**ABSTRACT NOT FOR CITATION WITHOUT AUTHOR PERMISSION. The title, authors, and abstract for this completion report are provided below. For a copy of the full completion report, please contact the author via e-mail at lupi@msu.edu. Questions? Contact the GLFC via email at frp@glfc.org or via telephone at 734-662-3209.**
COLLECTING
ANGLER BEHAVIOR DATA FROM GREAT LAKES CREEL SURVEYS
Frank Lupi
Department
of Agricultural Food and Resource Economics, Michigan State University, East
Lansing, MI, 48823
June 2008
ABSTRACT:
Our
project assessed the potential of gathering human dimensions data from creel
surveys and correcting for the avidity bias associated with intercept surveys.
As a part of the projects efforts to collect information on fisheries management
agency use of creel surveys for human dimensions data collection, the project collected
a more general set of information from each fisheries management agency in the
U.S. The survey results help document the status of human dimensions data
collection nationally. Some key findings include the fact that almost all
agencies fairly regularly collect some form of human dimensions data, and that
respondents that we classified as biologists tended to place less importance on
the human dimensions data than did the contacts we classified as HD staff or
upper management. In our investigation of avidity bias, we showed, via the
theory and several simulation experiments under a variety of possible distributional
assumptions and sampling sizes, that failure to correct for avidity bias can be
quite problematic. The bias corrections were shown to be straightforward and
feasible to collect as a part of a creel. The simulations showed a systematic
improvement toward the true population parameters with the use of the avidity
corrections. We also implemented the avidity corrections in a large scale field
trail of a creel survey. Interestingly, we found that in our empirical example,
the avidity bias was not particularly problematic. Never the less, the simulations
do show that in some cases the bias can be substantial so that, without collecting
site avidity information, managers would have no way to know how substantial the
effect of avidity bias might be.