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Biological Invasions

, Volume 19, Issue 10, pp 3013–3035 | Cite as

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

  • Ronald E. Fournier
  • Jean J. Turgeon
Original Paper

Abstract

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.

Keywords

Visual surveys Invasive alien species Adaptive management Organisational learning DIKW hierarchy Asian longhorned beetle 

Notes

Acknowledgements

We thank Ben Gasman (project manager of the Canadian Food Inspection Agency’s (CFIA) eradication programme against A. glabripennis in Toronto), Mary Orr (CFIA), and Steve Matsumoto (City of Toronto) for providing assistance, feedback and information necessary for us to develop and field test this decision support system; Robert Haack (U.S.D.A. Forest Service), R. Talbot Trotter III (U.S.D.A. Forest Service), Eckehard Brockerhoff (New Zealand Forest Research Institute), Kevin Dodds (U.S.D.A. Forest Service), and four anonymous reviewers for helpful comments and suggestions on earlier drafts of this manuscript; and, all inspectors, supervisors, and data management staff at the CFIA for implementing the system. Natural Resources Canada funded the development of this system.

Supplementary material

10530_2017_1505_MOESM1_ESM.pdf (69 kb)
Supplementary material 1 (PDF 69 kb)
10530_2017_1505_MOESM2_ESM.pdf (82 kb)
Supplementary material 2 (PDF 81 kb)
10530_2017_1505_MOESM3_ESM.pdf (2.1 mb)
Supplementary material 3 (PDF 2110 kb)

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Copyright information

© Her Majesty the Queen in Right of Canada 2017

Authors and Affiliations

  1. 1.Natural Resources Canada – Canadian Forest ServiceGreat Lakes Forestry CentreSault Ste. MarieCanada

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