Assessing Global Biome Exposure to Climate Change Through The

Global Ecology and Biogeography, (Global Ecol. Biogeogr.) (2013) ••, ••–••

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RESEARCH Assessing global biome exposure PAPER to climate change through the Holocene–Anthropocene transition

Marta Benito-Garzón1,2*, Paul W. Leadley3 and Juan F. Fernández-Manjarrés1,3

1CNRS, Laboratoire d’Ecologie, Systématique ABSTRACT et Evolution, Université Paris-Sud, CNRS, Aim To analyse global patterns of climate during the mid-Holocene and conduct UMR 8079, F-91405 Orsay Cedex, France, 2CNRS, Centre International de Recherche sur comparisons with pre-industrial and projected future climates. In particular, to l’Environnement et le Développement assess the exposure of terrestrial biomes and ecoregions to climate-related risks (CIRED), 94736, Nogent-sur-Marne Cedex, during the Holocene–Anthropocene transition starting at the pre-industrial France, 3Laboratoire d’Ecologie, Systématique period. et Evolution, Université Paris-Sud, CNRS, Location Terrestrial ecosystems of the Earth. UMR 8079, F-91405 Orsay Cedex, France Methods We calculated long-term climate differences (anomalies) between the mid-Holocene (6 ka cal bp, mH), pre-industrial conditions and projections for 2100 (middle-strength A1B scenario) using six global circulation models available for all periods. Climate differences were synthesized with multivariate statistics and average principal component loadings of temperature and precipitation differences (an estimate of climate-related risks) were calculated on 14 biomes and 766 ecoregions. Results Our results suggest that most of the Earth’s biomes will probably undergo changes beyond the mH recorded levels of community turnover and range shifts because the magnitude of climate anomalies expected in the future are greater than observed during the mH. A few biomes, like the remnants of North American and Euro-Asian prairies, may experience only slightly greater degrees of climate change in the future as compared with the mH. In addition to recent studies that have identiﬁed equatorial regions as the most sensitive to future climate change, we ﬁnd that boreal forest, tundra and vegetation of the Equatorial Andes could be at greatest risk, since these regions will be exposed to future climates that are well outside natural climate variation during the Holocene. Conclusions The Holocene–Anthropocene climate transition, even for a middle- strength future climate change scenario, appears to be of greater magnitude and different from that between the mH and the pre-industrial period. As a conse- quence, community- and biome-level changes due to of expected climate change *Correspondence: Marta Benito-Garzón, CNRS, may be different in the future from those observed during the mH. Laboratoire d’Ecologie, Systématique et Keywords Evolution, UMR 8079 Université Paris-Sud, CNRS, F-91405 Orsay Cedex, France. Anthropocene, biodiversity, biome refugia, climate change, global circulation E-mail: [email protected] models, mid-Holocene, no-analogue, resilience.

Anthropocene (Steffen et al., 2011; Vince, 2011). However, INTRODUCTION targets like the 2 °C global warming limit that has been the focus The cumulative human modiﬁcation of landscapes, ecosystems of recent UNFCCC (United Nations Framework Convention on and biomes since the settlement of people and the invention of Climate Change) negotiations may be insufﬁcient to maintain agriculture has pushed the Earth outside the conditions of the the Earth in a state that is reasonably close to that of the last relatively stable Holocene period into what has been termed the 10,000 years (Ellis et al., 2012). The tight links between climate

