Four degrees and beyond: the potential for a global ... - Amper

More documents

Recommendations

Info

146 P. Zelazowski et al. Table 1. Explanatory power of climate-related variables in terms of the distribution of four major vegetation types across the tropics: HTFs, other forests, dense shrubs and herbs and sparse shrubs and herbs. For each region, the first value is the RMSE of the actual versus predicted probability of HTFs across the variable gradient. The second value (s.d.) is deviance, and it concerns all four vegetation types (low value for dry-season length is because of its very low resolution). The presented ranking was done through averaging of regional RMSE-based ranks. See the electronic supplementary material for the actual and modelled probabilities of vegetation-type occurrence. performance as a driver for biome distribution Americas Africa Asia no. climate-related variable RMSE s.d. RMSE s.d. RMSE s.d. 1 MCWDHTF 0.0769 2.73 0.0304 3.93 0.0448 7.38 2 perhumidity index 0.0784 4.47 0.0312 3.65 0.0433 8.07 3 MCWD100 0.0763 5.09 0.0320 2.97 0.0495 7.98 4 precipitation of driest month 0.0533 1.70 0.0253 0.48 0.0886 3.30 5 dry-season length 0.0515 2.14 0.0391 2.74 0.0813 2.49 6 annual precipitation 0.0602 4.24 0.0562 3.72 0.0611 6.92 7 precipitation seasonalitya 0.0474 2.12 0.0327 5.06 0.1047 7.44 8 annual-temperature rangeb 0.0851 4.51 0.0379 2.90 0.0459 5.38 9 precipitation of driest quarter 0.0590 1.91 0.0214 0.73 0.1060 3.19 10 annual monthly temperature range 0.0987 3.45 0.0566 7.24 0.0520 6.22 11 precipitation of wettest month 0.0485 4.45 0.0770 6.44 0.1350 7.39 12 isothermalityc 0.0633 3.09 0.0394 8.30 0.1128 17.71 13 precipitation of wettest quarter 0.0503 4.54 0.0840 7.44 0.1556 8.81 14 maximum temperature of warmest month 0.0845 2.66 0.1003 8.81 0.0820 7.43 15 16 MCWDET mean diurnal temperature range 0.0572 3.83 0.0848 10.56 0.1665 9.52 d 0.0825 5.45 0.1198 5.30 0.0644 4.78 17 temperature seasonalitye 0.1266 5.01 0.0578 5.45 0.0652 6.97 18 mean temperature of wettest quarter 0.0931 3.13 0.1039 11.58 0.0782 5.79 19 precipitation of warmest quarter 0.0648 3.16 0.1535 12.80 0.0856 4.31 20 mean temperature of warmest quarter 0.0870 2.88 0.1150 11.35 0.0930 4.20 21 minimum temperature of coldest month 0.0895 4.69 0.1020 6.40 0.1336 11.01 22 annual mean temperature 0.1171 4.94 0.1526 12.82 0.0643 4.67 23 maximum mean temperature of warmest month 0.1334 5.74 0.1082 10.88 0.0902 7.13 24 minimum mean temperature of coldest month 0.1024 4.45 0.1093 13.31 0.2311 17.55 25 annual evapotranspiration (as in MCWDHTF) 0.1672 7.47 0.1196 12.47 0.0971 4.94 26 mean temperature of coldest quarter 0.1040 4.34 0.1149 12.20 0.2414 17.86 27 precipitation of coldest quarter 0.1354 5.45 0.2343 11.98 0.0937 3.92 28 mean temperature of driest quarter 0.1120 4.51 0.1230 8.55 0.1907 11.36 29 annual evapotranspiration (as in MCWDET) 0.1125 7.39 0.1513 20.05 0.2440 22.50 aCoefficient of variation. bMaximum temperature of warmest month − minimum temperature of coldest month. c (Mean diurnal range/annual-temperature range) × 100. dMean of monthly (maximum mean temperature of warmest month − minimum mean temperature of coldest month). eStandard deviation of monthly temperature series × 100. Phil. Trans. R. Soc. A (2011) Downloaded from rsta.royalsocietypublishing.org on November 30, 2010
Humid tropical forests on a warmer planet 147 The simple outline of the HTF niche (figure 2b), defined by one threshold of MCWD100 (−350 mm; about 50 mm lower than in Malhi et al. [12]) and one of annual precipitation (1500 mm), was found to be a good predictor for the majority of current HTFs distribution. It is apparent that both the MCWD100 and precipitation thresholds are useful (i.e. a logical AND combination of both thresholds). Consideration of the MCWD100 threshold alone would cause overprediction of HTF extent in southern Brazil and West and Central Africa (regions with sufficiently weak dry seasons but insufficient recharge in the weak wet season: red zones in figure 2b), and consideration of the precipitation threshold alone would cause over-prediction in southeastern