Mycorrhizal associations modify tree diversity-productivity relationships across experimental tree plantations.

Decades of studies have demonstrated links between biodiversity and ecosystem functioning, yet the generality of the relationships and the underlying mechanisms remain unclear, especially for forest ecosystems. Using 11 tree-diversity experiments, we tested tree species richness-community productivity relationships and the role of arbuscular (AM) or ectomycorrhizal (ECM) fungal-associated tree species in these relationships. Tree species richness had a positive effect on community productivity across experiments, modified by the diversity of tree mycorrhizal associations. In communities with both AM and ECM trees, species richness showed positive effects on community productivity, which could have resulted from complementarity between AM and ECM trees. Moreover, both AM and ECM trees were more productive in mixed communities with both AM and ECM trees than in communities assembled by their own mycorrhizal type of trees. In communities containing only ECM trees, species richness had a significant positive effect on productivity, whereas species richness did not show any significant effects on productivity in communities containing only AM trees. Our study provides novel explanations for variations in diversity-productivity relationships by suggesting that tree-mycorrhiza interactions can shape productivity in mixed-species forest ecosystems.

Soil fertility determines whether ectomycorrhizal fungi accelerate or decelerate decomposition in a temperate forest.

Ectomycorrhizal (ECM) fungi can both accelerate and decelerate decomposition of organic matter in forest soils, but a mechanistic understanding of this differential influence is limited. Here, we tested how ECM fungi affect decomposition along a natural fertility gradient in a temperate forest of European beech. Trees were girdled to reduce belowground carbon supply to the soil. Girdling shifted soil fungal community composition and decreased hyphal biomass production and soil CO2 efflux, indicating a reduced ECM fungal activity. Girdling also affected decomposition processes, but the effects depended on fertility. Our results indicate that ECM fungi decelerate decomposition under conditions of low fertility while under conditions of high fertility ECM fungi and their host roots have an accelerating effect. We conclude that both acceleration and deceleration of decomposition of organic matter by ECM fungi can occur within a forest, with soil fertility determining the direction and magnitude of these effects. We suggest a positive feedback between fertility, stand productivity and soil carbon and nitrogen dynamics that is mediated to a large extent by ECM fungi.

Soil geochemistry - and not topography - as a major driver of carbon allocation, stocks, and dynamics in forests and soils of African tropical montane ecosystems.

The lack of field-based data in the tropics limits our mechanistic understanding of the drivers of net primary productivity (NPP) and allocation. Specifically, the role of local edaphic factors - such as soil parent material and topography controlling soil fertility as well as water and nutrient fluxes - remains unclear and introduces substantial uncertainty in understanding net ecosystem productivity and carbon (C) stocks. Using a combination of vegetation growth monitoring and soil geochemical properties, we found that soil fertility parameters reflecting the local parent material are the main drivers of NPP and C allocation patterns in tropical montane forests, resulting in significant differences in below- to aboveground biomass components across geochemical (soil) regions. Topography did not constrain the variability in C allocation and NPP. Soil organic C stocks showed no relation to C input in tropical forests. Instead, plant C input seemingly exceeded the maximum potential of these soils to stabilize C. We conclude that, even after many millennia of weathering and the presence of deeply developed soils, above- and belowground C allocation in tropical forests, as well as soil C stocks, vary substantially due to the geochemical properties that soils inherit from parent material.

Soil fertility relates to fungal-mediated decomposition and organic matter turnover in a temperate mountain forest.

Fungi are known to exert a significant influence over soil organic matter (SOM) turnover, however understanding of the effects of fungal community structure on SOM dynamics and its consequences for ecosystem fertility is fragmentary. Here we studied soil fungal guilds and SOM decomposition processes along a fertility gradient in a temperate mountain beech forest. High-throughput sequencing was used to investigate fungal communities. Carbon and nitrogen stocks, enzymatic activity and microbial respiration were measured. While ectomycorrhizal fungal abundance was not related to fertility, saprotrophic ascomycetes showed higher relative abundances under more fertile conditions. The activity of oxidising enzymes and respiration rates in mineral soil were related positively to fertility and saprotrophic fungi. In addition, organic layer carbon and nitrogen stocks were lower on the more fertile plots, although tree biomass and litter input were higher. Together, the results indicated a faster SOM turnover at the fertile end of the gradient. We suggest that there is a positive feedback mechanism between SOM turnover and fertility that is mediated by soil fungi to a significant extent. By underlining the importance of fungi for soil fertility and plant growth, these findings furthermore emphasise the dependency of carbon cycling on fungal communities below ground.

