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In-water observations highlight the effects of provisioning on whale shark behaviour at the world’s largest whale shark tourism destination

Cite this dataset

Legaspi, Christine; Araujo, Gonzalo (2020). In-water observations highlight the effects of provisioning on whale shark behaviour at the world’s largest whale shark tourism destination [Dataset]. Dryad. https://doi.org/10.5061/dryad.fn2z34tqs

Abstract

The whale shark is the world’s largest fish that forms predictable aggregations globally, many of which support tourism industries. The largest non-captive provisioned whale shark destination globally is at Oslob, Philippines, where >500,000 tourists visit yearly. There, the sharks are provisioned daily, year-round, allowing the human-shark interaction in nearshore waters. We used in-water behavioural observations of whale sharks between 2015 and 2017 to understand the relationship between external stimuli and shark behaviour, whether frequency of visits at the site can act as a predictor of behaviour, and the tourist compliance to the code of conduct. Mixed effects models revealed that the number of previous visits at the site was a strong predictor of whale shark behaviour, and that provisioned sharks were less likely to exhibit avoidance. Compliance was poor, with 93% of surveys having people <2 m from the animal, highlighting overcrowding on whale sharks at Oslob. Given the behavioural implications to whale sharks highlighted here and the local community’s reliance on the tourism industry, it is imperative to look into improving management strategies to increase tourist compliance and strive for sustainable tourism practices.

Methods

The dataset was collected using through dedicated focal follows (Altmann, 1974) between February 2015 and May 2017. Within each survey, an assigned researcher would follow the first shark randomly encountered within the study area and identify the individual using photo-identification. The researcher would gather observations of the shark's predominant behaviour, and as well as events and the individual's corresponding reactions. Tourist compliance to the local code of conduct was also recorded within each survey.

The data gathered was processed by fitting a binomial generalised linear mixed model (GLMM) using the R program to determine variables that influence whale shark behaviour.

Usage notes

The attached files include: 

  1. FocalFollowSurveys_RSOS_Legaspi-2.xlsx: a copy of the data collected from the focal follow surveys 
  2. GLMMcodes_RSOS_Legaspi.rtf: a copy the R-Script and the command codes used in R to analyse the dataset