A 40‐year, continent‐wide, multispecies assessment of relevant climate predictors for species distribution modelling

By Morgane Barbet-Massin, Walter Jetz. 2014

129 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/e821452e6c35bdd69a09991fab0c463e2e023622

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. O. Broennimann
2. Antoine Guisan
3. B. Petitpierre
4. Christoph Kueffer
5. C. Daehler
6. Miguel B. Araújo
7. B. Leung
8. Johanna Bradie

In Ecology

1. O. Broennimann
2. B. Petitpierre
3. B. Leung
4. Johanna Bradie
5. J. Belmaker
6. R. A. Garcia
7. J. Pearce‐Higgins
8. C. Daehler

In Nature and Landscape Conservation

1. O. Broennimann
2. Antoine Guisan
3. B. Petitpierre
4. Christoph Kueffer
5. C. Daehler
6. B. Leung
7. Christopher M Thomas
8. Johanna Bradie

Citations in the corpus

• Empirical Evidence for the Scale Dependence of Biotic Interactions (2015, methodology): “We chose a suite of environmental variables to use as predictors that are relevant to the distributions of breeding birds in North America (Meehan et al., 2010; Rittenhouse et al., 2010; Matthews et al., 2011; Barbet-Massin & Jetz, 2014).”
• Selecting predictors to maximize the transferability of species distribution models: lessons from cross‐continental plant invasions (2017, background): “…doesn’t mean good elsewhere 360 In contrast to recent multi-species studies investigating the importance of variable selection for 361 SDMs (e.g. Barbet-Massin & Jetz, 2014; for birds or Ashcroft et al., 2011, for plants), our study 362 used a completely independent dataset (i.e. invaded…”
• Climate change vulnerability assessment of species (2018, background): “However, general biological knowledge accumulated for a variety of taxonomic groups and climate regions, assessments of bioclimatic variable performance (Barbet-Massin & Jetz, 2014) and previous published models provide a basis for an informed choice of bioclimatic variables for most species.”
• A quantitative synthesis of the importance of variables used in MaxEnt species distribution models (2017, methodology): “Historically, most analyses to examine variable importance have been done on a per species basis (Ara ujo & Guisan, 2006; but see Ashcroft et al., 2011; Barbet-Massin & Jetz, 2014), but here, we analyse the contributions of environmental variables for nearly 1900 species in 2040 MaxEnt models.”