Predictive Vegetation Mapping in the Mediterranean Context: Considerations and Methodological Issues

  • I. N. Vogiatzakis
  • A. Malounis
  • G. H. Griffiths
Part of the Forestry Sciences book series (FOSC, volume 76)


The need to map vegetation communities over large areas for nature conservation and to predict the impact of environmental change on vegetation distributions, has stimulated the development of techniques for predictive vegetation mapping. Predictive vegetation studies start with the development of a model relating vegetation units and mapped physical data, followed by the application of that model to a geographic database and over a wide range of spatial scales. This field is particularly important for identifying sites for rare and endangered species and locations of high biodiversity such as many areas of the Mediterranean Basin. The potential of the approach is illustrated with a mapping exercise in the alti-meditterranean zone of Lefka Ori in Crete. The study established the nature of the relationship between vegetation communities and physical data including altitude, slope and geomorphology. In this way the knowledge of community distribution was improved enabling a GIS-based model capable of predicting community distribution to be constructed. The paper describes the development of the spatial model and the methodological problems of predictive mapping for monitoring Mediterranean ecosystems. The paper concludes with a discussion of the role of predictive vegetation mapping and other spatial techniques, such as fuzzy mapping and geostatistics, for improving our understanding of the dynamics of Mediterranean ecosystems and for practical management in a region that is under increasing pressure from human impact.


