结合多指纹和非混合模型量化陆地-河流-湖泊连续体中的沉积有机碳源

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-04-01 DOI:10.1016/j.ijsrc.2023.12.003
Shilan Wang, Xiaodong Nie, Zhongwu Li, Fengwei Ran, Changrong Yang, Tao Xiao
{"title":"结合多指纹和非混合模型量化陆地-河流-湖泊连续体中的沉积有机碳源","authors":"Shilan Wang,&nbsp;Xiaodong Nie,&nbsp;Zhongwu Li,&nbsp;Fengwei Ran,&nbsp;Changrong Yang,&nbsp;Tao Xiao","doi":"10.1016/j.ijsrc.2023.12.003","DOIUrl":null,"url":null,"abstract":"<div><p>Identifying organic carbon (OC) sources in lake sediment is essential for elucidating biogeochemical cycling processes and effectively supporting watershed management. However, the complexity of sources as well as environments in the land–river–lake continuum makes it challenging to accurately identify OC sources. Accordingly, the current study utilized a systematic approach to identify and validate OC sources in a typical land–river–lake continuum. Two tracer groups (group 1: δ<sup>13</sup>C and δ<sup>15</sup>N; group 2: fluorescence index and biotic index, respectively (where C is carbon and N is nitrogen)) and one model (MixSIAR) were eventually selected from five tracer groups and two models to identify the OC sources in a land–river–lake continuum according to a consistency evaluation and virtual mixing test. The results showed that the distribution of OC sources in lake sediment was spatially heterogeneous. Closer to the lake center (from sampling site S1 to S3), the autochthonous contributions increased while the allochthonous contributions decreased. Downstream of the inlet river (site S1) was dominated by allochthonous contributions (78.6%), especially cropland (28.7% ± 0.5%, where ± indicates a standard deviation range) and urban land (30.5% ± 2.5%). From site S1 to S2, the allochthonous contribution decreased 11.4%. Autochthonous OC gradually became the major source closer to the lake center (site S3: phragmites: 48% ± 4.5%). This distribution of OC sources in the land–river–lake system was attributed to the mixing effect of the autochthonous sources, selective transport of sediment, and human activities. The current findings may aid in validating the ability of different tracers and models to identify OC sources in complex ecosystems and also provide a theoretical basis for watershed management.</p></div>","PeriodicalId":3,"journal":{"name":"ACS Applied Electronic Materials","volume":null,"pages":null},"PeriodicalIF":4.3000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S100162792300077X/pdfft?md5=509b4841b02a05621a24ace9664cde55&pid=1-s2.0-S100162792300077X-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Quantification of sedimentary organic carbon sources in a land–river–lake continuum combined with multi-fingerprint and un-mixing models\",\"authors\":\"Shilan Wang,&nbsp;Xiaodong Nie,&nbsp;Zhongwu Li,&nbsp;Fengwei Ran,&nbsp;Changrong Yang,&nbsp;Tao Xiao\",\"doi\":\"10.1016/j.ijsrc.2023.12.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Identifying organic carbon (OC) sources in lake sediment is essential for elucidating biogeochemical cycling processes and effectively supporting watershed management. However, the complexity of sources as well as environments in the land–river–lake continuum makes it challenging to accurately identify OC sources. Accordingly, the current study utilized a systematic approach to identify and validate OC sources in a typical land–river–lake continuum. Two tracer groups (group 1: δ<sup>13</sup>C and δ<sup>15</sup>N; group 2: fluorescence index and biotic index, respectively (where C is carbon and N is nitrogen)) and one model (MixSIAR) were eventually selected from five tracer groups and two models to identify the OC sources in a land–river–lake continuum according to a consistency evaluation and virtual mixing test. The results showed that the distribution of OC sources in lake sediment was spatially heterogeneous. Closer to the lake center (from sampling site S1 to S3), the autochthonous contributions increased while the allochthonous contributions decreased. Downstream of the inlet river (site S1) was dominated by allochthonous contributions (78.6%), especially cropland (28.7% ± 0.5%, where ± indicates a standard deviation range) and urban land (30.5% ± 2.5%). From site S1 to S2, the allochthonous contribution decreased 11.4%. Autochthonous OC gradually became the major source closer to the lake center (site S3: phragmites: 48% ± 4.5%). This distribution of OC sources in the land–river–lake system was attributed to the mixing effect of the autochthonous sources, selective transport of sediment, and human activities. The current findings may aid in validating the ability of different tracers and models to identify OC sources in complex ecosystems and also provide a theoretical basis for watershed management.</p></div>\",\"PeriodicalId\":3,\"journal\":{\"name\":\"ACS Applied Electronic Materials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.3000,\"publicationDate\":\"2024-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S100162792300077X/pdfft?md5=509b4841b02a05621a24ace9664cde55&pid=1-s2.0-S100162792300077X-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACS Applied Electronic Materials\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S100162792300077X\",\"RegionNum\":3,\"RegionCategory\":\"材料科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Electronic Materials","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S100162792300077X","RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

