文章摘要
金岳,李娜,金显仕,单秀娟.秋季黄海渔业生物多样性及生物量平均温度的时空变化.渔业科学进展,2023,44(2):1-9
秋季黄海渔业生物多样性及生物量平均温度的时空变化
Spatiotemporal variation of biodiversity and mean temperature of the biomass of fishery resources in the Yellow Sea in fall
投稿时间:2021-09-26  修订日期:2021-11-22
DOI:
中文关键词: 黄海  渔业生物  多样性  时空分布  生物量平均温度
英文关键词: Yellow Sea  Fishery resources  Biodiversity  Spatiotemporal distribution  Mean temperature of the biomass
基金项目:
作者单位
金岳 中国水产科学研究院黄海水产研究所 农业农村部海洋渔业可持续发展重点实验室 山东省渔业资源与生态 环境重点实验室 山东 青岛 266071崂山实验室海洋渔业科学与食物产出过程功能实验室 山东 青岛 266071山东长岛近海渔业资源国家野外科学观测研究站 山东 烟台 265800 
李娜 中国水产科学研究院黄海水产研究所 农业农村部海洋渔业可持续发展重点实验室 山东省渔业资源与生态 环境重点实验室 山东 青岛 266071崂山实验室海洋渔业科学与食物产出过程功能实验室 山东 青岛 266071山东长岛近海渔业资源国家野外科学观测研究站 山东 烟台 265800 
金显仕 中国水产科学研究院黄海水产研究所 农业农村部海洋渔业可持续发展重点实验室 山东省渔业资源与生态 环境重点实验室 山东 青岛 266071崂山实验室海洋渔业科学与食物产出过程功能实验室 山东 青岛 266071山东长岛近海渔业资源国家野外科学观测研究站 山东 烟台 265800 
单秀娟 中国水产科学研究院黄海水产研究所 农业农村部海洋渔业可持续发展重点实验室 山东省渔业资源与生态 环境重点实验室 山东 青岛 266071崂山实验室海洋渔业科学与食物产出过程功能实验室 山东 青岛 266071山东长岛近海渔业资源国家野外科学观测研究站 山东 烟台 265800 
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中文摘要:
      全球变暖等气候变化使渔业资源有向两极移动的趋势,导致渔业生物多样性的变化和生物量随纬度的变化,后者表现为生物量平均温度(mean temperature of the biomass, MTB)的改变。为充分了解黄海渔业资源多样性、生物量及MTB的长期时空动态,本研究基于2000、2009和2018年每年秋季(10月)底拖网调查数据,选择生物量占比超过0.05%的种类作为黄海渔业资源的表征种类,结合海表面温度(sea surface temperature, SST)遥感数据,对黄海鱼类、甲壳类和头足类等重要渔业生物的多样性时空分布及其与SST的关系,生物量及MTB的时空分布进行分析。结果显示,2000、2009和2018年的表征种类分别为39、37和46种。2009年丰度的绝对优势种占比最高,而2000年丰度的绝对优势种占比最低。生物量占比方面,鱼类各年份占比均高于70%,呈先下降后上升的趋势,甲壳类占比由11.45%增至25%以上,头足类占比最小(<1%)且不断下降。在生物多样性指数时空分布方面,Berger-Parker指数和Shannon-Wiener多样性指数的空间分布趋势相反,且未发现经向或纬向的变化趋势;Margalef丰富度指数高值区主要分布在黄海南部海域。SST与生物多样性指数间无显著线性关系(P>0.05)。MTB呈西南高、东北低的趋势,且在34°N附近变化明显,黄海深水区低于近岸;MTB最小值出现在黄海北部,最大值出现在调查海域南端。
英文摘要:
      Due to climate change, the biomass and biodiversity of fishery resources are increasing at higher latitudes and decreasing at lower latitudes (reflected by the mean temperature of the biomass, MTB). Studies have shown that the change in catch composition of marine fisheries at the global scale is largely related to seawater temperature. It remains important to accurately analyze biodiversity and biomass distribution to inform the sustainable utilization and adaptive management of fishery resources. To evaluate the long-term spatiotemporal dynamics of biodiversity and MTB of fishery resources in the Yellow Sea, we selected species that account for more than 0.05% of the total biomass as representative species based on scientific bottom trawling data in autumn (October) of 2000, 2009, and 2018. A total of 117 stations (39 stations each year) were surveyed by R/V Beidou. Considering that sea surface temperature (SST) is the most accessible oceanographic variable and has been shown to affect marine biomass, the impact of SST on the biodiversity of benthic fisheries in the Yellow Sea was analyzed. Therefore, the spatiotemporal distribution of fish, crustaceans, and cephalopods, their relationship with SST, and the spatiotemporal distribution of biomass and MTB were analyzed. The Shannon-Wiener, Berger-Parker, and Margalef biodiversity indices were used to evaluate distribution changes. Location-related data were matched at the same resolution (0.5°×0.5°) for further analysis. Data processing and plotting were performed using R. The results showed that 39 species in 2000, 37 species in 2009, and 46 species in 2018 were representative of the total biomass collected by bottom trawling. The increase in diversity observed in 