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1. 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

Author

C. A. Karavitis, Miloud Chaker, Hasan Güngör, Rudi Hessel, Abdellah Laouina, Candan Gokceoglu, A. Kounalaki, Albert Solé-Benet, J. de Vente, Faruk Ocakoğlu, Mongi Sghaier, A. Belgacem, H. Taamallah, Orestis Kairis, Costas Kosmas, Luca Salvati, H. Khatteli, Sanem Acikalin, V. Fassouli, H. Sonmez, Coen J. Ritsema, L. Tezcan, and Mohamed Ouessar

Subjects
Mediterranean climate, human pressure, media_common.quotation_subject, vulnerability, Geography, Planning and Development, response assemblage, system, Management, Monitoring, Policy and Law, computer.software_genre, Mediterranean Basin, land-use change, Soil retrogression and degradation, spain, Land use, land-use change and forestry, CB - Bodemfysica en Landgebruik, Mediterranean region, General Environmental Science, Water Science and Technology, media_common, Fluid Flow and Transfer Processes, region, Alterra - Soil physics and land use, data mining, erosion, abandonment, indicators, Geography, Desertification, Land degradation, Erosion, Spatial ecology, Data mining, europe, computer, performance, SS - Soil Physics and Land Use, Alterra - Bodemfysica en landgebruik
Abstract

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.

Published
2014
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2. Assessing the effectiveness of sustainable land management policies for combating desertification: A data mining approach

Author

Costas Kosmas, Luca Salvati, Faruk Ocakoğlu, Sanem Acikalin, Mongi Sghaier, Andrea Colantoni, V. Fassouli, H. Khatteli, Candan Gokceoglu, Christos A. Karavitis, Orestis Kairis, Coen J. Ritsema, Abdellah Laouina, H. Taamallah, L. Tezcan, Miloud Chaker, Albert Solé-Benet, H. Sonmez, Rudi Hessel, J. de Vente, Mohamed Ouessar, A. Belgacem, Margherita Carlucci, A. Kounalaki, Claire Kelly, and Hasan Güngör

Subjects
010504 meteorology & atmospheric sciences, Water en Landgebruik, Turkey, computer.software_genre, 01 natural sciences, Soil, Soil, Water and Land Use, Bodem, Sustainable agriculture, Data Mining, Mediterranean region, Waste Management and Disposal, Response assemblage, media_common, Principal Component Analysis, Greece, Environmental resource management, Agriculture, 04 agricultural and veterinary sciences, General Medicine, Human pressure, PE&RC, Multivariate statistics, Environmental Policy, Morocco, Geography, Desertification, Indicators, Land degradation, Data mining, Sustainable land management, Conservation of Natural Resources, Environmental Engineering, Tunisia, Erosion control, media_common.quotation_subject, Land management, Context (language use), Management, Monitoring, Policy and Law, Fires, Water Supply, Humans, 0105 earth and related environmental sciences, WIMEK, business.industry, Water and Land Use, Bodemfysica en Landbeheer, Bodem, Water en Landgebruik, Soil Physics and Land Management, Socioeconomic Factors, Spain, Sustainability, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, business, computer
Abstract

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.

