Climate change threatens European conservation areas
By Miguel B. Araújo, Diogo Alagador, M. Cabeza, D. Nogués-Bravo, Wilfried Thuiller. Ecology Letters, 2011
889 citations recorded by the source corpus.
Europe has the world's most extensive network of conservation areas. Conservation areas are selected without taking into account the effects of climate change. How effectively would such areas conserve biodiversity under climate change? We assess the effectiveness of protected areas and the Natura 2000 network in conserving a large proportion of European plant and terrestrial vertebrate species under climate change. We found that by 2080, 58 ± 2.6% of the species would lose suitable climate in protected areas, whereas losses affected 63 ± 2.1% of the species of European concern occurring in Natura 2000 areas. Protected areas are expected to retain climatic suitability for species better than unprotected areas (P<0.001), but Natura 2000 areas retain climate suitability for species no better and sometimes less effectively than unprotected areas. The risk is high that ongoing efforts to conserve Europe's biodiversity are jeopardized by climate change. New policies are required to avert this risk.
Subfields: Ecological Modeling, Ecology, Nature and Landscape Conservation
View Paper: https://www.semanticscholar.org/paper/fb81cec28006a3a9a36a546b18bb8e403ffe877e
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
- Miguel B. Araújo
- Wilfried Thuiller
- A. Townsend Peterson
- Antoine Guisan
- Jorge M. Lobo
- Catherine H. Graham
- Jane Elith
- Jens‐Christian Svenning
In Ecology
- Miguel B. Araújo
- Wilfried Thuiller
- A. Townsend Peterson
- Antoine Guisan
- Jorge M. Lobo
- Catherine H. Graham
- Jane Elith
- Jorge Soberón
In Nature and Landscape Conservation
- Miguel B. Araújo
- Wilfried Thuiller
- Antoine Guisan
- A. Townsend Peterson
- Catherine H. Graham
- Jorge M. Lobo
- Jens‐Christian Svenning
- Jane Elith
Citations in the corpus
- Invasive weed species’ threats to global biodiversity: Future scenarios of changes in the number of invasive species in a changing climate (2020, methodology): “The use of MaxEnt as a SDM, together with GIS, provides a powerful method for estimating distributions of species (Araújo et al., 2011; Mainali et al., 2015) and guides IWS risk control strategies under climate change (Thalmann et al.”
- The performance of protected areas for biodiversity under climate change (2015, background): “…studies have shown that species are likely to move out of individual reserves with continuing climate change, potentially requiring additional reserves to achieve a given level of conservation success in future (Araújo et al., 2004; 2011; Hannah et al., 2007; Leach, Zalat & Gilbert, 2013).”
- Species in a dynamic world: Consequences of habitat network dynamics on conservation planning (2012, background): “Second, due to climate change, many species are expected to lose suitable climate area, even inside protected areas (e.g. Araújo et al., 2011), and several calls for spatially adapting conservation networks to buffer the effects of climate change have been made (e.g. Hannah et al., 2007; Heller and…”
- Ongoing global biodiversity loss and the need to move beyond protected areas: a review of the technical and practical shortcomings of protected areas on land and sea (2011, background): “Existing statistics suggest, for instance, that for Europe alone, between 58 and 63% of species of plants and terrestrial vertebrates could lose suitable climate inside PAs by 2080, given conservative scenarios of climate change (Araujo et al. 2011).”
- A framework for incorporating evolutionary genomics into biodiversity conservation and management (2015, neutral): “Species distribution models, often also referred to as ecological niche models or bioclimatic envelope models, and methods of modelling community-level turnover such as generalised dissimilarity modelling are currently the main tools used to obtain spatially explicit predictions of habitat (environm”