Soundscape phenology: The effect of environmental and climatic factors on birds and insects in a subtropical woodland.

Climate change and biodiversity loss are significant global environmental issues. However, to understand their impacts we need to know how fauna respond to environmental and climatic variation over time. In this study, remote sensing techniques (satellite imagery and passive acoustic recorders) were used to investigate the variation in biophony over different timescales, ranging from one day to one year, in a sub-tropical woodland in eastern Australia. The prominent sources of biophony were birds at dawn and during the day, nocturnal insects at dusk and during the night, and diurnal birds and insects (mainly cicadas) over the summer period of December, January, and February. While different environmental factors were found to be key drivers of phenological response in different faunal groups, temperature, humidity and the interactions between temperature, humidity, moon illumination and vegetation greenness were most important factors overall. Using observed temperatures relative to the historical mean for each day of the year, we evaluated the impact of higher-than-average temperatures on calling activity. We found that nocturnal insects call less frequently on days when the temperature was hotter than average in winter months (June, July, and August), and birds call less frequently in hot spring days (September, October, and November) meaning these groups can be susceptible to temperature increase as consequence, for example, of climate change. This study demonstrates how animal calling behaviour is affected by different environmental variables over different temporal scales. This study also demonstrates the utility of remote sensing techniques for assessing the impacts of climate change on biodiversity. It is highly recommended that monitoring schemes and impact assessments account for phenological changes and environmental variability, as these are complex and important processes shaping animal communities.

Regulated timber harvesting does not reduce koala density in north-east forests of New South Wales.

The compatibility of forestry and koala conservation is a controversial issue. We used a BACIPS design to assess change in koala density after selective harvesting with regulations to protect environmental values. We also assessed additional sites heavily harvested 5-10 years previously, now dominated by young regeneration. We used replicate arrays of acoustic sensors and spatial count modelling of male bellowing to estimate male koala density over 3600 ha. Paired sites in nearby National Parks served as controls. Naïve occupancy was close to 100% before and after harvesting, indicating koalas were widespread across all arrays. Average density was higher than expected for forests in NSW, varying between arrays from 0.03-0.08 males ha-1. There was no significant effect of selective harvesting on density and little change evident between years. Density 5-10 years after previous heavy harvesting was equivalent to controls, with one harvested array supporting the second highest density in the study. Within arrays, density was similar between areas mapped as selectively harvested or excluded from harvest. Density was also high in young regeneration 5-10 years after heavy harvesting. We conclude that native forestry regulations provided sufficient habitat for koalas to maintain their density, both immediately after selective harvesting and 5-10 years after heavy harvesting.

Describing the sounds of nature: Using onomatopoeia to classify bird calls for citizen science.

Bird call libraries are difficult to collect yet vital for bio-acoustics studies. A potential solution is citizen science labelling of calls. However, acoustic annotation techniques are still relatively undeveloped and in parallel, citizen science initiatives struggle with maintaining participant engagement, while increasing efficiency and accuracy. This study explores the use of an under-utilised and theoretically engaging and intuitive means of sound categorisation: onomatopoeia. To learn if onomatopoeia was a reliable means of categorisation, an online experiment was conducted. Participants sourced from Amazon mTurk (N = 104) ranked how well twelve onomatopoeic words described acoustic recordings of ten native Australian bird calls. Of the ten bird calls, repeated measures ANOVA revealed that five of these had single descriptors ranked significantly higher than all others, while the remaining calls had multiple descriptors that were rated significantly higher than others. Agreement as assessed by Kendall's W shows that overall, raters agreed regarding the suitability and unsuitability of the descriptors used across all bird calls. Further analysis of the spread of responses using frequency charts confirms this and indicates that agreement on which descriptors were unsuitable was pronounced throughout, and that stronger agreement of suitable singular descriptions was matched with greater rater confidence. This demonstrates that onomatopoeia may be reliably used to classify bird calls by non-expert listeners, adding to the suite of methods used in classification of biological sounds. Interface design implications for acoustic annotation are discussed.

Passive acoustics and sound recognition provide new insights on status and resilience of an iconic endangered marsupial (koala Phascolarctos cinereus) to timber harvesting.

Retention forestry aims to mitigate impacts of native forestry on biodiversity, but data are limited on its effectiveness for threatened species. We used acoustics to investigate the resilience of a folivorous marsupial, the koala Phascolarctos cinereus, to timber harvesting where a key mitigation practice is landscape exclusion of harvesting. We deployed acoustic recorders at 171 sites to record male bellows (~14,640 hours) for use in occupancy modelling and for comparisons of bellow rate (bellows night-1). Surveys targeted modelled medium-high quality habitat, with sites stratified by time since logging and logging intensity, including old growth as a reference. After scanning recordings with software to identify koala bellows, we found a high probability of detection (~0.45 per night), but this varied with minimum temperature and recorder type. Naïve occupancy was ~ 64% across a broad range of forests, which was at least five times more than expected based on previous surveys using alternative methods. After accounting for imperfect detection, probability of occupancy was influenced by elevation (-ve), cover of important browse trees (+ve), landscape NDVI (+ve) and extent of recent wildfire (-ve, but minor effect). Elevation was the most influential variable, though the relationship was non-linear and low occupancy was most common at tableland elevations (> 1000 m). Neither occupancy nor bellow rate were influenced by timber harvesting intensity, time since harvesting or local landscape extent of harvesting or old growth. Extrapolation of occupancy across modelled habitat indicates that the hinterland forests of north-east NSW support a widespread, though likely low density koala population that is considerably larger than previously estimated. Retention forestry has a significant role to play in mitigating harvesting impacts on biodiversity, including for forest specialists, but localised studies are needed to optimise prescriptions for koalas.

