1 <h5>Introduction</h5> Predictive modeling of species geographic distributions based on the environmental conditions of sites of known occurrence constitutes an important technique in analytical biology, with applications in conservation and reserve planning, ecology, evolution, epidemiology, invasive-species management and other fields (Corsi et al., 1999; Peterson and Shaw, 2003; Peterson et al., 1999; Scott et al., 2002; Welk et al., 2002; Yom-Tov and Kadmon, 1998) . Sometimes both presence and absence occurrence data are available for the development of models, in which case general-purpose statistical methods can be used (for an overview of the variety of techniques currently in use, see Corsi et al., 2000; Elith, 2002; Guisan and Zimmerman, 2000; Scott et al., 2002 ). However, while vast stores of presence-only data exist (particularly in natural history museums and herbaria), absence data are rarely available, especially for poorly sampled tropical regions where modeling potentially has the most value for conservation (Anderson et al., 2002; Ponder et al., 2001; Soberón, 1999) . In addition, even when absence data are available, they may be of questionable value in many situations (Anderson et al., 2003) . Modeling techniques that require only presence data are therefore extremely valuable (Graham et al., 2004)
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