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Zhang Y, Cao J, Lu M, Kardol P, Wang J, Fan G, Kong D. The origin of bi-dimensionality in plant root traits. Trends Ecol Evol 2024; 39:78-88. [PMID: 37777374 DOI: 10.1016/j.tree.2023.09.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 09/01/2023] [Accepted: 09/01/2023] [Indexed: 10/02/2023]
Abstract
Plant roots show extraordinary diversity in form and function in heterogeneous environments. Mounting evidence has shown global bi-dimensionality in root traits, the root economics spectrum (RES), and an orthogonal dimension describing mycorrhizal collaboration; however, the origin of the bi-dimensionality remains unresolved. Here, we propose that bi-dimensionality arises from the cylindrical geometry of roots, allometry between root cortex and stele, and independence between root cell wall thickness and cell number. Root geometry and mycorrhizal collaboration may both underlie the bi-dimensionality. Further, we emphasize why plant roots should be cylindrical rather than flat. Finally, we highlight the need to integrate organ-, cellular-, and molecular-level processes driving the bi-dimensionality in plant roots to fully understand plant diversity and functions.
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Affiliation(s)
- Yue Zhang
- College of Forestry, Henan Agricultural University, Zhengzhou 450002, China
| | - Jingjing Cao
- College of Forestry, Henan Agricultural University, Zhengzhou 450002, China
| | | | - Paul Kardol
- Department of Forest Mycology and Plant Pathology, Swedish University of Agricultural Sciences, Umeå, 75007, Sweden; Department of Forest Ecology and Management, Swedish University of Agricultural Sciences, Umeå, 90183, Sweden
| | - Junjian Wang
- Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong 518055, China
| | - Guoqiang Fan
- College of Forestry, Henan Agricultural University, Zhengzhou 450002, China
| | - Deliang Kong
- College of Forestry, Henan Agricultural University, Zhengzhou 450002, China.
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Seibold S, Müller J, Allner S, Willner M, Baldrian P, Ulyshen MD, Brandl R, Bässler C, Hagge J, Mitesser O. Quantifying wood decomposition by insects and fungi using computed tomography scanning and machine learning. Sci Rep 2022; 12:16150. [PMID: 36168033 PMCID: PMC9515192 DOI: 10.1038/s41598-022-20377-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 09/13/2022] [Indexed: 11/18/2022] Open
Abstract
Wood decomposition is a central process contributing to global carbon and nutrient cycling. Quantifying the role of the major biotic agents of wood decomposition, i.e. insects and fungi, is thus important for a better understanding of this process. Methods to quantify wood decomposition, such as dry mass loss, suffer from several shortcomings, such as destructive sampling or subsampling. We developed and tested a new approach based on computed tomography (CT) scanning and semi-automatic image analysis of logs from a field experiment with manipulated beetle communities. We quantified the volume of beetle tunnels in wood and bark and the relative wood volume showing signs of fungal decay and compared both measures to classic approaches. The volume of beetle tunnels was correlated with dry mass loss and clearly reflected the differences between beetle functional groups. Fungal decay was identified with high accuracy and strongly correlated with ergosterol content. Our data show that this is a powerful approach to quantify wood decomposition by insects and fungi. In contrast to other methods, it is non-destructive, covers entire deadwood objects and provides spatially explicit information opening a wide range of research options. For the development of general models, we urge researchers to publish training data.
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Affiliation(s)
- Sebastian Seibold
- Ecosystem Dynamics and Forest Management Group, Technical University of Munich, 85354, Freising, Germany. .,Berchtesgaden National Park, Doktorberg 6, 83471, Berchtesgaden, Germany. .,Terrestrial Ecology Research Group, Technical University of Munich, 85354, Freising, Germany.
| | - Jörg Müller
- Field Station Fabrikschleichach, Animal Ecology and Tropical Biology, Biocenter, University of Würzburg, Glashüttenstrasse 5, 96181, Rauhenebrach, Germany.,Bavarian Forest National Park, Freyungerstrasse 2, 94481, Grafenau, Germany
| | | | - Marian Willner
- MITOS GmbH, Lichtenbergstrasse 8, 85748, Garching, Germany
| | - Petr Baldrian
- Laboratory of Environmental Microbiology, Institute of Microbiology of the Czech Academy of Sciences, Videnska 1083, 14220, Praha 4, Czech Republic
| | | | - Roland Brandl
- Faculty of Biology, Department of Ecology, Animal Ecology, Philipps-Universität Marburg, Karl-Von-Frisch Strasse 8, 35032, Marburg, Germany
| | - Claus Bässler
- Bavarian Forest National Park, Freyungerstrasse 2, 94481, Grafenau, Germany.,Faculty of Biological Sciences, Institute for Ecology, Evolution and Diversity, Goethe University Frankfurt, 60438, Frankfurt am Main, Germany
| | - Jonas Hagge
- Forest Nature Conservation, Northwest German Forest Research Institute NW-FVA, 34346, Hann. Münden, Germany.,Forest Nature Conservation, Georg-August-University Göttingen, 37077, Göttingen, Germany
| | - Oliver Mitesser
- Field Station Fabrikschleichach, Animal Ecology and Tropical Biology, Biocenter, University of Würzburg, Glashüttenstrasse 5, 96181, Rauhenebrach, Germany
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