AUTHOR=Gao Li , Bai Xuan , Wang Yingbin TITLE=Dynamic prediction of the ricker-type model of Portunus trituberculatus on the basis of marine environmental factors JOURNAL=Frontiers in Marine Science VOLUME=9 YEAR=2022 URL=https://www.frontiersin.org/journals/marine-science/articles/10.3389/fmars.2022.850317 DOI=10.3389/fmars.2022.850317 ISSN=2296-7745 ABSTRACT=

Based on the data of Portunus trituberculatus and environmental factors in the northern East China Sea from 2001 to 2014, a Ricker-type model was used in investigating the effects of environmental factors on P. trituberculatus recruitment. The main environmental factors include the area of red tide, sea level height, sea surface salinity, and typhoon landing times with wind forces above 6 near the center. We assumed that the distributions of environmental data vary and selected AIC, BIC, and maximum likelihood as criteria for the selection of the best distribution of each environmental factor. Environmental factor data were simulated according to the distributions (repeated 10,000 times). The Ricker model with ln-linear environmental impact was used in predicting the recruitment of P. trituberculatus under different combinations of various environmental factors for a given spawning stock biomass. Results show that the predicted recruitment abundance most likely appears between 10 × 103 and 15 × 103 million individuals, and the probability is approximately 39.56%. The environmental condition in which the four environmental factors have the best and worst combinations was also simulated. Our results indicate that red tide and typhoon are the two dominant factors affecting the recruitment of P. trituberculatus. The results show that at the 5% significance level, if the recruitment is less than 6.394 × 103 million individuals, then it is probably under a bad environment condition. Similarly, if recruitment is more than 28.305 × 103 million individuals, then it is probably under a good environmental condition. This study provides a technical reference for the scientific prediction and management of P. trituberculatus and other fishery resources subjected to various environmental conditions.