. The Canadian field-naturalist. 2004 Erickson: Bird Communities of Garry Oak Habitat 381 X < Community 2 +VGSw ^oSl Community 4 ^ChSp ^RBNu hDEJu ^TcyWfl Community 3. Axis 1 Figure 6. Garry Oak bird communities from DCA analysis of 1994 data, Axis 1 vs. 3. See explanation for Figure 4. ods (10, 12 species: Corcuera and Butterfield 1999). My averages were much lower than those recorded on multiple plot, large-area studies: 21 to 25 late-spring species on five, 70 to 130 ha, stands in Oregon (Ander- son 1970), and 9 to 29 breeding species from 40 ha oak census plots in Pennsylvania (Probst 1
. The Canadian field-naturalist. 2004 Erickson: Bird Communities of Garry Oak Habitat 381 X < Community 2 +VGSw ^oSl Community 4 ^ChSp ^RBNu hDEJu ^TcyWfl Community 3. Axis 1 Figure 6. Garry Oak bird communities from DCA analysis of 1994 data, Axis 1 vs. 3. See explanation for Figure 4. ods (10, 12 species: Corcuera and Butterfield 1999). My averages were much lower than those recorded on multiple plot, large-area studies: 21 to 25 late-spring species on five, 70 to 130 ha, stands in Oregon (Ander- son 1970), and 9 to 29 breeding species from 40 ha oak census plots in Pennsylvania (Probst 1980). My total number of species detections (66) is higher than in a number of studies in oak woodland (, 38 spe- cies in Dedon et al. 1984; 20 to 62 species in Leidolf et al. 2000; 43 to 51 species in Stone no date*; 50 and 58 species in each of two seasons, five forest types, Corcuera and Butterfield 1999) but is lower than in some other comparable results (, 77 species in Gar- cia et al. 1998). My total would be increased by an additional 12 species which I recorded as "out of plot", "out of habitat", or "overhead". However, much of this difference is irrelevant, in that my interest in defining bird communities was at the plot (not area) level, and was focused on frequently occurring species which are easily detected within my plot parameters, not on less common species used to round out a full species list. The graphical location method is an objective one, in its centering technique and the proportional alloca- tion of multivariate space to each community. Unbi- ased shapes, such as squares or circles, were used to define multivariate species aggregations and overlap in composition was accepted. Other methods include subjective ones (, Pojar 1995), and other objective approaches, such as the use of a "fuzzy-clustering partition coefficient" (Abernethy et al. 2001*). These methods tend to result in elUptic forms, irregular
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