• 技术与方法 •

### 零膨胀模型在珍稀鱼类资源时空分布预测中的应用——以长江口刀鲚为例

1. 1上海海洋大学海洋生态与环境学院， 上海 201306; 2上海海洋大学海洋科学学院， 上海 201306；3上海市水生野生动植物保护研究中心， 上海 200092；4国家远洋渔业工程技术研究中心， 上海 201306；5大洋渔业资源可持续开发教育部重点实验室， 上海 201306）
• 出版日期:2020-09-10 发布日期:2021-03-10

### Application of zero-inflated model in predicting the distribution of rare fish species: A case study ofCoilia nasus in Yangtze estuary, China.

ZHAO Jing1，2, LIU Xiao-xue2, WU Jian-hui3, HAN Dong-yan2,4,5, TIAN Si-quan2,4,5, MA Jin1*

1. (1College of Marine Ecology and Environment, Shanghai Ocean University, Shanghai 201306, China; 2College of Marine Sciences, Shanghai Ocean University, Shanghai 201306, China; 3 Center for Protection and Research ofAquaticWild Living Plants and Animals in Shanghai, Shanghai 200092; 4National Distant water Fisheries Engineering Research Center, Shanghai 201306, China; 5Key Laboratory of Sustainable Exploitation of Oceanic Fisheries Resources, Ministry of Education, Shanghai 201306, China).
• Online:2020-09-10 Published:2021-03-10

Abstract: Species distribution model has been widely used to estimate the habitat distribution of fishery resources. For rare fish species, the excessive zero- values in dataset is an important issue to be considered in the prediction of their spatiotemporal distribution. Zero-inflated model would be an effective way to solve this problem. With the survey data of Coilia nasusresources collected in the Yangtze estuary from 2009 to 2016, zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) models were used to establish the relationship between the density of Coilia nasus and the environmental factors. The optimal model was selected to predict the density distribution of Coilia nasus in the Yangtze estuary in all seasons of 2017. In the first part of the results of zero-inflated models, water temperature had a significant positive effect on the occurrence of non-zero resource density of Coilia nasus.In the second part of results of zero-inflated models, longitude had a significant negative effect on Coilia nasusdensity and water temperature had a significant positive effect on Coilia nasusdensity. The optimal ZINB model has better fitting and prediction ability than the optimal ZIP model. The predicted value of Coilia nasus density was gradually decreasing from west to east, with a consistency spatial distribution between the predicted and observed value. The predicted value of Coilia nasus density showed a temporal distribution: summer> spring> autumn> winter, consistent with the seasonal variation of water temperature. Our results provide reference for the studies of the relationship between rare fishes and environmental factors and related studies on spatial and temporal distribution of rare fishes.