bioRxivPhysiologyPreprint
Intermediate, rather than Isohydric or Anisohydric, Species were More Resilient to an Extreme Heatwave in a Common Garden in Sydney
Wahidullah RahmaniiD, Mohammad Golam KibriaiD, Mark G. TjoelkeriD, Paul L. RaymeriD, Renée M. MarchiniD
Abstract
Urban forests are increasingly exposed to climate extremes, yet selecting resilient urban species remains difficult as it is unclear why some species fail and others succeed. We monitored growth and survival of 48 urban tree and shrub species, respectively, for about five years after planting, plus we quantified species' crown dieback after a natural extreme heatwave (three days with temperatures exceeding 40 degrees C) in a common garden in Sydney, Australia. For 30 species we measured 15 plant functional traits, including both hydraulic and morphological traits. Native species had less crown dieback and higher absolute growth but lower survival than exotic species. Plant functional traits linked to heat and drought tolerance explained 20-30% of the variation in observed crown dieback across species. Extensive dieback exceeding 40% after the extreme heatwave was found for seven species with large leaf size (and leaf width), high leaf relative water content, and low wood density. Nonlinear relationships between crown dieback and leaf water potential traits identified that both isohydric and anisohydric species were vulnerable, indicating that vulnerability did not align neatly with a single hydraulic strategy. Hydraulic failure likely occurred for some, but not all, vulnerable isohydric and anisohydric species, suggesting vulnerability of certain species was directly caused by cumulative thermal stress. Importantly, survival was not related to any single functional trait, indicating that crown dieback was a more sensitive and earlier indicator of cumulative thermal stress than mortality. These findings support a shift from climate of origin-based to trait-based species selection in urban forestry.
- organism: plant (other)
- research focus: benchmarking
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- Citations
- 0
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