Data from: The coordination of dehydration tolerance and avoidance in oaks is mediated by leaf habit across a precipitation gradient

Forests worldwide are increasingly impacted by drought due to climate
change, prompting plants to adapt through dehydration tolerance (DT) and
avoidance (DA), two distinct physiological strategies. However, how these
strategies are coordinated in response to varying precipitation remains
unclear. To address this gap, we investigated key hydraulic traits
associated with DT and DA in eleven oaks (Quercus spp.) across a broad
precipitation gradient (498-1793 mm yr-1) in China. Specifically, we
measured three DT traits: water potential at 50% loss of hydraulic
conductivity (ΨP50), leaf turgor loss point water potential (ΨTLP), and
wood density (WD), as well as four DA traits: water potential at stomatal
closure (Ψclose), minimum leaf conductance, branch capacitance, and
leaf-to-sapwood area ratio (AL:AS). When analyzed collectively, most
traits showed no significant relationship with precipitation or aridity.
However, distinct patterns emerged when data were analyzed by leaf habit.
In evergreens, trait variation was largely and independently explained by
mean annual precipitation (MAP), with stronger DT (lower ΨP50 and ΨTLP,
higher WD) and enhanced DA (smaller AL:AS) under drier conditions. In
contrast, deciduous species showed weaker DT (higher ΨP50) but stronger DA
(higher Ψclose and lower AL:AS) as precipitation decreased, with much
variance driven by interactions between MAP and mean annual temperature
(MAT). Notably, DT and DA traits were strongly correlated in evergreens
but weakly associated in deciduous species. Our results show that
evergreen oaks rely on both DT and DA strategies for drought adaptation,
whereas deciduous species primarily depend on DA mechanisms. Considering
DT alone is insufficient, and incorporating multiple DA strategies is
essential for a mechanistic framework to understand forest responses. We
highlight the need to integrate leaf habit and complementary drought
strategies into predictive models and climate-resilient forest management
practices.