Context The distribution of the threatened greater bilby (Macrotis lagotis) has significantly contracted since the introduction of feral cats and foxes. To counteract these threats, bilbies have been reintroduced to multiple feral predator exclosures and offshore islands across Australia. Aims The aims of this study were to monitor the reintroduction of bilbies to the feral predator exclosure at Currawinya National Park and assess three hypotheses: (1) captive-born founders would establish stable home ranges and utilise habitats similar to those of wild-born bilbies in the exclosure; (2) founders would maintain adequate body condition and weight, enabling the survival of >50% of founders at 12 months post-release; and (3) the population would rapidly increase in the absence of feral predators, due to the high reproductive potential of bilbies. Methods We used VHF/GPS telemetry to compare home range size and habitat use of 12 founders and 11 wild-born bilbies. Founders were monitored intensively to assess reproductive success, weight, body condition and survival. Pouch activity was monitored to examine reproductive output. Spatially explicit capture–recapture modelling was used to estimate population density/size. Key results The population rapidly increased to >450 bilbies after 3 years, and founder survivorship was high (70% at 12 months post-release). Male founder home ranges (248.46 ha ± 97.22) were comparable in size to wild-born males (216.74 ha ± 54.19), but female founder home ranges (51.23 ha ± 12.22) were significantly larger than wild-born females (20.80 ha ± 2.94) (P = 0.04). The doubling of the population between 2021 and 2022 may have resulted in the contraction of female home ranges. Reproductive output decreased significantly in 2022, indicating that reproduction may be density-dependent at high densities. There was a significant relationship between track counts and population estimates, indicating that track counts are a reliable method for estimating population size inside the exclosure. Conclusions This reintroduction has been highly successful to date, demonstrating that bilbies are an adaptable species capable of rapid population growth in the absence of feral predators. Implications Bilbies are a model species for reintroductions to feral predator exclosures due to high survival rates, reproductive output, dietary flexibility and the ability to utilise a broad range of environments.

Monitoring is necessary for the management of any threatened species if its predicament and status are to improve. Monitoring establishes baseline data for tracking trends in distribution and abundance and is a key tool for informing threatened species management. Across much of the Old World, bats in the genus Pteropus (Pteropodidae, Chiroptera) face significant threats from habitat loss, conflict with humans, and hunting. Despite conflict with humans and their threatened status, few Pteropus are being monitored. Often, this is because of difficulties associated with their high mobility, large and easily disturbed aggregations, and their use of unknown or remote habitat. Here we describe 10 years of results from the National Flying-fox Monitoring Program (NFFMP) for the grey-headed flying-fox, (Pteropus poliocephalus) in Australia. Range-wide quarterly surveys were conducted over a three-day period since November 2012 using standardized methods appropriate to conditions encountered at each roost. For our analysis of the population and its trend, we used a state-space model to account for the ecology of the grey-headed flying-fox and the errors associated with the surveying process. Despite the general perception that the species is in decline, our raw data and the modelled population trend suggest the grey-headed flying-fox population has remained stable during the NFFMP period, with the range also stable. These results indicate that the species’ extreme mobility and broad diet bestow it with a high level of resilience to various disturbance events. Long-term, range-wide studies such as this one, are crucial for understanding relatively long-lived and highly nomadic species such as the grey-headed flying-fox. The outcomes of this study highlight the need for such systematic population monitoring of all threatened Pteropus species.

