Bioacoustic monitoring reveals shifts in breeding songbird populations and singing behaviour with selective logging in tropical forests

Complex and highly saturated soundscapes in restored oak woodlands reflect avian richness and abundance

Temperate woodlands are biodiverse natural communities threatened by land use change and fire suppression. Excluding historic disturbance regimes of periodic groundfires from woodlands causes degradation, resulting from changes in the plant community and subsequent biodiversity loss. Restoration, through prescribed fire and tree thinning, can reverse biodiversity losses, however, because the diversity of woodland species spans many taxa, efficiently quantifying biodiversity can be challenging. We assessed whether soundscapes in an eastern North American woodland reflect biodiversity changes during restoration measured in a concurrent multitrophic field study. In five restored and five degraded woodland sites in Wisconsin, USA, we sampled vegetation, measured arthropod biomass, conducted bird surveys, and recorded soundscapes for five days of every 15-day period from May to August 2022. We calculated two complementary acoustic indices: Soundscape Saturation, which focuses on all acoustically active species, and Acoustic Complexity Index (ACI), which was developed to study vocalizing birds. We used generalized additive models to predict both indices based on Julian date, time of day, and level of habitat degradation. We found that restored woodlands had higher arthropod biomass, and higher richness and abundance of breeding birds. Additionally, soundscapes in restored sites had higher mean Soundscape Saturation and higher mean ACI. Restored woodland acoustic indices exhibited greater magnitudes of daily and seasonal peaks. We conclude that woodland restoration results in higher soundscape saturation and complexity, due to greater richness and abundance of vocalizing animals. This bioacoustic signature of restoration offers a promising monitoring tool for efficiently documenting differences in woodland biodiversity.

Effects of agriculture and nature reserves on avian behavior in northwestern Costa Rica

Behavioral changes are often animals' first responses to environmental change and may act as a bellwether for population viability. Nonetheless, most studies of habitat conversion focus on changes in species occurrences or abundances. We analyzed >14,000 behavioral observations across 55 bird species in communities in northwestern Costa Rica to determine how land use affects reproductive, foraging, and other passive kinds of behaviors not associated with either foraging or reproduction. Specifically, we quantified differences in behaviors between farms, privately owned forests, and protected areas and implemented a novel modeling framework to account for variation in detection among behaviors. This framework entailed estimating abundances of birds performing different behaviors while allowing detection probabilities of individuals to vary by behavior. Birds were 1.2 times more likely to exhibit reproductive behaviors in forest than in agriculture and 1.5 times more likely to exhibit reproductive behaviors in protected areas than in private forests. Species were not always most abundant in the habitats where they were most likely to exhibit foraging or reproductive behaviors. Finally, species of higher conservation concern were less abundant in agriculture than in forest. Together, our results highlight the importance of behavioral analyses for elucidating the conservation value of different land uses.

Ecology & computer audition: Applications of audio technology to monitor organisms and environment

Among the 17 Sustainable Development Goals (SDGs) proposed within the 2030 Agenda and adopted by all the United Nations member states, the 13th SDG is a call for action to combat climate change. Moreover, SDGs 14 and 15 claim the protection and conservation of life below water and life on land, respectively. In this work, we provide a literature-founded overview of application areas, in which computer audition - a powerful but in this context so far hardly considered technology, combining audio signal processing and machine intelligence - is employed to monitor our ecosystem with the potential to identify ecologically critical processes or states. We distinguish between applications related to organisms, such as species richness analysis and plant health monitoring, and applications related to the environment, such as melting ice monitoring or wildfire detection. This work positions computer audition in relation to alternative approaches by discussing methodological strengths and limitations, as well as ethical aspects. We conclude with an urgent call to action to the research community for a greater involvement of audio intelligence methodology in future ecosystem monitoring approaches.

Soundscapes and deep learning enable tracking biodiversity recovery in tropical forests

Tropical forest recovery is fundamental to addressing the intertwined climate and biodiversity loss crises. While regenerating trees sequester carbon relatively quickly, the pace of biodiversity recovery remains contentious. Here, we use bioacoustics and metabarcoding to measure forest recovery post-agriculture in a global biodiversity hotspot in Ecuador. We show that the community composition, and not species richness, of vocalizing vertebrates identified by experts reflects the restoration gradient. Two automated measures - an acoustic index model and a bird community composition derived from an independently developed Convolutional Neural Network - correlated well with restoration (adj-R² = 0.62 and 0.69, respectively). Importantly, both measures reflected composition of non-vocalizing nocturnal insects identified via metabarcoding. We show that such automated monitoring tools, based on new technologies, can effectively monitor the success of forest recovery, using robust and reproducible data.

Loss of temporal structure of tropical soundscapes with intensifying land use in Borneo

Conservation and sustainable management efforts in tropical forests often lack reliable, effective, and easily-communicated ways to measure the biodiversity status of a protected or managed landscape. The sounds that many tropical species make can be recorded by pre-programmed devices and analysed to yield measures of biodiversity. Interpreting the resulting soundscapes has developed along two paths: analysing the whole soundscape using acoustic indices, used as a proxy of biodiversity, or focusing on individual species that can be either manually or automatically recognized from the soundscape. Here we develop an intermediate approach to divide the soundscape into frequency categories belonging to broad taxonomic groups of vocalizing animals. While the method was unable to distinguish between amphibian and mammal communities, it was successful in assigning parts of the soundscape as likely produced by birds and insects. Applying the approach in Borneo revealed that, with increasing land use intensity, i) the spectral saturation of the soundscape, a proxy of species richness, loses dawn and dusk peaks, ii) bird acoustic communities lose recurrent diurnal patterns, becoming less synchronized across sites, and that iii) insect Soundscape Saturation increases at night. If soundscapes are partitioned similarly in different regions, our method could be used to bridge soundscape-level and individual-species level analyses. Regaining dawn and dusk peaks, the synchrony of bird acoustic communities, and losing nocturnal dominance of insect could be used as a set of simple indicators of tropical forest retaining high levels of biodiversity.