© 2013 John Wiley & Sons Ltd DOI: 10.1111/geb.12097 http://wileyonlinelibrary.com/journal/geb 1 M. Benito-Garzón et al. and species distributions have spawned a wealth of research that areas (Kaufman et al., 2004). During the mH, biomes responded aims to understand and predict the impacts of future climate to gradual warming with shifts in species ranges and community change on the biota of the Earth (Pereira et al., 2010; Beaumont reorganization, but signiﬁcant extinctions did not occur et al., 2011; Bellard et al., 2012; Ellis et al., 2012). Substantial (Colinvaux et al., 2000; Jackson & Overpeck, 2000; Davis et al., efforts are currently being devoted to understanding the differ- 2003; Bush et al., 2004; Thompson et al., 2006; Urrego et al., ences between the current or the pre-industrial climates and 2010; Willis, 2010). projections for the end of the 21st century (Williams et al., In addition to our analysis of the mH, we discuss other 2007), together with the probable consequences of climate periods of warming in the palaeoclimatic record to provide change for ﬂora and fauna (Pereira et al., 2010; Beaumont et al., perspectives on biological responses to climatic events that 2011; Bellard et al., 2012). Despite substantial inter-model appear to have been as fast or faster than projected future uncertainty (Rogelj et al., 2012), great emphasis has been placed climate change, such as subglobal events of rapid warming on detecting novel climates relative to current conditions that during the Bølling and Allerød oscillations (14–13 ka cal bp) and might pose substantial challenges for species and ecosystem at the end of the Younger Dryas that led into the Holocene adaptation (Williams et al., 2007; Beaumont et al., 2011). Simi- period (11.5 ka cal bp). We also discuss periods that were larly, several efforts have been undertaken to understand differ- warmer than the mH, such as the mid-Pliocene (3.6–2.6 Myr cal ences between the early 20th-century climate and the climates bp) and the Eemian Interglacial (130–116 ka cal bp) (Salzmann of the Quaternary period in general (Pickett et al., 2004; et al., 2009; Haywood et al., 2011; Willis & MacDonald, 2011). MacDonald et al., 2008a; Willis et al., 2010; Zhang et al., 2010). Recent work in palaeoclimate modelling has opened the pos- These climate reconstructions have been used to explain the sibility of using multimodel simulations of mH climate that responses of biota to climate variation in the past (Benito have been benchmarked with a wide variety of palaeoclimate Garzón et al., 2007; Terry et al., 2011; Willis & MacDonald, proxies (the PMIP project; Braconnot et al., 2007a,b). This 2011). Evidence that the biosphere may have been exposed to allowed us to analyse global patterns of climate during the mH warmer and colder climates in the past can provide insight into and to make coherent comparisons with pre-industrial and pro- how species, communities and biomes respond through extinc- jected future climates using the same suite of climate models. To tions, range shifts and community turnover under changing explore the Holocene–Anthropocene transition, we combined climate conditions (Jackson & Overpeck, 2000; Pickett et al., multimodel simulations of palaeo, modern and future climate to 2004; Willis & MacDonald, 2011). We have combined climate quantify the magnitude and direction of climate change analyses of anomalies of the mid-Holocene and future climate between the mH, pre-industrial conditions and projected change expectations in order to examine the extent to which climate for the end of the 21st century. We used multivariate biomes and ecoregions may be exposed to future climates that statistics (principal components analysis, PCA) of climate differ from cooler (pre-industrial) and warmer (mid-Holocene) anomalies that included maximum, mean and minimum annual periods that occurred naturally during the Holocene. By using temperature as well as annual precipitation. We then mapped variation in climate over the Holocene as a benchmark for eco- this indicator onto the world’s biomes and ecoregions to assess system sensitivity, our approach differs from recent studies that exposure of the terrestrial biosphere to climate-related risks. have calculated climate exposure or climate sensitivity of biomes and ecoregions based on ratios of projected future climate METHODS change relative to current inter-annual climate variability (Williams et al., 2007; Beaumont et al., 2011). Climate models and data We have focused our analysis of palaeoclimate on the mid- Holocene (mH) thermal maximum, a period of about 2000 To examine global differences between potential future climate years centred around 6 ka cal bp, because it was the warmest change and the climate of the mH, we used six models with period of the Holocene for much of the Northern Hemisphere. simulations available for 2100, the pre-industrial conditions and Starting at the beginning of the Holocene about 11.5 ka cal bp the mH (CCSM3, ECHAM, FGOALS, IPSL, MIROC, and MRI). climate warmed – very rapidly in some regions – to close to We used simulations from the PMIP2 working group for the pre-industrial temperatures in the Northern Hemisphere during period of the mH and pre-industrial conditions (Braconnot the mH. The climate system then went through several smaller et al., 2007a,b). For 2100, we used models based on the Inter- periods of warming (most recently the Medieval Warm Period, governmental Panel on Climate Change (IPCC) A1B emissions c. 1–0.7 ka cal bp) and cooling (most recently the Little Ice Age, scenario, which result in projected increases in mean tempera- c. 0.45–0.15 ka cal bp). Climate change during the mH, which ture that are close to the changes predicted for the mH recon- was driven by changes in the Earth’s orbit, differed from future structions for certain regions in the Northern Hemisphere. We projected climate change which is being driven by the anthro- concentrated on four climate variables: (1) mean annual tem- pogenic emission of greenhouse gases (Steig, 1999; MacDonald perature, (2) maximum summer temperatures, (3) minimum et al., 2008b). The climate during the mH was characterized by winter temperatures, and (4) annual precipitation. For each of summer temperatures that were as much as 2.5 °C warmer in the the four variables we calculated climate between the mH and Northern Hemisphere and precipitation patterns different from pre-industrial conditions, the projected climate in 2100 and pre- present (Davis et al., 2003), but winters were colder in temperate industrial conditions, and mH and 2100 (Fig. 1).

