Qin et al. (2025) Response of SOC stocks in Northeast China to climate warming and precipitation changes

Identification

• Journal: CATENA
• Year: 2025
• Date: 2025-12-03
• Authors: Z. H. Qin, Huanjun Liu, Xiangtian Meng, Baicheng Du, Depiao Kong, Ying Zhan
• DOI: 10.1016/j.catena.2025.109682

Research Groups

• State Key Laboratory of Black Soils Conservation and Utilization, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences
• Jilin Jianzhu University

Short Summary

This study investigated the spatio-temporal dynamics and driving mechanisms of soil organic carbon (SOC) stocks in Northeast China under climate warming and precipitation changes, revealing a net SOC loss between 1985 and 2020 and projecting significant future declines, particularly in croplands, due to warming and drought.

Objective

• To elucidate the mechanisms of compound effects of temperature and precipitation on soil organic carbon (SOC) stock dynamics in Northeast China.
• To predict the spatio-temporal dynamics of SOC and simulate future scenarios under gradient changes of temperature and precipitation.

Study Configuration

• Spatial Scale: Northeast China (regional scale).
• Temporal Scale: Historical analysis from 1985 to 2020; Future scenario simulations with temperature changes (0–4 °C) and precipitation changes (−50 % to +50 %).

Methodology and Data

• Models used: Bayesian optimized XGBoost model (for prediction), Structural Equation Modeling (SEM), Partial Dependency Plots (for mechanism analysis).
• Data sources: Integrated spatio-temporal substitution method and meta-analytical framework (implying a synthesis of existing data/studies, likely including observational and/or reanalysis data for climate and SOC).

Main Results

• The regional SOC stock in Northeast China experienced a net loss of 5.38 Mg C/ha between 1985 and 2020, with carbon loss zones nearly twice the area of positive change zones.
• Climatic factors accounted for 50% of SOC variability, with average temperature (TAVG) being the primary negative driver. A critical temperature threshold of -1 °C was identified, below which low temperatures inhibit microbial activity and promote carbon accumulation, and above which cascading degradation amplifies SOC loss. Precipitation (PR) mitigates this loss through multi-pathway synergistic effects.
• Future warming scenarios project a systematic decline in SOC, with significant loss for every 1 °C warming. The synergistic effect of high temperature (4 °C warming) and drought (50% precipitation reduction) leads to a 26.89% SOC loss. The compensatory effect of increased precipitation diminishes with warming (e.g., 50% precipitation increase at 4 °C warming only increases SOC by 0.70%).
• Ecosystems show varying sensitivities: croplands are the most sensitive (28.83% loss from warming and drying), forests are the most stable (due to litter cover buffer), and wetlands are highly dependent on water (50% precipitation increase offsets the negative effect of 4 °C warming).

Contributions

• Developed an integrated approach combining spatio-temporal substitution, meta-analysis, Bayesian optimized XGBoost, structural equation modeling, and partial dependency plots for high-accuracy SOC dynamics prediction and mechanism analysis.
• Identified a critical temperature threshold (-1 °C) for SOC dynamics in Northeast China, revealing a cascading degradation mechanism above this threshold.
• Quantified the compound effects of temperature and precipitation on SOC stocks under future climate change scenarios, highlighting the diminishing compensatory effect of increased precipitation with warming.
• Provided differentiated ecosystem responses to climate change, emphasizing the vulnerability of croplands and the buffering capacity of forests and wetlands.

Funding

• Not specified in the provided text.

Citation

@article{Qin2025Response,
  author = {Qin, Z. H. and Liu, Huanjun and Meng, Xiangtian and Du, Baicheng and Kong, Depiao and Zhan, Ying},
  title = {Response of SOC stocks in Northeast China to climate warming and precipitation changes},
  journal = {CATENA},
  year = {2025},
  doi = {10.1016/j.catena.2025.109682},
  url = {https://doi.org/10.1016/j.catena.2025.109682}
}