Biology subjects

Aubin, I.

Publications and source records attributed to Aubin, I..

3 recordsLinked to original sources

bioRxiv2025

Intraspecific variability rivals interspecific differences in root traits of temperate tree seedlings

AbstractGlobal change and associated disturbances are increasing the risk of regeneration failure for tree species in temperate forests. Seedlings are particularly vulnerable to water stress due to their shallow root systems, making belowground plasticity a potentially key component of species adaptive capacity. Quantifying root trait variability and its drivers can improve our understanding of regeneration success under increasingly warm and dry conditions. We quantified between species variation (BTV) and intraspecific variation (ITV) in seven root traits linked to water uptake--root-to-shoot ratio, maximum rooting depth, proportion of absorptive roots, specific root length, root tissue density, average absorptive root diameter, and root branching density--for seedlings of seven common, co-occurring tree species in forests of northeastern North America. We sampled seedlings under contrasting climate and light conditions, and assessed the influence of abiotic (climate, light conditions, soil properties) and biotic drivers (neighboring vegetation) as well as seedling characteristics (species identity, age, spermatophyte type) on root ITV at local and regional scales. Species differed significantly for some traits but differed even more strongly in multivariate trait syndromes, suggesting distinct belowground strategies. ITV was substantial but trait-dependent, with maximum rooting depth and root to shoot ratio being the most variable (coefficient of variation > 45%) and branching density the least variable. BTV was the primary driver of overall trait variation for three traits, explaining more than 60% of variation, whereas within-plot ITV accounted for more than 50% of variation in the remaining four traits. Local drivers did not outweigh regional factors, and the overall explanatory power of measured drivers was limited, suggesting that fine-scale heterogeneity, not captured in our study, may strongly influence root ITV. High ITV in most traits suggests substantial plasticity in roots, which may contribute to the adaptive capacity of seedlings facing climate change. Integrating this plasticity into mechanistic models is critical for predicting regeneration dynamics or root-mediated ecosystem processes. We propose a set of guidelines for integrating root traits into comparative studies and models based on trait measurability and extent of ITV. We further highlight the need to account for the scale- and gradient-intensity dependence of ITV-environment relationships.

ecology↗

bioRxiv2021

Global trade-offs in tree functional traits

AO_SCPLOWBSTRACTC_SCPLOWDue to massive energetic investments in woody support structures, trees are subject to unique physiological, mechanical, and ecological pressures not experienced by herbaceous plants. When considering trait relationships across the entire plant kingdom, plant trait frameworks typically must omit traits unique to large woody species, thereby limiting our understanding of how these distinct ecological pressures shape trait relationships in trees. Here, by considering 18 functional traits--reflecting leaf economics, wood structure, tree size, reproduction, and below-ground allocation--we quantify the major axes of variation governing trait expression of trees worldwide. We show that trait variation within and across angiosperms and gymnosperms is captured by two independent processes: one reflecting tree size and competition for light, the other reflecting leaf photosynthetic capacity and nutrient economies. By exploring multidimensional relationships across clusters of traits, we further identify a representative set of seven traits which captures the majority of variation in form and function in trees: maximum tree height, stem conduit diameter, specific leaf area, seed mass, bark thickness, root depth, and wood density. Collectively, this work informs future trait-based research into the functional biogeography of trees, and contributes to our fundamental understanding of the ecological and evolutionary controls on forest biodiversity and productivity worldwide.

ecology↗

bioRxiv2020

Global Root Traits (GRooT) Database

MotivationTrait data are fundamental to quantitatively describe plant form and function. Although root traits capture key dimensions related to plant responses to changing environmental conditions and effects on ecosystem processes, they have rarely been included in large-scale comparative studies and global models. For instance, root traits remain absent from nearly all studies that define the global spectrum of plant form and function. Thus, to overcome conceptual and methodological roadblocks preventing a widespread integration of root trait data into large-scale analyses we created the Global Root Trait (GRooT) Database. GRooT provides ready-to-use data by combining the expertise of root ecologists with data mobilization and curation. Specifically, we (i) determined a set of core root traits relevant to the description of plant form and function based on an assessment by experts, (ii) maximized species coverage through data standardization within and among traits, and (iii) implemented data quality checks. Main types of variables containedGRooT contains 114,222 trait records on 38 continuous root traits. Spatial location and grainGlobal coverage with data from arid, continental, polar, temperate, and tropical biomes. Data on root traits derived from experimental studies and field studies. Time period and grainData recorded between 1911 and 2019 Major taxa and level of measurementGRooT includes root trait data for which taxonomic information is available. Trait records vary in their taxonomic resolution, with sub-species or varieties being the highest and genera the lowest taxonomic resolution available. It contains information for 184 sub-species or varieties, 6,214 species, 1,967 genera and 254 families. Due to variation in data sources, trait records in the database include both individual observations and mean values. Software formatGRooT includes two csv file. A GitHub repository contains the csv files and a script in R to query the database.

ecology↗