白云岩坡地土壤与表层岩溶带强风化层耦合结构特征
Journal of Soil and Water Conservation(2025)
Abstract
[目的]喀斯特区白云岩坡地植被恢复困难,石漠化治理难度大,其浅薄土层下伏的表层岩溶带深度参与生态系统过程,然而土壤与表层岩溶带二者的耦合发育关系尚不明确.[方法]选择典型白云岩山坡,在全坡面尺度上开展深入表层岩溶带强风化层底部的岩土探槽开挖试验,结合Kriging插值、地理加权回归分析等方法对土壤和表层岩溶带强风化层空间特征进行分析,初步探明白云岩坡地土壤与表层岩溶带强风化层间的空间耦合发育特征.[结果]1)白云岩坡地土壤和表层岩溶带强风化层厚度沿坡向下逐渐增加,坡地尺度上表层岩溶带强风化层平均厚度为50 cm,平均体积为0.47 m3/m2,占土壤全剖面总体积的43.9%,说明喀斯特区表层岩溶带的生态功能极其重要;2)白云岩坡地岩土结构呈极强的空间异质性,下伏表层岩溶带强风化层空间异质性(C+C0=18.88)显著高于上覆土壤层(C+C0=15.84);3)土壤总厚度,尤其是土壤B层厚度,与表层岩溶带风化程度呈显著正相关,说明土壤厚度的增加促进下伏表层岩溶带的风化,土壤和表层岩溶带强风化层间呈明显的耦合协同发育关系.[结论]喀斯特地区土壤和表层岩溶带强风化层协同演化,土壤层下伏的表层岩溶带可能是支撑喀斯特生态系统的重要介质,喀斯特水土资源的评估需要考虑除土壤以外的基岩风化层.土壤厚度及土壤发生层B层厚度可能成为预测喀斯特坡地表层岩溶带厚度的关键参数.
MoreTranslated text
Key words
karst critical zone,soil-epikarst system,karst ecosystems,karstification process,soil development
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper