Estimating the demographic parameters of contemporary populations is essential to the success of elasmobranch conservation programmes, and to understanding their recent evolutionary history. For benthic elasmobranchs such as skates, traditional fisheries-independent approaches are often unsuitable as the data may be subject to various sources of bias, whilst low recapture rates can render mark-recapture programmes ineffectual. Close-kin mark-recapture (CKMR), a novel demographic modelling approach based on the genetic identification of close relatives within a sample, represents a promising alternative approach as it does not require physical recaptures. We evaluated the suitability of CKMR as a demographic modelling tool for the critically endangered blue skate () in the Celtic Sea using samples collected during fisheries-dependent trammel-net surveys that ran from 2011 to 2017. We identified three full-sibling and 16 half-sibling pairs among 662 skates, which were genotyped across 6291 genome-wide single nucleotide polymorphisms, 15 of which were cross-cohort half-sibling pairs that were included in a CKMR model. Despite limitations owing to a lack of validated life-history trait parameters for the species, we produced the first estimates of adult breeding abundance, population growth rate, and annual adult survival rate for in the Celtic Sea. The results were compared to estimates of genetic diversity, effective population size ( ), and to catch per unit effort estimates from the trammel-net survey. Although each method was characterized by wide uncertainty bounds, together they suggested a stable population size across the time-series. Recommendations for the implementation of CKMR as a conservation tool for data-limited elasmobranchs are discussed. In addition, the spatio-temporal distribution of the 19 sibling pairs revealed a pattern of site fidelity in , and supported field observations suggesting an area of critical habitat that could qualify for protection might occur near the Isles of Scilly.
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http://dx.doi.org/10.1111/eva.13474 | DOI Listing |
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December 2024
The Sheba Pandemic Preparedness Research Institute (SPRI), Sheba Medical Center, Tel Hashomer, Ramat Gan 52621, Israel.
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December 2024
Associate Laboratory for Animal and Veterinary Sciences (AL4AnimalS), Interdisciplinary Center for Research in Animal Health (CIISA), Faculty of Veterinary Medicine, University of Lisbon, 1300-477 Lisbon, Portugal.
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Friedrich-Loeffler-Institut Institute of Epidemiology, Südufer 10, 17493 Greifswald-Insel Riems, Germany.
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December 2024
Discipline of Genetics, School of Life Sciences, University of KwaZulu-Natal, Pietermaritzburg 3209, South Africa.
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