Abstract:
Basin-scale patterns of biodiversity for zooplankton in the ocean may provide valuable insights for understanding the impact of climate change and global warming on the marine ecosystem. However, studies on this topic remain scarce or unavailable in vast regions of the world ocean, particularly in large regions where the amount and quality of available data are limited. In this study, we used a 27-year (1993-2019) database on species occurrence of planktonic copepods in the South Pacific, along with associated oceanographic variables, to examine their spatial patterns of biodiversity in the upper 200 m of the ocean. The aim of this study was to identify ecological regions and the environmental predictors explaining such patterns. It was found that hot and cold spots of diversity, and distinctive species assemblages were linked to major ocean currents and large regions over the basin, with increasing species richness over the subtropical areas on the East and West sides of the South Pacific. While applying the spatial models, we showed that the best environmental predictors for diversity and species composition were temperature, salinity, chlorophyll-a concentration, oxygen concentration, and the residual autocorrelation. Nonetheless, the observed spatial patterns and derived environmental effects were found to be strongly influenced by sampling coverage over space and time, revealing a highly under-sampled basin. Our findings provide an assessment of copepods diversity patterns and their potential drivers for the South Pacific Ocean, but they also stress the need for strengthening the data bases of planktonic organisms, as they can act as suitable indicators of ecosystem response to climate change at basin scale.
摘要:
海洋浮游动物生物多样性的盆地尺度模式可能为理解气候变化和全球变暖对海洋生态系统的影响提供有价值的见解。然而,在世界海洋的广大地区,关于这一主题的研究仍然很少或不可用,特别是在可用数据的数量和质量有限的大区域。在这项研究中,我们使用了一个27年(1993-2019年)关于南太平洋浮游co足类动物物种发生的数据库,以及相关的海洋学变量,研究他们在海洋200米上的生物多样性空间格局。这项研究的目的是确定生态区域和解释这种模式的环境预测因子。人们发现,热点和冷点的多样性,独特的物种组合与主要洋流和盆地上的大片区域有关,随着南太平洋东侧和西侧亚热带地区物种丰富度的增加。在应用空间模型时,我们表明,多样性和物种组成的最佳环境预测因子是温度,盐度,叶绿素a浓度,氧气浓度,和残差自相关。尽管如此,观察到的空间格局和衍生的环境效应被发现在空间和时间上受到采样覆盖率的强烈影响,揭示了一个高度采样不足的盆地。我们的研究结果提供了对co足类多样性模式及其对南太平洋的潜在驱动因素的评估,但他们也强调需要加强浮游生物的数据库,因为它们可以作为流域尺度的生态系统对气候变化响应的合适指标。