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.