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Landscape-scale monitoring is used to track changes in the status of fauna populations, including identifying when and where change is occurring over large areas. Yet few programs at this scale exist despite calls for long-term monitoring, especially after the 'black summer' fires of 2019/20. Landscape monitoring often sits in the 'too hard and too expensive basket'. To encourage land managers to maintain existing programs or establish new ones, it is important to demonstrate approaches that can cost-effectively monitor fauna and assess the level of investment required to adequately assess trends. We used passive acoustic and ultrasonic monitoring with artificial intelligence to semi-automate the detection of vocalisations from Koalas, Yellow-bellied Gliders, Powerful Owls and Sooty Owls and echolocation calls from two threatened bat species (Eastern Falsistrelle and Little Bent-wing Bat) as part of a pilot study for forest monitoring at a landscape-scale. Analyses that accounted for imperfect detection were used to: (1) generate detection probability and initial occupancy estimates for selected priority fauna species, and (2) undertake power analyses to inform sampling effort, and duration required to detect a commonly applied trend (30% decline over 10 years). Cost-effectiveness of sampling with remote sensors and traditional methods was also examined. Several thousand detections of priority species were recorded, with the number of detections varying by species and season. This translated to differences in detection probability and occupancy for each species. Detection probability was sensitive to the sampling intensity (number of surveys/sensors) deployed at a given site and this varied between seasons, with >95% probability of detection achieved for most species when multiple subplots were sampled for a 2-week period. Power analyses revealed trade-offs between sampling effort (number of sites) and duration (number of visits) required to detect a trend. Only a modest investment was needed to monitor widespread species that are moderately detectable using remote sensors with artificial intelligence and this investment was 2-11 times lower than monitoring using traditional methods for the priority species examined. For very rare species that are not widespread, localised monitoring and/or targeted research may be more suitable. Nevertheless, landscape-scale monitoring for many forest fauna is achievable using cost-effective remote sampling, artificial intelligence and robust analytics that account for imperfect detection. Now, more than ever, we urge support for and implementation of landscape monitoring for biodiversity. [ABSTRACT FROM AUTHOR]

Quantifying the cost‐effectiveness of alternative sampling methods is crucial for efficient biodiversity monitoring and detection of population trends. In this study, we compared the cost‐effectiveness of three novel sampling methods for detecting changes in koala (Phascolarctos cinereus) occupancy: thermal drones, passive acoustic recorders and camera trapping. Specifically, we fitted single‐season occupancy‐detection models to data recorded from 46 sites in eight bioregions of New South Wales, Australia, between 2018 and 2022. We explored the effect of weather variables on daily detection probability for each method and, using these estimates, calculated the statistical power to detect 30%, 50% and 80% declines in koala occupancy. We calculated power for different combinations of sites (1–200) and repeat surveys (2–40) and developed a cost model that found the cheapest survey design that achieved 80% power to detect change. On average, detectability of koalas was highest with one 24‐h period of acoustic surveys (0.32, 95% CI's: 0.26, 0.39) compared to a 25‐ha flight of drone surveys (0.28, 95% 0.15, 0.48) or a 24‐h period of camera trapping consisting of six cameras (0.019, 95% CI's: 0.014, 0.025). We found a negative quadratic relationship between detection probability and air temperature for all three methods. Our power and cost analysis suggested that 148 sites surveyed with acoustic recorders deployed for 14 days would be the cheapest method to sufficiently detect a 30% decline in occupancy with 80% power. We recommend passive acoustic recorders as the most efficient sampling method for monitoring koala occupancy compared to cameras or drones. Further comparative studies are needed to compare the relative effectiveness of these methods and others when the monitoring objective is to detect change in koala abundance over time. [ABSTRACT FROM AUTHOR]

Roost selection and diet are fundamentally important to bats and can vary geographically and with habitat. The greater broad-nosed bat (Scoteanax rueppellii) is infrequently captured and poorly known, meaning appropriate conservation actions are difficult to determine. To assess variation across different habitats, we collected faecal samples for dietary analysis and radio-tracked individuals to identify roost trees at four different sites across New South Wales, Australia. Analysis of droppings verified beetles as the main prey in each study area except one dominated by mangroves, and confirmed for the first time carnivory in wild-caught individuals from the presence of hair from other bat species in its droppings. Very large, hollow trees were used as maternity roosts, being typically larger than neighbouring trees. Roosting habitat varied from wet sclerophyll forest in gullies to old-growth mangroves, and tree species used as roosts also varied. Colony size at maternity roosts was often 50–100 bats and fidelity to the maternity roost varied, with some being switched almost daily and others occupied for at least several days. One maternity roost was re-used 2 years later. Both the importance of beetles in the diet and roosts located in more productive landscapes suggest coastal plains and foothills may represent key habitat. Understanding a species' ecology across different geographic regions provides a sound basis for improving its conservation. Greater broad-nosed bats were captured and radio-tracked in different regions to describe roosts used and diet. Beetles were the main prey in each study area except one dominated by mangroves, and for the first time carnivory in wild-caught individuals was documented. Very large, hollow trees were used as maternity roosts, but vegetation associations and tree species varied. [ABSTRACT FROM AUTHOR]