Figure 1 Climatic differences between the mid-Holocene and early 20th-century climate (6–0 ka cal bp,left panel), between 2100 (emissions scenario A1B, middle panel) and early 20th-century climate, and between 2100 A1B and the mH (right panel): (a) annual precipitation (mm); (b) mean annual temperature; (c) maximum temperature; and (d) minimum temperature. All temperature scales are in °C.

We processed the six global circulation models selected by ing the weighted average of the PCA scores for each pixel of all averaging the provided 50 or 100 years of the palaeo-simulations principal components (Fig. S1) according to the following and the pre-industrial conditions (climate system c. 1750 ce) formula: and the last 10 years for the global warming simulations (2090–99 ce). Maximum and minimum temperatures were esti- 4 weighted average= ∑C PCA (1) mated from the monthly mean temperatures available for each ii i=1 year and then averaged across years (over 10, 50 or 100 years depending on the model run). Monthly and yearly averages, where Ci is the contribution to the variance or loading from each totals and anomalies were calculated with the Climate Data principal component and PCAi is the score for each axis. Finally, Operators (CDO) directly on the netcdf files (U. Schulzweida, to verify that the calculated anomalies were not biased by inter- Max-Planck-Institute for Meteorology, https://code.zmaw.de/ model variability, we estimated the between-models coefficient projects/cdo/). The resolution of all the models was set to T85 of variation for each variable (Fig. S2). We then applied this (~1.4°) with the CDO bicubic interpolation. Subsequent statis- integrated climate anomaly to define the climate boundary of tical analyses and summary statistics were calculated with the R each biome and ecoregion, which we define as the maximum software (http://www.r-project.org/). anomaly between the mH and pre-industrial climates, across the set of all grid cells in a biome or ecoregion.

Climate analysis Estimation of climate boundaries for biodiversity We applied standard multivariate techniques (PCA) to examine the overall patterns of climate anomalies between 6–0 ka cal bp To estimate whether biomes and ecoregions through the and 2100 A1B scenario–0 cal for all variables resulting from Holocene–Anthropocene climate transition remain within the averaging the six climate simulation models in a unique analysis mH limits, we applied the classiﬁcation by Olson (Olson et al., (Fig. S1 in Supporting Information). We included in the dataset 2001) using two different approaches. First, we calculated the an additional single reference row of zero anomalies (no climate mean value of synthetic climate anomaly index for the world’s differences between periods) for centring the PCA scores results 14 biomes for both transitions (2100 A1B scenario–0 cal bp and around this point. We recentred each axis on zero by subtracting 6–0 ka cal bp). Second, to determine if the expected exposure in the scores corresponding to the row of zeros introduced in the 2100 A1B scenario–0 cal bp would be within the mH bounda- dataset to each score column. In this way, PCA scores close to ries, we calculated the Euclidean distance for the 766 ecoregions zero do represent areas of low anomalies and not the average between the PCA scores of both transition periods. In this way, anomaly between periods. This represents only a translocation we evaluated the degree of similarity between anomalies of both of axis, and the relative separation of scores in the multivariate transition periods in a single map. The Euclidean distances were space remains the same. We then calculated an integrated computed between the PCA values that correspond to the climate anomaly index (see conceptually similar approaches in anomalies between 6–0 ka cal bp and 2100 A1B scenario–0 cal bp Williams et al. (2007) and Beaumont et al. (2011)) by comput- for the same geographical coordinate. The results for the

