Simulation of climate warming and agricultural land expansion for sustainable lake fish catch in high-latitude agricultural regions

Abstract

Global sustainable fisheries play an important role towards achieving the UN Sustainable Development Goals. However, to the best of our knowledge, previous studies have mainly focused on the effects of climate and land use change on fish catch, lacking a systematic understanding of the driving mechanisms and restriction threshold value, especially in high-latitude lakes. In this study, a novel approach that combined Bayesian Modeling (BNM) with remote sensing was developed to identify the drivers and determine the threshold of climate warming and agricultural land expansion. Our results demonstrate that air temperature (ATP) and agricultural land use (ALU) are key factors resulting in the reduction of fish catch, while relative humidity index (RHI) may only play a minor role. Compared with the mean value of the fish catch between 2004 and 2019, increasing 2.5 °C would result in significant decrease in the fish catch. The increasing of 14.41% expansion of agricultural land use would also lead to a significant decline in the fish catch. The purposed multi-dimensional water management strategies that can balance the economic development and ecosystem health in terms of agri-food system towards achieving a blue transformation and improving fisheries management. The framework we developed in this study can also be applied in other similar regions globally.