Hoyos-Sanclemente Andrea, Menjivar-Flores Juan Carlos, Rueda-Saa German
Departamento de Ingeniería, Facultad de Ingeniería y Administración, Universidad Nacional de Colombia, Sede Palmira, Palmira, Colombia.
Departamento de Ciencias Agrícolas, Facultad de Ciencias Agropecuarias, Universidad Nacional de Colombia, Sede Palmira, Palmira, Colombia.
Environ Monit Assess. 2025 May 30;197(6):697. doi: 10.1007/s10661-025-14123-1.
This study assessed soil organic carbon (SOC) content and its spatial variability at 130 agricultural sites of an inter-Andean valley in the Guachal watershed in southwestern Colombia. The research tested two hypotheses: (1) the SOC content varies significantly across orders, types, and environmental conditions and (2) geostatistical methods incorporating auxiliary variables improve the accuracy of SOC prediction. Ordinary kriging (OK) and cokriging (CK) techniques were used to map SOC based on soil properties and environmental variables. The content of SOC varied from 20 to 294 t ha. The CK performed better than OK by including additional variables such as total nitrogen, pH, and Fe, reducing prediction error and improving spatial accuracy. The highest SOC content (174.83 t ha) was observed in soils from the order andisols located on steep slopes (50-75%) and in cold climates (12-18 °C) with secondary vegetation. Soils from the order mollisol, located in flat areas, with temperatures above 24 °C and covered by cultivated pastures, had the lowest organic carbon content (20.42 t ha). The major agricultural crops (sugarcane and cocoa) showed minimal variability in SOC reserves. These results indicate the critical role of soil order, land use, and environmental factors in SOC distribution. Furthermore, they provide essential information for policies aimed at improving carbon sequestration and sustainable soil management in tropical agricultural landscapes.
本研究评估了哥伦比亚西南部瓜查尔流域安第斯山间谷地130个农业地点的土壤有机碳(SOC)含量及其空间变异性。该研究检验了两个假设:(1)SOC含量在土纲、土壤类型和环境条件之间存在显著差异;(2)纳入辅助变量的地统计方法可提高SOC预测的准确性。基于土壤性质和环境变量,使用普通克里金法(OK)和协同克里金法(CK)绘制SOC图。SOC含量在20至294吨/公顷之间变化。通过纳入总氮、pH值和铁等额外变量,CK的表现优于OK,减少了预测误差并提高了空间精度。在陡坡(50 - 75%)、寒冷气候(12 - 18°C)且有次生植被的安山土纲土壤中,观察到最高的SOC含量(174.83吨/公顷)。位于平坦地区、温度高于24°C且覆盖有人工牧场的软土纲土壤,有机碳含量最低(20.42吨/公顷)。主要农作物(甘蔗和可可)的SOC储量变化最小。这些结果表明土纲、土地利用和环境因素在SOC分布中的关键作用。此外,它们为旨在改善热带农业景观中碳固存和可持续土壤管理的政策提供了重要信息。