Community Type Fuzzy Mapping Scree Slope Geomorphological Type Decision Makin 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Burrough, P.A., McDonnell, R.A. 1998. Principles of Geographical Information Systems. 2nd edition. Oxford University Press, Oxford.Google Scholar
  2. Dafis, S., Papastergiadou, E., Georghiou, K., Babalonas, D., Georgiadis, T., Papageorgiou, M., Lazaridou, T., Tsiaoussi, V. (eds.) 1996. Directive 92/43/EEC - The Greek “Habitat” project NATURA 2000: an Overview. Commission of the European Communities DG XI, The Goulandris Natural History Museum - Greek Biotope/Wetland Center.Google Scholar
  3. Davis, F.W., Goetz, S. 1990. Modelling vegetation pattern using digital terrain data. Landscape Ecology 4 (1): 69–80.CrossRefGoogle Scholar
  4. Davis, S.D., Heywood, V.H., Hamilton, A.C. 1994. Centres of Plant Diversity. WWF/IUCN, Cambridge.Google Scholar
  5. ESRI 2001. Getting to know ArcGIS desktop ESRI, Redlands, California.Google Scholar
  6. Franklin, J. 1995. Predictive Vegetation Mapping: geographical modelling of biospatial patterns in relation to environmental gradients. Progress in Physical Geography 19: 474–499.CrossRefGoogle Scholar
  7. Greuter, W. 1994. Extinction in the Mediterranean areas. Philosophical Transactions of the Royal Society, London, B 344: 41–46.Google Scholar
  8. Guisan, A., Zimmermann, N.E. 2000. Predictive habitat distribution models in ecology. Ecological Modelling 135: 147–186.CrossRefGoogle Scholar
  9. Hill, M.O. 1979. TWINSPAN - a FORTRAN Program for Arranging Multivariate Data in an Ordered Two Way Table by Classification of the Individuals and the Attributes. Cornell University, Department of Ecology and Systematics.Google Scholar
  10. Holmgren, P., Thuresson, T. 1998. Satellite remote sensing for forest planning–a review. Scandinavian Journal of Forest Research 13: 90–110.CrossRefGoogle Scholar
  11. Lillesand, T.M., Kiefer, M.W. 2000. Remote Sensing and Image Interpretation, 4th edn. John Wiley and Sons, New York.Google Scholar
  12. Kennedy, P., Karteris, M. (eds.) 1994. Satellite Technology and GIS for Mediterranean Forest Mapping and Fire Management. International Workshop Proceedings. European Commission, Thessaloniki.Google Scholar
  13. Kent, M., Gill, W.J., Weaver, R.E., Armitage, R.P. 1997. Landscape and plant community boundaries in biogeography. Progress in Physical Geography 21 (3): 315–353.CrossRefGoogle Scholar
  14. Kollias, V.J., Kalivas, D.P., Yassoglou, N.J. 1999. Mapping the soil resources of a recent alluvial plain in Greece using fuzzy sets in a GIS environment. European Journal of Soil Science 50 (2): 261–273.CrossRefGoogle Scholar
  15. Norton, T.W., Nix, H.A. 1991. Application of biological modelling and GIS to identify regional wildlife corridors. In Nature Conservation 2: the Role of Corridors. D.A.Saunders, R.J. Hobbs (eds.), pp. 19–26. Surrey Beatty & Sons, Chipping Norton, NSW.Google Scholar
  16. Odum, E.P. 1975. Ecology: The link between the natural and physical sciences. Holt-Saunders International Editions, London.Google Scholar
  17. Olsvig-Whittaker, L.S., Naveh, Z., Giskin, M., Nevo, E. 1992 Microsite differentiation in a Mediterranean oak savanna. Journal of Vegetation Science 3: 209–216.CrossRefGoogle Scholar
  18. Phitos, D., Strid, A., Snogerup, S., Greuter, W. 1996. The red Data Book of Rare and Threatened Plants of Greece. WWF, Athens.Google Scholar
  19. Quézel, P. 1985. Definition of the Mediterranean region and the origins of the flora. In Plant Conservation in the Mediterranean Area. Edited by C.Gomez-Campo, pp. 9–24, Junk, Dordrecht.Google Scholar
  20. Shoshany, M. 2000. Satellite remote sensing of natural Mediterranean vegetation: a review within an ecological context. Progress in Physical Geography 24 (2): 153–176.Google Scholar
  21. Tappeiner, U., Tasser, E., Tappeiner, G. 1998. Modelling vegetation patterns using natural and anthropogenic influence factors: preliminary experience with GIS based model applied to an Alpine area. Ecological Modelling 113: 225–237.CrossRefGoogle Scholar
  22. Braak, C.J.F. 1986. Canonical Correspondence Analysis: a new eigenvector technique for multivariate direct gradient analysis. Ecology 67 (5): 1167–1179.CrossRefGoogle Scholar
  23. Etten, E.J.R. 1998. Mapping vegetation in an arid, mountainous region of Western Australia. Applied Vegetation Science 1: 189–200.CrossRefGoogle Scholar
  24. Maarel, E. 1990. Ecotones and ecolines are different. Journal of Vegetation Science 1: 135–138.CrossRefGoogle Scholar
  25. Vogiatzakis, I.N. 2000. Predicting the distribution of plant communities in the Lefka Ori, Crete, using GIS. Unpublished Ph.D. Thesis, Department of Geography, The University of Reading. 291 pp.Google Scholar
  26. Vogiatzakis, I.N., Griffiths, G.H. 2001. Vegetation-environment relationships in Lefka Ori (Crete, Greece): ordination results from montane-mediterranean and oro-mediterranean communities. Ecologia Mediterranea 27 (1): 15–32.Google Scholar
  27. Walter K.S., Gillet, H.J. 1998. IUCN Red List of Threatened Plants.IUCN, Cambridge, 862 pp.Google Scholar
  28. WCMC 2000. European Forests and Protected Areas: Gap Analysis. World Conservation Monitoring Centre, Technical Report. Cambridge. 71 pp.Google Scholar
  29. White, F. 1983. The Vegetation of Africa. Unesco, Paris.Google Scholar
  30. Zimmermann, N.E., Kienast, F. 1999. Predictive mapping of alpine grasslands in Switzerland: species versus community approach. Journal of Vegetation Science 10: 469–482.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2003

Authors and Affiliations

  • I. N. Vogiatzakis
    • 1
  • A. Malounis
    • 2
  • G. H. Griffiths
    • 3
  1. 1.Department of GeographyThe University of ReadingReading BerksUK
  2. 2.Department of Agriculture and ForestryUniversity of AberdeenAberdeenUK
  3. 3.Department of GeographyThe University of ReadingReading BerksUK

Personalised recommendations