Bottlenose whales are more socially connected when in poor body condition
Walmsley, S. F.; Girard, C.; Newton, K.; Gaspard, D.; Whitehead, H.; Feyrer, L.
Show abstract
Social relationships are strongly linked to health and biological fitness in humans and other animals. For example, social support may buffer individuals against harsh ecological conditions. Reciprocally, better health may allow for greater investment in social relationships. We examined links between health and social behaviour in an endangered population of northern bottlenose whales (Hyperoodon ampullatus). Using photo-identifications spanning 37 years, we visually classified whether individuals had poor body condition on each day they were observed (N = 3,086 whale-days). We then used generalized linear mixed models to explore how body condition varied with sex, age, and within-individual deviations in group size or other social metrics derived from Bayesian social networks. Approximately 11% of individuals were classified as being in poor condition at any time, though the prevalence of poor condition varied across raters and years. Visually assessed condition was successfully validated with morphometric measures, though there was only weak evidence that poor condition predicted apparent survival. Contrary to expectations, whales in poor condition were found in larger groups and had more social partners than their average across the study period. These findings run counter to the expectation that health and social connectedness are positively correlated in social mammals.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
Similar papers in this journal
- Social tolerance mediates social learning in wild red-fronted lemurs (Eulemur rufifrons) and ring-tailed lemurs (Lemur catta) 92%
- Genetic relatedness cannot explain social preferences in black-and-white ruffed lemurs (Varecia variegata). 92%
- How does individual variation in sociality influence fitness in prairie voles? 92%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.