Evaluation of predicted Medfly (Ceratitis capitata) quarantine length in the United States utilizing degree-day and agent-based models

Authors: Collier, Travis; Manoukis, Nicholas

Submitted to: F1000Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/20/2017
Publication Date: 10/20/2017
Citation: Collier, T.C., Manoukis, N. 2017. Evaluation of predicted Medfly (Ceratitis capitata) quarantine length in the United States utilizing degree-day and agent-based models. F1000Research. 6:1863.

Interpretive Summary: This study reports on modeling results comparing two methods for deciding how long to maintain a quarantine following discovery of an invasive fruit fly in the US Mainland. One method is based on the time required for development, and halts quarantine after the time for three generations has passed without a further detection. The other models individual fruit flies in computers and tracks more aspects of their biology including mortality (an “Agent Based Simulation”). We compared the two methods for 11 sites across years within the range 1950-2017. Results indicate a strong seasonality in quarantine length, with longer predictions in the second half of the year compared with the first. Further, quarantine lengths increased with latitude, though again this feature was less pronounced under the ABS. Overall quarantine lengths were more consistent within a site under the ABS compared with the developmental model, and some unrealistically long quarantines at the far northern end of the range we studies were avoided.

Technical 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 to eliminate the invading population. However, it is notoriously difficult to set quarantine duration because non-detection does not necessarily mean the pest is extirpated. Most programs determine quarantine lengths 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 extirpation. Here, predicted quarantine lengths for 11 sites in the continental United States are evaluated. 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 again this feature 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 all but two were declared in the second half of the year, when degree day quarantine lengths are longest and have the highest uncertainty. For this set of hypothetical 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 seen in the northermost site studied (San Francisco), and realistically modeled the effects of rare events such as cold snaps.