Published
2016

3. An exploratory analysis of land abandonment drivers in areas prone to desertification

Author

Manuel E. Mendoza, Christian Prat, M. Alcalá, C. Ovalle, M. Darkoh, A. Belgacem, V. Fassouli, Coen J. Ritsema, V. Romanenkov, H. Taamallah, P. Alfama, N. Silva, J. Vente, Raban Chanda, H. Khatteli, A. Pozo, A. Ramos, Harun Sonmez, N. Khitrov, L. Medina, Mohamed Ouessar, K. Mulale, E. Zagal, J. Riquelme, Sanem Acikalin, A. Kounalaki, F. Fernandez, Rudi Hessel, Luca Salvati, L. Magole, Julius Atlhopheng, O. Ermolaeva, J.S. Perkins, Orestis Kairis, J. Barrera, J. Ramos, Candan Gokceoglu, C. Perez, L. Tezcan, Reuben Sebego, Mongi Sghaier, Abdellah Laouina, Albert Solé-Benet, Christos A. Karavitis, A. Zeiliguer, Faruk Ocakoğlu, Costas Kosmas, Hasan Güngör, J. Brito, D. Gonzalez, M. L. Sizemskaya, M. Chaker, Agricultural University of Athens, Énergie Matériaux Télécommunications - INRS (EMT-INRS), Institut National de la Recherche Scientifique [Québec] (INRS)-Université du Québec à Montréal (UQAM), Hacettepe University = Hacettepe Üniversitesi, Laboratory of Mycology, Institute of Biomedicine, Centre d'économie de la Sorbonne (CES), Centre National de la Recherche Scientifique (CNRS)-Université Panthéon-Sorbonne (UP1), Laboratoire d'étude des transferts en hydrologie et environnement (LTHE), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), ETS d'Enginyers de Camins, Instituto Flumen, Departamento de Bioquimica y Biologia Molecular, Universidad Complutense de Madrid [Madrid] (UCM)-Instituto Universitario de Investigacion en Neuroquimica-Centro de Investigacion Biomédica en Red sobre Enfermedades Neurodegenerativas ((CIBERNED))-Instituto Ramon y Cajal de Investigacion Sanitaria ((IRYCIS)), Pryanishnikov All-Russian Research Institute of Agrochemistry, Russian Academy of Agricultural Sciences, LAGIS-OSL, Laboratoire d'Automatique, Génie Informatique et Signal (LAGIS), Université de Lille, Sciences et Technologies-Ecole Centrale de Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Sciences et Technologies-Ecole Centrale de Lille-Centre National de la Recherche Scientifique (CNRS), Institut National de la Recherche Scientifique [Québec] (INRS)-Université du Québec à Montréal = University of Québec in Montréal (UQAM), Université Paris 1 Panthéon-Sorbonne (UP1)-Centre National de la Recherche Scientifique (CNRS), Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry]), Instituto Universitario de Investigacion en Neuroquimica-Centro de Investigacion Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III [Madrid] (ISC)-Instituto de Salud Carlos III [Madrid] (ISC)-Instituto Ramon y Cajal de Investigacion Sanitaria [Madrid, Spain] (IRYCIS), Universidad de Alcalá - University of Alcalá (UAH)-Universidad de Alcalá - University of Alcalá (UAH)-Universidad Complutense de Madrid = Complutense University of Madrid [Madrid] (UCM), Université de Lille, Sciences et Technologies-Centrale Lille-Centre National de la Recherche Scientifique (CNRS)-Université de Lille, Sciences et Technologies-Centrale Lille-Centre National de la Recherche Scientifique (CNRS), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS), Universidad Complutense de Madrid = Complutense University of Madrid [Madrid] (UCM)-Instituto Universitario de Investigacion en Neuroquimica-Centro de Investigacion Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), and Universidad de Alcalá - University of Alcalá (UAH)-Universidad de Alcalá - University of Alcalá (UAH)

Subjects
Mediterranean climate, FORET, VARIATION SAISONNIERE, SOL CULTIVE, RESSOURCES EN EAU, EXPLOITATION AGRICOLE, Environmental protection, 11. Sustainability, STATUT SOCIOECONOMIQUE, DEGRADATION DU SOL, Land tenure, ComputingMilieux_MISCELLANEOUS, soil-erosion, media_common, risk, 2. Zero hunger, METHODE D'ANALYSE, DESERTIFICATION, Environmental resource management, PATURAGE, [SHS.GEO]Humanities and Social Sciences/Geography, Alterra - Soil physics and land use, PRATIQUE CULTURALE, Geography, Desertification, PLUIE, Land degradation, PENTE, ANALYSE MULTIVARIABLE, europe, UTILISATION DU SOL, SS - Soil Physics and Land Use, Alterra - Bodemfysica en landgebruik, media_common.quotation_subject, Land management, TRAVAIL DU SOL, [SHS.DEMO]Humanities and Social Sciences/Demography, spain, media_common.cataloged_instance, patterns, CB - Bodemfysica en Landgebruik, European union, Socioeconomic status, Earth-Surface Processes, business.industry, Abandonment (legal), pédologie, [SHS.ANTHRO-SE]Humanities and Social Sciences/Social Anthropology and ethnology, 15. Life on land, indicators, SUREXPLOITATION, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, business
Abstract

