Evolutionary rescue in novel environments: towards improving predictability
Authored by Michael Barfield, Robert D Holt
Date Published: 2016
Sponsors:
French National Research Agency (ANR)
United States National Science Foundation (NSF)
Platforms:
R
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
Model code not found
Abstract
Background: Populations are often subject to changes in their
environments (either locally or due to movement of a population), which, if large enough, require them to adapt in order to persist. This is
`evolutionary rescue'.
Questions: What factors affect the ability of a population to recover
after a sudden change in its environment? What can be measured about an
initial population, prior to the environmental change, that can improve
the predictability of evolutionary rescue?
Methods: A deterministic model and simulations of an individual-based
model (IBM).
Results: Heritability that decreases with decreasing population size
could prevent evolutionary rescue in the deterministic model. For the
IBM, the probability of rescue decreased with increasing magnitude of
the environmental change and with decreasing initial population size. At
times, heritability of a trait can increase as selection occurs. Most
extinctions occurred shortly after the change. Rescue depended
significantly on the genetics of the population at the time of the
environmental change, and predictive power about which populations go
extinct, or persist, is improved by knowing the mean genotypic value and
genetic variance in the initial population. However, there remains
considerable uncertainty in such predictions.
Conclusions: Persistence after a sudden environmental change was greater
in populations with more individuals and more genetic variance at the
time of the change, and depended on rapid adaptation soon after the
change, without which extinction was likely. Understanding the amount
and dynamics of genetic variation can improve predictability of
persistence, but there is inescapable randomness in evolution and
ecology that will always, we believe, preclude tight predictions.
Tags
Prevent extinction