Abstract

The vigorous development of marine fisheries carbon sinks (MFCS) has become a momentous pathway to mitigate global warming and effectively cope with the climate crisis. Deservedly, based on clarifying mechanism of carbon sequestration, this paper designs a research paradigm for predicting and evaluating the potential of MFCS. Specifically, a novel nonlinear grey Bernoulli model, namely MFCSNGBM(1,1), is proposed by innovatively mining the original data law through adaptive cumulative series and introducing the compound Simpson formula to optimize background values. More precisely, we utilize a heuristic Grey Wolf Optimization algorithm to find the best power index, which enhances the adaptability. To prove usefulness and robustness of MFCSNGBM(1,1) model, yields of seven common shellfishes (oyster, clam, mussel, scallop, razor clam, bloody clam, and snail) and three main algae (kelp, pinnatifid undaria, and laver) are predicted and compared with six competing models. Based on prediction results, new model has the most accurate predictions, with all prediction errors being <10 %, and thus can achieve effective prediction of shellfish and algae production from 2022 to 2025. Further, the capacity and potential of MFCS in China are scientifically evaluated using a removable carbon sink model, considering various yield levels and biological parameters of shellfish and algae. The assessment results show that during the sample period, China's marine fisheries carbon sinks steadily increased with an annual growth rate of 57,000 tons. From 2022 to 2025, with support of policy of MFCS and improvement of disaster prevention and mitigation capacity, the potential of MFCS will be further released. The growth rate of MFCS will be increased to 94,000 tons per year, and its overall scale is expected to reach 2,198,245 tons by 2025, equivalent to fixing 8.06 million tons of CO2. The carbon sink's economic value is significantly estimated to be over 400 billion yuan.

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