基于HMSC模型分析山东近海夏季底层鱼类的环境适应性与种间关系

徐天姮; 张崇良; 薛莹; 徐宾铎; 纪毓鹏; 任一平

doi:10.12284/hyxb2023106

基于HMSC模型分析山东近海夏季底层鱼类的环境适应性与种间关系

doi: 10.12284/hyxb2023106

徐天姮^{1, 2,},
张崇良^{1, 2, ,},
薛莹^{1, 2},
徐宾铎^{1, 2},
纪毓鹏^{1, 2},
任一平^{1, 2}

1.
中国海洋大学水产学院，山东青岛 266003
2.
海州湾渔业生态系统教育部野外科学观测研究站，山东青岛 266003

基金项目: 国家重点研发计划（2022YFD2401301）。

详细信息

作者简介:
徐天姮（2000-），女，山东省枣庄市人，主要从事物种分布模型研究。E-mail：itisxuth@163.com

通讯作者:
张崇良，副教授，主要从事渔业资源评估与生态系统模拟。E-mail：zhangclg@ouc.edu.cn

中图分类号: S932.4；P714⁺.5
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出版历程
- 收稿日期: 2023-02-03
- 修回日期: 2023-04-20
- 网络出版日期: 2023-08-24
- 刊出日期: 2023-08-31

Environmental adaptability and interspecific relationships of demersal fishes in the coastal waters of Shandong in summer explored by HMSC models

Xu Tianheng^{1, 2
,},
Zhang Chongliang^{1, 2
, ,},
Xue Ying^{1, 2},
Xu Binduo^{1, 2},
Ji Yupeng^{1, 2},
Ren Yiping^{1, 2}

1.
Fisheries College, Ocean University of China, Qingdao 266003, China
2.
Field Observation and Research Station of Haizhou Bay Fishery Ecosystem, Ministry of Education, Qingdao 266003, China

摘要

摘要: 传统的物种分布模型很少将种间关系纳入建模框架中，妨碍了对物种栖息分布的准确预测。近年来联合物种分布模型（JSDMs）越来越受到关注，但在海洋领域实际应用仍较为缺乏。本研究根据2017年夏季山东近海底拖网调查数据，结合水深、底层水温和底层盐度等环境数据，采用物种群落层次模型（HMSC）方法研究了山东近海17种底层鱼类与环境因素之间的关系和种间相关性。本研究根据生物与环境之间的线性或非线性关系以及随机效应构建了5种HMSC，并利用广泛适用信息准则（WAIC）等指标以及交叉验证方法，评价了模型拟合程度和预测效果。结果表明，最优模型为包含随机效应的非线性模型（模型五），非线性模型优于线性模型，且在模型中考虑种间关系能明显地提高模型的拟合效果。温度是影响山东近海底层鱼类分布的主要因素，占平均可解释方差的51.4%，其次是水深和随机效应，分别占35.7%和12.8%。山东近海大部分底层鱼类与水深存在显著线性正相关关系，而与水温存在显著的非线性关系。底层鱼类种间具有显著相关性，按其相关性的正负可大致分为3组，表明种间关系在预测物种分布方面的作用不容忽视。本研究建议，在建模中应同时考虑非生物因素和生物之间的相互关系，研究结果为预测渔业资源栖息分布提供了重要参考。
- 联合物种分布模型（JSDMs） /
- 物种群落层次模型（HMSC） /
- 种间关系 /
- 模型比较 /
- 交叉验证
Abstract: Traditional species distribution models rarely incorporate interspecific relationships into the modeling framework, which hinders their predictions of habitat distributions. In recent years, joint species distribution models (JSDMs) have drawn increasing attentions, but their practical applications remain rare in the marine realm. In this study, we used the HMSC (hierarchical modelling of species communities) method to study their relationships between 17 demersal fish species and environmental factors and the interspecific correlation. The model was built on the basis of bottom trawling data collected in the coastal waters of Shandong in summer, 2017, including the environmental data of water depth, bottom water temperature and bottom water salinity. Five variants of HMSC models were developed with respect to the linear or nonlinear relationships between species and the environmental variables and the exists of random effects, and WAIC and other indicators as well as cross-validation were used to evaluate the performances of fitting and prediction of these models. The results showed that the optimal model was the one incorporating nonlinear relationships and random effects (Model 5). The nonlinear models were generally superior to the linear models, and including the interspecific relationships in the model could improve model fitting performances. Temperature was the main factor influencing the distribution of demersal fishes in the coastal waters of Shandong, accounting for 51.4% of the mean explained variance, followed by water depth and random effects, which accounted for 35.7% and 12.8% explained variance, respectively. There were significant linear positive correlations between most demersal fishes and water depth, and significant nonlinear relationships with water temperature. There were significant interspecific correlations among the demersal fishes, which could be roughly divided into three groups according to the sign of the correlations, indicating that the interspecies relationships played an important role in shaping species distributions. This study suggested that the abiotic factors and biotic factors should be integrated in species distribution modeling, and our results might provide a guideline for the prediction of habitat distribution of fishery resources.
- joint species distribution model (JSDMs) /
- hierarchical modelling of species communities (HMSC) /
- interspecies relationship /
- comparison of models /
- cross validation