Abstract International trade in horticultural produce happens under phytosanitary inspection and production protocols. Fruit inspection typically involves the sampling and inspection of either 600-pieces or 2% of packed product within a single consignment destined for export, with the purpose of certification (typically with 95% confidence) that the true infestation level within the consignment in question doesn’t exceed a pre-specified design prevalence. Sampling of multiple consignments from multiple production blocks in conjunction with pre-harvest monitoring for pests can be used to provide additional inference on the prevalence of infested fruit within an overall production system subject to similar protocols. Here we develop a hierarchical Bayesian model that combines in-field monitoring data with consignment sample inspection data to infer the prevalence of infested fruit in a production system. The results illustrate how infestation prevalence is influenced by the number of consignments inspected, the detection efficacy of consignment sampling, and in-field monitoring effort and sensitivity. Uncertainty in inspection performance, monitoring methods, and exposure of fruit to pests is accommodated using statistical priors within a Bayesian modelling framework. We demonstrate that pre-harvest surveillance with a sufficient density of traps and moderate detection sensitivity can provide 95% belief that the prevalence of infestation is below $$1 \times 10^{-6}$$ 1 × 10 - 6 . In the absence of pre-harvest monitoring, it is still possible to gain high confidence in a very low prevalence of infestation ( $$<1 \times 10^{-5}$$ < 1 × 10 - 5 ) on the basis of multiple clean samples if the inspection sensitivity during consignment sampling is high and sufficient consignments are inspected. Our work illustrates the cumulative power of in-field surveillance and consignment sampling to update estimates of infestation prevalence.

Ecosystems worldwide are increasingly being invaded by multiple species, and the rate of biological invasion is accelerating, leading to more interactions among invasive species. One such interaction that has received little attention is the phenomenon of ‘serial replacement’ or ‘over-invasion’, where an established invasive species is supplanted by a second invasive species. Understanding this interaction is important as controlling the second species could inadvertently lead to an increase in the abundance of the first species. We used a hierarchical state-space model to analyse changes in annual abundances (commercial catch-per-unit-effort) of three invasive fish species, tench (Tinca tinca), common carp (Cyprinus carpio) and redfin perch (Perca fluviatilis), in the Murray-Darling River system (MDRS), Australia between 1954–2002. Tench were present at low abundances until the mid-1970 s, before declining to the point of no commercial catch post-1989. This rapid decline coincided with a significant increase in carp abundance, suggesting that carp may have driven the tench decline through habitat modification (particularly the destruction of aquatic plants), consistent with findings from European studies that show the disappearance of tench from ponds with intensive carp farming. Redfin perch populations, were inferred to be much less impacted by the invading carp population. While carp were present in the MDRS for the duration of the study, the rapid increase in carp abundance in the early 1970 s coincided with the introduction of a specific genetic lineage—the “Boolarra strain”. Our analysis provides compelling evidence of serial replacement of long-established tench by invading common carp triggered by the introduction of a novel carp strain.

Pest insect surveillance using lures is widely used to support market access requirements for traded articles that are hosts or carriers of quarantine pests. Modeling has been used extensively to guide the design of surveillance to support pest free area claims but is less commonly applied to provide confidence in pest freedom or low pest prevalence within sites registered for trade. Site-based surveillance typically needs to detect pests that are already present in the site or that may be entering the site from surrounding areas. We assessed the ability of site-based surveillance strategies to detect pests originating from within or outside the registered site using a probabilistic trapping network simulation model with random-walk insect movement and biologically realistic parameters. For a given release size, time-dependent detection probability was primarily determined by trap density and lure attractiveness, whereas mean step size (daily dispersal) had limited effect. Results were robust to site shape and size. For pests already within the site, detection was most sensitive using regularly spaced traps. Perimeter traps performed best for detecting pests moving into the site, although the importance of trap arrangement decreased with time from release, and random trap placement performed relatively well compared to regularly spaced traps. High detection probabilities were achievable within 7 days using realistic values for lure attractiveness and trap density. These findings, together with the modeling approach, can guide the development of internationally agreed principles for designing site-based surveillance of lure-attractant pests that is calibrated against the risk of non-detection.

