Update: National Assessment of Fish Habitats Climate Change and Fish Habitat Meeting, Denver, CO, October 19-20, 2009 Dana Infante 1, Peter Esselman 1,2, Lizhu Wang 2, William W. Taylor 1, and Arthur Cooper 1,2 1.Department of Fisheries and Wildlife, Michigan State University, East Lansing, MI 2.Institute for Fisheries Research, Michigan Department of Natural Resources and University of Michigan, Ann Arbor, MI

Nationwide assessment A comprehensive, objective tool for nationwide comparison that will: 1.Identify healthy and degraded aquatic systems 2.Identify key disturbance factors 3.Measure the long-term success of protection and restoration activities

Project objectives 1.Develop an assessment spatial framework 2.Compile and evaluate existing data 3.Conduct initial assessment Current work: Improve assessment with additional data and consideration of regional relationships

Reach –Publically available for conterminous US, Hawaii –Contains information about directional linkages between reaches –Tools for summarizing variables in catchments Assessment framework: Stream reach as basic spatial unit National Hydrography Dataset Plus (NHDPlus); 2.6 million reaches w/ catchments defined Local catchment Reach Network catchment Reach

Local catchments, reaches NHD+ WWF ecoregions Agg. ecoregions Partnerships 8-digit HUsCatchments 8-digit HUs EcoregionsStates EDUs

Initial assessment approach Landscape-scale assessment –Assumes landscape features control local habitat conditions –Integrates info about disturbances to river reaches Multi-scale effects from local and network catchments Networkcatchment Habitat Fishes Localcatchment

Environmental databases 2001 National Land Cover 2001 Forest Canopy 2001 Impervious Surfaces 2000 TIGER Roads US Census/ESRI 2000 Population – NOAA SPARROW Nutrients - USGS Active Mines -USGS National Inventory of Dams 2005 STATSGO Soil data – NRCS-USDA USGS GAP Land Stewardship 2002 Agriculture Census of U.S 2000 Water Use Estimates EPA Geospatial Data (TRI, NPDES, treatment/storage/disposal facilities) EPA Impaired/Threatened Waters (303d) Fish Passage Decision Support System - FWS 1.Meaningful for assessing aquatic habitat condition 2.Coverage for majority of US 3.Consistently developed

Crops (30 m) Grazing/pasture Population density (people/km 2 ) CroplandUrban land cover

Cattle density (#/10,000 acres)Surface water use (MGD/10000 acres) Dams >3m highToxic release inventory sites

Initial assessment variables Developed open space (%) Low intensity urban (%) Medium intensity urban (%) High intensity urban (%) Impervious surfaces (%) Pasture/hay (%) Cultivated crops (%) Ground water use (MGD/km 2 ) Surface water use (MGD/km 2 ) Cattle density (#/acre farmland) Population density (#/km 2 ) Road crossings (#/km 2 ) Road length (m/km 2 ) Dams (#/km) Mines or mineral processing plants (#/km 2 ) Toxics Release Inventory sites (#/km 2 ) National Pollution Discharge Elimination System sites (#/km 2 ) Superfund National Priorities sites (#/km 2 ) 17 variables selected based on: – interpretability – utility for nationwide analysis – literature review – relationships to other variables

Initial assessment process Local vs. network influence, assigned by stream size Combined network disturbance index Combined local disturbance index Sum scores across axes Composite disturbance axes for local catchments Composite disturbance axes for network catchments Multiply reach scores for each axis by % variance explained Cumulative disturbance index Principal Components Analysis % Low, med, high urban % pasture % crops % impervious SW usage GW usage Cattle dens. Pop’n dens Rd. length Rd. crossings Dams Mines TRI NPDES CERC Data preparation Exclude outliers Multiply reach scores for each axis by CANCOR weights

PCA: Local catchments –Urban –Roads –Cattle grazing –Point sources –Row-crop agriculture –Surface water withdrawals Dams did not load heavily on any axis Six axes, ~63% variance explained

–Urban –Cattle grazing –Row-crop agriculture, roads –Water withdrawals –Point sources Dams did not load heavily on any axis… Five axes, ~59% variance explained PCA: Network catchments

CANCOR and influence weights Y 1 + Y 2 + Y 3 + Y 4 = b 1 X 1 + b 2 X 2 + b 3 X 3 + … b p X p Local –Urban, 3.9 –Roads –Cattle grazing, 2.76 –Point sources, 3.82 –Row-crop agriculture, 2.30 –Surface water withdrawals, 1.96 Network –Urban, 4.11 –Cattle grazing, 3.33 –Row-crop agriculture, roads, 1.95 –Water withdrawals, 2.01 –Point sources, 5.75

HeadwaterCreekSmall RiverMed. RiverLarge River 13% (0.52)11% (0.65)19% (0.69)22% (0.59)35% (0.59) 12% (0.48)6% (0.35)9% (0.31)15% (0.41)24% (0.41) 0.5 : : : 0.6 Local vs. network disturbance weights Used CCA to determine the % variance in fish P/A dataset explained by network or local disturbance factors (with variance explained by natural factors removed) –Stratified by stream size –Used 2,231 fish collection sites from Federal programs Network Local Weights (L : N)

Local disturbance Network disturbance

Landscape disturbance index Categories indicate relative degree of impact

Next step – revising river assessment Incorporate additional information (natural and anthropogenic landscape-scale disturbances) Consider regional differences in controls Assess Alaskan and Hawaiian streams

Thank you! Gary Whelan and Doug Beard NFHAP Science and Data Committee Andrea Ostroff and USGS TNC WWF “More people working for more fish”