Predicting presence and abundance of demersal fishes: a model application to shortspine thornyhead Sebastolobus alascanus

摘要

ABSTRACT: Predicting the abundance of marine fishes based on habitat models is often difficult due to the presence of large numbers of zero observations. The objective of this study was to analyze the ability of a 2-stage model to predict the presence and abundance of a rockfish species, shortspine thornyhead Sebastolobus alascanus. The data used for these analyses were collected during bottom-trawl surveys of the Gulf of Alaska ecosystem from 1993 to 2007 and in the Aleutian Islands ecosystem from 1994 to 2006. The presence of shortspine thornyhead was predicted from the 5th and 95th percentiles of the cumulative distribution function resampled over depth and temperature. The results predicted shortspine thornyhead would not occur at depths 176 m or 671 m, and presence or absence was correctly predicted at 86.3% of the trawl survey stations. Environmental variables were then used to model shortspine thornyhead abundance at stations where presence was predicted. The best-fitting model of abundance included the variables depth, local slope, thermocline temperature, shrimp catch per unit effort (CPUE), and an index of predation refuge. The model explained 72.4% of the variation in 1993–2005 Gulf of Alaska survey data and 73.7% of the variation in the 2007 data from the Gulf of Alaska. The model explained only 23.9% of the variation in shortspine thornyhead CPUE from the Aleutian Islands bottom-trawl surveys from 1994 to 2006. The habitat model included important variables for survival and growth in order to provide more biologically meaningful results than with other modeling methods.