DISSERTATION RESEARCH: Mechanisms of compensatory dynamics in natural systems

University Of California-Berkeley, Berkeley CA

Investigators

Abstract

Understanding the mechanisms governing ecological stability, such as why a property such as primary productivity is stable in some communities while variable in others, has long been a central focus of ecology. Interactions between environmental conditions and species dynamics are generally thought to be key determinants of stability at the community level over time. In variable environments, environment-species interactions may generate compensatory dynamics, which occur when asynchronous fluctuations at the population level buffer against fluctuation at the community level. For example, precipitation is a strong control of grassland productivity, and in grasslands characterized by high precipitation variability plant species tend to tradeoff over time because some species better tolerate drought years, whereas other species are more competitive in wet years. This project will show whether the stabilizing effect of compensatory dynamics in environments with variable precipitation depends on 1) the responses of species to precipitation and 2) the effects of species on productivity. Researchers will test this with experiments in California grasslands, where species tradeoffs are frequent, by manipulating precipitation variability and species interactions. Results will yield one of the first mechanistic, field-based tests of how compensatory dynamics shape community stability. This research is important to society because many people rely on stable sources of natural resources, but global change is likely to increase variability in rainfall and temperature. For example, ranchers in California depend upon grasslands for forage, but the reliability of this ecosystem service is threatened by climate change. Results will be disseminated to such land managers via the Central Coast Rangeland Coalition and through publications read by managers such as the California Naturalist and Rangelands, and the sets of data from the project will be made available to the public. The project will also train a Ph.D. student and undergraduates, five of whom have developed honors thesis projects related to the research.