- Life-history performance of individuals in wildlife populations emerges from the interplay between the multiple processes that constitute an animal’s health. Monitoring and modelling indicators of health can thus provide a way to asses and forecast the status of a population before its abundance changes.
- In this study, we develop a Bayesian state-space model that links multiple health indicators (representing energy, endocrine and morphometric status) and resulting female calving probability, using an 8-year dataset of repeated sightings, morphological measurements, faecal sampling and offspring observations of gray whales (Eschrichtius robustus) belonging to the Pacific Coast Feeding Group.
- Model results indicate that calving probability emerges from the combined effect of a female’s structural body size and available energy reserves, while also showing a weak negative correlation with glucocorticoid levels prior to pregnancy. Assessment of population age structure suggests that the number of individuals in younger age classes is smaller than expected for a growing or a stable population, which, together with decreasing body size, could indicate an impending decline in this group. Model development was made possible by the collection of high-resolution, longitudinal data on individuals, although several mechanistic assumptions were imposed by the relatively short time series (8 years), influencing the results.
- Our modelling approach could inform similar effects in other long-lived species where population dynamics cannot be easily monitored. Ultimately, models of wildlife health and vital rates can support assessments of the population-level consequences of multiple stressors, a key goal for management and conservation across systems and jurisdictions.
Citation:
Pirotta, E., L. New, A. Fernandez Ajó, K.C. Bierlich, C.N. Bird, C. Loren Buck, L. Hildebrand, K.E. Hunt, J. Calambokidis, & L.G. Torres. 2025. Body Size, Nutritional State and Endocrine State Are Associated with Calving Probability in a Long-Lived Marine Species. Journal of Animal Ecology. doi: 10.1111/1365-2656.70068
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