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Aim We developed a new method to design objective, risk-based surveillance systems for non-indigenous species of invertebrates, vertebrates and plants, which might be introduced to a natural area through an industrial project; here, we provide the invertebrate case study. The method addresses issues common to complex surveillance design problems: a statistical standard (e.g. power); information gaps; multiple targets of unclear identity; a large surveillance area of heterogeneous risk of invasion; integrating multiple sources of surveillance data; optimizing for cost. Location Barrow Island, Western Australia. Methods We mapped the surveillance area for risk to target surveillance activities. An expert group identified a set of exemplar species and identified and characterized a set of detection methods for each, such that all potential invaders would be detected. We devised multi-element surveillance systems to detect each exemplar to the design power (0.8), then integrated them to a single system that was optimized for cost. Results The surveillance system was deployed on the island to specification over 1 year, then reviewed for redesign in a second period. Main conclusions The new method provided practical, risk-based surveillance system designs that met application requirements and overcame complex issues common to many surveillance applications. A review of experiences from surveillance in the first year led to practical improvements and design efficiencies. [ABSTRACT FROM AUTHOR]

An intensive survey of terrestrial invertebrates was undertaken on Barrow Island, off the north-west coast of Western Australia, over a 5-year period from 2005 to 2009. The study was conducted as part of an environmental impact assessment for a liquefied natural gas (LNG) development on the island, with the aim of providing baseline information on invertebrates as a component of a future detection program in support of the island's quarantine system. The study used a standardised methodology for sampling a variety of undisturbed native vegetation communities, in addition to disturbed sites (vegetated and non-vegetated sites) across the island. Pre-eminent invertebrate taxonomists from Australia and overseas were engaged to assist with the identification of the various invertebrate orders collected. A total of 1873 species and morphospecies from 27 invertebrate orders were collected, 292 of which represented named species. A total of 321 families of invertebrates were represented in the collections. Samples taken during the same month in two consecutive years exhibited almost the same degree of difference as samples taken during the same year in the wet and the dry season. For ants, the fauna had greater affinity with the adjacent Pilbara than the Carnarvon basin Bioregion. In terms of sampling rigour and taxonomic coverage, this work represents one of the most intensive and comprehensive terrestrial invertebrate surveys presently undertaken in Australia. [ABSTRACT FROM AUTHOR]

Surveillance for invasive non-indigenous species (NIS) is an integral part of a quarantine system. Estimating the efficiency of a surveillance strategy relies on many uncertain parameters estimated by experts, such as the efficiency of its components in face of the specific NIS, the ability of the NIS to inhabit different environments, and so on. Due to the importance of detecting an invasive NIS within a critical period of time, it is crucial that these uncertainties be accounted for in the design of the surveillance system. We formulate a detection model that takes into account, in addition to structured sampling for incursive NIS, incidental detection by untrained workers. We use info-gap theory for satisficing (not minimizing) the probability of detection, while at the same time maximizing the robustness to uncertainty. We demonstrate the trade-off between robustness to uncertainty, and an increase in the required probability of detection. An empirical example based on the detection of Pheidole megacephala on Barrow Island demonstrates the use of info-gap analysis to select a surveillance strategy. [Copyright &y& Elsevier]