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

doi:10.13292/j.1000-4890.202009.028

生态学杂志 ›› 2020, Vol. 39 ›› Issue (9): 3155-3163.doi: 10.13292/j.1000-4890.202009.028

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

赵静^1,2,柳晓雪²,吴建辉³,韩东燕^2,4,5,田思泉^2,4,5,马金^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 Jing^1，2, LIU Xiao-xue², WU Jian-hui³, HAN Dong-yan^2,4,5, TIAN Si-quan^2,4,5, MA Jin^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

摘要/Abstract

摘要： 物种分布模型在估计渔业资源栖息分布中已有广泛应用，但在珍稀鱼类资源的时空分布预测方面，数据零值过多的情况是模型选择时应考虑的重要问题，零膨胀模型是解决此类问题的有效手段。根据2009—2016年每个季度在长江口采集的刀鲚资源量与环境调查数据，运用零膨胀泊松(zero-inflated Poisson, ZIP)模型和零膨胀负二项(zero-inflated negative binomial, ZINB)模型建立了长江口刀鲚资源密度与水温等环境因子之间的关系，并运用最优模型对2017年各季节长江口刀鲚资源密度分布进行预测。结果表明：在零膨胀模型结果的第一部分，水温对刀鲚资源密度非零值的发生有显著正向影响；零膨胀模型结果的第二部分显示，经度与刀鲚资源密度的大小呈显著负相关，水温对刀鲚资源密度的大小有显著正向影响；相比最优ZIP模型，最优ZINB模型对数据拟合较好，并具有较好的预测能力；最优模型显示，刀鲚资源密度的预测值在空间上呈现自西向东逐渐减小的趋势，预测结果与实际观测值存在空间分布的一致性；在时间上呈现夏季>春季>秋季>冬季的分布格局，这与水温的季节变化趋势一致。本研究将两种零膨胀模型应用于珍稀鱼类的时空分布预测，可为珍稀鱼类资源与环境之间的关系及其时空分布的研究提供参考。

关键词: 刀鲚, 零膨胀模型, 计数数据, 长江口

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.

Key words: Coilia nasus, zero-inflated model, count data, the Yangtze estuary.

赵静, 柳晓雪, 吴建辉, 韩东燕, 田思泉, 马金. 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[J]. 生态学杂志, 2020, 39(9): 3155-3163.

ZHAO Jing, LIU Xiao-xue, WU Jian-hui, HAN Dong-yan, TIAN Si-quan, MA Jin. Application of zero-inflated model in predicting the distribution of rare fish species: A case study ofCoilia nasus in Yangtze estuary, China.[J]. Chinese Journal of Ecology, 2020, 39(9): 3155-3163.

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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

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

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