Stoichiometry and population dynamics

Abstract

AbstractPopulation dynamics theory forms the quantitative core from which most ecologists have developed their intuition about how species interactions, heterogeneity, and biodiversity play out in time. Throughout its development, theoretical population biology has built on variants of the Lotka–Volterra equations and in nearly all cases has taken a single‐currency approach to understanding population change, abstracting populations as aggregations of individuals or biomass. In this review, we explore how depicting organisms as built of more than one thing (for example, C and an important nutrient, such as P) in stoichiometrically explicit models results in qualitatively different predictions about the resulting dynamics. Fundamentally, stoichiometric models incorporate both food quantity and food quality effects in a single framework, allow key feedbacks such as consumer‐driven nutrient recycling to occur, and generally appear to stabilize predator–prey systems while simultaneously producing rich dynamics with alternative domains of attraction and occasionally counterintuitive outcomes, such as coexistence of more than one predator species on a single‐prey item and decreased herbivore performance in response to increased light intensity experienced by the autotrophs. In addition to the theoretical background, we also review recent laboratory and field studies considering stoichiometric effects on autotroph–herbivore systems, emphasizing algae–Daphnia interactions. These studies support the predictions of stoichiometric theory, providing empirical evidence for alternative stable states under stoichiometric constraints, for negative effects of solar radiation on herbivores via stoichiometric food quality, and for diversity‐enhancing effects of poor food quality. Stoichiometric theory has strong potential for both quantitative and qualitative improvements in the predictive power of population ecology, a major priority in light of the multivariate anthropogenic and natural perturbations experienced by populations. However, full development and testing of stoichiometric population dynamics theory will require greater intellectual tolerance and exchange between researchers working in ecosystem and population ecology.