Characterization and interaction of driving factors in karst rocky desertification: a case study from Changshun, China

Xu, Erqi; Zhang, H. Q.

doi:10.5194/se-5-1329-2014

Cited by 61 publications

(57 citation statements)

References 37 publications

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“…Land degradation is a worldwide process that affects all five continents (Masto et al, 2015;Xu and Zhang, 2014;Thomas et al, 2015;Yan and Cai, 2015;Wang et al, 2013;Jafari and Bakhshandehmehr, 2013;Cerdà and Lavee, 1999;Bai et al, 2013). The process of land degradation deprives the quality of natural resources and impairs directly on human society (Izzo et al, 2013) through loss of ecosystem goods and services.…”

Section: Land Degradation In Senegalmentioning

confidence: 99%

Quantifying the impact of land degradation on crop production: the case of Senegal

2016

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Abstract. Land degradation has been a persistent problem in Senegal for more than a century and by now has become a serious impediment to long-term development. In this paper, we quantify the impact of land degradation on crop yields using the results of a nationwide land degradation assessment. For this, the study needs to address two issues. First, the land degradation assessment comprises qualitative expert judgements that have to be converted into more objective, quantitative terms. We propose a land degradation index and assess its plausibility. Second, observational data on soils, land use, and rainfall do not provide sufficient information to isolate the impact of land degradation. We, therefore, design a pseudo-experiment that for sites with otherwise similar circumstances compares the yield of a site with and one without land degradation. This pairing exercise is conducted under a gradual refining of the classification of circumstances, until a more or less stable response to land degradation is obtained. In this way, we hope to have controlled sufficiently for confounding variables that will bias the estimation of the impact of land degradation on crop yields. A small number of shared characteristics reveal tendencies of "severe" land degradation levels being associated with declining yields as compared to similar sites with "low" degradation levels. However, as we zoom in at more detail some exceptions come to the fore, in particular in areas without fertilizer application. Yet, our overall conclusion is that yield reduction is associated with higher levels of land degradation, irrespective of whether fertilizer is being applied or not.

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Section: Land Degradation In Senegalmentioning

confidence: 99%

Quantifying the impact of land degradation on crop production: the case of Senegal

2016

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“…The typical karst areas are characterized by high fragility own to their natural settings and anthropogenic impacts (Xu and Zhang, 2014). This, in turn, has not only damaged eco-environment including soil erosion, lower biodiversity and decreased soil productivity, but also exacerbated the poverty level in the rural areas of the region (Hu et al, 2014;Liu et al, 2005;Wang et al, 2004).…”

Section: Introductionmentioning

confidence: 99%

Combined deep sampling and mass-based approaches to assess soil carbon and nitrogen losses due to land-use changes in karst area of southwestern China

Wang

et al. 2016

Solid Earth

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Abstract. The conversion of natural vegetation to humanmanaged ecosystems, especially the agricultural systems, may decrease soil organic carbon (SOC) and total nitrogen (TN) stocks. The objective of present study was to assess SOC and TN stocks losses by combining deep sampling with mass-based calculations upon land-use changes in a typical karst area of southwestern China. We quantified the changes from native forest to grassland, secondary shrub, eucalyptus plantation, sugarcane and corn fields (both defined as croplands), on the SOC and TN stocks down to 100 cm depth using fixed-depth (FD) and equivalent soil mass (ESM) approaches. The results showed that converting forest to cropland and other types significantly led to SOC and TN losses, but the extent depended on both sampling depths and calculation methods selected (i.e., FD or ESM). On average, the shifting from native forest to cropland led to SOC losses by 19.1, 25.1, 30.6, 36.8 and 37.9 % for the soil depths of 0-10, 0-20, 0-40, 0-60 and 0-100 cm, respectively, which highlighted that shallow sampling underestimated SOC losses. Moreover, the FD method underestimated SOC and TN losses for the upper 40 cm layer, but overestimated the losses in the deeper layers. We suggest that the ESM together with deep sampling should be encouraged to detect the differences in SOC stocks. In conclusion, the conversion of forest to managed systems, in particular croplands significantly decreased in SOC and TN stocks, although the effect magnitude to some extent depended on sampling depth and calculation approach selected.

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“…The eco-environment of karst mountains is fragile and the land degradation is mainly driven by desertification processes. Generally speaking, lithology and soil type and road influence are identified as the leading factors influencing KRD (Xu and Zhang, 2014;Yang et al, 2013). The succession of KRD has had different impacts on soil fertility indicators ; i.e., the genesis of KRD has been attributed to land mismanagement of local households (Wu et al, 2011) and it has been found that climate change accelerates rocky desertification in the karst areas (Xiong et al, 2009).…”

Section: The Significance Of the Theoretical Model Suggested In This mentioning

confidence: 99%

Discussing the genesis of karst rocky desertification research based on the correlations between cropland and settlements in typical peak-cluster depressions

Luo

et al. 2016

Solid Earth

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Abstract. This paper attempts to explain the theoretical reasons why local farmers have executed land mismanagement measures such as steep slope land cultivation, in order to reveal the mechanisms of karst rocky desertification (KRD, including light KRD, moderate KRD and severe KRD) through typical case studies. Firstly, this paper assumes that the low land capacity is the initial cause of KRD in peak-cluster depression areas. Furthermore, the ecological quality of the peak-cluster depression zone (a combination of clustered karst cones with a common base and depressions between cones) is influenced by the relationship between the area of depressions and the population of residential areas. Therefore, six typical peak-cluster depression areas of Guizhou province were selected to compare the distribution circumstances of cropland, the characteristics of settlements and the formation of KRD with the help of ALOS images in 2010 (with a resolution of 10 m × 10 m). The results show that there is a negative correlation between the percentage of the cultivated land and the percentage of KRD at peak-cluster depressions. The relationship could be concluded by three situations of the process of KRD, which are low, middle and upper carrying capacities of land. Severe KRD is only distributed in peak-cluster depression areas with less flatland, low land capacity and a high population. The harmonization between population pressure and bearing capacity of land will influence the ecological qualities in the peak-cluster depressions. The KRD phenomenon which occurred in six typical peak-cluster depression areas confirms that the hypothesis suggested by this paper is correct, and this result will contribute to understanding the natural mechanisms of KRD and guide the ecological restoration of KRD land.

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Characterization and interaction of driving factors in karst rocky desertification: a case study from Changshun, China

Cited by 61 publications

References 37 publications

Quantifying the impact of land degradation on crop production: the case of Senegal

Quantifying the impact of land degradation on crop production: the case of Senegal

Combined deep sampling and mass-based approaches to assess soil carbon and nitrogen losses due to land-use changes in karst area of southwestern China

Discussing the genesis of karst rocky desertification research based on the correlations between cropland and settlements in typical peak-cluster depressions

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