Impact of Vegetation Restoration on Soil Fungal Community Structure in Karst Rocky Desertification Areas

In this paper,managed forest(MF)and natural forest(NF)in the Huajiang Demonstration Zone of Guanling,Guizhou were selected as research objects,and cropland(CL)was taken as control.High-throughput sequencing technology was used to study the characteristics of fungal community composition and species diversity in the surface(0-10 cm)soil of each restoration measure,in order to reveal the dominant soil fungal groups and fungal community composition in karst rocky desertification areas,which was conducive to a more comprehensive understanding of the soil conditions of different vegetation restoration measures.Research has shown that vegetation restoration significantly affected the diversity of soil fungal community,with significant increases in Sob index,Ace index,and Chao index.The vegetation restoration has significantly changed the composition of fungal community.The dominant fungi in the CL topsoil are Sordariomycetes(62.28%),Dothideomycetes(12.34%),and Eurotiomycetes(9.12%);the dominant fungi in the MF soil are Sordariomycetes(45.05%),Dothideomycetes(14.74%),and Mortierellomycetes(10.40%);the dominant fungi in the NF soil are unclassified fungal community(26.38%),Sordariomycetes(19.78%),and Agaricomycetes(13.82%).Vegetation restoration has changed the key fungal groups in the soil.Sordariomycetes,Fusarium,and Setophoma are the key dominant fungal groups in CL soil;Dioszegia is key dominant fungal group in MF soil;c_unclassified_k_Fungi,p_unclassified_k_Fungi,o_unclassified_k_Fungi,f_unclassified_k_Fungi,g_unclassified_k_Fungi,Teichospora,and Diaporthe are key dominant fungal groups in NF soil.

Monitoring of Karst Rocky Desertification Control Projects Based on Remote Sensing Images with Medium and High Spatial Resolution——A Case Study of Disi River Basin in Puan County

[ Objective] The study aimed to improve methods of monitoring Karst Rocky Desertification （KRD） control projects and increase the working efficiency. [Method] Based on remote sensing images with medium and high spatial resolution, KRD control projects in Disi River basin in Puan County were monitored, that is, information of the project construction in the study area was extracted using supervised classification and hu- man-computer interactive interpretation, and the monitoring results were testified with the aid of GPS. [Result] It was feasible to monitor KRD con- trol projects in Disi River basin based on remote sensing images with medium and high resolution, and the monitoring accuracy was satisfactory, reaching above 80% or 90%, so the method is worthy of popularizing. [ Conclusion] Remote sensing images with medium and high resolution can be used to monitor other KRD control Droiects.

Drivers of soil erosion and subsurface loss by soil leakage during karst rocky desertification in SW China

As an extreme manifestation of environmental degradation,karst rock desertification is caused by soil loss and rock exposure.In some areas with serious rocky desertification,there is no soil to be eroded or leaked.The soil loss in these areas superimposes soil erosion and unique subsurface loss by soil leakage through fissures,pipelines,sinkholes,etc.,which directly reduce soil resources and accelerate rocky desertification.However,the factors driving soil erosion and subsurface loss by soil leakage are still unclear.Rainfall experiments were conducted on simulated slopes with surface-exposed bedrock and subsurface fissures based on field investigations in a karst rocky desertification area of Guizhou Province,China.Four factors,including rainfall intensity,slope gradient,bedrock exposure rate and subsurface fissure degree,were considered in the experiment.We found that the amount of soil surface erosion and subsurface leakage loss is driven not only by the runoff volume but also by other influential factors.Rainfall intensity is the driving factor determining the amount of surface erosion and subsurface leakage loss of soil and water and the relationship between them.The slope gradient plays a leading role only in subsurface fissure flow leakage loss.The bedrock exposure rate drives the surface soil erosion rate,shows a critical value(30%),and dominates the fissure flow leakage loss rate.Subsurface fissure density plays an important role in the surface loss of soil and water;however,an increase in the subsurface fissure density does not obviously accelerate the subsurface leakage loss of soil and water.Although this result,obtained from laboratory simulations,may differ at the field scale or larger,it could provide a foundation for systematic studies on soil erosion/leakage and insights into the relations between rocky desertification and soil erosion/leakage and their driving factors in karst rocky desertification.

