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Data from: Minimum size limits and the reproductive value of numerous, young, mature female fish

Citation

Lavin, Charles; Jones, Geoffrey; Williamson, David; Harrison, Hugo (2021), Data from: Minimum size limits and the reproductive value of numerous, young, mature female fish, Dryad, Dataset, https://doi.org/10.5061/dryad.95x69p8jc

Abstract

Fisheries management relies on various catch and effort controls to preserve spawning stock biomass and maximise sustainable yields while limiting fishery impacts on marine ecosystems. These include species-specific minimum or maximum size limits to protect either small non-reproductive sub-adults, a portion of reproductively mature adults, or large highly fecund individuals. Protecting size classes of mature fish is expected to yield a viable source of larvae for replenishing populations and reduce the risk of recruitment overfishing, yet size-specific recruitment contributions have rarely been assessed empirically. Here we apply genetic parentage analysis to measure the reproductive success of a size-structured population of a commercially important species of coral grouper (Plectropomus maculatus - Serranidae) in no-take marine reserves in the Great Barrier Reef Marine Park, Australia. Although the per-capita reproductive success of individual fish increases rapidly with body-length, the numerous young mature female fish (NYMFFs), below the minimum size limit (38 cm total length), were responsible for generating disproportionately large contributions (36%) towards larval replenishment of both fished and reserve reefs. Our findings indicate that minimum size limits are an effective harvest control measure to safeguard a portion of the spawning stock biomass for coral grouper and supplement recruitment subsidies assured from no-take marine reserves.

Methods

Methods and results appear in manuscript

Usage Notes

Required data of sampled adults and offspring-assigned adults from genetic parentage analysis, as well as abundance data of the target species are provided as .csv files. See attached R file ‘fit.distribution.gamma.R’ in order to execute Gamma distribution fit. The script for all analyses and results is included in the R Markdown file.

Funding

Australian Research Council, Award: DE160101141

Australian Research Council, Award: DP190103056

Australian Research Council, Award: CE140100020