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Identifying areas at risk of drought-induced tree mortality across South-Eastern Australia.

Martin G De KauweBelinda E MedlynAnna M UkkolaMengyuan MuManon E B SabotAndrew J PitmanPatrick MeirLucas A CernusakSami W RifaiBrendan ChoatDavid T TissueChris J BlackmanXimeng LiMichael RoderickPeter R Briggs
Published in: Global change biology (2020)
South-East Australia has recently been subjected to two of the worst droughts in the historical record (Millennium Drought, 2000-2009 and Big Dry, 2017-2019). Unfortunately, a lack of forest monitoring has made it difficult to determine whether widespread tree mortality has resulted from these droughts. Anecdotal observations suggest the Big Dry may have led to more significant tree mortality than the Millennium drought. Critically, to be able to robustly project future expected climate change effects on Australian vegetation, we need to assess the vulnerability of Australian trees to drought. Here we implemented a model of plant hydraulics into the Community Atmosphere Biosphere Land Exchange (CABLE) land surface model. We parameterized the drought response behaviour of five broad vegetation types, based on a common garden dry-down experiment with species originating across a rainfall gradient (188-1,125 mm/year) across South-East Australia. The new hydraulics model significantly improved (~35%-45% reduction in root mean square error) CABLE's previous predictions of latent heat fluxes during periods of water stress at two eddy covariance sites in Australia. Landscape-scale predictions of the greatest percentage loss of hydraulic conductivity (PLC) of about 40%-60%, were broadly consistent with satellite estimates of regions of the greatest change in both droughts. In neither drought did CABLE predict that trees would have reached critical PLC in widespread areas (i.e. it projected a low mortality risk), although the model highlighted critical levels near the desert regions of South-East Australia where few trees live. Overall, our experimentally constrained model results imply significant resilience to drought conferred by hydraulic function, but also highlight critical data and scientific gaps. Our approach presents a promising avenue to integrate experimental data and make regional-scale predictions of potential drought-induced hydraulic failure.
Keyphrases
  • climate change
  • human health
  • big data
  • cardiovascular events
  • healthcare
  • heat stress
  • risk factors
  • type diabetes
  • diabetic rats
  • high glucose
  • coronary artery disease
  • plant growth
  • deep learning
  • stress induced