文章摘要
山东近海渔业物种多样性与环境因子关系
the relationship between species diversity and environmental factors in the fishery community of Shandong coastal waters
投稿时间:2020-10-31  修订日期:2021-03-03
DOI:
中文关键词: 物种多样性、空间分布、随机森林、山东近海
英文关键词: species diversity, spatial distribution, random forest, Shandong offshore
基金项目:国家重点研发计划资助(2019YFD0901204)
作者单位邮编
徐茂真 中国海洋大学 266003
张崇良 中国海洋大学 
薛莹 中国海洋大学 
徐宾铎 中国海洋大学 
纪毓鹏 中国海洋大学 
任一平 中国海洋大学 266003
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中文摘要:
      当前山东近海的渔业资源与生态环境面临较大压力,对海洋中的生物多样性水平有着较大影响。为了解山东近海生物多样性的空间分布与影响因素,本研究基于2017年冬季在山东近海进行的渔业资源和环境调查数据,分析了整体与山东近海3个不同海域的物种数、辛普森多样性(Simpson’s index of diversity)、香农?威纳多样性指数(Shannon-Wiener index of diversity)、皮尔洛均匀度(Pielou Evenness Index)等物种多样性指数的空间分布,利用随机森林算法(random forest)评估了多样性指数与环境因子的关系,研究将山东近海分三个区域并将分区作为空间因子加入到算法模型中。结果显示,山东近海的多样性水平空间分布上呈现半岛南部海域高于北方的烟威渔场及其临近海域、莱州湾渔场的趋势。物种数的模型拟合效果较好,方差解释率达到77.46%,而对均匀度指数的拟合效果较差。无论整体海域的模型还是分区模型,海底温度、海底盐度以及海水深度三种环境因子都是对多样性指数最为显著的影响因子,其中水深与海底温度在一定区间内与各个多样性指数间都存在显著正相关性;物种数随海底盐度的升高而升高,两种多样性指数随盐度变化不明显,而离岸距离与均匀度指数呈负相关关系。本研究系统分析了山东近海生态系统的多样性水平,对海洋生态系统长期监测和针对性的海洋管理提供了基础数据支持。
英文摘要:
      The fishery resources and ecological environment in Shandong offshore are under great pressure. With the impact of exploitation activities such as coastal engineering and overfishing in Shandong, the fishery resources in this area are in decline, and the number of fish of high economic value is significantly reduced. To effectively monitor and manage the fishery resources, it is necessary to understand fishery ecosystem, for which biodiversity is a crucial index in community ecology research to indicate ecosystem status. To understand the spatial distribution of coastal biodiversity, and the relationships between biodiversity indices and environmental factors, this study used several diversity indices, including number of species, Simpson index, Shannon index, and Pielou index, to analyze the spatial distribution of biodiversity based on investigation data of fishery resources in 2017 winter in Shandong offshore. Owing to a lot of non-linear and non-additive processes in fishery ecosystem, random forest model is used to assess the relationship between diversity indices and environmental factors. The results showed that the spatial distribution of diversity indices varied substantially in the Shandong offshore area, with a trend of higher diversity in the southern area of the Peninsula than that in the north, which included Yanwei fishery ground, Laizhou Bay, and the southern Bohai Sea. The southern Bohai Sea have the lowest level of species diversity. Random forest model could be properly fitted to the diversity data, and the rate of explained deviation reaches 77.46% and 45.66% for species number and the Shannon diversity index, respectively. However, the regression model of Pielou index had a low proportion of explained deviation. The bottom temperature, salinity, and water Depth had significant influences on the diversity indices, significantly correlated with species number, diversity index, and evenness index. The effect of bottom sediment type was not significant on species number and two diversity indices, but was high for the Pielou evenness index. The results were also compared for fishery resource surveys at different scales. The conclusion is that surveys of similar scale are necessary for long-term monitoring of biodiversity. This study systematically analyzes the diversity pattern of Shandong offshore ecosystem and provides scientific support for long-term marine ecosystem monitoring and specific marine management. We highlight the necessity of protecting biodiversity in order to restore fishery resources. Decisions could be made based on the level of biodiversity in terms of habitat restoration and the establishment of protected areas.
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