Journal
MARINE ECOLOGY PROGRESS SERIES
Volume 265, Issue -, Pages 197-212Publisher
INTER-RESEARCH
DOI: 10.3354/meps265197
Keywords
Cynoscion nebulosus; fish distributions; habitat suitability modelling; generalized additive models (GAM)
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Conservation and fisheries managers require models that describe the abundance and distribution of fishes in order to protect and manage exploited fish stocks in the face of anthropogenically induced habitat loss and exploitation. In this study, models describing environmental preferences were developed for juvenile spotted seatrout Cynoscion nebulosus within 3 Florida estuaries: the Indian River Lagoon, Tampa Bay, and Charlotte Harbor. A generalized additive model (GAM) was developed to describe the environmental preferences, spatial distribution, and temporal fluctuations of juvenile seatrout in each estuary based on a 4 yr time-series of fisheries-independent catches. All 3 models indicated similar environmental preferences for all populations examined and were also qualitatively consistent with the findings from other studies. Consequently, habitat-preference models based on GAMs are useful tools to predict fish abundances in estuaries lacking fisheries-independent data, given knowledge of the local environmental conditions. These initial findings were further supported by quantitative analyses of the models' abilities to predict abundance in independent datasets, despite complications with multicollinearity of independent variables and temporal differences in the recruitment periodicity between the 3 Florida populations. Estimates of environmentally based habitat value on a relative scale will aid conservation managers in protecting vital nursery habitats in estuaries currently lacking fisheries-independent information and in predicting the effects of future environmental change. Finally, assuming similar environmental conditions between years, the year effect from these models can serve as an index of relative abundance for fisheries managers to predict future recruitment strength and to tune catch-at-age stock-assessment models.
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