Phenotypic plasticity and population viability: the importance of environmental predictability.
Phenotypic plasticity plays a key role in modulating how environmental variation influences population dynamics, but we have only rudimentary understanding of how plasticity interacts with the magnitude and predictability of environmental variation to affect population dynamics and persistence. We developed a stochastic individual-based model, in which phenotypes could respond to a temporally fluctuating environmental cue and fitness depended on the match between the phenotype and a randomly fluctuating trait optimum, to assess the absolute fitness and population dynamic consequences of plasticity under different levels of environmental stochasticity and cue reliability. When cue and optimum were tightly correlated, plasticity buffered absolute fitness from environmental variability, and population size remained high and relatively invariant. In contrast, when this correlation weakened and environmental variability was high, strong plasticity reduced population size, and populations with excessively strong plasticity had substantially greater extinction probability. Given that environments might become more variable and unpredictable in the future owing to anthropogenic influences, reaction norms that evolved under historic selective regimes could imperil populations in novel or changing environmental contexts. We suggest that demographic models (e.g. population viability analyses) would benefit from a more explicit consideration of how phenotypic plasticity influences population responses to environmental change.
Reed
Thomas E
TE
School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98105, USA. tomreed@u.washington.edu
Waples
Robin S
RS
Schindler
Daniel E
DE
Hard
Jeffrey J
JJ
Kinnison
Michael T
MT
D000222:Adaptation, Physiological / Q000502:physiology*; D000818:Animals; D003198:Computer Simulation; D004777:Environment; D008954:Models, Biological; D010641:Phenotype; D010944:Plants; D012098:Reproduction; D013269:Stochastic Processes