Climate change threats to plant diversity in Europe


Climate change threats to plant diversity in Europe

Wilfried Thuiller,*§ Sandra Lavorel,* Miguel B. Araújo,* Martin T. Sykes,** and I. Colin Prentice††
*Centre d'Ecologie Fonctionnelle et Evolutive, Centre National de la Recherche Scientifique-Unité Mixte de Recherche 5175, 1919 Route de Mende, 34293 Montpellier Cedex 5, France; Climate Change Research Group, Kirstenbosch Research Center, National Botanical Institute, P/Bag x7, Claremont 7735, Cape Town, South Africa; Macroecology and Conservation Unit, University of Évora, Estrada dos Leões, 7000-730 Évora, Portugal; Laboratoire d'Ecologie Alpine, Centre National de la Recherche Scientifique-Unité Mixte de Recherche 5553, Université J. Fournier, B.P. 53X, 38041 Grenoble Cedex 9, France; Biodiversity Research Group, School of Geography and the Environment, Oxford University, Mansfield Road, Oxford OX1 3TB, United Kingdom; **Geobiosphere Science Centre, Department of Physical Geography and Ecosystems Analysis, Lund University, Sölvegatan 12, 223 62 Lund, Sweden; and ††QUEST, Department of Earth Sciences, University of Bristol, Wills Memorial Building, Queen's Road, Bristol BS8 1RJ, United Kingdom
§ To whom correspondence should be addressed. E-mail: [email protected].
Edited by Harold A. Mooney, Stanford University, Stanford, CA
Received December 31, 2004; Accepted April 26, 2005.

Freely available online through the PNAS open access option. Proc Natl Acad Sci U S A. 2005 June 7; 102(23): 8245–8250.


Climate change has already triggered species distribution shifts in many parts of the world. Increasing impacts are expected for the future, yet few studies have aimed for a general understanding of the regional basis for species vulnerability. We projected late 21st century distributions for 1,350 European plants species under seven climate change scenarios. Application of the International Union for Conservation of Nature and Natural Resources Red List criteria to our projections shows that many European plant species could become severely threatened. More than half of the species we studied could be vulnerable or threatened by 2080. Expected species loss and turnover per pixel proved to be highly variable across scenarios (27-42% and 45-63% respectively, averaged over Europe) and across regions (2.5-86% and 17-86%, averaged over scenarios). Modeled species loss and turnover were found to depend strongly on the degree of change in just two climate variables describing temperature and moisture conditions. Despite the coarse scale of the analysis, species from mountains could be seen to be disproportionably sensitive to climate change (≈60% species loss). The boreal region was projected to lose few species, although gaining many others from immigration. The greatest changes are expected in the transition between the Mediterranean and Euro-Siberian regions. We found that risks of extinction for European plants may be large, even in moderate scenarios of climate change and despite inter-model variability.

Keywords: Intergovernmental Panel on Climate Change storylines, species extinction, species turnover, niche-based model



Recent rapid climate change is already affecting a wide variety of organisms (1, 2). Long-term data indicate that the anomalous climate of the past half-century is already affecting the physiology, distribution, and phenology of some species in ways that are consistent with theoretical predictions (3). Although natural climate variation and nonclimatic factors such as land transformation may well be responsible for some of these trends, human-induced climate and atmospheric change are the most parsimonious explanation for many (3, 4).

Several studies have modeled future species distributions at regional (5-8) and local scales (9, 10) and have extrapolated alarming extinction risks for the next century (11). However, few studies have considered the consequences of multiple climate-change scenarios (7, 8), which represent the outcome of different assumptions about the future (12). Using four representative scenarios and three different climate models (HadCM3, CGCM2, and CSIRO2), and a range of niche-based modeling techniques implemented in biomod (13), we develop predictions of the potential consequences for 1,350 plant species in Europe. The “future climate” we contrast with today's climate (averaged from 1961 to 1990) is the projected mean for the period from 2051 to 2080.