Human activity and climate change triggered the expansion of rocky desertification in the karst areas of Southwestern China

It is conducive to the sustainable development of human beings in karst regions to research the mechanism of karst rocky desertification(KRD)expansion.Whether the large-scale KRD in southwestern China is caused by climate change or human activities is still controversial.In this study,the evolution of the KRD in southwestern China over the past 2000 years was reconstructed through the high-precisionδ^(13)C record of stalagmites from Shijiangjun(SJJ)Cave,Guizhou Province,China.Theδ^(13)C of the stalagmites from SJJ Cave exhibited heavy values from the Medieval Warm Period(MWP)to the Little Ice Age(LIA).Furthermore,theδ^(13)C records of other stalagmites and tufa from southwestern China also showed the same significant heavy trend.Because the stalagmiteδ^(13)C could record the change of ecological environment,it indicated that the consistent change of the stalagmitesδ^(13)C may record the process of KRD expansion in the karst regions of southwestern China.During the MWP,the stronger Asian summer monsoon and the northward movement of the rain belt led to a dry period in southwestern China and a wet period in northern China.In contrast,it was wet in southwestern China and dry in northern China during the LIA.In addition,after the Jing-Kang event(JK event,AD1127)occurred at the end of the Northern Song dynasty,the political and economic center of China migrated to southern China for the first time,which changed the population distribution pattern of larger population in the north and smaller population in the south.Therefore,the expansion of KRD in southwestern China was exacerbated in the MWP due to the change of climate in southwestern China,the migration of a large number of people,wars,the large-scale reclamation of arable land,and the cultivation of large areas of crops.

Regions and Their Typical Paradigms for Soil and Water Conservation in China

China is experiencing conflicts between its large population and scarce arable land,and between a demand for high productivity and the severe soil erosion of arable land.Since 1949,China has committed to soil and water conservation(SWC),for which eight regions and 41 subregions have been developed to improve the environment and increase land productivity.To obtain information from the regional planning and strategies for SWC and to explore whether SWC practices simultaneously contribute to soil conservation,ecosystem functioning,and the livelihoods of local farmers,and to summarize the successful experiences of various SWC paradigms with distinct characteristics and mechanisms of soil erosion,this paper systematically presents seven SWC regions(excluding the Tibetan Plateau region)and 14 typical SWC paradigms,focusing on erosion mechanisms and the key challenges or issues in the seven regions as well as on the core problems,main objectives,key technologies,and the performance of the 14 typical paradigms.In summary,the 14 typical SWC paradigms successfully prevent and control local soil erosion,and have largely enhanced,or at least do not harm,the livelihoods of local farmers.However,there remain many challenges and issues on SWC and socioeconomic development that need to be addressed in the seven SWC regions.China,thus,still has a long way to go in successfully gaining the win-win objective of SWC and human aspects of development.

Quantitative extraction of the bedrock exposure rate based on unmanned aerial vehicle data and Landsat-80LI image in a karst environment

In the karst regions of southwest China, rocky desertification is one of the most serious problems in land degradation. The bedrock exposure rate is an important index to assess the degree of rocky desertification in karst regions. Because of the inherent merits of macro-scale, frequency, efficiency, and synthesis, remote sensing is a promising method to monitor and assess karst rocky desertification on a large scale. However, actual measurement of the bedrock exposure rate is difficult and existing remote-sensing methods cannot directly be exploited to extract the bedrock exposure rate owing to the high complexity and heterogeneity of karst environments. Therefore, using unmanned aerial vehicle （UAV） and Landsat-8 Operational Land Imager （OLI） data for Xingren County, Guizhou Province, quantitative extraction of the bedrock exposure rate based on multi-scale remote-sensing data was developed. Firstly, we used an object-oriented method to carry out accurate classification of UAV images. From the results of rock extraction, the bedrock exposure rate was calculated at the 30 m grid scale. Parts of the calculated samples were used as training data; other data were used for model validation. Secondly, in each grid the band reflectivity ofLandsat-80LI data was extracted and a variety of rock and vegetation indexes （e.g., NDVI and SAVI） were calculated. Finally, a network model was established to extract the bedrock exposure rate. The correlation coefficient of the network model was 0.855, that of the validation model was 0.677 and the root mean square error of the validation model was 0.073. This method is valuable for wide-scale estimation of bedrock exposure rate in karst environments. Using the quantitative inversion model, a distribution map of the bedrock exposure rate in Xingren County was obtained.