A three-component model of phytoplankton size class for the Atlantic Ocean
A three-component model of phytoplankton size class for the Atlantic Ocean
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DOI：
10.1016/j.ecolmodel.2010.02.014
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发表时间：
2010-06-10
影响因子：
3.1
通讯作者：
Hardman-Mountford, Nick J.
中科院分区：
文献类型：
--
作者：
Brewin, Robert J. W.;Sathyendranath, Shubha;Hardman-Mountford, Nick J.
开发了一个三组分模型，计算了三种浮游植物大小类别（微型，纳米和微微型浮游生物）在大西洋的总体叶绿素a浓度的贡献。该模型是Sathyendranath等人（2001年）方法的延伸，其基础是小细胞在低叶绿素a浓度下占主导地位，而大细胞在高叶绿素a浓度下占主导地位的假设。诊断色素被用来推断细胞大小，使用一个既定的技术，适用于占超贫营养环境中的小picoeukaroytes。1997年至2004年之间采取的大西洋经向断面（AMT）的色素数据分为两个数据集，1935年的测量被用来参数化的模型，并进一步241表面测量，空间和时间匹配的叶绿素a来自SeaWiFS卫星数据，被搁置，以验证模型。与一个独立的全球色素数据集（256个测量值）的比较也支持该模型的更广泛的应用。光学深度对模型参数的影响也进行了研究，并明确纳入模型。预计未来的应用将包括验证多种浮游生物生物地球化学模型，并通过计算群落组成来改进初级生产量估计数。(C)2010 Elsevier B.V.保留所有权利。
A three-component model was developed which calculates the fractional contributions of three phytoplankton size classes (micro-, nano- and picoplankton) to the overall chlorophyll-a concentration in the Atlantic Ocean. The model is an extension of the Sathyendranath et al. (2001) approach, based on the assumption that small cells dominate at low chlorophyll-a concentrations and large cells at high chlorophyll-a concentrations. Diagnostic pigments were used to infer cell size using an established technique adapted to account for small picoeukaroytes in ultra-oligotrophic environments. Atlantic Meridional Transect (AMT) pigment data taken between 1997 and 2004 were split into two datasets; 1935 measurements were used to parameterise the model, and a further 241 surface measurements, spatially and temporally matched to chlorophyll-a derived from SeaWiFS satellite data, were set aside to validate the model. Comparison with an independent global pigment dataset (256 measurements) also supports the broader-scale application of the model. The effect of optical depth on the model parameters was also investigated and explicitly incorporated into the model. It is envisaged that future applications would include validating multi-plankton biogeochemical models and improving primary-production estimates by accounting for community composition. (C) 2010 Elsevier B.V. All rights reserved.