基于GAM 的吉尔伯特群岛海域黄鳍金枪鱼栖息地综合指数

为了可持续利用黄鳍金枪鱼(Thunnus albacares)资源,本文利用2009年10月～12月吉尔伯特群岛海域海上实测的34个站点海洋环境垂直剖面数据,黄鳍金枪鱼渔获率数据,应用广义加性模型(generalized additive model,GAM) 进行建模,预测渔获率,并通过wilcoxon检验来判断预测渔获率与名义渔获率是否存在显著相关性。根据预测渔获率估算黄鳍金枪鱼的栖息地综合指数(IHI),通过对各水层IHI均值分析和Pearson相关系数,判断该方法的预测能力。使用2010年11月～2011年1月在吉尔伯特群岛海域实测的16个站点40～80m水层和0～240m水体的环境数据,验证模型。结果表明：(1)拟合的各水层的IHI值分布各不相同,各水层中影响黄鳍金枪鱼分布的因子各不相同,黄鳍金枪鱼主要栖息在40～120m水层；(2)2010年数据验证结果表明,GAM模型的预测能力较好；(3)GAM在筛选影响黄鳍金枪鱼分布的因子时比较有效,能反应黄鳍金枪鱼渔获率与环境因子之间的非线性关系；(4)可通过GAM建立IHI指数模型来分析大洋性鱼类栖息地的空间分布。

An Integrated Habitat Index for Yellowfin Tuna in Waters near Gilbert Islands Based on GAM

The aim of this study is to contribute to the sustainable utilization of yellowfin tuna (Thunnus albacares) resources. In this study, Generalized Additive Model (GAM) was applied to develop the integrated habitat index (IHI) models on the basis of the data which were collected in waters near Gilbert Islands from October, 2009 through December, 2009. The profiles of environmental variables and the yellowfin tuna catch rate data were collected at 34 sites. These models were used to predict the corresponding potential catch rate. The Wilcoxon test was used to test if there were significant differences between the predicted catch rates predicted by the models and the nominal catch rates. The integrated habitat index (IHI) in different water strata of yellowfin tuna were estimated by the predicted catch rate predicted by the models. Comparing the nominal CPUE and the average integrated habitat index (IHI) in different water strata, the predicted power of the models were evaluated. The correlation coefficients between the nominal CPUE and the average integrated habitat index (IHI) in different water strata were calculated. This correlation coefficient was also used to evaluate the prediction power of the models. In addition, the Gilbert Islands survey data in 16 sites from Nov. 2010 through Jan. 2011 were used to verify the effectiveness of the models. These data were input into the models for water stratum of 40-80 m and the whole water bin (0 ~ 240 m), and the IHIs of the yellowfin tuna were estimated. The results showed that: (1) The IHI distributions of different water stratum were different from each other. The environmental variables which influenced the distribution of yellowfin tuna were different from the different water strata. The yellowfin tuna mainly distributed in the water stratum of 40-120 m; (2) The prediction power of the models was good on the basis of the verification data obtained in 16 sites from Nov. 2010 through Jan. 2011; (3) GAM is suitable for the environmental variable selectivity, which influenced the distribution of yellowfin tuna, and shows the nonlinear relationship between the environmental variable and the catch rate; (4) GAM can be used to study the spatial distribution of the pelagic fish by building the IHI model.