As a worldwide taxon inhabiting a diverse range of habitats and environmental conditions, bats also demonstrate some of the greatest variation in reproductive strategies of any mammalian order. Whilst monoestry is the predominant mating pattern of bats within the temperate zone, polyoestry and variants of this mode are more prevalent at tropical latitudes. As a tropical species occurring in a temperate climate in the southern extent of its range, the reproductive phenology of the golden-tipped bat (Phoniscus papuensis) is poorly understood. Here we present the first evidence of polyoestry in this species, an uncommon reproductive trait in Australian bats. The influence of weather and increase in prey density (orb-weaving spiders) are suggested as potential drivers for what appears to be a positive facultative breeding response to a pulse of resources. This observation demonstrates that there is still much to learn about the basic natural history and reproductive strategies of Australian bats. The reproductive traits in many Australian species of bat remain poorly known. We present the first evidence for multiple litters (polyoestry) in the golden-tipped bat. We discuss the tropical origins of golden-tipped bats and conditions which may have facilitated multiple births in the first breeding season following the 2019/2020 Black Summer fires. [ABSTRACT FROM AUTHOR]

Technologies for remotely observing animal movements have advanced rapidly in the past decade. In recent years, Australia has invested in an Integrated Marine Ocean Tracking (IMOS) system, a land ecosystem observatory (TERN), and an Australian Acoustic Observatory (A2O), but has not established movement tracking systems for individual terrestrial animals across land and along coastlines. Here, we make the case that the Motus Wildlife Tracking System, an open-source, rapidly expanding cooperative automated radio-tracking global network (Motus, https://motus.org) provides an unprecedented opportunity to build an affordable and proven infrastructure that will boost wildlife biology research and connect Australian researchers domestically and with international wildlife research. We briefly describe the system conceptually and technologically, then present the unique strengths of Motus, how Motus can complement and expand existing and emerging animal tracking systems, and how the Motus framework provides a much-needed central repository and impetus for archiving and sharing animal telemetry data. We propose ways to overcome the unique challenges posed by Australia's ecological attributes and the size of its scientific community. Open source, inherently cooperative and flexible, Motus provides a unique opportunity to leverage individual research effort into a larger collaborative achievement, thereby expanding the scale and scope of individual projects, while maximising the outcomes of scant research and conservation funding. [ABSTRACT FROM AUTHOR]

Three-dimensional structure of vegetation plays a key role in animal ecology and the arrival of LiDAR technologies has given ecologists the ability to understand species-habitat relationships in increasing detail. However, few studies have investigated the trait-environment relationships that underpin diverse animal relationships with vegetation structure. We used terrestrial laser scanning (TLS) and acoustic bat surveys to investigate relationships between forest structure and bat communities across a vegetation structural gradient at community, species and trait levels. We developed 20 measures of site scale vegetation structure and also quantified landscape scale vegetation cover and water availability. We predicted that overall bat activity would increase in open and decrease in cluttered vegetation, but this would vary with species, underpinned by ecomorphological traits. Overall bat activity was negatively associated with stem density, with total activity halving (from 380 to 190 calls night − 1 ) as stem densities increased from 60 to 1350 stems ha − 1 , while foraging activity declined from 8 to < 1 feeding buzzes night − 1 over the same range. Bat activity varied among species and structures and foraging strategy explained more of this variability than call, body size or wing traits. As predicted, above-canopy and edge-space foraging bats were negatively associated with local-scale clutter, while closed-space species were positively associated with cluttered stands. Stem density was the strongest predictor of bat-environment relationships, although there was evidence for differences in bat habitat use across different structural elements. Our study is the first to link detailed LiDAR-derived 3D forest structural metrics to multiple animal traits. [ABSTRACT FROM AUTHOR]