Xylem Functional Traits as Indicators of Health in Mediterranean Forests

Abstract

Purpose of Review We conducted a literature survey and meta-analysis to assess, in Mediterranean forests impacted by drought, the role of xylem functional traits as indicators of tree health, and their potential to adjust over a range of climatic conditions to support tree performance and survival. We aimed also to depict the geographic variability of xylem functional traits among Mediterranean forest trees as a tool for regional scale-oriented vulnerability assessment. Recent Findings Associations were investigated among xylem functional traits, hydraulic safety, and whole plant drought resistance for tree species in Mediterranean-type climates. Variable data were available from a number of study cases of Mediterranean forest communities impacted by intense drought, wherein tree growth and xylem functional traits were investigated along with tree decline and dieback episodes. Variable data were available from a number of studies that analyzed xylem trait adjustments to climatic conditions at different temporal scales. Summary We observed differing growth patterns and xylem conduit area responses in healthy and unhealthy trees and we sketched hydraulic strategies that may fit observed patterns. Overall, a clear role of xylem conduit size as stand-alone tree health indicator did not emerge. We showed that xylem traits may adjust along different temporal scales and may support the performance and health of Mediterranean tree species over a range of climatic conditions. We outlined substantial geographic variability in xylem traits across the Mediterranean region, suggesting patchy responses to increasing drought. Knowledge gaps and needed lines of research are highlighted.

Starch and lipid storage strategies in tropical trees relate to growth and mortality

“…Trees that belonged to slow growing, long‐lived and high‐survival species stored a large proportion of their starch reserves in the living fibers in the wood and had the biggest NSC pool. Trade‐offs between survival and growth have been reported for several tree species, where species that allocate more resources to high survival traits such as defense compounds and high wood density tend to grow slower than species with less allocation to survival traits (Gilbert et al ., 2006; Poorter et al ., 2008; Wright et al ., 2010; Adler et al ., 2014; Philipson et al ., 2014; Osazuwa‐Peters et al ., 2017; Borghetti et al ., 2020). Our results showed that storage of starch in living fibers in stem wood may also be an important trait of species that prioritize allocation of resources to increase survival rather than growth.…”

“…Tree survival during drought has already been linked to storage content in seedlings of tropical trees (O’Brien et al ., 2014, 2020). Nevertheless, these links are not well understood in adult tropical trees, principally due to the following factors: first, the influence of other tree traits such as xylem vulnerability to embolism, rooting depth or wood density on plant survival (McDowell et al ., 2008; Johnson et al ., 2012; Rowland et al ., 2015; Boonman et al ., 2020; Borghetti et al ., 2020); and, second, lack of understanding of NSC storage regulation (Dickman et al ., 2019).…”

Drought and heat waves, cues for an adaptive silviculture

“…Questa variabilità è legata a differenze nella struttura anatomica dello xilema: dimensioni dei condotti e loro interconnessione, porosità delle pareti cellulari, caratteristiche della membrana delle punteggiature, ecc. Una valutazione del ruolo delle caratteristiche xilematiche nel mantenimento del vigore arboreo in ambiente mediterraneo è stata svolta recentemente da Borghetti et al (2020). Oltre all'anatomia funzionale dello xilema, molto variabile in funzione dell'ambiente (Borghetti et al 2016), vi sono numerosi tratti della pianta collegati all'adattamento alla siccità, che variano in modo coordinato così da bilanciare il controllo della tensione xilematica con l'assimilazione del carbonio per via fotosintetica (Mencuccini et al 2015).…”

“…classi dimensionali e sociali, ricavabili da indagini inventariali o da ricognizioni da remoto, le cui potenzialità interpretative e facilità d'uso aumentano quasi giornalmente (Chirici 2020, Francini et al 2020. Si possono produrre, in questo modo, cartografie funzionali da utilizzare come guida operativa negli approcci colturali a scala di popolamento/comunità, e di indirizzo nelle decisioni gestionali a scala aziendale e territoriale; si rimanda a Lavorel et al (2011) per un'applicazione della diversità funzionale a scala di paesaggio e a Borghetti et al (2020) per un esercizio in cui la foresta mediterranea è stata descritta, ad ampia scala geografica, in termini di diversità funzionale basandosi sui caratteri dello xilema delle diverse specie che edificavano la comunità forestale;…”

MOSAIC: A Unified Trait Database to Complement Structured Population Models

“…Despite major improvements in the consolidation and accessibility of trait data, there is not yet a single-source centralised database spanning behaviour, physiology, habitat, and other trait data for a wide range of species. Existing databases are often linked by taxonomy ( e.g., FishBase (Froese & Pauly, 2010), CoralTraits (Madin et al, 2016), MammalBase (Lintulaakso, 2013), AmphiBio (Oliveira, São-Pedro, Santos-Barrera, Penone, & Costa, 2017)); trait type ( e.g., TreeOfSex (The Tree of Sex Consortium 2014), TreeBase (Boettiger & Temple Lang, 2012), Xylum Functional Traits (Borghetti, Gentilesca, Colangelo, Ripullone, & Rita, 2020)); data type ( e.g., GBIF (https://www.gbif.org/), MOL (Jetz, Thomas, Joy, Hartmann, & Mooers, 2012), TetraDensity (Santini, Isaac, & Ficetola, 2018)); or a combination of the taxonomies and traits (WooDiv (Monnet et al, 2021), CarniDiet (Middleton, Svensson, Scharlemann, Faurby, & Sandom, 2021)). A number of other databases take a more general approach in their thematic scope, but are still constrained to a limited set of traits and taxonomy ( e.g., Amniote (Myhrvold et al, 2015), Pantheria (Jones et al, 2009), BIEN (Enquist, Condit, Peet, Schildhauer, & Thiers, 2016; Maitner et al, 2018), TRY (Kattge et al, 2020)).…”