Surveillance during monitoring phase of an eradication programme against Anoplophora glabripennis (Motschulsky) guided by a spatial decision support system

Abstract

Listen

Translate article

In 2003, the Canadian Food Inspection Agency (CFIA) undertook an eradication programme against Anoplophora glabripennis (Motschulsky), a phloem- and wood-boring cerambycid beetle from Asia discovered in Toronto and Vaughan, Ontario. The programme included a multi-year surveillance phase in a quarantine area. We developed a spatial decision support system (SDSS) to aid in effective and efficient allocation, tracking, forecasting, and reporting of these surveillance activities. We parameterised our SDSS with data collected by the CFIA during the treatment phase, and from existing policy, scientific and expert knowledge. The SDSS operated within a multi-loop adaptive management framework designed to foster four levels of organisational learning, analogous to the Data–Information–Knowledge–Wisdom hierarchy, to address uncertainty in founding parameters. Increasingly complex feedback was escalated to higher levels of programme management for review, and then integrated into the SDSS for future implementation. Numerous enhancements were approved and implemented during both the SDSS development and operation because of organisational learning fostered by the system. Two basic forms of learning methods were used: visual pattern recognition within graphical SDSS outputs, and hypothesis testing through re-evaluation of founding precepts and parameters. The system successfully guided surveillance until pest-free status was declared nine survey-cycles later, the first four leading to the discovery of small, residual beetle populations. We believe our system is flexible enough to successfully integrate different precepts and parameters, and be implemented as a best practice against this species or other organisms.