Background/Question/Methods: Sustainable management of biological diversity requires a clear understanding of how stochastic fluctuations in the environment influence spatio-temporal population dynamics. For example, environmental fluctuations can synchronize population dynamics over large areas, increasing extinction risk. Population dynamics and their response to environmental fluctuations are shaped by a combination of factors, including spatial processes and intrinsic demography. In addition, species can influence each other’s dynamics through competitive interactions. Competition can be either symmetric (i.e., both species equally affected), or asymmetric (i.e., one species experiencing a greater negative effect of the interaction than its competitor). Here, I use a theoretical model to show how symmetric and asymmetric competition influence co-fluctuation of species abundances and patterns of population synchrony in fluctuating environments. I examine spatial scales of population synchrony both within species and between competing species. Predictions from the model will be tested on data from passerine birds. Results/Conclusions: Both symmetric and asymmetric competition between species cause their abundances to be less positively correlated (or more negatively correlated) than what would be predicted from environmental effects alone. Competition can also increase the spatial scale over which species are correlated, but this effect is weak, indicating that the spatial scale of species correlations is more likely to be determined by their shared environment than by their competitive interactions. Population synchrony within each of the species is influenced by the strength of their competitor, but not by their own competitive strength. These results provide important insight into how biological communities respond to environmental fluctuations, which is becoming increasingly relevant as environmental variability increases due to global warming. Patterns of spatial correlation and population synchrony, and our ability to predict them, have implications for extinction risk and management, including design of protected areas and fisheries bycatch.
