IPCC Fourth Assessment Report: Climate Change 2007
Climate Change 2007: Working Group II: Impacts, Adaptation and Vulnerability

4.4.11 Global synthesis including impacts on biodiversity

Considerable progress has been made since the TAR in key fields that allow projection of future climate change impacts on species and ecosystems. Two of these key fields, namely climate envelope modelling (also called niche-based, or bioclimatic modelling) and dynamic global vegetation modelling have provided numerous recent results. The synthesis of these results provides a picture of potential impacts and risks that is far from perfect, in some instances apparently contradictory, but overall highlights a wide array of key vulnerabilities (Figures 4.2; 4.4; 4.5, Table 4.1).

Climate envelope modelling has burgeoned recently due to increased availability of species distribution data, together with finer-scale climate data and new statistical methods that have allowed this correlative method to be widely applied (e.g., Guisan and Thuiller, 2005; McClean et al., 2005; Thuiller et al., 2005b). Despite several limitations (Section 4.3 and references cited therein) these models offer the advantage of assessing climate change impacts on biodiversity quantitatively (e.g., Thomas et al., 2004a). Climate envelope models do not simulate dynamic population or migration processes, and results are typically constrained to the regional level, so that the implications for biodiversity at the global level are difficult to infer (Malcolm et al., 2002a).

In modelling ecosystem function and plant functional type response, understanding has deepened since the TAR, though consequential uncertainties remain. The ecophysiological processes affected by climate change and the mechanisms by which climate change may impact biomes, ecosystem components such as soils, fire behaviour and vegetation structure (i.e., biomass distribution and leaf area index) are now explicitly modelled and have been bolstered by experimental results (e.g., Woodward and Lomas, 2004b). One emerging key message is that climate change impacts on the fundamental regulating services may previously have been underestimated (Sections 4.4.1, 4.4.10, Figures 4.2; 4.3; 4.4). Nevertheless, the globally applicable DGVMs are limited inasmuch as the few plant functional types used within the models aggregate numerous species into single entities (Sitch et al., 2003). These are assumed to be entities with very broad environmental tolerances, which are immutable and immune to extinction. Therefore, underlying changes in species richness are not accounted for, and the simultaneous free dispersal of PFTs is assumed (e.g., Neilson et al., 2005; Midgley et al., 2007). The strength of DGVMs is especially in their global application, realistic dynamics and simulation of ecosystem processes including essential elements of the global C-cycle (e.g., Malcolm et al., 2002b). Thus, it is reasonable to equate changes in DGVM-simulated vegetation (e.g., Figure 4.3) to changes in community and population structures in the real world.

What overall picture emerges from the results reviewed here? It appears that moderate levels of atmospheric CO2 rise and climate change relative to current conditions may be beneficial in some regions (Nemani et al., 2003), depending on latitude, on the CO2 responsiveness of plant functional types, and on the natural adaptive capacity of indigenous biota (mainly through range shifts that are now being widely observed – see Chapter 1). But as change continues, greater impacts are projected, while ecosystem and species response may be lagged (Sections 4.4.5, 4.4.6). At key points in time (Figure 4.4), ecosystem services such as carbon sequestration may cease, and even reverse (Figure 4.2). While such ‘tipping points’ (Kemp, 2005) are impossible to identify without substantial uncertainties, they may lead to irreversible effects such as biodiversity loss or, at the very least, impacts that have a slow recovery (e.g., on soils and corals).

Figure 4.4

Figure 4.4. Compendium of projected risks due to critical climate change impacts on ecosystems for different levels of global mean annual temperature rise, ΔT, relative to pre-industrial climate (approach and event numbers as used in Table 4.1 and Appendix 4.1). It is important to note that these impacts do not take account of ancillary stresses on species due to over-harvesting, habitat destruction, landscape fragmentation, alien species invasions, fire regime change, pollution (such as nitrogen deposition), or for plants the potentially beneficial effects of rising atmospheric CO2. The red curve shows observed temperature anomalies for the period 1900-2005 (Brohan et al., 2006, see also Trenberth et al., 2007, Figure 3.6). The two grey curves provide examples of the possible future evolution of temperature against time (Meehl et al., 2007, Figure 10.4), providing examples of higher and lower trajectories for the future evolution of the expected value of ΔT. Shown are the simulated, multi-model mean responses to (i) the A2 emissions scenario and (ii) an extended B1 scenario, where radiative forcing beyond the year 2100 was kept constant to the 2100 value (all data from Meehl et al., 2007, Figure 10.4, see also Meehl et al., 2007, Section 10.7).