Figure 2 Climate anomalies for 2100 A1B scenario–0 cal bp versus 6–0 ka cal bp for annual precipitation, mean temperature, maximum temperature and minimum temperature. The black dotted lines represent the climatic boundaries for each variable based on the maximum anomalies simulated for the mid-Holocene. minimum, average, maximum and range of the Euclidean dis- follow similar patterns in their geographical distribution for the tances are provided in Table S1. Northern Hemisphere, but the magnitude is much higher in the 2100 A1B scenario–0 ka cal bp than in the 6–0 ka cal bp anomalies (Fig. 1). This difference in magnitude among 2100 A1B scenario–0 cal bp and 6–0 ka cal bp anomalies is especially RESULTS strong for the minimum temperature in the Northern Hemi- sphere (Fig. 1d). Overall, precipitation levels were lower during Climatic transitions between periods the mH except for the Sahel region, which contrasts sharply with Mean, maximum and minimum temperatures are projected to the extreme spatial variation in precipitation changes expected increase across the entire globe in the A1B greenhouse gas emis- for 2100 (Fig. 1a). sion scenario with respect to 0 cal bp (Fig. 1). Modelled mH When the climatic anomalies between the 6–0 ka cal bp and maximum and mean temperatures are higher in the Northern 2100 A1B scenario–0 cal bp periods are plotted together (Fig. 2), Hemisphere than 0 cal bp. Maximum and mean temperatures the minimum and mean temperatures of the Earth are the vari- are lower for much of the Southern Hemisphere, with notable ables that are clearly projected to change more in the future with exceptions in the Amazon Basin and parts of southern Africa. respect to their maximum values during the mH (Fig. 2, dotted Modelled minimum annual temperatures are lower during the lines). On the other hand, the expected range of changes in mH than 0 cal bp for most of the globe. Precipitation patterns precipitation and mean temperatures for 2100 A1B scenario–0 are projected to be different in virtually all regions of the world cal bp are within the range of 6–0 ka cal bp differences, at least in 2100 compared with current conditions and the mH (Figs 1 & globally (Fig. 2). 2). Precipitation will probably increase in the Northern Hemi- When both sets of anomalies (2100 A1B scenario–0 cal bp and sphere, the Andes, the Parana Basin, eastern Africa and the 6–0 ka cal bp) are combined in a single PCA (Fig. S1e), the first Pacific tropical islands whereas it will probably decrease in the three components (which explain 99% of the data variance) Mediterranean Basin, northern and Equatorial Africa and show two separate, well-defined clouds that share little of the Central America. The general patterns of mH climate corre- multidimensional space of the PCA (Fig. S1e). The magnitude spond to palaeoclimate reconstructions (see Introduction), even and direction of expected climate changes for 2100 are projected if the model shows high variation in precipitation for some areas to largely surpass the conditions simulated for the mH. The first (Fig. S2). However, we have to bear in mind that that 6 ka component of the PCA is strongly determined by temperature models underestimate the expansion of the African monsoon in (minimum, mean and maximum) whereas precipitation is this region (Braconnot et al., 2007a). Temperature anomalies clearly the most important variable in the second axis (Table 1, between 2100 and pre-industrial climate, and 6 and 0 ka cal bp Fig. S1).

Table 1 Summary of the statistics for the principal components analysis (PCA) on the anomalies of four climatic variables between projected global warming for 2100 (A1B scenario) and the mid-Holocene (6 ka cal bp) with respect to pre-industrial conditions (0 cal bp). Only signiﬁcant correlations are shown for the four principal components noted, C1–C4.

C1 C2 C3 C4

Component Standard deviation 1.691 0.954 0.468 0.106 % of variance 0.715 0.228 0.055 0.003 Cumulative variance 0.715 0.942 0.997 1 Loadings Annual precipitation -0.281 0.951 -0.125 0.000 Maximum temperature -0.528 -0.255 -0.782 -0.211 Mean temperature -0.572 -0.153 0.228 0.773 Minimum temperature -0.561 0.000 0.566 -0.598

