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APPENDIX 1. CLIMATE SCENARIOS AND BIOCLIMATIC VARIABLES Table A1-1: Representative Concentration Pathways used in analysis. ...................................................................................................................................... 129 Table A1-2: Eighteen Global Climate Models used in analysis. ................................................................................................................................................... 130 Table A1-3: Thirty-year climate coverage .................................................................................................................................................................................... 132 Table A1-4: Bioclimatic variables ................................................................................................................................................................................................. 132 128 Climate change refugia for terrestrial biodiversity
Table A1-3: Representative Concentration Pathways used in analysis. RCP Short Description Detailed Description RCP3PD Low RCP with Peak & Decline (2005-2500) RCP45 Medium-Low RCP with stabilisation from 2150 onwards (2005-2500) RCP6 Medium-High RCP with stabilisation from 2150 onwards (2005-2500) The RCP 3-PD is developed by the IMAGE modeling team of the Netherlands Environmental Assessment Agency. The emission pathway is representative for scenarios in the literature leading to very low greenhouse gas concentration levels. It is a so-called peak scenario its radiative forcing level first reaches a value around 3.1 W/m2 mid-century returning to 2.6 W/m2 by 2100. In order to reach such radiative forcing levels greenhouse gas emissions (and indirectly emissions of air pollutants) Are reduced substantially over time. The final RCP is based on the publication by Van Vuuren et al. (2007). The RCP 4.5 is developed by the MiniCAM modeling team at the Pacific Northwest National Laboratorys Joint Global Change Research Institute (JGCRI). It is a stabilization scenario where total radiative forcing is stabilized before 2100 by employment of a range of technologies and strategies for reducing greenhouse gas emissions. The scenario drivers and technology options are detailed in Clarke et al. (2007). Additional detail on the simulation of land use and terrestrial carbon emissions is given by Wise et al (2009). The RCP 6.0 is developed by the AIM modeling team at the National Institute for Environmental Studies (NIES) Japan. It is a stabilization scenario where total radiative forcing is stabilized after 2100 without overshoot by employment of a range of technologies and strategies for reducing greenhouse gas emissions. The details of the scenario are described in Fujino et al. (2006) And Hijioka et al. (2008). RCP85 High RCP The RCP 8.5 is developed by the MESSAGE modeling team and the IIASA Integrated Assessment Framework at the International Institute for Applies Systems Analysis (IIASA) Austria. The RCP 8.5 is characterized by increasing greenhouse gas emissions over time representative for scenarios in the literature leading to high greenhouse gas concentration levels. The underlying scenario drivers and resulting development path are based on the A2r scenario detailed in Riahi et al. (2007). *source: https://tntcat.iiasa.ac.at:8743/RcpDb/dsd?Action=htmlpage&page=welcome#descript Climate change refugia for terrestrial biodiversity 129
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Climate change refugia for terrestr
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Published by the National Climate C
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3.4.4 Future: current-2085 ........
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APPENDIX 3. Species distribution mo
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Figure 29: A detailed view of the p
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x Climate change refugia for terres
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EXECUTIVE SUMMARY Climate change is
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we will be in a better position to
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1.2.2 Case study 2: Pleistocene sta
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efugia meeting this latter criterio
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2.7 Conclusions Natural systems are
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highest RCP reported in the SRES (A
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3.3.4 Species data The study genera
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AUC score is negatively correlated
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Finally, we assess climate change t
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Territory, the Great Australian Big
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Figure 5: The 10 th percentile of l
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Figure 8: The absolute predicted ch
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3.4.5 Distance measures At a given
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the continent, the required movemen
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Figure 16: An example of a species
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Figure 18: Species richness for eac
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Figure 20: The number of immigrants
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Figure 22 (cont.): The ‘Immigrant
