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  • 杜川军 副研究员
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● 个人简介:

杜川军,男,海南大学南海海洋资源利用国家重点实验室,副研究员。2016年博士毕业于厦门大学,2016-2021年在香港科技大学和厦门大学从事博士后研究。获2018 年博士后创新人才支持计划资助。作为主要参与人参与国家自然科学基金重大研究计划,南海深部生物地球化学-物理耦合过程对海-气界面CO2 通量的调控。作为项目骨干参与国家自然科学基金委员会,重大项目,海洋荒漠区常量和微量营养物质的来源、通量及其时空分布格局。已发表SCI 论文12 篇。


Chuanjun Du, associate research fellow at State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University. He received his Ph.D. from Xiamen University in 2016 and worked as a postdoctoral researcher at the Hong Kong University of Science and Technology and Xiamen University from 2016 to 2021. He was supported by the Postdoctoral Innovation Talent Support Program in 2018. He participated as a key member in the National Natural Science Foundation Major Program of China on the regulation of the coupling process of biogeochemistry and physics in the deep South China Sea on the flux of CO2 across the sea-air interface. He also participated as a core member in the National Natural Science Foundation Major Program of China on the sources, fluxes, and spatiotemporal distribution patterns of constant and trace nutrients in oceanic desert regions. He has published 12 SCI papers.

 

  

● 个人履历:

2021.07 – 至今,海南大学,南海海洋资源利用国家重点实验室,副研究员

2018.06–2021.06,厦门大学, 海洋与地球学院,博士后

2016.11–2017.11,香港科技大学,环境与可持续发展学部,博士后

2011.09–2016.07,厦门大学, 环境与生态学院,博士


Curriculum Vitae

2021.07-Present, Associate Research Fellow, State Key Laboratory of Marine Resource Utilization in South China Sea, Hainan University

2018.06–2021.06, Postdoctoral Fellow, School of Ocean and Earth, Xiamen University

2016.11-2017.11, Postdoctoral Fellow, Division of Environment and Sustainable Development, Hong Kong University of Science and Technology

2011.09-2016.07, Ph.D., School of Environment and Ecology, Xiamen University



 

研究方向:

海洋中营养元素的分布、来源、输运、交换及其控制机制

物理-生物地球化学相互作用

海洋数值模式应用及开发


Research Interests

Distribution, sources, transport, exchange, and control mechanisms of nutrients in the ocean

Physical-biogeochemical interactions

Application and development of ocean numerical models



前期科研成果概述:

(1)在寡营养盐海区,由海洋动力过程所驱动的跨等密度面营养盐输入是维持上层海洋新生产力的重要基础。由于缺乏营养盐与湍流混合过程的同步观测,准确量化相关通量非常困难。基于南海海盆湍流微结构与营养盐的高分辨率观测,首次同时定量了硝酸盐等生源要素跨密度面的扩散和平流通量。根据营养盐通量的垂向结构,提出真光层“双层结构”的新假设。在营养盐跃层上部的营养盐匮乏层,溶解无机氮的有效通量极低,而其它新生氮(如表层固氮和大气沉降)是支持新生产力与输出生产力的主要营养盐来源。从匮乏层以下到真光层底部称为营养盐充足层。该层内,营养盐浓度及其有效通量快速增加,其通量比匮乏层内大3个数量级,足以支持该层内的输出生产力。该研究已发表于Geophysical Research Letters期刊。

 

(2)南海是北太平洋最大的边缘海,然而南海北部海盆上层营养盐的空间分布、季节变化及其主要控制仍然不清楚,基于中国海973项目南海北部4个航次包含4个季节的营养盐观测,首次通过建立的等密度面混合模型,研究了黑潮入侵对南海的影响,揭示了黑潮入侵是影响南海北部营养盐空间和季节变化的主要因素。在南海建立的等密度面混合模型被广泛应用于南海北部和其它海域的物理和生物地球化学研究。该研究已发表于Biogeosciences期刊。

 

(3)传统营养盐观测受制于人力、物力和航次等因素,时空分辨率较低,制约了对海洋营养盐全貌的解析。世界海洋图集(WOA)是目前应用最广泛的营养盐气候态数据集,但在南海存在较大的误差。前期研究发现南海的营养盐与水团特征参数温度和盐度之间存在准保守的关系,因而可以通过温盐反演营养盐。利用优化插值算法,重建了1950-2018年南海营养盐的历史数据,将营养盐数据量增加1000倍以上,建立目前南海最大的营养盐数据集。基于该数据集,研究了南海营养盐的气候态分布及季节变化。该数据集将极大促进对南海营养盐在气候态和长时间尺度上的研究,并为南海初级生产、生物泵等研究提供基础数据,并改进数值模式的初始和边界条件。该研究已发表于Progress in Oceanograph期刊。

 