Anomalies in the synthetic climate index are always higher for the 2100 A1B scenario–0 cal bp period than for the 6–0 ka cal bp one (Fig. 3). The highest 6–0 ka cal bp anomalies are concentrated in eastern Europe and the Middle East, the Sahel and most parts of India and the Himalayas, but they are low in magnitude compared with projected future changes (Fig. 3a). In contrast, high 2100 A1B scenario–0 cal bp anomalies are expected over Figure 3 Global synthesis maps depicting the weighted average the entire globe (Fig. 3b). While the northern circumpolar areas principal components for the anomalies between: (a) 6 and 0 ka cal bp and (b) 2100 A1B scenario and 0 cal bp. Both maps are appear with high anomalies in both transitions, strong differ- based on the same principal components analysis (PCA) so the ences for the 2100 A1B scenario–0 cal bp transition are also scale is identical. Colours denote the number of standard largely localized in the central Andes, southern and eastern deviations by which the scores differ from zero (no climate Africa, the Central Asian plateau and the tropical Pacific islands variation). The principal components from which these maps (Fig. 3a, b). were calculated are shown in Table 1 and depicted in Fig. S1. (c) High inter-model variation was observed for the climate tran- Bean-plot figure of the values (average and density) of the sitions between periods for Greenland, the Himalayan Plateau, weighted average PCA scores calculated for the main biomes of the Sahara and Sahel, mostly for temperatures and for a lesser the world based on (a) and (b). Biomes are as follows: TSM, extent for precipitation (Fig. S2). A southern subtropical belt tropical and subtropical moist broadleaf forests; TSD, tropical and including the dry areas of South America in the Chile, Bolivia subtropical dry broadleaf forests; TSC, tropical and subtropical and Argentina areas, the western coast of South Africa and coniferous forests; TeB, temperate broadleaf and mixed forests; TeC, temperate coniferous forests; BT, boreal forests/taiga; TSG, Australia all exhibit high inter-model variation for precipitation. tropical and subtropical grasslands, savannas and shrublands; Finally, boreal and tundra areas have high inter-model variation TeG, temperate grasslands, savannas and shrublands; FG, flooded for minimum temperatures. grasslands and savannas; MG, montane grasslands and shrublands; T, tundra; Me, Mediterranean forests, woodlands and Biome and ecoregion exposure to climate change scrub; DX, deserts and xeric shrublands; Ma, mangroves.

Biomes with similar magnitudes of climate change during the 6–0 ka cal bp and 2100 A1B scenario–0 cal bp transitions are relatively rare. All biomes were found to be subject to very dif- (Fig. 4). Zones where 6–0 ka cal bp anomalies are the most ferent climatic patterns under future climate change compared similar to the 2100 A1B scenario–0 cal bp anomalies include with the mH except for grasslands and savannas that showed areas of continental North America, Greenland, the Mediterra- some overlap between periods (Fig. 3c). The biome exposure to nean Basin and the temperate areas of Europe, some parts of climate change for the 6–0 ka cal bp comparison is much lower, central Asia, Japan, Patagonia in South America (green colours). ranging from 0 to 1 standardized units as deﬁned in the The highest Euclidean distances between periods, indicating Methods, than the 2100 A1B scenario–0 cal bp anomalies, which that expected climates are well beyond the mH envelope, were varied between 2 and 4 units. found for the boreal–tundra areas of North America and The Euclidean distances between both anomalies are an indi- Eurasia, and the tropical equatorial zones all around the Earth cator of the dissimilarity of climate change between periods (red colours).

Figure 4 Mean values of the Euclidean distance between the principal components analysis (PCA) scores of the 6–0 ka cal bp and 2100 A1B scenario–0 cal bp anomalies for the 766 terrestrial ecoregions (Olson et al., 2001). Equatorial and northern circumpolar areas appeared equally exposed to climates beyond the mid-Holocene (mH) boundaries (red areas). Areas with lower exposure correspond to regions where expected climate change will resemble, to a certain degree, the changes that occurred during the mH (green areas). Table S1 contains the individual weighted PCA scores for all the 766 ecoregions for the 6–0 ka cal bp and 2100 A1B scenario–0 cal bp analyses.