The “bioclimatic envelope” describes the conditions under which populations of a species persist in the presence of other biota as well as climatic constraints (6, 14). Future distributions are projected on the assumption that current envelopes reflect species' environmental preferences, which will be retained under climate change. This principle has strong support from studies demonstrating the evolutionary conservatism of ecological niches and the phylogenetic inertia of species across time scales (15, 16) and comparative biogeographical studies (17, 18). However, this approach also assumes instantaneous species-range change, it ignores physiological CO2 responses, and it does not capture details of population dynamics or biotic interactions nor the lags in spatial range shifts associated with processes of dispersal, establishment, and local extinction. To assess the sensitivity of projections to the most critical of these assumptions, we considered two contrasting assumptions about migration ability (7, 8, 11): either species are unable to disperse at all on the time scale considered (no migration), or they have no constraints to dispersal and establishment (universal migration). The reality for most species is likely to fall between these extremes, depending on their ability to migrate across fragmented landscapes (19). We calculated losses of climatically suitable areas (“species loss”) assuming no migration and gains (“species gain”) and turnover (“species turnover”) assuming universal migration.



Data Sources. Species' distribution data are available for 2,294 plants (20), comprising ≈20% of the total European flora, sampled between 1972 and 1996. Modeling was conducted by using available data for Europe on a 50 × 50 km grid. The mapped area comprises western, northern and southern Europe, but excludes most of the eastern European countries where recording effort was both less uniform and less intensive (21). After removing species with <20 records, we considered range responses of 1,350 plant species of Europe. We assume this sample can be taken as representative of the responses of European plant species to climate change because it includes most of the life forms and phytogeographic patterns found among plant species in Europe.

Climate data were obtained from the Climatic Research Unit ( and included mean annual, winter, and summer precipitation, mean annual temperature and minimum temperature of the coldest month (MTC), growing degree days (>5°) and an index of moisture availability (22). These variables were chosen because of their strong link with the physiology and growth of plant species (23, 24). For instance, MTC discriminates species based on their ability to assimilate soil water and nutrients, and continue cell division, differentiation and tissue growth at low temperatures (lower limit), and chilling requirements for processes such as bud break and seed germination (upper limit). The moisture index discriminates species through processes related to phenology, rooting strategy, leaf morphology, and xylem vulnerability to cavitation. However, because there is surprisingly little experimental work for any particular species to guide the choice of bioclimatically limiting variables, the variables are generic and represent a hypothetical minimum basic set for niche-based modeling. Climate data were averaged for the 1961-1990 period. The data were supplied on a 10-foot (1 ft = 0.3 m) grid covering Europe. They were aggregated by averaging to 50 × 50 km Universal Transverse Mercator (UTM) to match the species data grid. Niche-based models were calibrated on the 50 × 50 km UTM grid, and modeled species distributions were projected back onto the 10′ grid for current and future climate.

Future projections were derived by using climate model outputs made available through the Intergovernmental Panel on Climate Change (IPCC) Data Distribution Centre (‡‡ The modeled climate anomalies were scaled based on four scenarios proposed by the IPCC (12). The A1 scenario describes a globalized world with rapid economic growth and global population that peaks in mid-century and declines thereafter and assumes rapid introduction of new and more efficient technologies. Concentrations of CO2 increase from 380 ppm in 2000 to 800 ppm in 2080, and temperature rises by 3.6 K (12). The A2 scenario describes a heterogeneous world with regionally oriented economic development. Per capita economic growth and technological change are slower than in the other scenarios. Global concentrations of CO2 increase from 380 ppm in 2000 to 700 ppm in 2080, and temperature rises by 2.8 K. The B1 scenario describes a convergent world with global population that peaks in mid-century and declines thereafter, as in A1, but with a rapid change toward a service and information economy and the introduction of clean and resource-efficient technology. Concentrations of CO2 increase from 380 ppm in 2000 to 520 ppm in 2080, and temperature rises by 1.8 K. The B2 scenario describes a world in which the emphasis is on local solutions to socioeconomic and environmental sustainability. It is a world with continuously increasing global population (at a rate lower than A2), intermediate levels of economic development, and less rapid and more diverse technological change than in the B1 and A1 scenarios. Concentrations of CO2 increase from 380 ppm in 2000 to 550 ppm in 2080, and temperature rises by 2.1 K (12).

