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Estimating effective soil depth at regional scales: Legacy maps versus environmental covariates
Authors:Wentai Zhang  Guiqing Hu  Jiandong Sheng  David C Weindorf  Hongqi Wu  Junwei Xuan  An Yan  Zhujun Gu
Institution:1. Xinjiang Agricultural University, Xinjiang Key Laboratory of Soil and Plant Ecological Processes, College of Grassland and Environmental Sciences, Urumqi, China;2. Texas Tech University, Department of Plant and Soil Science, College of Agricultural Sciences and Natural Resources, Lubbock, USA;3. Nanjing Xiaozhuang University, School of Environmental Science, Nanjing, China
Abstract:Soil depth reflects the quantity and ecosystem service functions of soil resources. However, there is no universal standard to measure soil depth at present, and digital soil mapping approaches for predicting soil depth at the regional scale remain immature. Using observation of soil profile morphology, we compared the soil depth nomenclatures from the World Reference Base for Soil Resources, Chinese Soil Taxonomy, and Soil Taxonomy. For this study, shallow soils were defined as those with an effective soil depth < 100 cm. Based on legacy data and field soil survey, the spatial distribution of shallow soils in Xinjiang, China, and the main controlling environmental factors were explored. Results showed that shallow soils in Xinjiang are mainly distributed in high altitude regions such as the Tian Mountains. At the regional scale, significant correlations were observed between soil depth and climate factors, as well as between soil depth and vegetation fractional coverage. Contrary to previous conclusions at small spatial scales, terrain attributes could not explain soil depth variation at the regional scale. This study addressed knowledge gaps on soil depth prediction at regional scales while elucidating climate‐vegetation‐soil coevolution.
Keywords:digital soil mapping  multiple linear regression  soil landscape coevolution  soil profile morphology  soil thickness
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