perate forests extended further north than today in the Eurasian DISCUSSION continent (Prentice et al., 1998). Tropical coniferous forests Our analysis of the climate transitions between the mH, 0 cal bp covered a larger region in western North America during the and 2100 A1B scenario shows that expected biome exposure to mH than nowadays (e.g. the Madrean mountains of north-west future climate change is heterogeneous spatially and future Mexico), as shown by biome reconstruction (Ortega-Rosas climate change would typically greatly exceed the climatic limits et al., 2008). Similarly, tropical areas like the high Andes páramo observed for the mH (Figs 1 & 2). This is broadly coherent with vegetation in equatorial South America were at least 300 m previous analyses of palaeo and future climates (Jackson & higher in altitude during the warm period of the mH than at Overpeck, 2000). In fact, many terrestrial ecosystems of the present (Niemann & Behling, 2008; Niemann et al., 2009). world appear to be subject not only to new climates in 2100 with Some of the large climate anomalies between the mH and 0 respect to current conditions but also with respect to the mH cal bp are associated with cooler temperatures during the mH (Fig. 1). This implies that many biomes and ecoregions will need and/or large differences in precipitation (e.g. the Sahel, equato- to respond to future climate change in ways not observed during rial regions in general). Overall, precipitation regimes made a the Holocene. We have identified a few areas with similar mag- larger contribution to climate change in the equatorial belt than nitudes of climate change during the 6–0 ka cal bp and 2100 A1B temperatures over the periods that we analysed. Reconstruction scenario–0 cal bp periods. Past exposure to climate similar to of the patterns of vegetation in Africa has revealed ample projected future climate may reduce the vulnerability of these responses to climate change during the mH: the northern extent areas (Jackson & Overpeck, 2000; Willis & MacDonald, 2011). of tropical rain forest was substantially greater, whereas that of the Sahara Desert was smaller during the mH than at present (Jolly et al., 1998). However, climate change models for the The Holocene–Anthropocene transition versus future future remain highly uncertain for this area with respect to climate change precipitation, and there is discussion whether some greening of Even though the anomalies for 6–0 ka cal bp were relatively the Sahel may occur (Giannini et al., 2008). It is also important small compared with that for 2100 A1B scenario–0 cal bp, they to note that even when vegetation feedbacks are included in mH were sufficient to produce significant changes in the composi- global circulation models, they fail to adequately simulate the tion of the vegetation from the mH to the present. The highest greening of the Sahara during this period, as precipitation 6–0 ka cal bp climatic anomalies in our analysis are those of the remains too low (Braconnot et al., 2007a,b). northern circumpolar areas, eastern Europe and the Middle Even though our analysis shows that almost all terrestrial East, the Sahel and the Indo-Himalayan region – all of which regions of the Earth could be exposed to future climate regimes had recorded high species turnover during the mH (Jolly et al., not seen during the mH, some areas of high biodiversity may be 1998; Prentice & Jolly, 2000; Bigelow, 2003; Giannini et al., particularly exposed. There is great concern that the drier parts 2008). Warmer maximum temperatures in the Northern Hemi- of the Amazon Basin (mostly towards the south-east and south- sphere and parts of the Southern Hemisphere were associated west in the ecotones towards the El Chaco region and the Atlan- with poleward or upward movements in altitude range shifts of tic forest) may change permanently, first to dry seasonal forest biomes and species (Figs 1, 3 & S1). For example, the tundra and then to a savanna-like vegetation type due to interactions vegetation extended at least 200 km north of its present distri- between climate change, deforestation and fire (Malhi et al., bution in Siberia (MacDonald et al., 2000; Prentice & Jolly, 2000; 2008; Lenton, 2011). However, the middle-elevation areas of the Bigelow, 2003; Patricola & Cook, 2007; Ivory et al., 2012). Tem- central Andes in the eastern slopes of the Amazon Basin drain-

