An integrated framework of plant form and function: the belowground perspective

Weigelt, Alexandra; Mommer, Liesje; Andraczek, Karl; Iversen, Colleen M.; Bergmann, Joana; Bruelheide, Helge; Fan, Ying; Freschet, Grégoire T.; Guerrero‐Ramírez, Nathaly R.; Kattge, Jens; Kuyper, Thom W.; Laughlin, Daniel C.; Meier, Ina C.; Plas, Fons van der; Poorter, Hendrik; Roumet, Catherine; Ruijven, Jasper van; Sabatini, Francesco; Semchenko, Marina; Sweeney, Christopher J.; Valverde‐Barrantes, Oscar J.; York, Larry M.; McCormack, M. Luke

doi:10.1111/nph.17590

Cited by 201 publications

(277 citation statements)

References 155 publications

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“…However, root hydraulics can be restored before growing new roots by renewing the permeability of damaged roots, as documented in succulent Agave and Opuntia [45,49]. Our results strongly confirm that a high root biomass allocation, as recorded in both species, plays a key role in coping drought [50][51][52], and highlight the urgency to fill gaps in our knowledge on the relevance of root hydraulics in regulating whole plant hydraulics, especially under drought [47,[53][54][55][56]. Additional experiments aimed to investigate coupled physiological and morphological root traits, and especially their changes in response to drought, are needed to improve our lacking knowledge on this topic.…”

Section: Two Different Drought Resistance Strategies But a Similar Root Hydraulics Recovery Abilitysupporting

confidence: 82%

When Water Availability Is Low, Two Mediterranean Salvia Species Rely on Root Hydraulics

Abate

Azzarà

Trifilò

2021

Plants

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Increase in severity and frequency of drought events is altering plant community composition, exposing biomes to a higher risk of biodiversity losses. This is exacerbated in the most fragile areas as Mediterranean biome. Thus, identifying plant traits for forecasting species with a high risk of drought-driven mortality is particularly urgent. In the present study, we investigated the drought resistance strategy of two Mediterranean native species: Salvia ceratophylloides Ard. (Sc) and Salvia officinalis L. (So) by considering the impact of drought-driven water content decline on plant hydraulics. Well-watered samples of Sc displayed higher leaf and stemsaturated water content and lower shoot biomass than So samples, but similar root biomass. In response to drought, Sc showed a conservative water use strategy, as the prompt stomatal closure and leaves shedding suggested. A drought-tolerant mechanism was confirmed in So samples. Nevertheless, Sc and So showed similar drought-driven plant hydraulic conductance (Kplant) recover ability. Root hydraulic traits played a key role to reach this goal. Relative water content as well as loss of cell rehydration capability and membrane damages, especially of stem and root, were good proxies of drought-driven Kplant decline.

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Section: Two Different Drought Resistance Strategies But a Similar Root Hydraulics Recovery Abilitysupporting

confidence: 82%

When Water Availability Is Low, Two Mediterranean Salvia Species Rely on Root Hydraulics

Abate

Azzarà

Trifilò

2021

Plants

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“…pPCA is an extended method of PCA that is a powerful multivariate analysis technique and can summarize a set of data on correlated variables with a few composite, uncorrelated principal components (James and McCulloch, 1990). pPCA has been widely used in the determination of independent axes of functional specialization (e.g., Wang et al, 2018a;Bergmann et al, 2020;Weigelt et al, 2021). The Kaiser's eigenvalue greater than 1 rule was used to determine the intrinsic dimensionality of root trait covariation, this is, eigenvalues of the principal components greater than 1 were considered significant (Kaiser, 1958;Tabachnik and Fidell, 1996).…”

Section: Data Analysesmentioning

confidence: 99%

“…However, recent global studies have provided growing evidence for the multiple dimensions of root trait covariation (Bergmann et al, 2020;Weigelt et al, 2021). Two or more independent gradients were found to represent different facets of root trait syndromes (Weemstra et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

“…One was defined as the collaboration gradient represented by a trade-off between root diameter (RD) and SRL, and the other was defined as the conservation gradient represented by the negative relationship between RTD and RNC. This multidimensional trait pattern allows roots to enhance resource uptake from soils through either the construction of thinner fine roots or the development of high mycorrhizal dependency (Bergmann et al, 2020;Weigelt et al, 2021), reflecting the root trait diversity and adaptation to different environments.…”

