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PREDICTION OF RARE‐PLANT OCCURRENCE: A SOUTHERN APPALACHIAN EXAMPLE
Author(s) -
Wiser Susan K.,
Peet Robert K.,
White Peter S.
Publication year - 1998
Publication title -
ecological applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.864
H-Index - 213
eISSN - 1939-5582
pISSN - 1051-0761
DOI - 10.1890/1051-0761(1998)008[0909:porpoa]2.0.co;2
Subject(s) - habitat , range (aeronautics) , ecology , biological dispersal , vegetation (pathology) , rare species , soil texture , ordination , indicator value , species distribution , environmental science , biology , soil water , population , medicine , materials science , demography , pathology , sociology , composite material
Ecologically sound efforts to manage or reintroduce populations of rare species require detailed knowledge of species habitat requirements. However, the fact that such species are rare implies that the data needed for habitat characterization are sparse and that species might well be absent from favorable sites due to chance aspects of dispersal or mortality. We use four rare plant species endemic to southern Appalachian high‐elevation rock outcrops, to illustrate how nonparametric and parametric logistic regression can yield predictive models of the probability that a species will occur, given certain site conditions. Models were constructed for each species at two scales: 100‐m 2 plots and 1‐m 2 subplots. At the 100‐m 2 plot scale, absences beyond the current geographic range were excluded. At the 1‐m 2 subplot scale, absences from subplots were only included if the species occurred elsewhere on the 100‐m 2 plot. Six significant models resulted; no significant model could be constructed for Solidago spithamaea or Calamagrostis cainii on 1‐m 2 subplots. For 100‐m 2 plots, the most valuable predictors were potential solar radiation, a soils gradient related to available soil iron, boron, and copper, and coarse‐scale rock surface texture, although Geum radiatum occurrences were difficult to predict at this scale. For 1‐m 2 subplots the best predictors were available soil cations, potential solar radiation, the proportion of exposed bedrock, and vegetation height. Along individual gradients response curves were often similar, but no two species were predicted by identical sets of site parameters. Beyond current range limits, existence of suitable habitat on 100‐m 2 plots was demonstrated for Solidago spithamaea, supporting a view that the range limits of this species are not necessarily set by availability of suitable habitat. Habitat‐based models have numerous management applications (such as to guide restoration and reintroduction efforts as well as to direct searches for additional populations) and provide a framework for future work on species‐specific physiological requirements.