6 Global Ecology and Biogeography, ••, ••–••, © 2013 John Wiley & Sons Ltd Biodiversity and long-term climate change age appear much more exposed to climate change than the their current location, and the reconstructions of the vegetation Amazon region itself. During the mH, the vegetation of the based on palaeodata show that similar northward shifts of Amazon lowlands adapted to slightly drier conditions than boreal forest and tundra would happen in the future (Salzmann those experienced nowadays (Behling, 1998, 2003; Whitney et al., 2008, 2009) if human transformation of the earth does not et al., 2011), while the mountain Andean flora responded mostly impede it. Overall, what can be learned from pre-Quaternary by altitudinal migrations that are seen in the pollen records warm periods is that no massive plant extinction happened even (Urrego et al., 2010). Hence, more adaptive variation may exist with warmer temperatures than those expected for the near in the larger populations of the Amazon lowlands that allow the future, but biomes changed their composition by local extinc- system to maintain a physiognomy close to that of the present- tion, species shifts, and community reshuffling (Willis & day forest, which could explain a certain degree of resilience of MacDonald, 2011). Similar conclusions for biodiversity can be this biome during periods of climate variation (Colinvaux et al., extracted from more recent warming periods like those happen- 2000; Mayle & Power, 2008) compared with Andean populations ing during the Pleistocene–Holocene transition that entailed that have necessarily smaller population sizes. Hence, the eastern relatively rapid warming and large temperature variability Andes may be more exposed and more constrained to respond (Moberg et al., 2005; Finsinger et al., 2011). Among them, the to climate change than the better-studied areas of the Amazon. Bølling–Allerød (c. 14.7–12.9 ka cal bp) period, and the end of Our analysis based on average distance between climate vari- the Younger Dryas (c. 11.5 ka cal bp) are examples of rapid ables highlights the existence of the highest climatic risks for climate change when temperatures increased by about 3 °C in equatorial and circumpolar areas (Fig. 4). The warming-related less than 200 years (MacDonald et al., 2008a), but starting from risk of circumpolar areas has been well indentified by other very cold temperatures. Whilst one can be tempted to conclude analyses (e.g. Lunt et al., 2012). However, the evaluation of that there is no risk for biodiversity in surpassing the mH envi- climate-related risks in equatorial areas has received less atten- ronmental conditions or any other warming event known from tion. Other analyses based on scaling future expected changes the past, the human transformation is hampering range shifts with current intra-annual climate variability also indicate that and migration of species necessary for ecosystems to adjust in equatorial areas may be at particularly high risk (Williams et al., the the Holocene–Anthropocene transition (Loarie et al., 2009; 2007; Beaumont et al., 2011). This occurs because inter-annual Bertrand et al., 2011). variability in climate is generally low in equatorial regions, and therefore future climates frequently exceed the extremes of Implications: refugia from climate change inter-annual variability (Williams et al., 2007; Beaumont et al., 2011). It is unclear, however, to what extent exceeding extremes Recent interest in identifying patterns of species survival during in inter-annual variability in temperature over relatively short different periods of climate change has led scientists to coin the periods is a good general indicator of the climate sensitivity of term ‘refugia from climate change’ to define areas where species species. could persist despite the new climate conditions that are expected in the future (Williams et al., 2008; Ashcroft, 2010). In our analyses, however, areas sharing similar degrees of climate Other recorded periods of warm climate change and change between the 6–0 ka cal bp and 2100 A1B scenario–0 cal future climate change bp transition are negligible (Figs 2–4) and belong mainly to the Whether ecosystems can adjust to climates beyond the natural grassland and savanna biomes. In temperate regions of North variation during the Holocene can be examined partially using America the ecotone between prairie and forest has shifted from palaeo-analogues of future climate change (Salzmann et al., its mH position, but most of the North American prairies were 2008; Haywood et al., 2011; Willis & MacDonald, 2011). Com- already present by 6 ka cal bp (Williams et al., 2009). Likewise, parative 2100 A1B scenario–0 cal bp climate analyses (Williams semi-arid and grassland vegetation in western China appeared et al., 2007), which have been used broadly to assess the risk of to display similar patterns during the mH as today (Ni et al., projected climate change to biodiversity (Beaumont et al., 2010). Hence, it is not unlikely that temperate grassland vegeta- 2011), show high climate-related risks, either because current tion will be a biome of high species turnover during ongoing climates disappear or novel climates are created. These decadal climate change but with sufficient resilience in the long term. timeframe analyses are extremely relevant from a species or Whether they can act as climate change refugia remains less population perspective, but they do not inform us about their clear, as these areas are heavily urbanized and cultivated, and relative strength with respect to previous major climate change may became more populated if climate change in these areas is events. In general, warm events that occurred before the Qua- effectively buffered to some extent. ternary are not considered good analogues of future climate change because the location of the continents and the climate Potential limitations of our approach sensitivity to CO2 were different from nowadays, and the warming rate was slower (Hunter et al., 2008; Salzmann et al., We developed a multivariate statistical method that does not 2008, 2009; Haywood et al., 2011). Among them, the most likely account for any compensation mechanisms or feedbacks on analogue of future climate change is the mid-Pliocene warm biome function. For instance, the role of CO2 fertilization in period (3.6–2.6 Myr cal bp) when continents were already in drought-prone areas is still unclear. Whereas some studies

