Assessing habitat selection using multivariate statistics: Some refinements of the ecological-niche factor analysis

By M. Basille, Clément Calenge, É. Marboutin, R. Andersen, J. Gaillard. 2008

192 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/2627282032a667063ef007e908a792f053423131

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecological Modeling

1. Jorge M. Lobo
2. A. Jiménez‐Valverde
3. Joaquín Hortal
4. A. Townsend Peterson
5. Jorge Soberón
6. Jane Elith
7. Miguel B. Araújo
8. Sara Varela

In Ecology, Evolution, Behavior and Systematics

1. A. Jiménez‐Valverde
2. Jorge M. Lobo
3. A. Townsend Peterson
4. Joaquín Hortal
5. Jorge Soberón
6. Sara Varela
7. J. Overton
8. P. Aragón

In Nature and Landscape Conservation

1. Jorge M. Lobo
2. A. Jiménez‐Valverde
3. Joaquín Hortal
4. Jorge Soberón
5. A. Townsend Peterson
6. Sara Varela
7. Miguel B. Araújo
8. Antoine Guisan

Citations in the corpus

• Use of niche models in invasive species risk assessments (2011, methodology): “A promising exploratory procedure to identify major environmental requirements of species consists of using Ecological-Niche Factor Analysis or analogous procedures (ENFA; see Hirzel et al. 2002; Basille et al. 2008; Calenge and Basille 2008; Calenge et al. 2008).”
• The uncertain nature of absences and their importance in species distribution modelling (2010, background): “The Ecological-Niche Factor Analysis (ENFA) provides a mean of making such exploration, since it allows identifying the major environmental requirements of a species (Hirzel et al. 2002, Basille et al. 2008, Calenge and Basille 2008, Calenge et al. 2008).”
• Using species distribution models in paleobiogeography: A matter of data, predictors and concepts (2011, methodology): “In the absence of such information, several statistical techniques can be used to select the most appropriate set of explanatory variables for SDMs, based on either presence (Calenge et al., 2005; Basille et al., 2008) or presence/absence data (Murtaugh, 2009).”
• Habitat suitability, corridors and dispersal barriers for large carnivores in Poland (2010, methodology): “The values given by the ENFA marginality factors indicate habitat preferences and avoidances of wolf and lynx that correspond well to findings by other studies (as far as the variables are comparable), even those using different methodology (Zimmerman 2004, Basille et al. 2008, Jedrzejewski et al.”
• Brown bear habitat suitability in the Pyrenees: transferability across sites and linking scales to make the most of scarce data (2012, methodology): “We used two complementary hindcasting methods to describe the Pyrenean population’s ecological niche: the Mahalanobis distance factor analysis (MADIFA, Calenge et al. 2008) and the ecological niche factor analysis (ENFA, Hirzel et al. 2002; Basille et al. 2008).”