Impacts of trophic interactions on the prediction of spatio-temporal distribution of mid-trophic level fishes

Abstract

Habitat models have gradually become important tools for assessing and predicting the spatio-temporal distribution of marine organisms. Species are closely associated with each other through biological processes such as predation, competition and mutualism. Neglecting the interaction between species might lead to biased prediction of species distributions, especially for the mid-trophic level species. In this study, the performance of three different kinds of habitat models, i.e., single species distribution model (Generalized linear regression, GLM), ensemble species distribution model (ESDM), and joint species distribution model (JSDM), were evaluated and compared to investigate how trophic interactions will impact the spatio-temporal distributions of mid-trophic fish species in the central and southern Yellow Sea. Potential variations in the distribution and abundance of five mid-trophic level fishes in the central and southern Yellow Sea under climate changes were also analyzed. Results showed that mutually associations derived from food web could explain a large proportion of the positive interactions among species. It was proved that JSDMs could reduce the bias in the estimation of abundance for mid-trophic level fishes by incorporating species trophic interactions, especially for species with low prevalence. The geographic center of gravity of five fishes showed a northward shift of less than 20 km under ocean warming scenarios. Ignoring species trophic interactions would result to overestimate or underestimate abundance of species under climate changes. The abundance of one species (Big head croaker Collichthys lucidus) would decrease, while the other four species would increase because of their different response to climate changes. This study is expected to improve our understanding of the importance of species interactions in predicting the spatio-temporal distribution of species, and will provide guidance for the spatial management strategies of fisheries resources under future climate changes.