Autonomous profiling float observations of the high-biomass plume downstream of the Kerguelen Plateau in the Southern Ocean

Autonomous profiling float observations of the high-biomass plume downstream of the Kerguelen Plateau in the Southern Ocean
复制标题

对南大洋凯尔盖朗高原下游高生物量羽流的自主剖面浮标观测

DOI:
--
复制
发表时间:
2014
期刊:
影响因子:
--
通讯作者:
T. Trull
T. Trull
中科院分区:
--
文献类型:
--
作者:
M. Grenier;A. Penna;T. Trull

文献摘要

参考文献

被引文献

相似文献

来自南大洋岛屿的天然铁肥导致高初级产量和浮游植物吨生物量积累,这在卫星海洋颜色观测中很容易看到。这些图像显示了叶绿素浓度高度变化的巨大空间复杂性,可能反映了铁供应的变化和有利于浮游植物积累的条件。为了研究第二个方面,特别是温度和混合层深度变化的影响,我们在南大洋印度板块克尔盖伦高原附近的南极环流中部署了四个自主剖面浮标。每台“生物剖面仪”在水柱顶部300米处测量了250多条温度(T)、盐度(S)、溶解氧、叶绿素a (Chl a)荧光和微粒后向散射(bbp)剖面,每天沿着蜿蜒的轨迹采样多达5条剖面,最长可达1000公里。地表Chl a估计值(类似于卫星图像的值)与总水柱清单的比较显示了很大程度上的线性关系,表明这些图像提供了关于总生物量空间分布的可靠信息,而不仅仅是地表生物量空间分布。然而,他们也表明,物理混合层深度往往不是生物量分布的可靠指南。高Chl - a积累区(1.5-10µg L−1)主要与狭窄的T-S类地表水有关。相比之下,只有中等浓度的Chl a(0.5-1.5µg L−1)的水与特定的水性质没有明显的相关性,包括不依赖于混合层深度或分层强度。地转轨迹分析表明,如果一个给定水包中生物量的主要决定因素是离开克尔盖伦高原的时间,那么这两个观测结果都可以解释。一个浮子被困在气旋涡流中,允许在初秋对水柱进行时间评估。在此期间,表面Chl - a库存的减少与亚混合层密度表面氧库存的减少相对应,这与海洋内部有机物(~ 35%)的大量输出及其呼吸和作为溶解无机碳的储存相一致。这些结果对于扩大自主观测平台的使用来研究生物地球化学、碳循环和生态问题是令人鼓舞的,尽管浮子实现的拉格朗日和欧拉采样的复杂混合表明,通常需要阵列而不是单个浮子,并且频繁的剖面分析在解决中尺度结构对生物量积累的作用方面提供了重要的好处。
Natural iron fertilisation from Southern Ocean islands results in high primary production and phytoplank-ton biomass accumulations readily visible in satellite ocean colour observations. These images reveal great spatial complexity with highly varying concentrations of chlorophyll, presumably reflecting both variations in iron supply and conditions favouring phytoplankton accumulation. To examine the second aspect, in particular the influences of variations in temperature and mixed layer depth, we deployed four autonomous profiling floats in the Antarctic Circumpo-lar Current near the Kerguelen Plateau in the Indian sector of the Southern Ocean. Each "bio-profiler" measured more than 250 profiles of temperature (T), salinity (S), dissolved oxygen, chlorophyll a (Chl a) fluorescence, and particulate backscattering (b bp) in the top 300 m of the water column, sampling up to 5 profiles per day along meandering trajecto-ries extending up to 1000 km. Comparison of surface Chl a estimates (analogous to values from satellite images) with total water column inventories revealed largely linear relationships , suggesting that these images provide credible information on total and not just surface biomass spatial distributions. However, they also showed that physical mixed layer depths are often not a reliable guide to biomass distributions. Regions of very high Chl a accumulation (1.5-10 µg L −1) were associated predominantly with a narrow T-S class of surface waters. In contrast, waters with only moderate Chl a enrichments (0.5-1.5 µg L −1) displayed no clear correlation with specific water properties, including no dependence on mixed layer depth or the intensity of stratifica-tion. Geostrophic trajectory analysis suggests that both these observations can be explained if the main determinant of biomass in a given water parcel is the time since leaving the Kerguelen Plateau. One float became trapped in a cyclonic eddy, allowing temporal evaluation of the water column in early autumn. During this period, decreasing surface Chl a inventories corresponded with decreases in oxygen inventories on sub-mixed-layer density surfaces, consistent with significant export of organic matter (∼ 35 %) and its respiration and storage as dissolved inorganic carbon in the ocean interior. These results are encouraging for the expanded use of autonomous observing platforms to study biogeochemical, carbon cycle, and ecological problems, although the complex blend of Lagrangian and Eulerian sampling achieved by the floats suggests that arrays rather than single floats will often be required, and that frequent profiling offers important benefits in terms of resolving the role of mesoscale structures on biomass accumulation.
DOI: 10.1073/pnas.1309345110
发表时间: 2013-12-17
影响因子: 11.1
作者:
Assmy, Philipp;Smetacek, Victor;Wolf-Gladrow, Dieter
通讯作者: Wolf-Gladrow, Dieter
DOI: 10.5194/os-11-83-2015
发表时间: 2015
期刊: Ocean Science
影响因子: 3.2
作者:
Biermann L
通讯作者: Biermann L