Unveiling soil degradation and desertification risk in the Mediterranean basin: a data mining analysis of the relationships between biophysical and socioeconomic factors in agro-forest landscapes

Soil degradation and desertification processes in the Mediterranean basin reflect the interplay between environmental and socioeconomic drivers. An approach to evaluate comparatively the multiple relationships between biophysical variables and socioeconomic factors is illustrated in the present study using the data collected from 586 field sites located in five Mediterranean areas (Spain, Greece, Turkey, Tunisia and Morocco). A total of 47 variables were chosen to illustrate land-use, farm characteristics, population pressure, tourism development, rainfall regime, water availability, soil properties and vegetation cover, among others. A data mining approach incorporating non-parametric inference, principal component analysis and hierarchical clustering was developed to identify candidate syndromes of soil degradation and desertification risk. While field sites in the same study area showed a substantial similarity, the multivariate relationship among variables diverged among study areas. Data mining techniques proved to be a practical tool to identify spatial determinants of soil degradation and desertification risk. Our findings identify the contrasting spatial patterns for biophysical and socioeconomic variables, in turn associated with different responses to land degradation

Assessing the effectiveness of sustainable land management policies for combating desertification: A data mining approach.

This study investigates the relationship between fine resolution, local-scale biophysical and socioeconomic contexts within which land degradation occurs, and the human responses to it. The research draws on experimental data collected under different territorial and socioeconomic conditions at 586 field sites in five Mediterranean countries (Spain, Greece, Turkey, Tunisia and Morocco). We assess the level of desertification risk under various land management practices (terracing, grazing control, prevention of wildland fires, soil erosion control measures, soil water conservation measures, sustainable farming practices, land protection measures and financial subsidies) taken as possible responses to land degradation. A data mining approach, incorporating principal component analysis, non-parametric correlations, multiple regression and canonical analysis, was developed to identify the spatial relationship between land management conditions, the socioeconomic and environmental context (described using 40 biophysical and socioeconomic indicators) and desertification risk. Our analysis identified a number of distinct relationships between the level of desertification experienced and the underlying socioeconomic context, suggesting that the effectiveness of responses to land degradation is strictly dependent on the local biophysical and socioeconomic context. Assessing the latent relationship between land management practices and the biophysical/socioeconomic attributes characterizing areas exposed to different levels of desertification risk proved to be an indirect measure of the effectiveness of field actions contrasting land degradation

Characterization of Aegean olive oils by their minor compounds

This study presents combined approach of establishing cultivar difference between Aegean olive oils, obtained from economically important olive oil producing cultivars (cv..Ayvalık and Memecik), based on chemometric evaluation of their content and in particular composition of minor compounds. Evaluation of minor compounds with principal component analysis (PCA) and linear discriminant analysis (LDA) indicated differentiation according to the cultivars. LDA produced a 100 % correct group classification. Moreover, stigmasterol, apparent β-sitosterol and total sterols were found to have the highest discriminating power. Memecik oils were characterized by the highest content of antioxidant compounds (α-tocopherol, phenolic compounds and total phenolic compounds). On the other hand, Ayvalık oil had the highest level of total sterols. The data were analyzed statistically to evaluate the differences according to variety and crop season. The minor compounds of Ayvalık and Memecik oils presented statistically significant differences (p < 0.01) according to variety, except for the hydroxytyrosol and clerosterol content. The amount of α-tocopherol, total phenolic compounds, apparent β-sitosterol and total sterols varied with respect to crop season. A good correlation was observed between the amount of α-tocopherol, total phenolic compounds, apparent β-sitosterol and total sterols and some climatic variables

LC-ESI-MS characterization of phenolic profiles Turkish olive oils as influenced by geographic origin and harvest year

The purpose of this investigation was to evaluate and compare the differences in the phenolic fractions and antioxidant properties of virgin olive oils from the Nizip yaglik and Kilis yaglik olive varieties cultivated in native and different olive growing areas of Turkey. The phenolic composition of olive oils was carried out by HPLC-DAD and identifications were made by LC-MS. Fourteen phenolic compounds were identified and among these compounds elenolic acid, tyrosol and hydroxytyrosol were the most dominant. Based on the results, there was no difference in distribution of phenolic compounds, but the total phenolic content in oil from native regions was higher than in oil from Bornova regions. The antioxidant capacity of olive oil extracts was determined by two different methods, including DPPH and ABTS. In both methods, antioxidant capacity values were higher in oil from native regions. © 2013 AOCS.110O602, ZF-2010-D24Acknowledgments The authors thank the Scientific and Technical Research Council of Turkey (TUBITAK) and Cukurova University Research Fund (ZF-2010-D24) for financial support for this research project (Project No. 110O602)