Quantitative Fisheries Center

 Travis Brenden

As Associate Director for the Quantitative Fisheries Center, I have daily administrative oversight of the QFC.  I am responsible for QFC budgeting and am the point-of-contact person for QFC partners.  I also hold a fixed-term Assistant Professor position in the Department of Fisheries at Wildlife at Michigan State University, where I conduct research on the ecology and population dynamics of managed fish populations in the Great Lakes.  Research projects with which I am currently involved include a natural mortality estimation project for whitefish stocks in Lakes Huron and Michigan, and a modeling project to determine possible consequences to changes in salmonine stocking practices in Lakes Huron and Ontario.  I also coordinate, develop, and help teach workshops, short courses, and on-line courses on quantitative fisheries topics.      

Although I was born in North Dakota, I was raised in Rapid City, South Dakota, at the foot of the Black Hills.  I received a BS degree in Biological Sciences from the Department of Wildlife and Fisheries Sciences at South Dakota State University.  I then attended graduate school at Virginia Polytechnic Institute and State University in Blacksburg, Virginia, where I received MS and PhD degrees in Fisheries and Wildlife Sciences and an MS degree in Statistics.  My thesis research involved an experimental evaluation of early competitive interactions between largemouth bass and bluegills.  For my PhD research, I studied a riverine muskellunge population in southwest Virginia.  There were several facets to this research, including evaluating effects of alternative harvest regulations on the stock and studying how changes in river discharge influenced fish habitat use and selection.

Shortly before completing my PhD, I moved to Michigan and worked as a Post-Doctoral Research Associate at the Institute for Fisheries Research, which is a Michigan Department of Natural Resources Research Station located at the University of Michigan in Ann Arbor.  My research at IFR was related to a larger EPA-funded project concerning development of a classification system and risk assessment for rivers in Michigan, Wisconsin, and Illinois streams.  My primary task for this project was the development of a spatially constrained clustering routine, which we refer to as ESSI-CAST, for delineating habitat patches (i.e., valley segments, ecological stream segments) for digital river network maps.  ESSI-CAST uses a clustering algorithm known as the cluster affinity search technique to cluster adjoining stream reaches.  ESSI-CAST currently is programmed as a VBA UserForm in Microsoft Excel.