Descriptions of known vocalisations of the Night Parrot Pezoporus occidentalis

Leseberg, Nicholas P.; Murphy, Stephen; Jackett, Nigel; Greatwich, Bruce R.; Brown, Jamie; Hamilton, Neil; Joseph, Leo; Watson, James

doi:10.20938/afo36079088

Cited by 8 publications

(9 citation statements)

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“…Birds occasionally return to their roost sites and call during the night, but typically return for another brief period of calling just before dawn. Night Parrot vocalizations are now relatively well known (Leseberg et al., 2019). Given this predictable calling behaviour, acoustic monitoring has proven the most efficient technique for both monitoring the species at known locations, and detecting it at new locations.…”

Section: Methods and Resultsmentioning

confidence: 99%

“…The Night Parrot is a cryptic and extremely rare bird that formerly occurred throughout arid central Australia (Higgins, 1999), but is now known from only a handful of sites. The species is relatively sedentary, and predictably vocal (Leseberg et al, 2019;Murphy, Silcock, Murphy, Reid, & Austin, 2017). They spend the day roosting in low, dense K E Y W O R D S acoustic monitoring, bioacoustics, call recognizer, night parrot, rare species vegetation, as pairs or small groups.…”

Section: Study Species and Data Collectionmentioning

confidence: 99%

“…Night Parrot vocalizations are now relatively well known (Leseberg et al, 2019). Given this predictable calling behaviour, acoustic monitoring has proven the most efficient technique for both monitoring the species at known locations, and detecting it at new locations.…”

Section: Study Species and Data Collectionmentioning

confidence: 99%

“…r is a programming language accessible to users without specialist programming skills, and in a comparison with recognizers using machine learning methods and commercially available packages, monitor performed well (Knight et al, 2017). We used the technique outlined in Katz Although Night Parrots have a variety of different calls, we focused on the bell-like and whistle calls, as these are the calls most likely to be heard in and around roost sites (Leseberg et al, 2019).…”

Section: Call Recognizer Development and Sound File Analysismentioning

confidence: 99%

“…There is a resultant risk of model overfitting. Additionally, the repertoire of this population is well-known (Leseberg et al, 2019), and the recognizer templates featured most of the variation that occurs at the study site. It is possible this combination of factors has exaggerated the success of our model.…”

Section: Model Application For Different Species and New Sitesmentioning

confidence: 99%

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Using intrinsic and contextual information associated with automated signal detections to improve call recognizer performance: A case study using the cryptic and critically endangered Night Parrot Pezoporus occidentalis

et al. 2020

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1. Rapid expansion in the collection of large acoustic datasets to answer ecological questions has generated a parallel requirement for techniques that streamline analysis of these datasets. In many cases, automated signal recognition algorithms, often termed 'call recognizers', are the only feasible option for doing this. To date, most research has focused on what types of recognizers perform best, and how to train these recognizers to optimize performance. 2. We demonstrate that once recognizer construction is complete and the data processed, further improvements are possible using intrinsic and contextual information associated with each detection. We initially construct a call recognizer for the Night Parrot Pezoporus occidentalis using the r package monitor, and scan a test dataset. We then examine a number of intrinsic variables associated with each detection generated by the recognizer, and several contextual variables associated with the species' environment and ecology, to determine if they might help predict whether a given detection is a true positive (target signal) or false positive (nontarget signal). We test several logistic regression models incorporating different combinations of intrinsic and contextual variables, selecting the best-performing model for application. We train the model, using it to calculate the probability each detection is a true or false positive. 3. Substituting this model-derived probability for raw recognizer score improved the recognizer's performance, reducing the number of detections requiring proofing by 60% to achieve a recall of 90%, and by 76% to achieve a recall of 75%. 4. This technique is applicable to any recognizer output, regardless of the underlying algorithm. Application requires an understanding of how the recognizer algorithm determines matches, and knowledge of a species' ecology and environment. Because advanced programming skills and expertise are not required to apply this technique, it will be particularly relevant to field ecologists for whom building and operating call recognizers is an element of their research toolbox, but not necessarily a focus. | 1521 Methods in Ecology and Evoluঞon LESEBERG Et aL. How to cite this article: Leseberg NP, Venables WN, Murphy SA, Watson JEM. Using intrinsic and contextual information associated with automated signal detections to improve call recognizer performance: A case study using the cryptic and critically endangered Night Parrot Pezoporus occidentalis.

