Integrated reconstruction of January and July temperature series in the Sanjiangyuan region during the Holocene

The Sanjiangyuan region, located in the hinterland of the Qinghai-Tibet Plateau(QTP), is highly sensitive to global climate change. Reconstructing its Holocene January and July temperatures is crucial for studying climate change and guiding ecological conservation in alpine regions. Current research on paleoclimate changes in Sanjiangyuan region primarily focuses on small subregions, limiting holistic understanding of regional climate.This study utilizes fossil pollen data, for the first time, integrates the Dynamic Multi-proxy Fusion and Scaling(DMFS) model to reconstruct the Holocene January and July temperature change sequences, thereby exploring temperature variations in the Sanjiangyuan region during 12.5 ka BP. The results indicated:12.5-6.0 ka BP: Both January and July temperatures showed a gradual increase,marking climatic improvement. 6.0-4.0 ka BP, both January and July temperatures remained at high levels, despite their fluctuations. During this period, temperatures reached their peak, reflecting a warm, humid, and most hospitable climate.4.0-2.5 ka BP: Both January and July temperatures showed declining trends to varying degrees, the climate became cold and dry. Post 2.5 ka BP: Both January and July temperatures rebounded. Comparisons with other high-resolution environmental records from the QTP confirmed consistent trends and synchronic dry-wet events. This study contributed essential fossil pollen data and paleotemperature records to the Sanjiangyuan region. This will fill a critical gap in paleoclimate research for the Sanjiangyuan region and provide valuable insights for long-term paleoclimate studies.

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Publication Details

Journal
PLoS ONE
Published
2026-01-20
DOI
https://doi.org/10.1371/journal.pone.0337521
Primary Topic
Geology and Paleoclimatology Research
Type
article
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article

Integrated reconstruction of January and July temperature series in the Sanjiangyuan region during the Holocene

Guangliang Hou, Yan Wang, Guangchao Cao, Li Yan et al.
PLoS ONE
Geology and Paleoclimatology Research
article

Integrated reconstruction of January and July temperature series in the Sanjiangyuan region during the Holocene

Guangliang Hou, Yan Wang, Guangchao Cao, Li Yan, Jinrong Hu, Tao Huang, Jian Ni
article en

Abstract

The Sanjiangyuan region, located in the hinterland of the Qinghai-Tibet Plateau(QTP), is highly sensitive to global climate change. Reconstructing its Holocene January and July temperatures is crucial for studying climate change and guiding ecological conservation in alpine regions. Current research on paleoclimate changes in Sanjiangyuan region primarily focuses on small subregions, limiting holistic understanding of regional climate.This study utilizes fossil pollen data, for the first time, integrates the Dynamic Multi-proxy Fusion and Scaling(DMFS) model to reconstruct the Holocene January and July temperature change sequences, thereby exploring temperature variations in the Sanjiangyuan region during 12.5 ka BP. The results indicated:12.5-6.0 ka BP: Both January and July temperatures showed a gradual increase,marking climatic improvement. 6.0-4.0 ka BP, both January and July temperatures remained at high levels, despite their fluctuations. During this period, temperatures reached their peak, reflecting a warm, humid, and most hospitable climate.4.0-2.5 ka BP: Both January and July temperatures showed declining trends to varying degrees, the climate became cold and dry. Post 2.5 ka BP: Both January and July temperatures rebounded. Comparisons with other high-resolution environmental records from the QTP confirmed consistent trends and synchronic dry-wet events. This study contributed essential fossil pollen data and paleotemperature records to the Sanjiangyuan region. This will fill a critical gap in paleoclimate research for the Sanjiangyuan region and provide valuable insights for long-term paleoclimate studies.

PLoS ONEVol. 21(1)
Zhejiang Normal University (CN), Qinghai Normal University (CN)
Climate action
Openalex Percentile: Top 86%
Geology and Paleoclimatology Research
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