Evaluation of soil quality in major grain-producing region of the North China Plain: Integrating minimum data set and established critical limits

Tian, Kang; Zhang, Beier; Zhang, Haidong; Huang, Biao; Darilek, Jeremy Landon; Zhao, Yanni; Yang, Jintao

doi:10.1016/j.ecolind.2020.106613

Cited by 28 publications

(16 citation statements)

References 56 publications

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“…The conventional approach to quantifying SQ measures the values of multiple indicators of SQ to form a composite soil quality index (SQI) (Karaca et al, 2021;Karlen et al, 1997;Tian et al, 2020).…”

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confidence: 99%

Soil quality assessment of cropland in China and its relationships with climate and topography

Chen

et al. 2022

Land Degrad Dev

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Assessing soil quality (SQ) of cropland is fundamental for food security and sustainable land management. However, there is limited information regarding SQ assessment on a national scale, which is vital to answer important SQ-related questions in quantitative terms on that scale. Here, the SQ of cropland in China was assessed by constructing a minimum data set (MDS) from 23 soil physicochemical properties based on principal component analysis. The interaction roles and relative contributions of climate and topography on SQ was evaluated by a structural equation model.The MDS comprised eight indicators: proportion of silt, bulk density, total phosphorus, total potassium, available nitrogen, exchangeable calcium, chlorite, and vermiculite. The soil quality index (SQI) varied from 0.245 to 0.705 and showed a clear pattern of decreasing quality from the north to the south of the country. Of the total cropland area in China, the largest share (27.91%) was of soils of high quality, followed by those of moderate quality (24.63%), low quality (20.37%), very high quality (14.18%), and very low quality (12.91%). The north and the south differed significantly in terms of total potassium, exchangeable calcium, chlorite, and vermiculite, which are the four most important indicators of SQ. Climate and elevation explained about 2.2%-30.1% of the variation in SQ on the national and regional scales. These findings suggest that croplands in southern China will benefit from potassium and calcium fertilizers, which will contribute to enhance food security and promote sustainable land management in China.

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confidence: 99%

Soil quality assessment of cropland in China and its relationships with climate and topography

Chen

et al. 2022

Land Degrad Dev

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“…The combination of Principal Component Analysis (PCA) with Norm Value Determination was used to obtain the pivotal constitutors (or indicators) of the soil MDS from the soil TDS (Yu et al, 2018;Tian et al, 2020). The grouping process of the PCA was referred to Jin et al (2021b).…”

Section: The Soil Mds Selection and Verificationmentioning

confidence: 99%

“…Researchers want to select a small number of indicators to provide an integrated, comprehensive, and accurate view of the overall soil properties, while maximizing the inclusion of all relevant information about the soil properties and minimizing data redundancy (Andrews et al, 2004). Larson and Pierce (1991) proposed the concept of a minimum data set of soil properties (soil MDS), whose core function is to establish a set of simplified and practical data (including few properties) to replace a large number of complex soil data, and to better grasp the whole characteristics or status of soils (Yu et al, 2018;Li et al, 2019;Tian et al, 2020). Such method saved the substantial cost of time and labor for measurement of all soil properties, and reduce data redundancy due to collinearity among different properties (Li et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Predicting spatial variability of species diversity with the minimum data set of soil properties in an arid desert riparian forest

Chen

et al. 2022

Front. Plant Sci.

