Relationship between species diversity and biomass of demersal fish in Haizhou Bay
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摘要: 随着生物多样性的丧失，全球许多海洋生态系统的功能发生了显著变化。为了解生物多样性和生态系统功能之间的关系，科学的海洋生态保护与管理显得尤为重要。本研究根据2013−2022年春季在海州湾及其邻近海域进行的底拖网调查数据，基于结构方程模型（SEM）探究了底栖鱼类群落中环境因素、生物多样性（物种丰富度与均匀度）和生态系统功能指标（以总生物量表示）之间的关系。结果表明：物种丰富度和生物量之间存在显著的正相关，而均匀度和生物量存在显著的负相关。环境因素中盐度对物种丰富度和生物量均有显著的影响，而对于温度来说，夏季与冬季的温度比年平均温度对生物量的影响更强烈。本研究表明，生态位互补效应和选择效应这两种机制可能同时对维持海州湾底层鱼类群落中的生物多样性−生物量关系发挥了作用，此外这种关系还依赖于它们所生存的环境和栖息条件。Abstract: Many of the global ecosystem functions are changing with the loss of biodiversity. It is therefore particularly important to understand the biodiversity-ecosystem functioning (BEF) relationships to support scientific ecological conservation and management. In this study, we evaluated the relationship between environmental factors, biodiversity (species richness and evenness) and ecosystem functions (measured as total biomass) in the benthic fish community of Haizhou Bay, using structural equation modeling (SEM) based on bottom trawl survey data conducted in spring 2013−2022. The results showed that there was a significant positive correlation between species richness and biomass, and a significant negative correlation between evenness and biomass. Among the environmental factors, salinity had significant effects on both species richness and biomass. Regarding the effects of temperature, the temperatures in winter and summer had a stronger effect on biomass than that of annual average temperature. The study suggested that two mechanisms, the niche complementarity mechanism and selection mechanism, may simultaneously play a role in maintaining the biodiversity-biomass relationships in the groundfish communities of Haizhou Bay, and in addition to the fact that such relationships depend on the environmental and habitat conditions.
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图 1 海州湾及其邻近海域渔业资源底拖网调查站位
Fig. 1 Sampling stations of the fishery resource surveys in the Haizhou Bay and its adjacent waters
图 3 2013−2022年底层鱼类生物量的变化趋势（a）和物种丰富度、均匀度的变化趋势（b）
Fig. 3 Trends in demersal fish biomass (a) and species richness and evenness (b) from 2013 to 2022
图 4 年均温度初始模型图示（a）和优化模型结果图示（b）
红色线表示显著的正影响路径，蓝色线表示显著的负影响路径，虚线表示影响不显著的路径
Fig. 4 Illustration of annual mean temperature model (a) and optimization model results (b)
Red lines indicate significant positive effects paths, blue lines indicate significant negative effects paths, and dashed lines indicate insignificant paths
图 5 季节温度模型结果图示
红色线表示显著的正影响路径，蓝色线表示显著的负影响路径，灰色虚线表示影响不显著路径，红色虚线表示有正影响的显著缺失路径
Fig. 5 Illustration of the results of seasonal temperature model
Red lines indicate significant positive effects paths, blue lines indicate significant negative effects paths, gray dashed lines indicate insignificant paths, and red dashed lines indicate significant missing paths with positive effects
图 6 最优模型结果图示
红色线表示显著的正影响路径，蓝色线表示显著的负影响路径
Fig. 6 Illustration of the optimal model results
Red lines indicate significant positive effects paths, blue lines indicate significant negative impact paths
表 1 各模型参数对比
Tab. 1 Comparison of parameters of each model
指标 初始模型 年均温度模型 季节温度模型 最优模型 模型设置 包含全部路径 去掉不显著路径 加入夏季与冬季温度变量 去掉不显著路径，加入显著缺失路径 显著缺失路径 无 无 均匀度和win2.SST 无 Fisher’s C 1.761 13.626 31.099 15.591 p 0.780 0.191 0.411 0.621 AIC 49.8 45.6 73.1 51.6 BIC 123.7 94.9 137.8 107.1 R2 0.34 0.35 0.41 0.39 
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