Annual boom-bust cycles of polar phytoplankton biomass revealed by space-based lidar
Annual boom-bust cycles of polar phytoplankton biomass revealed by space-based lidar
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DOI：
10.1038/ngeo2861
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发表时间：
2017-02-01
影响因子：
18.3
通讯作者：
Scarino, Amy Jo
中科院分区：
文献类型：
--
作者：
Behrenfeld, Michael J.;Hu, Yongxiang;Scarino, Amy Jo
极地浮游生物群落是全球海洋中最具生产力、季节动态和变化最快的生态系统之一。然而，极地地区持续的云层、持续的夜间时段和普遍的低太阳海拔严重限制了传统的被动卫星海洋颜色测量，使每年连续许多月无法观测到大片地区。因此，我们对极地浮游生物的年周期及其年际变化的了解是不完整的。在这里，我们使用空间激光雷达观测，以克服历史上被动传感器的限制，并报告十年来不间断的极地浮游植物生物量循环。我们发现，极地浮游植物的动态被归类为由浮游生物捕食者-猎物平衡的轻微失衡引起的“繁荣-萧条”周期。观测到的生物量从季节到年际的变化是通过浮游植物分区的数学模型变化率来预测的。此外，我们发现，在过去十年中，冰盖的变化主导了南极浮游植物种群的变化，而生态过程是北极变化的主要驱动因素。我们得出的结论是，极地食物网中微妙的环境驱动的失衡是浮游植物每年盛衰周期的基础，每一极的浮游植物盛衰周期每年都会发生变化。
Polar plankton communities are among the most productive, seasonally dynamic and rapidly changing ecosystems in the global ocean. However, persistent cloud cover, periods of constant night and prevailing low solar elevations in polar regions severely limit traditional passive satellite ocean colour measurements and leave vast areas unobserved for many consecutive months each year. Consequently, our understanding of the annual cycles of polar plankton and their interannual variations is incomplete. Here we use space-borne lidar observations to overcome the limitations of historical passive sensors and report a decade of uninterrupted polar phytoplankton biomass cycles. We find that polar phytoplankton dynamics are categorized by 'boom-bust' cycles resulting from slight imbalances in plankton predator-prey equilibria. The observed seasonal-to-interannual variations in biomass are predicted by mathematically modelled rates of change in phytoplankton division. Furthermore, we find that changes in ice cover dominated variability in Antarctic phytoplankton stocks over the past decade, whereas ecological processes were the predominant drivers of change in the Arctic. We conclude that subtle and environmentally driven imbalances in polar food webs underlie annual phytoplankton boom-bust cycles, which vary interannually at each pole.