Data From: Applying empirical dynamic modeling to distinguish abiotic and biotic drivers of population fluctuations in sympatric fishes

Fluctuations in the population abundances of interacting species are widespread. Such fluctuations could be a response to abiotic factors, biotic interactions, or a combination of the two. Correctly identifying the drivers are critical for effective population management. However, such effects are not always static in nature. Nonlinear relationships between abiotic factors and biotic interactions make it difficult to parse true effects. We used a type of nonlinear forecasting, empirical dynamic modeling, to investigate the context-dependent species interaction between a common fish (threespine stickleback) and an endangered one (northern tidewater goby) in a fluctuating environment: a central California bar-built estuary. We found little evidence for competition, instead both species largely responded independently to abiotic conditions. Stickleback were negatively affected by sandbar breaching. The strongest predictor of tidewater goby abundance was stickleback abundance; however, this effect wasn't a uniform negative effect of stickleback on goby as would be hypothesized under interspecific competition. The effect of stickleback on gobies was positive, though it was temporally restricted. Tidewater goby abundance in the summer was strongly positively correlated to stickleback abundance in the spring, which represents an offset in the reproductive and recruitment peaks in the two species that may help minimize competition and promote coexistence. Our study demonstrates how empirical dynamic modeling can be applied to understand drivers of population abundance in putative competitors and inform management for endangered species.