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Coordination of stem and leaf traits define different strategies to regulate water loss and tolerance ranges to aridity
Author(s) -
López Rosana,
Cano Francisco Javier,
MartinStPaul Nicolas K.,
Cochard Hervé,
Choat Brendan
Publication year - 2021
Publication title -
new phytologist
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.742
H-Index - 244
eISSN - 1469-8137
pISSN - 0028-646X
DOI - 10.1111/nph.17185
Subject(s) - biology , deserts and xeric shrublands , specific leaf area , arid , intraspecific competition , drought tolerance , stomatal conductance , ecology , trait , resistance (ecology) , botany , habitat , photosynthesis , computer science , programming language
Summary Adaptation to drought involves complex interactions of traits that vary within and among species. To date, few data are available to quantify within‐species variation in functional traits and they are rarely integrated into mechanistic models to improve predictions of species response to climate change. We quantified intraspecific variation in functional traits of two Hakea species growing along an aridity gradient in southeastern Australia. Measured traits were later used to parameterise the model SurEau to simulate a transplantation experiment to identify the limits of drought tolerance. Embolism resistance varied between species but not across populations. Instead, populations adjusted to drier conditions via contrasting sets of trait trade‐offs that facilitated homeostasis of plant water status. The species from relatively mesic climate, Hakea dactyloides , relied on tight stomatal control whereas the species from xeric climate, Hakea leucoptera dramatically increased Huber value and leaf mass per area, while leaf area index (LAI) and epidermal conductance ( g min ) decreased. With trait variability, SurEau predicts the plasticity of LAI and g min buffers the impact of increasing aridity on population persistence. Knowledge of within‐species variability in multiple drought tolerance traits will be crucial to accurately predict species distributional limits.