Composition and spatial-temporal dynamics of phytoplankton community shaped by environmental selection and interactions in the Jiaozhou Bay
文献类型：期刊论文
| 作者 | Liu, Shuya3,4,6; Cui, Zongmei3,4,5,6; Zhao, Yongfang1,3,4; Chen, Nansheng2,3,4,6 |
| 刊名 | WATER RESEARCH
 |
| 出版日期 | 2022-06-30 |
| 卷号 | 218页码:12 |
| ISSN号 | 0043-1354 |
| 关键词 | Jiaozhou Bay Metabarcoding analysis Spatial-temporal dynamics Phytoplankton community assembly Environmental selection Species-species interactions |
| DOI | 10.1016/j.watres.2022.118488 |
| 通讯作者 | Chen, Nansheng(chenn@qdio.ac.cn) |
| 英文摘要 | The Jiaozhou Bay as a model marine ecosystem in China has been intensively investigated over the last 90 years. However, detailed phytoplankton community composition, spatial-temporal dynamics, and its assembly mechanism were still unclear. To address these, we systematically examined the composition and spatial-temporal dynamics of phytoplankton in the Jiaozhou Bay through high-throughput sequencing of 18S rDNA V4. Analysis of 468 samples from 12 sampling sites over one full year revealed much higher phytoplankton diversity than previous reports, and strong seasonal succession patterns. Some phytoplankton also showed spatial variations, although the phytoplankton community didn't show significant distance-decay pattern. Environmental factors (especially temperature), species-species interrelationships and unique resting stages were uncovered to be the main contributors instead of stochastic process in shaping the phytoplankton community assembly. The overwhelming positive correlations between phytoplankton and other protists suggested that coevolution might be critical in this marine ecosystem. Complementary distributions of different amplicon sequence variants (ASVs) of same genera, such as Skeletonema marinoi (ASV_2) and Skeletonema tropicum (ASV_263) of the genus Skeletonema, suggested that phytoplankton have evolved differentially to exploit a wide range of ecological niches. This study laid a solid foundation for asertaining phytoplankton composition and spatial-temporal dynamics in temperate seawaters and mechanisms underlying phytoplankton community assembly, allowing in-depth studies of marine ecology. |
| 资助项目 | Strategic Priority Research Program of Chinese Academy of Sciences[XDB42000000] ; Natural Science Foundation of China[41906118] ; Chinese Academy of Sciences Pioneer Hundred Talents Program ; Taishan Scholar Project Special Fund ; Qingdao Innovation and Creation Plan[19-3-2-16-zhc] ; Natural Sciences and Engineering Research Council of Canada (NSERC) |
| WOS研究方向 | Engineering ; Environmental Sciences & Ecology ; Water Resources |
| 语种 | 英语 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| WOS记录号 | WOS:000798540900005 |
| 源URL | [http://ir.qdio.ac.cn/handle/337002/179425]  |
| 专题 | 海洋研究所_海洋生态与环境科学重点实验室 |
| 通讯作者 | Chen, Nansheng |
| 作者单位 | 1.Chinese Acad Sci, Inst Oceanol, Jiaozhou Bay Natl Marine Ecosyst Res Stn, Qingdao 266071, Peoples R China 2.Simon Fraser Univ, Dept Mol Biol & Biochem, 8888 Univ Dr, Burnaby, BC V5A 1S6, Canada 3.Chinese Acad Sci, Ctr Ocean Mega Sci, Qingdao 266071, Peoples R China 4.Qingdao Natl Lab Marine Sci & Technol, Lab Marine Ecol & Environm Sci, Qingdao 266200, Peoples R China 5.Univ Chinese Acad Sci, Coll Marine Sci, Beijing, Peoples R China 6.Chinese Acad Sci, Inst Oceanol, CAS Key Lab Marine Ecol & Environm Sci, Qingdao 266071, Peoples R China |
| 推荐引用方式 GB/T 7714 | Liu, Shuya,Cui, Zongmei,Zhao, Yongfang,et al. Composition and spatial-temporal dynamics of phytoplankton community shaped by environmental selection and interactions in the Jiaozhou Bay[J]. WATER RESEARCH,2022,218:12. |
| APA | Liu, Shuya,Cui, Zongmei,Zhao, Yongfang,&Chen, Nansheng.(2022).Composition and spatial-temporal dynamics of phytoplankton community shaped by environmental selection and interactions in the Jiaozhou Bay.WATER RESEARCH,218,12. |
| MLA | Liu, Shuya,et al."Composition and spatial-temporal dynamics of phytoplankton community shaped by environmental selection and interactions in the Jiaozhou Bay".WATER RESEARCH 218(2022):12. |
入库方式： OAI收割
来源：海洋研究所
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