Revealing the ecological content of long-duration audio-recordings of the environment through clustering and visualisation.

Audio recordings of the environment are an increasingly important technique to monitor biodiversity and ecosystem function. While the acquisition of long-duration recordings is becoming easier and cheaper, the analysis and interpretation of that audio remains a significant research area. The issue addressed in this paper is the automated reduction of environmental audio data to facilitate ecological investigations. We describe a method that first reduces environmental audio to vectors of acoustic indices, which are then clustered. This can reduce the audio data by six to eight orders of magnitude yet retain useful ecological information. We describe techniques to visualise sequences of cluster occurrence (using for example, diel plots, rose plots) that assist interpretation of environmental audio. Colour coding acoustic clusters allows months and years of audio data to be visualised in a single image. These techniques are useful in identifying and indexing the contents of long-duration audio recordings. They could also play an important role in monitoring long-term changes in species abundance brought about by habitat degradation and/or restoration.

Using soundscapes to detect variable degrees of human influence on tropical forests in Papua New Guinea.

There is global concern about tropical forest degradation, in part, because of the associated loss of biodiversity. Communities and indigenous people play a fundamental role in tropical forest management and are often efficient at preventing forest degradation. However, monitoring changes in biodiversity due to degradation, especially at a scale appropriate to local tropical forest management, is plagued by difficulties, including the need for expert training, inconsistencies across observers, and lack of baseline or reference data. We used a new biodiversity remote-sensing technology, the recording of soundscapes, to test whether the acoustic saturation of a tropical forest in Papua New Guinea decreases as land-use intensity by the communities that manage the forest increases. We sampled soundscapes continuously for 24 hours at 34 sites in different land-use zones of 3 communities. Land-use zones where forest cover was fully retained had significantly higher soundscape saturation during peak acoustic activity times (i.e., dawn and dusk chorus) compared with land-use types with fragmented forest cover. We conclude that, in Papua New Guinea, the relatively simple measure of soundscape saturation may provide a cheap, objective, reproducible, and effective tool for monitoring tropical forest deviation from an intact state, particularly if it is used to detect the presence of intact dawn and dusk choruses.

Development and field validation of a regional, management-scale habitat model: A koala Phascolarctos cinereus case study.

Species distribution models have great potential to efficiently guide management for threatened species, especially for those that are rare or cryptic. We used MaxEnt to develop a regional-scale model for the koala Phascolarctos cinereus at a resolution (250 m) that could be used to guide management. To ensure the model was fit for purpose, we placed emphasis on validating the model using independently-collected field data. We reduced substantial spatial clustering of records in coastal urban areas using a 2-km spatial filter and by modeling separately two subregions separated by the 500-m elevational contour. A bias file was prepared that accounted for variable survey effort. Frequency of wildfire, soil type, floristics and elevation had the highest relative contribution to the model, while a number of other variables made minor contributions. The model was effective in discriminating different habitat suitability classes when compared with koala records not used in modeling. We validated the MaxEnt model at 65 ground-truth sites using independent data on koala occupancy (acoustic sampling) and habitat quality (browse tree availability). Koala bellows (n = 276) were analyzed in an occupancy modeling framework, while site habitat quality was indexed based on browse trees. Field validation demonstrated a linear increase in koala occupancy with higher modeled habitat suitability at ground-truth sites. Similarly, a site habitat quality index at ground-truth sites was correlated positively with modeled habitat suitability. The MaxEnt model provided a better fit to estimated koala occupancy than the site-based habitat quality index, probably because many variables were considered simultaneously by the model rather than just browse species. The positive relationship of the model with both site occupancy and habitat quality indicates that the model is fit for application at relevant management scales. Field-validated models of similar resolution would assist in guiding management of conservation-dependent species.

Sampling environmental acoustic recordings to determine bird species richness.

Acoustic sensors can be used to estimate species richness for vocal species such as birds. They can continuously and passively record large volumes of data over extended periods. These data must subsequently be analyzed to detect the presence of vocal species. Automated analysis of acoustic data for large numbers of species is complex and can be subject to high levels of false positive and false negative results. Manual analysis by experienced surveyors can produce accurate results; however the time and effort required to process even small volumes of data can make manual analysis prohibitive. This study examined the use of sampling methods to reduce the cost of analyzing large volumes of acoustic sensor data, while retaining high levels of species detection accuracy. Utilizing five days of manually analyzed acoustic sensor data from four sites, we examined a range of sampling frequencies and methods including random, stratified, and biologically informed. We found that randomly selecting 120 one-minute samples from the three hours immediately following dawn over five days of recordings, detected the highest number of species. On average, this method detected 62% of total species from 120 one-minute samples, compared to 34% of total species detected from traditional area search methods. Our results demonstrate that targeted sampling methods can provide an effective means for analyzing large volumes of acoustic sensor data efficiently and accurately. Development of automated and semi-automated techniques is required to assist in analyzing large volumes of acoustic sensor data.