CCAMLR

In this paper, I show how data that are routinely collected by survey vessels can be used to estimate the number of Concentrations of krill (in the sense of Butterworth (1988), Mangel (1988)) in a given region of the southern ocean. Sample computations are performed, using data collected by Soviet research/survey vessels in the early 1980s. These examples highlight the need for a navigational log as well as a fishing log in order to make accurate inferences.

Published in: Selected Scientific Papers, Volume 1, pp. 127-252

A model is set up for the operation (which includes both searching and fishing) of a Japanese krill trawler over a half-month period. It is based on an underlying krill distribution model whose parameters are determined primarily from the scientific FIBEX surveys. Output from the model of the operation is compared with (and partially tuned to) statistics for a sample of data from the commercial fishery. A major inconsistency is found: haul times are a factor of 4-5 times greater in reality than in the model. Two ad hoc model modifications are introduced to eliminate this inconsistency: artificially elongating krill swarms, and allowing hauls to continue through more than one swarm. Twenty four candidate abundance indices (generally of a CPUE form) for krill biomass in the 600 n.mile square oceanic sector modelled are considered, and their performance in response to a variety of ways in which the overall krill biomass might decline is investigated. Generally the indices respond by dropping relatively less than the proportional biomass decrease. Catch statistics collected at present (centred primarily on catch per fishing time) are of low utility in detecting biomass decline. Combination catch rate indices incorporating within-concentration search time give improved performances, but are able to monitor changes in within-concentration krill distribution parameters only. Indices that distinguish primary searching time from secondary searching time (searching while waiting to finish processing) within concentrations perform better, but collection of the requisite data may not be practical. Other approaches (e.g. research vessel surveys) need to be considered to monitor changes in the number, distribution and size of krill concentrations, both because there are doubts about the reliability of indices based on concentration searching time (which do respond to such changes), and because such indices are relatively imprecise. Priority needs to be given to improving the krill distribution model underlying the analysis; this probably requires that scientific surveys be planned to operate in small areas concurrently with fishing vessels.

The history of the Japanese krill fishery is reviewed briefly. Important aspects of the fishing operation are the constraints imposed by processing rate limitations on the vessels, and product quality considerations - in particular the increasing tendency to avoid catching "green” krill. These factors result in Catch-per-Day and Catch-per-Haul measures being unlikely to index krill abundance. During the high season, Catch-per-Towing-Time seems likely to index only within-swarm density. Search time data may be needed to assess the density of swarms in a concentration, but may be difficult to record in practice, and a number of other factors may complicate any analysis. The possibility of indexing the extent of the krill distribution through routine oceanographic monitoring merits attention. A data sample from the Japanese krill fishery statistics data-base has been selected for further studies.