The abandonment of land is a global problem with environmental and socioeconomic implications. An approach to assess the relationship between land abandonment and a large set of indicators was illustrated in the present study by using data collected in the framework of the European Union DESIRE research project from 808 field sites located in 10 study sites in the Mediterranean region, Eastern Europe, Latin America, Africa and Asia. A total of 48 indicators provided information for biophysical conditions and socioeconomic characteristics measured at the plot level. The selected indicators refer to farm characteristics (family status, land tenure, present and previous types of land-use, soil depth, slope gradient, tillage operations) and to site-specific characteristics including annual rainfall, rainfall seasonality and water availability. Classes were designated for each indicator and a sensitivity score was assigned to each class based on existing research or empirically assessing the importance of each indicator to the land abandonment issue. Questionnaires for each process of land degradation were prepared and data were collected at field site level in collaboration with land users. Based on correlation statistics and multivariate analyses more than ten indicators out of 48 resulted as significant in affecting land abandonment in the studied field sites. Among them, the most important were rainfall seasonality, elderly index, land fragmentation, farm size, selected soil properties, and the level of policy implementation. Results contribute to the development of appropriate tools for assessing the effectiveness of land management practices for contrasting land abandonment.

Published
2015
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4. Evaluation and selection of indicators for land degradation and desertification monitoring : methodological approach

Author

Albert Solé-Benet, Raban Chanda, J. Feng, Constantinos Kosmas, Abdellah Laouina, Francesca Santaloia, António J. D. Ferreira, Manuel E. Mendoza, V. Fassouli, A. Pozo, F. Fernandez, Miloud Chaker, C. Prat, Luca Salvati, Faruk Ocakoğlu, Coen J. Ritsema, J. Riquelme, Mongi Sghaier, F. Pliakas, P. Alfama, A. Zeiliguer, I. Diamantis, J. Soares, P. Morais, H. Taamallah, M. L. Sizemskaya, L. Magole, Mohamed Ouessar, Julius Atlhopheng, J.S. Perkins, K. Mulale, W. Fei, J. Brito, C. A. Karavitis, N. Khitrov, V. Romanenkov, Celeste Coelho, Rudi Hessel, E. Zagal, Y. Qinke, Sanem Acikalin, Dino Torri, Maurizio Polemio, J. de Vente, H. Khatteli, Hasan Güngör, A. Kounalaki, A. Belgacem, Sandra Valente, Or. Kairis, L. Tezcan, A. Ramos, J. Juying, Reuben Sebego, Fabrizio Ungaro, C. Ovalle, M. Darkoh, H. Sonmez, W. Zhonging, J. Barrera, L. Rui, J. Ramos, C. Perez, Candan Gokceoglu, Piernicola Lollino, M. Alcalá, N. Silva, M. Lopes, L. Medina, O. Ermolaeva, A. Ziogas, D. Gonzalez, Agricultural University of Athens, Laboratoire d'étude des transferts en hydrologie et environnement (LTHE), Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Observatoire des Sciences de l'Univers de Grenoble (OSUG), Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS), Institut National Polytechnique de Grenoble (INPG)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG), and Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Joseph Fourier - Grenoble 1 (UJF)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)

