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Guilbeault-Mayers, X.

Publications and source records attributed to Guilbeault-Mayers, X..

3 recordsLinked to original sources

Coordination among leaf and fine root traits across a strong natural soil fertility gradient

Unravelling how fundamental axes of trait variation correlate among leaves and roots and relate to nutrient availability is crucial for understanding plant distribution. While the leaf trait variation axis is linked to nutrient availability gradients, the response of root trait variation to the same gradients yields inconsistent results. We studied leaf and root trait variation among 23 co-occurring plant species along a 2-million year soil chronosequence to assess how leaf and root traits coordinate and how this resulting joint axis of variation relates to soil fertility. Mycorrhizal association types primarily structured the axes of leaf and root trait variation. However, when considering species abundance, soil nutrient availability was an important driver of trait distribution. Leaves that support rapid growth in younger, fertile soils were associated with roots of larger diameter and arbuscular mycorrhizal colonization. In contrast, leaves that favour nutrient conservation in nutrient-impoverished soil were associated with greater root hair length and phosphorus-mobilizing root exudates. At the species level, the signals deviated from the community-wide results presented above, highlighting the challenge of generalizing a specific set of root trait values that consistently meet the requirements of leaves supporting either rapid growth or survival.

ecology↗

Root phosphatase activity is coordinated with the root conservation gradient across a phosphorus gradient in a lowland tropical forest

Soil phosphorus (P) is a growth-limiting nutrient in tropical ecosystems, driving diverse P-acquisition strategies among plants. Particularly, mining for inorganic P through phosphomonoesterase (PME) activity is essential, given the substantial proportion of organic P in soils. Yet the relationship between PME activity and other P-acquisition root traits remains unclear. We measured root PME activity and commonly-measured root traits, including root diameter, specific root length (SRL), root tissue density (RTD), and nitrogen concentration ([N]) in 18 co-occurring trees across soils with varying P availability to better understand trees response to P supply. Root [N] and RTD were inversely related, and that axis was related to soil P supply. Indeed, both traits correlated positively and negatively to PME activity, which responded strongly to P supply. Conversely, root diameter was inversely related to SRL, but this axis was not related to P supply. Suggesting that limiting similarity influenced variation along the diameter-SRL axis, explaining high local trait diversity. Meanwhile, environmental filtering tended to impact trait values along the root [N]-RTD axis. Overall, P availability indicator traits like PME activity and root hairs only tended to be associated with these axes, highlighting limitations of these axes in describing convergent adaptations at local sites.

plant biology↗

Predicting leaf traits across functional groups using reflectance spectroscopy

O_LIPlant ecologists use functional traits to describe how plants respond to and influence their environment. Reflectance spectroscopy can provide rapid, non-destructive estimates of leaf traits, but it remains unclear whether general trait-spectra models can yield accurate estimates across functional groups and ecosystems. C_LIO_LIWe measured leaf spectra and 22 structural and chemical traits for nearly 2000 samples from 104 species. These samples span a large share of known trait variation and represent several functional groups and ecosystems. We used partial least-squares regression (PLSR) to build empirical models for estimating traits from spectra. C_LIO_LIWithin the dataset, our PLSR models predicted traits like leaf mass per area (LMA) and leaf dry matter content (LDMC) with high accuracy (R2>0.85; %RMSE<10). Models for most chemical traits, including pigments, carbon fractions, and major nutrients, showed intermediate accuracy (R2=0.55-0.85; %RMSE=12.7-19.1). Micronutrients such as Cu and Fe showed the poorest accuracy. In validation on external datasets, models for traits like LMA and LDMC performed relatively well, while carbon fractions showed steep declines in accuracy. C_LIO_LIWe provide models that produce fast, reliable estimates of several widely used functional traits from leaf reflectance spectra. Our results reinforce the potential uses of spectroscopy in monitoring plant function around the world. C_LI

ecology↗