{"title":"利用贝叶斯多源混合模型,利用正烷烃的浓度和δ13C量化沉积有机质中沉水植物的相对贡献:长江冲积平原案例研究","authors":"Linghan Zeng, Xianyu Huang, Deming Yang, Guang Yang, Yiming Zhang, Xu Chen","doi":"10.1029/2024JG008159","DOIUrl":null,"url":null,"abstract":"<p>Submerged macrophytes are important indicators of the state of shallow freshwater ecosystems. Reconstruction long-term changes in submerged macrophytes remains a challenge in paleoecology. Here, the relative biomass (mass weight) of different plants to sedimentary organic matter in a shallow lake in central China was estimated using a Bayesian multi-source mixing model with concentrations and δ<sup>13</sup>C of <i>n</i>-alkanes extracted from surface lake sediments. The spatial distribution of submerged macrophytes biomass estimated by the model correlates with water transparency, water depth, and total nitrogen. The correlation patterns are consistent with previously established patterns of submerged macrophyte growth and water conditions, which supports the utility of the Bayesian approach in shallow freshwater lakes. In comparison, <i>P</i><sub>aq</sub>, proportion of mid-chain length (C23, C25) to long-chain length (C29, C31) homologs, underestimated the contribution of submerged macrophytes, especially in samples with moderate <i>P</i><sub>aq</sub> values (0.3 < <i>P</i><sub>aq</sub> < 0.4). On the other hand, some discrepancies between the model output and the satellite imagery estimated macrophyte coverage are present, which suggests that ground-truthing is needed to further evaluate this approach. Our study demonstrates that the Bayesian mixing model combining the abundance and isotopes of <i>n</i>-alkanes makes a reasonable estimation of the relative biomass of submerged macrophytes in the sediments. This approach provides new insights into reconstructing long-term variations in submerged macrophytes for paleoecological studies, which is valuable for the restoration and conservation of shallow freshwater lakes when long-term limnological monitoring is lacking.</p>","PeriodicalId":16003,"journal":{"name":"Journal of Geophysical Research: Biogeosciences","volume":"129 9","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quantifying Relative Contribution of Submerged Macrophytes to Sedimentary Organic Matter Using Concentrations and δ13C of n-Alkanes With the Bayesian Multi-Source Mixing Model: A Case Study From the Yangtze Floodplain\",\"authors\":\"Linghan Zeng, Xianyu Huang, Deming Yang, Guang Yang, Yiming Zhang, Xu Chen\",\"doi\":\"10.1029/2024JG008159\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Submerged macrophytes are important indicators of the state of shallow freshwater ecosystems. Reconstruction long-term changes in submerged macrophytes remains a challenge in paleoecology. Here, the relative biomass (mass weight) of different plants to sedimentary organic matter in a shallow lake in central China was estimated using a Bayesian multi-source mixing model with concentrations and δ<sup>13</sup>C of <i>n</i>-alkanes extracted from surface lake sediments. The spatial distribution of submerged macrophytes biomass estimated by the model correlates with water transparency, water depth, and total nitrogen. The correlation patterns are consistent with previously established patterns of submerged macrophyte growth and water conditions, which supports the utility of the Bayesian approach in shallow freshwater lakes. In comparison, <i>P</i><sub>aq</sub>, proportion of mid-chain length (C23, C25) to long-chain length (C29, C31) homologs, underestimated the contribution of submerged macrophytes, especially in samples with moderate <i>P</i><sub>aq</sub> values (0.3 < <i>P</i><sub>aq</sub> < 0.4). On the other hand, some discrepancies between the model output and the satellite imagery estimated macrophyte coverage are present, which suggests that ground-truthing is needed to further evaluate this approach. Our study demonstrates that the Bayesian mixing model combining the abundance and isotopes of <i>n</i>-alkanes makes a reasonable estimation of the relative biomass of submerged macrophytes in the sediments. This approach provides new insights into reconstructing long-term variations in submerged macrophytes for paleoecological studies, which is valuable for the restoration and conservation of shallow freshwater lakes when long-term limnological monitoring is lacking.</p>\",\"PeriodicalId\":16003,\"journal\":{\"name\":\"Journal of Geophysical Research: Biogeosciences\",\"volume\":\"129 9\",\"pages\":\"\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2024-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Geophysical Research: Biogeosciences\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1029/2024JG008159\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Geophysical Research: Biogeosciences","FirstCategoryId":"93","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1029/2024JG008159","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Quantifying Relative Contribution of Submerged Macrophytes to Sedimentary Organic Matter Using Concentrations and δ13C of n-Alkanes With the Bayesian Multi-Source Mixing Model: A Case Study From the Yangtze Floodplain
Submerged macrophytes are important indicators of the state of shallow freshwater ecosystems. Reconstruction long-term changes in submerged macrophytes remains a challenge in paleoecology. Here, the relative biomass (mass weight) of different plants to sedimentary organic matter in a shallow lake in central China was estimated using a Bayesian multi-source mixing model with concentrations and δ13C of n-alkanes extracted from surface lake sediments. The spatial distribution of submerged macrophytes biomass estimated by the model correlates with water transparency, water depth, and total nitrogen. The correlation patterns are consistent with previously established patterns of submerged macrophyte growth and water conditions, which supports the utility of the Bayesian approach in shallow freshwater lakes. In comparison, Paq, proportion of mid-chain length (C23, C25) to long-chain length (C29, C31) homologs, underestimated the contribution of submerged macrophytes, especially in samples with moderate Paq values (0.3 < Paq < 0.4). On the other hand, some discrepancies between the model output and the satellite imagery estimated macrophyte coverage are present, which suggests that ground-truthing is needed to further evaluate this approach. Our study demonstrates that the Bayesian mixing model combining the abundance and isotopes of n-alkanes makes a reasonable estimation of the relative biomass of submerged macrophytes in the sediments. This approach provides new insights into reconstructing long-term variations in submerged macrophytes for paleoecological studies, which is valuable for the restoration and conservation of shallow freshwater lakes when long-term limnological monitoring is lacking.
期刊介绍:
JGR-Biogeosciences focuses on biogeosciences of the Earth system in the past, present, and future and the extension of this research to planetary studies. The emerging field of biogeosciences spans the intellectual interface between biology and the geosciences and attempts to understand the functions of the Earth system across multiple spatial and temporal scales. Studies in biogeosciences may use multiple lines of evidence drawn from diverse fields to gain a holistic understanding of terrestrial, freshwater, and marine ecosystems and extreme environments. Specific topics within the scope of the section include process-based theoretical, experimental, and field studies of biogeochemistry, biogeophysics, atmosphere-, land-, and ocean-ecosystem interactions, biomineralization, life in extreme environments, astrobiology, microbial processes, geomicrobiology, and evolutionary geobiology