Min Zhang

Dr. Min Zhang


Research Focus & Metrics

Academic Career Length

6Years (2021-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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2 July 2022 in Chemosphere
Verified
Journal Article
Closed access
YZYangkai Zhang
Yangkai Zhang
LCLiu Cao
Liu Cao
HFHaibin Fu
Haibin Fu
MZMin Zhang
Min Zhang
JMJun Meng
Jun Meng
ZGZhanhu Guo
Zhanhu Guo

17 November 2021 in Advanced Composites and Hybrid Materials
Verified
Journal Article
Closed access
PDF file
XBXueWei Bai
XueWei Bai
JLJuan Liu
Juan Liu
HFHaibin Fu
Haibin Fu
XGXinyu Gao
Xinyu Gao
MZMin Zhang
Min Zhang
JGJiang Guo
Jiang Guo

4 December 2024 in Forests
Verified
Journal Article
Open access
PDF file
Shuai WangShuai Wang
Shuai Wang
YGYuxi Guan
Yuxi Guan
ZWZicheng Wang
Zicheng Wang
ZYZijiao Yang
Zijiao Yang
CLChen Li
Chen Li
MZMin Zhang
Min Zhang
Soil organic carbon (SOC) serves as a highly sensitive indicator of climate change and plays a crucial role in terrestrial carbon cycles. Evaluating the impact of regional land use changes on SOC stocks is essential for assessing ecological and environmental effects. In this study, we utilized 157 soil samples and 11 environmental variables—including soil properties, topographic factors, and climatic conditions—to develop boosted regression tree (BRT) and random forest (RF) models to estimate topsoil SOC stocks for the year 2015. We used a 10-fold cross-validation approach, along with four validation metrics, to assess model performance. The BRT model demonstrated superior accuracy, with a higher R2 and Lin’s consistency correlation coefficient and a lower mean absolute error and root mean square error compared to the RF model. The key environmental factors influencing SOC stock variability in the BRT model included mean annual temperature, elevation, mean annual precipitation, the topographic wetness index (TWI), and catchment area. Based on this, we employed the space-for-time substitution approach and BRT model to forecast the spatial distribution of soil organic carbon (SOC) stocks in Northeast China’s forested regions under future climate scenarios for the 2050s and 2090s. Our findings indicate that, compared to the 2015 levels, the forecast indicates that SOC stocks will decrease by 122 Tg carbon and 123 Tg carbon under two different future scenarios, SSP245 and SSP585, respectively, by the 2050s. By the 2090s, these figures are expected to decrease further by 127 Tg C and 126 Tg C, respectively. Throughout both future periods, SOC stocks will predominantly be concentrated in the northwest region. This research highlights the necessity of thoroughly considering climatic factors in future studies of regional SOC stock dynamics. Moreover, the high-resolution maps produced in this study offer a scientific foundation for enhancing the implementation of ecological management practices in the forested regions of Northeast China, fostering environmental improvement and bolstering SOC and soil management strategies in response to future climate change.