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

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Figure 66: The refugia areas resulting from the species distribution modelling analyses (left: SDM refugia) from section 3.4.4 and the generalised dissimilarity modelling (right: GDM refugia) from section 4 for comparison. Differences in the spatial predictions for refugia using the different techniques are also expected given the differences in the input data used: different taxa will use different refuges. Additionally, different input climate data were used for projecting future outcomes: the SDM were projected to each GCM and then a median output was generated for examination, while the GDM was projected using specific GCMs. The GDM approach had the advantage of using finer resolution data. The SDM approach also had the advantage of projecting the outcomes for individual species, which can be valuable for informing conservation prioritisation analysis such as that used in Case study 4. 8.1.2 Comparison of the different methods for a case study area Most of the primary analytical techniques (except for ‘greenspot’ modelling of drought refugia) are represented in the AWT bioregion (species distribution modelling, generalised dissimilarity modelling, evolutionary refugia modelling and Zonation). This allows for direct comparison of techniques within a common geographically defined region. A detailed map of the subregions for the AWT region can be found in Figure 2 of Williams (2006). The comparison shows that while there are some differences, there is good spatial congruence for the important refugia areas. In particular, the upland areas in the north (Carbine, Windsor, Thornton), central (Bellenden-Ker/Bartle-Frere, Lamb and Herberton ranges) and south (Spec and Elliot) are all represented by each of the four techniques (Figure 64). These upland areas are recognised as conservation hotspots, being centres of evolution and containing endemic species (Williams 1996). Differences across the techniques in this comparison can be found either side of the uplands. The SDM results favour the inland (western) area which is the transition zone from rainforest to sclerophyll forest. The SDM refugia would probably have mirrored the Zonation results if the detailed, fine resolution SDMs were used for the AWT region, with a stronger focus on the subset of rainforest-dependent species (Williams et al. 2003, Williams et al. 2010). The differences in the SDM approach in comparison to the others are almost certainly because this approach focusses on areas that will act as refuges for immigrating species: in this case species moving uphill from the lowland areas of the western slopes. Additionally, the SDM results do not account for endemism, or for specific habitats (e.g. rainforest endemics). The GDM results particularly highlight the upland areas, and the evolutionary refugia and Zonation results emphasise some coastal regions including the Daintree, which is not as well represented by the other techniques. The current protected areas largely encompass 110 Climate change refugia for terrestrial biodiversity
the refugial areas predicted by the GDM, evolutionary refugia and Zonation; however, large areas of refugia predicted by the SDM approach fall outside the current protected areas. The southern Atherton Tablelands contains the largest tract of upland rainforest and has some of the highest diversity and abundance of rainforest species, as well as high productivity. This region was well-represented by the Zonation analysis, and by the evolutionary refugia, but under-represented by the two Australia-wide analyses (GDM and SDM). In contrast, the northern uplands of Windsor and Carbine Uplands gain particularly high refugia status across all techniques (Moritz et al. 2005). In the case of Windsor, it is currently moderately depauperate in comparison to other upland areas, with a fauna that is likely to have been recolonised after rainforest contractions in the past. It is also likely to be particularly vulnerable to changes in future rainfall, which is difficult to predict given the uncertainty around future rainfall projections. The southern upland rainforest of the AWT, particularly Hinchinbrook Island, Paluma Range and Mt Elliot, come out as important refugia across all techniques. Mt Elliot is the southernmost upland area of the AWT, has three endemic vertebrates, and is the southern outlier for many rainforest species distributions. Despite the importance of Mt Elliot for its endemics, these southern upland regions are all relatively depauperate and lack the current diversity found in the extensive tracts of rainforest of the Atherton Tablelands. The analyses containing future projections (SDM, GDM and Zonation) are likely to all emphasise the importance of upland areas, even if current diversity is low, because the upland areas hold high potential for species currently at lower elevations to move into. The evolutionary refugia are also concentrated at high elevations in most regions, indicating their importance as refugia from past climate change. Despite the differences, the congruence across techniques gives us confidence that the techniques used in this study are able to point to high value refugia. Figure 67: Comparison of techniques for a common region, the AWT bioregion of north-east Queensland. a) the SDM refugia analyses from section 3.4.4; b) the GDM refugia analyses from section 4.4.2; c) the evolutionary refugia from section 5.5; all compared to d) the Zonation analysis from section 7.4; and e) the current protected areas within this region. Climate change refugia for terrestrial biodiversity 111
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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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Page 104 and 105: Northern Tablellands Figure 60: Gla
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Page 110 and 111: Within each sub-region, potential e
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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
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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
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Page 170 and 171: 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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