JOURNAL ARTICLE

Trophic interactions between plants, pollinators, florivores and predators: a global systematic review.

  • Published In: Biological Journal of the Linnean Society, 2024, v. 141, n. 2. P. 214 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Camurça, Letícia Menezes; Santos, André Mauricio Melo; Castro, Cibele Cardoso; Leite, Ana Virgínia 3 of 3

Abstract

This article systematically reviews global research on multitrophic interactions among plants, pollinators, florivores (organisms that feed on floral tissues), and spiders, focusing on how plant characteristics influence these relationships and their effects on plant reproductive success. The review found that herbaceous plants, especially from the family Asteraceae, and temperate broadleaf and mixed forests are the most studied, with bees (Apidae) as the predominant pollinators, Chrysomelidae beetles as common florivores, and Thomisidae spiders as frequent predators. Floral longevity significantly explains florivore presence, while spider presence is associated with plant life-form, floral symmetry, shape, pollination unit (isolated flowers versus inflorescences), and nectar availability; however, flower color and odor were not significant factors. Meta-analysis indicated that spiders generally have a neutral effect on fruit set, though results vary by study, and a notable knowledge gap exists regarding florivore impacts on fruit production. The authors emphasize the need for standardized methodologies in future research to better quantify these complex interactions.

Additional Information

  • Source:Biological Journal of the Linnean Society. 2024/02, Vol. 141, Issue 2, p214
  • Document Type:Article
  • Subject Area:Science
  • Publication Date:2024
  • ISSN:0024-4066
  • DOI:10.1093/biolinnean/blad079
  • Accession Number:175194385
  • Copyright Statement:Copyright of Biological Journal of the Linnean Society is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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