Date of Award
Doctor of Philosophy (PhD)
Ecology and Evolutionary Biology
Accelerated rates of climate change are expected to either lead to adaptation and persistence, or extinction. Traditionally, ecological models predict extinction risk based on how environmental change alters a population’s intrinsic growth rate (r). However, these predictions often ignore the potential for evolutionary rescue, whereby populations avoid extinction via adaptive evolution. This dissertation sets out to address what allows rapid evolution to rescue natural populations in the face of environmental change. Our current lack of understanding of the role of ecological and evolutionary dynamics, and their combined effect on population responses to climate change, demands further theoretical and experimental work to investigate these processes. I utilize theoretical modeling approaches to investigate the dynamics of small populations that have been reduced due to environmental change, and what allows them to rebound and avoid extinction. (1) Successful evolutionary tracking depends on how selection acts on key life history traits. The environment may impose selective pressure on specific demographic rates (birth and death) rather than directly on r (the difference between the birth and death rates). Therefore, when considering the potential for evolutionary rescue, populations with the same r can have different abilities to persist amidst environmental change. We cannot adequately understand evolutionary rescue without accounting for demography, and interactions between density dependence and environmental change. Using stochastic birth-death population models, I found evolutionary rescue to be more likely when environmental change alters the birth rather than death rate. Furthermore, species that evolve via density-dependent selection are less vulnerable to extinction than species that undergo selection independent of population density. Resolving the key demographic factors affected by environmental change can lead to an understanding of how populations evolve to avoid extinction. By incorporating these considerations into our models we can better predict how species will respond to climate change. (2) Propensity for evolutionary rescue varies in complex environments. Natural populations may experience a diversity of selection pressures across space and time due to differences in spatial and temporal environments, as well as in the competition they are subject to. I develop a spatially explicit individual based model to determine how the slope, spatial heterogeneity and patchiness of an environmental gradient as well as the dispersal ability of individuals will alter population extinction risk across a landscape due to environmental change. We find that as expected, the larger the magnitude of environmental change, the more likely a population will go extinct. Furthermore, there is a complex interplay between the spatial scenarios of gradient steepness, patchiness, and heterogeneity. Components that tend to encourage genetic diversity via local adaption to spatially diverse landscapes tended to allow for persistence. But, there are notable exceptions to this general rule. Too much heterogeneity leads populations to being maladapted to their local environment. In this case, landscape patchiness can serve to allow for environmental refugia. Thus we show that the spatial landscape significantly alters probability of evolutionary rescue, highlighting the importance of spatial realism in predictive models. (3) Resource scarcity plays a vital role in thermal performance amidst changing temperatures. Consumers and resources both have characteristic responses to temperature change, but how these temperature responses interact in the context of consumer-resource dynamics and adaptive evolution has not been well established. We utilize a consumer resource model to assess how communities will respond to temperature change. Our models demonstrate that within the consumer thermal niche, performance and equilibrium biomass differ. This implies that estimates of thermal stress and extinction risk based solely upon the individual thermal performance is problematic. We find that as consumers reduce a resource, there is adaptive pressure for that resource to grow successfully at lower temperatures where the consumer uptake rate is lower. Lastly we assess the importance of thermal asymmetry of the consumer and resource. If the resource’s thermal performance shifts to warmer temperatures, the consumer’s persistence in low temperatures decreases to reflect the effect of resource limitation at low temperatures. Likewise if the resource’s thermal performance shifts to colder temperatures, the consumer’s ability to persist in the hottest temperatures also decreases. Thus we must consider the dynamic interplay between temperature and interacting species as this can determine species response to temperature.Overall, we find that the assumptions we make when modeling environmental change in the life history of individuals, species interactions, and their spatial landscape have significant effects on species ability to survive environmental change. We provide generalizable frameworks to improve our ability to understand and predict how natural populations will respond to climate change.
Vinton, Anna, "How Eco-Evolutionary Interactions Mitigate Climate Risk: A Theoretical Perspective" (2021). Yale Graduate School of Arts and Sciences Dissertations. 122.