Ensemble modelling of species distribution: the effects of geographical and environmental ranges

By G. Grenouillet, L. Buisson, Nicolas Casajus, Sovan Lek. 2011

401 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/ee10a95b812f554fe244ae0e7a617c516c178c90

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. Miguel B. Araújo
2. C. Rahbek
3. G. Grenouillet
4. M. Cabeza
5. R. A. Garcia
6. Francis Gilbert
7. César Capinha
8. Victoria Nolan

In Ecology

1. Miguel B. Araújo
2. C. Rahbek
3. M. Cabeza
4. César Capinha
5. P. Anastácio
6. G. Grenouillet
7. R. A. Garcia
8. Francis Gilbert

In Nature and Landscape Conservation

1. C. Rahbek
2. Miguel B. Araújo
3. G. Grenouillet
4. M. Cabeza
5. R. A. Garcia
6. Francis Gilbert
7. N. Burgess
8. Victoria Nolan

Citations in the corpus

• Assessing the environmental requirements of invaders using ensembles of distribution models (2011, background): “Ensemble and consensus approaches have been shown to be a useful framework for assessing the predictive uncertainty of NBM (Buisson et al., 2010; Grenouillet et al., 2010), and even improve predictive accuracy (Marmion et al.”
• Do stream fish track climate change? Assessing distribution shifts in recent decades (2013, methodology): “Although Gaussian functions have usually been applied, combinative algorithms are known to increase the accuracy of an ensemble of model outputs (Marmion et al. 2009, Grenouillet et al. 2011).”
• A comparison between Ensemble and MaxEnt species distribution modelling approaches for conservation: A case study with Egyptian medicinal plants (2020, background): “Ensemble modelling has been shown to improve model predictions (Grenouillet et al., 2011; Oppel et al., 2012; Stohlgren et al., 2010), reduce overfitting when modelling rare species (Breiner et al., 2016), and has been advocated as a better alternative to single models for future climate projection…”
• Exploring consensus in 21st century projections of climatically suitable areas for African vertebrates (2011, background): “The proportion of variance explained by the first principal component axis provided a measure of consensus among projections (Thuiller, 2004; Arau´jo et al. , 2006; Grenouillet et al. , 2011).”
• PCA – A Powerful Method for Analyze Ecological Niches (2012, background): “…variation (e.g., Kelt et al., 1999; Johnson et al., 2006; Rissler & Apodaca 2007; Glor & Warren 2010; Novak et al., 2010a; Faucon et al., 2011; Grenouillet et al., 2011), the investigated species or community characteristics (e.g., Kingston et al., 2000; Pearman 2002; Youlatos 2004; Kitahara…”
• An overview of methods to evaluate uncertainty of deterministic models in decision support (2015, neutral): “Ensemblemodelling has mainly been used in twoways: to produce one “best” predictive model (e.g. Kronvang et al., 2009; Grenouillet et al., 2011; Trolle et al., 2014), and to evaluate the predictive uncertainty (e.g. Georgakakos et al., 2004; Gal et al., 2014).”