Global warming presents urgent challenges for tilapia aquaculture. This study introduces a tailored loss function to assess long-term impacts under extreme drought, using historical drought data in China as a baseline. The TaiESM1 climate model within the CMIP6 framework is applied to project future conditions under SSP245, SSP370, and SSP585 scenarios, focusing on Guangdong Province (2024–2100). The results indicate a general decline in the frequency of extreme droughts across all scenarios. Under SSP245, technological advancements combined with reduced drought risk may boost yields of tilapia aquaculture of Guangdong to 2.369–2.418 million tons by 2100. In SSP370 and SSP585, while humidity increases, drought risk reduction is less pronounced, resulting in marginally lower yields (2.285–2.408 and 2.300–2.416 million tons, respectively). When a unified loss parameter is applied, projected yields exhibit a U-shaped trend across all SSP scenarios, reaching a minimum under SSP370 in the mid-century period before recovering toward the end of the century, driven by scenario-dependent marginal responses of production to changes in extreme drought risk, highlighting the nonlinearity of climate impacts driven by complex climatic factors and socioeconomic interactions. These findings are subject to uncertainties associated with the use of a single climate model and the simplified representation of drought impacts in the loss-function framework.

Climate change, especially extreme weather events, has significantly heightened the vulnerability of fisheries production supply chains. This study firstly investigates the input-driven climate risks through intermediate goods trade and their indirect impacts on China’s fisheries sector and constructs the Climate Risk-Trade-Production Model (CRTPM). Key findings include: (1) The input-driven climate risk indicator for China’s fisheries sector has increased over the period 1995–2020, with Brazil, Canada, the United States, Japan, South Korea, and Russia as major contributors. (2) From 1995 to 2020, rising climate risk index in Brazil and Canada negatively affected China’s fisheries output, with a 1% increase in climate risk index resulting in production declines of 0.173% and 0.367%, respectively. (3) In contrast, a reduction in the climate risk index in the United States and Japan lowered intermediate goods prices, boosting China’s output by 0.934% and 0.172%, respectively, for every 1% decrease in the climate risk index. (4) Climate risk index in South Korea and Russia, while initially increasing, eventually stabilized, having minimal impact on China’s fisheries production. It is the importance of monitoring extreme weather events to mitigate the economic vulnerabilities of China’s fisheries.

Against the backdrop of global warming and an increase in extreme weather events, the freshwater aquaculture industry, which is highly dependent on environmental conditions, faces severe challenges. As the world’s largest producer of freshwater aquaculture, the stability of China’s production is crucial for ensuring national food security and rural livelihoods. This study utilizes provincial panel data from China (2007–2023) and employs the HP filter separately for each province to construct a “climate-induced output” indicator. A panel data model is then established to examine the impact and transmission mechanisms of extreme climate risks on freshwater aquaculture output. The findings reveal the following: (1) Climate risks exert a significant negative impact on freshwater aquaculture production, with extreme low temperatures, droughts, and extreme rainfall having particularly pronounced effects. (2) Natural disasters play a partial mediating role between extreme climate and output, accounting for approximately 26.35% of the total effect. (3) From an overall perspective, both increased labor productivity and greater operational scale can significantly mitigate the negative impacts of climate risks. This study provides empirical evidence to inform policies on optimizing regional aquaculture layouts, enhancing climate resilience, and formulating adaptive strategies.

As global climate change intensifies and resources become increasingly scarce, China’s sustainable development of freshwater aquaculture faces unprecedented challenges. This study utilizes panel data from 31 provincial-level regions in mainland China (2000–2023) and innovatively constructs a multi-stage sequential modified slack-based measure data envelopment analysis (MSBM-DEA) model. By endogenizing extreme climate factors within the aquaculture production efficiency framework, this study reveals the dynamic impact of climate change on freshwater aquaculture total factor productivity (TFP). The finding indicates that extreme climate events reduce freshwater aquaculture TFP by 1.66% and technical advancement by 18.9%. The impact varies regionally, with eastern provinces experiencing a maximum TFP decline of 3.1%, while western provinces face a significant drop of 5.2%. The eastern region, supported by technology and policy, shows a relatively strong recovery capacity, whereas the western region suffers more due to resource scarcity and technical lag. To tackle these challenges, this study recommends establishing a climate-adaptive TFP monitoring framework and promoting a dual-driven model of technical innovation and efficiency enhancement to bolster fisheries’ climate resilience. This research provides valuable decision making support for climate adaptation strategies in China’s freshwater aquaculture and serves as empirical evidence and theoretical guidance for other climate-vulnerable regions globally.

Freshwater aquaculture in China has expanded rapidly in recent decades, raising growing concerns about its environmental sustainability. However, the relationship between industrial agglomeration and environmental efficiency in freshwater aquaculture remains insufficiently understood. Using panel data from 18 major freshwater aquaculture provinces in China from 2009 to 2023, this study investigates the nonlinear effects of industrial agglomeration on environmental efficiency. Environmental efficiency is evaluated using a Global Super-SBM model incorporating undesirable outputs, while industrial agglomeration is measured by the location quotient index. A two-way fixed-effects model is employed for empirical estimation. The results reveal a significant inverted U-shaped relationship between industrial agglomeration and environmental efficiency, with a turning point at an agglomeration level of 2.519. Moderate agglomeration improves environmental efficiency through economies of scale and technology diffusion, whereas excessive agglomeration generates crowding effects that reduce efficiency. Further mechanism analysis shows that technology diffusion, proxied by the number of trained fishermen, plays a significant mediating role in this relationship. This study provides new empirical evidence on the nonlinear environmental effects of industrial agglomeration in freshwater aquaculture and offers policy implications for optimizing industrial spatial layout and developing differentiated environmental regulations to support the green and sustainable development of the sector.