In the two simulations presented in Figure 4.2 (warming of 2.9°C and 5.3°C by 2100 over land relative to the 1961-1990 baseline), the DGVM approach reveals salient changes in a key regulating service of the world’s ecosystems: carbon sequestration. Changes in the spatial distributions of ecosystems are given in Figure 4.3 (where it must be stressed that the figure highlights only key vulnerabilities through depicting appreciable vegetation type changes, i.e., PFT change over >20% of the area of any single pixel modelled). In the B1 emissions scenario (Figure 4.3b) about 26% of extant ecosystems reveal appreciable changes by 2100, with some positive impacts especially in Africa and the Southern Hemisphere. However, these positive changes are likely to be due to the assumed CO2-fertilisation effect (Section 4.4.10, Figure 4.3). By contrast, in mid- to high latitudes on all continents, substantial shifts in forest structure toward more rain-green, summer-green or deciduous rather than evergreen forest, and forest and woodland decline, underlie the overall drop in global terrestrial carbon sequestration potential that occurs post-2030, and approaches a net source by about 2070 (Figure 4.2; 4.3). In the A2 emissions scenario, roughly 37% of extant ecosystems reveal appreciable changes by 2100. Desert amelioration persists in the regions described above, but substantial decline of forest and woodland is seen at northern, tropical and sub-tropical latitudes. In both scenarios the current global sink deteriorates after 2030, and by 2070 (ΔT ~2.5°C over pre-industrial) the terrestrial biosphere becomes an increasing carbon source (Figure 4.2; see also Scholze et al., 2006) with the concomitant risk of positive feedback, developments that amplify climate change. Similar results were obtained by using a wide range of climate models which indicate that the biosphere becomes consistently within this century a net CO2 source with a global warming of >3°C relative to pre-industrial (Scholze et al., 2006). On the other hand, it must be noted that by about 2100 the modelled biosphere has nevertheless sequestered an additional 205-228 PgC (A2 and B1 emissions scenarios respectively) relative to the year 2000 (Lucht et al., 2006).

Climate envelope modelling suggests that climate change impacts will diminish the areal extent of some ecosystems (e.g., reduction by 2-47% alone due to 1.6°C warming above pre-industrial, Table 4.1, No. 6) and impact many ecosystem properties and services globally. Climate impacts alone will vary regionally and across biomes and will lead to increasing levels of global biodiversity loss, as expressed through area reductions of wild habitats and declines in the abundance of wild species putting those species at risk of extinction (e.g., 3-16% of European plants with 2.2°C warming (Table 4.1, No. 20) or major losses of Amazon rainforest with 2.5°C warming above pre-industrial, Figure 4.4, Table 4.1, No. 36). Globally, biodiversity (represented by species richness and relative abundance) may decrease by 13 to 19% due to a combination of land-use change, climate change and nitrogen deposition under four scenarios by 2050 relative to species present in 1970 (Duraiappah et al., 2005). Looking at projected losses due to land-use change alone (native habitat loss), habitat reduction in tropical forests and woodland, savanna and warm mixed forest accounts for 80% of the species projected to be lost (about 30,000 species – Sala, 2005). The apparent contrast between high impacts shown by projections for species (climate envelope models) relative to PFTs (DGVMs) is likely to be due to a number of reasons – most importantly, real species virtually certainly have narrower climate tolerances than PFTs, a fact more realistically represented by the climate envelope models. DGVM projections reveal some increasing success of broad-range, generalist plant species, while climate envelope model results focus on endemics. Endemics, with their smaller ranges, have been shown to have a greater vulnerability to climate change (Thuiller et al., 2005a), and may furthermore be dependent on keystone species in relationships that are ignored in DGVMs. Therefore, for assessing extinction risks, climate envelope modelling currently appears to offer more realistic results.

