How much do we overestimate future local extinction rates when restricting the range of occurrence data in climate suitability models
By Morgane Barbet-Massin, Wilfried Thuiller, Frédéric Jiguet. 2010
181 citations recorded by the source corpus.
Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation
View Paper: https://www.semanticscholar.org/paper/138e0385a106457432e882272146bc3a887489b4
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
- Wilfried Thuiller
- Miguel B. Araújo
- Antoine Guisan
- A. Townsend Peterson
- Jorge M. Lobo
- Jane Elith
- N. E. Zimmermann
- Carsten F. Dormann
In Ecology
- Wilfried Thuiller
- Miguel B. Araújo
- Antoine Guisan
- A. Townsend Peterson
- Jorge M. Lobo
- Jane Elith
- R. P. Anderson
- N. E. Zimmermann
In Nature and Landscape Conservation
- Wilfried Thuiller
- Antoine Guisan
- Miguel B. Araújo
- Jorge M. Lobo
- Jane Elith
- A. Townsend Peterson
- Carsten F. Dormann
- N. E. Zimmermann
Citations in the corpus
- Shifts in plant distributions in response to climate warming in a biodiversity hotspot, the Hengduan Mountains (2018, methodology): “In addition to the Hengduan Mountains, the other regions where the selected species currently occur (extending from 18° to 55°N, and 60° to 130°E, Appendix S1, Figure S1) were also included in the final modelling analyses (Barbet-Massin & Jiguet, 2010).”
- Integrating ensemble species distribution modelling and statistical phylogeography to inform projections of climate change impacts on species distributions (2013, background): “Especially in mountainous regions, coarse SDMs are likely to underestimate the potential for suitable habitat under future climate change (Randin et al., 2009; Barbet-Massin et al., 2010).”
- Predicting species distribution at range margins: testing the effects of study area extent, resolution and threshold selection in the Sahara–Sahel transition zone (2014, background): “To reduce both sources of uncertainty, many ideas have emerged (for instance, Thuiller et al., 2004; Grenouillet et al., 2011) such as ENMs should use data at least from a complete biogeographical area (Barbet-Massin et al., 2010).”
- Standards for distribution models in biodiversity assessments (2019, background): “4 of 11 Critical questions include: whether the distributional data available for the species have been comprehensively sampled (40) while being representative of the regions and the environments in which the species lives (41) or can live (42), whether the spatial accuracy of the distributional occ”
- The fate of European breeding birds under climate, land‐use and dispersal scenarios (2012, background): “Here, we aim at addressing these two main issues (species dispersal and land-use change) by predicting the future distributions of 409 European bird species for 2050, using range data from the entire western Palaearctic zone to account for the full realized niche of each species within a large bioge”
- Potential Impacts of Climate Change on Ecosystem Services in Europe: The Case of Pest Control by Vertebrates (2012, background): “…there is the possibility that some southern European species are able to tolerate conditions that are more arid than those recorded in Europe and that some North African species will migrate northward, thus colonizing southern European ecosystems ( Barbet-Massin et al. 2010, Maiorano et al. 2011).”
- A 40‐year, continent‐wide, multispecies assessment of relevant climate predictors for species distribution modelling (2014, background): “…closer to non-independence would be to use spatial filters or striped or checkerboard designs (Munson et al., 2010), but this would in turn very likely lead to a truncated estimation of the climatic niche and therefore an underestimation of the projected distribution (Barbet-Massin et al., 2010).”