Root traits as drivers of plant and ecosystem functioning: current understanding, pitfalls and future research needs.

The effects of plants on the biosphere, atmosphere and geosphere are key determinants of terrestrial ecosystem functioning. However, despite substantial progress made regarding plant belowground components, we are still only beginning to explore the complex relationships between root traits and functions. Drawing on the literature in plant physiology, ecophysiology, ecology, agronomy and soil science, we reviewed 24 aspects of plant and ecosystem functioning and their relationships with a number of root system traits, including aspects of architecture, physiology, morphology, anatomy, chemistry, biomechanics and biotic interactions. Based on this assessment, we critically evaluated the current strengths and gaps in our knowledge, and identify future research challenges in the field of root ecology. Most importantly, we found that belowground traits with the broadest importance in plant and ecosystem functioning are not those most commonly measured. Also, the estimation of trait relative importance for functioning requires us to consider a more comprehensive range of functionally relevant traits from a diverse range of species, across environments and over time series. We also advocate that establishing causal hierarchical links among root traits will provide a hypothesis-based framework to identify the most parsimonious sets of traits with the strongest links on functions, and to link genotypes to plant and ecosystem functioning.

A starting guide to root ecology: strengthening ecological concepts and standardising root classification, sampling, processing and trait measurements.

In the context of a recent massive increase in research on plant root functions and their impact on the environment, root ecologists currently face many important challenges to keep on generating cutting-edge, meaningful and integrated knowledge. Consideration of the below-ground components in plant and ecosystem studies has been consistently called for in recent decades, but methodology is disparate and sometimes inappropriate. This handbook, based on the collective effort of a large team of experts, will improve trait comparisons across studies and integration of information across databases by providing standardised methods and controlled vocabularies. It is meant to be used not only as starting point by students and scientists who desire working on below-ground ecosystems, but also by experts for consolidating and broadening their views on multiple aspects of root ecology. Beyond the classical compilation of measurement protocols, we have synthesised recommendations from the literature to provide key background knowledge useful for: (1) defining below-ground plant entities and giving keys for their meaningful dissection, classification and naming beyond the classical fine-root vs coarse-root approach; (2) considering the specificity of root research to produce sound laboratory and field data; (3) describing typical, but overlooked steps for studying roots (e.g. root handling, cleaning and storage); and (4) gathering metadata necessary for the interpretation of results and their reuse. Most importantly, all root traits have been introduced with some degree of ecological context that will be a foundation for understanding their ecological meaning, their typical use and uncertainties, and some methodological and conceptual perspectives for future research. Considering all of this, we urge readers not to solely extract protocol recommendations for trait measurements from this work, but to take a moment to read and reflect on the extensive information contained in this broader guide to root ecology, including sections I-VII and the many introductions to each section and root trait description. Finally, it is critical to understand that a major aim of this guide is to help break down barriers between the many subdisciplines of root ecology and ecophysiology, broaden researchers' views on the multiple aspects of root study and create favourable conditions for the inception of comprehensive experiments on the role of roots in plant and ecosystem functioning.

High Fungal Diversity but Low Seasonal Dynamics and Ectomycorrhizal Abundance in a Mountain Beech Forest.

Forests on steep slopes constitute a significant proportion of European mountain areas and are important as production and protection forests. This study describes the soil fungal community structure in a European beech-dominated mountain forest stands in the Northern Calcareous Alps and investigates how it is determined by season and soil properties. Samples were collected at high spatial resolution in an area of ca. 100 m × 700 m in May (spring) and August (summer). Illumina MiSeq high-throughput sequencing of the ITS2-region revealed distinct patterns for the soil fungal communities. In contrast to other studies from temperate European beech forest stands, Ascomycota dominated the highly diverse fungal community, while ectomycorrhizal fungi were of lower abundance. Russulaceae, which are often among the dominant ectomycorrhizal fungi associated with European beech, were absent from all samples. Potentially plant pathogenic fungi were more prevalent than previously reported. Only subtle seasonal differences were found between fungal communities in spring and summer. Especially, dominant saprotrophic taxa were largely unaffected by season, while slightly stronger effects were observed for ectomycorrhizal fungi. Soil characteristics like pH and organic carbon content, on the other hand, strongly shaped abundant taxa among the saprotrophic fungal community.

Root traits of European Vicia faba cultivars-Using machine learning to explore adaptations to agroclimatic conditions.

