A generalised and scalable framework for modelling incursions, surveillance and control of plant and environmental pests

Invasive plant and environmental pests can seriously impact environment, economy, health and amenity. It is challenging to form response policies given the diversity of pest species; complex spatiotemporal interplay between arrival, spread, surveillance, and control; and limited field data when pest...

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Veröffentlicht in:Environmental modelling & software : with environment data news 2021-05, Vol.139, p.105004, Article 105004
Hauptverfasser: Bradhurst, Richard, Spring, Danny, Stanaway, Mark, Milner, James, Kompas, Tom
Format: Artikel
Sprache:eng
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Zusammenfassung:Invasive plant and environmental pests can seriously impact environment, economy, health and amenity. It is challenging to form response policies given the diversity of pest species; complex spatiotemporal interplay between arrival, spread, surveillance, and control; and limited field data when pests are rare/absent. Models can provide useful decision support through the exploration of incursion pathways and comparison of surveillance and control strategies. However, increased use of quantitative models to inform pest management requires adaptable modelling frameworks. The new Australian Priority Pest and Disease modelling framework (APPDIS) allows pest models to be constructed through user configuration choices for a broad range of different pest types. Pest populations may be defined as point incursions, established populations, or estimated mechanistically from environmental criteria. Spread occurs at multiple scales, through either simple mathematical kernels, or more complex spatial pathways, depending on data availability and pest type. Useful experiments can be conducted on general surveillance, specific surveillance, and treatment regimes. Control activities are dynamically resource-constrained and costed for relative comparisons in terms of benefit and cost. A case study on a tramp ant incursion is provided for illustrative purposes.
ISSN:1364-8152
1873-6726
DOI:10.1016/j.envsoft.2021.105004