2018 may have resulted from a decrease in the abundance of dominant species. Although Liparis tanakae was dominant between years, there were significant differences in biomass proportions: 27.00% in 2000, 37.85% in 2009, and 22.82% in 2018. Fish showed the highest richness around 33°~34°N, and that of the southern Yellow Sea was higher than the northern Yellow Sea; crustaceans showed higher richness south of 34°N, and gradually increased from 2000 to 2018. For cephalopods, Japanese flying squid (Todarodes pacificus) was the only species occupying more than 0.05% of the total biomass. Except for cephalopods, the richness of all categories increased northward. According to the species accumulation curve, approximately 20 random stations were needed to represent Yellow Sea species richness. The Rényi profile further verified that 1) species were not evenly distributed, 2) species richness decreased from 2000 to 2009 and increased in 2018, and 3) the proportion of the most dominant species was highest in 2009 and lowest in 2000. In terms of biomass, high biomass stations occupied only one-third of the total stations and were mainly distributed around 35°~37°N in 2000, while high biomass stations occupied half of the total stations in 2009 and 2018. The proportion of fish was >70% in all years with a downward trend, followed by an upward trend; the proportion of crustaceans increased from 11.45% to more than 25%; the proportion of cephalopods was the lowest (less than 1%) with a downward trend. Previous studies have also shown that crustaceans gradually dominate over time in both abundance and biomass. In particular, the abundance of Crangon affinis was dominant in all years, accounting for 53.25% in 2000, 75.40% in 2009, and 63.81% in 2018. In terms of the spatiotemporal distribution of biodiversity indices, the Berger-Parker index and Shannon-Wiener index showed contradictory distribution trends; high Shannon-Wiener and Margalef index values were mainly distributed in the southern Yellow Sea, whereas high Berger-Parker index values were mainly distributed in the middle and southern Yellow Sea. For the same diversity index, Berger-Parker had the lowest values in 2018, while the Shannon-Wiener index and Margalef index values increased over time, and no obvious longitudinal or latitudinal change was found for any of the indices. There was no significant linear relationship between the SST and biodiversity indices (P>0.05). SST had a weak positive correlation with species richness, the Margalef index, and the Shannon-Weiner index, while SST had a weak negative correlation with the Berger-Parker index. Therefore, we concluded that bottom species are not sensitive to changes in SST, and bottom sea temperature should be compared to diversity indices in future studies. In terms of MTB, it was higher in the southwest and lower in the northeast with an obvious change around 34°N; it was lower in the deep-water area than in the coastal area; the lowest value appeared in the northern survey area, while the highest value appeared in the southern survey area. Considering the weak relationship between SST and diversity indices, SST is not feasible for diversity studies of bottom species. Research on the relationship between bottom sea temperature and diversity and the spatiotemporal distribution of bottom temperature-based MTB are needed in the future.
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