Using marine mammal necropsy data in animal health surveillance: the case of the harbor porpoise in the Southern North Sea - IJsseldijk, Lonneke L.; van den Broek, Jan; Kik, Marja J. L.; Leopold, Mardik F.; Bravo Rebolledo, Elisa; Gröne, Andrea; Heesterbeek, Hans (Frontiers in Marine Science, 2024)
Rapid changes of marine ecosystems resulting from human activities and climate change, and the subsequent reported rise of infectious diseases in marine mammals, highlight the urgency for timely detection of unusual health events negatively affecting populations. Studies reporting pathological findings in the commonly stranded harbor porpoise (Phocoena phocoena) on North Atlantic coastlines are essential to describe new and emerging causes of mortality. However, such studies can often not be used as long-term health surveillance tools due to analytical limitations. We reassessed stranding-, necropsy-, dietary-and marine debris data of 405 harbor porpoises on 31 variables and applied supervised and unsupervised machine learning techniques to explore and analyze these data. We classified and cross-correlated the variables and characterized the importance of the different variables for accurately predicting cause-of-death categories. The variable 'age class' seemed most influential in determining cause-of-death categories. The variables assigned as part of the external examination of carcasses, such as imprints from nets and lesions induced by predators, as well as nutritional condition were most important for predicting cause-of-death categories, with a model prediction accuracy of 75%. There was a group of variables that either rarely occurred or widely occurred, regardless of other variables, making them unimportant in explaining variance in our data. These included 'ingested plants', 'ingested debris', 'iron accumulation in hepatocytes', 'sex', 'blunt force trauma', 'edema in respiratory tract', 'multiple organ congestion', and finally, 'pathology cardiovascular system'. Future porpoise monitoring, and in particular the assessment of temporal trends, should predominantly focus on influential variables as determined in this study. Structural pathogen-and contaminant assessment data was not available but would be an important step to further complete the dataset. This could be vital for drawing population-inferences and thus for longterm harbor porpoise population health monitoring as an early warning tool for population change.