Min Zhang
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Min Zhang has a total of 26 co-authors. Here are the top co-authors by number of shared publications:
Haibin Fu
Technology Center, Shenyang Customs, Shenyang, 110016, China
2 shared publicationsHuanhuan Wei
College of Engineering, Shenyang Agricultural University, Shenyang, 110866, China
2 shared publicationsYangkai Zhang
College of Engineering, Shenyang Agricultural University, Shenyang, 110866, China
2 shared publications- Ben Bin Xu
School of Engineering, Physics and Mathematics, Northumbria University, Newcastle Upon Tyne, UK
1 shared publication - Chen Li
Zhangwu County Agricultural Development Service Center, Fuxin 123200, China
1 shared publication - Di Shi
College of Land and Environment, Shenyang Agricultural University, Shenyang 110866, China
1 shared publication
Latest Publications
- Open Access
Response of Topsoil Organic Carbon in the Forests of Northeast China Under Future Climate Scenarios
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.
Open AccessResponse of Topsoil Organic Carbon in the Forests of Northeast China Under Future Climate Scenarios
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.
- 2 July 2022
- Published by Elsevier in Chemosphere
- Vol. 306, 135567
Effect of sulfamethazine on anaerobic digestion of manure mediated by biochar
- 2 July 2022
- Published by Elsevier in Chemosphere
- Vol. 306, 135567
Effect of sulfamethazine on anaerobic digestion of manure mediated by biochar
- 17 November 2021
- Published by Springer Nature in Advanced Composites and Hybrid Materials
- Vol. 5 (1) , 294-306
Composting of mixture of total mixed ration and cow manure: quality of the finished compost
- 17 November 2021
- Published by Springer Nature in Advanced Composites and Hybrid Materials
- Vol. 5 (1) , 294-306
Composting of mixture of total mixed ration and cow manure: quality of the finished compost