Introducing the Software CASE (Cluster and Analyze Sound Events) by Comparing Different Clustering Methods and Audio Transformation Techniques Using Animal Vocalizations

Simple Summary

Unsupervised clustering algorithms are widely used in ecology and conservation to classify animal vocalizations, but also offer various advantages in basic research, contributing to the understanding of acoustic communication. Nevertheless, there are still some challenges to overcome. For instance, the quality of the clustering result depends on the audio transformation technique previously used to adjust the audio data. Moreover, it is difficult to verify the reliability of the clustering result. To analyze bioacoustic data using a clustering algorithm, it is, therefore, essential to select a reasonable algorithm from the many existing algorithms and prepare the recorded vocalizations so that the resulting values characterize a vocalization as accurately as possible. Frequency-modulated vocalizations, whose frequencies change over time, pose a particular problem. In this paper, we present the software CASE, which includes various clustering methods and provides an overview of their strengths and weaknesses concerning the classification of bioacoustic data. This software uses a multidimensional feature-extraction method to achieve better clustering results, especially for frequency-modulated vocalizations.

Abstract

Unsupervised clustering algorithms are widely used in ecology and conservation to classify animal sounds, but also offer several advantages in basic bioacoustics research. Consequently, it is important to overcome the existing challenges. A common practice is extracting the acoustic features of vocalizations one-dimensionally, only extracting an average value for a given feature for the entire vocalization. With frequency-modulated vocalizations, whose acoustic features can change over time, this can lead to insufficient characterization. Whether the necessary parameters have been set correctly and the obtained clustering result reliably classifies the vocalizations subsequently often remains unclear. The presented software, CASE, is intended to overcome these challenges. Established and new unsupervised clustering methods (community detection, affinity propagation, HDBSCAN, and fuzzy clustering) are tested in combination with various classifiers (k-nearest neighbor, dynamic time-warping, and cross-correlation) using differently transformed animal vocalizations. These methods are compared with predefined clusters to determine their strengths and weaknesses. In addition, a multidimensional data transformation procedure is presented that better represents the course of multiple acoustic features. The results suggest that, especially with frequency-modulated vocalizations, clustering is more applicable with multidimensional feature extraction compared with one-dimensional feature extraction. The characterization and clustering of vocalizations in multidimensional space offer great potential for future bioacoustic studies. The software CASE includes the developed method of multidimensional feature extraction, as well as all used clustering methods. It allows quickly applying several clustering algorithms to one data set to compare their results and to verify their reliability based on their consistency. Moreover, the software CASE determines the optimal values of most of the necessary parameters automatically. To take advantage of these benefits, the software CASE is provided for free download.

Community Bioacoustics: Studying Acoustic Community Structure for Ecological and Conservation Insights

The diversity of animal acoustic signals has evolved due to multiple ecological processes, both biotic and abiotic. At the level of communities of signaling animals, these processes may lead to diverse outcomes, including partitioning of acoustic signals along multiple axes (divergent signal parameters, signaling locations, and timing). Acoustic data provides information on the organization, diversity and dynamics of an acoustic community, and thus enables study of ecological change and turnover in a non-intrusive way. In this review, we lay out how community bioacoustics (the study of acoustic community structure and dynamics), has value in ecological monitoring and conservation of diverse landscapes and taxa. First, we review the concepts of signal space, signal partitioning and their effects on the structure of acoustic communities. Next, we highlight how spatiotemporal ecological change is reflected in acoustic community structure, and the potential this presents in monitoring and conservation. As passive acoustic monitoring gains popularity worldwide, we propose that the analytical framework of community bioacoustics has promise in studying the response of entire suites of species (from insects to large whales) to rapid anthropogenic change.

A community context for aggression? Multi-species audience effects on territorial aggression in two species of Paridae

Territorial aggression in birds is widely observed and is commonly linked to sex, age, body size, physiology, seasonal cues, food resource, urbanization, and a variety of social contexts including conspecific audience effects. However, little is known about the heterospecific audience effects on territorial aggression.Here, we address an emerging idea that heterospecific audience effects may be pervasive influences in the social lives of free-living birds. We tested the hypothesis that the composition, number, and relative body size of heterospecific audiences observing an aggressive contest will influence the response probability and intensity of aggression displayed.We subjected two Paridae species, tufted titmouse (TUTI, Baeolophus bicolor) and Carolina chickadee (CACH, Poecile carolinensis), to playbacks of aggressive calls during a breeding season in north-central Florida. At widely spaced playback sites (N = 134) in woodland habitats, we characterized the makeup of heterospecific audiences, aggression type (intra vs. interspecific territoriality), local population density, and various environmental factors (tree density, wind speed, and noise level) that are likely to influence territorial aggression.We found that the presence of heterospecific audiences increased TUTI aggression levels and that both parids were more likely to respond to playback stimuli when their audiences had higher heterospecific diversity (more heterospecific individuals and species). We also found TUTI were more likely to respond when CACH were present but not vice versa.In conclusion, we found evidence that heterospecific audiences significantly influenced the metrics of territorial aggression of free-living animals and we suggest that the definition of audience effects on the behavior of free-living animals be expanded to incorporate heterospecific audiences.