Ecological Indicators (Dec 2024)

Spatio-temporal variation in arthropod-plant interactions: A direct comparison of eDNA metabarcoding of tree crop flowers and digital video recordings

  • Joshua H. Kestel,
  • Philip W. Bateman,
  • David L. Field,
  • Nicole E. White,
  • Ben L. Phillips,
  • Paul Nevill

Journal volume & issue
Vol. 169
p. 112827

Abstract

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Collating data about natural capital and the ecosystem services that underpin agricultural productivity, such as the activity of beneficial (e.g., pollinators) and antagonistic (e.g., plant pests) native and introduced arthropod taxa, is critical for timely management strategies. To date, these monitoring efforts have largely relied upon conventional survey and monitoring methods (e.g., sweep netting and morphological identifications), which are difficult to implement at the large scale of agriculture. Environmental DNA (eDNA) metabarcoding is a molecular method that amplifies trace amounts of DNA deposited by organisms from diverse substrates including soil, plant tissue and even air. In this study, we used eDNA metabarcoding of tree flowers, complemented with digital video recording (DVR) devices, to detect temporal, fine- and large-scale arthropod community changes across two Persea americana (‘Hass’ avocado) orchards. In total, we detected 42 arthropod families with eDNA metabarcoding. This molecular method detected five times the number of unique taxa (N = 50) compared to the DVRs (N = 10), nearly all of which are unmanaged native species. The number of arthropod eDNA detections increased by 14 % during peak flowering and included species from different functional groups including known arthropod pollinators, pests, parasites and predators. At fine-spatial scales, inflorescence samples collected in the upper and lower canopy show that Hymenoptera taxa were 13 % more likely to be detected in the upper canopy. While at large-spatial scales, eDNA metabarcoding showed that the arthropod communities in both orchards shared less than 50 % similarity at low flowering and became more similar towards peak flowering. With occupancy modelling, we determined that arthropod length did not correlate with eDNA detection probability. Our findings highlight the value of eDNA-based monitoring and illustrate that agroecosystem management requires a growing awareness that the production boundary has expanded, and that the goods and services that unmanaged arthropod species provide need to be included on the balance sheet.

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