Williams-Climate-change-refugia-for-terrestrial-biodiversity_0

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Invoking space-for-time substitution, a fitted GDM model can also be used to predict the compositional similarity between a given location i in the present and this same location in the future under a given climate scenario:
• a sample of 20 000 cells within a radius of 100 km of cell i with these cells selected randomly according to a half-Cauchy distribution (Shaw 1995) with a mean dispersal distance of 10 km • as for the previous sample but with a mean dispersal distance of 50 km. Figure 36: The two types of predicted compositional similarities used to calculate refugial potential for a given grid-cell i under a given climate scenario: in red, predicted similarities, in the future, between cell i and each of n cells within a surrounding radius; and in blue, predicted similarities between cell i under future environmental conditions and each of the same n cells under present conditions. This particular measure of refugial potential assesses the extent to which a given location is predicted to exhibit an environment in the future (i.e. under a given climate scenario) that is likely to have undergone a marked proportional reduction in extent, and will be relatively rare throughout the surrounding landscape as a result of climate change (note that the squared denominator in the above formula results from dividing the proportional reduction in extent by the extent remaining in the future). This general concept is illustrated in Figure 34 in which, for ease of explanation, both geographical space and environmental space have been simplified to a single dimension each (the geographical dimension can be thought of as a straight-line transect across a landscape, whereas the environmental dimension can be thought of as a bioticallyscaled temperature gradient). The concentric ellipses centred on each of the labelled locations depict decreasing levels of compositional similarity with increasing distance from a location in biotically scaled environmental space, and decreasing likelihood of dispersal with increasing distance in geographical space. A visual impression of the refugial potential of each of the labelled locations (A to E) can be obtained by comparing the extent to which the concentric ellipses, centred on the future environment of that location, overlap with current environments in the surrounding landscape versus the extent of overlap with future environments in the same landscape. For example, the future environment at location B (think of this as situated on a flat plain surrounded by an expanse of similar elevation, and therefore temperature) is expected to be much more extensive in the surrounding landscape under climate change than it is at present, and this location therefore has very low refugial potential. In contrast, the future environment of location E (a mountain peak) is Climate change refugia for terrestrial biodiversity 61
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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
Page 22 and 23: 2.7 Conclusions Natural systems are
Page 24 and 25: highest RCP reported in the SRES (A
Page 26 and 27: 3.3.4 Species data The study genera
Page 28 and 29: AUC score is negatively correlated
Page 30 and 31: Finally, we assess climate change t
Page 32 and 33: Territory, the Great Australian Big
Page 34 and 35: Figure 5: The 10 th percentile of l
Page 36 and 37: Figure 8: The absolute predicted ch
Page 38 and 39: 3.4.5 Distance measures At a given
Page 40 and 41: the continent, the required movemen
Page 42 and 43: Figure 16: An example of a species
Page 44 and 45: Figure 18: Species richness for eac
Page 46 and 47: Figure 20: The number of immigrants
Page 48 and 49: Figure 22 (cont.): The ‘Immigrant
Page 50 and 51: Figure 24 (cont.): The immigrants a
Page 52 and 53: Figure 26 (cont.): The areas with t
Page 54 and 55: 3.4.7.6 Areas of stability Understa
Page 56 and 57: including the Nullarbor Regional Re
Page 58 and 59: Table 2: The different classes of r
Page 60 and 61: most of the continent by 2085 that
Page 62 and 63: 3.7 Gaps and future research The ne
Page 64 and 65: individual species) will respond to
Page 66 and 67: 4.3.2 Topographically adjusted clim
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Page 70 and 71: Table 1: Biological groups compiled
Page 74 and 75: expected to be considerably less ex
Page 76 and 77: is, the refugial analysis itself, f
Page 78 and 79: Figure 40: Refugial potential based
Page 80 and 81: Figure 43: Enlarged portion (Kimber
Page 82 and 83: Figure 46: Enlarged portion (Sydney
Page 84 and 85: Figure 48: Inclusion of areas of hi
Page 86 and 87: Figure 51: Refugial potential in th
Page 88 and 89: 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
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Figure 66: The refugia areas result
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8.1.3 Overall lessons from the diff
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9. GAPS AND FUTURE RESEARCH DIRECTI
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REFERENCES Ackerly, D. D., S. R. Lo
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Couper, P. J., B. Hamley, and C. J.
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Winton, A. T. Wittenberg, F. Zeng,
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A. Utteridge, J. E. Watkins, R. Wil
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R Development Core Team. 2011. R: A
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Tingley, M. W., W. B. Monahan, S. R
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APPENDIX 1. CLIMATE SCENARIOS AND B
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Table A1-4: Eighteen Global Climate
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Table A1-5: Thirty-year climate cov
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Figure A2-68. Change in temperature
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Figure A2-70. Proportionate change
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Figure A2-72. The distance an organ
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Figure A2-74. The areas for which t
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APPENDIX 3. SPECIES DISTRIBUTION MO
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APPENDIX 4. PROJECTED SPECIES RICHN
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Figure A4-2. The species richness s
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Table of contents ABSTRACT ........
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INTRODUCTION Terrain modifies local
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RESEARCH ACTIVITIES AND METHODS Dat
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Land Cover The Geosciences Australi
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Figure A5-4: Terrain adjusted model
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RESULTS AND OUTPUTS Figures 8 and 9
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Figure A5-10 Channel Country (SW Qu
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REFERENCES ANU Fenner School of Env
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APPENDIX 6. ENVIRONMENTAL VARIABLES
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Group Short name Name Units Source
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Group Short name Name Units Source
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Data Citations Bureau of Rural Scie
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APPENDIX 7. COMPOSITIONAL TURNOVER
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Table A7-9. Vascular plant data app
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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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