Community-based catch-monitoring of dugongs (Dugong dugon) and green turtles (Chelonia mydas) in the Kaiwalagal region of Torres Strait 2006
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This study trialled community-based catch-monitoring strategies for dugongs and green turtles in two communities (Hammond and Thursday Islands) in the Kaiwalagal region (inner islands) of Torres Strait. Hunters completed datasheets after each hunting trip and these were collected weekly by Indigenous catch-monitors employed on the project. The catch-monitoring program was evaluated in terms of the reliability of the informaition collected and the suitability of the method to the communities. The information collected included biological information about the composition of the catch (e.g. sex ratio, size distribution, reproductive status), selectivity of the green turtle catch, catch-effort, catch-gear and the uses for which dugongs and turtles were hunted. The participating communities can use the information in future management of dugongs and green turtles in their communities.
Community-based catch-monitoring of a traditional fishery for marine turtles in the Kaiwalagal traditional sea country of Torres Strait 2006
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26th Annual Symposium on Sea Turtle Biology and Conservation Island of Crete, Greece, 3-8 April 2006. Oral Presentation. The Torres Strait and northern Queensland have the largest population of green turtles in the world. This population supplies a large, internationally-based green turtle harvest, which is currently not managed. In Queensland, successful management will need the involvement of the Indigenous Torres Strait Islanders who use green turtles for cultural, social and economic purposes. This project developed community-based strategies for green turtle catch-monitoring upon which communities could base management plans. I engaged two Torres Strait Island communities in a step-wise process: (1) I obtained support from the Torres Strait Regional Authority; (2) This support enabled me to engage Traditional Owners and Community Councils in each community; and (3) I involved turtle hunters through participatory workshops/meetings. Community members helped me design a datasheet to collect data about hunting behavior needed for co-management. Hunters completed the datasheet after each hunting trip. I assessed the project's success by evaluating the proportion of hunters in the community that participated and the quality of the information they provided. We have one year of data from two communities that actively participate in hunting. Ninety-two and 25% of hunters who signed up from Hammond and Thursday Islands, respectively, handed in datasheets consistently. On Thursday Island, a larger community with a broad social structure, it was more difficult to involve community members in catch-monitoring than on Hammond Island, where there is strong community support for the project. In this paper I discuss culturally appropriate aspects of hunting behavior and catch-monitoring statistics from these two communities. Acknowledgments: Acknowledging project support from: CRC Torres Strait, James Cook University, Department of Environment and Heritage, Ocean Parks Conservation Foundation, Hammond Island Council, TRAWQ Community Council, Kaurareg Traditional Aboriginal Elders Corporation, WNM Community Fisher Group and Prince of Wales Community Fisher Group; Acknowledging travel award support from: Sea Turtle Symposium, Disney Animal Kingdom, Western Pacific Regional Fisheries Management Council, US National Marine Fisheries Service, and US Fish and Wildlife Service.
Using Marine Turtles to Identify Habitat and Assess Connectivity of the North and North-West Marine Park Networks and Sea Country
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This project compiled marine turtle satellite tracking data for four species: green (Chelonia mydas, n=126), flatback (Natator depressus, n=164), hawksbill (Eretmochelys imbricata, n=59) and olive ridley (Lepidochelys olivacea, n=27) turtles, as well as a comprehensive dataset of modelled benthic habitat data from Northern Australia. Tracking data were used to build species-level movement network models to identify connectivity among Australian Marine Parks (AMPs), Indigenous Protected Areas (IPAs) and State Marine Protected Areas (MPAs) across the North and North-West Marine Regions. Tracking datasets were further processed to classify foraging behaviour and quantify foraging activity spaces. Foraging activity spaces were then overlayed with existing modelled benthic habitats using local entropy analysis to assess how well turtle foraging spaces can be used to identify benthic habitats.