n Southern African Forestry Journal - Weed composition in relation to site in re-established pine compartments on the Mpumalanga Escarpment, South Africa : scientific paper
|Article Title||Weed composition in relation to site in re-established pine compartments on the Mpumalanga Escarpment, South Africa : scientific paper|
|© Publisher:||South African Institute of Forestry (SAIF)|
|Journal||Southern African Forestry Journal|
|Author||Leander Jarvel and Robert Pallett|
|Publication Date||Nov 2002|
|Pages||15 - 20|
A survey of weed species distribution patterns and abundance in clearfelled pine compartments in the Mpumalanga escarpment region was undertaken to determine the relationship between weed species and cover abundance in relation to environmental and compartmental factors. In total 359 transects were sampled each with 5 X 25 m<sup>2</sup> quadrats (1 795 square quadrats in total). <br><I>Phytolacca octandra</I> and <I>Solanum mauritianum</I> were found to be the most widespread species in the study area and dominated most transects. Less common were <I>Pteridium</I> spp., <I>Bidens pillosa, Oplismenis hirtillus</I> and <I>Senecio tamoides</I>, but these species had high cover abundance ratings where they did occur and therefore may be considered as having a high potential to compete with the tree crop for resources. <br>The most important factor affecting vegetation cover abundance and species composition was altitude. Other factors which were important in determining weed distribution patterns were the length of time since clearfelling, aspect, the proximity of the stand to indigenous woody vegetation in ravines, local moisture conditions as affected by slope shape and type and position in the landscape with respect to river valley systems. <br>Eight weed groups were identified in the survey area using discriminant function analysis to link environmental variables to weed communities. Each weed group is characterised by differences in cover abundance and relative proportions of different weed types. The weed groups and their association with environmental variables are used as a predictive tool for developing weed control strategies and control measures in forest operations.
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