Date of Award
1985
Degree Type
Dissertation
Degree Name
Doctor of Philosophy
Abstract
The investigation which I described in this thesis focused on methodogical problems in community ecology as well as the actual properties of structure and composition in ruderal weed communities. The study sites were located within the city limits of London, Ontario. Concerning the methdodology, the problem of the choice of an optimal plot size was addressed on an experimental basis. As an outcome, an effective procedure was found and described. In addition, various conventional data types used in phytosociology were evaluated for their suitability to depict underlying group structure and trends. It was discovered that untransformed ordinal data yielded comparable pattern information to that of percentage cover data. However, as further analyses have shown, presence/absence data gave different results from those obtained with the ordinal data.;Three ruderal habitats, namely, old fields, vacant lots, and topsoil mounds were chosen for quantitative examination of the vegetation and its relationships to environment. Vegetation was sampled using a stratified multistage random sampling design. An optimal plot size (7.5*7.5 m('2)) was determined in a pilot study and quantitative vegetation data was gathered (251 plots). Soil samples from each plot were analysed physically and chemically. Data sets from each habitat were submitted to analysis by clustering techniques and ordinations.;The vegetation types resulting from cluster analyses for each data set were found to be interpretable with respect to a temporal (successional) sequence of the sites. Besides suggesting potential continuity in vegetation, ordinations disclosed successional trends and environmental gradients. Variation in environmental factors such as moisture availability and nutrient supply were found closely associated with the successional trends.
Recommended Citation
Shaukat, Syed Shahid, "Approaches To The Analysis Of Ruderal Weed Vegetation" (1985). Digitized Theses. 1466.
https://ir.lib.uwo.ca/digitizedtheses/1466