Abstract
Ecological and societal disruptions by modern climate change are critically determined by the time frame over which climates shift beyond historical analogues. Here we present a new index of the year when the projected mean climate of a given location moves to a state continuously outside the bounds of historical variability under alternative greenhouse gas emissions scenarios. Using 1860 to 2005 as the historical period, this index has a global mean of 2069 (±18 years s.d.) for near-surface air temperature under an emissions stabilization scenario and 2047 (±14 years s.d.) under a ‘business-as-usual’ scenario. Unprecedented climates will occur earliest in the tropics and among low-income countries, highlighting the vulnerability of global biodiversity and the limited governmental capacity to respond to the impacts of climate change. Our findings shed light on the urgency of mitigating greenhouse gas emissions if climates potentially harmful to biodiversity and society are to be prevented.
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Acknowledgements
We thank D. Beilman for commenting on the paper; E. Wingert for help on the figures; D. Olsen for technical support; H. Kreft and the International Union for Conservation of Nature, BirdLife International, the Food and Agriculture Organization of the United Nations, the World Bank Database, the National Centers for Environmental Prediction, the World Database of Protected Areas, and the Gridded Human Population of the World Database for making their data openly available. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP5, and we thank the climate modelling groups (listed in Extended Data Table 1) for producing and making available their model outputs. This work was made possible by funding from the University of Hawai‘i Sea Grant to C.M. The paper was developed as part of the graduate course on ‘Methods for Large Scale Analyses’ in the Department of Geography, University of Hawai‘i at Mānoa. A.G.F. and T.W.G were supported by Pacific Islands Climate Change Cooperative (PICCC) award F10AC00077 and National Science Foundation Hawai‘i EPSCoR grant no. EPS-0903833. R.J.L. was supported by the Pacific Islands Climate Science Center and PICCC award F10A00079. R.S.D. and E.J.T. were supported by National Science Foundation Graduate Fellowships, and I.F.-S. by a postdoctoral fellowship from the Japanese Society for the Promotion of Science.
Author information
Affiliations
Department of Geography, University of Hawai‘i at Mānoa, Honolulu, Hawai‘i 96822, USA
- Camilo Mora
- , Abby G. Frazier
- , Ryan J. Longman
- , Joseph J. Sanchez
- , Lauren R. Kaiser
- , Yuko O. Stender
- , Louise M. Giuseffi
- & Thomas W. Giambelluca
Department of Biology, University of Hawai‘i at Mānoa, Honolulu, Hawai‘i 96822, USA
- Rachel S. Dacks
- , Maya M. Walton
- , James M. Anderson
- & Christine M. Ambrosino
Hawai‘i Institute of Marine Biology, University of Hawai‘i at Mānoa, Kāne‘ohe, Hawai‘i 96744, USA
- Maya M. Walton
- , Eric J. Tong
- , Yuko O. Stender
- , James M. Anderson
- , Christine M. Ambrosino
- & Iria Fernandez-Silva
Department of Oceanography, University of Hawai‘i at Mānoa, Honolulu, Hawai‘i 96822, USA
- Eric J. Tong
Trans-disciplinary Organization for Subtropical Island Studies (TRO-SIS), University of the Ryukyus, Senbaru, Nishihara, Okinawa 903-0213, Japan
- Iria Fernandez-Silva
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Contributions
All authors contributed equally to conceive the study, compile the data, conduct analyses, and write the manuscript.
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The authors declare no competing financial interests.
Corresponding author
Correspondence to Camilo Mora.
Extended data
Extended data figures
- 1.
Evaluating robustness of Earth System Models.
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Multi-model uncertainty in the projected timing of climate departure.
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Sea surface temperature and projected timing of climate departure.
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Projected timing of climate departure for different climate variables.
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Biodiversity hotspots.
- 6.
Average gross domestic product (US$) per person for countries where the world’s biodiversity hotspots are located.
Extended data tables
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