| Abstract |
As environments change rapidly across the globe, we need to understand the mechanisms driving disease transmission in climate and human-impacted landscapes to mitigate the negative effects of wildlife disease for animals, humans and wider environments. To do this, we need to know how the landscape affects wildlife movement so we can identify disease spread dynamics. We need to understand how wildlife genetic resistance to diseases affects disease spread across landscapes so we can identify measures to mitigate the negative effects of wildlife disease. And we need to know how the distribution of wildlife and their diseases will change under climate change so we can predict the risk of future disease spread. This project will develop a framework for predicting the effects of diseases on wildlife populations, distribution and evolution that accounts for the effects of landscapes, animal movement, adaptation and climate change. We will apply our framework to a key bat fungal disease system, white-nose syndrome, that has decimated North American bat populations for the past two decades. We will analyse information about bat genetic makeup and fungal diseases to understand how the landscape affects wildlife movement and the distribution of diseases. We will identify genetic responses of bats to fungal infection to model how wildlife resistance or tolerance to disease affects the spread of diseases across landscapes. We will identify genetic responses of bats to climate and their effects on suitable conditions for bats to predict how the distribution of bats and their diseases will change under climate change. We will sample bats from caves across climatic and disease exposure gradients in eastern USA, from northern states, where white nose syndrome is well established, to Texas, representing the expanding frontline of the disease. We will collect non-lethal paired bat and fungal disease samples to link the genetic makeup of individual bats to their disease state. We will focus on three bat species that show different responses to infection. We will sequence the genomes of the bats to identify barriers to connectivity between caves, adaptive responses to fungal infection, climate adaptations and vulnerability to climate change. We will apply our framework to model the effects of landscape and movement on the spread of diseases and bat adaptations and the impacts of climate change on the distribution of bats and the diseases they carry. We will provide disease risk maps and field-based estimates of disease resistance and climate adaptations that offer immediate predictive solutions for white nose syndrome in North America bats. We will develop a flexible model that can be widely applied to other wildlife disease systems across the world. This project will advance our understanding of the genetic basis of fungal disease resistance in bats and the impacts of fungal diseases and climate change on bat populations. More generally, this project will advance our understanding of disease systems, impacts of the landscape on wildlife movement and fitness and the interactions between risk of disease exposure and the genetic makeup of individual animals. Our new modelling framework can simulate range-wide population changes, range shift and evolution of wildlife carriers of diseases, driven by both changing climate and disease-associated selection. The UK team will be involved in all aspects of the project, leading on the genomic data generation and analysis, providing key expertise in both bat and fungal ecology and genomics. |
