36 research outputs found
Mortality, Recruitment and Change of Desert Tree Populations in a Hyper-Arid Environment
BACKGROUND: Long-term vegetation changes in hyper-arid areas have long been neglected. Mortality, recruitment and change in populations of the ecologically and culturally important and drought persistent Acacia tortilis and Balanites aegyptiaca are therefore estimated in the Eastern Desert of Egypt, and are related to the primary agents of change, water conditions and human intervention. METHODOLOGY: A change analysis using high-resolution Corona images (1965) in combination with field data (2003) is the basis for recruitment, mortality and change estimates. For assessing the influence of water conditions on patterns in recruitment and survival, different types of generalized linear models are tested. CONCLUSIONS: The overall trend in population size in that part of the Eastern Desert studied here is negative. At some sites this negative trend is alarming, because the reduction in mature trees is substantial (>50%) at the same time as recruitment is nearly absent. At a few sites there is a positive trend and better recruitment. Frequent observations of sprouting in saplings indicate that this is an important mechanism to increase their persistence. It is the establishment itself that seems to be the main challenge in the recruitment process. There are indications that hydrological variables and surface water in particular can explain some of the observed pattern in mortality, but our results indicate that direct human intervention, i.e., charcoal production, is the main cause of tree mortality in the Eastern Desert
A dynamic simulation model of land-use, population, and rural livelihoods in the central Rift Valley of Ethiopia
The dynamic interactions between society and land resources have to be taken into account when planning and managing natural resources. A computer model, using STELLA software, was developed through active participation of purposively selected farm households from different wealth groups, age groups and gender within a rural community and some members of Kebelle council. The aim of the modeling was to study the perceived changes in land-use, population and livelihoods over the next 30 years and to improve our understanding of the interactions among them. The modeling output is characterized by rapid population growth, declining farm size and household incomes, deteriorating woody vegetation cover and worsening land degradation if current conditions remain. However, through integrated intervention strategies (including forest increase, micro-finance, family planning, health and education) the woody vegetation cover is likely to increase in the landscape, population growth is likely to slow down and households’ income is likely to improve. A validation assessment of the simulation model based on historical data on land-use and population from 1973 to 2006 showed that the model is relatively robust. We conclude that as a supporting tool, the simulation model can contribute to the decision making process
Estimating soil loss for sustainable land management planning at the Gelana sub-watershed, northern highlands of Ethiopia
Land degradation severity assessment with sand encroachment in an ecologically fragile arid environment: a geospatial perspective
Lower CYP2C9 activity in Turkish patients with Behçet’s disease compared to healthy subjects: a down-regulation due to inflammation?
Quantitative mapping of global land degradation using Earth observations
Land degradation is a global issue on par with climate change and loss of biodiversity, but its extent and severity are only roughly known and there is little detail on the immediate processes – let alone the drivers. Earth-observation methods enable monitoring of land degradation in a consistent, physical way and on a global scale by making use of vegetation productivity and/or loss as proxies. Most recent studies indicate a general greening trend, but improved data sets and analysis also show a combination of greening and browning trends. Statistically based linear trends average out these effects. Improved understanding may be expected from data-driven and process-modelling approaches: new models, model integration, enhanced statistical analysis and modern sensor imagery at medium spatial resolution should substantially improve the assessment of global land degradation