Predicting the effects of human developments on individual dolphins to understand potential long-term population consequences
Author(s) -
Enrico Pirotta,
John Harwood,
Paul M. Thompson,
Leslie New,
Barbara Cheney,
Mònica Arso Civil,
Philip S. Hammond,
Carl Donovan,
David Lusseau
Publication year - 2015
Publication title -
proceedings of the royal society b biological sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.342
H-Index - 253
eISSN - 1471-2954
pISSN - 0962-8452
DOI - 10.1098/rspb.2015.2109
Subject(s) - population , wildlife , dredging , term (time) , population model , ecology , population growth , environmental resource management , biology , demography , environmental science , physics , quantum mechanics , sociology
Human activities that impact wildlife do not necessarily remove individuals from populations. They may also change individual behaviour in ways that have sublethal effects. This has driven interest in developing analytical tools that predict the population consequences of short-term behavioural responses. In this study, we incorporate empirical information on the ecology of a population of bottlenose dolphins into an individual-based model that predicts how individuals' behavioural dynamics arise from their underlying motivational states, as well as their interaction with boat traffic and dredging activities. We simulate the potential effects of proposed coastal developments on this population and predict that the operational phase may affect animals' motivational states. For such results to be relevant for management, the effects on individuals' vital rates also need to be quantified. We investigate whether the relationship between an individual's exposure and the survival of its calves can be directly estimated using a Bayesian multi-stage model for calf survival. The results suggest that any effect on calf survival is probably small and that a significant relationship could only be detected in large, closely studied populations. Our work can be used to guide management decisions, accelerate the consenting process for coastal and offshore developments and design targeted monitoring.
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