期刊
JOURNAL OF OCEAN UNIVERSITY OF CHINA
卷 22, 期 4, 页码 1119-1128出版社
OCEAN UNIV CHINA
DOI: 10.1007/s11802-023-5422-y
关键词
Alexandrium minutum; MaxEnt, habitat suitability; environmental variable; potential distributions
类别
This study predicts the potential distribution of Alexandrium minutum in the China Sea using maximum entropy modeling. The results show highly suitable areas in the southwest of the Yellow Sea, Laizhou Bay, and north of Haizhou Bay, while the coast of the South China Sea is predicted as low-suitability and the coast of the East China Sea as unsuitable. The presence of A. minutum is influenced by mean temperature of the coldest month, nitrate concentration, and annual mean temperature. Low phosphate concentration and N_P_ratio favor the occurrence of A. minutum.
Alexandrium minutum from the China Sea produces a range of toxins and causes damage to the local ecosystems and aquaculture. This is essential to understand environmental factors affecting potential distribution. Potential distributions of A. minutum in the China Sea were predicted based on maximum entropy modeling, and dominant environmental variables were studied through analyses of variable contributions and response curves. The results showed that highly suitable areas were mainly located in the southwest of the Yellow Sea, the Laizhou Bay, and north of Haizhou Bay. The coast of the South China Sea was predicted as a low-suitability area, and the coast of the East China Sea as an unsuitable area. Mean temperature of the coldest month (T_min) had the largest drop in permutation importance but a low percent contribution. The probability of presence of A. minutum increased with increasing concentration of nitrate (NO3-) and annual mean temperature (T_ann) over a wide range of them. The response curves decreased with increasing concentration of phosphate (PO43-) and ratio of NO3- to PO43- (N_P_ratio) when PO43- is above 0.049 mu mol L-1 and N_P_ratio above 4, indicating that low values of PO43- concentration and N_P_ratio favour the occurrence of A. minutum. As a predictor, the variance of annual temperature (T_Var) had the highest percent contribution and gains. PO43- was predicted to have much more information than the other variables, and exhibited the second largest drop in permutation importance and percent contribution. The T_Var and PO43- are the most important dominant predictor variables.
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