Analysis for Soil Characteristics of Degraded Grassland on Alpine Meadow

[Objective]The aim of this study is to explore the effects of grassland degradation on soil physical and chemical properties.[Method]The ratio of plant root to soil and soil texture on Alpine Meadow were investigated in this study,and soil available N,P,K,Cu,Zn,organic matter and pH value were also analyzed by routine analysis of soil nutrients in different degraded grasslands.[Result]With the intensification of degraded gradient and the soil depth,the ratio of plant root to soil was decreased gradually.The highest ratio of plant root to soil was in 0-10 cm depth of soil in grassland with different degraded gradients,while its ratio of plant root to soil changed from 0.001 to 0.040 with soil type of loam.Soil chemical characteristic changed in different degraded gradients.The content of available N,P,K reduced significantly with the soil depth and the intensification of degraded gradients.The content of Cu and Zn was relatively lack in degraded grassland.[Conclusion]There is no significant correlation between nutrition content or pH value and the succession degree of degraded grassland.

Fuzzy Synthetic Evaluation of Wetland Soil Quality Degradation:A Case Study on the Sanjiang Plain,Northeast China

Wetland soil quality degradation caused by large-scale agricultural reclamation on the Sanjiang Plain of Northeast China has been widely reported. A relative soil quality evaluation (RSQE) model and a projection pursuit evaluation (PPE) model based on real-coded accelerating genetic algorithm were introduced to evaluate quality variations in top layers of the main wetland soils on the Sanjiang Plain in 1999 and 2003, respectively. As soil quality degradation boundaries were vague, this study established two fuzzy synthetic evaluation (FSE) models based on the original data and criteria used in the RSQE and PPE models. The outputs of the two FSE models were obtained by choosing two fuzzy composite operators M(∧, ∨) and M(·, ⊕). Statistical analysis showed that the results of the FSE, RSQE, and PPE models were correlated. In particular, outputs of the FSE model using M(·, ⊕) were significantly correlated with those of the RSQE model with r = 0.989 at P < 0.01. Compared with RSQE and PPE models, the FSE model may be more objective in showing soil quality variations and was closer to the natural situation, showing the feasibility and applicability of the FSE model in evaluating soil quality degradation. However, the choice of composite operator was of critical importance. The study of wetland soil quality degradation on the Sanjiang Plain was of scientific and practical significance for protection and management of soils and for sustainable development of agriculture in this area in the future.

Quantification and Remediation of Soil Chemical Degradation in Tropical Australia,China and Thailand

Soil and land degradation in the tropics can be identified and described interms of physical, chemical, and biological changes from its pristine state brought about by naturaland anthropogenic influences. A characteristic of these ecosystems is their capacity to recyclenutrients through soil organic matter (SOM). Following disturbance through changed land management,SOM is rapidly mineralized and there is a corresponding decline in fertility and the variable chargecomponent of the cation exchange capacity. As these ecosystems are strongly dependent on SOM fortheir functionality, changed land use can have irreversible impacts on the productivity of thesesystems. The paper focuses on quantifying chemical degradation through 'benchmarking' using datafrom paired sites in tropical China and Thailand using surface charge fingerprinting. Using valuestaken from the fingerprint of an undisturbed soil, an index of chemical degradation from 'ideality'was calculated. Various management strategies that attempt to reverse degradative trends or improvepoor quality soils in their natural condition are discussed, such as the addition of natural claysand silicated materials. Results are present to show the effect of each of the aforementionedstrategies on surface charge characteristics and associated increases in plant productivity.

Soil Quality Degradation in a Magnesite Mining Area

Fourteen soil properties in 17 sampling sites were analyzed to study the soil degradation in a magnesite mining area in Halcheng City, Northeast China. Such areas have hitherto received little attention. The current practices of magnesite mining in this area resulted in degradation of soil quality and specifically led to an increase in soil pH, the ratio of magnesium to calcium, bulk density, clay dispersibility, total magnesium and equivalent calcium carbonate and a decrease in surface soil porosity and available phosphorous. The soil quality in the areas affected by intensive mining activity was obviously worse than that of areas far away from the mine. Four factors were identified and ＂magnesium factor＂, ＂pH factor＂ and ＂fertility factor＂, involving 13 soil properties, explained 82~0 of the total variance in the entire data set. Discriminant analysis showed that the total magnesium, water-soluble calcium and available phosphorous were the most sensitive indicators for soil quality.

Spatial Distribution of Soil Organic Matter Using Geostatistics: A Key Indicator to Assess Soil Degradation Status in Central Italy

Soil organic matter (SOM) content is one of the main factors to be considered in the evaluation of soil health and fertility. As timing, human and monetary resources often limit the amount of available data, geostatistical techniques provide a valid scientific approach to cope with spatial variability, to interpolate existing data and to predict values at unsampled locations for accurate SOM status survey. Using geostatistical and geographic information system (GIS) approaches, the spatial variability of some physical and chemical soil parameters was investigated under Mediterranean climatic condition in the Abruzzo region of central Italy, where soil erosion processes accelerated by human induced factors are the main causes of soil degradation associated with low SOM content. Experimental semivariograms were established to determine the spatial dependence of the soil variables under investigation. The results of 250 soil sampling point data were interpolated by means of ordinary kriging coupled with a GIS to produce contour maps distribution of soil texture, SOM content related to texture, and C/N ratio. The resulting spatial interpolation of the dataset highlighted a low content of SOM in relation with soil texture in most of the surveyed area (87%) and an optimal C/N ratio for only half of the investigated surface area. Spatial location of degraded area and the assessment of its magnitude can provide decision makers with an accurate support to design appropriate soil conservation strategies and then facilitate a regional planning of agri-environmental measures in the framework of the European Common Agricultural Policy.