As indicated in the TAR, climate changes are being imposed on ecosystems experiencing other substantial and largely detrimental pressures. Roughly 60% of evaluated ecosystems are currently utilised unsustainably and show increasing signs of degradation (Reid et al., 2005; Hassan et al., 2005; Worm et al., 2006). This alone will be likely to cause widespread biodiversity loss (Chapin et al., 2000; Jenkins, 2003; Reid et al., 2005), given that 15,589 species, from every major taxonomic group, are already listed as threatened (Baillie et al., 2006). The likely synergistic impacts of climate change and land-use change on endemic species have been widely confirmed (Hannah et al., 2002a; Hughes, 2003; Leemans and Eickhout, 2004; Thomas et al., 2004a; Lovejoy and Hannah, 2005; Hare, 2006; Malcolm et al., 2006; Warren, 2006), as has over-exploitation of marine systems (Worm et al., 2006; Chapters 5 and 6).

Overall, climate change has been estimated to be a major driver of biodiversity loss in cool conifer forests, savannas, mediterranean-climate systems, tropical forests, in the Arctic tundra, and in coral reefs (Thomas et al., 2004a; Carpenter et al., 2005; Malcolm et al., 2006). In other ecosystems, land-use change may be a stronger driver of biodiversity loss at least in the near term. In an analysis of the SRES scenarios to 2100 (Strengers et al., 2004), deforestation is reported to cease in all scenarios except A2, suggesting that beyond 2050 climate change is very likely to be the major driver for biodiversity loss globally. Due to climate change alone it has been estimated that by 2100 between 1% and 43% of endemic species (average 11.6%) will be committed to extinction (DGVM-based study – Malcolm et al., 2006), whereas following another approach (also using climate envelope modelling-based studies – Thomas et al., 2004a) it has been estimated that on average 15% to 37% of species (combination of most optimistic assumptions 9%, most pessimistic 52%) will be committed to extinction by 2050 (i.e., their range sizes will have begun shrinking and fragmenting in a way that guarantees their accelerated extinction). Climate-change-induced extinction rates in tropical biodiversity hotspots are likely to exceed the predicted extinctions from deforestation during this century (Malcolm et al., 2006). In the mediterranean-climate region of South Africa, climate change may have at least as significant an impact on endemic Protea species’ extinction risk as land-use change does by 2020 (Bomhard et al., 2005). Based on all above findings and our compilation (Figure 4.4, Table 4.1) we estimate that on average 20% to 30% of species assessed are likely to be at increasingly high risk of extinction from climate change impacts possibly within this century as global mean temperatures exceed 2°C to 3°C relative to pre-industrial levels (this chapter). The uncertainties remain large, however, since for about 2°C temperature increase the percentage may be as low as 10% or for about 3°C as high as 40% and, depending on biota, the range is between 1% and 80% (Table 4.1; Thomas et al., 2004a; Malcolm et al., 2006). As global average temperature exceeds 4°C above pre-industrial levels, model projections suggest significant extinctions (40-70% species assessed) around the globe (Table 4.1).

Losses of biodiversity will probably lead to decreases in the provision of ecosystem goods and services with trade-offs between ecosystem services likely to intensify (National Research Council, 1999; Carpenter et al., 2005; Duraiappah et al., 2005). Gains in provisioning services (e.g., food supply, water use) are projected to occur, in part, at the expense of other regulating and supporting services including genetic resources, habitat provision, climate and runoff regulation. Projected changes may also increase the likelihood of ecological surprises that are detrimental for human well-being (Burkett et al., 2005; Duraiappah et al., 2005). Ecological surprises include rapid and abrupt changes in temperature and precipitation, leading to an increase in extreme events such as floods, fires and landslides, increases in eutrophication, invasion by alien species, or rapid and sudden increases in disease (Carpenter et al., 2005). This could also entail sudden shifts of ecosystems to less desired states (Scheffer et al., 2001; Folke et al., 2004; e.g., Chapin et al., 2004) through, for example, the exeedance of critical temperature thresholds, possibly resulting in the irreversible loss of ecosystem services, which were dependent on the previous state (Reid et al., 2005).

