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-584 ![]() |
EM Short Name
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Nutrient Tracking Tool (NTT), north central Texas, USA |
EM Full Name
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Nutrient Tracking Tool (NTT), Upper North Bosque River watershed, Texas, USA |
EM Source or Collection
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None |
EM Source Document ID
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354 |
Document Author
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Saleh, A., O. Gallego, E. Osei, H. Lal, C. Gross, S. McKinney, and H. Cover |
Document Year
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2011 |
Document Title
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Nutrient Tracking Tool - a user-friendly tool for calculating nutrient reductions for water quality trading |
Document Status
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Peer reviewed and published |
Comments on Status
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Published journal manuscript |
EM ID
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EM-584 ![]() |
http://ntt.tiaer.tarleton.edu/welcomes/new?locale=en | |
Contact Name
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Ali Saleh |
Contact Address
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Texas Institute for Applied Environmental Research-Tarleton State University, Stephenville, TX 76401,USA |
Contact Email
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saleh@tiaer.tarleton.edu |
EM ID
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EM-584 ![]() |
Summary Description
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ABSTRACT: "The Nutrient Tracking Tool (NTrT) is an enhanced version of the Nitrogen Trading Tool, a user-friendly Web-based computer program originally developed by the USDA. The NTrT estimates nutrient (nitrogen and phosphorus) and sediment losses from fields managed under a variety of cropping patterns and management practices through its user-friendly, Web-based linkage to the Agricultural Policy Environmental eXtender (APEX) model. It also accesses the USDA Natural Resources Conservation Service’s Web Soil Survey to utilize their geographic information system interface for field and operation identification and load soil information. The NTrT provides farmers, government officials, and other users with a fast and efficient method of estimating nitrogen and phosphorus credits for water quality trading, as well as other water quality, water quantity, and farm production impacts associated with conservation practices. The information obtained from the tool can help farmers determine the most cost-effective conservation practice alternatives for their individual operations and provide them with more advantageous options in a water quality credit trading program. An application of the NTrT to evaluate conservation practices on fields receiving dairy manure in a north central Texas watershed indicates that phosphorus-based application rates, filter strips, forest buffers, and complete manure export off the farm all result in reduced phosphorus losses from the fields on which those practices were implemented. When compared to a base¬line condition that entailed manure application at the nitrogen agronomic rate of receiving crops, the reductions in total phosphorus losses associated with these practices ranged from 15% (2P Rate scenario) to 76% (forest buffer scenario)." AUTHOR'S DESCRIPTION: "This paper provides a brief overview of the NTrT and presents results of verification and application of the tool on a selected field on a test field in the Upper North Bosque River (UNBR) watershed in Texas…simulations for the baseline and all five alternative scenarios were replicated for each of 90 specific soil types in Erath County, Texas…results reported and discussed in this report represent the averages of the output for all soil types." |
Specific Policy or Decision Context Cited
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None identified |
Biophysical Context
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The UNBR watershed is comprised primarily of two main physiographic areas, the West Cross Timbers and the Grand Prairie Land Resource Areas. In the West Cross Timbers, soils are primarily fine sandy loams with sandy clay subsoils. Soils in the Grand Prairie area, on the other hand, are typically calcareous clays and clay loams (Ward et al. 1992). |
EM Scenario Drivers
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Conservation management strategies to reduce phosphorus losses |
EM ID
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EM-584 ![]() |
Method Only, Application of Method or Model Run
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Method + Application (multiple runs exist) View EM Runs |
New or Pre-existing EM?
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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-584 ![]() |
Document ID for related EM
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Doc-352 |
EM ID for related EM
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EM-549 |
EM Modeling Approach
EM ID
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EM-584 ![]() |
EM Temporal Extent
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1960-2001 |
EM Time Dependence
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time-dependent |
EM Time Reference (Future/Past)
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future time |
EM Time Continuity
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discrete |
EM Temporal Grain Size Value
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1 |
EM Temporal Grain Size Unit
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Day |
EM ID
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EM-584 ![]() |
Bounding Type
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Watershed/Catchment/HUC |
Spatial Extent Name
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Upper North Bosque River watershed |
Spatial Extent Area (Magnitude)
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100-1000 km^2 |
EM ID
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EM-584 ![]() |
EM Spatial Distribution
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spatially lumped (in all cases) |
Spatial Grain Type
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Not applicable |
Spatial Grain Size
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Not applicable |
EM ID
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EM-584 ![]() |
EM Computational Approach
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Numeric |
EM Determinism
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deterministic |
Statistical Estimation of EM
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EM ID
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EM-584 ![]() |
Model Calibration Reported?
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Yes |
Model Goodness of Fit Reported?
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No |
Goodness of Fit (metric| value | unit)
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None |
Model Operational Validation Reported?
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No |
Model Uncertainty Analysis Reported?
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No |
Model Sensitivity Analysis Reported?
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No |
Model Sensitivity Analysis Include Interactions?
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Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-584 ![]() |
None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-584 ![]() |
Centroid Latitude
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32.09 |
Centroid Longitude
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-98.12 |
Centroid Datum
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WGS84 |
Centroid Coordinates Status
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Estimated |
EM ID
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EM-584 ![]() |
EM Environmental Sub-Class
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Agroecosystems |
Specific Environment Type
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Rangeland and forage fields for dairy |
EM Ecological Scale
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Ecological scale corresponds to the Environmental Sub-class |
Scale of differentiation of organisms modeled
EM ID
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EM-584 ![]() |
EM Organismal Scale
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Not applicable |
Taxonomic level and name of organisms or groups identified
EM-584 ![]() |
None Available |
EnviroAtlas URL
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GAP Ecological Systems, Agricultural water use (million gallons/day), The Watershed Boundary Dataset (WBD) |
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-584 ![]() |
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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-584 ![]() |
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