2017
DOI: 10.1086/690025
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Spatial Clustering and Ecological Crowding of Valley Oak (Quercus lobata, Née) Associated with Shifts in Recruitment Establishment Sites in Southern California

Abstract: Premise of research. Valley oak (Quercus lobata, Née) has received much attention due to concerns about regeneration failure and, more recently, compositional and structural community changes associated with this foundation species. Changes in the structure and spatial distribution of valley oak stands, as examined in this article, are likely affecting ecological processes and interactions throughout communities where it is found. Methodology. We used quadrat-based methods of spatial analysis, Morisita's index… Show more

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Cited by 1 publication
(3 citation statements)
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References 45 publications
(87 reference statements)
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“…Differences in I Mr values do not have a clear interpretation other than "higher" or "lower", and analyzing differences in the index generated with different quadrat sizes is even more confounding. For example, Hayes and Donnell [30] applied I M and I Mr to valley oak stem locations at the same sites examined in the present paper, and they found clear evidence of clustering at all three sites, for multiple quadrat sizes. Their results, however, demonstrate the difficulty of comparing the index values across sites since only relative statements about differences in the degree and intensity of crowding could be made and only when the sites are analyzed using the same quadrat size.…”
Section: Discussionsupporting
confidence: 57%
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“…Differences in I Mr values do not have a clear interpretation other than "higher" or "lower", and analyzing differences in the index generated with different quadrat sizes is even more confounding. For example, Hayes and Donnell [30] applied I M and I Mr to valley oak stem locations at the same sites examined in the present paper, and they found clear evidence of clustering at all three sites, for multiple quadrat sizes. Their results, however, demonstrate the difficulty of comparing the index values across sites since only relative statements about differences in the degree and intensity of crowding could be made and only when the sites are analyzed using the same quadrat size.…”
Section: Discussionsupporting
confidence: 57%
“…Further, since the rMax curves are based on maximum I Mr values and the r number of stems for that maximum value, using the I Mr curves to choose our quadrat size assures that the definition of clustering is based on an empirical limit of r stems being clustered using the quadrat size chosen. While Hayes and Donnell [30] examined I Mr values at the three sites using multiple quadrat sizes for analysis, interpretation was constrained by the necessity of having results from each quadrat size on different scales, and the clearest interpretation of differences among sites was possible only when the same quadrat size was used for all three sites. Applying our final measure of clustering, d M (see Figure 8), we showed a new approach to solve the problem of scale in terms of a single quadrat size.…”
Section: Discussionmentioning
confidence: 99%
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