QUANTILE REGRESSION REVEALS HIDDEN BIAS AND UNCERTAINTY IN HABITAT MODELS

By Brian S. Cade, B. Noon, C. Flather. 2005

165 citations recorded by the source corpus.

Subfields: Ecology, Economics and Econometrics, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/050537559c3f71e88d807c3ce5412dda2901eeeb

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Citations in the corpus

Can species distribution modelling provide estimates of population densities? A case study with jaguars in the Neotropics (2012, methodology): “Parameters and confidence interval estimates of quantile regression were fitted using weighted least square regression according to Cade et al. (2005) and Koenker & Machado (1999).”
Animal-sediment relationships re-visited: Characterising species' distributions along an environmental gradient using canonical analysis and quantile regression splines (2008, methodology): “Quantile regression (Koenker and Bassett, 1978; Cade and Noon, 2003; Koenker, 2005) is an effective tool that can be used to ameliorate the heterogeneity caused by such unmeasured factors (Cade et al., 2005).”
Species Distribution Models: Ecological Explanation and Prediction Across Space and Time (2009, unknown): “They can reveal biases or missing predictors, and arguably can indicate the potential rather than the actual distribution (Cade et al. 2005).”
Modelling species distributions using regression quantiles (2007, methodology): “In contrast to Cade et al. (2005) who successfully used dAICc to select appropriate variables for models at the same quantile, we computed AIC post hoc to compare our final models with alternative ones at the same quantile.”
Remotely sensed spectral heterogeneity as a proxy of species diversity: Recent advances and open challenges (2010, background): “…(Luoto et al., 2005; Heikkinen et al., 2006; Hortal, 2008), ecological gradient mapping (Foody, 1996; Fisher, 2000), habitat resource modeling (Cade et al., 2005), environmental management decision making (Fuller et al., 2008), and species–area relationships (Guilhaumon et al., 2008; Dengler,…”