气候变化领域集成服务门户(CCPortal): High-resolution mapping of soil carbon stocks in the western Amazon

CCPortal

DOI	10.1016/j.geodrs.2024.e00773
	High-resolution mapping of soil carbon stocks in the western Amazon
	Moquedacea, Cassio Marques; Baldia, Clara Gloria Oliveira; Siqueiraa, Rafael Gomes; Cardoso, Irene Maria; de Souza, Emanuel Fernando Maia; Fontes, Renildes Lucio Ferreira; Francelino, Marcio Rocha; Gomes, Lucas Carvalho; Fernandes-Filho, Elpidio Inacio
发表日期	2024
ISSN	2352-0094
起始页码	36
卷号	36
英文摘要	Global soil carbon maps are essential to understanding the global carbon cycle and supporting policy decisions, but their uncertainty in remote areas with limited data remains a significant challenge. Assessing and quantifying soil carbon at a regional level can shed light on existing uncertainties in global maps, providing more dependable information for stakeholders. Therefore, we aimed to model and map the soil organic carbon (SOC) stock in the Western Amazon, state of Rond & ocirc;nia, which witnessed a loss of 30% of its native coverage in the last 35 years. We used information from almost three thousand soil profiles that have not been included in the modeling of global and national existing soil maps. SOC stocks were stratified at 0-5, 5-15, 15-30, 30-60, and 60-100 cm depths and we selected the environmental predictors based on correlation < \|0.95\| and importance (recursive feature elimination). To reduce uncertainties and select the best model, we tested six different machine learning algorithms and ran the models 100 times for each depth with different subsets of samples, resulting in maps of mean, quantiles (Q05 and Q95), and uncertainty (Coefficient of variation). The Random Forest model presented the best performance, and the soil class was one of the predictors that most influenced the SOC stock, especially in the superficial layers (0-30 cm). The largest SOC stocks are in the southern region (protected areas), at low altitudes and places with seasonal flooding dynamics, and the smallest values are found in the central region, associated with the high-weathered Latossolos. Our results show that national and global maps overestimate SOC stocks (up +100 Mg C ha(-1)) in the central region with lower SOC stocks, and underestimate (- 400 Mg C ha(-1)) in the southern region with higher SOC stocks. These higher SOC stocks are concentrated in protected areas, but this information was hidden until now since global and national SOC maps could not identify these hotspots. Although global and national maps are handy for first assessment in locations without specific information, regional soil sampling and mapping should be used in hotspots of soil carbon sequestration and land use changes to ensure the continuous protection of these areas.
英文关键词	Amazon; Soil organic carbon; Random forest; Protected areas; Digital soil mapping; Rondo nia
语种	英语
WOS研究方向	Agriculture
WOS类目	Soil Science
WOS记录号	WOS:001194134100001
来源期刊	GEODERMA REGIONAL
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/306032
作者单位	Universidade Federal de Vicosa; Universidade Federal de Vicosa; Universidade Federal de Rondonia
推荐引用方式 GB/T 7714	Moquedacea, Cassio Marques,Baldia, Clara Gloria Oliveira,Siqueiraa, Rafael Gomes,et al. High-resolution mapping of soil carbon stocks in the western Amazon[J],2024,36.
APA	Moquedacea, Cassio Marques.,Baldia, Clara Gloria Oliveira.,Siqueiraa, Rafael Gomes.,Cardoso, Irene Maria.,de Souza, Emanuel Fernando Maia.,...&Fernandes-Filho, Elpidio Inacio.(2024).High-resolution mapping of soil carbon stocks in the western Amazon.GEODERMA REGIONAL,36.
MLA	Moquedacea, Cassio Marques,et al."High-resolution mapping of soil carbon stocks in the western Amazon".GEODERMA REGIONAL 36(2024).