High‐resolution minirhizotrons advance our understanding of root‐fungal dynamics in an experimentally warmed peatland

Defrenne, Camille E.; Childs, Joanne; Fernandez, Christopher W.; Taggart, Michael; Nettles, W. R.; Allen, Michael F.; Hanson, Paul J.; Iversen, Colleen M.

doi:10.1002/ppp3.10172

Cited by 26 publications

(30 citation statements)

References 64 publications

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“…This fits well to changes in the fine root morphology as discussed above (increases in SRL, SRA, RAI, and RTID), because alterations in host–plant nutrition might induce a direct shift in host–tree C allocation to EcM fungi (Lilleskov & Bruns, 2001; Treseder, 2004). The increase in the relative abundance of the genus Boletus , a long‐distance exploration EcM species, appears conflicting, but it is very long and highly differentiated hydrophobic mantles and rhizomorphs, which avoid hyphal water and nutrient leakage when transported over long distances (Agerer, 2006), may indicate increasing plant demand for nutrients such as P and K. The increase in the relative abundance of long‐distance EcM, like Boletus at 10–20 cm soil depth in warmed plots, was also observed in other soil warming studies (Defrenne et al, 2021), although it was mainly related to increasing water uptake from deeper soil layers.…”

Section: Discussionmentioning

confidence: 54%

Long‐term soil warming alters fine root dynamics and morphology, and their ectomycorrhizal fungal community in a temperate forest soil

Kengdo

Peršoh

Schindlbacher

et al. 2022

Global Change Biology

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Climate warming is predicted to affect temperate forests severely, but the response of fine roots, key to plant nutrition, water uptake, soil carbon, and nutrient cycling is unclear. Understanding how fine roots will respond to increasing temperature is a prerequisite for predicting the functioning of forests in a warmer climate. We studied the response of fine roots and their ectomycorrhizal (EcM) fungal and root‐associated bacterial communities to soil warming by 4°C in a mixed spruce‐beech forest in the Austrian Limestone Alps after 8 and 14 years of soil warming, respectively. Fine root biomass (FRB) and fine root production were 17% and 128% higher in the warmed plots, respectively, after 14 years. The increase in FRB (13%) was not significant after 8 years of treatment, whereas specific root length, specific root area, and root tip density were significantly higher in warmed plots at both sampling occasions. Soil warming did not affect EcM exploration types and diversity, but changed their community composition, with an increase in the relative abundance of Cenoccocum at 0–10 cm soil depth, a drought‐stress‐tolerant genus, and an increase in short‐ and long‐distance exploration types like Sebacina and Boletus at 10–20 cm soil depth. Warming increased the root‐associated bacterial diversity but did not affect their community composition. Soil warming did not affect nutrient concentrations of fine roots, though we found indications of limited soil phosphorus (P) and potassium (K) availability. Our findings suggest that, in the studied ecosystem, global warming could persistently increase soil carbon inputs due to accelerated fine root growth and turnover, and could simultaneously alter fine root morphology and EcM fungal community composition toward improved nutrient foraging.

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Section: Discussionmentioning

confidence: 54%

Long‐term soil warming alters fine root dynamics and morphology, and their ectomycorrhizal fungal community in a temperate forest soil

Kengdo

Peršoh

Schindlbacher

et al. 2022

Global Change Biology

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“…Up to now, the manual annotation of roots in the minirhizotron images has been the bottleneck for studying root dynamics in high spatial and temporal resolution. Automated minirhizotrons for field studies exist, but manual analysis of the resulting images have so far prevented tapping their full potential concerning temporal resolution and replication (Allen & Kitajima, 2013;Defrenne et al, 2021). Once trained to the given ecosystem (soil type, root morphology, etc.…”

Section: Discussionmentioning

confidence: 99%

As good as human experts in detecting plant roots in minirhizotron images but efficient and reproducible: The Convolutional Neural Network “RootDetector”