Global Ecology and Biogeography, ••, ••–••, © 2013 John Wiley & Sons Ltd 7 M. Benito-Garzón et al. suggest that the combination of carbon fertilization with warm Bigelow, N.H. (2003) Climate change and Arctic ecosystems: 1. conditions can induce increased water-use efficiency by stomatal Vegetation changes north of 55°N between the Last Glacial closure (Keenan et al., 2011), other studies highlight that even if Maximum, mid-Holocene, and present. Journal of Geophysical the water-use efficiency increases, it will be not enough to com- Research: Atmospheres, 108, 8170. pensate for future drought conditions for some areas of the Braconnot, P., Otto-Bliesner, B., Harrison, S., Joussaume, S., planet (Peñuelas et al., 2011). Second, our approach does not Peterchmitt, J.-Y., Abe-Ouchi, A., Crucifix, M., Driesschaert, account in the analysis for shifts in the vegetation during the mH E., Fichefet, T., Hewitt, C.D., Kageyama, M., Kitoh, A., Loutre, that could change our conclusions of overall biome exposure to M.-F., Marti, O., Merkel, U., Ramstein, G., Valdes, P., Weber, climate change. Other statistical techniques such as niche mod- L., Yu, Y. & Zhao, Y. (2007a) Results of PMIP2 coupled simu- elling could have been used to estimate the relationship between lations of the mid-Holocene and Last Glacial Maximum – climate and ecosystem distribution (Roberts & Hamann, 2012), part 2: feedbacks with emphasis on the location of the ITCZ but our multivariate PCA allowed us to compare in one single and mid- and high latitudes heat budget. Climate of the Past, 3, analysis several periods of time (6 ka, pre-industrial and 2100) 279–296. which is not possible with SDM analyses. Braconnot, P., Otto-Bliesner, B., Harrison, S. et al. (2007b) Finally, the coarse resolution of our analysis would not detect Results of PMIP2 coupled simulations of the mid-Holocene many possible microrefugia from future climate change and Last Glacial Maximum – part 1: experiments and large- (Ashcroft, 2010) for species within heterogeneous landscapes in scale features. Climate of the Past, 3, 261–277. areas of high anomalies. Bush, M.B., Silman, M.R. & Urrego, D.H. (2004) 48,000 years of climate and forest change in a biodiversity hot spot. Science, 303, 827–829. ACKNOWLEDGEMENTS Colinvaux, P.A., De Oliveira, P.E. & Bush, M.B. (2000) Amazo- The authors wish to thank the PMIP2 consortium for providing nian and Neotropical plant communities on glacial time- palaeoclimate reconstructions and the IPCC Data Distribution scales: the failure of the aridity and refuge hypotheses. Centre for climate change model simulations. M.B.G. was par- Quaternary Science Reviews, 19, 141–169. tially supported by a Juan de la Cierva fellowship and a Marie Davis, B.A.S., Brewer, S., Stevenson, A.C. & Guiot, J. (2003) The Curie FPT7-PEOPLE-2012 ‘AMECO’ individual post-doctoral temperature of Europe during the Holocene reconstructed fellowship. This study was partially supported by the ANR- from pollen data. Quaternary Science Reviews, 22, 1701– AMTools, and by the CNRS INGEO-ECO and IngECOtech 1716. CNRS-Cemagref grants. Ellis, E.C., Antill, E.C. & Kreft, H. (2012) All is not loss: plant biodiversity in the Anthropocene. PLoS ONE, 7, e30535. Finsinger, W., Lane, C.S., Van Den Brand, G.J., Wagner-Cremer, REFERENCES F., Blockley, S.P.E. & Lotter, A.F. (2011) The late glacial Ashcroft, M.B. (2010) Identifying refugia from climate change. Quercus expansion in the southern European Alps: rapid veg- Journal of Biogeography, 37, 1407–1413. etation response to a late Allerød climate warming? Journal of Beaumont, L.J., Pitman, A., Perkins, S., Zimmermann, N.E., Quaternary Science, 26, 694–702. Yoccoz, N.G. & Thuiller, W. (2011) Impacts of climate change Giannini, A., Biasutti, M. & Verstraete, M.M. (2008) A climate on the world’s most exceptional ecoregions. Proceedings of the model-based review of drought in the Sahel: desertification, National Academy of Sciences USA, 108, 2306–2311. the re-greening and climate change. Global and Planetary Behling, H. (1998) Late Quaternary vegetational and climatic Change, 64, 119–128. changes in Brazil. Review of Palaeobotany and Palynology, 99, Haywood, A.M., Ridgwell, A., Lunt, D.J., Hill, D.J., Pound, M.J., 143–156. Dowsett, H.J., Dolan, A.M., Francis, J.E. & Williams, M. Behling, H. (2003) Late glacial and Holocene vegetation, climate (2011) Are there pre-Quaternary geological analogues for a and fire history inferred from Lagoa Nova in the southeastern future greenhouse warming? Philosophical Transactions of the Brazilian lowland. Vegetation History and Archaeobotany, 12, Royal Society A: Mathematical, Physical, and Engineering Sci- 263–270. ences, 369, 933–956. Bellard, C., Bertelsmeier, C., Leadley, P., Thuiller, W. & Hunter, S., Valdes, P.J., Haywood, A.M. & Markwick, P.J. (2008) Courchamp, F. (2012) Impacts of climate change on the future Modelling Maastrichtian climate: investigating the role of

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