PMID- 35982576
OWN - NLM
STAT- MEDLINE
DCOM- 20220822
LR  - 20220822
IS  - 1095-8630 (Electronic)
IS  - 0301-4797 (Linking)
VI  - 319
DP  - 2022 Oct 1
TI  - Dynamics of soil organic carbon and nitrogen and their relations to hydrothermal 
      variability in dryland.
PG  - 115751
LID - S0301-4797(22)01324-X [pii]
LID - 10.1016/j.jenvman.2022.115751 [doi]
AB  - Carbon (C) and nitrogen (N) cycles of terrestrial ecosystems play key roles in 
      global climate change and ecosystem sustainability. In recent decades, climate 
      change has threatened the nutrient balance of dryland ecosystems. However, its 
      impact on soil organic carbon (SOC) and soil total nitrogen (STN) in drylands of 
      China are still unclear. In this study, the structural equation model (SEM) was 
      used to explain the relationship between environmental variables used by the best 
      model and SOC or STN. Then Adaptive Boosting Regressor (AdaBoost), Gradient 
      Boosting Regression (GBRT), Extreme gradient boosting Regression (XGBoost) and 
      Random Forest Regression (RF) were used to establish the prediction model of SOC 
      and STN based on soil samples along with environmental variables. The performance 
      of these models was assessed based on a 10-fold cross-validation method using 
      three statistical indicators. Finally, we predicted the SOC and STN of soil 
      samples from 2000 to 2019 based on the best model. Overall, the RF model 
      performed better at predicting SOC and STN in drylands than the other three 
      prediction models (AdaBoost, GBRT, XGBoost). Climate factors were the main 
      factors affecting SOC and STN in the study area. In the Alashan, a dryland in 
      northern China, the precipitation in the growing season increased from 2000 to 
      2019, at a rate of 12.9 mm/decade. During the same period, the annual sunshine 
      duration significantly decreased by 66 h/decade. Along with interannual 
      hydrothermal variability, SOC showed a fluctuating upward trend at a rate of 
      0.04 g/kg/decade, while STN exhibited a fluctuating downward trend at 
      0.003 g/kg/decade from 2000 to 2019. Due to the effects of climate change, 
      dryland were considered as potential sites for carbon sequestration. However, due 
      to the annual hydrothermal variance causing dynamic annual changes, it was deemed 
      unstable. Moreover, it would cause STN loss, which might reduce soil fertility. 
      More attention should be paid to STN monitoring in dryland in the future.
CI  - Copyright (c) 2022 Elsevier Ltd. All rights reserved.
FAU - He, Mingzhu
AU  - He M
AD  - Shapotou Desert Research and Experiment Station, Northwest Institute of 
      Eco-Environment and Resources, Chinese Academy of Sciences, 730000, Lanzhou, 
      Gansu, China. Electronic address: hmzecology@lzb.ac.cn.
FAU - Tang, Liang
AU  - Tang L
AD  - Shapotou Desert Research and Experiment Station, Northwest Institute of 
      Eco-Environment and Resources, Chinese Academy of Sciences, 730000, Lanzhou, 
      Gansu, China. Electronic address: tangliangdyx@163.com.
FAU - Li, Chengyi
AU  - Li C
AD  - Shapotou Desert Research and Experiment Station, Northwest Institute of 
      Eco-Environment and Resources, Chinese Academy of Sciences, 730000, Lanzhou, 
      Gansu, China; University of Chinese Academy of Sciences, 100000, Beijing, China.
FAU - Ren, Jianxin
AU  - Ren J
AD  - Hami Agricultural Product Quality and Safety Inspection and Testing Center, 
      839000, Hami, Xinjiang, China.
FAU - Zhang, Libin
AU  - Zhang L
AD  - Shapotou Desert Research and Experiment Station, Northwest Institute of 
      Eco-Environment and Resources, Chinese Academy of Sciences, 730000, Lanzhou, 
      Gansu, China; University of Chinese Academy of Sciences, 100000, Beijing, China.
FAU - Li, Xinrong
AU  - Li X
AD  - Shapotou Desert Research and Experiment Station, Northwest Institute of 
      Eco-Environment and Resources, Chinese Academy of Sciences, 730000, Lanzhou, 
      Gansu, China.
LA  - eng
PT  - Journal Article
DEP - 20220720
PL  - England
TA  - J Environ Manage
JT  - Journal of environmental management
JID - 0401664
RN  - 0 (Soil)
RN  - 7440-44-0 (Carbon)
RN  - N762921K75 (Nitrogen)
SB  - IM
MH  - *Carbon/chemistry
MH  - Carbon Sequestration
MH  - China
MH  - Ecosystem
MH  - Nitrogen/analysis
MH  - *Soil/chemistry
OTO - NOTNLM
OT  - Climate change
OT  - Machine learning
OT  - Soil organic carbon
OT  - Soil total nitrogen
OT  - Structural equation model
EDAT- 2022/08/20 06:00
MHDA- 2022/08/23 06:00
CRDT- 2022/08/19 01:12
PHST- 2022/01/22 00:00 [received]
PHST- 2022/06/30 00:00 [revised]
PHST- 2022/07/10 00:00 [accepted]
PHST- 2022/08/19 01:12 [entrez]
PHST- 2022/08/20 06:00 [pubmed]
PHST- 2022/08/23 06:00 [medline]
AID - S0301-4797(22)01324-X [pii]
AID - 10.1016/j.jenvman.2022.115751 [doi]
PST - ppublish
SO  - J Environ Manage. 2022 Oct 1;319:115751. doi: 10.1016/j.jenvman.2022.115751. Epub 
      2022 Jul 20.