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| Citation: | Sui Yue, Yang Chuanyu, 2025. Simulation of Mixed Needleleaf and Broadleaf Forest Distribution in Changbai Mountain of China Using CLM5-FATES Model. Earth Science, 50(9): 3357-3368. doi: 10.3799/dqkx.2025.073
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The broadleaved Korean pine forest in Changbai Mountain is one of the few large-area primary mixed needleleaf and broadleaf forest in the world, so it is particularly necessary to conduct simulation research on it. This study is based on the new generation dynamic vegetation model CLM5-FATES (Community Land Model version 5-Functionally Assembled Terrestrial Ecosystem Simulator), by selecting the maximum carboxylation rate at 25 ℃, specific leaf area, and leaf longevity to simulate the distribution of mixed needleleaf and broadleaf forest in Changbai Mountain. This paper explores the parameter sensitivity of the distribution of mixed needleleaf and broadleaf forest in the model, and investigates the model's ability to simulate the distribution of these forests. The study finds that different combinations of trait parameters significantly affect the distribution of vegetation types in the region. The maximum carboxylation rate at 25 ℃ and specific leaf area have a greater impact compared to leaf longevity. Under an appropriate combination of trait parameters, the model can reproduce the observed distribution of mixed needleleaf and broadleaf forest in Changbai Mountain. This study validates the applicability of the model to the mixed needleleaf and broadleaf forest in Changbai Mountain, providing crucial support for further research on climate-vegetation interactions.
|
Aboelyazeed, D., Xu, C. G., Hoffman, F. M., et al., 2023. A Differentiable, Physics-Informed Ecosystem Modeling and Learning Framework for Large-Scale Inverse Problems: Demonstration with Photosynthesis Simulations. Biogeosciences, 20(13): 2671-2692. https://doi.org/10.5194/bg-20-2671-2023
|
|
Argles, A. P. K., Moore, J. R., Cox, P. M., 2022. Dynamic Global Vegetation Models: Searching for the Balance between Demographic Process Representation and Computational Tractability. PLOS Climate, 1(9): e0000068. https://doi.org/10.1371/journal.pclm.0000068
|
|
Bao, Y., Wang, Y. Q., Nan, S. L., et al., 2023. Evaluation of Vegetation Characteristics over Qinghai-Xizang Plateau Simulated by a Vegetation Dynamic Model. Plateau Meteorology, 42(2): 333-343 (in Chinese with English abstract).
|
|
Bonan, G. B., 2008. Forests and Climate Change: Forcings, Feedbacks, and the Climate Benefits of Forests. Science, 320(5882): 1444-1449. https://doi.org/10.1126/science.1155121
|
|
Bonan, G. B., Doney, S. C., 2018. Climate, Ecosystems, and Planetary Futures: The Challenge to Predict Life in Earth System Models. Science, 359(6375): eaam8328. https://doi.org/10.1126/science.aam8328
|
|
Bonan, G. B., Lucier, O., Coen, D. R., et al., 2024. Reimagining Earth in the Earth System. Journal of Advances in Modeling Earth Systems, 16(8): e2023MS004017. https://doi.org/10.1029/2023MS004017
|
|
Cheng, K., Chen, Y. L., Xiang, T. Y., et al., 2024. A 2020 Forest Age Map for China with 30 m Resolution. Earth System Science Data, 16(2): 803-819. https://doi.org/10.5194/essd-16-803-2024
|
|
Cheng, Y. Y., Leung, L. R., Huang, M. Y., et al., 2022. Modeling the Joint Effects of Vegetation Characteristics and Soil Properties on Ecosystem Dynamics in a Panama Tropical Forest. Journal of Advances in Modeling Earth Systems, 14(1): e2021MS002603. https://doi.org/10.1029/2021MS002603
|
|
Dai, Y. J., Zeng, X. B., Dickinson, R. E., et al., 2003. The Common Land Model. Bulletin of the American Meteorological Society, 84(8): 1013-1024. https://doi.org/10.1175/bams-84-8-1013
|
|
Fisher, R. A., Koven, C. D., Anderegg, W. R. L., et al., 2018. Vegetation Demographics in Earth System Models: A Review of Progress and Priorities. Global Change Biology, 24(1): 35-54. https://doi.org/10.1111/gcb.13910
|
|
Fisher, R. A., Muszala, S., Verteinstein, M., et al., 2015. Taking off the Training Wheels: The Properties of a Dynamic Vegetation Model without Climate Envelopes, CLM4.5(ED). Geoscientific Model Development, 8(11): 3593-3619. https://doi.org/10.5194/gmd-8-3593-2015
|
|
Han, S. J., 2012. China Ecosystem Location Observation and Research Dataset, Forest Ecosystem Volume: Changbaishan Station from 2001 to 2008, Jilin. China Agriculture Press, Beijing (in Chinese).
