Ensemble predictions of high trophic-level fish distribution and species association in response to climate change in the coastal waters of China

Abstract

As climate change shifts marine ecosystems, understanding distribution changes of high trophic-level fish is critical for ecological and fisheries management. This study examined the distribution changes of five high trophic-level fish species in China's coastal waters from 1990 to 2023, using species distribution models (SDMs) combined in an ensemble modeling framework to predict future trends under RCP26 and RCP85 scenarios. The ensemble approach integrated multiple SDM algorithms to reduce uncertainty and improve predictive accuracy. The analysis incorporated ecological metrics like niche breadth, niche overlap, and species association indices to assess habitat suitability and interspecies interactions. The ensemble model performed well, particularly for monkfish (Lophius litulon) and whitespotted conger (Conger myriaster), both of which are demersal species. Key environmental factors influencing habitat distribution included bottom water temperature and depth. Under climate change scenarios, the spatial niche breadth of only the largehead hairtail (Trichiurus lepturus) was expected to increase, while the niche breadth of the other species was projected to decrease, especially under high emissions. Fish habitats were predicted to shrink under future climate scenarios, especially under high emissions, with significant losses projected by 2100, ranging from −47 % for the Slender lizardfish (Saurida elongata) to −24 % for the Monkfish, although habitat suitability was expected to improve in southern coastal areas and near the Korean Peninsula. This study emphasizes the profound effects of climate change on the distribution and ecological niches of high trophic-level fish, offering insights for future fisheries management and climate adaptation strategies.