Habitat Standardization of Cpue Indices: Research Needs

Methods for standardizing CPUE and how to select among them

A number of methods for estimating trends in relative abundance based on standardized catch-per-unit-effort (CPUE) are discussed, including general linear and additive models, habitat-based standardization, neural networks, and regression trees. Methods and criteria for testing among various standardization techniques are presented and recommendations for future research are presented. Authors’

SCIENTIFIC COMMITTEE FOURTH REGULAR SESSION 11-22 August 2008 Port Moresby, Papua New Guinea MONITORING HOOK AND CATCH-AT-DEPTH PROFILES AND APPLICATION OF A HABITAT-BASED CPUE STANDARDIZATION IN THE AUSTRALIAN EASTERN TUNA AND BILLFISH FISHERY

Busan, Republic of Korea Catch per Unit Effort of Oceanic Whitetip Sharks in the Western and Central Pacific Ocean Wcpfc‐sc8‐2012/sa‐ip‐10 Catch per Unit Effort of Oceanic Whitetip Sharks in the Western and Central Pacific Ocean

This paper follows from the indicator based analysis presented to the Western and Central Pacific Fisheries Commission (WCPFC) Scientific Committee (SC7, Clarke et al. 2011). Following a brief summary of exploratory data analysis, this report presents a Catch Per Unit Effort (CPUE) standardization for oceanic whitetip shark (Carcharhinus longimanus) taken in longline and purse seine fisheries b...

Application of a habitat-based model to estimate effective longline fishing effort and relative abundance of Pacific bigeye tuna (Thunnus obesus)

A new habitat-based model is developed to improve estimates of relative abundance of Pacific bigeye tuna (Thunnus obesus). The model provides estimates of ‘effective’ longline effort and therefore better estimates of catch-per-unit-of-effort (CPUE) by incorporating information on the variation in longline fishing depth and depth of bigeye tuna preferred habitat. The essential elements in the mo...

Does habitat or depth influence catch rates of pelagic species?

The efficiency of a pelagic longline fishing operation and the species composition of the resulting catch is influenced primarily by the relationship between the distribution of hooks and species vulnerability, with vulnerability described by either depth or some suite of environmental variables. We therefore fitted longline catch rate models to determine whether catch is estimated better by ve...