|
|
Hao, Z. Q., Li, B. H., Zhang, J., et al., 2008. Broad-Leaved Korean Pine (Pinus Koraiensis) Mixed Forest Plot in Changbaishan (CBS) of China: Community Composition and Structure. Journal of Plant Ecology, 32(2): 238-250 (in Chinese with English abstract).
|
|
Kattge, J., Knorr, W., Raddatz, T., et al., 2009. Quantifying Photosynthetic Capacity and Its Relationship to Leaf Nitrogen Content for Global-Scale Terrestrial Biosphere Models. Global Change Biology, 15(4): 976-991. https://doi.org/10.1111/j.1365-2486.2008.01744.x
|
|
Koven, C. D., Knox, R. G., Fisher, R. A., et al., 2020. Benchmarking and Parameter Sensitivity of Physiological and Vegetation Dynamics Using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES) at Barro Colorado Island, Panama. Biogeosciences, 17(11): 3017-3044. https://doi.org/10.5194/bg-17-3017-2020
|
|
Lawrence, D. M., Fisher, R. A., Koven, C. D., et al., 2019. The Community Land Model Version 5: Description of New Features, Benchmarking, and Impact of Forcing Uncertainty. Journal of Advances in Modeling Earth Systems, 11(12): 4245-4287. https://doi.org/10.1029/2018MS001583
|
|
Li, S. Q., Zhang, X., Lu, Z. Y., et al., 2024. Progress of Vegetation Modelling and Future Research Prospects. Science China Earth Sciences, 54(9): 2762-2782 (in Chinese).
|
|
Li, X., Ma, H. Q., Ran, Y. H., et al., 2021. Terrestrial Carbon Cycle Model-Data Fusion: Progress and Challenges. Science China Earth Sciences, 51(10): 1650-1663 (in Chinese).
|
|
Liu, C. C., He, N. P., Li, Y., et al., 2024. Current and Future Trends of Plant Functional Traits in Macro-Ecology. Chinese Journal of Plant Ecology, 48(1): 21-40 (in Chinese with English abstract). doi: 10.17521/cjpe.2023.0111
|
|
Liu, K. J., He, N. P., Hou, J. H., 2022. Spatial Patterns and Influencing Factors of Specific Leaf Area in Typical Temperate Forests. Acta Ecologica Sinica, 42(3): 872-883 (in Chinese with English abstract).
|
|
Liu, Y. L., Holm, J. A., Koven, C. D., et al., 2024. Large Divergence of Projected High Latitude Vegetation Composition and Productivity Due to Functional Trait Uncertainty. Earth's Future, 12(8): e2024EF004563. https://doi.org/10.1029/2024EF004563
|
|
Massoud, E. C., Xu, C. G., Fisher, R. A., et al., 2019. Identification of Key Parameters Controlling Demographically Structured Vegetation Dynamics in a Land Surface Model: CLM4.5(FATES). Geoscientific Model Development, 12(9): 4133-4164. https://doi.org/10.5194/gmd-12-4133-2019
|
|
Peng, J. M., Liu, S. F., Dai, Y. J., et al., 2020. Evaluation of Common Land Model Based on International Land Model Benchmarking System. Climatic and Environmental Research, 25(6): 649-666 (in Chinese with English abstract).
|
|
Peng, S. S., Yue, C., Chang, J. F., 2020. Developments and Applications of Terrestrial Biosphere Model. Chinese Journal of Plant Ecology, 44(4): 436-448 (in Chinese with English abstract). doi: 10.17521/cjpe.2019.0315
|
|
Piao, S. L., Liu, Q., Chen, A. P., et al., 2019. Plant Phenology and Global Climate Change: Current Progresses and Challenges. Global Change Biology, 25(6): 1922-1940. https://doi.org/10.1111/gcb.14619
|
|
Shi, M. J., Keller, M., Bomfim, B., et al., 2024. Functionally Assembled Terrestrial Ecosystem Simulator (FATES) for Hurricane Disturbance and Recovery. Journal of Advances in Modeling Earth Systems, 16(1): e2023MS003679. https://doi.org/10.1029/2023MS003679
|
|
Sui, Y., Wei, M., Liu, B., 2025. Biophysical Impacts of Global Deforestation on Near-Surface Air Temperature in China: Results from Land Use Model Intercomparison Project Simulations. Advances in Atmospheric Sciences, 42(6): 1141-1155. https://doi.org/10.1007/s00376-024-4149-z
|
|
Viovy, N., 2018. CRUNCEP Version 7—Atmospheric Forcing Data for the Community Land Model. Research data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, Boulder, CO.
|
|
Wang, D. Y., Zeng, X. D., Song, X., 2024. Evaluation of CMIP6 Models in Simulating the Sensitivity of Leaf Area Index to Temperature and Precipitation Changes over China. Chinese Journal of Atmospheric Sciences, 48(5): 1961-1977 (in Chinese with English abstract).
