Articles | Volume 19, issue 7
https://doi.org/10.5194/bg-19-1913-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-19-1913-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Examining the role of environmental memory in the predictability of carbon and water fluxes across Australian ecosystems
ARC Centre of Excellence for Climate Extremes, Sydney, NSW 2052, Australia
Climate Change Research Centre, University of New South Wales, Sydney, NSW 2052, Australia
Martin G. De Kauwe
School of Biological Sciences, University of Bristol, 24 Tyndall Avenue, Bristol, BS8 1TQ, UK
ARC Centre of Excellence for Climate Extremes, Sydney, NSW 2052, Australia
Climate Change Research Centre, University of New South Wales, Sydney, NSW 2052, Australia
Gab Abramowitz
ARC Centre of Excellence for Climate Extremes, Sydney, NSW 2052, Australia
Climate Change Research Centre, University of New South Wales, Sydney, NSW 2052, Australia
Jamie Cleverly
Terrestrial Ecosystem Research Network, College of Science and Engineering, James Cook University, Cairns, QLD 4870, Australia
Nina Hinko-Najera
School of Ecosystem and Forest Sciences, The University of Melbourne, 4 Water Street, Creswick, VIC 3363, Australia
Mark J. Hovenden
Biological Sciences, School of Natural Sciences, University of Tasmania, Hobart, TAS 7005, Australia
Yao Liu
Department of Geography and Environmental Sciences, Northumbria University, Newcastle upon Tyne, NE1 8ST, UK
Andy J. Pitman
ARC Centre of Excellence for Climate Extremes, Sydney, NSW 2052, Australia
Climate Change Research Centre, University of New South Wales, Sydney, NSW 2052, Australia
Kiona Ogle
School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, Arizona 86011, USA
Model code and software
Model and Analysis Code Jon Cranko Page https://github.com/JDCP93/OzFlux_SAM
OzFlux_SAM J. Cranko Page, M. G. De Kauwe, G. Abramowitz, Y. Liu, and K. Ogle https://doi.org/10.5281/zenodo.6361060
Short summary
Although vegetation responds to climate at a wide range of timescales, models of the land carbon sink often ignore responses that do not occur instantly. In this study, we explore the timescales at which Australian ecosystems respond to climate. We identified that carbon and water fluxes can be modelled more accurately if we include environmental drivers from up to a year in the past. The importance of antecedent conditions is related to ecosystem aridity but is also influenced by other factors.
Although vegetation responds to climate at a wide range of timescales, models of the land carbon...
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