Skip to main navigation Skip to search Skip to main content

Evaluation and Selection of Indicators for Land Degradation and Desertification Monitoring: Methodological Approach

  • C. Kosmas
  • , Or Kairis
  • , Ch Karavitis
  • , C. Ritsema
  • , L. Salvati
  • , S. Acikalin
  • , M. Alcalá
  • , P. Alfama
  • , J. Atlhopheng
  • , J. Barrera
  • , A. Belgacem
  • , A. Solé-Benet
  • , J. Brito
  • , M. Chaker
  • , R. Chanda
  • , C. Coelho
  • , M. Darkoh
  • , I. Diamantis
  • , O. Ermolaeva
  • , V. Fassouli
  • W. Fei, J. Feng, F. Fernandez, A. Ferreira, C. Gokceoglu, D. Gonzalez, H. Gungor, R. Hessel, J. Juying, H. Khatteli, N. Khitrov, A. Kounalaki, A. Laouina, P. Lollino, M. Lopes, L. Magole, L. Medina, M. Mendoza, P. Morais, K. Mulale, F. Ocakoglu, M. Ouessar, C. Ovalle, C. Perez, J. Perkins, F. Pliakas, M. Polemio, A. Pozo, C. Prat, Y. Qinke, A. Ramos, J. Ramos, J. Riquelme, V. Romanenkov, L. Rui, F. Santaloia, R. Sebego, M. Sghaier, N. Silva, M. Sizemskaya, J. Soares, H. Sonmez, H. Taamallah, L. Tezcan, D. Torri, F. Ungaro, S. Valente, J. de Vente, E. Zagal, A. Zeiliguer, W. Zhonging, A. Ziogas
  • Agricultural University of Athens
  • Wageningen University & Research
  • Italian National Council for Agricultural Research
  • Osmangazi University
  • Institut de recherche pour le développement
  • National Institute for Agriculture Research and Development
  • University of Botswana
  • Instituto de Investigaciones Agropecuarias - Ministerio de Agricultura, Chile
  • Institut des Régions Arides
  • Consejo Superior de Investigaciones Científicas (EEZA-CSIC)
  • Mohammed V University in Rabat
  • University of Aveiro
  • Democritus University of Thrace
  • Moscow State University of Environmental Engineering
  • CAS - Institute of Soil and Water Conservation
  • Polytechnic Institute of Coimbra
  • Research Institute for Hydrogeological Protection

Research output: Contribution to journalArticlepeer-review

127 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)951-970
Number of pages20
JournalEnvironmental Management
Volume54
Issue number5
DOIs
Publication statusPublished - Nov 2013
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 15 - Life on Land
    SDG 15 Life on Land

Keywords

  • Desertification risk
  • Indicators
  • Land degradation

Fingerprint

Dive into the research topics of 'Evaluation and Selection of Indicators for Land Degradation and Desertification Monitoring: Methodological Approach'. Together they form a unique fingerprint.

Cite this