|
|
Wright, I. J., Reich, P. B., Westoby, M., et al., 2004. The Worldwide Leaf Economics Spectrum. Nature, 428(6985): 821-827. https://doi.org/10.1038/nature02403
|
|
Xia, J. Y., Lu, R. L., Zhu, C., et al., 2020. Response and Adaptation of Terrestrial Ecosystem Processes to Climate Warming. Chinese Journal of Plant Ecology, 44(5): 494-514 (in Chinese with English abstract). doi: 10.17521/cjpe.2019.0323
|
|
Xie, X. Y., Li, A. N., Jin, H. A., 2018. The Simulation Models of the Forest Carbon Cycle on a Large Scale: A Review. Acta Ecologica Sinica, 38(1): 41-54 (in Chinese with English abstract).
|
|
Yang, Y. Z., Wang, H., Zhu, Q. A., et al., 2018. Research Progresses in Improving Dynamic Global Vegetation Models (DGVMS) with Plant Functional Traits. Chinese Science Bulletin, 63(25): 2599-2611 (in Chinese with English abstract). doi: 10.1360/N972018-00366
|
|
Zhang, Z. S., Li, S. L., Wang, H. J., et al., 2022. Introduction of Crossing Disciplines between Geology and Atmospheric Science. Earth Science, 47(10): 3569-3579 (in Chinese with English abstract).
|
|
Zhao, D. S., Wang, K., Cui, Y. P., 2023. Feedback Mechanisms and Regulatory Effects of Vegetation Change on Climate. Acta Ecologica Sinica, 43(19): 7830-7840 (in Chinese with English abstract).
|
|
Zhu, Q., Zhou, W. M., Jia, X., et al., 2019. Ecological Vulnerability Assessment on Changbai Mountain National Nature Reserve and Its Surrounding Areas, Northeast China. Chinese Journal of Applied Ecology, 30(5): 1633-1641 (in Chinese with English abstract).
|
|
鲍艳, 王玉琦, 南素兰, 等, 2023. 动态植被模型对青藏高原植被的模拟检验. 高原气象, 42(2): 333-343.
|
|
韩士杰, 2012. 中国生态系统定位观测与研究数据集, 森林生态系统卷: 吉林长白山站(2001-2008). 北京: 中国农业出版社.
|
|
郝占庆, 李步杭, 张健, 等, 2008. 长白山阔叶红松林样地(CBS): 群落组成与结构. 植物生态学报, 32(2): 238-250.
|
|
李思其, 张旭, 陆正遥, 等, 2024. 植被模型研究进展与展望. 中国科学: 地球科学, 54(9): 2762-2782.
|
|
李新, 马瀚青, 冉有华, 等, 2021. 陆地碳循环模型‒数据融合: 前沿与挑战. 中国科学: 地球科学, 51(10): 1650-1663.
|
|
刘聪聪, 何念鹏, 李颖, 等, 2024. 宏观生态学中的植物功能性状研究: 历史与发展趋势. 植物生态学报, 48(1): 21-40.
|
|
刘可佳, 何念鹏, 侯继华, 2022. 中国温带典型森林植物比叶面积的空间格局及其影响因素. 生态学报, 42(3): 872-883.
|
|
彭静漫, 刘少锋, 戴永久, 等, 2020. 基于陆面模式基准平台ILAMB对陆面模式CoLM的评估. 气候与环境研究, 25(6): 649-666.
|
|
彭书时, 岳超, 常锦峰, 2020. 陆地生物圈模型的发展与应用. 植物生态学报, 44(4): 436-448.
|
|
王丹云, 曾晓东, 宋翔, 2024. CMIP6模式关于中国叶面积指数对温度和降水变化敏感性的模拟能力评估. 大气科学, 48(5): 1961-1977.
|
|
夏建阳, 鲁芮伶, 朱辰, 等, 2020. 陆地生态系统过程对气候变暖的响应与适应. 植物生态学报, 44(5): 494-514.
|
|
谢馨瑶, 李爱农, 靳华安, 2018. 大尺度森林碳循环过程模拟模型综述. 生态学报, 38(1): 41-54.
|
|
杨延征, 王焓, 朱求安, 等, 2018. 植物功能性状对动态全球植被模型改进研究进展. 科学通报, 63(25): 2599-2611.
|
|
张仲石, 李双林, 王会军, 等, 2022. 浅谈大气科学与地质学的学科交叉. 地球科学, 47(10): 3569-3579. https://d.wanfangdata.com.cn/periodical/dqkx202210007
|
|
赵东升, 王珂, 崔耀平, 2023. 植被变化对气候的反馈机制及调节效应. 生态学报, 43(19): 7830-7840.
|
|
朱琪, 周旺明, 贾翔, 等, 2019. 长白山国家自然保护区及其周边地区生态脆弱性评估. 应用生态学报, 30(5): 1633-1641.
|
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