Please use this identifier to cite or link to this item: http://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
RMID: 0030032797
DOI: 10.1071/MF14081
Grant ID: http://purl.org/au-research/grants/arc/DP1096427
http://purl.org/au-research/grants/arc/FS110200051
Appears in Collections:Earth and Environmental Sciences publications

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