Phytoplankton response to climate change (PRIME)

浮游植物对气候变化的响应（PRIME）

• 批准号: MR/V022792/1
• 负责人: Robert Brewin
• 金额: $ 185.22万
• 依托单位: UNIVERSITY OF EXETER
• 依托单位国家: 英国
• 项目类别: Fellowship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MR%2FV022792%2F1
• 关键词: Phytoplankton; response; climate; change; PRIME

Phytoplankton are at the heart of the Earth system, connecting light to life in the ocean. Considered the most dynamic primary producer on Earth, regenerating every two to five days, they respond rapidly to changes in their environment, modulate the planetary cycling of major elements and compounds, and supply energy to the marine food-web. Understanding the response of phytoplankton to climate change is critical to predicting future changes in the Earth system. Approaching 25 years of continuous data acquisition, and with an unparalleled capability to view the entire planet within a few days, satellite remote sensing of ocean colour is our principal means of monitoring phytoplankton abundance at global scale, through estimates of the chlorophyll-a pigment concentration, a measure of phytoplankton abundance. However, there are two major challenges to using satellite remote sensing of ocean colour for monitoring trends in phytoplankton abundance. Firstly, converting the ocean-colour signal into estimates of phytoplankton abundance demands consideration of the phytoplankton type present and other optically active constituents in the water. Standard phytoplankton abundance algorithms in use by space agencies assume these constituents co-vary, which is unsuitable for detecting long-term trends as climate change may alter these constituents in different ways. Secondly, the signal retrieved by satellite is only representative of the surface layer of the ocean (top 40 m at most). For many regions, below the surface layer (40-200 m), there exists a forest of phytoplankton hidden from the eyes of the satellite. At present, ocean-colour trends in surface phytoplankton abundance using standard algorithms cannot be trusted, and we cannot be sure that, if any such trends exist, they are representative of changes in the forest hidden below. In this project, my team will develop the first ocean-colour algorithm designed specifically for monitoring climate change, that separates signals from water constituents using a theoretical and ecological framework, that harnesses the principles of compound remote sensing (thermal and visible satellite remote sensing). It will be run on climate-quality ocean satellite data records, recently available through the European Space Agency, to produce a multi-decadal record of surface phytoplankton abundance. Furthermore, by mining vertical profiles of phytoplankton abundance from the past 30+ years of oceanographic sampling and emerging autonomous ocean robotics, my team will also produce a global, multi-decadal record of subsurface phytoplankton abundance. Bringing these data records together, we will quantify the effect of anthropogenic climate change on phytoplankton abundance, at least in parts of the ocean where the record is long-enough. These data records will serve as a benchmark to compare and improve climate models, that simulate future predictions of the marine carbon cycle, marine biodiversity and fish stocks. The data records will be used as input to study the impact of climate change on oceanic primary production, phytoplankton carbon and ocean biogeography.

浮游植物是地球系统的核心，将光与海洋中的生命联系起来。被认为是地球上最具活力的初级生产者，每两到五天再生一次，它们对环境的变化迅速作出反应，调节主要元素和化合物的行星循环，并为海洋食物网提供能量。了解浮游植物对气候变化的反应对于预测地球系统未来的变化至关重要。卫星对海洋颜色的遥感已经连续获取数据将近25年，并具有在几天内观测整个地球的无与伦比的能力，因此，它是我们通过估算叶绿素a色素浓度----一种衡量浮游植物丰度的尺度----来监测全球浮游植物丰度的主要手段。然而，在利用卫星遥感海洋颜色监测浮游植物丰度趋势方面存在两大挑战。首先，将海洋颜色信号转换为浮游植物丰度的估计值需要考虑浮游植物类型和水中的其他光学活性成分。空间机构使用的标准浮游植物丰度算法假设这些成分是共同变化的，这不适合检测长期趋势，因为气候变化可能以不同的方式改变这些成分。第二，卫星检索的信号仅代表海洋表层（最高40米）。对于许多地区来说，在表层（40-200 m）以下，存在着卫星看不到的浮游植物森林。目前，使用标准算法计算的表层浮游植物丰度的海洋颜色趋势不能被信任，我们不能确定，如果存在任何这样的趋势，它们代表了隐藏在下面的森林的变化。在这个项目中，我的团队将开发第一个专门用于监测气候变化的海洋颜色算法，该算法使用理论和生态框架将信号与水成分分离，利用复合遥感（热和可见光卫星遥感）的原理。它将利用最近通过欧洲航天局获得的气候质量海洋卫星数据记录运行，以产生数十年的表层浮游植物丰度记录。此外，通过从过去30多年的海洋采样和新兴的自主海洋机器人技术中挖掘浮游植物丰度的垂直剖面，我的团队还将产生一个全球性的、数十年的地下浮游植物丰度记录。把这些数据记录放在一起，我们将量化人为气候变化对浮游植物丰度的影响，至少在海洋的部分地区，记录是足够长的。这些数据记录将作为比较和改进气候模型的基准，这些模型将模拟对海洋碳循环、海洋生物多样性和鱼类种群的未来预测。这些数据记录将用于研究气候变化对海洋初级生产、浮游植物碳和海洋地理学的影响。

