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首页> 外文期刊>International journal of remote sensing >Macroscale factors affecting diatom abundance: a synergistic use of Continuous Plankton Recorder and satellite remote sensing data
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Macroscale factors affecting diatom abundance: a synergistic use of Continuous Plankton Recorder and satellite remote sensing data

机译：影响硅藻丰度的宏观因素：连续性浮游生物记录仪和卫星遥感数据的协同使用

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摘要

Diatoms exist in almost every aquatic regime; they are responsible for ～20% of global carbon fixation and ~25% of global primary production, and are regarded as a key food for copepods, which are subsequently consumed by larger predators such as fish and marine mammals. A decreasing abundance and a vulnerability to climatic change in the North Atlantic Ocean have been reported in the literature. In the present work, a data matrix composed of concurrent satellite remote sensing and Continuous Plankton Recorder (CPR) in situ measurements was collated for the same spatial and temporal coverage in the Northeast Atlantic. Artificial neural networks (ANNs) ware applied to recognize and learn the complex non-monotonic and non-linear relationships between diatom abundance and spatiotemporal environmental factors. Because of their ability to mimic non-linear systems, ANNs proved far more effective in modelling the diatom distribution in the marine ecosystem. The results of this study reveal that diatoms have a regular seasonal cycle, with their abundance most strongly influenced by sea surface temperature (SST) and light intensity. The models indicate that extreme positive SSTs decrease diatom abundances regardless of other climatic conditions. These results provide information on the ecology of diatoms that may advance our understanding of the potential response of diatoms to climatic change.
机译：硅藻几乎存在于每个水生环境中。它们约占全球固碳的约20％和全球初级生产的约25％，被视为co足类动物的主要食物，后来被较大的食肉动物如鱼类和海洋哺乳动物食用。文献中已经报道了北大西洋的丰度下降和易受气候变化的影响。在本工作中，整理了由并发卫星遥感和连续浮游生物记录仪（CPR）原位测量组成的数据矩阵，以获取东北大西洋相同的时空覆盖范围。人工神经网络（ANN）应用于识别和学习硅藻丰度与时空环境因素之间的复杂非单调和非线性关系。由于其具有模仿非线性系统的能力，因此人工神经网络在模拟海洋生态系统中的硅藻分布方面被证明更为有效。这项研究的结果表明，硅藻具有规律的季节周期，其丰度受海面温度（SST）和光强度的影响最大。这些模型表明，无论其他气候条件如何，极端正的SST都会降低硅藻的丰度。这些结果提供了有关硅藻生态学的信息，这可能会加深我们对硅藻对气候变化的潜在反应的了解。

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  • 来源
    《International journal of remote sensing》 |2011年第8期|p.2081-2094|共14页
  • 作者

    DIONYSIOS E. RAITSOS; SAMANTHA J. LAVENDER; CHRISTOS D. MARAVELIAS; JOHN HARALABOUS; ABIGAIL MCQUATTERS-GOLLOP; MARTIN EDWARDS; PHILIP C. REID;

  • 作者单位

    Hellenic Centre for Marine Research (HCMR), 46,7 Km Athens-Sounio, PO Box 712,190 13 Anavissos, Attica, Greece;

    School of Earth, Ocean and Environmental Sciences (SEOES), University of Plymouth,Drake Circus, Plymouth PL4 8AA, UK;

    Hellenic Centre for Marine Research (HCMR), 46,7 Km Athens-Sounio, PO Box 712,190 13 Anavissos, Attica, Greece;

    Hellenic Centre for Marine Research (HCMR), 46,7 Km Athens-Sounio, PO Box 712,190 13 Anavissos, Attica, Greece;

    Sir Alister Hardy Foundation for Ocean Science (SAHFOS), The Laboratory, Citadel Hill, Plymouth PL1 2PB, UK;

    Sir Alister Hardy Foundation for Ocean Science (SAHFOS), The Laboratory, Citadel Hill, Plymouth PL1 2PB, UK;

    Sir Alister Hardy Foundation for Ocean Science (SAHFOS), The Laboratory, Citadel Hill, Plymouth PL1 2PB, UK;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
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