document Status
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Other or unclear (explain in Comment) | Peer reviewed and published |
Comments on Status
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Not applicable | Published journal manuscript |
EM ID
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EM-466 |
EM-605 ![]() |
http://en.ilmatieteenlaitos.fi/yasso-download-and-support ?Comment:User's manual states that the software will be downloadable at this site. |
https://www.epa.gov/water-research/visualizing-ecosystem-land-management-assessments-velma-model-20 | |
Contact Name
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Jari Liski | Heather Golden |
Contact Address
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Finnish Meteorological Institute, P.O. Box 503, 00101 Helsinki | National Exposure Research Laboratory, Office of Research and Development, US EPA, Cincinnati, OH 45268, USA |
Contact Email
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jari.liski@ymparisto.fi | Golden.Heather@epa.gov |
EM ID
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EM-466 |
EM-605 ![]() |
Summary Description
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AUTHOR'S DESCRIPTION: "The Yasso15 calculates the stock of soil organic carbon, changes in the stock of soil organic carbon and heterotrophic soil respiration. Applications the model include, for example, simulations of land use change, ecosystem management, climate change, greenhouse gas inventories and education. The Yasso15 is a relatively simple soil organic carbon model requiring information only on climate and soil carbon input to operate... In the Yasso15 model litter is divided into five soil organic carbon compound groups (Fig. 1). These groups are compounds hydrolysable in acid (denoted with A), compounds soluble in water (W) or in a non-polar solvent, e.g. ethanol or dichloromethane (E), compounds neither soluble nor hydrolysable (N) and humus (H). The AWEN form the group of labile fractions whereas H fraction contains humus, which is more recalcitrant to decomposition. Decomposition of the fractions results in carbon flux out of soil and carbon fluxes between the compartments (Fig. 1). The basic idea of Yasso15 is that the decomposition of different types of soil carbon input depends on the chemical composition of the input types and climate conditions. The effects of the chemical composition are taken into account by dividing carbon input to soil between the four labile compartments explicitly according to the chemical composition (Fig. 1). Decomposition of woody litter depends additionally on the size of the litter. The effects of climate conditions are modelled by adjusting the decomposition rates of the compartments according to air temperature and precipitation. In the Yasso15 model separate decomposition rates are applied to fast-decomposing A, W and E compartments, more slowly decomposing N and very slowly decomposing humus compartment H. The Yasso is a global-level model meaning that the same parameter values are suitable for all applications for accurate predictions. However, the current GUI version also includes possibility to use earlier parameterizations. The parameter values of Yasso15 are based on measurements related to cycling of organic carbon in soil (Table 1). An extensive set of litter decomposition measurements was fundamental in developing the model (Fig. 2). This data set covered, firstly, most of the global climate conditions in terms of temperature precipitation and seasonality (Fig 3.), secondly, different ecosystem types from forests to grasslands and agricultural fields and, thirdly, a wide range of litter types. In addition, a large set of data giving information on decomposition of woody litter (including branches, stems, trunks, roots with different size classes) was used for fitting. In addition to woody and non-woody litter decomposition measurements, a data set on accumulation of soil carbon on the Finnish coast and a large, global steady state data sets were used in the parameterization of the model. These two data sets contain information on the formation and slow decomposition of humus." | ABSTRACT: "Low Impact Development (LID) is an alternative to conventional urban stormwater management practices, which aims at mitigating the impacts of urbanization on water quantity and quality. Plot and local scale studies provide evidence of LID effectiveness; however, little is known about the overall watershed scale influence of LID practices. This is particularly true in watersheds with a land cover that is more diverse than that of urban or suburban classifications alone. We address this watershed-scale gap by assessing the effects of three common LID practices (rain gardens, permeable pavement, and riparian buffers) on the hydrology of a 0.94 km2 mixed land cover watershed. We used a spatially-explicit ecohydrological model, called Visualizing Ecosystems for Land Management Assessments (VELMA), to compare changes in watershed hydrologic responses before and after the implementation of LID practices. For the LID scenarios, we examined different spatial configurations, using 25%, 50%, 75% and 100% implementation extents, to convert sidewalks into rain gardens, and parking lots and driveways into permeable pavement. We further applied 20 m and 40 m riparian buffers along streams that were adjacent to agricultural land cover…" AUTHOR'S DESCRIPTION: "VELMA’s modeling domain is a three-dimensional matrix that includes information regarding surface topography, land use, and four soil layers. VELMA uses a distributed soil column framework to model the lateral and vertical movement of water and nutrients through the four soil layers. A soil water balance is solved for each layer. The soil column model is placed within a watershed framework to create a spatially distributed model applicable to watersheds (Figure 2, shown here with LID practices). Adjacent soil columns interact through down-gradient water transport. Water entering each pixel (via precipitation or flow from an adjacent pixel) can either first infiltrate into the implemented LID and the top soil layer, and then to the downslope pixel, or continue its downslope movement as the lateral surface flow. Surface and subsurface lateral flow are routed using a multiple flow direction method, as described in Abdelnour et al. [21]. A detailed description of the processes and equations can be found in McKane et al. [32], Abdelnour et al. [21], Abdelnour et al. [40]." |
Specific Policy or Decision Context Cited
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None identified | None identified |
Biophysical Context
