气候变化对东北大西洋渔获物组成、多样性和营养级的影响

陈爽; 陈新军

doi:10.3969/j.issn.0253-4193.2020.10.010

气候变化对东北大西洋渔获物组成、多样性和营养级的影响

doi: 10.3969/j.issn.0253-4193.2020.10.010

陈爽¹,
陈新军^{1, 2, 3, 4, 5, ,}

详细信息

作者简介:
陈爽(1993-)，男，江苏省南通市人，主要从事渔业资源研究。 E-mail：1076482889@qq.com

通讯作者:
陈新军(1967-)，教授，研究方向为渔业资源。 E-mail： xjchen@shou.edu.cn

中图分类号: P714⁺.5；S932.4
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出版历程
- 收稿日期: 2018-10-20
- 修回日期: 2019-01-02
- 发布日期: 2020-12-07

Effects of climate change on catch composition, diversity of catch and mean trophic level in the Northeast Atlantic Ocean

Chen Shuang¹,
Chen Xinjun^{1, 2, 3, 4, 5
, ,}

摘要

摘要: 东北大西洋是世界上重要的捕捞海域，气候变化对该海域捕捞产生了重要的影响。本文基于联合国粮农组织所提供的1982−2016年东北大西洋渔获产量数据，对该海域渔获物组成、多样性、平均营养级及主成分变化特征进行时间序列上的分析，并结合东北大西洋海域气候、环境因子，应用广义可加模型探究渔获物组成与气候变化之间的关系。结果显示：渔获物多样性的变化总体上呈下降趋势，2002−2010年间处于较低水平；平均营养级在2002年之前呈平缓下降的趋势，2002年之后开始波动上升，相关性分析表明这两个指标与海域环境因子的变化较为相关。对渔获物组成进行主成分分析显示，第一主成份变化的方差解释率达到35.3%，且与海域气候、环境因素有较高的相关性，第一主成分变化能够较好地表征气候影响下渔获物组成变化的情况。广义可加模型分析结果显示，渔获物组成变化的影响因素按解释率由高到低分别为：海表温度、海平面高度、盐度、海冰和北大西洋涛动指数。该研究有助于认识气候变化对海洋渔业资源及其结构组成的影响。
- 东北大西洋 /
- 气候变化 /
- 渔获物组成 /
- 渔获多样性 /
- 营养级
Abstract: Global climate change has a profound impact on the world fisheries. Recently, the composition of catch in Northeast Atlantic Ocean has changed significantly. Based on the catch data in the Northeast Atlantic Ocean from 1982 to 2016 provided by the United Nations Food and Agricuture Organization, the diversity of catch, mean trophic level and the variation of principal component were analyzed in time series. Finally, combined with climate and environmental factors (sea surface temperature, SST; sea surface salinity, SSS; sea surface height, SSH; Sea Ice Concentration, SIC; North Atlantic Oscillation, NAO; Arctic Oscillation, AO; Atlantic Multidecadal Oscillation, AMO) in the Northeast Atlantic Ocean, the relationship between catches composition and climate change was explored by generalized additive model (GAM). The results showed that the diversity generally presented a declining trend, it was at a relatively low level during 2002 to 2010. The mean trophic level decreased slowly before 2002, then began to rise sharply. The correlation analysis showed that the changes of these two indicators were related to the environmental factors. The principal component analysis of catch composition showed that the variance of the first principal component was 35.3%, and it also has a close relationship with climatic and environmental factors, which could characterize the change of catch structure under the influence of climate. The results of GAM analysis showed that the orders of the contribution to structure change of catches were in sequence of SST, SSH, SSS, SIC and NAO.
- Northeast Atlantic Ocean /
- climate change /
- catch composition /
- diversity of catch /
- mean trophic level

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图 1 1982−2016年多样性指数和平均营养级变化

Figure 1. The variations of diversity index and mean trophic level during 1982 to 2016

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图 2 1982−2016年渔获物组成主成分得分年际变化

Figure 2. The variations of the principal component scores for the catch composition during 1982 to 2016

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图 3 1982−2016年东北大西洋气候、环境因素主成分得分年际变化

Figure 3. The variations of the principal component scores for the climatic and environmental factors during 1982 to 2016

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图 4 气候、环境因素对渔获物组成PC1的影响

Figure 4. Effects of climatic and environmental factors on the first principal component scores of catch composition (PC1)

