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An ordination study to view vegetation structure dynamics in disturbed and undisturbed mangrove forests in Kenya and Sri Lanka
Dahdouh-Guebas, F.; Kairo, J.G.; Jayatissa, L.P.; Cannicci, S.; Koedam, N. (2002). An ordination study to view vegetation structure dynamics in disturbed and undisturbed mangrove forests in Kenya and Sri Lanka. Plant Ecology 161(1): 123-135
In: Plant Ecology. Springer: London; Dordrecht; Boston. ISSN 1385-0237; e-ISSN 1573-5052, more
Peer reviewed article  

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Keywords
Author keywords
    vegetation, environmental factors

Authors  Top 
  • Dahdouh-Guebas, F., more
  • Kairo, J.G., more
  • Jayatissa, L.P., more
  • Cannicci, S.
  • Koedam, N., more

Abstract
    The mangrove vegetation of a disturbed and undisturbed site in both Kenya and Sri Lanka was investigated in the field for three vegetation layers: adult trees, young trees, and juvenile trees. A minimum of 25 sample points, in which the vegetation was described and environmental factors (salinity, light intensity, land/water ratio, abundance of herbivorous crabs and snail abundance) were measured or estimated, were taken on each site. Detrended correspondence analysis (DCA) and canonical correspondence analysis (CCA) were used to summarize the data bulk, to investigate the vegetation dynamics (e.g., comparability of species distribution in the three vegetation layers), and/or to link the vegetation data to the environmental factors. Results showed that species clusters were relatively easy to delineate, whether mangrove zonation was present or not. Among the environmental factors, the abundance of propagule predators (mostly sesarmid crabs) contributed significantly to the variation in vegetation and could be an explanatory parameter for the observed vegetation data in a majority of sites. In the site where it was not, the most important factor in the ordination was the land/water ratio, which is important at the ecological level as well (link between water level and vegetation dynamics). However, none of the environmental factors could successfully explain the total variability in the vegetation data suggesting that other, more determining factors exist. Our results further provide information on the dynamic or non-dynamic nature of a forest and on its ability to rejuvenate, and may contribute to appropriate forestry management guidelines in the future.

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