Faba bean (Vicia faba L.) is an important source of protein, but breeding for increased yield stability and stress tolerance is hampered by the scarcity of phenotyping information. Because comparisons of cultivars adapted to different agroclimatic zones improve our understanding of stress tolerance mechanisms, the root architecture and morphology of 16 European faba bean cultivars were studied at maturity. Different machine learning (ML) approaches were tested in their usefulness to analyse trait variations between cultivars. A supervised, that is, hypothesis-driven, ML approach revealed that cultivars from Portugal feature greater and coarser but less frequent lateral roots at the top of the taproot, potentially enhancing water uptake from deeper soil horizons. Unsupervised clustering revealed that trait differences between northern and southern cultivars are not predominant but that two cultivar groups, independently from major and minor types, differ largely in overall root system size. Methodological guidelines on how to use powerful ML methods such as random forest models for enhancing the phenotypical exploration of plants are given.

Root architecture simulation improves the inference from seedling root phenotyping towards mature root systems.

Root phenotyping provides trait information for plant breeding. A shortcoming of high-throughput root phenotyping is the limitation to seedling plants and failure to make inferences on mature root systems. We suggest root system architecture (RSA) models to predict mature root traits and overcome the inference problem. Sixteen pea genotypes were phenotyped in (i) seedling (Petri dishes) and (ii) mature (sand-filled columns) root phenotyping platforms. The RSA model RootBox was parameterized with seedling traits to simulate the fully developed root systems. Measured and modelled root length, first-order lateral number, and root distribution were compared to determine key traits for model-based prediction. No direct relationship in root traits (tap, lateral length, interbranch distance) was evident between phenotyping systems. RootBox significantly improved the inference over phenotyping platforms. Seedling plant tap and lateral root elongation rates and interbranch distance were sufficient model parameters to predict genotype ranking in total root length with an RSpearman of 0.83. Parameterization including uneven lateral spacing via a scaling function substantially improved the prediction of architectures underlying the differently sized root systems. We conclude that RSA models can solve the inference problem of seedling root phenotyping. RSA models should be included in the phenotyping pipeline to provide reliable information on mature root systems to breeding research.

Redefining fine roots improves understanding of below-ground contributions to terrestrial biosphere processes.

Fine roots acquire essential soil resources and mediate biogeochemical cycling in terrestrial ecosystems. Estimates of carbon and nutrient allocation to build and maintain these structures remain uncertain because of the challenges of consistently measuring and interpreting fine-root systems. Traditionally, fine roots have been defined as all roots ≤ 2 mm in diameter, yet it is now recognized that this approach fails to capture the diversity of form and function observed among fine-root orders. Here, we demonstrate how order-based and functional classification frameworks improve our understanding of dynamic root processes in ecosystems dominated by perennial plants. In these frameworks, fine roots are either separated into individual root orders or functionally defined into a shorter-lived absorptive pool and a longer-lived transport fine-root pool. Using these frameworks, we estimate that fine-root production and turnover represent 22% of terrestrial net primary production globally - a c. 30% reduction from previous estimates assuming a single fine-root pool. Future work developing tools to rapidly differentiate functional fine-root classes, explicit incorporation of mycorrhizal fungi into fine-root studies, and wider adoption of a two-pool approach to model fine roots provide opportunities to better understand below-ground processes in the terrestrial biosphere.

It's complicated: intraroot system variability of respiration and morphological traits in four deciduous tree species.

Within branched root systems, a distinct heterogeneity of traits exists. Knowledge about the ecophysiology of different root types is critical to understand root system functioning. Classification schemes have to match functional root types as closely as possible to be used for sampling and modeling. Among ecophysiological root traits, respiration is of particular importance, consuming a great amount of carbon allocated. Root architecture differs between the four deciduous tree seedlings. However, two types of terminal root segments (i.e. first and second orders), white colored and brown colored, can be distinguished in all four species but vary in frequency, their morphology differing widely from each other and higher coarse root orders. Root respiration is related to diameter and tissue density. The use of extended root ordering (i.e. order and color) explains the variance of respiration two times as well as root diameter or root order classes alone. White terminal roots respire significantly more than brown ones; both possess respiration rates that are greater than those of higher orders in regard to dry weight and lower in regard to surface area. The correlation of root tissue density to respiration will allow us to use this continuous parameter (or easier to determine dry matter content) to model the respiration within woody root systems without having to determine nitrogen contents. In addition, this study evidenced that extended root orders are better suited than root diameter classes to picture the differences between root functional types. Together with information on root order class frequencies, these data allow us to calculate realistic, species-specific respiration rates of root branches.

