Advantages of experiential legacies are determined by interaction of environment and life history: A matrix-model approach

Long-term effects of early-life environments on individuals (experiential legacies) can scale to cohort and population-level consequences. The observed natural diversity of experiential legacies suggests that specific experiential legacies may be beneficial under different circumstances. We explored how six experiential legacies (lifetime trajectories, compensation, environmental specialization, later stressor resilience, live-fast die-young, and no experiential legacy) affected population growth rates and age structure across a range of environmental scenarios and life histories. We constructed a general matrix model initially parameterized for a population with a periodic life history (Lake Erie Walleye, Sander vitreus), which we then modified to apply to populations representing an equilibrium species (cave fishes, family Amblyopsidae) and an opportunistic species (Bay Anchovy, Anchoa mitchilli). While quality of the early-life growth environment had consistent effects on population growth rate and age structure, these relationships were modified by the interaction with experiential legacies and life history. For example, populations across life histories benefited from experiential legacies that set individuals on lifetime growth trajectories in response to quality of early-life environments, when early environments were good; the set of environmental characteristics that allowed populations to benefit from “live-fast, die-young” experiential legacies differed depending on life history; and some experiential legacies (environmental specialization, later stressor resilience) were beneficial only to specific life histories. A compensation experiential legacy was not beneficial under any scenario. Overall, our results demonstrate how individual responses may or may not benefit populations and further emphasize the need for research linking complex long-term responses from individuals to cohorts to populations.