摘要

确定湖泊沉积物中的有机碳(OC)来源对于阐明生物地球化学循环过程和有效支持流域管理至关重要。然而,在陆地-河流-湖泊的连续过程中,来源和环境的复杂性使得准确识别 OC 来源具有挑战性。因此,本研究采用了一种系统方法来识别和验证典型陆地-河流-湖泊连续体中的 OC 来源。从五个示踪剂组和两个模型中最终选择了两个示踪剂组(第 1 组:δ13C 和 δ15N;第 2 组:荧光指数和生物指数,其中 C 为碳,N 为氮)和一个模型(MixSIAR),根据一致性评价和虚拟混合试验确定了陆地-河流-湖泊连续体中的 OC 来源。结果表明,湖泊沉积物中 OC 源的分布具有空间异质性。靠近湖心(采样点 S1 至 S3),自生贡献增加,异生贡献减少。入湖河流下游(S1 采样点)主要是异源物质(78.6%),尤其是耕地(28.7% ± 0.5%,± 表示标准偏差范围)和城市土地(30.5% ± 2.5%)。从 S1 地点到 S2 地点,异源占比下降了 11.4%。自生 OC 逐渐成为靠近湖心的主要来源(S3 点:葭萌:48% ± 4.5%)。陆地-河流-湖泊系统中 OC 来源的这种分布归因于自生来源的混合效应、沉积物的选择性迁移以及人类活动。目前的研究结果有助于验证不同示踪剂和模型识别复杂生态系统中 OC 来源的能力,也为流域管理提供了理论依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Quantification of sedimentary organic carbon sources in a land–river–lake continuum combined with multi-fingerprint and un-mixing models

Identifying organic carbon (OC) sources in lake sediment is essential for elucidating biogeochemical cycling processes and effectively supporting watershed management. However, the complexity of sources as well as environments in the land–river–lake continuum makes it challenging to accurately identify OC sources. Accordingly, the current study utilized a systematic approach to identify and validate OC sources in a typical land–river–lake continuum. Two tracer groups (group 1: δ13C and δ15N; group 2: fluorescence index and biotic index, respectively (where C is carbon and N is nitrogen)) and one model (MixSIAR) were eventually selected from five tracer groups and two models to identify the OC sources in a land–river–lake continuum according to a consistency evaluation and virtual mixing test. The results showed that the distribution of OC sources in lake sediment was spatially heterogeneous. Closer to the lake center (from sampling site S1 to S3), the autochthonous contributions increased while the allochthonous contributions decreased. Downstream of the inlet river (site S1) was dominated by allochthonous contributions (78.6%), especially cropland (28.7% ± 0.5%, where ± indicates a standard deviation range) and urban land (30.5% ± 2.5%). From site S1 to S2, the allochthonous contribution decreased 11.4%. Autochthonous OC gradually became the major source closer to the lake center (site S3: phragmites: 48% ± 4.5%). This distribution of OC sources in the land–river–lake system was attributed to the mixing effect of the autochthonous sources, selective transport of sediment, and human activities. The current findings may aid in validating the ability of different tracers and models to identify OC sources in complex ecosystems and also provide a theoretical basis for watershed management.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
7.20
自引率
4.30%
发文量
567
期刊最新文献
Hyperbaric oxygen treatment promotes tendon-bone interface healing in a rabbit model of rotator cuff tears. Oxygen-ozone therapy for myocardial ischemic stroke and cardiovascular disorders. Comparative study on the anti-inflammatory and protective effects of different oxygen therapy regimens on lipopolysaccharide-induced acute lung injury in mice. Heme oxygenase/carbon monoxide system and development of the heart. Hyperbaric oxygen for moderate-to-severe traumatic brain injury: outcomes 5-8 years after injury.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1