2014
DOI: 10.1016/j.ecolmodel.2013.11.016
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Seeking the flowers for the bees: Integrating biotic interactions into niche models to assess the distribution of the exotic bee species Lithurgus huberi in South America

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Cited by 76 publications
(78 citation statements)
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“…Species distribution modeling (SDM) based on observed occurrences are good tools for predicting the potential distribution of exotic species including bees (e.g., Hinojosa-Díaz et al 2005, 2009, Gonzalez et al 2010, Silva et al 2014. Incorporating biotic interactions in these models, such as plant-bee relationships, is expected to have a major influence on the modeled distribution.…”
Section: Discussionmentioning
confidence: 99%
“…Species distribution modeling (SDM) based on observed occurrences are good tools for predicting the potential distribution of exotic species including bees (e.g., Hinojosa-Díaz et al 2005, 2009, Gonzalez et al 2010, Silva et al 2014. Incorporating biotic interactions in these models, such as plant-bee relationships, is expected to have a major influence on the modeled distribution.…”
Section: Discussionmentioning
confidence: 99%
“…We georeferenced the localities using the point-radius method (Wieczorek et al 2004). The methods we used were described elsewhere in previous studies (i.e., Silva et al 2014aSilva et al , b, 2015Martins et al 2015). Briefly, we applied a principal components analysis to the 19 variables from Worldclim to generate 19 orthogonal principal components (PCs hereon; Table S1, supplementary material), from which we considered the first 4 (∼90 % of the original climatic variation) to predict the distribution for C. merrillae .…”
Section: Potential Distribution Modelmentioning
confidence: 99%
“…Then, we used the first seven PCs in our modeling procedures for the predictions of D. brazili future distributions. The use of PCs (or any other collinearity reduction method) is advised to avoid model overfitting that may result in biologically unreliable species potential distributions (Jiménez-Valverde et al, 2011;Serra et al, 2012;Silva et al, 2014a).…”
Section: Environmental Data Principal Component Variables and Modelmentioning
confidence: 99%
“…By correlating the known records of a target species with their climatic data, SDM techniques allow projecting its Grinnellian niche (Peterson, 2001;Soberón, 2007) onto the geographic space, providing some support for practical conservation actions. These methods have been used to achieve a variety of objectives, such as: (i) to define the potential distribution of a given taxa, especially rare, threatened or invasive species (e.g., Martinelli and Moraes, 2013;Rödder et al, 2009;Silva et al, 2014a;Costa et al, 2015); (ii) to indicate suitable areas for future sampling (e.g. Marini et al, 2010); (iii) to test biogeographical and evolutionary hypotheses (Carnaval and Moritz, 2008;Stephens and Wiens, 2009;Porto et al, 2013;Silva et al, 2014b); (iv) to suggest the establishment of new conservation units (Diniz-Filho et al, 2004;Loyola et al, 2008;Nóbrega and De Marco Jr., 2011);and (v) to determine how species may respond to different climate change scenarios Sinervo et al, 2010).…”
Section: Introductionmentioning
confidence: 99%