Urban development can alter resource availability, land use, and community composition, which, in turn, influences wildlife health. Generalizable relationships between wildlife health and urbanization have yet to be quantified and could vary across different measures of health and among species. We present a phylogenetic meta‐analysis of 516 comparisons of the toxicant loads, parasitism, body condition, or stress of urban and non‐urban wildlife populations reported in 106 studies spanning 81 species in 30 countries. We found a small but significant negative relationship between urbanization and wildlife health, driven by considerably higher toxicant loads and greater parasite abundance, greater parasite diversity, and/or greater likelihood of infection by parasites transmitted through close contact. Invertebrates and amphibians were particularly affected, with urban populations having higher toxicant loads and greater physiological stress than their non‐urban counterparts. We also found strong geographic and taxonomic bias in research effort, highlighting future research needs. Our results suggest that some types of health risks are more pronounced for wildlife in urban areas, which could have important implications for conservation.
Identifying patterns and drivers of infectious disease dynamics across multiple scales is a fundamental challenge for modern science. There is growing awareness that it is necessary to incorporate multi-host and/or multi-parasite interactions to understand and predict current and future disease threats better, and new tools are needed to help address this task. Eco-phylogenetics (phylogenetic community ecology) provides one avenue for exploring multi-host multi-parasite systems, yet the incorporation of eco-phylogenetic concepts and methods into studies of host pathogen dynamics has lagged behind. Eco-phylogenetics is a transformative approach that uses evolutionary history to infer present-day dynamics. Here, we present an eco-phylogenetic framework to reveal insights into parasite communities and infectious disease dynamics across spatial and temporal scales. We illustrate how eco-phylogenetic methods can help untangle the mechanisms of host-parasite dynamics from individual (e.g. co-infection) to landscape scales (e.g. parasite/host community structure). An improved ecological understanding of multi-host and multi-pathogen dynamics across scales will increase our ability to predict disease threats.
Wildlife are important reservoirs for many pathogens, yet the role that different species play in pathogen maintenance frequently remains unknown. This is the case for rabies, a viral disease of mammals. While Carnivora (carnivores) and Chiroptera (bats) are the canonical mammalian orders known to be responsible for the maintenance and onward transmission of rabies Lyssavirus (RABV), the role of most species within these orders remains unknown and is continually changing as a result of contemporary host shifting. We combined a trait-based analytical approach with gradient boosting machine learning models to identify physiological and ecological host features associated with being a reservoir for RABV. We then used a cooperative game theory approach to determine species-specific traits associated with known RABV reservoirs. Being a carnivore reservoir for RABV was associated with phylogenetic similarity to known RABV reservoirs, along with other traits such as having larger litters and earlier sexual maturity. For bats, location in the Americas and geographic range were the most important predictors of RABV reservoir status, along with having a large litter. Our models identified 44 carnivore and 34 bat species that are currently not recognized as RABV reservoirs, but that have trait profiles suggesting their capacity to be or become reservoirs. Further, our findings suggest that potential reservoir species among bats and carnivores occur both within and outside of areas with current RABV circulation. These results show the ability of a trait-based approach to detect potential reservoirs of infection and could inform rabies control programs and surveillance efforts by identifying the types of species and traits that facilitate RABV maintenance and transmission.
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