(4)受限于传统观测手段的局限性,对南海碳酸盐体系的收支与动力学机制仍然知之甚少。数值模式是海洋生物地球化学研究的有力工具。利用三维的生物地球化学耦合数值模式在系统水平上对南海碳收支进行综合分析。结果揭示了西菲律宾海水通过吕宋海峡与南海水进行交换,是南海溶解无机碳(DIC)的主要来源,南海内部的强物理动力和生物化学过程主导了DIC的空间分布、季节变化、海气交换和对周围边缘海的影响。在真光层内,物理输运和生物净消耗对DIC季节变化的影响同等重要。物理输运和生物净消耗均表现为冬季大于夏季,这主要与冬季黑潮入侵、垂向涌生和生产力的加强有关。在中层和深层,物理输运则是影响DIC季节变化的主要因子。该研究已发表于Progress in Oceanography期刊。


Academic Achievement at an earlier stage

(1)In oligotrophic sea areas, the cross-density nutrient input driven by ocean dynamic processes is an important basis for maintaining upper ocean new productivity. Due to the lack of synchronous observations of nutrient and turbulence mixing processes, accurate quantification of related fluxes is very difficult. Based on high-resolution observations of turbulence microstructure and nutrients in the South China Sea basin, the diffusion and advection fluxes of nitrogen sources such as nitrate across density surfaces were quantified simultaneously for the first time. Based on the vertical structure of nutrient flux, a new hypothesis of "double-layer structure" in the euphotic zone is proposed. In the nutrient-depleted layer above the nutrient jump layer, the effective flux of dissolved inorganic nitrogen is very low, while other new nitrogen sources (such as surface nitrogen fixation and atmospheric deposition) are the main nutrient sources supporting new and output productivity. From below the depleted layer to the bottom of the euphotic zone is called the nutrient-rich layer. Within this layer, nutrient concentration and its effective flux increase rapidly, and its flux is three orders of magnitude larger than that in the depleted layer, which is sufficient to support output productivity within this layer. This study has been published in Geophysical Research Letters.

(2)The South China Sea is the largest marginal sea in the North Pacific, but the spatial distribution, seasonal variation, and main controls of nutrients in the upper layer of the northern basin of the South China Sea are still unclear. Based on nutrient observations from four seasons during four cruises in the northern part of the South China Sea under the Chinese 973 project, the impact of Kuroshio intrusion on the South China Sea was studied for the first time using an established isopycnal mixing model, revealing that Kuroshio intrusion is the main factor affecting the spatial and seasonal variation of nutrients in the northern part of the South China Sea. The isopycnal mixing model established in the South China Sea has been widely used in physical and biogeochemical studies in the northern part of the South China Sea and other areas. The study has been published in Biogeosciences.

(3)Traditional nutrient observation is limited by factors such as manpower, resources, and voyages, resulting in low temporal and spatial resolution, which restricts the analysis of the overall picture of ocean nutrients. The World Ocean Atlas (WOA) is currently the most widely used nutrient climatology dataset, but there are significant errors in the South China Sea. Previous studies have found a quasi-conservative relationship between nutrient salts and water mass characteristic parameters such as temperature and salinity in the South China Sea, which can be used to infer nutrients through temperature and salinity inversion. Using an optimized interpolation algorithm, the historical data of nutrient salts in the South China Sea from 1950 to 2018 were reconstructed, increasing the amount of nutrient data by more than 1,000 times, and establishing the largest nutrient salt dataset in the South China Sea. Based on this dataset, the climatological distribution and seasonal variation of nutrient salts in the South China Sea were studied. This dataset will greatly promote research on the climatology and long-term scale of nutrient salts in the South China Sea, provide basic data for research on primary production, biological pumps, and improve the initial and boundary conditions of numerical models. This study has been published in Progress in Oceanography.

(4) Due to the limitations of traditional observation methods, little is known about the carbon budget and dynamic mechanisms of the carbonate system in the South China Sea. Numerical models are powerful tools for studying marine biogeochemistry. A three-dimensional biogeochemical coupled numerical model was used to comprehensively analyze the carbon balance in the South China Sea at the system level. The results revealed that the exchange of water between the West Philippine Sea and the South China Sea through the Luzon Strait is the main source of dissolved inorganic carbon (DIC) in the South China Sea, and the strong physical and biogeochemical processes within the South China Sea dominate the spatial distribution, seasonal variation, air-sea exchange, and impact on surrounding marginal seas of DIC. In the euphotic layer, physical transport and biological net consumption are equally important factors affecting the seasonal variation of DIC. Both physical transport and biological net consumption show a winter greater than summer trend, which is mainly related to the invasion of the Kuroshio current, vertical upwelling, and increased productivity in winter. In the middle and deep layers, physical transport is the main factor affecting the seasonal variation of DIC. This study has been published in Progress in Oceanography.



 

南海海洋资源利用国家重点实验室(海南大学)
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