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Stock Assessment of Whaler and Hammerhead Sharks (Carcharhinidae and Sphyrnidae) in Queensland

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Stock Assessment of Whaler and Hammerhead Sharks (Carcharhinidae and Sphyrnidae) in Queensland Stock assessment of whaler and hammerhead sharks (Carcharhinidae and Sphyrnidae) in Queensland George M. Leigh Agri-Science Queensland; Department of Agriculture and Fisheries Queensland Government 1 This publication provides an assessment of the state of populations of tropical and subtropical sharks, some of Australia’s most important marine predators, with recommendations for management, future research and data collection. While every care has been taken in preparing this publication, the State of Queensland accepts no responsibility for decisions or actions taken as a result of any data, information, statement or advice, expressed or implied, contained in this report. © The State of Queensland 2015 Copyright protects this publication. The State of Queensland has no objection to this material being reproduced but asserts its right to be recognised as author of its original material and the right to have its material remain unaltered. Cover photo: The common blacktip shark, Carcharhinus limbatus (source: Albert Kok, public domain licence) Inquiries should be addressed to: Manager, DAF Publications Department of Agriculture and Fisheries GPO Box 46 Brisbane Qld 4001 2 Executive summary The majority of commercial shark product caught in Queensland comes from the East Coast Inshore Fin Fish Fishery (ECIFFF) and the Gulf of Carpentaria Inshore Fin Fish Fishery (GOCIFFF). The take of shark is managed through a variety of input and output controls such as maximum legal size limits, in possession limits and, in the case of the Queensland east coast, a total allowable commercial catch (TACC) limit. Data on shark catch sizes and catch rates are principally obtained through the commercial logbook system which has operated from 1988 to present, while data on the shark species composition have come mainly from the Fishery Observer Program (FOP) which operated only from 2006 to 2012. The logbook information has been built upon by ancillary projects such as the National Status of Australian Fish Stocks (SAFS) and Queensland Stock Status assessment processes. Shark species that interact with Queensland commercial and recreational fisheries have not been the subject of a formal stock assessment until now. This stock assessment provides detailed results for the most common sharks encountered by Queensland commercial fishers. These sharks come from the whaler (Carcharhinidae) and hammerhead (Sphyrnidae) families and comprise sharpnose sharks ( Rhizoprionodon taylori and R. oligolinx ), the milk shark ( R. acutus ), the creek whaler ( Carcharhinus fitzroyensis ), the hardnose shark ( C. macloti ), the spot-tail shark ( C. sorrah ), the Australian blacktip shark ( C. tilstoni ), the common blacktip shark ( C. limbatus ), the spinner shark ( C. brevipinna ), bull and pigeye sharks ( C. leucas and C. amboinensis ), the winghead shark ( Eusphyra blochii ), the scalloped hammerhead ( Sphyrna lewini ) and the great hammerhead ( S. mokarran ). Reef sharks were excluded because fishery observer data indicated that they were largely spatially segregated from sharks caught in the inshore net fisheries. The three common species of reef sharks in Queensland, which are all whaler sharks, are the grey reef shark Carcharhinus amblyrhynchos , the blacktip reef shark C. melanopterus and the whitetip reef shark Triaenodon obesus . The assessment includes a new demographic analysis to estimate shark populations’ natural mortality rates and productivity parameters. Compared to previously published demographic analyses of sharks, the new one offers consistent methodology over all the species assessed, uses up-to-date data specific to Australia where possible, corrects some errors and converts the demographic parameters into parameters commonly used in fishery stock assessment models (most notably in the stock–recruitment relationship). The population dynamic model used in the assessment was tailored to the quality of the available data, especially the lack of shark species identification by fishers in the logbook data. The model analysed all shark species simultaneously and used population parameters from the new demographic analysis which in turn made use of the wealth of biological data available for sharks. Input data on species composition came only from the Fishery Observer Program. Species compositions before and after the time of the FOP were inferred indirectly by the model. The model divided Queensland waters into three broad “Management regions”: the Gulf of Carpentaria, the northern east coast and the southern east coast. As shark populations can display strong regional differences, the Management regions were further