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Home My WebLink AboutRTI_BiofidelityRTI International RTI International is a trade name of Research Triangle Institute.www.rti.org Biological Fidelity Analysis of EFS Stream Classes Funded by: Environmental Defense Fund Conducted by: RTI International RTI International Project Objectives: To adopt a stream classification system that represents the distribution of aquatic biota in North Carolina –evaluate the 7 stream classes of the Environmental Flow Specialist (EFS) hydrological stream classification system: A. Coastal Streams B. Small Stable Streams F. Medium Stable Streams C. Large Stable Streams E. Large Piedmont Rivers D. Small Flashy Streams G. Small Seasonal RTI International Project Objectives: To adopt a stream classification system that represents the distribution of aquatic biota in North Carolina –Compare fidelities of aquatic biota to different stream classification systems –If necessary, modify the EFS stream classes to more accurately describe the distribution of biota RTI International Stream Class – Biological Fidelity Analysis RTI International Step 1. Objective: Examine the biological fidelity of aquatic biota to the 7 EFS stream classes Pair USGS gages (185 gages) to biota at biological monitoring sites to determine stream class – biology assignments RTI International Step 1. Aquatic Biota Database Supporting NC Agency, Department or Program Benthic macroinvertebrate N.C. Department of Environment and Natural Resources (NCDENR) Division of Water Quality (DWQ) Stream fish community NCDENR DWQ Natural Heritage Inventory NCDENR Natural Heritage Program Trout database N.C. Wildlife Resources Commission RTI International Step 1. Objective: Examine the biological fidelity of aquatic biota to the 7 EFS stream classes Pair USGS gages (185 gages) to biota at biological monitoring sites to determine stream class – biology assignments Generate 500 “virtual gages” with WaterFALLTM hydrologic data to assign stream classes to biological monitoring stations without gages RTI International Criteria for biological monitoring stations Monitoring stations distributed evenly across the state Eliminate: –catchments with impaired water quality (as determined by NC Division of Water Quality – 303d listings) –catchments with major in-stream flow alterations (impoundments, discharges and/or intake points) –catchments with “poor” or “questionable” biological monitoring data RTI International Criteria for biological monitoring stations Select: –catchments that contain biological monitoring stations from multiple aquatic biota datasets –biological monitoring stations sampled during years with average climate conditions –biological monitoring stations with most recent biological data –biological monitoring stations with multiple biological measurement dates and presence/absence that doesn’t change by > 10% –biological monitoring stations upstream from USGS reference gages RTI International Step 1. Objective: Examine the biological fidelity of aquatic biota to the 7 EFS stream classes Pair USGS gages (185 gages) to biota at biological monitoring sites to determine stream class – biology assignments Generate 500 “virtual gages” with WaterFALLTM hydrologic data to assign stream classes to biological monitoring stations without gages Random Forest non-parametric analyses to determine probability of species occurrence and biological fidelity to stream classes RTI International Random Forest is a decision-tree modeling and classification approach (Cutler et al., 2007) A decision tree is a predictive model that uses a set of binary rules (yes/no) to split the data based on the predictor variable Random Forest Approach All Stream Class and Aquatic Biology Data Stream Class A Species 1 present Species 2 present Species 3 present Species 4 present YesYes No No Stream Class B Predictive Variable RTI International Random Forest Analysis -Biological fidelity to stream class = high probability = medium probability = low probability = absent Aquatic species Stream Class ABCDEFG 1 2 3 4 5 6 7 8 9 10 RTI International = high probability = medium probability = low probability = absent Random Forest Analysis –NO Biological fidelity to stream class Aquatic species Stream Class ABCDEFG 1 2 3 4 5 6 7 8 9 10 RTI International Step 1. Objective: Examine the biological fidelity of aquatic biota to the 7 EFS stream classes Pair USGS gages (185 gages) to biota at biological monitoring sites to determine stream class – biology assignments Generate 500 “virtual gages” with WaterFALLTM hydrologic data and EFS software to assign stream classes to biological monitoring stations without gages Random Forest non-parametric analyses to determine probability of species occurrence and biological fidelity to stream classes RTI International Stream Class – Biological Fidelity Analysis RTI International Step 1a. Objective: To test biological fidelity to other stream classification systems and compare with EFS –Other stream classifications: McManamay et al. (2011) – regional classification of unregulated streams Konrad (in review) –hydrological classification in southeastern U.S. –Analyses: comparison of classes determined by the three classification systems comparison of biological fidelities to the three stream classification systems RTI International Stream Class – Biological Fidelity Analysis RTI International Step 2. Objective: Assess the biological fidelity of aquatic biota to stream classes that only include streams that are not altered (i.e., minimal instream flow alterations). re-classify streams (at 185 gage locations) using WaterFALLTM hydrologic data (unaltered condition) and EFS software streams that change classes with the reclassification are considered “altered” eliminate “altered” streams from dataset repeat Random Forest non-parametric analyses to determine if biological fidelity to stream classes is improved with dataset restricted to non-altered streams RTI International Stream Class – Biological Fidelity Analysis RTI International Step 3. Objective: Evaluate the ability to improve biological fidelity to stream classes by sub-dividing and/or aggregating the 7 EFS stream classes •Repeat Random Forest non-parametric statistical analyses to determine aquatic biota associations to stream classes divided by: Physiographic/Eco region RTI International Physiographic/Eco Region Classifications Classification System Reference Ecoregions of the Conterminous United States Omernik (1987) Bailey’s Ecoregions and Subregions of the United States http://www.nationalatlas.gov/mld/ecoregp.html, http://na.fs.fed.us/sustainability/ecomap/sectio n_descriptions.pdf Physiographic Regions of the Conterminous United States Fenneman and Johnson (1964) TNC Ecological Drainage Units http://www.2c1forest.org/atlas/metadata/edu_ metadata.htm Hydrologic Landscapes Wolock (2003) RTI International Omernik Ecoregions – Level III RTI International Bailey Ecoregions RTI International Fenneman Physiographic Regions RTI International TNC Environmental Drainage Units RTI International Wolock’s Hydrologic Landscape Regions RTI International Step 3. Objective: Evaluate the ability to improve biological fidelity to stream classes by sub-dividing and/or aggregating the current NC hydrological stream classifications Repeat Random Forest non-parametric statistical analyses to determine aquatic biota associations to stream classes divided by: Physiographic/Eco region Flow metrics that determine stream class RTI International Step 3. Objective: Evaluate the ability to improve biological fidelity to stream classes by sub-dividing and/or aggregating the current NC hydrological stream classifications “Clusters” of biota may indicate the ability to divide stream classes Biota occurring in multiple stream classes may offer opportunity to combine classes RTI International Questions?