Maximum entropy networks show that plant–arbuscular mycorrhizal fungi associations are anti‐nested and modular

The authors acknowledge funding for the European Joint Programme-Soils project ‘Symbiotic Solutions for Healthy Agricultural Landscapes (SOIL-HEAL)’, national support for which came from the German Federal Ministry of Education and Research (031B1266); the Biotechnology and Biological Sciences Resea...

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Detalles Bibliográficos
Autores: Ajaz, S., Amin, N., López García, Álvaro, Birt, H., Pajares Murgó, Mariona, Lanfranco, Luisa, Garrido Sánchez, José Luis, Alcántara, Julio M., Rillig, M.C., Johnson, D., Caruso, T.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2026
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:dnet:digitalcsic_::8b4eb7fe089f7ad990ac28da157d2f41
Acceso en línea:http://hdl.handle.net/10261/429703
Access Level:acceso abierto
Palabra clave:Maximum entropy bipartite networks
Modularity
Nestedness
Network structure
Null models
Plant-AMF association
Descripción
Sumario:The authors acknowledge funding for the European Joint Programme-Soils project ‘Symbiotic Solutions for Healthy Agricultural Landscapes (SOIL-HEAL)’, national support for which came from the German Federal Ministry of Education and Research (031B1266); the Biotechnology and Biological Sciences Research Council (BB/X000729/1); the Department of Agriculture, Food and the Marine (DAFM, project 2021EJPSOILEN303) and Research Ireland (20/FFP-P/8584) in Ireland; and the Italian Ministero delle Politiche Agricole Alimentari e Forestali (project ID170). ALG was funded by MCIN/AEI/10.13039/501100011033 and FSE+ through the grant ref. RYC2022-038499-I (Programa Ramón y Cajal). The dataset from Garrido et al. (2023) was obtained through grant PGC2018-100966-B-I00 funded by MCIN /AEI/10.13039/501100011033 and by ‘ERDF A way of making Europe’. TC also wishes to thank Diego Garlaschelli and Giulio Virginio Clemente for advice on data modelling. We also wish to acknowledge the very constructive input from three anonymous reviewers and the editor.