4.7 Article

Evaluation of soil carbon dynamics after forest cover change in CMIP6 land models using chronosequences

期刊

ENVIRONMENTAL RESEARCH LETTERS
卷 16, 期 7, 页码 -

出版社

IOP PUBLISHING LTD
DOI: 10.1088/1748-9326/ac0be1

关键词

soil carbon; land use change; model-data intercomparison; chronosequences

资金

  1. European Union [641816]
  2. Strategic Research Area MERGE
  3. Swedish national strategic e-science research program eSSENCE

向作者/读者索取更多资源

Land surface models are utilized to estimate global soil organic carbon (SOC) changes resulting from past and future land use changes. A study compared the performance of six different land models in simulating SOC changes after land use change, revealing significant discrepancies in their representations. While models generally capture the direction of SOC changes after reforestation of cropland, they exhibit notable differences in the magnitude and rate of changes.
Land surface models are used to provide global estimates of soil organic carbon (SOC) changes after past and future change land use change (LUC), in particular re-/deforestation. To evaluate how well the models capture decadal-scale changes in SOC after LUC, we provide the first consistent comparison of simulated time series of LUC by six land models all of which participated in the coupled model intercomparison project phase 6 (CMIP6) with soil carbon chronosequences (SCCs). For this comparison we use SOC measurements of adjacent plots at four high-quality data sites in temperate and tropical regions. We find that initial SOC stocks differ among models due to different approaches to represent SOC. Models generally meet the direction of SOC change after reforestation of cropland but the amplitude and rate of changes vary strongly among them. The normalized root mean square errors of the multi model mean range from 0.5 to 0.8 across sites and 0.1-0.7 when excluding outliers. Further, models simulate SOC losses after deforestation for crop or grassland too slow due to the lack of crop harvest impacts in the models or an overestimation of the SOC recovery on grassland. The representation of management, especially nitrogen levels is important to capture drops in SOC after land abandonment for forest regrowth. Crop harvest and fire management are important to match SOC dynamics but more difficult to quantify as SCC rarely report on these events. Based on our findings, we identify strengths and propose potential improvements of the applied models in simulating SOC changes after LUC.

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