Mountain ecosystems are, however, fragile and particularly vulnerable to the adverse impacts of climate change, deforestation and forest degradation, land-use change, land degradation and natural disasters.
Salinization and sodication are abiotic soil factors, important hazards to soil fertility and consequently affect the crop production. Soil salinization is of great concern for irrigated agriculture in arid and semi‐arid regions of the world; sodicity is characterized by an excessively high concentration of sodium (Na) in their cation exchange system. In recent times, attention has been turned to study the impacts of these factors (salinity and sodicity) on soil microbial activities.
Soil erosion and contamination are two main desertification indices or land degradation agents in agricultural areas. Global climate change consequence is a priority to predict global environmental change impacts on these degradation risks. This agro-ecological approach can be especially useful when formulating soil specific agricultural practices based on the spatial variability of soils and related resources to reverse environmental degradation.
The island of Sri Lanka is free from serious natural hazards such as volcanic activity and earthquakes resulting from climatic extremes, but there are impacts of many natural disasters, such as landslides, floods and droughts, the intensity and frequency of which are increasing due to human interventions. Some areas of Sri Lanka are also periodically subject to cyclones that occur due to climatic conditions and geographical locations.Land degradation denotes all natural or anthropogenic processes that diminish or impair productivity of land.
The soil erodibility factor of RUSLE is one of the important indicators of land degradation. It can be measured either directly under natural or simulated rainfall condition or indirectly estimated by empirical models. A geospatial variation of this factor is essential for prioritization of reclamation measures. However, geospatial upscaling of soil erodibility factor is very uncertain because of its dynamic nature and dependent on the parameters used in the model.
Scenario analysis constitutes a valuable deployment method for scientific models to inform environmental decision-making, particularly for evaluating land degradation mitigation options, which are rarely based on formal analysis. In this paper we demonstrate such an assessment using the PESERA–DESMICE modeling framework with various scenarios for 13 global land degradation hotspots.
Examples of sustainable land management (SLM) exist throughout the world. In many cases, SLM has largely evolved through local traditional practices and incremental experimentation rather than being adopted on the basis of scientific evidence. This means that SLM technologies are often only adopted across small areas. The DESIRE (DESertIfication mitigation and REmediation of degraded land) project combined local traditional knowledge on SLM with empirical evaluation of SLM technologies.
Indicator-based approaches are often used to monitor land degradation and desertification from the global to the very local scale. However, there is still little agreement on which indicators may best reflect both status and trends of these phenomena. In this study, various processes of land degradation and desertification have been analyzed in 17 study sites around the world using a wide set of biophysical and socioeconomic indicators.
Understanding the patterns of land degradation indicators can help to identify areas under threat as basis for designing and implementing site-specific management options. This study sort to identify and assess the patterns of land degradation indicators in selected districts of western Kenya. The study employed the use of Land Degradation Sampling Framework (LDSF) to characterize the sites. LDSF a spatially stratified, random sampling design framework consisting of 10km×10km blocks and clusters of plots.