个人简介

湖南师范大学资源与环境科学学院讲师，硕士研究生导师（自然地理与学科教学方向）。

2019年博士毕业于加拿大魁北克大学蒙特利尔分校（UQAM）。

电子邮箱：zelin.liu@hunnu.edu.cn

主要研究方向

1、自然干扰对陆地生态系统的影响。

2、流域水文与碳循环

3、环境和生态学模型开发与应用。

主持或参加科研项目

1、国家自然科学基金，面上项目，项目名称《虫害叶损失对亚热带常绿森林的固碳影响机理及模拟预测研究》，2024-2027，主持。

2、国家自然科学基金联合基金重点支持项目，项目名称《洞庭湖流域典型自然生态系统碳汇功能演变规律及影响机制》，2023-2026，子课题主持。

3、湖南省自然科学基金，面上项目，项目名称《洞庭湖流域森林非结构性碳对虫害叶损失的响应及模拟研究》，2024-2026，主持。

4、湖南省教育厅科学研究项目，优秀青年项目，项目名称《基于TRIPLEX模型的长株潭城市森林碳收支时空动态对极端气候变化响应的模拟研究》，2020-2022，主持。

5、湖南创新型省份建设专项重点领域研发计划，项目名称《湖南省森林碳中和技术研究》，2021-2023，参与

6、Natural Sciences and Engineering Research Council of Canada (NSERC) 资助项目（加拿大），项目名称《Evaluating and forecasting climate-induced tree mortality risks and uncertainties of Quebec boreal forests under a changing climate》，2017-2019，参与。

7、Fonds de recherche du Québec (FQRNT) 资助项目（加拿大），项目名称《Understanding, Quantifying, and Predicting Greenhouse Gas Emissions and Budgets of Forest Soils under a Changing Climate in Canada》，2015-2019，参与。

代表性论文

Zhu, Y., Liu, C*., Peng, C., Zhou, X., Xie, B., Li, T., Li, P., Zou, Z., Tang, J., and Liu, Z*. (2024). Applications of structural equation modeling in plant functional trait research. Environmental Reviews, dx.doi.org/10.1139/er-2023-0128.

Yang, M., Zhou, X*., Liu, Z*., Li, P*., Liu, C., Huang, H., Tang, J., Zhang, C., Zou, Z., Xie, B., and Peng, C. (2024). Dynamic carbon allocation trade-off: A robust approach to model tree biomass allometry. Methods in Ecology and Evolution, 15, 886-899.

Liu, H., Li, P., Peng, C., Liu, C., Zhou, X., Deng, Z., Zhang, C*., and Liu, Z*. (2023). Application of climate change scenarios in the simulation of forest ecosystems: An overview. Environmental Reviews, dx.doi.org/10.1139/er-2022-0111.

Liu, Z., Peng, C., MacLean, D., Grandpre, L., Candau, J., and Kneeshaw, D. (2022). Evaluating and quantifying the effect of various spruce budworm intervention strategies on forest carbon dynamics in Atlantic Canada. Forest Ecosystems. 9, 100052. DOI: doi.org/10.1016/j.fecs.2022.100052.

Liu, Z., Peng, C., De Grandpré, L., Candau, J.N., Work, T., Zhou, X., and Kneeshaw, D. (2020). Aerial spraying of spruce budworm leads to environmental benefits of reduced carbon losses especially in fir dominated forests. Ecosphere, 11 (1).

Liu, Z., Peng, C., De Grandpré, L., Candau, J.N., Work, T., Huang, C., and Kneeshaw, D. (2019). Simulation and analysis of the effect of spruce budworm outbreak on carbon dynamics in boreal forests of Quebec. Ecosystems. 22, 1838-1851.

Liu, Z., Peng, C., Work, T., Candau, J.N., DesRochers, A., and Kneeshaw, D. (2018). Application of machine-learning methods in forest ecology: recent progress and future challenges. Environmental Reviews, (999), 1-12.

Liu, Z., Peng, C., Louis, D., Candau, J.N., Zhou, X., and Kneeshaw, D. (2018). Development of a New TRIPLEX-Insect Model for Simulating the Effect of Spruce Budworm on Forest Carbon Dynamics. Forests, 9(9), 513.

Liu, Z., Peng, C., Xiang, W., Deng, X., Tian, D., Zhao, M., and Yu, G. (2012). Simulations of runoff and evapotranspiration in Chinese fir plantation ecosystems using artificial neural networks. Ecological modelling, 226, 71-76.

Liu, Z., Peng, C., Xiang, W., Tian, D., Deng, X., and Zhao, M. (2010). Application of artificial neural networks in global climate change and ecological research: An overview. Chinese science bulletin, 55(34), 3853-3863.

Liu, Q., Peng, C., Schneider, R., Cyr, D., Liu, Z., Zhou, X., Du, M., Li, P., Jiang, Z., McDowell, N., and Kneeshaw, D. (2023). Vegetation browning: global drivers, impacts, and feedbacks. Trends in Plant Science, 28(9), 1014-1032.

Zhou, X., Yang, M., Liu, Z., Li, P., Xie, B., and Peng, C. (2021). Dynamic allometric scaling of tree biomass and size. Nature, Plants. 1-8. DOI: 10.1038/s41477-020-00815-8.

Wu, C., Chen, Y., Hong, X., Liu, Z., and Peng, C. (2020). Evaluating soil nutrients of Dacrydium pectinatum in China using machine learning techniques. Forest Ecosystems, 7:30.

Yue, K., Fornara, D.A., Yang, W., Peng, Y., Peng, C., Liu, Z., and Wu, F. (2017). Influence of multiple global change drivers on terrestrial carbon storage: additive effects are common. Ecology letters, 20(5), 663-672.