Peters

Blume‐Werry

Gillert

et al. 2022

Preprint

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Plant roots influence many ecological and biogeochemical processes, such as carbon, water and nutrient cycling. Because of difficult accessibility, knowledge on plant root dynamics in field conditions, however, is fragmentary at best. Minirhizotrons, i.e. transparent tubes placed in the substrate into which specialized cameras are inserted, facilitate the capture of high-resolution images of root dynamics at the soil-tube interface with little to no disturbance after the initial installation. Their use, especially in field studies with multiple species and heterogeneous substrates, though, is limited by the amount of work that subsequent manual tracing of roots in the images requires. Furthermore, the reproducibility and objectivity of manual root detection is questionable. Here, we use a Convolutional Neural Network (CNN) for the automatic detection of roots in minirhizotron images and compare the performance of our RootDetector with human analysts with different levels of expertise. The minirhizotron data stem from various wetland types on organic soils. RootDetector showed a high capability to correctly segmenting root pixels in minirhizotron images from field observations (F1 = 0.6044; r² compared to a human expert = 0.99). Reproducibility among humans, however, depended strongly on expertise level, with novices showing drastic variation among individual analysts and annotating on average almost 3-times higher root length/cm² per image compared to expert analysts. Analyses with RootDetector save resources, are reproducible and objective, and are as accurate as manual analyses performed by human experts.

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“…The qualitative and quantitative analysis of root anatomy has been facilitated by the development of high-throughput root phenotyping techniques such as laser ablation tomography (Strock et al ., 2019) or vibratome sectioning coupled with confocal microscopy (Atkinson & Wells, 2017). The development of high-resolution minirhizotrons has revolutionised our understanding of root-fungal dynamics (Defrenne et al ., 2020), and automated root imaging platforms have enabled an in-depth characterisation of the natural variation in growth dynamics and root system architecture within species (Rellán-Álvarez et al ., 2015; LaRue et al ., 2021). The measurement of physiological root traits is being facilitated by the development of functional phenomics platforms for the high-throughput phenotyping of ion uptake rates and root respiration (Griffiths et al ., 2021; Guo et al ., 2021), as well as methods for collecting and characterising root exudates (Oburger & Jones, 2018; Uthe et al ., 2021; Williams et al ., 2021).…”

Section: A Way Forwardmentioning

confidence: 99%

A snapshot of the root phenotyping landscape in 2021

Delory

Hernandez‐Soriano

Wacker

et al. 2022

Preprint

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Root phenotyping describes methods for measuring root properties, or traits. While root phenotyping can be challenging, it is advancing quickly. In order for the field to move forward, it is essential to understand the current state and challenges of root phenotyping, as well as the pressing needs of the root biology community. In this letter, we present and discuss the results of a survey that was created and disseminated by members of the Graduate Student and Postdoc Ambassador Program at the 11th symposium of the International Society of Root Research. This survey aimed to (1) provide an overview of the objectives, biological models and methodological approaches used in root phenotyping studies, and (2) identify the main limitations currently faced by plant scientists with regard to root phenotyping. Our survey highlighted that (1) monocotyledonous crops dominate the root phenotyping landscape, (2) root phenotyping is mainly used to quantify morphological and architectural root traits, (3) 2D root scanning/imaging is the most widely used root phenotyping technique, (4) time-consuming tasks are an important barrier to root phenotyping, (5) there is a need for standardised, high-throughput methods to sample and phenotype roots, particularly under field conditions, and to improve our understanding of trait-function relationships.

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High‐resolution minirhizotrons advance our understanding of root‐fungal dynamics in an experimentally warmed peatland

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 26 publications

References 64 publications

Long‐term soil warming alters fine root dynamics and morphology, and their ectomycorrhizal fungal community in a temperate forest soil

Long‐term soil warming alters fine root dynamics and morphology, and their ectomycorrhizal fungal community in a temperate forest soil

As good as human experts in detecting plant roots in minirhizotron images but efficient and reproducible: The Convolutional Neural Network “RootDetector”

A snapshot of the root phenotyping landscape in 2021

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