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图 1 山东近海底拖网渔业资源调查站位

Fig. 1 Bottom trawl survey stations of fishery resources in the coastal waters of Shandong

下载: 全尺寸图片幻灯片

图 2 山东近海主要底层鱼类5个HMSC模型的R²比较

箱线图表示使用交叉验证的模型预测性的R²；红色十字表示模型拟合度的R²；横坐标为17个物种（表1）

Fig. 2 R²comparison of five HMSC models of main demersal fishes in the coastal waters of Shandong

The boxplots represent R²in model prediction using cross validation; the red cross represents R² in model fitting; the x-coordinate denotes 17 species (Tab.1)

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图 3 山东近海17种底层鱼类解释率的方差划分图

Fig. 3 Variogram of interpretation rates of 17 species of bottom fishes in the coastal waters of Shandong

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图 4 物种对环境因子响应的显著性

纵坐标分别代表17种底层鱼类（表1）；横坐标中C1为截距，C2为水深对应的回归系数，C3和C4分别为SBT一次项和二次项对应的β参数；红色表示物种与环境具有显著正相关，蓝色表示物种与环境具有显著负相关，白色表示物种与环境没有显著相关性

Fig. 4 Significance of species responses to environmental factors

The y-coordinate represents 17 species of bottom fishes respectively (Tab.1); in the x-coordinate, C1 is the intercept, C2 is the regression coefficient corresponding to the water depth, C3 and C4 are the β parameters corresponding to the primary and secondary terms of SBT, respectively; red indicates a significant positive correlation between species and environment, blue indicates a significant negative correlation between species and environment, white indicates no significant correlation between species and environment

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图 5 山东近海17种底层鱼类的种间关系

红色表示物种之间有正相关性；蓝色表示物种之间有负相关性

Fig. 5 Interspecific relationships among 17 demersal fishes in the coastal waters of Shandong

Red indicates a positive correlation between species; blue indicates a negative correlation between species

下载: 全尺寸图片幻灯片

表 1 山东近海17种主要底层鱼类

Tab. 1 The major 17 species of demersal fishes in the coastal water of Shandong

编号	物种	学名	平均标准化生物量/ (kg·h⁻¹)
S1	方氏云鳚	Pholis fangi	2.312
S2	大泷六线鱼	Hexagrammos otakii	1.477
S3	小黄鱼	Pseudosciaena polyactis	0.643
S4	星康吉鳗	Conger myriaster	0.563
S5	六丝钝尾虾虎鱼	Chaeturichthys hexanema	0.313
S6	短吻红舌鳎	Cynoglossus joyneri	0.049
S7	小眼绿鳍鱼	Chelidonichthys spinosus	2.543
S8	细纹狮子鱼	Liparis tanakae	5.793
S9	细条天竺鲷	Apogonichthys lineatus	0.392
S10	矛尾虾虎鱼	Chaeturichthys stigmatias	0.162
S11	吉氏绵鳚	Enchelyopus gilli	0.332
S12	白姑鱼	Argyrosomus argentatus	0.993
S13	长蛇鲻	Saurida elongata	0.341
S14	高眼鲽	Cleisthenes herzensteini	0.457
S15	皮氏叫姑鱼	Johnius belangeri	0.051
S16	瓦氏鴨	Callionymus valenciennei	0.262
S17	黄鮟鱇	Lophius litulon	4.993

下载: 导出CSV

表 2 山东近海主要底层鱼类栖息分布的最优模型

Tab. 2 Optimal models for the habitat distribution of main bottom fishes in the coastal waters of Shandong

模型类型	物种与环境的关系	是否存在随机效应	环境变量
模型一	线性	否	Depth+SBT
模型二	非线性	否	Depth+SBT+SBT²
模型三	无	是	1
模型四	线性	是	Depth+SBT
模型五	非线性	是	Depth+SBT+SBT²

下载: 导出CSV

表 3 山东近海主要底层鱼类5个HMSC模型的参数比较

Tab. 3 Parameter comparison of five HMSC models for the main demersal fishes in the coastal waters of Shandong

模型类型	WAIC	ess 平均 (β)	psrf 平均 (β)	ess 平均 ($\varOmega $)	psrf 平均 ($\varOmega $)
模型一	无	2 073.04	1.00
模型二	无	2 032.82	1.00
模型三	17 876.67			833.14	1.86
模型四	2 107.11	1 935.82	1.00	1 202.29	1.01
模型五	1 817.33	2 035.90	1.01	1 943.30	1.00

下载: 导出CSV

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