Table 4.1. Projected impacts of climate change on ecosystems and population systems as reported in the literature for different levels of global mean annual temperature rise, ΔTg, relative to pre-industrial climate – mean and range (event numbers as used in Figure 4.4 and Appendix 4.1). The global temperature change values are used as an indicator of the other associated climate changes that match particular amounts of ΔTg, e.g., precipitation change and, where considered, change in the concentration of greenhouse gases in the atmosphere. Projections from the literature were harmonised into a common framework by down/upscaling (where necessary) from local to global temperature rise using multiple GCMs, and by using a common global mean temperature reference point for the year 1990 (after Warren, 2006). Whilst some of the literature relates impacts directly to global mean temperature rises or particular GCM scenarios, many studies give only local temperature rises, ΔTreg, and hence require upscaling. The thirteen GCM output data sets used are taken from the IPCC DDC at http://www.ipcc-data.org/.

No.i  ΔTg above pre-ind ii  ΔTg above pre-ind iii (range)   ΔTreg above 1990 (range)  Impacts to unique or widespread ecosystems or population systems  Region  Ref. no. 
0.6     Increased coral bleaching Caribbean, Indian Ocean, Great Barrier Reef 
0.6     Amphibian extinctions/extinction risks on mountains due to climate-change-induced disease outbreaks Costa Rica, Spain, Australia 52, 54 
<1.0     Marine ecosystems affected by continued reductions in krill possibly impacting Adelie penguin populations; Arctic ecosystems increasingly damaged Antarctica, Arctic 42, 11, 14 
1.3 1.1-1.6 8% loss freshwater fish habitat, 15% loss in Rocky Mountains, 9% loss of salmon N. America 13 
1.6  1.2-2.0  0.7-1.5 9-31% (mean 18%) of species committed to extinction Globe iv 
1.6     Bioclimatic envelopes eventually exceeded, leading to 10% transformation of global ecosystems; loss of 47% wooded tundra, 23% cool conifer forest, 21% scrubland, 15% grassland/steppe, 14% savanna, 13% tundra and 12% temperate deciduous forest. Ecosystems variously lose 2-47% areal extent.  Globe  
1.6 1.1-2.1  Suitable climates for 25% of eucalypts exceeded Australia 12 
1.7  1-2.3 1°C SST  All coral reefs bleached Great Barrier Reef, S.E. Asia, Caribbean 
1.7 1.2-2.6   38-45% of the plants in the Cerrado committed to extinction Brazil 1, 44 
10 1.7 1.3-3   2-18% of the mammals, 2-8% of the birds and 1-11% of the butterflies committed to extinction Mexico 1, 26 
11 1.7 1.3-2.4 16% freshwater fish habitat loss, 28% loss in Rocky Mountains, 18% loss of salmon N. America 13 
12  <1.9 <1.6-2.4 <1  Range loss begins for golden bowerbird  Australia 

i Same numbers as used in first column in Appendix 4.1.

ii The mean temperature change is taken directly from the literature, or is the central estimate of a range given in the literature, or is the mean of upscaling calculations (cf. caption).

iii The range of temperature change represents the uncertainty arising from the use of different GCM models to calculate global temperature change.

iv 20% of the Earth’s land surface covered by study.