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Figure 24 (cont.): The immigrants a
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Figure 26 (cont.): The areas with t
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3.4.7.6 Areas of stability Understa
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including the Nullarbor Regional Re
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Table 2: The different classes of r
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most of the continent by 2085 that
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3.7 Gaps and future research The ne
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individual species) will respond to
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4.3.2 Topographically adjusted clim
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Tmax adj 0.5° GCM change grids (19
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Table 1: Biological groups compiled
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Invoking space-for-time substitutio
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expected to be considerably less ex
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is, the refugial analysis itself, f
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Figure 40: Refugial potential based
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Figure 43: Enlarged portion (Kimber
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Figure 46: Enlarged portion (Sydney
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Figure 48: Inclusion of areas of hi
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Figure 51: Refugial potential in th
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4.6 Gaps and future research The GD
Page 90 and 91: 5.3 Research activities and methods
Page 92 and 93: time periods to a distance calculat
Page 94 and 95: proportion of this suitability foun
Page 96 and 97: (a) Figure 54: Stability of the cli
Page 98 and 99: Figure 55: Climate and habitat suit
Page 100 and 101: Mountains in Queensland, the Eungel
Page 102 and 103: Figure 58: Areas of endemism in the
Page 104 and 105: Northern Tablellands Figure 60: Gla
Page 106 and 107: 5.6 Discussion 5.6.1 Endemism in re
Page 108 and 109: (back to 120 kya compared to LGM in
Page 110 and 111: Within each sub-region, potential e
Page 112 and 113: Table 9: Greenspot statistics for o
Page 114 and 115: drought micro-refuges, then targete
Page 116 and 117: The iterative recalculation of all
Page 118 and 119: Figure 64: Zonation conservation pr
Page 120 and 121: 7.6 Gaps and future research The co
Page 122 and 123: Figure 66: The refugia areas result
Page 124 and 125: 8.1.3 Overall lessons from the diff
Page 126 and 127: 9. GAPS AND FUTURE RESEARCH DIRECTI
Page 128 and 129: REFERENCES Ackerly, D. D., S. R. Lo
Page 130 and 131: Couper, P. J., B. Hamley, and C. J.
Page 132 and 133: Winton, A. T. Wittenberg, F. Zeng,
Page 134 and 135: A. Utteridge, J. E. Watkins, R. Wil
Page 136 and 137: R Development Core Team. 2011. R: A
Page 138 and 139: Tingley, M. W., W. B. Monahan, S. R
Page 142 and 143: Table A1-4: Eighteen Global Climate
Page 144 and 145: Table A1-5: Thirty-year climate cov
Page 146 and 147: Figure A2-68. Change in temperature
Page 148 and 149: Figure A2-70. Proportionate change
Page 150 and 151: Figure A2-72. The distance an organ
Page 152 and 153: Figure A2-74. The areas for which t
Page 154 and 155: APPENDIX 3. SPECIES DISTRIBUTION MO
Page 156 and 157: APPENDIX 4. PROJECTED SPECIES RICHN
Page 158 and 159: Figure A4-2. The species richness s
Page 160 and 161: Table of contents ABSTRACT ........
Page 162 and 163: INTRODUCTION Terrain modifies local
Page 164 and 165: RESEARCH ACTIVITIES AND METHODS Dat
Page 166 and 167: Land Cover The Geosciences Australi
Page 168 and 169: Figure A5-4: Terrain adjusted model
Page 170 and 171: RESULTS AND OUTPUTS Figures 8 and 9
Page 172 and 173: Figure A5-10 Channel Country (SW Qu
Page 174 and 175: REFERENCES ANU Fenner School of Env
Page 176 and 177: APPENDIX 6. ENVIRONMENTAL VARIABLES
Page 178 and 179: Group Short name Name Units Source
Page 180 and 181: Group Short name Name Units Source
Page 182 and 183: Data Citations Bureau of Rural Scie
Page 184 and 185: APPENDIX 7. COMPOSITIONAL TURNOVER
Page 186 and 187: Table A7-9. Vascular plant data app
Page 188 and 189: to support in house applications an
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Table A7-10. Summary of GDM model f
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Variable Group Predictor variable a
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a) c) Figure A7-78. Continental Aus
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Table A7-15. Overall relative impor
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a) c) Figure A7-92. Eastern Austral
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Table A7-18. Overall relative impor
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a) c) Figure A7-94. Tingle Mosaic s
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References Allen R, Pereira L, Raes
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APPENDIX 8. PLEISTOCENE STABILITY A
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Figure A8-3. Rainforest in the Aust
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Canis lupus dingo CANLUPU MAMM Cani
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Lampropholis mirabilis LAMMIRA REPT
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Stegonotus cucullatus STECUCU REPT
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Figure A10-1. Spatial patterns of v
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