A generic risk-based surveying method for invading plant pathogens

A - Papers appearing in refereed journals

Parnell, S., Gottwald, T. R., Riley, T. and Van Den Bosch, F. 2014. A generic risk-based surveying method for invading plant pathogens. Ecological Applications. 24 (4), pp. 779-790. https://doi.org/10.1890/13-0704.1

AuthorsParnell, S., Gottwald, T. R., Riley, T. and Van Den Bosch, F.

Invasive plant pathogens are increasing with international trade and travel, with damaging environmental and economic consequences. Recent examples include tree diseases such as sudden oak death in the Western United States and ash dieback in Europe. To control an invading pathogen it is crucial that newly infected sites are quickly detected so that measures can be implemented to control the epidemic. However, since sampling resources are often limited, not all locations can be inspected and locations must be prioritized for surveying. Existing approaches to achieve this are often species specific and rely on detailed data collection and parameterization, which is difficult, especially when new arrivals are unanticipated. Consequently regulatory sampling responses are often ad hoc and developed without due consideration of epidemiology, leading to the suboptimal deployment of expensive sampling resources. We introduce a flexible risk-based sampling method that is pathogen generic and enables available information to be utilized to develop epidemiologically informed sampling programs for virtually any biologically relevant plant pathogen. By targeting risk we aim to inform sampling schemes that identify high-impact locations that can be subsequently treated in order to reduce inoculum in the landscape. This "damage limitation" is often the initial management objective following the first discovery of a new invader. Risk at each location is determined by the product of the basic reproductive number (R-0), as a measure of local epidemic size, and the probability of infection. We illustrate how the risk estimates can be used to prioritize a survey by weighting a random sample so that the highest-risk locations have the highest probability of selection. We demonstrate and test the method using a high-quality spatially and temporally resolved data set on Huanglongbing disease (HLB) in Florida, USA. We show that even when available epidemiological information is relatively minimal, the method has strong predictive value and can result in highly effective targeted surveying plans.

KeywordsEcology; Environmental Sciences
Year of Publication2014
JournalEcological Applications
Journal citation24 (4), pp. 779-790
Digital Object Identifier (DOI)https://doi.org/10.1890/13-0704.1
PubMed ID24988776
Open accessPublished as non-open access
FunderBiotechnology and Biological Sciences Research Council
USDA Department of Agriculture Farm Bill
Department of Environment, Food and Rural Affairs
Bill and Melinda Gates Foundation
Funder project or codeDelivering Sustainable Systems (SS) [ISPG]
Movement and spatial ecology in agricultural landscapes
Output statusPublished
Publication dates
Online01 Jun 2014
Publication process dates
Accepted05 Sep 2013

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