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Modeling of grassland biomass and evaluation of uncertainties caused by differences in frozen soil type on the Qinghai Plateau

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Abstract

Global warming has caused changes in the area and thickness of permafrost on the Qinghai-Tibet Plateau and prompted the transition from permafrost to seasonally frozen soil, which has affected the soil moisture, soil temperature, and distribution of plant roots. This, in turn, affects grassland vegetation productivity and aboveground/belowground biomass. In this study, we took Qinghai Province in the northeastern Qinghai-Tibet Plateau as the research area to model the spatial pattern of grassland biomass and then evaluated the potential influence of frozen soil type information on aboveground and belowground biomass. Our research shows that there are significantly more biomass observations in seasonally frozen soil regions than in permafrost regions. However, when we ignore the type of frozen soil, the model does not show more accurate simulation in seasonally frozen soil regions, mainly because the stronger correlation between permafrost biomass and environmental factors, such as precipitation, compensates for the lack of observational data. In addition, we found that the biomass estimation error can be reduced significantly by building different models for each type of frozen soil, which implies that the type of frozen soil has an important impact on grassland biomass. Therefore, in considering the effects of future climate warming, more attention should be given to the impact of changes in frozen soil type on regional vegetation productivity. In addition, our investigation contributes a benchmark dataset of above- and belowground vegetation carbon storage in different frozen soil types, which provides the research community with useful information for optimizing process-based carbon cycle models.

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Data availability

The data and material analyzed in this study are available from the corresponding author upon reasonable request.

Code availability

The main data process is done using the corrplot and randomForest packet in R3.5.1. R code available on request from the authors.

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Acknowledgements

We would like to thank the high-performance computing support from the Center for Geodata and Analysis, Faculty of Geographical Science, Beijing Normal University (https://gda.bnu.edu.cn/).

Funding

This work was supported by the second Tibetan Plateau Scientific Expedition and Research Program (2019QZKK0405), the Key Special Foundation/Project of Science and Technology Department of Qinghai Province (Grant No. 2019-SF-A12), and the National Natural Science Foundation of China (42277206).

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Authors and Affiliations

  1. State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing, 100875, China

    Yajie Zhang, Tao Zhou, Peijun Shi, Xia Liu, Peixin Yu, Hui Luo, Peifang Zhou & Yixin Xu

  2. Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Faculty of Geographical Science, Beijing Normal University, Beijing, 100875, China

    Yajie Zhang, Tao Zhou, Peijun Shi, Xia Liu, Peixin Yu, Hui Luo, Peifang Zhou & Yixin Xu

  3. Academy of Plateau Science and Sustainability, People’s Government of Qinghai Province and Beijing Normal University, Xining, 810016, China

    Peijun Shi

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  1. Yajie Zhang
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Correspondence to Tao Zhou.

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Zhang, Y., Zhou, T., Shi, P. et al. Modeling of grassland biomass and evaluation of uncertainties caused by differences in frozen soil type on the Qinghai Plateau. Theor Appl Climatol 154, 1309–1322 (2023). https://doi.org/10.1007/s00704-023-04620-z

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