The influence of scale on the discernment of plant community patterns was examined using vegetation-environment data collected from a subalpine wet meadow in south-coastal British Columbia. Species cover data were recorded in 225, 0.25 m quadrats systematically located at 5m intervals in a 40 m × 120 m sampling grid. Environmental data consisted of quadrat elevations as well as measured and kriged estimates of five soil variables (carbon content, pH, electrical conductivity, percent sand, and percent clay). Sampling scale was adjusted by aggregating neighbouring quadrats into composite sampling units; analytical scale was altered by varying the intercept level in dendrograms from minimum increase of sum of squares cluster analysis of the vegetation data corresponding to the different sampling scales. The resulting classifications were evaluated for their ability to explain variation in the vegetation data and in the environmental data. The vegetation variation explained by the classifications was highest at the smallest sampling scale indicating that vegetation heterogeneity is fine grained. In contrast, the environmental variation explained was higher for the classifications based on the larger composite sampling units implying a coarser scaling of abiotic conditions within the study area. These results were consistent with the recognition of three main zones along a drainage gradient within the sampling grid — upper mixed-forb, middle heath, and lower sedge. There was also evidence that the orientation of rectangular sampling units parallel to the drainage gradient leads to higher levels of explained variation. This study reaffirms the need for careful consideration of alternatives both in field sampling and analytical phases of vegetation research to ensure that description and interpretation of patterns adequately address study objectives and that vegetation-environment relationships are more completely investigated from a hierarchical perspective.
Minimum increase of sum of squares cluster analysis
Principal component analysis.
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Drewa, P.B., Bradfield, G.E. Large scale related effects on the determination of plant communities and relationships with environmental variables. COMMUNITY ECOLOGY 1, 157–164 (2000). https://doi.org/10.1556/ComEc.1.2000.2.5
- Environmental variance explained
- Grain size
- Minimum increase of sum of squares cluster analysis
- Principal component analysis
- Sampling scale
- Vegetation classification