Modeling and Predicting Species Occurrence Using Broad‐Scale Environmental Variables: an Example with Butterflies of the Great Basin

By E. Fleishman, R. Mac Nally, John P. Fay, D. Murphy. 2001

151 citations recorded by the source corpus.

Subfields: Ecological Modeling, Global and Planetary Change, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/cea4455d42e13a9301bc5fbace3021bc2bbfd8aa

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In Ecological Modeling

In Global and Planetary Change

In Nature and Landscape Conservation

Citations in the corpus

Environment, dispersal and patterns of species similarity (2006, background): “Dispersal processes produce a distance decay in species similarity because dispersal distances are always limited in space, so that at any given time not all species detect (and thus, occupy) all habitats (Shmida & Ellner, 1984; Fleishman et al., 2001).”
Predicting distributions of invasive species (2013, unknown): “… have provided key inputs for conservation planning and resource management, identifying new sites for rare species surveys, and global analyses of species distributions (Ferrier, 2002; Fleishman et al., 2001; Rangel et al., 2006; Zimmermann et al., 2007).”
Species Distribution Models: Ecological Explanation and Prediction Across Space and Time (2009, unknown): “For instance, macroecological and global change studies tend to be continental to global in scope (e.g., Araújo & New 2007), whereas studies targeting detailed ecological understanding or conservation planning tend toward local to regional extents (Fleishman et al. 2001, Ferrier et al. 2002).”
Evaluating predictive models of species’ distributions: criteria for selecting optimal models (2003, background): “Predictive modeling of species’ distributions now represents an important tool in biogeography, evolution, ecology, conservation, and invasive-species management ( Busby, 1986; Nicholls, 1989; Walker, 1990; Walker and Cocks, 1991; Sindel and Michael, 1992; Wilson et al., 1992; Box et al., 1993; Carp”
Species’ Distribution Modeling for Conservation Educators and Practitioners (2010, methodology): “For example, Fleishman et al. (2001) built models using butterfly occurrence records collected by the researchers during surveys in Nevada, USA.”
EXPLOITING TEMPORAL VARIABILITY TO UNDERSTAND TREE RECRUITMENT RESPONSE TO CLIMATE CHANGE (2007, background): “The future distributional range is identified with predicted climates that match the current range (e.g., Fleishman et al. 2001, Lasch et al. 2002, Thomas et al. 2004).”
Threshold criteria for conversion of probability of species presence to either–or presence–absence (2007, methodology): “…are actually widely used in order to generate binary distribution maps (see, for example, Li et al., 1997; Guisan et al., 1998; Manel et al., 1999a; Fleishman et al., 2001; Thuiller, 2003; Berg et al., 2004; Meggs et al., 2004; Segurado and Araújo, 2004; Araújo et al., 2005; Luoto et al., 2005).”
Predicting species distributions: a critical comparison of the most common statistical models using artificial species (2007, background): “Finally, on occasions it might be useful to know if the models are predicting the presences or absences more successfully (Fleishman et al., 2001; Bulluck et al., 2006).”
Real vs. artefactual absences in species distributions: tests for Oryzomys albigularis (Rodentia: Muridae) in Venezuela (2003, methodology): “…Carpenter et al., 1993; Huntley et al., 1995; Austin & Meyers, 1996; Kadmon & Heller, 1998; Yom-Tov & Kadmon, 1998; Corsi et al., 1999; Jarvis & Robertson, 1999; Peterson et al., 1999, 2002c; Samways et al., 1999; Skov, 2000; Zalba et al., 2000; Fleishman et al., 2001; James & McCulloch, 2002).”
Which species will succesfully track climate change? The influence of intraspecific competition and density dependent dispersal on range shifting dynamics (2007, background): “Since the metapopulation model of Levins (1969), many authors have produced models of species on fragmented habitats for a variety of purposes (Hanski and Thomas 1994, Hanski et al.”
Validation Tests of Predictive Models of Butterfly Occurrence Based on Environmental Variables (2003, methodology): “Our approach to developing predictive models of species occurrence has four phases ( for full details see Fleishman et al. 2001 b ).”