The fourth‐corner solution – using predictive models to understand how species traits interact with the environment

By Alexandra M. Brown, David I. Warton, N. Andrew, Matthew R. Binns, Gerasimos Cassis, H. Gibb. 2014

285 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/5ce976723e8496fcbbce1fb6a1e0b12f392da534

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In Ecological Modeling

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In Nature and Landscape Conservation

Citations in the corpus

Quantifying variable importance in a multimodel inference framework (2016, background): “2014), elucidating linkages between environment and functional traits of species (Brown et al. 2014), and understanding correlates of infectious diseases (Miller et al.”
Handbook of protocols for standardized measurement of terrestrial invertebrate functional traits (2017, unknown): “…Speight & Castella (2010) for hoverflies, Bertelsmeier et al. (2013) for ants (see also Yates et al. 2014), Homburg et al. (2014) for carabid beetles, and Pey, Laporte & Hedde (2014) for soil invertebrates), as well as new statistical developments (e.g. Brown et al. 2014) have been published.”
Functional traits and community composition: A comparison among community‐weighted means, weighted correlations, and multilevel models (2018, methodology): “The resampling procedure used in MLM2(glm) was designed to account for nonindependence among species in residual errors (Brown et al., 2014), although it is less successful when the number of species exceeds the number of sites (Warton et al., 2017).”
A comprehensive evaluation of predictive performance of 33 species distribution models at species and community levels (2019, background): “2006) as well as improve predictive performance (Brown et al. 2014).”
How to make more out of community data? A conceptual framework and its implementation as models and software. (2017, background): “2016b), to relate such patterns to species traits and phylogenies (Pollock et al. 2012; Brown et al. 2014; Abrego et al. 2017a) and to quantify co-occurrence patterns among species (Pollock et al.”
So Many Variables: Joint Modeling in Community Ecology. (2015, methodology): “corner model’ [24,64], predicting abundance as a function of environmental variables and functional traits, b3 being the coefficient characterizing this interaction.”
GlobalAnts: a new database on the geography of ant traits (Hymenoptera: Formicidae) (2017, unknown): “The availability of both species traits and abundance data also allows us to use exciting new analytical techniques that link traits with the environment through the abundances of species; the new predictive fourth corner analysis is one example (Brown et al., 2014; Gibb et al., 2015a).”