The biogeography of invasive alien plants in California: an application of GIS and spatial regression analysis

By S. Dark. 2004

153 citations recorded by the source corpus.

Subfields: Ecology, Nature and Landscape Conservation, Plant Science

View Paper: https://www.semanticscholar.org/paper/25d9e261500a3bb4f6c4d5902070fea56e26aa8f

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In Ecology

In Nature and Landscape Conservation

In Plant Science

Citations in the corpus

The habitat and conduit functions of roads in the spread of three invasive plant species (2009, unknown): “At a coarse scale, there are many qualitative reports of species’ distributions expanding along roadsides, and the assumption that roadsides serve as dispersal corridors in regional invasions is widely accepted (e.g. Brothers 1992; Matlack 2002; Dark 2004; Essl 2005).”
Species distribution models in conservation biogeography: developments and challenges (2013, methodology): “(Dark, 2004) 62 Application invasives: spatial autoregressive model contrasting invasive versus non-invasive”
Conservation Biogeography: assessment and prospect (2005, background): “…issues concerned with the proper analysis of spatially distributed data, and especially the concerns over spatial autocorrelation, and other artefacts such as the so-called geometric constraints problem (see, e.g. Diniz-Filho et al., 2003; Hawkins & Porter, 2003; Colwell et al., 2004; Dark, 2004).”
Effect of species rarity on the accuracy of species distribution models for reptiles and amphibians in southern California (2009, background): “…for conservation planning and land management (Ferrier et al ., 2002; Burgman et al ., 2005), to forecast the potential range of invasive species (Dark, 2004; Richardson & Thuiller, 2007), and to predict the impacts of climate change on species and ecosystems (Iverson & Prasad, 1998; Araújo et…”
Scale for resource selection functions (2006, background): “Although Dark (2004) claimed that autocorrelation is fundamentally important in building models of distribution, inspection of her results leads me to question this conclusion because model coefficients were virtually identical whether or not a spatially autoregressive model was used.”
Effects of incorporating spatial autocorrelation into the analysis of species distribution data (2007, methodology): “© 2006 The Author 134 Global Ecology and Biogeography, 16, 129–138 Journal compilation © 2006 Blackwell Publishing Ltd Dutilleul correction employed by Deutschewitz et al. (2003), Fang (2005) and Rodríguez et al. (2006) only corrects the significance value of a correlation (in both cases the effect ”
Distribution of alien vs. native plant species in roadside communities along an altitudinal gradient in Tenerife and Gran Canaria (Canary Islands) (2005, background): “Hence, lower DUN and higher road density can be related to increased ‘propagule pressure’ which is one of the most important factors explaining richness in alien species invasion success (Wace, 1977; Wester and Juvik, 1983; Turland et al., 1993; Williamson, 1996; Sakai et al., 2001; Scott et al., 20”
Predicting species distributions: a critical comparison of the most common statistical models using artificial species (2007, methodology): “Other simulation studies have been applied to these questions (Hirzel & Guisan, 2002; Dark, 2004; Reese et al., 2005; Wintle & Bardos, 2006) and could guide our empirical studies in a more systematic fashion.”
Bird species richness patterns of northern Taiwan: primary productivity, human population density, and habitat heterogeneity (2006, background): “Several recent studies have demonstrated the importance of using statistical techniques that account for spatial autocorrelation on some level when assessing species distributions (Lichstein et al ., 2002; Dark, 2004; Tognelli & Kelt, 2004).”
Spatial autocorrelation and the selection of simultaneous autoregressive models (2007, background): “…for decades in the statistical literature (Besag, 1974; Cliff & Ord, 1981), their application in ecology and species distribution research has been limited up to now (e.g. Jetz & Rahbek, 2002; Keitt et al. , 2002; Lichstein et al. , 2002; Dark, 2004; Tognelli & Kelt, 2004; Kissling et al. , 2007).”
Invasive alien plant species in China: regional distribution patterns (2005, background): “There is an ongoing debate over the relationship between species diversity and invasibility (Dark, 2004).”
Accounting for multi‐scale spatial autocorrelation improves performance of invasive species distribution modelling (iSDM) (2012, background): “Previous studies that considered SAC were thus limited to correlative or regression-based models (e.g. Dark, 2004; Bini et al., 2009).”
Methods to account for spatial autocorrelation in the analysis of species distributional data : a review (2007, methodology): “…models based on generalised least squares have been known in the statistical literature for decades (Besag 1974, Cliff and Ord 1981), their application in ecology has been very limited so far (Jetz and Rahbek 2002, Keitt et al. 2002, Lichstein et al. 2002, Dark 2004, Tognelli and Kelt 2004).”
The invasion paradox: reconciling pattern and process in species invasions. (2007, background): “…larger scale plant communities examined to date, whether continental (Planty-Tabacchi et al. 1996, Stohlgren et al. 1998, 1999, 2001, 2003, 2005, 2006a, Lonsdale 1999, Dark 2004, Davies et al. 2005, Seabloom et al. 2006) or island floras (Sax et al. 2002), exhibit highly significant positive NERRs.”
Tolerance to herbivory, and not resistance, may explain differential success of invasive, naturalized, and native North American temperate vines (2007, methodology): “…and naturalized species has been used recently for field and greenhouse surveys (Smith & Knapp, 2001; Grotkopp et al ., 2002; McDowell, 2002; Dark, 2004; Cappuccino & Arnason, 2006), few experimental studies with this approach have been carried out (but, see Burns, 2004; Muth & Pigliucci,…”
Towards an integrated computational tool for spatial analysis in macroecology and biogeography (2006, methodology): “The GLS framework also allows the direct computation of other forms of spatial regressions that have been used recently in ecology and macroecology (e.g. Lichstein et al., 2002; Dark, 2004; Tognelli & Kelt, 2004), such as Simultaneous and Conditional Autoregression Models (SAR and CAR, respectively)”