Border interceptions of forest insects established in Australia: intercepted invaders travel early and often

Historical plant introductions predict current insect invasions

Thousands of insect species have been introduced outside of their native ranges, and some of them strongly impact ecosystems and human societies. Because a large fraction of insects feed on or are associated with plants, nonnative plants provide habitat and resources for invading insects, thereby facilitating their establishment. Furthermore, plant imports represent one of the main pathways for accidental nonnative insect introductions. Here, we tested the hypothesis that plant invasions precede and promote insect invasions. We found that geographical variation in current nonnative insect flows was best explained by nonnative plant flows dating back to 1900 rather than by more recent plant flows. Interestingly, nonnative plant flows were a better predictor of insect invasions than potentially confounding socioeconomic variables. Based on the observed time lag between plant and insect invasions, we estimated that the global insect invasion debt consists of 3,442 region-level introductions, representing a potential increase of 35% of insect invasions. This debt was most important in the Afrotropics, the Neotropics, and Indomalaya, where we expect a 10 to 20-fold increase in discoveries of new nonnative insect species. Overall, our results highlight the strong link between plant and insect invasions and show that limiting the spread of nonnative plants might be key to preventing future invasions of both plants and insects.

Seasonal Phenology and Climate Associated Feeding Activity of Introduced Marchalina hellenica in Southeast Australia

Invasive insects pose an increasing risk to global agriculture, environmental stability, and public health. Giant pine scale (GPS), Marchalina hellenica Gennadius (Hemiptera: Marchalinidae), is a phloem feeding scale insect endemic to the Eastern Mediterranean Basin, where it primarily feeds on Pinus halepensis and other Pinaceae. In 2014, GPS was detected in the southeast of Melbourne, Victoria, Australia, infesting the novel host Pinus radiata. An eradication program was unsuccessful, and with this insect now established within the state, containment and management efforts are underway to stop its spread; however, there remains a need to understand the insect's phenology and behaviour in Australia to better inform control efforts. We documented the annual life cycle and seasonal fluctuations in activity of GPS in Australia over a 32 month period at two contrasting field sites. Onset and duration of life stages were comparable to seasons in Mediterranean conspecifics, although the results imply the timing of GPS life stage progression is broadening or accelerating. GPS density was higher in Australia compared to Mediterranean reports, possibly due to the absence of key natural predators, such as the silver fly, Neoleucopis kartliana Tanasijtshuk (Diptera, Chamaemyiidae). Insect density and honeydew production in the Australian GPS population studied varied among locations and between generations. Although insect activity was well explained by climate, conditions recorded inside infested bark fissures often provided the weakest explanation of GPS activity. Our findings suggest that GPS activity is strongly influenced by climate, and this may in part be related to changes in host quality. An improved understanding of how our changing climate is influencing the phenology of phloem feeding insects such as GPS will help with predictions as to where these insects are likely to flourish and assist with management programs for pest species.

Use of mixed-type data clustering algorithm for characterizing temporal and spatial distribution of biosecurity border detections of terrestrial non-indigenous species

Appropriate inspection protocols and mitigation strategies are a critical component of effective biosecurity measures, enabling implementation of sound management decisions. Statistical models to analyze biosecurity surveillance data are integral to this decision-making process. Our research focuses on analyzing border interception biosecurity data collected from a Class A Nature Reserve, Barrow Island, in Western Australia and the associated covariates describing both spatial and temporal interception patterns. A clustering analysis approach was adopted using a generalization of the popular k-means algorithm appropriate for mixed-type data. The analysis approach compared the efficiency of clustering using only the numerical data, then subsequently including covariates to the clustering. Based on numerical data only, three clusters gave an acceptable fit and provided information about the underlying data characteristics. Incorporation of covariates into the model suggested four distinct clusters dominated by physical location and type of detection. Clustering increases interpretability of complex models and is useful in data mining to highlight patterns to describe underlying processes in biosecurity and other research areas. Availability of more relevant data would greatly improve the model. Based on outcomes from our research we recommend broader use of cluster models in biosecurity data, with testing of these models on more datasets to validate the model choice and identify important explanatory variables.