Section: Introductionmentioning

confidence: 99%

“…For the same set of root traits -namely RD, SRL, SRA, RTD, RNC, root C content (RCC), RCN, stele diameter, and cortex thickness reported two primary dimensions of trait covariation in the subtropical forests of China, whereas Zhou et al (2018) demonstrated three main dimensions in the temperate steppes of China. These inconsistencies in results among the regional studies may be related to multiple factors, including the differences in the selection of root traits defining the trait coordination and tradeoffs (de la Riva et al, 2021a), species composition (e.g., plant growth form and phylogenetic group) (Wang et al, 2018a;Weigelt et al, 2021), mycorrhizal association type (Comas et al, 2014;Akatsuki and Makita, 2020), and biome type (Wang et al, 2018b;Valverde-Barrantes et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Evidence of Differences in Covariation Among Root Traits Across Plant Growth Forms, Mycorrhizal Types, and Biomes

Lü

et al. 2022

Front. Plant Sci.

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Fine roots play an important role in plant ecological strategies, adaptation to environmental constraints, and ecosystem functions. Covariation among root traits influence the physiological and ecological processes of plants and ecosystems. Root trait covariation in multiple dimensions at the global scale has been broadly discussed. How fine-root traits covary at the regional scale and whether the covariation is generalizable across plant growth forms, mycorrhizal types, and biomes are largely unknown. Here, we collected six key traits – namely root diameter (RD), specific root length (SRL), root tissue density (RTD), root C content (RCC), root N content (RNC), and root C:N ratio (RCN) – of first- and second-order roots of 306 species from 94 sampling sites across China. We examined the covariation in root traits among different plant growth forms, mycorrhizal types, and biomes using the phylogenetic principal component analysis (pPCA). Three independent dimensions of the covariation in root traits were identified, accounting for 39.0, 26.1, and 20.2% of the total variation, respectively. The first dimension was represented by SRL, RNC, RTD, and RCN, which was in line with the root economics spectrum (RES). The second dimension described a negative relationship between RD and SRL, and the third dimension was represented by RCC. These three main principal components were mainly influenced by biome and mycorrhizal type. Herbaceous and ectomycorrhizal species showed a more consistent pattern with the RES, in which RD, RTD, and RCN were negatively correlated with SRL and RNC within the first axis compared with woody and arbuscular mycorrhizal species, respectively. Our results highlight the roles of plant growth form, mycorrhizal type, and biome in shaping root trait covariation, suggesting that root trait relationships in specific regions may not be generalized from global-scale analyses.

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A machine learning approach to study plant functional trait divergence

Majumder,

Mason

2024

Appl Plant Sci

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PremisePlant functional traits are often used to describe the spectra of ecological strategies used by different species. Here, we demonstrate a machine learning approach for identifying the traits that contribute most to interspecific phenotypic divergence in a multivariate trait space.MethodsDescriptive and predictive machine learning approaches were applied to trait data for the genus Helianthus, including random forest and gradient boosting machine classifiers and recursive feature elimination. These approaches were applied at the genus level as well as within each of the three major clades within the genus to examine the variability in the major axes of trait divergence in three independent species radiations.ResultsMachine learning models were able to predict species identity from functional traits with high accuracy, and differences in functional trait importance were observed between the genus and clade levels indicating different axes of phenotypic divergence.ConclusionsApplying machine learning approaches to identify divergent traits can provide insights into the predictability or repeatability of evolution through the comparison of parallel diversifications of clades within a genus. These approaches can be implemented in a range of contexts across basic and applied plant science from interspecific divergence to intraspecific variation across time, space, and environmental conditions.

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An integrated framework of plant form and function: the belowground perspective

Abstract: This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as

Cited by 201 publications

References 155 publications

When Water Availability Is Low, Two Mediterranean Salvia Species Rely on Root Hydraulics

When Water Availability Is Low, Two Mediterranean Salvia Species Rely on Root Hydraulics

Evidence of Differences in Covariation Among Root Traits Across Plant Growth Forms, Mycorrhizal Types, and Biomes

A machine learning approach to study plant functional trait divergence

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