As delphinid populations become increasingly exposed to human activities we rely on our capacity to produce accurate abundance estimates upon which to base management decisions. This study applied mark–recapture methods following the Robust Design to estimate abundance, demographic parameters, and temporary emigration rates of an Indo-Pacific bottlenose dolphin (Tursiops aduncus) population off Bunbury, Western Australia. Boat-based photo-identification surveys were conducted year-round over three consecutive years along pre-determined transect lines to create a consistent sampling effort throughout the study period and area. The best fitting capture–recapture model showed a population with a seasonal Markovian temporary emigration with time varying survival and capture probabilities. Abundance estimates were seasonally dependent with consistently lower numbers obtained during winter and higher during summer and autumn across the three-year study period. Specifically, abundance estimates for all adults and juveniles (combined) varied from a low of 63 (95% CI 59 to 73) in winter of 2007 to a high of 139 (95% CI 134 to148) in autumn of 2009. Temporary emigration rates (γ') for animals absent in the previous period ranged from 0.34 to 0.97 (mean = 0.54; ±SE 0.11) with a peak during spring. Temporary emigration rates for animals present during the previous period (γ'') were lower, ranging from 0.00 to 0.29, with a mean of 0.16 (± SE 0.04). This model yielded a mean apparent survival estimate for juveniles and adults (combined) of 0.95 (± SE 0.02) and a capture probability from 0.07 to 0.51 with a mean of 0.30 (± SE 0.04). This study demonstrates the importance of incorporating temporary emigration to accurately estimate abundance of coastal delphinids. Temporary emigration rates were high in this study, despite the large area surveyed, indicating the challenges of sampling highly mobile animals which range over large spatial areas.
Conservation management typically focuses on protecting wildlife habitat that is linked to important behaviours such as resting, breeding or caring for young. However, development of conservation strategies of social species would benefit from inclusion of social dynamics, particularly for species where social relationships influence fitness measures such as survival and reproduction. We combined the study of dolphin sociality, distribution and calving to identify important behavioural and ecological patterns to inform management. Over 3 consecutive years, 231 boat-based photo-identification surveys were conducted to individually identify adult female bottlenose dolphins over a 120 km 2 area in Bunbury, Western Australia. The density distribution of female dolphins was highest in the inner waters during December-February (austral summer) and March (early autumn), which also coincided in time with the majority of calving. The temporal stability of social bonds between adult females was measured (using lagged association rates) and remained stable over multiple years. A cyclic model best described female-female associations with an annual peak occurring each austral summer (Dec-Jan-Feb). These results informed the implementation of a legislative no-go area and vessel speed restriction areas. In addition to conventional management approaches of protecting important habitat and breeding periods, our measure of dolphin sociality provides a new metric to consider in conservation efforts. We encourage studies on socially complex species to incorporate social dynamics when evaluating possible impacts of anthropogenic activities. 462
Policy analytics combines new data sources, such as from mobile smartphones, Internet of Everything devices, and electronic payment cards, with new data analytics techniques for informing and directing public policy. However, those who do not own these devices may be rendered digitally invisible if data from their daily actions are not captured. We explore the digitally invisible through an exploratory study of homeless individuals in Phoenix, Arizona, in the context of extreme heat exposure. Ten homeless research participants carried a temperature-sensing device during an extreme heat week, with their individually experienced temperatures (IETs) compared to outdoor ambient temperatures. A nonhomeless, digitally connected sample of 10 university students was also observed, with their IETs analyzed in the same way. Surveys of participants complement the temperature measures. We found that homeless individuals and university students interact differently with the physical environment, experiencing substantial differences in individual temperatures relative to outdoor conditions, potentially leading to differentiated health risks and outcomes. They also interact differently with technology, with the homeless having fewer opportunities to benefit from digital services and lower likelihood to generate digital data that might influence policy analytics. Failing to account for these differences may result in biased policy analytics and misdirected policy interventions.
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