Data from: A dynamic state model of migratory behavior and physiology to assess the consequences of environmental variation and anthropogenic disturbance on marine vertebrates ...

• Main Authors: Pirotta, Enrico, Mangel, Marc, Costa, Daniel P., Mate, Bruce, Goldbogen, Jeremy A., Palacios, Daniel M., Huckstadt, Luis A., McHuron, Elizabeth A., Schwarz, Lisa, New, Leslie
• Format: Dataset
• Language: English
• Published: Dryad 2017
• Subjects: energetics; Ecology spatial; Balaenoptera musculus; Environmental variability; Foraging ecology; Modeling ecological; Methods computer simulations; Marine; Ecology behavioral; Reproduction costs; Pacific; baleen whales
• Online Access: https://dx.doi.org/10.5061/dryad.md416; https://datadryad.org/stash/dataset/doi:10.5061/dryad.md416

Integrating behavior and physiology is critical to formulating new hypotheses on the evolution of animal life-history strategies. Migratory capital breeders acquire most of the energy they need to sustain migration, gestation and lactation before parturition. Therefore, when predicting the impact of environmental variation on such species, a mechanistic understanding of the physiology of their migratory behavior is required. Using baleen whales as a model system, we developed a dynamic state variable model that captures the interplay among behavioral decisions, energy, reproductive needs and the environment. We applied the framework to blue whales (Balaenoptera musculus) in the Eastern North Pacific Ocean, and explored the effects of environmental and anthropogenic perturbations on female reproductive success. We demonstrate the emergence of migration to track prey resources, enabling us to quantify the trade-offs among capital breeding, body condition, and metabolic expenses. We predict that periodic ... : Rcpp model code and associated filesThe archive includes the Rcpp code to run the Stochastic Dynamic Programming model, forward Monte Carlo simulations and sensitivity analysis. The data files required to run the model are also attached. These include the coordinates of model locations (file locs_100 km), the number of hours available to feed at different locations over time (file twilight_times_byLoc_forModel) and the upwelling index per location over time (file UpwellingIndex1). The details of how these data were generated are reported in the manuscript.Rcpp code + files.zip ...