T-7,8-7 Comparing Standard North American Freshwater Fish Data Using a Web-Accessible Database

Tuesday, August 21, 2012: 9:30 AM
Meeting Room 7,8 (RiverCentre)
Scott A. Bonar , USGS Cooperative Research Unit, University of Arizona, Tucson, AZ
Matt Rahr , College of Agriculture and Life Sciences, University of Arizona, Tucson, AZ
Toby Torrey , College of Agriculture and Life Sciences, University of Arizona, Tucson, AZ
Averill Cate Jr. , School of Natural Resources, University of Arizona, Tucson, AZ
Norman Mercado Silva , University of Arizona
Recently, the American Fisheries Society developed standard methods to sample freshwater fish populations, publishing them in 2009 in the book Standard Methods for Sampling North American Freshwater Fishes.  This project involved 284 scientists from 107 different organizations across Canada, Mexico and the United States.   Data collected using standard methods gives biologists the ability to compare data across regions or time.  Here we discuss recent progress on an on-line web-accessible database program to compare fish growth, condition, length-frequency, and catch per unit effort data collected using AFS standard methods.  Development of this database is a collaborative effort among AFS, the US Geological Survey, the National Park Service, the U.S. Forest Service, the University of Arizona, and the University of Guadalajara, Mexico.  The database (1) provides on-line summaries of 4,092 data sets of condition, length-frequency, CPUE and growth indices of common freshwater fishes, collected using standard gears from 42 states and provinces across North America, (2) allows entry of new data collected using standardized methods, so averages of commonly-used fishery indices can be updated, and (3) allows queries, graphical, and tabular output of the data summaries so they can be easily accessed and integrated into projects across North America. Users will be able to compare condition, growth and abundance of fish collected in a particular waterbody with regional and rangewide averages and percentiles, thus increasing resource information in a variety of areas. The database is programmed in a PHP-based Drupal framework.