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      Cooperative root graft networks benefit mangrove trees under stress

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          Abstract

          The occurrence of natural root grafts, the union of roots of the same or different trees, is common and shared across tree species. However, their significance for forest ecology remains little understood. While early research suggested negative effects of root grafting with the risk of pathogen transmission, recent evidence supports the hypothesis that it is an adaptive strategy that reduces stress by facilitating resource exchange. Here, by analysing mangrove root graft networks in a non-destructive way at stand level, we show further evidence of cooperation-associated benefits of root grafting. Grafted trees were found to dominate the upper canopy of the forest, and as the probability of grafting and the frequency of grafted groups increased with a higher environmental stress, the mean number of trees within grafted groups decreased. While trees do not actively ‘choose’ neighbours to graft to, our findings point to the existence of underlying mechanisms that regulate ‘optimal group size’ selection related to resource use within cooperating networks. This work calls for further studies to better understand tree interactions (i.e. network hydraulic redistribution) and their consequences for individual tree and forest stand resilience.

          Abstract

          Vovides et al. investigate mangrove trees at a field site in the Gulf of Mexico to determine the effect of stress on root networks. Non-destructive analyses indicate that the probability of non-selective cooperative root grafting increases with higher environmental stress.

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          Fitting Linear Mixed-Effects Models Usinglme4

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            Emergence of Scaling in Random Networks

            Systems as diverse as genetic networks or the World Wide Web are best described as networks with complex topology. A common property of many large networks is that the vertex connectivities follow a scale-free power-law distribution. This feature was found to be a consequence of two generic mechanisms: (i) networks expand continuously by the addition of new vertices, and (ii) new vertices attach preferentially to sites that are already well connected. A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
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                Author and article information

                Contributors
                Alejandra.Vovides@glasgow.ac.uk
                Journal
                Commun Biol
                Commun Biol
                Communications Biology
                Nature Publishing Group UK (London )
                2399-3642
                5 May 2021
                5 May 2021
                2021
                : 4
                : 513
                Affiliations
                [1 ]GRID grid.8756.c, ISNI 0000 0001 2193 314X, School of Geographical and Earth Sciences, , University of Glasgow, ; Scotland, UK
                [2 ]GRID grid.4488.0, ISNI 0000 0001 2111 7257, Institute of Forest Growth and Forest Computer Sciences, , Technische Universität Dresden, ; Dresden, Germany
                [3 ]GRID grid.121334.6, ISNI 0000 0001 2097 0141, CIRAD, UMR CBGP, INRAE, Institut Agro, IRD, , Univ Montpellier, ; Montpellier, France
                [4 ]GRID grid.8183.2, ISNI 0000 0001 2153 9871, CIRAD, UR GREEN, ; Montpellier, France
                [5 ]GRID grid.452507.1, ISNI 0000 0004 1798 0367, Functional Ecology Network, , Instituto de Ecología A.C., ; Veracruz, Mexico
                Author information
                http://orcid.org/0000-0002-3293-5770
                http://orcid.org/0000-0002-4542-6764
                http://orcid.org/0000-0001-7733-5069
                http://orcid.org/0000-0003-1866-6743
                http://orcid.org/0000-0002-9378-9404
                http://orcid.org/0000-0001-6633-6269
                http://orcid.org/0000-0002-6827-3297
                Article
                2044
                10.1038/s42003-021-02044-x
                8100114
                33953329
                1bc857fa-aa32-4adf-b9fb-852ab086ef47
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 19 November 2020
                : 26 March 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001663, Volkswagen Foundation (VolkswagenStiftung);
                Award ID: 94844
                Award ID: 94844
                Award ID: 94844
                Award ID: 94844
                Award ID: 94844
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000270, RCUK | Natural Environment Research Council (NERC);
                Award ID: NE/P014127/1
                Award ID: NE/P014127/1
                Award Recipient :
                Funded by: Association of Friends and Sponsors of TU-Dresden (No. 61/2017) INECOL (No. 00016)
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                climate-change ecology,ecosystem ecology,ecological networks

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