Context Migratory populations of bogong moths in Australia are in decline. Numbers decreased after European settlement in the 1800s, and were stable before declining again from about 1980. Numerous hypothesised drivers for the decline have been postulated, and Caughley’s declining population paradigm provides a systematic approach to diagnosing which of these are important, and hence the knowledge to guide recovery actions. Aims This paper aims to assess which of the hypothesised drivers remain as candidate hypotheses for further investigation. Methods Within the context of known bogong moth life history and the timing of observed declines, hypothesised drivers of the two decline phases were assessed with respect to their potential impact on larval recruitment and adult survival during migration and aestivation. Key results Changes in vegetation composition and availability arising from the spread of pastoralism stand out as a likely driver of the early decline, with the herbivorous moth larva facing competition with introduced livestock, feral herbivores, and increased densities of native macropods. Many of the numerous postulated drivers of the most recent decline (e.g. changes in rainfall, rising temperatures in aestivation sites, increasing fire frequency) appear to have little support to be retained. Postulated drivers that remain as working hypotheses include increasing soil temperatures, increased cropping areas, and changed cropping practices and area. The effect of some drivers, such as artificial light pollution, is unclear and may warrant further investigation. Conclusions Inference on the drivers of bogong moth population decline is wanting. Implications Designed experiments are needed.

Invasive alien species are responsible for considerable biodiversity loss and environmental damage. Timely detection of new incursions is critical in preventing novel populations establishing. Citizen reports currently account for the majority of alien species detections, arising from the massive observation effort that the physical and digital ‘eyes and ears’ of citizens provide, in combination with crowd-sourced species identification. Because the reporting of alien species sightings is generally not mandatory, there is interest in whether mining social media data via image recognition and/or natural language processing can improve on existing passive citizen surveillance in a cost-effective manner. Here, we illustrate, using examples from Australia, how citizen surveillance for most vertebrate groups appears to currently be effective using existing voluntary reporting mechanisms. Where citizen surveillance is currently ineffective, for reasons of inadequate sampling, data mining of social media feeds will be similarly affected. We argue that mining citizens’ social media data for evidence of invasive alien species needs to demonstrate not only that it will be an improvement on the business as usual case, but also that any gains achieved cannot be achieved by alternative approaches. We highlight the potential role of education in increasing the surveillance effectiveness of citizens for detecting and reporting sightings of alien species. Should data mining of social media platforms be pursued, we note that the scale of the task in terms of the potential number of exotic vertebrate species to be classified is very large. The expected number of false positive classifications would present a considerable workload to process, possibly undermining the efficiency rationale for the use of data mining. Hence, prioritisation is needed, and we illustrate how the number of species to be classified can be reduced considerably. If we are to deploy data mining and analysis of social media data to help with detecting introductions of invasive alien species, we need to conduct it in a manner where it adds value and is trusted.

Predicting novel ranges of non-native species is a critical component to understanding the biosecurity threat posed by pests and diseases on economic, environmental and social assets. Species distribution models (SDMs) are often employed to predict the potential ranges of exotic pests and diseases in novel environments and geographic space. To date, researchers have focused on model complexity, data available for model fitting, the size of the geographic area to be considered and how the choice of model impacts results. These investigations are coupled with considerable examination of how model evaluation methods and test scores are influenced by these choices. An area that remains under-discussed is how to account for uncertainty in predictor selection while also selecting variables that increase a model’s ability to predict to novel environments (model transferability). Here we propose a novel method to finesse this problem by using multiple simple (bivariate) models to search for the candidate sets of predictor variables that are likely to produce transferable models. Once identified, each set is then used to construct 2-dimensional niche envelopes of pest presence/absence. This process ultimately results in a number of possible models that can be used to predict pest potential distributions, however, rather than relying on a single model, we ensemble these models in an attempt to account for predictor uncertainty. We apply this method to both virtual species and real species data, and find that it generally performs well against conventional approaches for statistically fitting numerous variables in a single model. While our methods only consider simple ecological relationships of species to environmental predictors, they allow for increased model transferability because they reduce the likelihood of over-fitting and collinearity issues. Simple models are also likely to be more conservative (over-predict potential distributions) relative to complex models containing many covariates – making them more appropriate for risk-averse applications such as biosecurity. The approach we have explored transforms a model selection problem, for which there is no true correct answer amongst the typically distal covariates on offer, to one of model uncertainty. We argue that increased model transferability at the expense of model interpretation is perhaps more important for effective rapid predictions and management of non-native species and biological invasions.

