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REFERENCES ANU Fenner School of Environment and Society and Geoscience Australia (2008). GEODATA 9 Second DEM and D8 Digital Elevation Model and Flow Direction Grid, User Guide. Geoscience Australia, 43 pp. Bastiaanssen, W.G.M., Menenti, M., Feddes, R.A. and Holtslag, A.A.M., (1998a). A remote sensing surface energy balance algorithm for land (SEBAL) - 1. Formulation. Journal of Hydrology, 213(1-4): 198-212. Bastiaanssen, W.G.M. et al., (1998b). A remote sensing surface energy balance algorithm for land (SEBAL) - 2. Validation. Journal of Hydrology, 213(1-4): 213-229. Budyko, M.I (1958) The heat balance of the earth’s surface, US Dept. Of Commerce, Washington. Budyko, M.I.(1974) Climate and life. Academic Press, New York. Bureau of Rural Sciences (2000) Digital Atlas of Australian Soils, Canberra, Department of Agriculture, Fisheries and Forestry, Australian Government. Choudhury, B.J. (1999) Evaluation of an empirical equation fro annual evaporation using field observations and results from a biophysical model. J. Hydrology 216: 99- 110. Claridge J, Williams KJ, Storey RJL (2000) Creation of the South-East Queensland depth index rescaled using CTI, Brisbane, Enhanced Resource Assessment 2000-05. A JVAP project QDN3A Technical Report. Queensland Department of Natural Resources. Delworth, T., Broccoli, Anthony J., Rosati, Anthony, Stouffer, Ronald J., Balaji, V., Beesley, John A., Cooke, William F., Dixon, Keith W. et al. (2006). GFDL's CM2 global coupled climate models—Part 1: Formulation and simulation characteristics. J. Climate 19 (5): 643–74. Donohue, R.J., McVicar, T.R. and Roderick, M.L. (2010) Assessing the ability of potential evaporation formulations to capture the dynamics in evaporative demand within a changing climate. Journal of Hydrology 386: 186–197 Donohue, R.J., Roderick, M.L, and McVicar, T.R. (2011) Assessing the differences in sensitivity of runoff to changes in climatic conditions across a large basin. Journal of Hydrology 406: 234-244 Freeman, T.G. (1991) Calculating catchment area with divergent flow based on a regular grid. Computers and Geosciences 17L 413-422. Gallant J, Austin J, Dowling T (2012) Metadata: Topographic Wetness Index (TWI), 3” resolution, derived from 1 second DEM-H. pp Page, Canberra, CSIRO Land and Water. 162 Climate change refugia for terrestrial biodiversity
Gnanadesikan, A; Dixon, Keith W.; Griffies, Stephen M.; Balaji, V.; Barreiro, Marcelo; Beesley, J. Anthony; Cooke, William F.; Delworth, Thomas L. et al. (2006). GFDL's CM2 global coupled climate models—Part 2: The baseline ocean simulation. J. Climate 19 (5): 675–97. Guerschman, J.P. et al., (2009). Scaling of potential evapotranspiration with MODIS data reproduces flux observations and catchment water balance observations across Australia. Journal of Hydrology, 369(1-2): 107-119. Jacquier D (2011a) Metadata: ASRIS 0-1m Plant Available Water Capacity (250m raster). pp Page, Canberra, CSIRO Land and Water. Kalma, J.D., McVicar, T.R. and McCabe, M.F.,( 2008). Estimating Land Surface Evaporation: A Review of Methods Using Remotely Sensed Surface Temperature Data. Surveys in Geophysics, 29 (4-5): 421-469. Lindsay, J. (2011) Whitebox Geospatial Analysis Tools. University of Guelph. http://www.uoguelph.ca/~hydrogeo/Whitebox/index.html McKenzie NJ, Jacquier DW, L.J. A, Cresswell HP (2000) Estimation of Soil Properties Using the Atlas of Australian Soils. In: CSIRO Land and Water Technical Report 11/00. pp Page, Canberra, CSIRO Land and Water. McVicar, T.R. and Jupp, D.L.B., (1999). Estimating one-time-of-day meteorological data from standard daily data as inputs to thermal remote sensing based energy balance models. Agricultural and Forest Meteorology, 96 (4): 219-238. McVicar, T.R. and Jupp, D.L.B., (2002). Using covariates to spatially interpolate moisture availability in the Murray-Darling Basin: a novel use of remotely sensed data. Remote Sensing of Environment, 79 (2-3): 199-212. McVicar, T.R. et al., (2007). Spatially distributing monthly reference evapotranspiration and pan evaporation considering topographic influences. Journal of Hydrology, 338 (3- 4): 196-220. McVicar, T.R. et al., (2008). Wind speed climatology and trends for Australia, 1975– 2006: capturing the stilling phenomenon and comparison with near-surface reanalysis output. Geophysical Research Letters 35, L20403. Pike, J.G. (1964) The estimation of annual run-off from meteorological data in a tropical climate. Journal of Hydrology, 2: 116-123. Wittenberg, A.; Rosati, Anthony; Lau, Ngar-Cheung; Ploshay, Jeffrey J. (2006). GFDL's CM2 global coupled climate models—Part 3: Tropical Pacific Climate and ENSO. J. Climate 19 (5): 698–722. Xu T, Hutchinson M. (2011). ANUCLIM 6.1 User’s Guide. Australian National University, Fenner School of Environment and Society. Climate change refugia for terrestrial biodiversity 163
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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
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5.3 Research activities and methods
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time periods to a distance calculat
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proportion of this suitability foun
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(a) Figure 54: Stability of the cli
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Figure 55: Climate and habitat suit
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Mountains in Queensland, the Eungel
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Figure 58: Areas of endemism in the
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Northern Tablellands Figure 60: Gla
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5.6 Discussion 5.6.1 Endemism in re
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(back to 120 kya compared to LGM in
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Within each sub-region, potential e
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Table 9: Greenspot statistics for o
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drought micro-refuges, then targete
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The iterative recalculation of all
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Figure 64: Zonation conservation pr
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7.6 Gaps and future research The co
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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 140 and 141: APPENDIX 1. CLIMATE SCENARIOS AND B
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 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
Page 190 and 191: Table A7-10. Summary of GDM model f
Page 192 and 193: Variable Group Predictor variable a
Page 194 and 195: a) c) Figure A7-78. Continental Aus
Page 208 and 209: Table A7-15. Overall relative impor
Page 210 and 211: a) c) Figure A7-92. Eastern Austral
Page 212 and 213: Table A7-18. Overall relative impor
Page 214 and 215: a) c) Figure A7-94. Tingle Mosaic s
Page 216 and 217: References Allen R, Pereira L, Raes
Page 218 and 219: APPENDIX 8. PLEISTOCENE STABILITY A
Page 220 and 221: Figure A8-3. Rainforest in the Aust
Page 222 and 223: 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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