Development of hazard site surveillance programs for forest invasive species: A case study from Brisbane, Australia

Hazard site surveillance is a system for post-border detection of new pest incursions, targeting sites that are considered potentially at high risk of such introductions. Globalisation, increased volumes of containerised freight and competition for space at domestic ports means that goods are increasingly being first opened at premises some distance from the port of entry, thus dispersing risk away from the main inspection point. Hazard site surveillance acts as a backstop to border control to ensure that new incursions are detected sufficiently early to allow the full range of management options, including eradication and containment, to be considered. This is particularly important for some of the more cryptic forest pests whose presence in a forest often is not discovered until populations are already high and the pest is well established. General requirements for a hazard site surveillance program are discussed using a program developed in Brisbane, Australia, in 2006 as a case study. Some early results from the Brisbane program are presented. In total 67 species and 5757 individuals of wood-boring beetles have been trapped and identified during the program to date. Scolytines are the most abundant taxa, making up 83% of the catch. No new exotics have been trapped but 19 of the species and 60% of all specimens caught are exotics that are already established in Australia.

Fuel manipulation with herbicide treatments to reduce fire hazard in young pine (Pinus elliottii × P. caribaea) plantations in south-east Queensland, Australia

Wildfire represents a major risk to pine plantations. This risk is particularly great for young plantations (generally less than 10 m in height) where prescribed fire cannot be used to manipulate fuel biomass, and where flammable grasses are abundant in the understorey. We report results from a replicated field experiment designed to determine the effects of two rates of glyphosate (450 g L–1) application, two extents of application (inter-row only and inter-row and row) with applications being applied once or twice, on understorey fine fuel biomass, fuel structure and composition in south-east Queensland, Australia. Two herbicide applications (~9 months apart) were more effective than a once-off treatment for reducing standing biomass, grass continuity, grass height, percentage grass dry weight and the density of shrubs. In addition, the 6-L ha–1 rate of application was more effective than the 3-L ha–1 rate of application in periodically reducing grass continuity and shrub density in the inter-rows and in reducing standing biomass in the tree rows, and application in the inter-rows and rows significantly reduced shrub density relative to the inter-row-only application. Herbicide treatment in the inter-rows and rows is likely to be useful for managing fuels before prescribed fire in young pine plantations because such treatment minimised tree scorch height during prescribed burns. Further, herbicide treatments had no adverse effects on plantation trees, and in some cases tree growth was enhanced by treatments. However, the effectiveness of herbicide treatments in reducing the risk of tree damage or mortality under wildfire conditions remains untested.

Hazard Function Models to Estimate Mortality Rates Affecting Fish Populations with Application to the Sea Mullet (Mugil cephalus) Fishery on the Queensland Coast (Australia)

Fisheries management agencies around the world collect age data for the purpose of assessing the status of natural resources in their jurisdiction. Estimates of mortality rates represent a key information to assess the sustainability of fish stocks exploitation. Contrary to medical research or manufacturing where survival analysis is routinely applied to estimate failure rates, survival analysis has seldom been applied in fisheries stock assessment despite similar purposes between these fields of applied statistics. In this paper, we developed hazard functions to model the dynamic of an exploited fish population. These functions were used to estimate all parameters necessary for stock assessment (including natural and fishing mortality rates as well as gear selectivity) by maximum likelihood using age data from a sample of catch. This novel application of survival analysis to fisheries stock assessment was tested by Monte Carlo simulations to assert that it provided unbiased estimations of relevant quantities. The method was applied to the data from the Queensland (Australia) sea mullet (Mugil cephalus) commercial fishery collected between 2007 and 2014. It provided, for the first time, an estimate of natural mortality affecting this stock: 0.22±0.08 year −1 .