Driving Factors and Prediction of Rock Desertification of Non-Tillage Lands in a Karst Basin, Southwest China
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Institute for Forest Resources & Environment of Guizhou, Key Laboratory of Forest Cultivation in Plateau Mountain Area, College of Forestry, Guizhou University, Guiyang 550025, P. R. China
Guizhou Provincial Key Laboratory for Environment, Guizhou Normal University, Guiyang 550001, P. R. China
Institute of Biology, Guizhou Academy of Sciences, Guiyang 550001, P. R. China
Guizhou Botanical Garden, Guiyang, Guizhou 550000, P. R. China
Submission date: 2020-09-27
Final revision date: 2020-11-04
Acceptance date: 2020-11-12
Online publication date: 2021-04-12
Publication date: 2021-07-07
Pol. J. Environ. Stud. 2021;30(4):3627-3635
Rocky desertification is seriously restricting the sustainable development of agricultural production and tourism industry in karst regions. This study focus on the characteristics of rocky desertification and its main driving factors on non-tillage lands in Houzhai River Basin of southwestern China. Artificial neural networks (ANNs) were employed in this study to identify the importance of different environmental factors on rocky desertification. The results showed that the rock outcrops in non-tillage lands ranged from 0.00 to 91.12% with a mean value of 19.10% in the Houzhai River Basin, and the rates of rock outcrops among different types of vegetation were ordered as: shrub grasslands (35.30%)>arbor forestlands (30.07%)>shrublands (23.13%)>arbour-shrub mixed forestlands (27.54%). With increases in slope gradient and altitude, the cover rate of rock outcrops became higher and rocky desertification became more serious. Based on ANNs analysis, the correlation coefficients between observed and predicted values of remaining data sets ranged from 0.828 to 0.998, which indicated that the importance of altitude, slope gradient, gravel content and soil bulk density are the dominant factors affecting soil erosion and thereby leading to the occurrence of rocky desertification in the Houzhai River Basin. In addition, ANNs combine with environmental factors can be a feasible way to predict tendency of rocky desertification in a karst regions.
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