Using ecological community data to optimise the sensitivity and specificity of biosecurity surveillance networks

Trade is never zero risk; there is always some residual probability that an unwanted, potentially invasive, species will cross our border. The most crucial element that prevents an incursion from progressing to an establishment is early detection, to maximise potential eradication success. Detection relies on surveillance and Biosecurity NZ operates 13 targeted surveillance programmes (species or pathways) and a general surveillance programme that encourages public reporting via a 0800 hot line. New Zealand does not operate a non-specific trapping programme at first ports of entry, e.g., flight intercept traps at air and sea ports. However, internationally such trapping programmes have shown that they can detect new incursions. Globally the big research gap for non-specific trapping is that we do not understand the sensitivity and specificity of a given trapping programme design. We propose to solve this problem by using ecological community data of invertebrates collected by a range of different trap types, e.g., pitfall, flight intercept etc. Normally when analysing such data for ecological purposes we remove rare species from the analysis. However, these are the species that we want to detect for biosecurity purposes and thus surveillance network must be optimised to detect these rare events.
Supervisors
Supervisor: Steve Pawson
Key qualifications and skills
An interest in biological systems and a Bachelor and Masters level qualification in mathematics, statistics or closely related subject, with prior learning in areas such as mathematical modelling, stochastic processes, and sampling design. Biologists that have a strong affinity for, and proven experience in, applied mathematical problems will be considered.
Does the project come with funding
Yes - The scholarship will cover living expenses at NZ$28,000 per year for three years and study fees
Final date for receiving applications
Ongoing
Keywords
invertebrates, systems, modelling, sampling design, biology, statistics, biosecurity