One for all and all for one: an efficient blood sampling strategy to assess penguin health and immune status

Antarctic penguins are considered sentinels of ecosystem health. They face multiple anthropogenic threats, including global climate change and local stressors such as tourism, fisheries, and pollution. Monitoring their physiological responses to stress is essential for assessing the Antarctic population and ecosystem health. On the other hand, it is equally important to minimize impact of handling stress, i.e., reducing time of restraint, and if possible, reducing the number of birds sampled. Given the valuable insights provided by hematological parameters in monitoring and assessing individual physiological conditions, there is growing interest in refining analytical methods (i.e., the amount of blood) and counting techniques to minimize analysis time and the number of samples required. We here refined the analysis of Erythrocytes Nuclear Abnormalities (ENAs), for genomic instability, and total White Blood Cells (WBCs) for immune status, in Adélie penguin (Pygoscelis adeliae) blood smears. The improved method, using Giemsa staining, effectively distinguishes nuclear and cytoplasmic components in both erythrocytes and leukocytes, enabling the reliable enumeration of ENAs and the clear identification of different WBC classes. A statistical sample size-rarefaction analysis also informed on the number of individuals required, optimizing sampling effort while maintaining data precision. More specifically, the sums of ENAs and WBCs can be precisely estimated for all the three study colonies with a sample size of about 20–25 individuals, while the parameters micronucleus and two-lobed nucleus show greater uncertainty. For most other parameters, the estimates stabilize with approximately 15–20 samples. Our findings provide a foundation for developing optimized sampling protocols for improved hematological analysis in penguins, offering a practical tool for assessing their health and immune status; therefore, the adoption of the presented method should be supported as a cost-effective and less invasive tool at the population level for long-term conservation studies.