Title
Environmental modulation of self-organized periodic vegetation patterns in Sudan Environmental modulation of self-organized periodic vegetation patterns in Sudan
Author
Faculty/Department
Faculty of Medicine and Health Sciences
Publication type
article
Publication
Copenhagen ,
Subject
Biology
Source (journal)
Ecography. - Copenhagen
Volume/pages
34(2011) :6 , p. 990-1001
ISSN
0906-7590
ISI
000297738200009
Carrier
E
Target language
English (eng)
Full text (Publishers DOI)
Affiliation
University of Antwerp
Abstract
Spatially periodic vegetation patterns in arid to semi-arid regions have inspired numerous mechanistic models in the last decade. All embody a common principle of self-organization and make concordant, hence robust, predictions on how environmental factors may modulate the morphological properties of these patterns. Such an array of predictions still needs to be corroborated by synchronic and diachronic field observations on a large scale. Using Fourier-based texture analysis of satellite imagery, we objectively categorized the typical morphologies of periodic patterns and their characteristic scales (wavelength) over extensive areas in Sudan. We then analyzed the environmental domain and the modulation of patterns morphologies at different dates to test the theoretical predictions within a single synthetic and quantitative study. Our results show that, below a critical slope gradient which depends on the aridity level, pattern morphologies vary in space in relation to the decrease of mean annual rainfall in a sequence consistent with the predictions of self-organization models: gaps, labyrinths and spots with increasing wavelengths. Moreover, the same dynamical sequence was observed over time during the Sahelian droughts of the 1970s and 1980s. For a given morphology, the effect of aridity is to increase the pattern wavelength. Above the critical slope gradient, we observed a pattern of parallel bands oriented along the contour lines (the so called tiger-bush). The wavelength of these bands displayed a loose inverse correlation with the slope. These results highlight the pertinence of self-organization theory to explain and possibly predict the dynamics of these threatened ecosystems.
E-info
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