Predicting Ecological Distribution of the Toxic Dinoflagellate Alexandrium minutum in China Sea Using Ecological Niche Modeling
作者机构:School of Marine SciencesNanjing University of Information Science and TechnologyNanjing 210044China Third Institute of OceanographyMinistry of Natural ResourcesXiamen 361005China Key Laboratory of Marine Biogenetic ResourcesThird Institute of OceanographyMinistry of Natural ResourcesXiamen 361005China
出 版 物:《Journal of Ocean University of China》 (中国海洋大学学报(英文版))
年 卷 期:2023年第22卷第4期
页 面:1119-1128页
核心收录:
基 金:supported by the National Key Research and the Development Program of China(No.2019YFE 0124700) the China National Key Research and Development Program(No.2022YFC3106002) the National Natural Science Foundation of China(No.U1901215) the Startup Foundation for Introducing Talent of NUIST(No.2020r028)
主 题:Alexandrium minutum MaxEnt,habitat suitability environmental variable potential distributions
摘 要:Alexandrium minutum from the China Sea produces a range of toxins and causes damage to the local ecosystems and *** is essential to understand environmental factors affecting potential *** distributions of *** in the China Sea were predicted based on maximum entropy modeling,and dominant environmental variables were studied through analyses of variable contributions and response *** results showed that highly suitable areas were mainly located in the southwest of the Yellow Sea,the Laizhou Bay,and north of Haizhou *** coast of the South China Sea was predicted as a low-suitability area,and the coast of the East China Sea as an unsuitable *** temperature of the coldest month(T_min)had the largest drop in permutation importance but a low percent *** probability of presence of *** increased with increasing concentration of nitrate(NO3−)and annual mean temperature(T_ann)over a wide range of *** response curves decreased with increasing concentration of phosphate(PO43−)and ratio of NO_(3)^(−)to PO_(4)^(3−)(N_P_ratio)when PO_(4)^(3)−is above 0.049μmolL^(-1) and N_P_ratio above 4,indicating that low values of PO_(4)^(3−) concentration and N_P_ratio favour the occurrence of *** a predictor,the variance of annual temperature(T_Var)had the highest percent contribution and ***_(4)^(3−) was predicted to have much more information than the other variables,and exhibited the second largest drop in permutation importance and percent *** T_Var and PO_(4)^(3−) are the most important dominant predictor variables.