Antarctic terrestrial biodiversity occurs almost exclusively in ice-free areas that cover less than 1% of the continent. Climate change will alter the extent and configuration of ice-free areas, yet the distribution and severity of these effects remain unclear. Here we quantify the impact of twenty-first century climate change on ice-free areas under two Intergovernmental Panel on Climate Change (IPCC) climate forcing scenarios using temperature-index melt modelling. Under the strongest forcing scenario, ice-free areas could expand by over 17,000 km2 by the end of the century, close to a 25% increase. Most of this expansion will occur in the Antarctic Peninsula, where a threefold increase in ice-free area could drastically change the availability and connectivity of biodiversity habitat. Isolated ice-free areas will coalesce, and while the effects on biodiversity are uncertain, we hypothesize that they could eventually lead to increasing regional-scale biotic homogenization, the extinction of less-competitive species and the spread of invasive species.
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This project was supported by the Holsworth Wildlife Research Endowment – Equity Trustees Charitable Foundation, the Australian Antarctic Science Program (projects 4296 and 4297) and the Ecological Society of Australia. I.C. was supported by a CSIRO Julius Career award, and R.A.F. by an Australian Research Council Future Fellowship. The contribution of T.J.B. was funded as part of the Polar Science for Planet Earth programme of the British Antarctic Survey with additional support from the SCAR (Scientific Committee for Antarctic Research) AntClim21 (Antarctic Climate in the 21st Century) SRP (Scientific Research Programme). We thank J. Rhodes, S. Robinson, A. Fraser, M. Stafford Smith and A. Richardson for discussions and valuable feedback on this project. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output (listed in Supplementary Table 5 of this paper). For CMIP the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We thank the National Centre for Atmospheric Research, the University Corporation for Atmospheric Research and the Byrd Polar and Climate Research Center who are responsible for AMPS and the European Centre for Medium-Range Weather Forecasts who are responsible for the ERA-interim reanalysis data. The Antarctic coastline spatial layer used in the figures was downloaded from the Antarctic Digital Database (ADD Version 7; http://www.add.scar.org).
The authors declare no competing financial interests.
Reviewer Information Nature thanks N. Golledge, B. van Vuuren and the other anonymous reviewer(s) for their contribution to the peer review of this work.
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Extended data figures and tables
Extended Data Figure 1 Projected 21st century climate change in Antarctica between 2014 and 2098 under RCP4.5.
a, Change in degree days. b, Change in precipitation rate (mm per year). c, Projected melt (m) using mean melt coefficients. RCP climate forcing scenarios were derived from the IPCC Fifth Assessment Report (AR5), see Methods. Maps have been generated from original data and the Antarctic coastline file downloaded from the Antarctic Digital Database (ADD Version 7; http://www.add.scar.org).
Extended Data Figure 2 New Antarctic ice-free area (km2) predicted to emerge between 2014 and 2098 under climate forcing scenario RCP4.5.
Mean melt coefficients used to determine the melt rate. Grid cell resolution is 50 km in the continental map and 10 km in the Antarctic Peninsula inset. Maps have been generated from original data and the Antarctic coastline file downloaded from the Antarctic Digital Database (ADD Version 7; http://www.add.scar.org).
Extended Data Figure 3 Current and future ice-free area (km2) in each Antarctic Conservation Biogeographic Region.
Estimates of future ice-free area are provided for three different climate change scenarios (RCP2.6, RCP4.5, RCP8.5), using full-ensemble ER mean models. Bars represent total area using the mean ice-melt coefficients, while error bars represent the lower and upper bounds, respectively (total projected ice-free area using the lowest and highest ice melt coefficients; see Methods).
Extended Data Figure 4 Ice-free area metrics for Antarctic Conservation Biogeographic Region 3a (North Antarctic Peninsula).
Metrics provided under current climate conditions (C) and two different RCP scenarios (4.5, 8.5). a, Mean area of ice-free patches (km2). b, Total ice-free area (km2). c, Number of ice-free patches. d, Mean distance to nearest neighbour (NN; metres). Mid-line on box represents the mean ice melt coefficient, while bottom of box represents lower bound, top of box represents upper bound, and error bars represent standard error of the mean (n = 12,638 ice-free areas, see ACBR 3a in Supplementary Tables 1 and 2).
Simple overview of the methods used to model changes in distribution and size of Antarctic ice-free areas at the end of the 21st century.
a–c, 2014 (a), 2015 (b) and 2014–2015 (c). The anomalies are relative to the period 1979 through 2015. The source of the data is the ECMWF ERA interim re-analysis (ref. 57).
This file contains Supplementary Tables 1-4 (Ice-free area metric ANOVA tables), Supplementary Table 5 (List of CMIP5 models used in this study), Supplementary Tables 7 and 8 (Melt factor and radiation coefficient values obtained from the literature), and Supplementary Table 9 (Description of ice-free area metrics). (PDF 208 kb)
This table contains degree day factor (DDF) values obtained from the literature. (XLSX 16 kb)
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Lee, J., Raymond, B., Bracegirdle, T. et al. Climate change drives expansion of Antarctic ice-free habitat. Nature 547, 49–54 (2017). https://doi.org/10.1038/nature22996
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