Effects of grazing and topography on long-term vegetation changes in a Mediterranean ecosystem in Israel

TitleEffects of grazing and topography on long-term vegetation changes in a Mediterranean ecosystem in Israel
Publication TypeJournal Article
Year of Publication1999
AuthorsCarmel, Y., & Kadmon R.
JournalPlant Ecology
Volume145
Pagination243-254
Keywordsaerial photographs, GIS, landscape ecology, regression model, spatial structure, Vegetation dynamics
Abstract

The dynamics of Mediterranean vegetation over 28 years was studied in the Northern Galilee Mountains, Israel, in order to identify and quantify the major factors affecting it at the landscape scale. Image analysis of historical and current aerial photographs was used to produce high resolution digital vegetation maps (pixel size = 30 cm) for an area of 4 km2 in the Galilee Mountains, northern Israel. GIS tools were used to produce corresponding maps of grazing regime, topographic indices and other relevant environmental factors. The effects of those factors were quantified using a multiple regression analyses. Major changes in the vegetation occurred during the period studied (1964–1992); tree cover increased from 2% in 1964 to 41% in 1992, while herbaceous vegetation cover decreased from 56% in 1964 to 24% in 1992. Grazing, topography and initial vegetation cover were found to significantly affect present vegetation patterns. Both cattle grazing and goat grazing reduced the rate of increase in tree cover, yet even intensive grazing did not halt the process. Grazing affected also the woody-herbaceous vegetation dynamics, reducing the expansion of woody vegetation. Slope, aspect, and the interaction term between these two factors, significantly affected vegetation pattern. Altogether, 56% and 72% of the variability in herbaceous and tree cover, respectively, was explained by the regression models. This study indicates that spatially explicit Mediterranean vegetation dynamics can be predicted with fair accuracy using few biologically important environmental variables.