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Not applicable | The Shayler Crossing (SHC) watershed is a subwatershed of the East Fork Little Miami River Watershed in southwest Ohio, USA and falls within the Till Plains region of the Central Lowland physiographic province. The Till Plains region is a topographically young and extensive flat plain, with many areas remaining undissected by even the smallest stream. The bedrock is buried under a mantle of glacial drift 3–15 m thick. The Digital Elevation Model (DEM) has a maximum value of ~269 m (North American_1983 datum) within the watershed boundary (Figure 1). The soils are primarily the Avonburg and Rossmoyne series, with high silty clay loam content and poor to moderate infiltration. Average annual precipitation for the period, 1990 through 2011, was 1097.4 _ 173.5 mm. Average annual air temperature for the same period was 12 _C Mixed land cover suburban watershed. The primary land uses consist of 64.1% urban or developed area (including 37% lawn, 12% building, 6.5% street, 6.4% sidewalk, and 2.1% parking lot and driveway), 23% agriculture, and 13% deciduous forest. Total imperviousness covers approximately 27% of the watershed area. |
EM Scenario Drivers
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No scenarios presented | Three types of Low Impact Development (LID) practices (rain gardens, permeable pavements, forested riparian buffers) applied a different conversion levels. |
EM ID
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EM-466 |
EM-605 ![]() |
Method Only, Application of Method or Model Run
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Method Only | Method + Application (multiple runs exist) View EM Runs |
New or Pre-existing EM?
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New or revised model | New or revised model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
EM ID
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EM-466 |
EM-605 ![]() |
Document ID for related EM
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Doc-343 | Doc-344 | Doc-13 | Doc-366 |
EM ID for related EM
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EM-467 | EM-469 | EM-480 | EM-485 | EM-375 | EM-377 | EM-378 | EM-884 | EM-883 | EM-887 |
EM Modeling Approach
EM ID
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EM-466 |
EM-605 ![]() |
EM Temporal Extent
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Not applicable | Jan 1, 2009 to Dec 31, 2011 |
EM Time Dependence
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time-dependent | time-dependent |
EM Time Reference (Future/Past)
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Not applicable | past time |
EM Time Continuity
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discrete | discrete |
EM Temporal Grain Size Value
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1 | 1 |
EM Temporal Grain Size Unit
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Year | Day |
EM ID
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EM-466 |
EM-605 ![]() |
Bounding Type
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Not applicable | Watershed/Catchment/HUC |
Spatial Extent Name
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Not applicable | Shayler Crossing watershed, a subwatershed of the East Fork Little Miami River Watershed |
Spatial Extent Area (Magnitude)
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Not applicable | 10-100 ha |
EM ID
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EM-466 |
EM-605 ![]() |
EM Spatial Distribution
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spatially lumped (in all cases) | spatially distributed (in at least some cases) |
Spatial Grain Type
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Not applicable | area, for pixel or radial feature |
Spatial Grain Size
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Not applicable | 10m x 10m |
EM ID
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EM-466 |
EM-605 ![]() |
EM Computational Approach
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Numeric | Numeric |
EM Determinism
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stochastic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-466 |
EM-605 ![]() |
Model Calibration Reported?
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Not applicable | Yes |
Model Goodness of Fit Reported?
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Not applicable |
Yes ?Comment:Goodness of fit for calibrated (2009-2010) and observed streamflow. |
Goodness of Fit (metric| value | unit)
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None | None |
Model Operational Validation Reported?
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Not applicable | Yes |
Model Uncertainty Analysis Reported?
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Not applicable | No |
Model Sensitivity Analysis Reported?
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Not applicable | No |
Model Sensitivity Analysis Include Interactions?
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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-466 |
EM-605 ![]() |
None |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-466 |
EM-605 ![]() |
None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-466 |
EM-605 ![]() |
Centroid Latitude
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Not applicable | 39.19 |
Centroid Longitude
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Not applicable | -84.29 |
Centroid Datum
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Not applicable | WGS84 |
Centroid Coordinates Status
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Not applicable | Provided |
EM ID
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EM-466 |
EM-605 ![]() |
EM Environmental Sub-Class
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Forests | Grasslands | Scrubland/Shrubland | Tundra | Rivers and Streams | Ground Water | Forests | Agroecosystems | Created Greenspace |
Specific Environment Type
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Not applicable | Mixed land cover suburban watershed |
EM Ecological Scale
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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
EM ID
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EM-466 |
EM-605 ![]() |
EM Organismal Scale
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Species | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-466 |
EM-605 ![]() |
None Available | None Available |
EnviroAtlas URL
EM-466 |
EM-605 ![]() |
Average Annual Precipitation, Carbon storage by tree biomass (kg/m2), Carbon Storage by Tree Biomass | Average Annual Precipitation, Average Annual Daily Potential Wind Energy |
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-466 |
EM-605 ![]() |
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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-466 |
EM-605 ![]() |
None |
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