Causes of maladaptation

Abstract

Evolutionary biologists tend to approach the study of the natural world within a framework of adaptation, inspired perhaps by the power of natural selection to produce fitness advantages that drive population persistence and biological diversity. In contrast, evolution has rarely been studied through the lens of adaptation's complement, maladaptation. This contrast is surprising because maladaptation is a prevalent feature of evolution: population trait values are rarely distributed optimally; local populations often have lower fitness than imported ones; populations decline; and local and global extinctions are common. Yet we lack a general framework for understanding maladaptation; for instance in terms of distribution, severity, and dynamics. Similar uncertainties apply to the causes of maladaptation. We suggest that incorporating maladaptation-based perspectives into evolutionary biology would facilitate better understanding of the natural world. Approaches within a maladaptation framework might be especially profitable in applied evolution contexts - where reductions in fitness are common. Toward advancing a more balanced study of evolution, here we present a conceptual framework describing causes of maladaptation. As the introductory article for a Special Feature on maladaptation, we also summarize the studies in this Issue, highlighting the causes of maladaptation in each study. We hope that our framework and the papers in this Special Issue will help catalyze the study of maladaptation in applied evolution, supporting greater understanding of evolutionary dynamics in our rapidly changing world.

Keywords: adaptation; fitness; global change; maladaptation.

Figure 1

Number of evolutionary studies referring to adaptation versus maladaptation. Data were obtained by searching Web of Science Core Collections on July 16, 2019. Studies reporting adaptation (blue bars) were identified by searching on “evolution* and (ecolog* or biol*) and (adapt*)” whereas studies reporting maladaptation (red bars) were identified by searching on “evolution* (and ecolog* or biol*) and maladapt*”

Figure 2

Scenarios of maladaptation. Nine scenarios are illustrated using an archery metaphor of arrows and targets. In each scenario, arrows indicate representative individuals of the population while the target represents the fitness landscape. Rows indicate trait–fitness landscape scenarios that can generate maladaptation. Columns indicate various causes of the scenarios, involving either change in the focal population (left), change in the environment (middle), or eco‐evolutionary/eco‐plasticity feedbacks in which the focal population's evolution or dynamics alter the fitness landscape

Figure 3

A conceptual fitness surface showing various ways for mean absolute fitness to decline. Fitness is indicated by heat map colors and is shown in relation to environmental condition (x‐axis) and phenotype value (y‐axis). Under conditions shown, there exists a range of phenotype and environment values that confer maximal fitness. Scenarios causing maladaptation are represented in terms of trait distribution change (blue arrows) and environmental change (black arrows). For trait distribution change, maladaptation can arise through (A, biased arrows) resulting from change in trait mean ($\frac{\text{d}\overline{x}}{\text{d}t}$) that reduces mean fitness or (B, imprecise arrows) increasing trait variation ($\frac{\text{d}\text{var}(x)}{\text{d}t}$) e.g., due to immigration, assortative mating, mutation, maladaptive plasticity), which increases variance in fitness and thereby reduces mean fitness). For environmental change, maladaptation can arise when (c, moving target) the environmental value changes ($\frac{\text{d}E}{\text{d}t}$), (D, retreating target) the fitness peak narrows ( $\frac{\text{d}\text{var}(E)}{\text{d}t}$; e.g., due to increased competition or niche contraction) resulting in stronger stabilizing selection which in turn increases variance in fitness and thereby reduces mean fitness, or (E, degraded target) the environmental quality decreases ($\frac{\text{d}{W}_{\max }}{\text{d}t}$).