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Fire strongly affects animals’ behavior, population dynamics, and environmental surroundings, which in turn are likely to affect their immune systems and exposure to pathogens. However, little work has yet been conducted on the effects of wildfires on wildlife disease. This research gap is rapidly growing in importance because wildfires are becoming globally more common and more severe, with unknown impacts on wildlife disease and unclear implications for livestock and human health in the future.

Here, we discussed how wildfires could influence susceptibility and exposure to infection in wild animals, and the potential consequences for ecology and public health. In our framework, we outlined how habitat loss and degradation caused by fire affect animals’ immune defenses, and how behavioral and demographic responses to fire affect pathogen exposure, spread, and maintenance. We identified relative unknowns that might influence disease dynamics in unpredictable ways (e.g., through altered community composition and effects on free-living parasites). Finally, we discussed avenues for future investigations of fire-disease links.

We hope that this review will stimulate much-needed research on the role of wildfire in influencing wildlife disease, providing an important source of information on disease dynamics in the wake of future wildfires and other natural disasters, andmore »encouraging further integration of the fields of fire and disease ecology.

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Abstract Direct pathogen and parasite transmission is fundamentally driven by a population’s contact network structure and its demographic composition and is further modulated by pathogen life-history traits. Importantly, populations are most often concurrently exposed to a suite of pathogens, which is rarely investigated, because contact networks are typically inferred from spatial proximity only. Here, we use 5 years of detailed observations of Indo-Pacific bottlenose dolphins (Tursiops aduncus) that distinguish between four different types of social contact. We investigate how demography (sex and age) affects these different social behaviors. Three of the four social behaviors can be used as a proxy for understanding key routes of direct pathogen transmission (sexual contact, skin contact, and aerosol contact of respiratory vapor above the water surface). We quantify the demography-dependent network connectedness, representing the risk of exposure associated with the three pathogen transmission routes, and quantify coexposure risks and relate them to individual sociability. Our results suggest demography-driven disease risk in bottlenose dolphins, with males at greater risk than females, and transmission route-dependent implications for different age classes. We hypothesize that male alliance formation and the divergent reproductive strategies in males and females drive the demography-dependent connectedness and, hence, exposure risk to pathogens. Ourmore »study provides evidence for the risk of coexposure to pathogens transmitted along different transmission routes and that they relate to individual sociability. Hence, our results highlight the importance of a multibehavioral approach for a more complete understanding of the overall pathogen transmission risk in animal populations, as well as the cumulative costs of sociality.« less

Social network analysis is an invaluable tool to understand the patterns, evolution, and consequences of sociality. Comparative studies over a range of social systems across multiple taxonomic groups are particularly valuable. Such studies however require quantitative social association or interaction data across multiple species which is not easily available. We introduce the Animal Social Network Repository (ASNR) as the first multi-taxonomic repository that collates 790 social networks from more than 45 species, including those of mammals, reptiles, fish, birds, and insects. The repository was created by consolidating social network datasets from the literature on wild and captive animals into a consistent and easy-to-use network data format. The repository is archived athttps://bansallab.github.io/asnr/. ASNR has tremendous research potential, including testing hypotheses in the fields of animal ecology, social behavior, epidemiology and evolutionary biology.