Quantifying competition between two demersal fish species from spatiotemporal stomach content data

Abstract

AbstractCompetition is challenging to quantify in natural systems and inference is often made on indirect patterns of potential competition, such as trends in population trajectories and overlap in spa-tiotemporal distribution and resource use. However, these indicators are not direct measures of fitness, nor do they say if the contested resource is limited in supply, which are key features of competition. Here we combine stomach content and biomass density data from scientific bottom trawl surveys to evaluate if competition is occurring between two dominant demersal fish species in the southern Baltic Sea: Atlantic cod (Gadus morhua) and flounder (Platichthys spp). We use multivariate generalized linear latent variable models (GLLVMs) to quantify diet similarities across the domain, diet overlap indices on relatively small spatial scales to test if predator density drives diet overlap, and spatiotemporal GLMMs fit to prey weights in individual predators to evaluate the effects of local biotic and abiotic covariates. We find clear dietary clusters by species and size. The latter is especially pronounced in cod, which shift from benthic to pelagic prey at around 30 cm. Overall, the dietary overlap is low and unaffected by predator density. However, signs of resource partitioning to reduce interspecific competition is evident in the most local scale anal-ysis. As flounder densities increase, small and large cod tend to feed less on the isopodSaduria entomon— an important prey species. However, the benthic prey weight in small cod, and benthic and total prey weight in large cod, are not affected by flounder densities. We do not find evidence of intraspecific competition. Our results suggest that interspecific competition is not limiting cod feeding rates but affects their diet composition. These findings illustrate the importance of local scale processes when inferring competition from stomach content data. Quantifying ecological interactions is important for increasing our understanding of changes in the productivity of pop-ulations, and for developing ecosystem-based management.