Amazonia and peninsular southeast Asia (regions with annual precipitation but very strong dry seasons: light blue zones in figure 2b). Therefore, the use of the overlap of the two index-based domains limits their individual shortfalls and makes the potential HTF niche more conservative. This contrasts with the analysis of Malhi et al. [12] for Amazonia, which used a logical OR combination of both the thresholds, with either threshold being sufficient for HTFs. Nevertheless, there were a few regions where HTF extent is over-predicted (purple zones in figure 2b), in particular, northwest Amazonia (Colombia and Venezuela) with parts of southern Brazil, and the southwest Congo Basin. The South American mismatch zones partially correspond to seasonal wetlands (the Llanos) where poor surface drainage may prevent HTFs occurrence. The under-prediction in the southwest Congo Basin may be accounted for by radiation: this region has a very cloudy dry season, and hence water demand may be lower than our global analysis indicates—the cloud cover may allow HTFs to persist in drier rainfall regimes than otherwise possible. Deforestation may also be a factor in explaining discrepancies between predicted and observed extent, something very apparent in insular southeast Asia. Overall, the MCWD100- and annual precipitation-based definition appears to be an adequate descriptor of the current spatial extent of HTFs, and was used as a basis for the assessment of the future extent at global warming of 2 ◦ C and 4 ◦ C. (b) Changes in the climatological niche at global warming of 2 ◦ C and 4 ◦ C Global warming is expected to alter both the rainfall and temperature regimes, but prognoses for variables that appeared here as important are not equally robust. The predicted changes in precipitation vary between AOGCMs more than the changes in temperature, both in terms of the magnitude and direction of change (table 2), but also the spatial and seasonal distribution, which is of relevance to both annual precipitation and water stress. Future decreases in precipitation over HTFs of tropical Americas are predicted by seven of the analysed models (approx. 41%), including the well-known extreme scenario from the HadCM3 model. In contrast, precipitation in the other two regions is consistently predicted to increase. The mean rainfall change for each contemporary HTF region at +2 ◦ C of global warming is −4, +42 and +73 mm yr −1 for South America, Africa and Asia, respectively, and more than twice these amounts at +4 ◦ C(table 2). However, the mean change in water stress is greater in tropical Asia than in Africa, owing to differences in the spatial and seasonal distribution of rainfall change predicted by different AOGCMs. Phil. Trans. R. Soc. A (2011) Downloaded from rsta.royalsocietypublishing.org on November 30, 2010
Page 1 and 2:
ISSN 1364-503X volume 369 number 19
Page 3 and 4:
Phil. Trans. R. Soc. A (2011) 369,
Page 5 and 6:
Editorial David Garner Phil. Trans.
Page 7 and 8:
Four degrees and beyond: the potent
Page 9 and 10:
Preface 5 commitments might give us
Page 11 and 12:
Downloaded from rsta.royalsocietypu
Page 13 and 14:
8 M. New et al. In the final plenar
Page 15 and 16:
10 M. New et al. supports the messa
Page 17 and 18:
12 M. New et al. Table 1. Impacts a
Page 19 and 20:
14 M. New et al. actors (NNSAs)—r
Page 21 and 22:
16 M. New et al. as permanent crop
Page 23 and 24:
18 M. New et al. 24 Boe, J. L., Hal
Page 25 and 26:
Beyond 'dangerous' climate change:
Page 27 and 28:
Beyond dangerous climate change 21
Page 29 and 30:
Page 31 and 32:
Page 33 and 34:
(i) Energy and industrial process e
Page 35 and 36:
Page 37 and 38:
Page 39 and 40:
(a) 50 (b) GtCO 2e yr -1 40 30 20 1
Page 41 and 42:
Table 1. Summary of scenario pathwa
Page 43 and 44:
Page 45 and 46:
Page 47 and 48:
Page 49 and 50:
Page 51 and 52:
Cumulative carbon emissions, emissi
Page 53 and 54:
46 N. H. A. Bowerman et al. althoug
Page 55 and 56:
48 N. H. A. Bowerman et al. a likel
Page 57 and 58:
50 N. H. A. Bowerman et al. (b) Mod
Page 59 and 60:
52 N. H. A. Bowerman et al. In most
Page 61 and 62:
