https://github.com/cjabradshaw/sharkmanagementstrategieseffectsize
Analyses to estimate power to detect differences in the number of shark bites on humans with/without shark management strategies in place
https://github.com/cjabradshaw/sharkmanagementstrategieseffectsize
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Analyses to estimate power to detect differences in the number of shark bites on humans with/without shark management strategies in place
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README.md
Shark-management strategies effect-size analyses
Analyses to assess probability of detecting differences in the number of shark bites on humans with/without shark management strategies in place.
See also the Australian Shark-Incident Database (ASID).
Prof Corey J. A. Bradshaw
Global Ecology | Partuyarta Ngadluku Wardli Kuu, Flinders University, Adelaide, Australia
July 2023/updated October 2023
e-mail
contributors: Charlie Huveneers
Paper
Huveneers, C, C Blount, CJA Bradshaw, PA Butcher, MP Lincoln Smith, WG MacBeth, DP McPhee, N Moltschaniwskyj, VM Peddemors, M Green. 2023. Shifts in the incidence of shark bites and efficacy of beach-focussed mitigation in Australia. Marine Pollution Bulletin 198:115855. doi:10.1016/j.marpolbul.2023.115855
Abstract
Shark-human interactions are some of the most pervasive human-wildlife conflicts, and their frequencies are increasing globally. New South Wales (Australia) was the first to implement a broad-scale program of shark-bite mitigation in 1937 using shark nets, which expanded in the late 2010s to include non-lethal measures. Using 196 unprovoked shark-human interactions recorded in New South Wales since 1900, we show that bites shifted from being predominantly on swimmers to 79 % on surfers by the 1980s and increased 2–4-fold. We could not detect differences in the interaction rate at netted versus non-netted beaches since the 2000s, partly because of low incidence and high variance. Although shark-human interactions continued to occur at beaches with tagged-shark listening stations, there were no interactions while SMART drumlines and/or drones were deployed. Our effectsize analyses show that a small increase in the difference between mitigated and non-mitigated beaches could indicate reductions in shark-human interactions. Area-based protection alone is insufficient to reduce shark-human interactions, so we propose a new, globally transferable approach to minimise risk of shark bite more effectively.
Scripts
SMSeffectSizeAnalysis.R: main R code for analysisnewlmerAIC_tables3.R: source code for information-theoretic algorithmsr.squared.R: source code for calculating goodness-of-fit for linear models (including mixed-effects models)
Data
- beachmesh.csv: data of shark bites at beaches with and without beach-mess protection (all interactions)
- beachmeshonlybites.csv: data of shark bites at beaches with and without beach-mess protection (bites only)
- sms.csv: data describing shark bites across different beaches before and after shark-management strategies
Required R packages
performancesjPlotlme4doSNOWsnowiteratorsforeachparallel
Owner
- Name: Corey Bradshaw
- Login: cjabradshaw
- Kind: user
- Location: Adelaide, South Australia
- Company: Flinders University
- Website: http://globalecologyflinders.com
- Twitter: conservbytes
- Repositories: 15
- Profile: https://github.com/cjabradshaw
Matthew Flinders Professor of Global Ecology @GlobalEcologyFlinders @CABAH
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