Automatic Root Length Estimation from Images Acquired In Situ without Segmentation.

Image-based root phenotyping technologies, including the minirhizotron (MR), have expanded our understanding of the in situ root responses to changing environmental conditions. The conventional manual methods used to analyze MR images are time-consuming, limiting their implementation. This study presents an adaptation of our previously developed convolutional neural network-based models to estimate the total (cumulative) root length (TRL) per MR image without requiring segmentation. Training data were derived from manual annotations in Rootfly, commonly used software for MR image analysis. We compared TRL estimation with 2 models, a regression-based model and a detection-based model that detects the annotated points along the roots. Notably, the detection-based model can assist in examining human annotations by providing a visual inspection of roots in MR images. The models were trained and tested with 4,015 images acquired using 2 MR system types (manual and automated) and from 4 crop species (corn, pepper, melon, and tomato) grown under various abiotic stresses. These datasets are made publicly available as part of this publication. The coefficients of determination (R2), between the measurements made using Rootfly and the suggested TRL estimation models were 0.929 to 0.986 for the main datasets, demonstrating that this tool is accurate and robust. Additional analyses were conducted to examine the effects of (a) the data acquisition system and thus the image quality on the models' performance, (b) automated differentiation between images with and without roots, and (c) the use of the transfer learning technique. These approaches can support precision agriculture by providing real-time root growth information.

Particulate matter accumulation by tree foliage is driven by leaf habit types, urbanization- and pollution levels.

Particulate matter (PM) pollution poses a significant threat to human health. Greenery, particularly trees, can act as effective filters for PM, reducing associated health risks. Previous studies have indicated that tree traits play a crucial role in determining the amount of PM accumulated on leaves, although findings have often been site-specific. To comprehensively investigate the key factors influencing PM binding to leaves across diverse tree species and geographical locations, we conducted an extensive analysis using data extracted from 57 publications. The data covers 11 countries and 190 tree species from 1996 to 2021. We categorized tree species into functional groups: evergreen conifers, deciduous conifers, deciduous broadleaves, and evergreen broadleaves based on leaf habit and phylogeny. Evergreen conifers exhibited the highest PM accumulation on leaves, and in general, evergreen leaves accumulated more PM compared to deciduous leaves across all PM size classes. Specific leaf traits, such as epicuticular wax, played a significant role. The highest PM loads on leaves were observed in peri-urban areas along the rural-peri-urban-urban gradient. However, the availability of global data was skewed, with most data originating from urban and peri-urban areas, primarily from China and Poland. Among different climate zones, substantial data were only available for warm temperate and cold steppe climate zones. Understanding the problem of PM pollution and the role of greenery in urban environments is crucial for monitoring and controlling PM pollution. Our systematic review of the literature highlights the variation on PM loading among different vegetation types with varying leaf characteristics. Notably, epicuticular wax emerged as a marker trait that exhibited variability across PM size fractions and different vegetation types. In conclusion, this review emphasizes the importance of greenery in mitigation PM pollution. Our findings underscore the significance of tree traits in PM binding. However, lack of data stresses the need for further research and data collection initiatives.

Root and branch hydraulic functioning and trait coordination across organs in drought-deciduous and evergreen tree species of a subtropical highland forest.

Vessel traits are key in understanding trees' hydraulic efficiency, and related characteristics like growth performance and drought tolerance. While most plant hydraulic studies have focused on aboveground organs, our understanding of root hydraulic functioning and trait coordination across organs remains limited. Furthermore, studies from seasonally dry (sub-)tropical ecosystems and mountain forests are virtually lacking and uncertainties remain regarding potentially different hydraulic strategies of plants differing in leaf habit. Here, we compared wood anatomical traits and specific hydraulic conductivities between coarse roots and small branches of five drought-deciduous and eight evergreen angiosperm tree species in a seasonally dry subtropical Afromontane forest in Ethiopia. We hypothesized that largest vessels and highest hydraulic conductivities are found in roots, with greater vessel tapering between roots and equally-sized branches in evergreen angiosperms due to their drought-tolerating strategy. We further hypothesized that the hydraulic efficiencies of root and branches cannot be predicted from wood density, but that wood densities across organs are generally related. Root-to-branch ratios of conduit diameters varied between 0.8 and 2.8, indicating considerable differences in tapering from coarse roots to small branches. While deciduous trees showed larger branch xylem vessels compared to evergreen angiosperms, root-to-branch ratios were highly variable within both leaf habit types, and evergreen species did not show a more pronounced degree of tapering. Empirically determined hydraulic conductivity and corresponding root-to-branch ratios were similar between both leaf habit types. Wood density of angiosperm roots was negatively related to hydraulic efficiency and vessel dimensions; weaker relationships were found in branches. Wood density of small branches was neither related to stem nor coarse root wood densities. We conclude that in seasonally dry subtropical forests, similar-sized coarse roots hold larger xylem vessels than small branches, but the degree of tapering from roots to branches is highly variable. Our results indicate that leaf habit does not necessarily influence the relationship between coarse root and branch hydraulic traits. However, larger conduits in branches and a low carbon investment in less dense wood may be a prerequisite for high growth rates of drought-deciduous trees during their shortened growing season. The correlation of stem and root wood densities with root hydraulic traits but not branch wood points toward large trade-offs in branch xylem towards mechanical properties.

