PUB - Publikationen an der Universität Bielefeld

Physiological parameters have the potential to serve as valuable early warning indicators for the conservation of animal populations. However, measuring physiological adaptations in wildlife is often challenging, due to intrinsic differences causing natural variations of physiological measures between individuals across species. This study is aimed at addressing this by investigating the influence of intrinsic factors, including sex, age, body condition, and the incubation of eggs on the H/L ratio of a forest bird community. As physiological measure, we used the heterophil to lymphocyte (H/L) ratio of individuals belonging to different species in the forest bird community, which was assessed using a novel deep learning approach based on convolutional neural networks (CNNs) applied to whole blood smear scans. Using phylogenetically controlled Bayesian analyses across the bird species, we found higher H/L ratios in adult birds than in juveniles and observed slightly higher H/L ratios in females than in males. While body condition had no effect on the H/L ratio, incubating birds tended to have higher H/L ratios than non‐reproductive birds, regardless of their sex. Furthermore, we found a robust phylogenetic signal of the H/L ratio in the studied bird community. Our results reveal significant general patterns of the effect of intrinsic factors on the H/L ratio across a bird community.