The paralarval stage as key to predicting squid catch: Hints from a process-based model. (August 2022)

• Record Type: Journal Article
• Authors: Bruggeman, Jorn; Jacobs, Zoe L.; Popova, Ekaterina; Sauer, Warwick H.H.; Gornall, Jessica M.; Brewin, Robert J.W.; Roberts, Michael J.
• Is Part Of: Deep sea research. Volume 202(2022)
• Publication Date: 2022-08
• Subjects: Chokka squid -- Size spectra -- Dynamic energy budget models -- Paralarvae -- Catch prediction -- Agulhas bank; Oceanography -- Periodicals; Ocean bottom -- Periodicals; Marine biology -- Periodicals; 551.46
• DOI: 10.1016/j.dsr2.2022.105123
• Languages: English
• ISSNs: 0967-0645

Abstract

Abstract: Squid species show pronounced interannual variability in population size. While this may partially reflect changes in fisheries pressure, it is thought to be primarily the result of environmental variability. Most squid have an annual life cycle with only a short period dedicated to reproduction. With little overlap between generations, the environment can exert a major influence on stock size. In this study we explore, through a combination of process-based modelling and statistical analysis, whether environmental variability explains variability in catch of the chokka squid, Loligo reynaudii, over the Agulhas Bank off South Africa. We focus on growth and survival during the first two months spent as "paralarva" in the pelagic. This period has been suggested to be a key bottleneck and a potential predictor of catch. To describe prey availability and predation pressure, we develop a dynamic model of the size spectrum (1 mg–1000 kg) of the ecosystem over the Agulhas Bank, with trophic interactions governed by size. In tandem, we develop a model for the growth of individual L. reynaudii, which specifies where in the size spectrum individual squid can be found at each stage of their development. We find a correlation of 0.74 between modelled biomass representative for L. reynaudii at the end of its paralarval stage and catch per unit effort (CPUE) in the subsequent season in the period 1995–2015. This suggests that the paralarval stage is indeed a bottleneck: modelled food availability and predation pressure experienced by paralarvae explains 55% of the variability in CPUE, which is a proxy for spawning stock biomass. As the paralarval stage ends approximately nine months before the time of spawning and maximum catch, this work could be used to develop catch predictor with a nine-month lag.