Semantic segmentation of plant roots from RGB (mini-) rhizotron images-generalisation potential and false positives of established methods and advanced deep-learning models.

BACKGROUND: Manual analysis of (mini-)rhizotron (MR) images is tedious. Several methods have been proposed for semantic root segmentation based on homogeneous, single-source MR datasets. Recent advances in deep learning (DL) have enabled automated feature extraction, but comparisons of segmentation accuracy, false positives and transferability are virtually lacking. Here we compare six state-of-the-art methods and propose two improved DL models for semantic root segmentation using a large MR dataset with and without augmented data. We determine the performance of the methods on a homogeneous maize dataset, and a mixed dataset of > 8 species (mixtures), 6 soil types and 4 imaging systems. The generalisation potential of the derived DL models is determined on a distinct, unseen dataset. RESULTS: The best performance was achieved by the U-Net models; the more complex the encoder the better the accuracy and generalisation of the model. The heterogeneous mixed MR dataset was a particularly challenging for the non-U-Net techniques. Data augmentation enhanced model performance. We demonstrated the improved performance of deep meta-architectures and feature extractors, and a reduction in the number of false positives. CONCLUSIONS: Although correction factors are still required to match human labelled root lengths, neural network architectures greatly reduce the time required to compute the root length. The more complex architectures illustrate how future improvements in root segmentation within MR images can be achieved, particularly reaching higher segmentation accuracies and model generalisation when analysing real-world datasets with artefacts-limiting the need for model retraining.

Phenotypic plasticity and water flux rates of Citrus root orders under salinity.

Knowledge about the root system structure and the uptake efficiency of root orders is critical to understand the adaptive plasticity of plants towards salt stress. Thus, this study describes the phenological and physiological plasticity of Citrus volkameriana rootstocks under severe NaCl stress on the level of root orders. Phenotypic root traits known to influence uptake processes, for example frequency of root orders, specific root area, cortical thickness, and xylem traits, did not change homogeneously throughout the root system, but changes after 6 months under 90 mM NaCl stress were root order specific. Chloride accumulation significantly increased with decreasing root order, and the Cl(-) concentration in lower root orders exceeded those in leaves. Water flux densities of first-order roots decreased to <20% under salinity and did not recover after stress release. The water flux densities of higher root orders changed marginally under salinity and increased 2- to 6-fold in second and third root orders after short-term stress release. Changes in root order frequency, morphology, and anatomy indicate rapid and major modification of C. volkameriana root systems under salt stress. Reduced water uptake under salinity was related to changes of water flux densities among root orders and to reduced root surface areas. The importance of root orders for water uptake changed under salinity from root tips towards higher root orders. The root order-specific changes reflect differences in vulnerability (indicated by the salt accumulation) and ontogenetic status, and point to functional differences among root orders under high salinity.

Diversity and composition of farm plantation tree/shrub species along altitudinal gradients in North-eastern Ethiopia: implication for conservation.