No.  ΔTg above pre-ind ΔTg above pre-ind (range)   ΔTreg above 1990 (range)  Impacts to unique or widespread ecosystems or population systems  Region  Ref. no. 
13 1.9  1.6-2.4 1  7-14% of reptiles, 8-18% of frogs, 7-10% of birds and 10-15% of mammals committed to extinction as 47% of appropriate habitat in Queensland lost Australia 1, 7 
14 1.9 1.6-2.4 Range loss of 40-60% for golden bowerbird Australia 
15 1.9 1.0-2.8   Most areas experience 8-20% increase in number ³7day periods with Forest Fire Weather Index >45: increased fire frequency converts forest and maquis to scrub, leads to more pest outbreaks  Mediterranean  34  
16  2.1      41-51% loss in plant endemic species richness  S. Africa, Namibia  39  
17  2.1  1.0-3.2 1-2 Alpine systems in Alps can tolerate local temperature rise of 1-2°C, tolerance likely to be negated by land-use change Europe 
18 2.1   1.4-2.6 13-23% of butterflies committed to extinction Australia 1, 30 
19 2.1 1.4-2.6   Bioclimatic envelopes of 2-10% plants exceeded, leading to endangerment or extinction; mean species turnover of 48% (spatial range 17-75%); mean species loss of 27% (spatial range 1- 68%)  Europe 22 
20 2.2     3-16% of plants committed to extinction Europe 
21 2.2 2.1-2.3  1.6-1.8 15-37% (mean 24%) of species committed to extinction Globe iv 
22 2.2 1.7-3.2   8-12% of 277 medium/large mammals in 141 national parks critically endangered or extinct; 22-25% endangered Africa 23 
23 2.3 1.5-2.7 2°C SST  Loss of Antarctic bivalves and limpets  Southern Ocean 51 
24 2.3 2.0-2.5   Fish populations decline, wetland ecosystems dry and disappear  Malawi, African Great Lakes 20 
25 2.3  1.5-2.7 2.5-3.0 Extinctions (100% potential range loss) of 10% endemics; 51-65% loss of Fynbos; including 21-40% of Proteaceae committed to extinction; Succulent Karoo area reduced by 80%, threatening 2,800 plant species with extinction; 5 parks lose >40% of plant species S. Africa 1, 5, 24, 25 
26 2.3 2.3-4.0 2.5-3.0 24-59% of mammals, 28-40% of birds, 13-70% of butterflies, 18-80% of other invertebrates, 21-45% of reptiles committed to extinction; 66% of animal species potentially lost from Kruger National Park S. Africa 1, 27 
27 2.3 2.2-4.0   2-20% of mammals, 3-8% of birds and 3-15% of butterflies committed to extinction Mexico 1, 26 
28 2.3 1.6-3.2   48-57% of Cerrado plants committed to extinction Brazil 
29 2.3     Changes in ecosystem composition, 32% of plants move from 44% of area with potential extinction of endemics Europe 16 
30 2.3 1.6-3.2 24% loss freshwater fish habitat, 40% loss in Rocky Mountains, 27% loss of salmon.  N. America 13 
31 2.4     63 of 165 rivers studied lose >10% of their fish species Globe 19 
32 2.4     Bioclimatic range of 25-57% (full dispersal) or 34-76% (no dispersal) of 5,197 plant species exceeded Sub-Saharan Africa 
33 >2.5     Sink service of terrestrial biosphere saturates and begins turning into a net carbon source Globe 55, 56 
34 2.5   2°C SST Extinction of coral reef ecosystems (overgrown by algae) Indian Ocean 
35 2.5 1.9-4.3   42% of UK land area with bioclimate unlike any currently found there; in Hampshire, declines in curlew and hawfinch and gain in yellow-necked mouse numbers; loss of montane habitat in Scotland; potential bracken invasion of Snowdonia montane areas   57 
36 2.5 2.0-3.0   Major loss of Amazon rainforest with large losses of biodiversity S. America, Globe 21, 46 
37 2.5     20-70% loss (mean 44%) of coastal bird habitat at 4 sites USA  29 
38 2.6 1.6-3.5   Most areas experience 20-34% increase in number ³7day periods with Forest Fire Weather Index >45: increased fire frequency converts forest and maquis to scrub, causing more pest outbreaks  Mediterranean  34  
39  2.6      4-21% of plants committed to extinction  Europe  1  
40  2.7      Bioclimatic envelopes exceeded leading to eventual transformation of 16% of global ecosystems: loss of 58% wooded tundra, 31% cool conifer forest, 25% scrubland, 20% grassland/steppe, 21% tundra, 21% temperate deciduous forest, 19% savanna. Ecosystems variously lose 5-66% of their areal extent. Globe 
No.  ΔTg above pre-ind ΔTg above pre-ind (range)   ΔTreg above 1990 (range)  Impacts to unique or widespread ecosystems or population systems  Region  Ref. no. 
41 2.8 1.2-4.5 1-3  Extensive loss/conversion of habitat in Kakadu wetland due to sea-level rise and saltwater intrusion Australia 10 
