Accompanies the article: BRADSHAW, CJA, P MEAGHER, MJ THIELE, RG HARCOURT, C HUVENEERS. 2021. Predicting potential future reduction in shark bites on people. Royal Society Open Science 8: 201197. doi:10.1098/rsos.201197
Despite the low chance of a person being bitten by a shark, there are serious associated costs. Electronic deterrents are currently the only types of personal deterrent with empirical evidence of a substantial reduction in the probability of being bitten by a shark. We aimed to predict the number of people who could potentially avoid being bitten by sharks in Australia if they wear personal electronic deterrents. We used the Australian Shark Attack File from 1900 to 2020 to develop sinusoidal time-series models of per capita incidents, and then stochastically projected these to 2066. We predicted that up to 1063 people (range: 185–2118) could potentially avoid being bitten across Australia by 2066 if all people used the devices. Avoiding death and injury of people over the next half-century is of course highly desirable, especially when considering the additional costs associated with the loss of recreational, commercial and tourism revenue potentially in the tens to hundreds of millions of dollars following clusters of shark-bite events.
January 2021
Corey J. A. Bradshaw (e-mail), Global Ecology, Flinders University
The R code attached reproduces an analysis to predict the number of people who could avoid being bitten by a shark in Australia from 2020-2066 if wearing electronic deterrents.
The analysis requires four different data files:
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Australian Shark Attack File ('sharkbite.exp.csv') — for proprietry reasons, this dataset is only available upon request to Taronga Conservation Society Australia (attn: Phoebe Meagher), Taronga Zoo, Sydney, New South Wales, Australia (but see this repository: Australian Shark-Incident Database)
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Monthly southern oscillation index (soi) values from the Australian Bureau of Meteorology (BoM) ('soi.csv')
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Monthly Pacific Decadal Oscillation (pdo) values from the National Centres for Environmental Information ('pdo.csv')
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Australian population size estimates (past) and projections to 2066 ('auspop.csv') from the Australian Bureau of Statistics
Also accompanying the code are two source files with additional functions necessary to reproduce the analyses (r.squared.R & new_lmer_AIC_tables3.R)