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Section: Methods and Resultsmentioning

confidence: 99%

Section: Study Species and Data Collectionmentioning

confidence: 99%

Section: Study Species and Data Collectionmentioning

confidence: 99%

Section: Call Recognizer Development and Sound File Analysismentioning

confidence: 99%

Section: Model Application For Different Species and New Sitesmentioning

confidence: 99%

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Using intrinsic and contextual information associated with automated signal detections to improve call recognizer performance: A case study using the cryptic and critically endangered Night Parrot Pezoporus occidentalis

et al. 2020

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Establishing effective conservation management strategies for a poorly known endangered species: a case study using Australia’s Night Parrot (Pezoporus occidentalis)

et al. 2023

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An evidence-based approach to the conservation management of a species requires knowledge of that species’ status, distribution, ecology, and threats. Coupled with budgets for specific conservation strategies, this knowledge allows prioritisation of funding toward activities that maximise benefit for the species. However, many threatened species are poorly known, and determining which conservation strategies will achieve this is difficult. Such cases require approaches that allow decision-making under uncertainty. Here we used structured expert elicitation to estimate the likely benefit of potential management strategies for the Critically Endangered and, until recently, poorly known Night Parrot (Pezoporus occidentalis). Experts considered cat management the single most effective management strategy for the Night Parrot. However, a combination of protecting and actively managing existing intact Night Parrot habitat through management of grazing, controlling feral cats, and managing fire specifically to maintain Night Parrot habitat was thought to result in the greatest conservation gains. The most cost-effective strategies were thought to be fire management to maintain Night Parrot habitat, and intensive cat management using control methods that exploit local knowledge of cat movements and ecology. Protecting and restoring potentially suitable, but degraded, Night Parrot habitat was considered the least effective and least cost-effective strategy. These expert judgements provide an informed starting point for land managers implementing on-ground programs targeting the Night Parrot, and those developing policy aimed at the species’ longer-term conservation. As a set of hypotheses, they should be implemented, assessed, and improved within an adaptive management framework that also considers the likely co-benefits of these strategies for other species and ecosystems. The broader methodology is applicable to conservation planning for the management and conservation of other poorly known threatened species.

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The endocast of the Night Parrot (Pezoporus occidentalis) reveals insights into its sensory ecology and the evolution of nocturnality in birds

Iwaniuk

Keirnan

Janetzki

et al. 2020

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The Night Parrot (Pezoporus occidentalis) is a rare, nocturnal parrot species that has largely escaped scientific investigation due to its behaviour and habitat preferences. Recent field studies have revealed some insights into Night Parrot behaviour, but nothing is known of its sensory abilities. Here, we used μCT scans of an intact Night Parrot specimen to determine if its visual system shares similarities with other nocturnal species. The endocast of the Night Parrot revealed relatively small optic lobes and optic foramina, especially compared with closely related grass parakeets, but no apparent differences in orbit dimensions. Our data suggests that the Night Parrot likely has lower visual acuity than most other parrots, including its congener, the Eastern Ground Parrot (P. wallicus). We propose that the visual system of the Night Parrot might represent a compromise between the need to see under low light conditions and the visual acuity required to detect predators, forage, and fly. Based on the endocast and optic foramen measurements, the Night Parrot fits into a common pattern of decreased retinal input to the optic lobes in birds that should be explored more thoroughly in extant and extinct species.

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Descriptions of known vocalisations of the Night Parrot Pezoporus occidentalis

Cited by 8 publications

References 0 publications

Using intrinsic and contextual information associated with automated signal detections to improve call recognizer performance: A case study using the cryptic and critically endangered Night Parrot Pezoporus occidentalis

Using intrinsic and contextual information associated with automated signal detections to improve call recognizer performance: A case study using the cryptic and critically endangered Night Parrot Pezoporus occidentalis

Establishing effective conservation management strategies for a poorly known endangered species: a case study using Australia’s Night Parrot (Pezoporus occidentalis)

The endocast of the Night Parrot (Pezoporus occidentalis) reveals insights into its sensory ecology and the evolution of nocturnality in birds

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