Soil organic carbon density in Mexico under future climate change

被引:0
作者
Wang, Yuan [1 ]
机构
[1] Sichuan Normal Univ, Fac Geog Resource Sci, Chengdu 610101, Peoples R China
来源
SIXTH INTERNATIONAL CONFERENCE ON GEOSCIENCE AND REMOTE SENSING MAPPING, GRSM 2024, PT 1 | 2025年 / 13506卷
关键词
SOC density change; environmental covariates; random forest; climate change; Mexico;
D O I
10.1117/12.3057613
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Soil organic carbon (SOC) serves as a critical indicator of soil health, influencing both fertility and carbon sequestration potential. This study examines future soil organic carbon (SOC) stocks in Mexico under climate change scenarios, employing an innovative framework integrating high- resolution spatial data, machine learning, and climate projections. Utilizing a dataset of 24,000 samples and NASA's Carbon Monitoring System Program, we developed climate data-driven models to generate SOC maps for Mexico from 2021 to 2100 under SSP245 and SSP370 scenarios. Our optimized Random Forest model (R-squared = 0.4457) identified temperature seasonality, annual temperature range, and precipitation as key SOC drivers. Projections reveal complex SOC density changes, with both scenarios showing a 16.17% increase by 2040. However, by 2100, SSP245 maintains a 9.93% increase, while SSP370 preserves only a 2.97% increase. The southeastern region, particularly states like Chiapas and Tabasco, showed the highest SOC densities (8-12 kg/m(2)), while northern and northwestern regions displayed the lowest (<2 kg/m(2)). This research enhances our understanding of spatiotemporal SOC variations under future climate scenarios, providing critical insights for targeted interventions to preserve and enhance soil carbon stocks. Our findings have significant implications for sustainable land management and climate change mitigation strategies in Mexico, supporting policymakers in pursuing carbon neutrality goals.
引用
收藏
页数:7
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