Citizen observations of the natural world are increasing in detail, growing in volume and increasingly being shared on web-based platforms for the purpose of sharing information and/or the crowd-sourcing of species identification. From a biosecurity perspective, such citizen data streams are important as they are responsible for the majority of post-border reports and most detections of exotic pest species of concern. The sharing of sightings amongst what are effectively communities of practice is a key driver of having the sighting of an exotic pest species recognized and reported. Whilst it is clear that the eyes, ears, cameras, and microphones of citizens are a major component of biosecurity surveillance, it is unclear what level of surveillance this provides in the prospective sense. As an example, what confidence does citizen science provide about “proof of absence” for exotic pests of concern? The taxonomy of surveillance used within the field of biosecurity would classify such citizen activities as contributing to “general surveillance,” for which non-detections are typically not recorded and methods of quantitative analysis are still under development. We argue that while not recorded, there is considerable information about citizens activities that routinely underpins peoples mental inference about the level of surveillance provided by citizen activities. Furthermore, we show that it is possible to make such inference from general surveillance transparent by describing and characterizing the activities that potentially generate sightings in a way that is amenable to quantitative analysis. In the context of evaluating surveillance provided by citizens for incursions of exotic vertebrates, we provide examples of citizen observations providing early warning and hence preventing the establishment of species from a range of animal groups. Historically, analysis of the power of general surveillance has been restricted to being conceptual, based on qualitative arguments. We provide this, but also provide a quantitative model framework and provide examples of how different forms of general surveillance data may be analyzed, particularly in supporting inference of eradication/extinction.

Abstract Context Wild house mice cause substantial economic damage to grain crops in Australia, particularly during mouse plagues. Populations were monitored to detect changes in abundance, with data from surveys used in models to forecast likely mouse outbreaks. However, it is not always feasible to use live-trapping (the ‘gold standard’) for assessing mouse abundance at a large number of monitoring sites spread across south-eastern Australia. A range of alternative methods was tried to assist the grains industry with strategic decisions to reduce crop damage. Aims The aim of this work was to determine which survey methods could provide useful and effective indexes of mouse abundance across a large area. Methods Monitoring of mouse populations was conducted at representative grain farms by using (1) live-trapping at long-term ‘benchmark’ sites (n = 2), and (2) mouse chew cards and active burrow counts at ‘rapid-assessment’ sites (n = 44 farms across 5 regions). Monitoring was conducted for 22 monitoring sessions over 7.5 years through low, medium and high mouse abundance conditions. Key results Live-trapping provided the most useful, but most resource-intensive, information. There were strong relationships between the index of mouse abundance from live-trapping with mouse chew cards and active burrow counts at a local (explaining 63% and 71% of variation respectively) and regional (explaining 71% and 81% of variation respectively) scales. The same quantitative relationship held between the mouse chew cards and trapping regardless of season and year. However, the relationship between active burrow counts and trapping was best in winter and autumn seasons. There was a strong relationship between mouse abundance from live-trapping and active burrows across 1 ha grids (R2 = 0.88). We determined there were 1.3 ± 0.2 (mean ± s.e.) mice per active burrow. Conclusions Live-trapping supplemented with data from chew cards and active burrows remains sufficient to monitor a wide range of sites to show regional trends. Implications It is likely that live-trapping will need to be used for the foreseeable future to provide useful parameters such as breeding condition and population abundance that are required for the forecast models. Supplementary monitoring at rapid-assessment sites (using chew cards in all seasons and active burrow counts particularly in autumn and winter), that can be collected easily without the need for animal handling, will provide additional indications of region-specific changes in mouse abundance and activity.

