Nosy Be in the northwestern Madagascar hosts one of the largest known seasonal feeding aggregations of whale sharks. However, the environmental drivers influencing whale shark surface feeding behaviour in this area remain poorly understood. This study investigates the relationship between environmental variability and surface feeding strategies of immature whale sharks at Nosy Be. Boat-based surveys were conducted in November 2018, 2019, 2022, and 2023, resulting in the photo-identification of 88 individuals and the recording of 85 surface feeding events. The influence of environmental factors on feeding behaviour was assessed using multicollinearity among the environmental covariates and three-level step approach: permanova, multinomial logistic regression, marginal effects, and Cochran’s Q, to evaluate whether environmental conditions discriminate feeding-behaviour categories and to quantify how individual covariates relate to behavioural composition under a multi-step framework. Results showed that there is not a strong enough predictive signal for behaviour based on environmental variables; however, thanks to the marginal effects, it is possible to better assess the probability of a certain type of eating behaviour in the presence of an increase in one of the environmental variables, for example, chlorophyll-a appears to be the most interesting, because its increase is associated with a greater probability of some behaviours instead the others. These preliminary observations provide the first insights to evaluate environmental influences on immature whale shark surface feeding behaviour in Nosy Be, highlighting that it is therefore necessary to deepen and increase data collection to have long and significant series of data, integrated also with data on the preys subject to feeding behaviour and to evaluate which other unobserved aspects, perhaps linked precisely to the consistency and quality of the prey, could allow us to predict feeding behaviour. Improving the understanding of these relationships is essential for predicting whale shark habitat use and for supporting conservation and management strategies in a region increasingly affected by climate variability and anthropogenic pressures.
Micarelli et al. (Thu,) studied this question.