项目成果

Superyachts could support satellite ocean colour validation

• DOI: 10.3389/frsen.2024.1336494
• 发表时间: 2024-01
• 期刊: Frontiers in Remote Sensing
• 作者: Robert J. W. Brewin;Xuerong Sun;Dirk A. Aurin;Johannes J. Viljoen;Christopher Walsh;S. Sathyendranath

Evaluating historic and modern optical techniques for monitoring phytoplankton biomass in the Atlantic Ocean

• DOI: 10.3389/fmars.2023.1111416
• 发表时间: 2023-03-07
• 期刊: FRONTIERS IN MARINE SCIENCE
• 影响因子: 3.7
• 作者: Brewin，Robert J. W.;Pitarch，Jaime;Tilstone，Gavin H.
• 通讯作者: Tilstone，Gavin H.

Ocean carbon from space: Current status and priorities for the next decade

• DOI: 10.1016/j.earscirev.2023.104386
• 发表时间: 2023-03
• 期刊: Earth-Science Reviews
• 影响因子: 12.1
• 作者: R. Brewin;S. Sathyendranath;G. Kulk;M. Rio;Javier A. Concha;T. Bell;A. Bracher;C. Fichot;T. Frölicher;M. Galí;D. Hansell;T. Kostadinov;Catherine Mitchell;A. Neeley;E. Organelli;K. Richardson;C. Rousseaux;Fang Shen;D. Stramski;M. Tzortziou;A. Watson;C. I. Addey;M. Bellacicco;H. Bouman;D. Carroll;I. Cetinić;G. Dall’Olmo;R. Frouin;J. Hauck;M. Hieronymi;Chuanmin Hu;V. Ibello;B. Jönsson;Christina Eunjun Kong;Ž. Kovač;M. Laine;J. Lauderdale;S. Lavender;E. Livanou;Joan Llort;Larisa Lorinczi;M. Nowicki;N. A. Pradisty;S. Psarra;D. Raitsos;A. Ruescas;J. Russell;J. Salisbury;R. Sanders;J. Shutler;Xuerong Sun;F. G. Taboada;G. Tilstone;Xinyuan Wei;D. Woolf

Complementary Approaches to Assess Phytoplankton Groups and Size Classes on a Long Transect in the Atlantic Ocean

评估大西洋长断面浮游植物群和大小等级的补充方法

• DOI: 10.3389/fmars.2021.682621
• 发表时间: 2022
• 期刊: Frontiers in Marine Science
• 影响因子: 3.7
• 作者: Brotas V

A high-tech, low-cost, Internet of Things surfboard fin for coastal citizen science, outreach, and education

• DOI: 10.1016/j.csr.2022.104748
• 发表时间: 2022-05-10
• 期刊: CONTINENTAL SHELF RESEARCH
• 影响因子: 2.3
• 作者: Bresnahan, Philip;Cyronak, Tyler;Waters, Shannon
• 通讯作者: Waters, Shannon