Monitoring waterbird populations in Australia is challenging for reasons of counting logistics, and because population aggregation and dispersion can shift rapidly in response to large spatio-temporal variations in resource availability. The East Australian Waterbird survey has conducted annual, aerial, systematic counts of waterbirds over eastern Australia for almost 40 years. It was designed to monitor waterbird populations using design-based inference though for many species this form of inference appears inadequate in the face of these challenges. Here we develop a state-space model-based Bayesian approach that, in addition to explicitly incorporating process noise and observation uncertainty, uses random effects and rainfall-derived covariates to model the year-to-year variation in the proportion of the total (super) population that is present on surveyed wetlands, and available to be counted. We use this model-based approach to estimate the superpopulation size of 45 waterbird species annually, and model the rate of population increase as a function of antecedent rainfall. The results confirm the strong positive effect of antecedent rainfall on population growth rates for nearly all species, and illustrate that species respond to rainfall differently in terms of habitat use, which influences whether they are present on surveyed wetlands. For many species, the year-to-year variation in the estimated proportion of the population on surveyed wetlands is very high. The results have implications for making inferences on population trends from these data, with the ability to model the year-to-year sampling variation a key requirement before the rate of population increase can be estimated with any precision. This study illustrates how to progress this approach, and infers that under average rainfall conditions, the general trend is for estimated superpopulation rates of increase to be negative, though for only a few species is this occurring with strong belief.

Understanding the complexities of pasture responses (the overall seasonal gains or losses in herbage mass) under different environmental conditions is critical to the effective management of total grazing pressure, whether to achieve agricultural, cultural or biodiversity conservation outcomes. Whilst large-scale management programmes for kangaroos (Macropus spp. and Osphranter spp.) occur across much of south-eastern Australia, there is limited understanding of how such programmes influence the overall pasture response across different environmental contexts in the temperate environment. This study investigates the effects of potential grass productivity (measured as the growth of pasture protected from large herbivore grazing), initial herbage mass (measured as the attached, above-ground component of grass tussocks), kangaroo density (measured at the site scale) and season on the overall pasture response in plots dominated by six common grass types from south-eastern Australia. Using generalised additive mixed modelling, we demonstrate potential grass productivity (related to but not synonymous with grass palatability) to be the major predictor variable for pasture responses across all six grass types. Kangaroo density, either directly or via an interaction with initial herbage mass, was related to overall pasture responses for most grasses in spring and remained an important variable in favoured areas dominated by preferred Kangaroo Grass (Themeda triandra) and Redleg Grass (Bothriochloa macra) throughout the autumn survey period. Plots dominated by grazing-tolerant species, including wallaby grasses (Rytidosperma spp.) and Phalaris (Phalaris aquatica; an introduced pasture grass), showed marginally positive pasture responses under higher kangaroo densities, whilst plots with Wild Oats (Avena fatua; an introduced annual grass) and less preferred native spear grasses (Austrostipa spp.) showed no significant effect of kangaroo density on pasture response. Results support a context-specific mix of 'bottom-up' (resource-driven) and 'top-down' (consumer-driven) processes in temperate grassy ecosystems, highlighting the importance of considering landscape productivity, existing herbage mass and grass species composition when informing kangaroo management decisions.

Populations of macropods are higher than estimated pre-European densities in many parts of Australia. To achieve appropriate densities of macropods in the Australian Capital Territory's nature reserves, multi-tenure kangaroo management units are used to tailor management of kangaroos and total grazing pressure to achieve conservation objectives. An adaptive management framework is recommended that monitors the state of the ground-layer vegetation and alters the cull accordingly. This case study may provide insights for kangaroo management in other temperate areas of Australia.

