首页|基于环境因子的全球主要陆地土壤δ15N分布图绘制

基于环境因子的全球主要陆地土壤δ15N分布图绘制

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基于全球812个样点的土壤δ15N与气象、土壤、地形和植被等环境因子数据集,通过随机森林回归算法构建土壤δ15N与环境因子关系的总集和分集模型,对比精度识别最优模型.根据最优模型和环境因子数据,绘制空间分辨率为0.25°的全球主要陆地自然生态系统土壤δ15N空间分布图.结果表明:总集模型精度为RMSE=1.63‰,R2=0.61;基于归一化植被指数(NDVI)分类的分集模型精度最高,为最优模型,平均精度为RMSE=1.19%c,R2=0.69;全球主要陆地自然生态系统土壤δ15N平均值为4.88‰,变化范围为-0.49‰~12.29‰,标准差为1.74‰.
Mapping of δ15N Distribution in Major Terrestrial Soil Worldwide Based on Environmental Factors
Based on a dataset of δ15N in soil from 812 sampling sites worldwide and environmental factors such as meteorology,soil,terrain and vegetation,a total model and sub model of the relationship betweenδ15N in soil and environmental factors were constructed using random forest regression algorithm,and the opti-mal model was identified through accuracy comparison.The spatial distribution of δ15N in soil from major terres-trial natural ecosystems worldwide with a spatial resolution of 0.25° was mapped based on the optimal model and environmental factor data.The results indicated that the accuracy of the total model was RMSE=1.63‰ and R2=0.61.The sub model based on normalized difference vegetation index(NDVI)classification had the high-est accuracy and was the optimal model,with an average accuracy of RMSE=1.19‰ and R2=0.69.The aver-age of δ15N in soil from major terrestrial natural ecosystems worldwide was 4.88‰,with a variation range of-0.49‰~12.29‰ and a standard deviation of 1.74‰.

δ15NNitrogen cycleEnvironmental factorsRandom forest regressionSoils

单阳、王霞、昝麒麟、赖晓明、姜晟、范清华、李娣、李旭文

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江苏省环境监测中心,江苏 南京 210041

中国科学院南京地理与湖泊研究所,江苏 南京 210008

δ15N 氮循环 环境因子 随机森林回归 土壤

2024

环境监测管理与技术
江苏省环境监测中心,南京市环境监测中心站

环境监测管理与技术

CSTPCD北大核心
影响因子:1.086
ISSN:1006-2009
年,卷(期):2024.36(6)