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.
Research article
| 
05 Apr 2022
Research article |
| 05 Apr 2022
| 05 Apr 2022
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
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- Empirical upscaling of OzFlux eddy covariance for high-resolution monitoring of terrestrial carbon uptake in Australia C. Burton et al. 10.5194/bg-20-4109-2023
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12 citations as recorded by crossref.
- Sub-seasonal forest carbon dynamics lose persistence under extremes T. Williams et al. 10.1088/1748-9326/ade8ff
- Carbon and water fluxes are more responsive to water restriction in grassland than in forest ecosystem in the semiarid Loess Plateau, China Y. Zhou et al. 10.1016/j.catena.2025.109344
- Modeling Terrestrial Net Ecosystem Exchange Based on Deep Learning in China Z. Chen et al. 10.3390/rs17010092
- Empirical upscaling of OzFlux eddy covariance for high-resolution monitoring of terrestrial carbon uptake in Australia C. Burton et al. 10.5194/bg-20-4109-2023
- Land cover and management effects on ecosystem resistance to drought stress C. Xiao et al. 10.5194/esd-14-1211-2023
- Importance of the memory effect for assessing interannual variation in net ecosystem exchange W. Liu et al. 10.1016/j.agrformet.2023.109691
- Ecosystem Resilience Monitoring and Early Warning Using Earth Observation Data: Challenges and Outlook S. Bathiany et al. 10.1007/s10712-024-09833-z
- Non‐Stationary Lags and Legacies in Ecosystem Flux Response to Antecedent Rainfall J. Cranko Page et al. 10.1029/2022JG007144
- Variability and uncertainty in flux-site-scale net ecosystem exchange simulations based on machine learning and remote sensing: a systematic evaluation H. Shi et al. 10.5194/bg-19-3739-2022
- Importance of the antecedent environmental factors’ memory effects on the temporal variation of terrestrial gross primary productivity W. Liu et al. 10.1016/j.ecolind.2025.113558
- Winter climate preconditioning of summer vegetation extremes in the Northern Hemisphere M. Anand et al. 10.1088/1748-9326/ad627d
- Are Plant Functional Types Fit for Purpose? J. Cranko Page et al. 10.1029/2023GL104962
1 citations as recorded by crossref.
Latest update: 30 Oct 2025
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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