Multi-year drought strengthens positive and negative functional diversity effects on tree growth response
Serrano-Leon, H.; Blondeel, H.; Glenz, P.; Steurer, J.; Schnabel, F.; Baeten, L.; Guillemot, J.; Martin-StPaul, N.; Skiadaresis, G.; Scherer-Lorenzen, M.; Bonal, D.; Boone, M.; Decarsin, R.; Druel, A.; Godbold, D. L.; Gong, J.; Hajek, P.; Jactel, H.; Koricheva, J.; Mereu, S.; Ponette, Q.; Rewald, B.; Sanden, H.; Van den Bulcke, J.; Verheyen, K.; Werner, R.; Bauhus, J.
Show abstract
O_LIMixed-species forests are proposed as strategy to increase the resistance and resilience of forests to drought stress. However, evidence suggest that increasing tree species richness does not consistently enhance tree growth responses to drought. Moreover, tree diversity effects under unprecedented multiyear droughts remain uncertain, calling for a better understanding of the underlying processes. C_LIO_LIHere, we used a network of planted tree diversity experiments to investigate how drought-induced growth responses of individual trees are influenced by neighborhood tree diversity and the functional traits of the focal tree species. We analyzed tree cores (948 trees across 16 species) from nine experiments across Europe featuring gradients of tree species richness (1-6 species), which experienced severe droughts in recent years. Radial growth response to drought was quantified as tree-ring biomass increment using X-ray computed tomography. We applied hydraulic trait-based growth models to analyze single-year drought responses across all sites and site-specific responses during consecutive drought years for six sites as a function of neighborhood tree diversity. C_LIO_LIThe large variability in tree growth responses to a single-year drought was partially explained by the focal species hydraulic safety margin (representing species drought tolerance) and drought intensity, but independent of neighborhood species richness or functional trait diversity. However, tree diversity effects on growth responses strengthened during consecutive drought years and were site-specific, with contrasting direction (both positive and negative). This indicated opposing pathways of diversity effects under consecutive drought events, possibly resulting from competitive release or greater water consumption in diverse mixtures. C_LIO_LIWe conclude that tree diversity effects on growth responses to single-year droughts may differ considerably from responses to consecutive drought years. Our study highlights the need to consider trait-based approaches (specifically, hydraulic traits) and tree neighborhood scale processes to understand the multifaceted growth responses of tree mixtures under prolonged drought stress. C_LI
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Forest growth resistance and resilience to the 2018-2020 drought depend on tree diversity and mycorrhizal type 98%
- Changes in quantity and timing of foliar and reproductive phenology of tropical dry-forest trees under a warming and drying climate 95%
- Physiological responses to light explain competition and facilitation in a tree diversity experiment 94%
Similar papers in this journal
- Seasonal structural stability promoted by forest diversity and composition explains overyielding 96%
- Tree demographic strategies largely overlap across succession in Neotropical wet and dry forest communities 95%
- Tree diversity effects on productivity depend on mycorrhizae and life strategies in a temperate forest experiment 94%
Similar papers in this journal
Similar papers in this journal
- Phenology across scales: an intercontinental analysis of leaf-out dates in temperate deciduous tree communities 95%
- A cross-scale assessment of productivity-diversity relationships 94%
- Trait-based responses to land use and canopy dynamics modify long-term diversity changes in forest understories 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.