Data streams arising from citizen reporting activities continue to grow, yet the information content within these streams remains unclear, and methods for addressing the inherent reporting biases little developed. Here, we quantify the major influence of physical insect features (colour, size, morphology, pattern) on the propensity of citizens to upload photographic sightings to online portals, and hence to contribute to biosecurity surveillance. After correcting for species availability, we show that physical features and pestiness are major predictors of reporting probability. The more distinctive the visual features, the higher the reporting probabilities—potentially providing useful surveillance should the species be an unwanted exotic. Conversely, the reporting probability for many small, nondescript high priority pest species is unlikely to be sufficient to contribute meaningfully to biosecurity surveillance, unless they are causing major harm. The lack of citizen reporting of recent incursions of small, nondescript exotic pests supports the model. By examining the types of insects of concern, industries or environmental managers can assess to what extent they can rely on citizen reporting for their surveillance needs. The citrus industry, for example, probably cannot rely on passive unstructured citizen data streams for surveillance of the Asian citrus psyllid (Diaphorina citri). In contrast, the forestry industry may consider that citizen detection and reporting of species of the large and colourful insects such as pine sawyers (Monochamus spp.) may be sufficient for their needs. Incorporating citizen surveillance into the general surveillance framework is an area for further research.

The Bogong moth Agrotis infusa is well known for its remarkable long‐distance migration – a return journey from the plains of southeast Australia to the Australian Alps – as well as for its cultural significance for Indigenous Australians. Each spring, as many as four billion moths are estimated to arrive in the Australian Alps to aestivate in cool mountain caves and in boulder fields, bringing with them a massive annual influx of energy and nutrients critical for the health of the alpine ecosystem. However, a massive decline in moths present at their aestivation sites has occurred over the past 3 years, with only a few individuals present where hundreds of thousands could earlier be found. In order to understand the possible sources of decline, we analysed historical records of Bogong moth numbers at aestivation sites in the Australian Alps, including observations on Mt. Gingera (NSW) in the early 1950s, observations from 1980 onwards in the Snowy Mountains (NSW) and an almost‐unbroken series of observations each summer over the past 53 years in three caves at different elevations on Mt. Buffalo (Victoria). This analysis shows that moth numbers were probably steady from 1951 until about 1980, fluctuated and slowly fell from then until 2016 and dramatically crashed in 2017. In the Murray–Darling Basin, the main winter breeding ground of Bogong moths, changes in farming practices, such as increasing land clearing for crops (which has removed around a quarter of a billion moths annually from the mountains compared to pre‐European levels), has probably driven some of the decline in Bogong moth numbers observed from 1980 to 2016. The impact of insecticide remains unclear and is in urgent need of further study. Even though we found little evidence that increasing global temperatures per se are responsible for the Bogong moth decline, the Australian climate has nonetheless become drier and warmer over past decades, possibly hampering the survival of immature stages in the breeding areas and confining adult aestivation to gradually higher elevations. The crash in moth numbers from 2017 is most likely due to the recent severe drought in the moth's breeding grounds.

Decisions regarding invasive risk of exotic species are often based on species distribution models projected onto the recipient region of interest. Such projections are essentially a measure of prior belief in the ability of an organism to invade. Whilst many decisions are made on the basis of such projections, it is less clear how such prior belief may be empirically modified on the basis of data, in particular introduction events that haven't led to establishment. Here, using the Asian green mussel (Perna viridis) as an example, we illustrate how information on failed introduction attempts may be used to continually update our beliefs in the ability of an organism to invade per introduction, and the underlying habitat suitability for establishment. Our results show that the establishment probability of P. viridis per fouled ship visit in the supposedly favourable northern Australian waters are much lower than initially though, and are continuing to decline. A Bayesian interpretation of our results notes the dramatic reduction in our belief of the ability of P. viridis to invade in the light of what we estimate to be 100's of fouled vessels per year visiting ports without any persistent populations establishing. Under a hypothetico-deductive approach we would reject the null (prior) species distribution model as being useful, and seek to find a better one that can withstand the challenge of data.

