The detailed spatial and temporal data collected for the regulation
of the silver hake (Merluccius bilinearis) fishery on the Scotian
Shelf provide a unique opportunity to test hypotheses about variability
in catch rates on the scale of individual trawls. I used these data to
examine vessel interactions and long term temporal trends in catchability.
An index of course linearity, derived from observed positions, times, and
speeds of fishing vessels, indicated that interference competition was
present in the fishery. However, catch rate did not decline with local
vessel density. This apparent contradiction is consistent with fleet dynamic
theory and suggests that the direct examination of catch rates is a poor
test for interference in the retrospective analysis of fisheries data.
The study of extended periods of high, localized fishing activity revealed
a cycle in catch rates with periods of about 6 days. Such periods may represent
an interaction between tidal, diel, and/or technological factors. Though
more study is required to identify the cause of these cycles, their existence
should be considered in the design of surveys and other population studies
using catch and effort data.
Despite recognized biases, catch per unit effort (CPUE) statistics remain widely used for the estimation of fish abundance. Previous workers have shown that CPUE can be a misleading index of abundance due to fish behavior, the nominal effort units used, and increases through time in efficiency of fishing (catchability). We examine the theoretical implications of a different factor, interactions among fishing vessels, for the relationship between abundance and CPUE. Our model simulates a fishery that occurs in several adjacent fishing grounds. The spatial distribution of catch and effort is based upon a simplification of the Baranov catch equation, the relationship between fishing efficiency and local fishing effort (interference), and the assumptions of the ideal free distribution. Our results indicate that 1) even low levels of interference among fishing vessels can cause a breakdown in the correlation between CPUE and local abundance, and 2) the influence of interference on this relationship is dependent on the correlation of abundances among adjacent areas. Our model suggests an alternative index of abundance, based upon the proportion of fishing effort on a ground, that would be appropriate for cases where interference occurs among fishing gear.
The decision by fishermen to discard or retain fish of low value to make room for more valuable fish in the hold of a boat (high-grading) is similar to diet choice problems faced by natural foragers. In our study, we apply the rationale of diet choice theory to high-grading behavior in the Oregon trawl fishery by treating fishermen as foragers who must decide how much of each net's haul to "ingest" before searching for more prey. We derive a state-dependent, temporal model of discarding behavior within a fishing trip. This optimization considers the availability of differently valued fish, trip quotas set by the regulatory agency, and the risk of premature trip termination due to loss of gear or injury. The results indicate that those parameters affect discarding behavior through their effect on the probability of exceeding the allowable catch, which we consider analogous to gut capacity. High-grading (partial prey consumption) occurred throughout many simulated trips. The predictions were consistent with the trends in discarding observed in the Oregon trawl fleet. Behavioral models such as ours can be useful to fishery managers by providing a means to explore the potential responses of fishermen to new regulations before they are implemented.
(Figure and tables from the publication - ABOUT
450K)
Many traditional analyses of fisheries data assume that there is a negligible effect of alternative fish stocks on the spatial distribution of fishing effort and that the amount of local effort does not influence catchability. There is growing evidence that contradicts these assumptions. Because of the potential biases that these erroneous assumptions may cause in the interpretation of catch-per-unit-effort (CPUE) statistics, it is important to determine the factors governing the spatial distribution of effort in a fishery. We used data on the Hecate Strait, British Columbia, Canada trawl fishery to test hypotheses about spatial allocation of effort and interaction among fishing vessels. The ideal free distribution of Fretwell and Lucas (1970) was the foundation for deriving these tests. We found evidence for competition among vessels, although we could not distinguish whether the mechanism was interference or exploitation competition. As well, CPUE was generally equalized among the areas fished as predicted by the ideal free distribution, because of movement of boats among areas. Thus area-specific CPUE would not be a reliable index of relative abundance of fish in different areas; relative fishing effort may be better.
(Figures and tables from the publication - ABOUT
420K)