Divergent impacts of warming weather on wildlife disease risk across climates

Abstract

Disease outbreaks among wildlife have surged in recent decades alongside climate change, although it remains unclear how climate change alters disease dynamics across different geographic regions. We amassed a global, spatiotemporal dataset describing parasite prevalence across 7346 wildlife populations and 2021 host-parasite combinations, compiling local weather and climate records at each location. We found that hosts from cool and warm climates experienced increased disease risk at abnormally warm and cool temperatures, respectively, as predicted by the thermal mismatch hypothesis. This effect was greatest in ectothermic hosts and similar in terrestrial and freshwater systems. Projections based on climate change models indicate that ectothermic wildlife hosts from temperate and tropical zones may experience sharp increases and moderate reductions in disease risk, respectively, though the magnitude of these changes depends on parasite identity.

Understanding how temperature shifts could impact infectious disease

“…Recently, support was found for the TMH across 7,346 wildlife populations and 2,021 host–parasite combinations [ 55 ]. The strength of support, however, was stronger for ectothermic than endothermic hosts and depended on the pathogen taxon [ 55 ].…”

“…Recently, support was found for the TMH across 7,346 wildlife populations and 2,021 host–parasite combinations [ 55 ]. The strength of support, however, was stronger for ectothermic than endothermic hosts and depended on the pathogen taxon [ 55 ]. Projections based on these statistical models and climate change projections suggest that wildlife hosts from temperate and tropical zones will experience sharp increases and moderate reductions in disease risk, respectively, supporting the hypotheses that shifts in infectious disease distributions and net increases in disease globally could occur in the future [ 55 ].…”

“…Although many researchers have correctly submitted that differences in the TPCs of hosts and parasites can lead to nonlinear host–parasite interactions (i.e., the net outcome of virulence and resistance) as temperatures shifts [ 28 , 47 ], the value of TMH is that it incorporates local adaptation, is derived from first principles of MTE (i.e., the temperature range at which an organism maintains performance is negatively related to body size), and integrates TPCs of the host and parasite but does not require quantification of TPCs for all temperature-dependent traits of each. It can be tested easily by coupling local weather (temperature of peak prevalence) and climate data (30-year mean temperature) with field surveys of infections across temperature, which are plentiful (e.g., [ 55 ]). Finally, it offers more nuanced predictions for climate change–disease interactions than past models.…”

“…Finally, it offers more nuanced predictions for climate change–disease interactions than past models. It posits that cool-adapted hosts will be at greater risk of disease with climate change than warm-adapted hosts, providing predictions for host populations and species and locations on the planet that might experience the greatest change in disease with a changing climate (e.g., [ 55 ]).…”

Introduction to the special issue: Ecoimmunology in ectotherms

“…This increase in the prevalence of pathogens and the resulting diseases, in turn, are associated with climate change and environmental contamination (Becker & Zamudio, 2011;Brem & Lips, 2008;Burrowes et al, 2004). Interacting with emerging diseases, there are other consequences of anthropogenic action in environments, such as habitat loss, fragmentation, disconnection (Becker et al, 2017;Smith et al, 2019;Wake & Vredenburg, 2008), environmental contamination, light pollution, and an increase in temperature (Bernardo et al, 2007;Cohen et al, 2020;Dominoni & Nelson, 2018;Midgley & Hannah, 2019;Prevedello et al, 2019). Ectotherms are characterized by the low ability of endogenous control of body temperature, relying mostly on behavioral thermoregulation (Abram et al, 2017;Angilletta et al, 2002;Huey et al, 2003).…”