Papers by Rik C Buckworth
Journal of Fish Biology, Oct 24, 2016
Multivariate and machine-learning methods were used to develop field identification techniques fo... more Multivariate and machine-learning methods were used to develop field identification techniques for two species of cryptic blacktip shark. From 112 specimens, precaudal vertebrae (PCV) counts and molecular analysis identified 95 Australian blacktip sharks Carcharhinus tilstoni and 17 common blacktip sharks Carcharhinus limbatus. Molecular analysis also revealed 27 of the 112 were C. tilstoni × C. limbatus hybrids, of which 23 had C. tilstoni PCV counts and four had C. limbatus PCV counts. In the absence of further information about hybrid phenotypes, hybrids were assigned as either C. limbatus or C. tilstoni based on PCV counts. Discriminant analysis achieved 80% successful identification, but machine-learning models were better, achieving 100% successful identification, using six key measurements (fork length, caudal-fin peduncle height, interdorsal space, second dorsal-fin height, pelvic-fin length and pelvic-fin midpoint to first dorsal-fin insertion). Furthermore, pelvic-fin markings could be used for identification: C. limbatus has a distinct black mark >3% of the total pelvic-fin area, while C. tilstoni has markings with diffuse edges, or has smaller or no markings. Machine learning and pelvic-fin marking identification methods were field tested achieving 87 and 90% successful identification, respectively. With further refinement, the techniques developed here will form an important part of a multi-faceted approach to identification of C. tilstoni and C. limbatus and have a clear management and conservation application to these commercially important sharks. The methods developed here are broadly applicable and can be used to resolve species identities in many fisheries where cryptic species exist.
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G3: Genes, Genomes, Genetics, Apr 1, 2013
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Marine Ecology Progress Series, Aug 15, 2013
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Marine Ecology Progress Series, 2013
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Endangered Species Research, 2013
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Copyright and disclaimer © 2015 CSIRO To the extent permitted by law, all rights are reserved and... more Copyright and disclaimer © 2015 CSIRO To the extent permitted by law, all rights are reserved and no part of this publication covered by copyright may be reproduced or copied in any form or by any means except with the written permission of CSIRO. Important disclaimer CSIRO advises that the information contained in this publication comprises general statements based on scientific research. The reader is advised and needs to be aware that such information may be incomplete or unable to be used in any specific situation. No reliance or actions must therefore be made on that information without seeking prior expert professional, scientific and technical advice. To the extent permitted by law, CSIRO (including its employees and consultants) excludes all liability to any person for any consequences, including but not limited to all losses, damages, costs, expenses and any other compensation, arising directly or indirectly from using this
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Journal of Fish Biology, 2016
Sustainable exploitation of fisheries populations is challenging to achieve when the size of the ... more Sustainable exploitation of fisheries populations is challenging to achieve when the size of the population prior to exploitation and the actual numbers removed over time and across fishing zones are not clearly known. Quantitative fisheries' modeling is able to address this problem, but accurate and reliable model outcomes depend on high quality input data. Much of this information is obtained through the operation of the fishery under consideration, but while this seems appropriate, biases may occur. For example, poorly quantified changes in fishing methods that increase catch rates can erroneously suggest that the overall population size is increasing. Hence, the incorporation of estimates of abundance derived from independent data sources is preferable. We review and evaluate a fisheries-independent method of indexing population size; inferring adult abundance from estimates of the genetic effective size of a population (Ne ). Recent studies of elasmobranch species have shown correspondence between Ne and ecologically determined estimates of the population size (N). Simulation studies have flagged the possibility that the range of Ne /N ratios across species may be more restricted than previously thought, and also show that declines in Ne track declines in the abundance of model fisheries species. These key developments bring this new technology closer to implementation in fisheries science, particularly for data-poor fisheries or species of conservation interest.
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Fish and Fisheries, 2013
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ICES Journal of Marine Science: Journal du Conseil, 2015
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Marine Policy, 2015
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ICES Journal of Marine Science, 2014
Biomass, catchability, and natural mortality are key parameters in fish stock assessment. Yet, it... more Biomass, catchability, and natural mortality are key parameters in fish stock assessment. Yet, it is difficult to estimate these quantities, especially natural mortality, when only fishery data are available. Using a method of population depletion analysis, we estimated these population and biological quantities for the white banana prawn (Penaeus merguiensis) in Australia's valuable Northern Prawn Fishery. In addition, we directly included fishing power change over time. The models were implemented in a Bayesian framework by incorporating process error, observation error, and random variability for the underlying parameters. The posterior median initial fishable biomass ranged from ∼2000 to 7000 t year−1, and the median catchability varied from ∼3.8 × 10−4 to 7.3 × 10−4 boat-day−1, resulting in an average fishing power increase of 2.6% per year. An unexpected result is the estimate of exponential natural mortality rate of ∼0.03 week−1. This value is substantially lower than an ...
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The current project investigated relationships between environmental factors and harvests of crab... more The current project investigated relationships between environmental factors and harvests of crabs in the Gulf of Carpentaria (GoC), northern Australia. This was in response to industry and managerial concerns about consistent declines in harvests of GoC Giant Mud Crab (Scylla serrata). In the orthern Territory (NT), declines occurred between 2009 and 2016, whilst in Queensland (Qld), declines occurred between 2013 and 2016. The declines occurred despite different management arrangements (e.g. NT harvests females, whereas Qld does not), suggesting common environmental factors were involved.
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Papers by Rik C Buckworth