Subjects
AGRICULTURE, Rain, mediterranean conditions, Soil, Environmental protection, Environmental monitoring, DEGRADATION DU SOL, Europe, Eastern, Environmental Restoration and Remediation, media_common, 2. Zero hunger, Global and Planetary Change, METHODE D'ANALYSE, Ecology, DESERTIFICATION, Mediterranean Region, greece, Environmental resource management, ASIE, Alterra - Soil physics and land use, Vegetation, PE&RC, erosion, Pollution, 6. Clean water, PRATIQUE CULTURALE, Desertification, tillage, Land degradation, Regression Analysis, Seasons, INDICATEUR ECOLOGIQUE, Desert Climate, UTILISATION DU SOL, Environmental Monitoring, SS - Soil Physics and Land Use, Alterra - Bodemfysica en landgebruik, CONSERVATION DU SOL, INDICATEUR BIOLOGIQUE, Asia, EUROPE, COUVERT VEGETAL, AMERIQUE LATINE, media_common.quotation_subject, [SDE.MCG]Environmental Sciences/Global Changes, Land management, Plant Development, TRAVAIL DU SOL, [SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil study, FACTEUR ANTHROPIQUE, vegetation, Deforestation, Indicators, Desertification risk, CB - Bodemfysica en Landgebruik, organic-matter, aggregate stability, biomass, business.industry, rock fragments, Bodemfysica en Landbeheer, 15. Life on land, [SDE.ES]Environmental Sciences/Environmental and Society, Soil Physics and Land Management, Latin America, Socioeconomic Factors, 13. Climate action, Agriculture, CLIMAT, soil properties, Africa, Environmental science, Plant cover, DEFORESTATION, business, AFRIQUE
Abstract

International audience; An approach to derive relationships for defining land degradation and desertification risk and developing appropriate tools for assessing the effectiveness of the various land management practices using indicators is presented in the present paper. In order to investigate which indicators are most effective in assessing the level of desertification risk, a total of 70 candidate indicators was selected providing information for the biophysical environment , socioeconomic conditions, and land management characteristics. The indicators were defined in 1,672 field sites located in 17 study areas in the Mediterranean region, Eastern Europe, Latin America, Africa, and Asia. Based on an existing geo-referenced database, classes were designated for each indicator and a sensitivity score todesertification was assigned to each class based on existing research. The obtained data were analyzed for the various processes of land degradation at farm level. The derived methodology was assessed using independent indicators, such as the measured soil erosion rate, and the organic matter content of the soil. Based on regression analyses, the collected indicator set can be reduced to a number of effective indicators ranging from 8 to 17 in the various processes of land degradation. Among the most important indicators identified as affecting land degradation and desertification risk were rain seasonality, slope gradient,plant cover, rate of land abandonment, land-use intensity, and the level of policy implementation.

Published
2014
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6. Assessing the effectiveness of sustainable land management policies for combating desertification: A data mining approach.

Author

Salvati L, Kosmas C, Kairis O, Karavitis C, Acikalin S, Belgacem A, Solé-Benet A, Chaker M, Fassouli V, Gokceoglu C, Gungor H, Hessel R, Khatteli H, Kounalaki A, Laouina A, Ocakoglu F, Ouessar M, Ritsema C, Sghaier M, Sonmez H, Taamallah H, Tezcan L, de Vente J, Kelly C, Colantoni A, and Carlucci M

Subjects
Agriculture, Fires, Greece, Humans, Morocco, Principal Component Analysis, Socioeconomic Factors, Soil, Spain, Tunisia, Turkey, Water Supply, Conservation of Natural Resources, Data Mining methods, Environmental Policy economics
Abstract

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., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Published
2016
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7. Evaluation and selection of indicators for land degradation and desertification monitoring: methodological approach.

Author

Kosmas C, Kairis O, Karavitis Ch, Ritsema C, Salvati L, Acikalin S, Alcala M, Alfama P, Atlhopheng J, Barrera J, Belgacem A, Solé-Benet A, Brito J, Chaker M, Chanda R, Coelho C, Darkoh M, Diamantis I, Ermolaeva O, Fassouli V, Fei W, Feng J, Fernandez F, Ferreira A, Gokceoglu C, Gonzalez D, Gungor H, Hessel R, Juying J, Khatteli H, Khitrov N, Kounalaki A, Laouina A, Lollino P, Lopes M, Magole L, Medina L, Mendoza M, Morais P, Mulale K, Ocakoglu F, Ouessar M, Ovalle C, Perez C, Perkins J, Pliakas F, Polemio M, Pozo A, Prat C, Qinke Y, Ramos A, Ramos J, Riquelme J, Romanenkov V, Rui L, Santaloia F, Sebego R, Sghaier M, Silva N, Sizemskaya M, Soares J, Sonmez H, Taamallah H, Tezcan L, Torri D, Ungaro F, Valente S, de Vente J, Zagal E, Zeiliguer A, Zhonging W, and Ziogas A

