Using Soil Survey Database to Assess Soil Quality in the Heterogeneous Taihang Mountains, North China

Shoubao Geng, Peili Shi, Ning Zong and Wanrui Zhu
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Shoubao Geng: Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Peili Shi: Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Ning Zong: Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
Wanrui Zhu: Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

Sustainability, 2018, vol. 10, issue 10, 1-18

Abstract: Soil quality evaluation is an effective pathway to understanding the status of soil function and ecosystem productivity. Numerous studies have been made in managed ecosystems and land cover to quantify its effects on soil quality. However, little is coincident regarding soil quality assessment methods and its compatibility in highly heterogeneous soil. This paper used the soil survey database of Taihang Mountains as a case study to: (i) Examine the feasibility of soil quality evaluation with two different indicator methods: Total data set (TDS) and minimum data set (MDS); and (ii) analyze the controlling factors of regional soil quality. Principal component analysis (PCA) and the entropy method were used to calculate soil quality index (SQI). SQI values assessed from the TDS and MDS methods were both significantly correlated with normalized difference vegetation index ( p < 0.001), suggesting that both indices were effective to describe soil quality and reflect vegetation growth status. However, the TDS method represented a slightly more accurate assessment than MDS in terms of variance explanation. Boosted regression trees (BRT) models and path analysis showed that soil type and land cover were the most important controlling factors of soil quality, within which soil type had the greatest direct effect and land cover had the most indirect effect. Compared to MDS, TDS is a more sensitive method for assessing regional soil quality, especially in heterogeneous mountains. Soil type is the fundamental factor to determining soil quality. Vegetation and land cover indirectly modulate soil properties and soil quality.

Keywords: soil quality index; Taihang Mountains; soil survey database; method comparison; controlling factors (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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