Dataset Information
The potential global distribution of the papaya mealybug, Paracoccus marginatus, a polyphagous pest.
Ontology highlight
ABSTRACT: Background
The papaya mealybug, Paracoccus marginatus, is a highly polyphagous invasive pest that affects more than 200 plants, many of which are of economic importance. We modelled the potential distribution of P. marginatus using CLIMEX, a process-oriented, climate-based niche model. We combined this model with spatial data on irrigation and cropping patterns to increase the real-world applicability of the model.Results
The resulting model agreed with known distribution points for this pest and with broad areas where P. marginatus has been reported, but for which no GPS data were available. Our model highlights the potential expansion of P. marginatus into novel areas in Central and East Africa, as well as further expansion in Central America and Asia, as these areas are highly climatically suitable, and have large expanses of suitable crop hosts. It also highlights areas, such as the central and eastern states of the USA as well as the western provinces of China, that are suitable for seasonal invasions of P. marginatus.Conclusion
Our results offer refined resolution on areas with high potential for invasion by P. marginatus. © 2020 Society of Chemical Industry.
SUBMITTER: Finch EA
PROVIDER: S-EPMC7894313 | biostudies-literature | 2021 Mar
REPOSITORIES: biostudies-literature
Publications
The potential global distribution of the papaya mealybug, Paracoccus marginatus, a polyphagous pest.
Pest management science 20201104 3
<h4>Background</h4>The papaya mealybug, Paracoccus marginatus, is a highly polyphagous invasive pest that affects more than 200 plants, many of which are of economic importance. We modelled the potential distribution of P. marginatus using CLIMEX, a process-oriented, climate-based niche model. We combined this model with spatial data on irrigation and cropping patterns to increase the real-world applicability of the model.<h4>Results</h4>The resulting model agreed with known distribution points ...[more]
