NIGPAS OpenIR
Spatial pattern of marine oxygenation set by tectonic and ecological drivers over the Phanerozoic
通讯作者Wang, Xiangli(xlw@mail.iggcas.ac.cn) ; Li, Chao(chaoli@cdut.edu.cn)
Wang, Xiangli1,2; Algeo, Thomas J.3,4,5; Li, Chao6,7,8,9; Zhu, Maoyan2,10,11
2023-10-26
发表期刊NATURE GEOSCIENCE
ISSN1752-0894
页码19
摘要Marine redox conditions (that is, oxygen levels) impact a wide array of biogeochemical cycles, but the main controls of marine redox since the start of the Phanerozoic about 538 million years ago are not well established. Here we combine supervised machine learning with shale-hosted trace metal concentrations to reconstruct a near-continuous record of redox conditions in major marine depositional settings. We find synchronously opposite redox changes in upper ocean versus deep shelf and (semi-)restricted basin settings ('redox anticouples', nomen novum) in several multi-million-year intervals, which can be used to track the positions of oxygen-minimum zones and the primary locations of organic burial through time. These changes coincided with biological innovations that altered large-scale oxidant-reductant fluxes (mid-Palaeozoic spread of land plants; Mesozoic plankton revolution) and tectonic upheavals that regulated sea-level elevation (Pangaea amalgamation and break-up). We find that the pre-Devonian deep shelf was buffered at a largely anoxic state probably by dissolved organic matter, switched to a transitional state during the Devonian-Carboniferous interval characterized by the inception of persistent oxygen-minimum zones and subsequently shifted to a redox regime featuring thin oxygen-minimum zones ballasted probably by particulate organic matter. Deep shelf redox changes are correlated with background extinction rates of marine animals, and mass extinctions during major redox transitions generally were more severe. Tectonic and ecological factors controlled spatially contrasting marine redox changes through the Phanerozoic, a pattern that was in turn linked to background extinction rates, according to a machine learning-based analysis of shale geochemical data.
DOI10.1038/s41561-023-01296-y
收录类别SCI
语种英语
关键词[WOS]STATISTICAL-ANALYSIS ; OCEAN ACIDIFICATION ; MASS EXTINCTIONS ; ANOXIC EVENTS ; LAND PLANTS ; EVOLUTION ; MODEL ; RATES ; ORIGINATION ; SELECTIVITY
资助项目This research was supported by the National Natural Science Foundation of China (41888101 to X.W., C.L. and M.Z.; 42293293 to X.W.; 41921002 to M.Z.; 41821001, 41825019, 42130208 to C.L.), the National Key Research and Development Program of China (2022YFF[41888101] ; This research was supported by the National Natural Science Foundation of China (41888101 to X.W., C.L. and M.Z.; 42293293 to X.W.; 41921002 to M.Z.; 41821001, 41825019, 42130208 to C.L.), the National Key Research and Development Program of China (2022YFF[42293293] ; This research was supported by the National Natural Science Foundation of China (41888101 to X.W., C.L. and M.Z.; 42293293 to X.W.; 41921002 to M.Z.; 41821001, 41825019, 42130208 to C.L.), the National Key Research and Development Program of China (2022YFF[41921002] ; This research was supported by the National Natural Science Foundation of China (41888101 to X.W., C.L. and M.Z.; 42293293 to X.W.; 41921002 to M.Z.; 41821001, 41825019, 42130208 to C.L.), the National Key Research and Development Program of China (2022YFF[41821001] ; This research was supported by the National Natural Science Foundation of China (41888101 to X.W., C.L. and M.Z.; 42293293 to X.W.; 41921002 to M.Z.; 41821001, 41825019, 42130208 to C.L.), the National Key Research and Development Program of China (2022YFF[41825019] ; This research was supported by the National Natural Science Foundation of China (41888101 to X.W., C.L. and M.Z.; 42293293 to X.W.; 41921002 to M.Z.; 41821001, 41825019, 42130208 to C.L.), the National Key Research and Development Program of China (2022YFF[42130208] ; National Natural Science Foundation of China[2022YFF0800100] ; National Natural Science Foundation of China[2020YFA0607700] ; National Key Research and Development Program of China[BP0820004] ; 111 Project of China
WOS研究方向Geology
WOS类目Geosciences, Multidisciplinary
WOS记录号WOS:001089878800002
项目资助者This research was supported by the National Natural Science Foundation of China (41888101 to X.W., C.L. and M.Z.; 42293293 to X.W.; 41921002 to M.Z.; 41821001, 41825019, 42130208 to C.L.), the National Key Research and Development Program of China (2022YFF ; National Natural Science Foundation of China ; National Key Research and Development Program of China ; 111 Project of China
出版者NATURE PORTFOLIO
文献类型期刊论文
条目标识符http://ir.nigpas.ac.cn/handle/332004/43189
专题中国科学院南京地质古生物研究所
通讯作者Wang, Xiangli; Li, Chao
作者单位1.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Cenozo Geol & Environm, Beijing, Peoples R China
2.Univ Chinese Acad Sci, Coll Earth & Planetary Sci, Beijing, Peoples R China
3.China Univ Geosci, State Key Lab Biogeol & Environm Geol, Wuhan, Peoples R China
4.China Univ Geosci, State Key Lab Geol Proc & Mineral Resources, Wuhan, Peoples R China
5.Univ Cincinnati, Dept Geosci, Cincinnati, OH USA
6.Chengdu Univ Technol, State Key Lab Oil & Gas Reservoir Geol & Exploitat, Chengdu, Peoples R China
7.Chengdu Univ Technol, Inst Sedimentary Geol, Chengdu, Peoples R China
8.Chengdu Univ Technol, Key Lab Deep time Geog & Environm Reconstruct & Ap, Minist Nat Resources, Chengdu, Peoples R China
9.Chengdu Univ Technol, Int Ctr Sedimentary Geochem & Biogeochem Res, Chengdu, Peoples R China
10.Nanjing Inst Geol & Palaeontol, Chinese Acad Sci, State Key Lab Palaeobiol & Stratig, Nanjing, Peoples R China
推荐引用方式
GB/T 7714
Wang, Xiangli,Algeo, Thomas J.,Li, Chao,et al. Spatial pattern of marine oxygenation set by tectonic and ecological drivers over the Phanerozoic[J]. NATURE GEOSCIENCE,2023:19.
APA Wang, Xiangli,Algeo, Thomas J.,Li, Chao,&Zhu, Maoyan.(2023).Spatial pattern of marine oxygenation set by tectonic and ecological drivers over the Phanerozoic.NATURE GEOSCIENCE,19.
MLA Wang, Xiangli,et al."Spatial pattern of marine oxygenation set by tectonic and ecological drivers over the Phanerozoic".NATURE GEOSCIENCE (2023):19.
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