Date of Award:


Document Type:


Degree Name:

Doctor of Philosophy (PhD)




Peter B. Adler


Forecasting the effects of climate change on plant and animal populations is a high priority in ecology. We studied the effects of climate on plant populations through the use of observational and experimental data, as well as analytical models. Our research questions were: (1) Do the effects of interannual climate variation on the population growth rates of widespread species show a coherent pattern across gradients of mean annual climate? (2) How well can population models fit to observational data predict the response of populations to field experiments that manipulate climate? And (3) does niche overlap between competitors predict the magnitude of competition-mediated indirect effects in mechanistic resource competition models? To test the first question, we assessed how interannual variation in climate affected the abundance of big sagebrush (Artemisia tridentata) at 131 monitoring sites across its range. We found that years of above average temperature increased sagebrush abundance at cold sites, but decreased sagebrush abundance at hot sites. This pattern indicates that sagebrush distribution may be limited by hot and cold temperatures at the extremes of its distribution. We addressed iv our second research question by fitting statistical models to over 25 years of observational data on the performance of four dominant plant species in a sagebrush steppe community. We then experimentally manipulated soil moisture in this community and tested how well the statistical models fit to observational data could predict species’ responses to the experimental treatments. In two out of four species, we found that including climate effects in our models helped us predict the population-level responses to the experiment. Moreover, effects of historical soil moisture variation on vital rates were generally consistent with the effects of drought and irrigation treatments. Our results provide some evidence that observational data can be used to predict species’ responses to climate change in the future. We addressed our third question by simulating environmental change in analytical models of resource competition and quantifying the size of direct and competition-mediated indirect effects that resulted. We showed that the magnitude of indirect effects increased as the niche overlap between competitors increased.