42 2.8 2.5-3.0   Multi-model mean 62% (range 40-100%) loss of Arctic summer ice extent, high risk of extinction of polar bears, walrus, seals; Arctic ecosystem stressed  Arctic  11,53 
43  2.8  2.3-4.6  2.1-2.5  Cloud-forest regions lose hundreds of metres of elevational extent, potential extinctions ΔTreg 2.1°C for C. America and ΔTreg 2.5°C for Africa  C. America, Tropical Africa, Indonesia 17 
44 2.8 2.1-3.1 Eventual loss of 9-62% of the mammal species from Great Basin montane areas USA  32 
45 2.8 1.9-3.8 38-54% loss of waterfowl habitat in Prairie Pothole region USA 37, 38 
46 2.9   3.2-6.6  50% loss existing tundra offset by only 5% eventual gain; millions of Arctic-nesting shorebird species variously lose up to 5-57% of breeding area; high-Arctic species most at risk; geese species variously lose 5-56% of breeding area Arctic 14 
47 2.9     Latitude of northern forest limits shifts N. by 0.5° latitude in W. Europe, 1.5° in Alaska, 2.5° in Chukotka and 4° in Greenland Arctic 40 
48 2.9 1.6-4.1   Threat of marine ecosystem disruption through loss of aragonitic pteropods  Southern Ocean 49 
49 2.9 1.6-4.1   70% reduction in deep-sea cold-water aragonitic corals Ocean basins 48 
50 2.9   2.1-3.9  21-36% of butterflies committed to extinction; >50% range loss for 83% of 24 latitudinally-restricted species Australia 1,30 
51 2.9 2.6-3.3 2.1-2.8 21-52% (mean 35%) of species committed to extinction Globe iv 
52 2.9     Substantial loss of boreal forest  China 15 
53 3.0     66 of 165 rivers studied lose >10% of their fish species Globe 19 
54 3.0 1.9-3.5   20% loss of coastal migratory bird habitat Delaware, USA 36 
55 3.1 2.3-3.7 2°C SST Extinction of remaining coral reef ecosystems (overgrown by algae) Globe  
56 3.1 1.9-4.1 3-4  Alpine systems in Alps degraded Europe 
57 3.1 2.5-4.0 2  High risk of extinction of golden bowerbird as habitat reduced by 90%  Australia 
58 3.1 1.8-4.2 3-4  Risk of extinction of alpine species  Europe 41 
59 3.3 2.0-4.5   Reduced growth in warm-water aragonitic corals by 20%-60%; 5% decrease in global phytoplankton productivity Globe 2, 47, 48 
60 3.3 2.3-3.9 2.6-2.9  Substantial loss of alpine zone, and its associated flora and fauna (e.g., alpine sky lily and mountain pygmy possum) Australia 45 
61 3.3  2.8-3.8 Risk of extinction of Hawaiian honeycreepers as suitable habitat reduced by 62-89% Hawaii 18 
62 3.3   3.7 4-38% of birds committed to extinction  Europe 
63 3.4     6-22% loss of coastal wetlands; large loss migratory bird habitat particularly in USA, Baltic and Mediterranean Globe 35, 36 
64 3.5 2.0-5.5   Predicted extinction of 15-40% endemic species in global biodiversity hotspots (case “narrow biome specificity”) Globe 50 
65 3.5 2.3-4.1 2.5 – 3.5  Loss of temperate forest wintering habitat of monarch butterfly Mexico 28 
66 3.6 2.6-4.3 Bioclimatic limits of 50% of eucalypts exceeded Australia 12 
67 3.6 2.6-3.7   30-40% of 277 mammals in 141 parks critically endangered/extinct; 15-20% endangered Africa 23 
68 3.6 3.0-3.9   Parts of the USA lose 30-57% neotropical migratory bird species richness USA 43 
69 3.7     Few ecosystems can adapt  Globe 
70 3.7     50% all nature reserves cannot fulfil conservation objectives Globe 
71 3.7     Bioclimatic envelopes exceeded leading to eventual transformation of 22% of global ecosystems; loss of 68% wooded tundra, 44% cool conifer forest, 34% scrubland, 28% grassland/steppe, 27% savanna, 38% tundra and 26% temperate deciduous forest. Ecosystems variously lose 7-74% areal extent. Globe 
72 3.9      4-24% plants critically endangered/extinct; mean species turnover of 63% (spatial range 22-90%); mean species loss of 42% (spatial range 2.5-86%)  Europe 22 
No.  ΔTg above pre-ind ΔTg above pre-ind (range)   ΔTreg above 1990 (range)  Impacts to unique or widespread ecosystems or population systems  Region  Ref. no. 
73 4.0 3.0-5.1 Likely extinctions of 200-300 species (32-63%) of alpine flora New Zealand 33 
74 >4.0   3.5 38-67% of frogs, 48-80% of mammals, 43-64% of reptiles and 49-72% of birds committed to extinction in Queensland as 85-90% of suitable habitat lost  Australia  1, 7 
75 >>4.0   5  Bioclimatic limits of 73% of eucalypts exceeded Australia 12 
76 >>4.0   5  57 endemic frogs/mammal species eventually extinct, 8 endangered  Australia 
77 >>4.0   Eventual total extinction of all endemic species of Queensland rainforest  Australia 
78 5.2     62-100% loss of bird habitat at 4 major coastal sites  USA 29 

