Carbon and Nitrogen Turnover Times of South Korean Forests Estimated via Data-Model Fusion

Hyung Sub Kim, Yiqi Luo, Florent Noulèkoun, Nam Jin Noh, Jongyeol Lee, Yowhan Son

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Biogeochemical models use estimates of carbon (C) and nitrogen (N) turnover times for the future projection of global forest C and N stocks, but unexplained variation in the C and N turnover times is causing considerable uncertainty. This study aimed to estimate C and N turnover times of South Korean forests and explain their variation with forest type, temperature, precipitation, stand age, and ecosystem C:N ratio. We used the balance method and data-model fusion to estimate the C and N turnover times. Data-model fusion was used to integrate the National Forest Inventory data (2011–2020) with a biogeochemical model, Forest Biomass and Dead organic matter Carbon and Nitrogen (FBD-CAN). The N turnover time (376–499 years) was ∼45 times longer than the C turnover time (9–10 years). Forest type had no substantial effects on the C and N turnover times. However, the C and N turnover times were positively correlated with stand age and ecosystem C:N ratio, and negatively correlated with temperature. Overall, ecosystem C:N ratio, stand age, temperature, and precipitation explained 45%, 15%, 12%, and 3%, respectively, of the total variation of the C and N turnover times. These results contribute to the understanding and prediction of forest C and N changes in a changing world and highlight the importance of considering C:N ratio for reliable estimation of the C and N turnover times.

Original languageEnglish
Article numbere2021JG006368
JournalJournal of Geophysical Research G: Biogeosciences
Volume126
Issue number10
DOIs
Publication statusPublished - 2021 Oct

Bibliographical note

Funding Information:
This work was financially supported by the National Research Foundation of Korea (NRF-2018R1A2B6001012) and by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure, and Transport (Grant 20UMRG-B158194-01). The authors gratefully appreciate the theoretical and practical supports of Northern Arizona University for holding “2nd Training Course on New Advances in Land Carbon Cycle Modeling.” Florent Noulèkoun specifically acknowledges the support of the BK21 (Brain Korea 21 Program for Leading Universities and Students) FOUR program (Grant No. 4120200313708) and that of the Grant No. 2019R1I1A1A01064336, both funded by the National Research Foundation of Korea (NRF).

Funding Information:
This work was financially supported by the National Research Foundation of Korea (NRF‐2018R1A2B6001012) and by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure, and Transport (Grant 20UMRG‐B158194‐01). The authors gratefully appreciate the theoretical and practical supports of Northern Arizona University for holding “2nd Training Course on New Advances in Land Carbon Cycle Modeling.” Florent Noulèkoun specifically acknowledges the support of the BK21 (Brain Korea 21 Program for Leading Universities and Students) FOUR program (Grant No. 4120200313708) and that of the Grant No. 2019R1I1A1A01064336, both funded by the National Research Foundation of Korea (NRF).

Publisher Copyright:
© 2021. American Geophysical Union. All Rights Reserved.

ASJC Scopus subject areas

  • Soil Science
  • Forestry
  • Water Science and Technology
  • Palaeontology
  • Atmospheric Science
  • Aquatic Science
  • Ecology

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