Subjects
Africa, Asia, Desert Climate, Environmental Restoration and Remediation trends, Europe, Eastern, Latin America, Mediterranean Region, Plant Development physiology, Rain, Regression Analysis, Seasons, Socioeconomic Factors, Soil chemistry, Environmental Monitoring methods, Environmental Restoration and Remediation methods
Abstract

An approach to derive relationships for defining land degradation and desertification risk and developing appropriate tools for assessing the effectiveness of the various land management practices using indicators is presented in the present paper. In order to investigate which indicators are most effective in assessing the level of desertification risk, a total of 70 candidate indicators was selected providing information for the biophysical environment, socio-economic conditions, and land management characteristics. The indicators were defined in 1,672 field sites located in 17 study areas in the Mediterranean region, Eastern Europe, Latin America, Africa, and Asia. Based on an existing geo-referenced database, classes were designated for each indicator and a sensitivity score to desertification was assigned to each class based on existing research. The obtained data were analyzed for the various processes of land degradation at farm level. The derived methodology was assessed using independent indicators, such as the measured soil erosion rate, and the organic matter content of the soil. Based on regression analyses, the collected indicator set can be reduced to a number of effective indicators ranging from 8 to 17 in the various processes of land degradation. Among the most important indicators identified as affecting land degradation and desertification risk were rain seasonality, slope gradient, plant cover, rate of land abandonment, land-use intensity, and the level of policy implementation.

Published
2014
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8. Evaluation and selection of indicators for land degradation and desertification monitoring: types of degradation, causes, and implications for management.

Author

Kairis O, Kosmas C, Karavitis Ch, Ritsema C, Salvati L, Acikalin S, Alcalá M, Alfama P, Atlhopheng J, Barrera J, Belgacem A, Solé-Benet A, Brito J, Chaker M, Chanda R, Coelho C, Darkoh M, Diamantis I, Ermolaeva O, Fassouli V, Fei W, Feng J, Fernandez F, Ferreira A, Gokceoglu C, Gonzalez D, Gungor H, Hessel R, Juying J, Khatteli H, Khitrov N, Kounalaki A, Laouina A, Lollino P, Lopes M, Magole L, Medina L, Mendoza M, Morais P, Mulale K, Ocakoglu F, Ouessar M, Ovalle C, Perez C, Perkins J, Pliakas F, Polemio M, Pozo A, Prat C, Qinke Y, Ramos A, Ramos J, Riquelme J, Romanenkov V, Rui L, Santaloia F, Sebego R, Sghaier M, Silva N, Sizemskaya M, Soares J, Sonmez H, Taamallah H, Tezcan L, Torri D, Ungaro F, Valente S, de Vente J, Zagal E, Zeiliguer A, Zhonging W, and Ziogas A

Subjects
Agriculture methods, Agriculture statistics & numerical data, Conservation of Natural Resources trends, Desert Climate, Environmental Monitoring statistics & numerical data, Environmental Restoration and Remediation trends, Fires, Rain, Risk Assessment methods, Salinity, Socioeconomic Factors, Water Movements, Conservation of Natural Resources methods, Environmental Monitoring methods, Environmental Restoration and Remediation methods, Soil chemistry
Abstract

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. The database described earlier in this issue by Kosmas and others (Environ Manage, 2013) for defining desertification risk was further analyzed to define the most important indicators related to the following degradation processes: water erosion in various land uses, tillage erosion, soil salinization, water stress, forest fires, and overgrazing. A correlation analysis was applied to the selected indicators in order to identify the most important variables contributing to each land degradation process. The analysis indicates that the most important indicators are: (i) rain seasonality affecting water erosion, water stress, and forest fires, (ii) slope gradient affecting water erosion, tillage erosion and water stress, and (iii) water scarcity soil salinization, water stress, and forest fires. Implementation of existing regulations or policies concerned with resources development and environmental sustainability was identified as the most important indicator of land protection.

Published
2014
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