Predicting species distributions: use of climatic parameters in BIOCLIM and its impact on predictions of species’ current and future distributions

By Linda Beaumont, Lesley Hughes, Michael Poulsen. 2005

567 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/1556421c4fc6a2566870c465bddb5b4775e52fd5

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In Ecological Modeling

In Ecology, Evolution, Behavior and Systematics

In Nature and Landscape Conservation

Citations in the corpus

Using presence‐only modelling to predict Asian elephant habitat use in a tropical forest landscape: implications for conservation (2010, methodology): “Other methods using presence-only data, such as Maxent (Phillips et al., 2006), garp (Stockwell & Peters, 1999), bioclim (Beaumont et al., 2005) and Mahalonobis factor analysis (Calenge et al., 2008), have recently become increasingly popular tools to model species habitat relations.”
Using species distribution models in paleobiogeography: A matter of data, predictors and concepts (2011, background): “A key factor here is to select the minimum number of predictors possible, since the more variables are included in the model, the narrower its predictions will be (Beaumont et al., 2005; Bulluck et al., 2006; Soberón, 2010).”
Modelling the potential geographic distribution of invasive ant species in New Zealand (2007, methodology): “BIOCLIM is an established method and has been widely used for species distribution modelling (Téllez-Valdés and Dávila-Aranda 2003; Meynecke 2004; Beaumont et al. 2005), DOMAIN has not been widely used (Loiselle et al. 2003), and MAXENT has only recently been applied to modelling species…”
Global warming will affect the genetic diversity and uniqueness of Lycaena helle populations (2011, methodology): “Based on these, we used DIVA-GIS 5.4 to compute 19 so-called bioclim variables (Busby, 1991), which are better suited for species distribution modelling than monthly values (Busby, 1991; Beaumont et al., 2005).”
The ability of climate envelope models to predict the effect of climate change on species distributions (2006, methodology): “The extent to which the number of variables influences the results should be related to how correlated they are, and perhaps that explains the differences between our results and those of Beaumont et al. (2005) .”
On the brink of extinction? How climate change may affect global chelonian species richness and distribution (2012, background): “Bioclimatic variables have been shown to perform superior to monthly temperature and precipitation variables in SDM approaches, wherein a total of 19 bioclimatic variables were proposed to sufficiently describe the climatic conditions at a given site (Busby, 1991; Beaumont et al., 2005).”
Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS) (2006, background): “... potential of invading species (Peterson & Robins 2003; Rouget et al . 2004; Thuiller et al . 2005b), identify and manage threatened species (Engler, Guisan & Rechsteiner 2004; Norris 2004), prioritize places for biodiversity conservation (Araujo et al . 2004; Ortega-Huerta & Peterson 2004; Sanch”
Where will species go? Incorporating new advances in climate modelling into projections of species distributions (2007, methodology): “Conversely, the correlative model BIOCLIM continually projects smaller potential distributions with the inclusion of more variables (e.g. Beaumont et al., 2005).”
Predicting the Potential Worldwide Distribution of the Red Palm Weevil Rhynchophorus ferrugineus (Olivier) (Coleoptera: Curculionidae) using Ecological Niche Modeling (2012, methodology): “…Florida Entomologist 95(3) September 2012 literature for only a few locations, we generated coordinates via reference to the directory of world named places in the Global Gazetteer version 2.2 (http://www.fallingrain.com/world; see summary of known occurrences in Fig.”
Ongoing invasions of the African clawed frog, Xenopus laevis: a global review (2012, methodology): “Bioclimatic data (Beaumont et al. 2005; Busby 1991) with a spatial resolution of 2.5 arcmin was obtained from the Worldclim database (Hijmans et al. 2005).”
Species distribution models that do not incorporate global data misrepresent potential distributions: a case study using Iberian diving beetles (2011, methodology): “Because distributional simulations obtained by MDE procedures are highly dependent on the number of selected predictors (Beaumont et al., 2005), we estimated the minimum set of climatic variables needed to explain the occurrence of each species using ecological-niche factor analysis (ENFA; Hirzel…”
Climate change effects on fishes and fisheries: towards a cause-and-effect understanding. (2010, background): “‘Bioclimatic envelope modelling’ represents a second approach which is more physiology-based, in that it makes projections based upon changes in environmental conditions correlated with the survival (or current distribution) and productivity of individual species (Beaumont et al., 2005).”
Predicting the past distribution of species climatic niches. (2009, background): “Progressive addition of climatic variables causes a gradual narrowing of the distributions of the climatic niches ( Beaumont et al., 2005 ).”
Potential Impacts of Climate Change on the Distribution of North American Trees (2007, background): “In choosing a set of climate variables, one looks for the smallest set that defines important climatic constraints on tree survival and growth—larger sets can unnecessarily constrain potential ranges with superfluous climatic requirements (Box 1981, Beaumont et al. 2005).”