Transcending pairwise interactions in ecological networks remains a challenge. Higher-order interactions (HOIs), the modulation of a pairwise interaction by a third species, are thought to play a particularly important role in stabilizing coexistence and maintaining species diversity. However, HOIs have so far only been demonstrated in models or isolated experimental systems including only a few interacting species. Their ubiquity and importance at a community level in the real world remain unknown. We hypothesized that a complex network of HOIs could be constantly modifying pairwise interactions and shaping ecological communities and that consequently the outcome of pairwise interactions would be a product of many influences from distinct sources. Using field experiments, we tested how multiple interactions within a diverse arthropod community associated with the tropical shrub Baccharis dracunculifolia D.C. (Asteraceae) were modified by the removal of ant species or live or hatched insect galls (a non-trophic engineering effect) of the dominant galler species. We revealed an extensive hidden network of HOIs modifying each other and the "visible" pairwise interactions. Most pairwise interactions were affected indirectly by the manipulation of non-interacting taxonomic groups. The pervasiveness of these interaction modifications challenges pairwise approaches to understanding interaction outcomes and could shift our thinking about the structure and persistence of ecological communities. Investigating coexistence mechanisms involving interaction modulation by HOIs may be key to elucidating the underlying causes of the stability and persistence of ecological communities.
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http://dx.doi.org/10.1016/j.cub.2022.11.057 | DOI Listing |
J Affect Disord
January 2025
Research Department of Clinical, Educational & Health Psychology, University College London, UK; Anna Freud National Centre for Children and Families, London, UK.
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View Article and Find Full Text PDFJ Sport Rehabil
January 2025
Faculty of Physical Therapy and Rehabilitation, Hacettepe University, Ankara, Turkey.
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Design: Cross-sectional and pre-post intervention designs were utilized on this study.
Sensors (Basel)
January 2025
Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR 999078, China.
Visible-infrared person re-identification (VI-ReID) is a challenging cross-modality retrieval task to match a person across different spectral camera views. Most existing works focus on learning shared feature representations from the final embedding space of advanced networks to alleviate modality differences between visible and infrared images. However, exclusively relying on high-level semantic information from the network's final layers can restrict shared feature representations and overlook the benefits of low-level details.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
Departamento de Biologia, Faculdade de Filosofia, Ciências e Letras de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto 14040-901, SP, Brazil.
In the flower development study, we identified SCI1 (Stigma/style Cell-cycle Inhibitor 1), a regulator of cell proliferation. SCI1 interacts with NtCDKG;2 ( Cyclin-Dependent Kinase G;2), a homolog of human CDK11, which is responsible for RanGTP-dependent microtubule stabilization, regulating spindle assembly rate. In a Y2H screening of a cDNA library using NtCDKG;2 as bait, a RanBP1 (Ran-Binding Protein 1) was revealed as its interaction partner.
View Article and Find Full Text PDFMed Image Anal
January 2025
Leiden University Medical Center, Albinusdreef 2, 2333 ZA, Leiden, The Netherlands; Amsterdam University Medical Center, Meibergdreef 9, 1105 AZ, Amsterdam, The Netherlands.
Histopathological analysis of whole slide images (WSIs) has seen a surge in the utilization of deep learning methods, particularly Convolutional Neural Networks (CNNs). However, CNNs often fail to capture the intricate spatial dependencies inherent in WSIs. Graph Neural Networks (GNNs) present a promising alternative, adept at directly modeling pairwise interactions and effectively discerning the topological tissue and cellular structures within WSIs.
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