Abstract
Invasions by pest insects pose a significant threat to agriculture worldwide. In the case of Ceratitis capitata incursions on the US mainland, where it is not officially established, repeated detections are followed by quarantines and treatments to eliminate the invading population. However, it is difficult to accurately set quarantine duration because non-detection may not mean the pest is eliminated. Most programs extend quarantine lengths past the last fly detection by calculating the amount of time required for 3 generations to elapse under a thermal unit accumulation development model ("degree day"). A newer approach is to use an Agent-Based Simulation (ABS) to explicitly simulate population demographics and elimination. Here, predicted quarantine lengths for 11 sites in the continental United States are evaluated using both approaches. Results indicate a strong seasonality in quarantine length, with longer predictions in the second half of the year compared with the first; this pattern is more extreme in degree day predictions compared with ABS. Geographically, quarantine lengths increased with latitude, though this was less pronounced under the ABS. Variation in quarantine lengths for particular times and places was dramatically larger for degree day than ABS, generally spiking in the middle of the year for degree day and peaking in second half of the year for ABS. Analysis of 34 C. capitata quarantines from 1975 to 2017 in California shows that, for all but two, quarantines were started in the second half of the year, when degree day quarantine lengths are longest and have the highest uncertainty. For a set of hypothetical outbreaks based on these historical quarantines, the ABS produced significantly shorter quarantines than degree day calculations. Overall, ABS quarantine lengths were more consistent than degree day predictions, avoided unrealistically long values, and captured effects of rare events such as cold snaps.
Highlights
Invasions by insects, pathogens and pests are increasingly a defining challenge of the 21st century, facilitated by global connectivity, climatic shifts, and other factors[1,2], with a severe impact on agriculture[3]
SFO is an exception to this common trend, with the mean normal accounting for only 9.1% of the variation in degree day based predicted quarantine length (PQL) and 28.0% of the Agent-Based Simulation (ABS) based PQL
Analyzing the timing and locations of historic outbreaks suggests that quarantine lengths would generally be more consistent and shorter on average in California if estimated by ABS compared with degree day
Summary
Pathogens and pests are increasingly a defining challenge of the 21st century, facilitated by global connectivity, climatic shifts, and other factors[1,2], with a severe impact on agriculture[3]. One factor determining the feasibility of elimination is if the new environment is only marginally or seasonally suitable to the invading insect, facilitating its eradication. Another is when the high cost of allowing establishment leads to extensive efforts for eradication. The examples given for eradications are all historical, including the cited review paper[2], which is not very optimistic about eradication as an effective tool for managing invasions. The science of eradication has advanced considerably in recent years and better understanding of invasive ecology, improved surveillance and control tools, and important advances in understanding and managing social expectations around eradication programmes mean that biosecurity agencies can conduct such operations with much greater certainty, efficacy and efficiency. I am intrigued by the statement that predicting generation times into the future using normal temperatures is “mathematically flawed” and would like further clarification about what the authors mean
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