135991 20260219090931.0 doi 10.1088/2632-072X/ad459e sideral 138952 ART-2024-138952 eng Payrató-Borrás, Claudia Beyond the aggregated paradigm: phenology and structure in mutualistic networks 2024 Access copy available to the general public Unrestricted Mutualistic relationships, where species interact to obtain mutual benefits, constitute an essential component of natural ecosystems. The use of ecological networks to represent the species and their ecological interactions allows the study of structural and dynamic patterns common to different ecosystems. However, by neglecting the temporal dimension of mutualistic communities, relevant insights into the organization and functioning of natural ecosystems can be lost. Therefore, it is crucial to incorporate empirical phenology -the cycles of species' activity within a season- to fully understand the impact of temporal variability on network architecture. In this paper, by using empirical datasets together with a set of synthetic models, we propose a framework to characterize the phenology of plant-pollinator communities and assess how it reshapes their portrayal as a network. Analyses of three empirical cases reveal that non-trivial information is missed when representing the network of interactions as static, which leads to overestimating the value of fundamental structural features. We discuss the implications of our findings for mutualistic relationships and intra-guild competition for common resources. We show that recorded interactions and species' activity duration are pivotal factors in accurately replicating observed patterns within mutualistic communities. Furthermore, our exploration of synthetic models underscores the system-specific character of the mechanisms driving phenology, increasing our understanding of the complexities of natural ecosystems. info:eu-repo/grantAgreement/ES/DGA/E36-23R-FENOL info:eu-repo/grantAgreement/ES/MICINN/PID2020-115800GB-I00 info:eu-repo/semantics/openAccess by https://creativecommons.org/licenses/by/4.0/deed.es 1.9 2024 0.641 2024 Artificial Intelligence 2024 Q2 Information Systems 2024 Q2 Computer Science Applications 2024 Q2 Computer Networks and Communications 2024 Q2 4.7 2024 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Gracia-Lázaro, Carlos (orcid)0000-0002-9769-8796 Hernández, Laura Moreno, Yamir Universidad de Zaragoza (orcid)0000-0002-0895-1893 2004 405 Universidad de Zaragoza Dpto. Física Teórica Área Física Teórica 5, 2 (2024), e025013 [17 pp.] Journal of Physics: Complexity 2632-072X 1194631 http://zaguan.unizar.es/record/135991/files/texto_completo.pdf Versión publicada 610591 http://zaguan.unizar.es/record/135991/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:135991 articulos driver 2026-02-19-09:00:15 ARTICLE