divided into a total of ten Subregions, based on sampling regions used in the Queensland Long Term Monitoring Program (LTMP). Population parameter estimates were calculated for each species present in each Subregion. The FOP data used for species identification in the assessment were compared to the frequency of species encountered in a major shark tagging experiment (James Cook University, FRDC, project no. 2010/006). The comparison showed close agreement between the two data sets, thereby providing verification of the accuracy of the FOP data on species composition, except for a discrepancy in the proportions of sharpnose sharks recorded. The 1 tagging program recorded more sharpnose sharks while the FOP recorded more of other species of small sharks. Fishery logbook data were not used for species composition due to the inaccuracy of shark species identification by fishers. Logbook data were used only to calculate annual harvest sizes and standardised catch rates for the aggregate of all shark species. These model inputs were still subject to substantial statistical error and potentially to biases from sources including frequent catches of sharks by fishers targeting various species of bony fish such as mackerel and barramundi, consequent discarding of sharks, market preference for small sharks, and political sensitivities that may affect fishers’ reporting of shark catches. Discards usually were not recorded in logbooks. Other sources of error include possible inconsistencies in how characteristics such as net length are reported in the logbooks, absence of data on net depth, and absence of detail on precise locations in which nets were set, e.g., distance from shore and depth of water. Fishery catch rates were considered reliable enough to use in the assessment only from the year 1991 onwards, i.e., three years after the beginning of the logbook system. Standardised catch rates, due to the difficulty of species identification by fishers, could be defined only for all shark species combined and were not species-specific. The catch rates showed no meaningful trends in most Subregions but trended downward in the Whitsunday (covering Bowen and Mackay) and Stanage Subregions, and upward in the Rockhampton, Sunshine Coast and Moreton Subregions. Biological data, in contrast to fisheries data, are of high quality for some species of sharks. Growth parameters, life cycles and reproductive rates are known with some precision. These data supported the stock assessment by providing reliable estimates of length at age, age at maturity, litter size and maximum age attained. Use of data from the Shark Control Program (SCP) protecting popular Queensland east coast bathing beaches was explored. On the advice of the assessment’s Project Team, these data were not used in the assessment, mainly due to concerns about numerous changes in both gear and gear-setting techniques over time. SCP data were available from the beginning of the SCP in 1962. A major feature was a long (roughly 15-year) initial period of depletion of local shark populations after shark control gear was introduced, followed by much lower catch rates after this period. As with fishery data, SCP data suffered from lack of reliable species identification. Estimates of population parameters in the assessment are presented from model simulations by Markov chain Monte Carlo (MCMC). The study ran a total of 500,000 MCMC iterations with every 50th simulation being saved. The limitations of the input data were reflected in the population model outputs with population size estimates subject to large statistical errors. The input data failed to provide realistic upper limits for the population size estimates, due to standardised catch-rates remaining stable or increasing in the majority of Subregions. However, minimum values of population size were determined with greater certainty. The primary reasons for this were that (a) values had to be consistent with the catch-size history and (b) none of the catch-rate time series for the different Subregions displayed large declines. As a consequence of the data limitations, the assessment adopted a conservative approach to the estimation of maximum sustainable yield (MSY) for sharks. Species-specific MSY calculations assumed a multi-species fishery in which no species was allowed to be fished beyond the fishing mortality rate corresponding to its individual MSY: hence the rate of fishing for all species present in a Subregion was limited to that which produced MSY for the most sensitive species in that Subregion. In addition, the maximum-likelihood MSY estimate was not used and the scope of the study was restricted to the lowest 25% of the saved simulations. The study selected two representative parameter vectors for further analysis. The first vector was termed the Substitute Maximum Likelihood Estimate vector and came from the low-end of a
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