On-farm tree plantation is a form of land use where trees are planted at the edge or interspersed with crops. It has been practiced in different parts of Ethiopia due to its contribution to the household economy and soil fertility. This study was carried out to evaluate the variation in tree/shrub plantations along altitudinal gradients and plantation niches, and farmers' on-farm tree plantation practices at Kobo and Guba Lafto districts, North-eastern Ethiopia. Transect walks and semi-structured questionnaire were administered to appraise farmers' tree/shrub plantation practices and compositions between August and December 2020. A total of 135 plots along altitudinal gradients (Forty-five sample plots per altitude) and 135 retrieved questionnaires (45 per altitude) were analyzed. At each plot, tree/shrub richness, diversity, stem density, and important value index (IVI) were computed. Multivariate analysis, descriptive statistics, and preference rankings were used to evaluate vegetation data and farmers' perceptions on tree/shrub plantations. The results showed that most farmers (78.5 %) integrate trees with their crops for household use and soil fertility maintenance. The multivariate analysis revealed a significant reduction in the number of taxa, stem density, richness, and diversity with increasing elevation, from homestead to the boundary and on-farm plantation niches. Ziziphus spina-christi and Cordia africana were the most preferred tree species; Fabaceae was the dominant family representing 18.9 % of the species. The results emphasized considerable variations in relative density, relative dominance, and important value index (IVI) across altitudinal gradients and plantation niches. Acacia seyal and Z. spina-christi contributed the highest IVI at lower and middle elevations, whereas Eucalyptus globulus had high IVI at a higher elevation. In the study districts, the distribution of multifunctional indigenous tree plantations gradually decreases with the entire altitudinal gradients compared to exotic trees/shrubs. This calls for substantial efforts on the propagation and conservation of native tree and shrub genetic resources.

Scions impact biomass allocation and root enzymatic activity of rootstocks in grafted melon and watermelon plants.

Vegetable grafting is increasingly recognized as an effective and sustainable plant production alternative. Grafted plants usually show increased uptake of water and minerals compared with self-rooted plants, mostly thought a consequence of the vigorous rootstocks selected. However, while studies frequently addressed the effects of rootstocks on the performance of scions, knowledge on the influences of scions on biomass allocation, morphology, and metabolic activity of roots is rare. In particular, the plasticity of root traits affecting resource acquisition and its efficiency remains poorly understood. Two different rootstock species, Cucurbita maxima × Cucurbita moschata and Lagenaria siceraria, were grafted in combination with melon (Cucumis melo) and watermelon (Citrullus lanatus). Self-grafted rootstocks were used as control. Plant biomass and root traits were determined after destructive harvesting 30 and/or 60 days after grafting. Traits included biomass allocation, leaf and root morphology, potential activities of four extracellular enzymes on root tips and basal root segments, and root respiration. Successfully grafted scions increase the ratio of root to whole plant dry matter (RMF), and increased ratios of root length to whole plant dry matter (RLR) and to plant leaf area (RL : LA). In contrast, morphological root traits such as diameter, tissue density, and specific root length remain surprisingly stable, and thus scion-induced changes of those traits may only play a minor role for the beneficial effects of grafting in Cucurbitaceae. Incompatibility in melon/L. siceraria grafts, however, was likely responsible for the reduced root growth in combination with clear changes in root morphological traits. Reduced root respiration rates seem to be the effects of a non-compatible rootstock-scion combination rather than an active, C-efficiency increasing acclimation. In contrast, heterografts with melon and watermelon frequently resulted in root-stock-specific, often enhanced potential enzymatic activities of acid phosphatase, ß-glucosidase, leucine-amino-peptidase, and N-acetyl-glucosaminidase both at root tips and basal parts of lateral roots-presenting a potential and complementary mechanism of grafted plants to enhance nutrient foraging. The studied melon and watermelon scions may thus increase the nutrient foraging capacity of grafted plants by fostering the relative allocation of C to the root system, and enhancing the extracellular enzymatic activities governed by roots or their rhizobiome.

A root is a root is a root? Water uptake rates of Citrus root orders.

Knowledge about the physiological function of root orders is scant. In this study, a system to monitor the water flux among root orders was developed using miniaturized chambers. Different root orders of 4-year-old Citrus volkameriana trees were analysed with respect to root morphology and water flux. The eight root orders showed a broad overlap in diameter, but differences in tissue densities and specific root area (SRA) were clearly distinguishable. Thirty per cent of the root branch biomass but 50% of the surface area (SA) was possessed by the first root order, while the fifth accounted for 5% of the SA (20% biomass). The root order was identified as a determinant of water flux. First-order roots showed a significantly higher rate of water uptake than the second and third root orders, whereas the fourth and fifth root orders showed water excess. The water excess suggested the occurrence of hydraulic redistribution (HR) as a result of differences in osmotic potentials. We suggest that plants may utilize hydraulic redistribution to prevent coarse root desiccation and/or to increase nutrient acquisition. Our study showed that the novel 'miniature depletion chamber' method enabled direct measurement of water fluxes per root order and can be a major tool for future studies on root order traits.