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https://hdl.handle.net/2440/101371
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Type: | Journal article |
Title: | Evidence for a broad-scale decline in giant Australian cuttlefish (Sepia apama) abundance from non-targeted survey data |
Author: | Prowse, T. Gillanders, B. Brook, B. Fowler, A. Hall, K. Steer, M. Mellin, C. Clisby, N. Tanner, J. Ward, T. Fordham, D. |
Citation: | Marine and Freshwater Research, 2015; 66(8):692-700 |
Publisher: | CSIRO Publishing |
Issue Date: | 2015 |
ISSN: | 1323-1650 1448-6059 |
Statement of Responsibility: | Thomas A. A. Prowse, Bronwyn M. Gillanders, Barry W. Brook, Anthony J. Fowler, Karina C. Hall, Michael A. Steer, Camille Mellin, N. Clisby, Jason E. Tanner, Tim M. Ward and Damien A. Fordham |
Abstract: | Little is known about the population trajectory and dynamics of many marine invertebrates because of a lack of robust observational data. The giant Australian cuttlefish (Sepia apama) is IUCN-listed as Near Threatened because the largest known breeding aggregation of this species in northern Spencer Gulf, South Australia, has declined markedly since the turn of the century. We used by-catch records from long-term trawl surveys to derive abundance data for S. apama and commercial cuttlefish harvest data as a measure of exploitation. Using Bayesian hierarchical models to account for zero-inflation and spatial dependence in these abundance counts, we demonstrated a high probability of broad-scale declines in the density of S. apama, particularly surrounding the primary aggregation site, which supports the recent closure of the entire S. apama fishery in northern Spencer Gulf. Historical harvest data were positively correlated with S. apama density estimated from the trawl surveys, suggesting that the commercial cuttlefish catch tracks the species abundance. Our results also indicated the possibility that the known S. apama breeding grounds might be supplemented by individuals that were spawned elsewhere in northern Spencer Gulf. |
Keywords: | Bayesian hierarchical model; Cephalopoda; commercial harvest; conditional autoregressive model; vector autoregression |
Rights: | Journal compilation © CSIRO 2015 |
DOI: | 10.1071/MF14081 |
Grant ID: | http://purl.org/au-research/grants/arc/DP1096427 http://purl.org/au-research/grants/arc/FS110200051 |
Published version: | http://dx.doi.org/10.1071/mf14081 |
Appears in Collections: | Aurora harvest 7 Earth and Environmental Sciences publications |
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