2013
DOI: 10.1890/es13-00155.1
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Process‐based and correlative modeling of desert mistletoe distribution: a multiscalar approach

Abstract: Abstract. Because factors affecting distributional areas of species change as scale (extent and grain) changes, different environmental and biological factors must be integrated across geographic ranges at different resolutions, to understand fully the patterns and processes underlying species' ranges. We expected climate factors to be more important at coarse resolutions and biotic factors at finer resolutions. We used data on occurrence of a parasitic plant (Phoradendron californicum), restricted to parts of… Show more

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Cited by 25 publications
(29 citation statements)
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References 70 publications
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“…The distribution and ecology of vector species is a determinant of mistletoe distribution and aggregation patterns at multiple spatial scales (Larson, ; Overton, ; Aukema & Martínez del Rio, ,b; Aukema, ; Rist et al ., ; Lira‐Noriega et al ., ). In our analyses, overall host and mistletoe niches showed similarity with nine species of potential dispersers in year‐round and winter distributions.…”
Section: Discussionmentioning
confidence: 97%
See 1 more Smart Citation
“…The distribution and ecology of vector species is a determinant of mistletoe distribution and aggregation patterns at multiple spatial scales (Larson, ; Overton, ; Aukema & Martínez del Rio, ,b; Aukema, ; Rist et al ., ; Lira‐Noriega et al ., ). In our analyses, overall host and mistletoe niches showed similarity with nine species of potential dispersers in year‐round and winter distributions.…”
Section: Discussionmentioning
confidence: 97%
“…We also assembled information on mistletoe occurrences associated with each host species from the same online databases, as well as from A.L.‐N. 's field collections across the geographical range of the species in 2010 and 2012 (Lira‐Noriega et al ., ). The numbers of unique occurrences of infected hosts were: A. constricta , 8; A. greggii , 131; C. floridum , 13; C. microphyllum , 23; L. tridentata , 8; O. tesota , 30; P. glandulosa , 37; and P. velutina , 45.…”
Section: Methodsmentioning
confidence: 97%
“…Current theory (Sober on, 2007(Sober on, , 2010Peterson et al, 2011) considers that the unlinked variables needed for niche/distributional models are abiotic (or reflective of habitat/vegetation structure), but this exclusion of biotic interactors may not be justified (Anderson, 2013;Lira-Noriega et al, 2013). Seemingly, the only restriction prohibiting the use of a biotic interactor as a variable in building a niche/distribution model would be if its values are affected by (linked to) the population level of the focal species ( Fig.…”
Section: Niche Perspectives and Predictor Variablesmentioning
confidence: 99%
“…These depictions of the range of the interactor likely would be maps of binary presence/absence or continuous representations of suitability (or probability of presence) within the areas occupied. Indeed, many recent studies have used biotic interactors as predictors (Meier et al, 2010;Jaeschke et al, 2012;Giannini et al, 2013), although seldom considering whether or not they constitute unlinked variables (Lira-Noriega et al, 2013).…”
Section: Niche Perspectives and Predictor Variablesmentioning
confidence: 99%
“…Macroecological analyses are powerful in that they allow patterns to be drawn over large taxonomic and geographic extents, but also have some limitations. First, they frequently have a coarse resolution (Beck et al, 2012;Lira-Noriega, Sobéron, & Miller, 2013), but species often interact with their environment at finer (microhabitat) scale. Microhabitat conditions are not always captured by macroecological variables, and can provide a more accurate description of the effect of environmental variation on individuals (De Frenne et al, 2019;Ficetola et al, 2018;Moore, Stow, & Kearney, 2018;Scheffers, Edwards, Diesmos, Williams, & Evans, 2014).…”
Section: Introductionmentioning
confidence: 99%