The dingo (Canis dingo or C. familiaris, including hybrids with feral dogs) is the apex carnivore on mainland Australia. Fifteen non-native ungulate species have established wild populations in Australia. Dingoes are managed to reduce impacts on domestic ungulates, and introduced wild ungulates are managed to reduce impacts on natural ecosystems and to minimise competition with domestic ungulates. There is speculation about the extent to which (1) dingoes limit the abundances of introduced wild ungulates, and (2) introduced wild ungulates sustain dingo populations. We reviewed the literature to identify potential ecological interactions between dingoes and introduced wild ungulates, and to synthesise evidence for interactions between dingoes and each ungulate species (including the percentage frequency occurrence (%FO) of ungulates in dingo diets). Eleven of the 15 ungulate species were recorded in the diet of dingoes, with the highest %FO occurrences reported for feral goats (73%) and cattle (60%). Two studies concluded that dingoes reduced ungulate abundances (feral goat (Capra hircus) and feral donkey (Equus asinus)), and two studies concluded that dingoes did not regulate feral pig (Sus scrofa) abundances. A fifth study concluded that dingoes exhibited a Type III functional response to increasing sambar deer (Cervus unicolor) abundances. A sixth study concluded that dingoes made relatively little use of hunter-shot sambar deer carcasses. We propose that interactions between dingoes and introduced wild ungulates depend on the sex–age classes vulnerable to dingo predation, dingo pack sizes, the availability of escape terrain for ungulates and the availability of alternative foods for dingoes. The interplay between environmental conditions and the population growth rate of ungulates, and hence their ability to sustain losses from predation, could also be important. We predict that dingoes will have most impact on the abundance of smaller ungulate species and neonates.

The dingo (Canis dingo or C. familiaris, including hybrids with feral dogs) is the apex carnivore on mainland Australia. Fifteen non-native ungulate species have established wild populations in Australia. Dingoes are managed to reduce impacts on domestic ungulates, and introduced wild ungulates are managed to reduce impacts on natural ecosystems and to minimise competition with domestic ungulates. There is speculation about the extent to which (1) dingoes limit the abundances of introduced wild ungulates, and (2) introduced wild ungulates sustain dingo populations. We reviewed the literature to identify potential ecological interactions between dingoes and introduced wild ungulates, and to synthesise evidence for interactions between dingoes and each ungulate species (including the percentage frequency occurrence (%FO) of ungulates in dingo diets). Eleven of the 15 ungulate species were recorded in the diet of dingoes, with the highest %FO occurrences reported for feral goats (73%) and cattle (60%). Two studies concluded that dingoes reduced ungulate abundances (feral goat (Capra hircus) and feral donkey (Equus asinus)), and two studies concluded that dingoes did not regulate feral pig (Sus scrofa) abundances. A fifth study concluded that dingoes exhibited a Type III functional response to increasing sambar deer (Cervus unicolor) abundances. A sixth study concluded that dingoes made relatively little use of hunter-shot sambar deer carcasses. We propose that interactions between dingoes and introduced wild ungulates depend on the sex-age classes vulnerable to dingo predation, dingo pack sizes, the availability of escape terrain for ungulates and the availability of alternative foods for dingoes. The interplay between environmental conditions and the population growth rate of ungulates, and hence their ability to sustain losses from predation, could also be important. We predict that dingoes will have most impact on the abundance of smaller ungulate species and neonates.

We document predation of aestivating bogong moths (Agrotis infusa) by wild pigs (Sus scrofa) at a location in the Australian Alps. This is the first known record of pigs preying on bogong moths. Wild pigs are recent colonisers of the region, though already the population appears seasonally habituated to foraging on aestivating moths. This is indicative of adaptation of a feral animal undertaking dietary resource switching within what is now a modified ecosystem and food web. The significance of this predation on moth abundance is unclear. Long-term monitoring to compare numbers of moths with historical surveys undertaken before the colonisation by wild pigs will require that they are excluded from aestivation sites. Our surveys in 2014–15 observed bogong moths to arrive about one month earlier compared with a similar survey in 1951–52, though to also depart earlier.