We did not assess the impacts of land-use change, even though this factor will potentially compound the effects of climate change on species distributions (25). However, given the spatial extent and resolution of our data and the magnitude of climate change in most projections, the effect of land use would be most likely overridden by climate (26, 27).

Niche-Based Models of Species Climatic Envelops. We used the biomod framework, which capitalizes on several widely used niche-based modeling techniques (generalized linear models, generalized additive models, classification tree analysis, and artificial neural networks) to provide alternative spatial projections (13). For each climate change scenario, models relating species distributions to the seven bioclimatic variables were fitted by using biomod and projected into the future. Then, a consensus principal component analysis was run to explore central tendencies in projections and select the niche-based model representing the greatest commonality among projections (8).

There is increasing evidence that model projections can be extremely variable, and there remains a need to test the accuracy of models and to reduce uncertainties (8, 28, 29). One recent analysis has however provided the first test of the predictive accuracy of such models by using bird observed species' range shifts and climate change in two periods of the recent past (30). This work provides validation of niche-based models under climate change and demonstrated how uncertainty can be reduced by selecting the most consensual projections, as done in this study. We are therefore confident that this strategy provides a robust and defensible approach to species range projections for the purposes of conservation planning and biodiversity management.

To evaluate species extinction risks, we summed the number of pixels lost, potentially gained (under universal migration), or stable by each species for the different climate-change scenarios. We assigned each species to an International Union for Conservation of Nature and Natural Resources (IUCN) threat category (IUCN 2001). Those that were not listed were classified as lower risk, depending on the projected reduction in range size from present to 2080. Present and future range sizes (area of occupancy) were estimated from the number of pixels where species occurred. Loss in range size was calculated by subtracting future potential range size from present potential range size. In line with IUCN Red List criterion A3(c), the following thresholds were then used to assign a species to a threat category (IUCN 2001). Extinct is a species with a projected range loss of 100% in 50 or 80 years, critically endangered has a projected range loss of >80%, endangered has a projected range loss of >50%, and vulnerable has a projected range loss of >30%. Although this Red Listing approach is simplistic and considers only the effects of climate change, it provides a synthetic overview of species-specific threats due to climate change.

To evaluate the percentage of extinctions for a given area, we summed the number of species lost (L) by pixel and related it to current species richness by pixel. The procedure was the same to assess the percentage of species gained (G) by pixel (under assumptions that species could reach a new suitable climate space). Percentage of species turnover by pixel, under the assumption of universal migration, is then given by T = 100 × (L + G)/(SR + G) where SR is the current species richness.

Results and Discussion

Many European species could be threatened by future climate change (Fig. 1). Under the assumption of no migration, more than half of the species we considered become vulnerable or committed to extinction by 2080. The impacts of climate change are, naturally, less under the universal migration because of the possibility for species to move across landscapes. Under the no-migration assumption and the most severe climate change scenario (A1-HadCM3), 22% of the species become critically endangered (>80% range loss), and 2% extinct by 2080. These numbers decrease for the other scenarios and climate models. Under the universal migration assumption, the results are, as expected, less severe. Under tA1-HadCM3, 67% of species would be classified as low risk, whereas under B1-HadCM3, 76% of the species would be at low risk.

Our results coincide with the direction of predictions made by Thomas et al. (11), although the magnitude of the risks we project is less [and note that we project distributions to 2080, whereas Thomas et al. (11) only projected to 2050].

Niche-based modeling does not address the proximate causes of species extinction. Nevertheless, any reduction in the potential geographic range of a species is likely to lead to an increased risk of local extinction (11). This conclusion is, in fact, the rationale for building IUCN Red Lists (31). A decrease in range size implies that smaller stochastic events affect a larger proportion of the species' total population, especially in fragmented landscapes. If a species becomes restricted to a few sites, then local catastrophic events (such as droughts or disease outbreaks) or an increase of land transformation by humans could easily cause the extinction of that species (32).

Rates of species' loss and turnover show great variation across scenarios (Fig. 2). In A1-HadCM3, the mean European temperature increases by up to 4.4 K, leading to a mean species loss of 42% and turnover of 63%. This scenario provides the widest range of variability across Europe for both species loss (2.5-86%) and turnover (22-90%). The percentage of