Skip to main content Skip to main navigation menu Skip to site footer
Type: Proceedings Papers
Published: 2022-11-30
Page range: 63-64
Abstract views: 116
PDF downloaded: 9

Modelling and predicting transport of Acari on the plant import pathway

Citrus Research International, Stellenbosch University, Stellenbosch, South Africa
Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, Stellenbosch, South Africa, South African National Biodiversity Institute, Kirstenbosch Research Centre, Cape Town, South Africa
Centre of Excellence for Biosecurity Risk Analysis, School of BioSciences, The University of Melbourne, Parkville, Victoria, Australia
Centre for Invasion Biology, Department of Conservation Ecology and Entomology, Faculty of AgriSciences, Stellenbosch University, Stellenbosch, South Africa
Acari

Abstract

Acari, as with other small arthropods, are most commonly introduced to new areas as contaminants of agricultural trade. The biosecurity risk of such trade is managed by national and regional biosecurity systems, a chief aim of which is to prevent the introduction of agricultural and environmental pests. However, agricultural contaminants are introduced unintentionally, can occur on any product in a wide range of places, and are often very small in size, which makes them inherently difficult to study, understand, and manage.

References

  1. Saccaggi, D.L., Arendse, M., Wilson, J.R.U. & Terblanche. J.S. (2021) Contaminant organisms recorded on plant product imports to South Africa 1994-2019. Scientific Data, 8, 1–11. https://doi.org/10.1038/s41597-021-00869-z

  2. Saccaggi, D.L., Karsten, M., Robertson, M.P., Kumschick, S., Somers, M.J.J., Wilson, R.U. & Terblanche, .J.S. (2016) Methods and approaches for the management of arthropod border incursions. Biological Invasions, 18, 1057–1075. https://doi.org/10.1007/s10530-016-1085-6

  3. Saccaggi, D.L., Wilson, J.R.U., Robinson, A.P. & Terblanche, J.S. (2022) Arthropods on imported plant products: Volumes predict general trends while contextual details enhance predictive power. Ecological Applications, 1–14. https://doi.org/10.1002/eap.2554