Sources by Ref. no.: 1-Thomas et al., 2004a; 2-Hoegh-Guldberg, 1999; 3-McClean et al., 2005; 4-Hilbert et al., 2004; 5-Rutherford et al., 2000; 6-Leemans and Eickhout, 2004; 7-Williams et al., 2003; 8-Theurillat and Guisan, 2001; 9-Sheppard, 2003; 10-Eliot et al., 1999; 11-Symon et al., 2005; 12-Hughes et al., 1996; 13-Preston, 2006; 14-Zöckler and Lysenko, 2000; 15-Ni, 2001; 16-Bakkenes et al., 2002; 17-Still et al., 1999; 18-Benning et al., 2002; 19-Xenopoulos et al., 2005; 20-ECF, 2004; 21-Cox et al., 2004; 22-Thuiller et al., 2005b; 23-Thuiller et al., 2006b; 24-Midgley et al., 2002; 25-Hannah et al., 2002a; 26-Peterson et al., 2002; 27-Erasmus et al., 2002; 28-Villers-Ruiz and Trejo-Vazquez, 1998; 29-Galbraith et al., 2002; 30-Beaumont and Hughes, 2002; 31-Kerr and Packer, 1998; 32-McDonald and Brown, 1992; 33-Halloy and Mark, 2003; 34-Moriondo et al., 2006; 35-Nicholls et al., 1999; 36-Najjar et al., 2000; 37-Sorenson et al., 1998; 38-Johnson et al., 2005; 39-Broennimann et al., 2006; 40-Kaplan et al., 2003; 41-Theurillat et al., 1998; 42-Forcada et al., 2006; 43-Price and Root, 2005; 44-Siqueira and Peterson, 2003; 45-Pickering et al., 2004; 46-Scholze et al., 2006; 47-Raven et al., 2005; 48-Cox et al., 2000; 49-Orr et al., 2005; 50-Malcolm et al., 2006; 51-Peck et al., 2004; 52-Pounds et al., 2006; 53-Arzel et al., 2006; 54-Bosch et al., 2006; 55-Lucht et al., 2006; 56-Schaphoff et al., 2006; 57-Berry et al., 2005.

There is detailed information on the derivation for each entry in Table 4.1 listed in Appendix 4.1.