Soil temperature and respiration dataset from Mt. Namsan: Long-term projection and its implications under SSP climate scenarios

This study presents a comprehensive dataset of soil temperature and respiration measurements from Mt. Namsan, South Korea, collected between 2009 and 2010, with estimated values for 2011 to 2020 and projections for 2021 to 2100 under Shared Socioeconomic Pathways (SSP) climate scenarios ranging from SSP1-2.6 to SSP5-8.5. Soil respiration (mg CO₂ m⁻² h⁻¹) and temperature (°C) were measured using automated sensors and the closed chamber method. Regression models were developed to estimate soil temperature for 2011-2020 and predict future trends based on SSP scenarios. The results demonstrate significant increases in soil respiration rates under SSP5-8.5, highlighting the temperature sensitivity of soil carbon fluxes. This dataset provides valuable insights for ecological modeling, long-term carbon budget analysis, and climate change adaptation studies in temperate forest ecosystems.

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Publication Details

Journal
Data in Brief
Published
2025-02-18
DOI
https://doi.org/10.1016/j.dib.2025.111397
Citations
2
Primary Topic
Agriculture, Soil, Plant Science
Type
article
Field-Weighted Citation Impact
6.05
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article

Soil temperature and respiration dataset from Mt. Namsan: Long-term projection and its implications under SSP climate scenarios

Young-Ju Yu, Yong‐Su Kwon, Jae‐Ho Lee, Jae‐Seok Lee
2 citations
Data in Brief
Agriculture, Soil, Plant Science
6.05
article

Soil temperature and respiration dataset from Mt. Namsan: Long-term projection and its implications under SSP climate scenarios

Young-Ju Yu, Yong‐Su Kwon, Jae‐Ho Lee, Jae‐Seok Lee
article en
2 citations

Abstract

This study presents a comprehensive dataset of soil temperature and respiration measurements from Mt. Namsan, South Korea, collected between 2009 and 2010, with estimated values for 2011 to 2020 and projections for 2021 to 2100 under Shared Socioeconomic Pathways (SSP) climate scenarios ranging from SSP1-2.6 to SSP5-8.5. Soil respiration (mg CO₂ m⁻² h⁻¹) and temperature (°C) were measured using automated sensors and the closed chamber method. Regression models were developed to estimate soil temperature for 2011-2020 and predict future trends based on SSP scenarios. The results demonstrate significant increases in soil respiration rates under SSP5-8.5, highlighting the temperature sensitivity of soil carbon fluxes. This dataset provides valuable insights for ecological modeling, long-term carbon budget analysis, and climate change adaptation studies in temperate forest ecosystems.

Data in BriefVol. 59
Konkuk University (KR), National Institute of Ecology (IN), National IT industry Promotion Agency (KR)
Climate action
Openalex Percentile: Top 6%
Agriculture, Soil, Plant Science
6.05
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