Exploring the potential effects of arthropod-infecting pathogens on pollination

Rover Bernhard1, Nardine Francis2, Anna Luckenbach2, Isabella Ng2, Maisy Feely2, Katherine Garcia2, Winelia Recart-Gonzalez2, Arietta Fleming-Davies2

1. Lewis & Clark College; 2. University of San Diego

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Abstract
  • Arthropods such as insects play significant direct and indirect roles in the lives of plants. Although some of these relationships are harmful to the plant, such as herbivory, others are mutually beneficial, such as pollination. The relationships between plants and arthropods, especially pollination, have been intensely studied in the literature. However, arthropods, like most living organisms, are vulnerable to infection by pathogens. Despite the fact that arthropod pollination and infection have been extensively studied, little work has been done to elucidate the intersection of these two phenomena. Pathogens of arthropods have the potential to disrupt the pollination process directly, by affecting pollinator populations or traits. In addition, pathogens might infect insect herbivores and or reduce herbivory damage, therefore allowing a plant to delegate more resources to production of flowers and floral rewards for pollinators. Lastly, pathogens could also infect arthropod predators of pollinators or herbivores, with potential indirect effects on pollination. We conducted a meta-analysis to 1) summarize the existing literature on effects of pathogens on arthropod pollinators and herbivores and 2) quantify the extent to which pathogens affect arthropod population density, physiology, morphology, and behavior, with potential repercussions for pollination. To find prior published studies, we searched the Web of Science database, as well as the articles cited in literature reviews on pollination or disease. So far, we have reviewed 1470 published articles for relevant data. Of these, 63 articles have been deemed to have relevant data, and we have extracted data from 19 of them, recording the means and standard errors of relevant traits. In the future, we plan to use statistical analysis to determine the true effect size of pathogens in each category.