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Species diversity has spatial heterogeneity in ecological systems. Although a large number of studies have demonstrated the influence of soil properties on species diversity, most of them have not considered their spatial variabilities. To remedy the knowledge gap, a 1 ha (100 m × 100 m) plots of arid desert riparian forest was set up in the Ebinur Wetland Nature Reserve (ELWNR) in the NW China. Then, the minimum data set of soil properties (soil MDS) was established using the Principal Component Analysis (PCA) and the Norm Value Determination to represent the total soil property data set (soil TDS). The Geo-statistics and two models (i.e., Random Forest/RF and Multiple Linear Regression/MLR) were used to measure the spatial variability of species diversity, and predict its spatial distribution by the soil MDS, respectively. The results showed that the soil MDS was composed of soil salt content (SSC), soil total phosphorus (STP), soil available phosphorus (SAP), soil organic carbon (SOC) and soil nitrate nitrogen (SNN); which represented the soil TDS perfectly (R2 =0.62). Three species diversity indices (i.e., Shannon–Wiener, Simpson and Pielou indices) had a high spatial dependence (C0/(C0+C)< 25%; 0.72 m ≤ range≤ 0.77 m). Ordinary kriging distribution maps showed that the spatial distribution pattern of species diversity predicted by RF model was closer to its actual distribution compared with MLR model. RF model results suggested that the soil MDS had significant effect on spatial distribution of Shannon–Wiener, Simpson and Pielou indices (Varex= 56%, 49% and 36%, respectively). Among all constituents, SSC had the largest contribution on the spatial variability of species diversity (nearly 10%), while STP had least effect (< 5.3%). We concluded that the soil MDS affected spatial variability of species diversity in arid desert riparian forests. Using RF model can predict spatial variability of species diversity through soil properties. Our work provided a new case and insight for studying the spatial relationship between soil properties and plant species diversity.

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“…Various methods have been developed to evaluate soil quality. The most important of which are soil quality indicators (SQI) and fuzzy methods (Qi et al 2009;Askari and Holden 2014;Jahany and Rezapour 2020;Tian et al 2020). The SQI approach has been used extensively to evaluate different soil types due to its flexibility and performance (Nabiollahi et al 2017;Raiesi 2017;Tian et al 2020;dos Santos et al 2021).…”

Section: Introductionmentioning

confidence: 99%

“…The most important of which are soil quality indicators (SQI) and fuzzy methods (Qi et al 2009;Askari and Holden 2014;Jahany and Rezapour 2020;Tian et al 2020). The SQI approach has been used extensively to evaluate different soil types due to its flexibility and performance (Nabiollahi et al 2017;Raiesi 2017;Tian et al 2020;dos Santos et al 2021). Soil quality has been also studied concerning various landscape properties including land use, topographic and morphological features (Davari et al 2020;Shao et al 2020;Derakhshan-Babaei et al 2021).…”

Section: Introductionmentioning

confidence: 99%

Effect of Landscape Fragmentation on Soil Quality and Ecosystem Services in Land Use and Landform Types

Mirghaed

Souri

2021

Preprint

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This study was carried out according to the following objectives in the Shoor River Basin in southwestern Iran: (i) Evaluation of ecosystem services (ES) including habitat quality (HQ), carbon storage (CS), nutrient export (NE), and soil export (SE) using the InVEST approach as well as soil quality (SQ) using an integrated quality index; (ii) Assessment of the relationship between ES and SQ with landscape metrics using Pearson correlation test; and (iii) Investigation of the interaction between ES efficiency, SQ and landscape fragmentation using a ternary plot. The results showed that the northern and eastern parts of the region are prioritized for HQ, CS, and SQ but the southern and western parts for NE and SE. The highest ES efficiency and SQ were found for the forests as well as for the ridge/tops landforms. Statistical analysis clarified that there was a positive and significant relationship between HQ and CS (R>0.8) while the relationship of the two with NE was inverse and significant (-0.55<R<-0.50). The correlation between SE and NE was also positive and significant (R>0.50). SQ was also correlated positively and significantly with HQ and CS (0.43<R<0.5) while no relation with NE and SE was found. It was also perceived that increasing the landscape fragmentation decreases HQ, CS, and SQ but increases NE and SE. Besides, the interaction between ES, SQ, and landscape fragmentation across the sub-basins of the study area can change under the influence of the dominant land use and landform types.

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Evaluation of soil quality in major grain-producing region of the North China Plain: Integrating minimum data set and established critical limits

Cited by 28 publications

References 56 publications

Soil quality assessment of cropland in China and its relationships with climate and topography

Soil quality assessment of cropland in China and its relationships with climate and topography

Predicting spatial variability of species diversity with the minimum data set of soil properties in an arid desert riparian forest

Effect of Landscape Fragmentation on Soil Quality and Ecosystem Services in Land Use and Landform Types

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