54 N. H. A. Bowerman et al. rates o
Page 63 and 64:
56 N. H. A. Bowerman et al. (a) pea
Page 65 and 66:
58 N. H. A. Bowerman et al. We can
Page 67 and 68:
60 N. H. A. Bowerman et al. (a) rel
Page 69 and 70:
62 N. H. A. Bowerman et al. (a) 0.3
Page 71 and 72:
64 N. H. A. Bowerman et al. 4. Conc
Page 73 and 74:
66 N. H. A. Bowerman et al. increas
Page 75 and 76:
Page 77 and 78:
emissions (GtC) Review. Global warm
Page 79 and 80:
Review. Global warming reaching 4
Page 81 and 82:
Page 83 and 84:
global surface warming (°C) 6 5 4
Page 85 and 86:
Page 87 and 88:
temperature (relative to 1861-1890
Page 89 and 90:
°C above pre-industrial 8 7 6 5 4
Page 91 and 92:
Page 93 and 94:
Regional temperature and precipitat
Page 95 and 96:
86 M. G. Sanderson et al. technical
Page 97 and 98:
88 M. G. Sanderson et al. Table 1.
Page 99 and 100:
90 M. G. Sanderson et al. (a) 90°
Page 101 and 102:
92 M. G. Sanderson et al. An area o
Page 103 and 104:
94 M. G. Sanderson et al. South Ame
Page 105 and 106:
96 M. G. Sanderson et al. For DJF (
Page 107 and 108: 98 M. G. Sanderson et al. 12 Betts,
Page 109 and 110: Downloaded from rsta.royalsocietypu
Page 111 and 112: Water availability in +2 ◦ C and
Page 113 and 114: (ii) Water stress index Water avail
Page 115 and 116: (b) (c) (d) (a) Water availability
Page 119 and 120: (a) number of models, black line nu
Page 121 and 122: change in run-off (%) change in run
Page 127 and 128: Agriculture and food systems in sub
Page 129 and 130: 118 P. K. Thornton et al. 1. Introd
Page 131 and 132: 120 P. K. Thornton et al. increases
Page 133 and 134: 122 P. K. Thornton et al. Table 1.
Page 135 and 136: 124 P. K. Thornton et al. century.
Page 137 and 138: 126 P. K. Thornton et al. and polit
Page 139 and 140: 128 P. K. Thornton et al. — The r
Page 141 and 142: 130 P. K. Thornton et al. keepers i
Page 143 and 144: 132 P. K. Thornton et al. 3 Frayne,
Page 145 and 146: 134 P. K. Thornton et al. 41 Erikse
Page 147 and 148: 136 P. K. Thornton et al. 83 Challi
Page 149 and 150: Downloaded from rsta.royalsocietypu
Page 151 and 152: Humid tropical forests on a warmer
Page 153 and 154: (a) Humid tropical forests on a war
Page 157: Humid tropical forests on a warmer
Page 161 and 162: 0 retraction risk 17 120 80 40 (a)
Page 165 and 166: 0 retraction risk 17 120 80 40 0
Page 173 and 174: Sea-level rise and its possible imp
Page 175 and 176: 162 R. J. Nicholls et al. expected.
Page 177 and 178: 164 R. J. Nicholls et al. sea-level
Page 179 and 180: 166 R. J. Nicholls et al. mean temp
Page 181 and 182: 168 R. J. Nicholls et al. interglac
Page 183 and 184: 170 R. J. Nicholls et al. discussed
Page 185 and 186: 172 R. J. Nicholls et al. land loss
Page 187 and 188: 174 R. J. Nicholls et al. global ad
Page 189 and 190: 176 R. J. Nicholls et al. Hence, th
Page 191 and 192: 178 R. J. Nicholls et al. to climat
Page 193 and 194: 180 R. J. Nicholls et al. 43 Pardae
Page 195 and 196: Climate-induced population displace
Page 209 and 210:
Climate-induced population displace
Page 211 and 212:
Page 213 and 214:
198 M. Stafford Smith et al. the di
Page 215 and 216:
200 M. Stafford Smith et al. greate
Page 217 and 218:
202 M. Stafford Smith et al. Table
Page 219 and 220:
204 M. Stafford Smith et al. (c) Go
Page 221 and 222:
206 M. Stafford Smith et al. mean g
Page 223 and 224:
208 M. Stafford Smith et al. These
Page 225 and 226:
210 M. Stafford Smith et al. consid
Page 227 and 228:
212 M. Stafford Smith et al. — De
Page 229 and 230:
214 M. Stafford Smith et al. 12 Lem
Page 231 and 232:
216 M. Stafford Smith et al. 51 Ste
Page 233 and 234:
REVIEW Phil. Trans. R. Soc. A (2011
Page 235 and 236:
Review. Interactions in a 4 ◦ C w
Page 237 and 238:
Page 239 and 240:
spread in mosquitoborne disease may
Page 241 and 242:
[89,94,95] further acidification by
Page 243 and 244:
Page 245 and 246:
Page 247 and 248:
Page 249 and 250:
Page 251 and 252:
Page 253 and 254:
Page 255 and 256:
Page 257 and 258:
Page 259:
Editorial Editorial 3 D. Garner Pre
show all

Four degrees and beyond: the potential for a global ... - Amper

Create successful ePaper yourself

Delete template?

Save as template?