Do we need land‐cover data to model species distributions in Europe?

By Wilfried Thuiller, Miguel B. Araújo, S. Lavorel. 2004

452 citations recorded by the source corpus.

Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/ceab695d19b449c2d32fc97b48912b6a73346ff8

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Citations in the corpus

On the brink of extinction? How climate change may affect global chelonian species richness and distribution (2012, result): “These patterns are also in concordance with previous findings, suggesting that cold range margins of most species are primarily limited through physiological tolerance limits, rather than biological interactions (reviewed in Gaston, 2003), especially on continental scales (Thuiller et al., 2004).”
Using niche‐based modelling to assess the impact of climate change on tree functional diversity in Europe (2006, background): “However, at the spatial extent and resolution considered in this study, land use has been found to be largely overridden by climate (Thuiller et al ., 2004a) and should not affect the power of our analysis.”
sdm: a reproducible and extensible R platform for species distribution modelling (2016, background): “…(Segurado and Araújo 2004, Elith et al. 2006), and when used for transferring the distributions of species into different geographical (Randin et al. 2006) or temporal contexts (Thuiller et al. 2004, Araújo et al. 2005b, Pearson et al. 2006) projections can vary startlingly among techniques.”
Accounting for uncertainty when mapping species distributions: The need for maps of ignorance (2011, methodology): “Those created from climatic models and/or geographical interpolations present a certain degree of error depending on the accuracy of these models (see, for example, Luoto et al., 2005; Thuiller et al., 2004; Figure 1).”
Soil nutritional factors improve models of plant species distribution: an illustration with Acer campestre (L.) in France (2006, background): “Indeed, with the development of geographical information systems (GIS), access to climatic data layers interpolated from meteorological station measurements is facilitated (McKenzie & Halpern, 1999; McKenzie et al., 2003a,b; Thuiller et al., 2003b, 2004).”
Accuracy of resource selection functions across spatial scales (2006, methodology): “The geographical-grain RSFs were GAMs (Thuiller et al ., 2004).”
Distribution patterns of boreal marshland birds: modelling the relationships to land cover and climate (2005, methodology): “However, the grid cell resolution was 50 · 50 km, and inside each grid cell habitat heterogeneity is probably a crucial factor predicting species occurrences (Thuiller et al., 2004).”
Forecasting fish distribution along stream networks: brown trout (Salmo trutta) in Europe (2013, background): “Importantly, land cover variables did not substantially improve the predictive accuracy of SDMs, as in analogous studies where climate also prevailed as the main predictor of current species distributions (Lavorel et al., 2004).”