Molly D. O’Beirne, Jamie R. Vornlocher, Laura Lopera-Congote, Emeka E. Emordi, Godspower Ubit, Sergio Contreras, A. Araneda, E. Tejos, J. Moscoso, Josef P. Werne
{"title":"探索温度对智利湖泊和土壤brdgt分布的影响:原位测量和模拟温度数据的比较分析","authors":"Molly D. O’Beirne, Jamie R. Vornlocher, Laura Lopera-Congote, Emeka E. Emordi, Godspower Ubit, Sergio Contreras, A. Araneda, E. Tejos, J. Moscoso, Josef P. Werne","doi":"10.1029/2024JG008506","DOIUrl":null,"url":null,"abstract":"<p>Branched glycerol dialkyl glycerol tetraethers (brGDGTs) are bacterial membrane-spanning lipids that change in response to temperature variations. Their adaptability to temperature and widespread presence in sedimentary archives make brGDGTs a valuable tool for reconstructing past temperatures. However, the models used to relate brGDGT distributions to temperature vary widely (e.g., global vs. regional vs. site-specific, differing subsets of brGDGTs, and brGDGT-based indices), leading to inconsistencies in their application and inaccurate temperature predictions in some locations. Using previously published lacustrine and soil brGDGT distributions, we determined whether the type of temperature data used for model calibration (i.e., in situ vs. modeled air temperatures) influences the degree to which temperature relates to brGDGT distributions and therefore the fidelity with which brGDGT-based indices (i.e., MBT′<sub>5ME</sub>) may predict temperature. Accounting for differences in the number of samples among lake surface sediment and soil sample data sets, we find that the impact of temperature on brGDGT distribution significantly varies depending on both the temperature and sample data set used, with the most pronounced effects observed in lake surface sediment samples. Similarly, the MBT′<sub>5ME</sub> index shows varied correlations with temperature across different temperature and sample data sets. These findings suggest that other factors influence brGDGT distributions to a greater degree than temperature in some locations and that these effects are obscured when samples are combined into global data sets. This insight helps to explain why global brGDGT-based calibration models may not accurately predict temperatures at specific locations and underscores the need for targeted (e.g., cluster-based, regional, or site-specific) temperature calibration models.</p>","PeriodicalId":16003,"journal":{"name":"Journal of Geophysical Research: Biogeosciences","volume":"130 7","pages":""},"PeriodicalIF":3.7000,"publicationDate":"2025-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024JG008506","citationCount":"0","resultStr":"{\"title\":\"Exploring the Influence of Temperature on brGDGT Distributions in Chilean Lakes and Soils: A Comparative Analysis of In Situ Measured and Modeled Temperature Data\",\"authors\":\"Molly D. O’Beirne, Jamie R. Vornlocher, Laura Lopera-Congote, Emeka E. Emordi, Godspower Ubit, Sergio Contreras, A. Araneda, E. Tejos, J. Moscoso, Josef P. Werne\",\"doi\":\"10.1029/2024JG008506\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Branched glycerol dialkyl glycerol tetraethers (brGDGTs) are bacterial membrane-spanning lipids that change in response to temperature variations. Their adaptability to temperature and widespread presence in sedimentary archives make brGDGTs a valuable tool for reconstructing past temperatures. However, the models used to relate brGDGT distributions to temperature vary widely (e.g., global vs. regional vs. site-specific, differing subsets of brGDGTs, and brGDGT-based indices), leading to inconsistencies in their application and inaccurate temperature predictions in some locations. Using previously published lacustrine and soil brGDGT distributions, we determined whether the type of temperature data used for model calibration (i.e., in situ vs. modeled air temperatures) influences the degree to which temperature relates to brGDGT distributions and therefore the fidelity with which brGDGT-based indices (i.e., MBT′<sub>5ME</sub>) may predict temperature. Accounting for differences in the number of samples among lake surface sediment and soil sample data sets, we find that the impact of temperature on brGDGT distribution significantly varies depending on both the temperature and sample data set used, with the most pronounced effects observed in lake surface sediment samples. Similarly, the MBT′<sub>5ME</sub> index shows varied correlations with temperature across different temperature and sample data sets. These findings suggest that other factors influence brGDGT distributions to a greater degree than temperature in some locations and that these effects are obscured when samples are combined into global data sets. This insight helps to explain why global brGDGT-based calibration models may not accurately predict temperatures at specific locations and underscores the need for targeted (e.g., cluster-based, regional, or site-specific) temperature calibration models.</p>\",\"PeriodicalId\":16003,\"journal\":{\"name\":\"Journal of Geophysical Research: Biogeosciences\",\"volume\":\"130 7\",\"pages\":\"\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2025-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024JG008506\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Geophysical Research: Biogeosciences\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1029/2024JG008506\",\"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/10.1029/2024JG008506","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}
Exploring the Influence of Temperature on brGDGT Distributions in Chilean Lakes and Soils: A Comparative Analysis of In Situ Measured and Modeled Temperature Data
Branched glycerol dialkyl glycerol tetraethers (brGDGTs) are bacterial membrane-spanning lipids that change in response to temperature variations. Their adaptability to temperature and widespread presence in sedimentary archives make brGDGTs a valuable tool for reconstructing past temperatures. However, the models used to relate brGDGT distributions to temperature vary widely (e.g., global vs. regional vs. site-specific, differing subsets of brGDGTs, and brGDGT-based indices), leading to inconsistencies in their application and inaccurate temperature predictions in some locations. Using previously published lacustrine and soil brGDGT distributions, we determined whether the type of temperature data used for model calibration (i.e., in situ vs. modeled air temperatures) influences the degree to which temperature relates to brGDGT distributions and therefore the fidelity with which brGDGT-based indices (i.e., MBT′5ME) may predict temperature. Accounting for differences in the number of samples among lake surface sediment and soil sample data sets, we find that the impact of temperature on brGDGT distribution significantly varies depending on both the temperature and sample data set used, with the most pronounced effects observed in lake surface sediment samples. Similarly, the MBT′5ME index shows varied correlations with temperature across different temperature and sample data sets. These findings suggest that other factors influence brGDGT distributions to a greater degree than temperature in some locations and that these effects are obscured when samples are combined into global data sets. This insight helps to explain why global brGDGT-based calibration models may not accurately predict temperatures at specific locations and underscores the need for targeted (e.g., cluster-based, regional, or site-specific) temperature calibration models.
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