Again, the analysis is not at a stage where definitive conclusions can be made; however it does provoke interest in pursuing this line of research for its potential implications for both poverty alleviation and improvements in the management of environmental resources.
Surprisingly, degradation decreases with slope. The other disadvantage of the GLASOD dataset for the purposes of this study is that it is for only one period in time, preventing time series analysis.
The GLASOD data represent the cumulative amount of soil degradation that was present at the time the data was collected in the late s. The dramatic differences in shading across national borders are exaggerated if unmeasured trade and movement across borders is non-negligible.
Downloadable country level information on agricultural production, land use and irrigation, food balances, fertilizer and pesticide, fishery and forestry production, population and food aid shipments.
The problem with using proxy variables is that they often do not capture the same effect as the original variable over varying circumstances and conditions. Roberts and Osgood, Table 5 presents the first-stage results, with a high R squared. Analogous to the maps generated for the Africa-wide regression, Figure 16 presents the share of soil degradation of poverty inducing factors in Ghana.
Data cleaning in which inappropriate regions are removed from the regression data before the aggregation occurs is important to remove possible sources of estimation error. In this way, the information captured during the statistical procedure using the data aggregated by national borders can be used to predict the variations that occur within nations.
Increased road density is associated with a lower poverty rate, as is increased irrigation project density. Information that may be valid but that cannot be distinguished from confounding data must either be filtered or not used. The regression has an acceptable R squared.
Since soil degradation is a dynamic process, maps of changes in degradation over time would be invaluable in separating out the relative causes and effects. They also allow communication and feedback with those who have a great deal of expertise with the regions involved but who do not have experience with the mathematics involved.
The consequence of ignoring spatial autocorrelation in a linear regression is inefficient parameter estimation. Although in some ways this presentation is more difficult to read than a two-dimensional image, it is very effective at communicating the magnitude and scale of the information contained in the windspeed coverage.
Standard errors and associated P values are calculated using the original soil degradation variable instead of the forecast variable used in the regression Greene, Land in balance: The scientific conceptual framework for Land Degradation Neutrality.
including biophysical and socio-economic aspects, and their interactions. S. Walter, S. WeltonScientific Conceptual Framework for Land Degradation Neutrality.
A Report of the Science-Policy Interface. United Nations Convention to Combat Desertification. socio-economic and biophysical causes of land degradation have been identified locally in many case studies, these have not been inventoried systematically at district, national or. methodological issues in analysing the linkages between socio-economic and environmental systems Dan Osgood and Leslie Lipper Dan Osgood is an Assistant Professor and Assistant Extension Specialist in the Department of Agricultural and Resource Economics, College of Agriculture, University of Arizona.
UNESCO – EOLSS SAMPLE CHAPTERS WATER RESOURCES MANAGEMENT – Vol. I - Land Degradation and Desertification: History, Nature, Causes, Consequences, and Solutions - Conacher, Arthur ©Encyclopedia of Life Support Systems (EOLSS) above. Thus, Arthur and Jeanette Conacher defined land degradation as ‘alterations to all.
and Land Degradation Trends. Martius C, Vogt J, Akhtar-Schuster M and Thomas R (eds). Understanding Desertification and Land Degradation Trends.
Proceedings of the UNCCD First Scientific Conference, 22–24 Septemberduring the UNCCD Ninth Conference of Economic aspects and. Socio-economic impact of land degradation However, some aspects of land degradation are less easily reversed than others.
For example, terrain deformation by gully erosion, or total topsoil loss from erosion, or the wiping out of native soil fauna is.Download