Jared Steed, The College of Wooster

Class Year:

2009

Mentor:

Michael Wilberg, Ph.D.

Abstract:

Accurate surveying techniques are necessary for the creation and enforcement of fisheries management practices. Previous creel surveys used to estimate angler effort have had large amounts of variance, mostly due to day to day variation in effort. Effort data taken from a creel survey, performed on nine Chesapeake Bay tributaries, was compared to weather data from National Oceanic and Atmospheric Administration (NOAA) weather stations. The three weather patterns investigated were daily rain fall, average wind speed, and daily precipitation. Various prediction models were created using all possible combinations of these three variables. These models were then compared via Akaike Information Criterion (AIC) for each model. Out of the eight systems optimal prediction models all used temperature as a predicting variable. Additionally, two models used wind data and three models used precipitation data. The variables used for prediction appeared not only to depend upon what environmental conditions were seen, but also depended on the fishing population and the locations available for fishing. In the future, these prediction models may provide more accurate total angler effort predictions by explaining some of inter-day effort variation.

Location:

Chesapeake Biological Laboratory