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表 1 渔获物组成第1和第2主成分载荷值

Table 1. Loadings on the first and second principal components from the analysis of catch composition

种类	拉丁学名	主成分载荷值
种类	拉丁学名	PC1	PC2
大西洋鲱	Clupea harengus	−0.733	−0.223
大西洋鳕	Gadus morhua	0.236	0.811
毛鳞鱼	Mallotus villosus	0.671	−0.123
蓝鳕	Micromesistius poutassou	−0.537	−0.422
大西洋鲭	Scomber scombrus	−0.508	0.757
玉筋鱼属	Ammodytes spp	0.713	−0.192
绿青鳕	Pollachius virens	0.085	0.121
黍鲱	Sprattus sprattus	−0.816	−0.370
黑线鳕	Melanogrammus aeglefinus	−0.366	0.484
挪威长臀鳕	Trisopterus esmarkii	0.903	0.144
竹䇲鱼	Trachurus trachurus	0.315	−0.110
平鲉属	Sebastes spp	0.932	−0.034
沙丁鱼	Sardina pilchardus	0.812	−0.138
欧洲鲽	Pleuronectes platessa	0.764	0.521
牙鳕	Merlangius merlangus	0.913	0.181
欧洲无须鳕	Merluccius merluccius	−0.173	0.943
竹䇲鱼属	Trachurus spp	0.173	−0.164
魣鳕	Molva molva	0.634	0.583
格陵兰大比目鱼	Reinhardtius hippoglossoides	0.316	0.624
欧洲鳀	Engraulis encrasicolus	−0.225	0.242
长鳍金枪鱼	Thunnus alalunga	0.607	0.188
单鳍鳕	Brosme brosme	0.759	0.333
鳎	Solea solea	0.425	0.020
鳐科	Rajidae	0.703	−0.593
北极鳕	Boreogadus saida	0.086	−0.433
白斑角鲨	Squalus acanthias	0.976	0.066
鮟鱇属	Lophius spp	0.084	0.627
尖吻平鲉	Sebastes mentella	−0.842	−0.066
金平鲉	Sebastes marinus	−0.881	0.099
鮟鱇	Lophius piscatorius	−0.698	0.063
大西洋狼鱼	Anarhichas lupus	0.054	−0.133
水珍鱼属	Argentina spp	−0.749	0.102
圆鲭	Scomber colias	−0.657	0.666
条长臀鳕	Trisopterus luscus	0.690	0.093

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表 2 气候、环境因素第1和第2主成分载荷值

Table 2. Loadings on the first and second principal components from the analysis of the climatic and environmental factors

因素	主成分载荷值
因素	PC Ⅰ	PC Ⅱ
温度	0.935	0.284
盐度	0.610	0.632
海面高度	0.820	−0.086
海冰	−0.660	−0.437
北大西洋涛动指数	−0.580	0.744
大西洋年代际涛动指数	0.863	−0.183
北极涛动指数	−0.335	0.833

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表 3 气候、环境因素主成分变化与各类渔获物组成指数相关性系数

Table 3. The correlation coefficients of climatic and environmental factors principal component scores and different kinds of catch composition indexes

	多样性指数	平均营养级	PC1	PC2
PCI	−0.609**	0.623**	−0.783**	0.396
PCII	0.370	−0.225	0.382*	0.148
注：表示p<0.05下相关性显著，*表示p<0.01下相关性极显著。

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表 4 渔获物组成PC1与各气候、环境因素的GAM模型拟合

Table 4. GAM models fitted to the first principal component scores of catch composition (PC1) and climatic and environmental factors

模型因子	P值	F值	累计解释偏差/%	可解释偏差/%	AIC值
+水温	2.12×10⁻²	6.05	74.8	74.8	59.53
+盐度	1.46×10⁻⁴	9.27	81.2	6.4	59.48
+海面高度	7.10×10⁻⁵	22.08	89.2	8.0	42.65
+海冰	1.73×10⁻⁴	19.15	92.3	3.1	24.20
+北大西洋涛动	3.82×10⁻¹	1.14	94.3	2.0	16.84
+大西洋年代际涛动	6.83×10⁻¹	0.17	94.4	0.1	18.82
+北极涛动	4.44×10⁻¹	0.60	94.6	0.2	19.31

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