Digital carbon accounting and spatial transition analysis for Litopenaeus vannamei aquaculture: toward data-driven low-carbon governance

Background Guided by the concept of the Great Food View and the coordinated management of ecological thresholds in fisheries, this study examines the spatiotemporal evolution and trend prediction of carbon emissions from Litopenaeus vannamei aquaculture in China. Purpose This study aims to develop an analytical framework that promotes both industrial efficiency improvement and ecological value enhancement, to inform integrated food supply system optimization and national carbon peaking strategies. Method A novel GIS–LCA spatial carbon footprint model was developed, integrating the Theil index, kernel density estimation, Moran’s I , and spatial Markov chain methods to analyze carbon emissions across ten coastal provinces from 2009 to 2023. Finding The results show that total carbon emissions have increased significantly, with steel and compound feed production as dominant sources. Regional disparities widened, forming a hierarchical pattern of “southern northern eastern” marine economic zones. The emission distribution exhibited a rightward–then-leftward shift, elongated right tails, and narrowing variance, accompanied by significant High–High and Low–Low spatial clustering. Moreover, provincial emissions displayed strong spatial continuity and a “Matthew effect” during state transitions, with potential for leapfrogging shifts. Policy Based on these spatial patterns, a multi-scale regulation strategy is proposed to promote differentiated governance and accelerate the low-carbon transformation of China’s aquaculture industry, which include optimizing region-specific emission reduction policies, strengthening interregional coordination in carbon mitigation, improving carbon emission monitoring and assessment systems, enhancing the integration of ecological protection with industrial development, and advancing low-carbon governance capacity together with residents’ well-being.