Abstract
A procedure for monitoring plant community change was described using data from 189 quadrats (each 0.09 m2 in area) from or near 11 Carex exserta meadow sites in the high Sierra Nevada, California, USA. Initially the quadrats were agglomerated into five clusters by the flexible clustering strategy (beta=−0.25) with the standard absolute distance resemblance function. Data for each quadrat were cover percentages for C. exserta, other plants, litter, soil, gravel, and rock. The five clusters appeared to define a cover gradient, from quadrats with mostly gravel and rock to those with mostly C. exserta, and were accordingly designated pioneer, low seral, mid-seral, high seral, and climax.
Classification functions (from discriminant analysis) are used with values of the variables to classify individual quadrats on sites used to monitor change. A site is characterized at repeated observations by the proportions of quadrats in each class. Within-class (low seral vs. low seral) rather than between-class (pioneer vs. low seral) tests are made for presence of change. Confidence intervals for differences in proportions of quadrats or individual quadrat probabilities of class membership are computed. If the confidence intervals do not cover zero, values for time one versus time two differ significantly.
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Ratliff, R.D., Westfall, S.E. Monitoring plant community change: an application of quadrat classification + discriminant analysis. Vegetatio 80, 1–9 (1989). https://doi.org/10.1007/BF00049136
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DOI: https://doi.org/10.1007/BF00049136