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Three candidate classification tree models were constructed to estimate the probability of obtaining lake sturgeon Acipenser fulvescens bycatch under specific environmental and gillnet fishing conditions in Lake Erie. This analysis was based on a fishery-independent survey, the Lake Erie Partnership Index Fishing Survey (PIS), from 1989 to 2008. The 3 classification tree models included 1 conditional-inference classification tree generated by the R-package 'party' and 2 exhaus- tive-search-based classification trees generated by the R-package 'tree' and 'rpart,' respectively. The discriminative performance of each tree was evaluated by the receiver operating characteristic (ROC) curve and the area under the curve (AUC) using a jackknife approach. Most of the lake stur- geon captured in the PIS were juveniles. The 3 tree models identified fishing basin and gear type as factors related to gillnet fishing that had important influences on lake sturgeon bycatch and implica- tions for lake sturgeon conservation and management. Results indicated that the west basin of Lake Erie could be a hotspot for lake sturgeon bycatch in the commercial gillnet fisheries, and the use of bottom gillnets might increase the probability of catching lake sturgeon. A model comparison indi- cated that the conditional-inference tree model could provide unbiased predictor selection and bet- ter discriminative performance in predicting the probability of taking lake sturgeon as bycatch.

Influences of gillnet fishing on lake sturgeon bycatch in Lake Erie and implications for conservation