Public Engagement Technology for Bioacoustic Citizen Science

Inexpensive mobile devices offer new capabilities for non-specialist use in the field for the purpose of conservation. This thesis explores the potential for such devices to be used by citizen scientists interacting with bioacoustic data such as birdsong. This thesis describes design research and field evaluation, in collaboration with conservationists and educators, and technological artefacts implemented as mobile applications for interactive educational gaming and creative composition. This thesis considers, from a participant-centric collaborative design approach, conservationists' demand for interactive artefacts to motivate engagement in citizen science through gameful and playful interactions. Drawing on theories of motivation, frequently applied to the study of Human-Computer Interaction (HCI), and on approaches to designing for motivational engagement, this thesis introduces a novel pair of frameworks for the analysis of technological artefacts and for assessing participant engagement with bioacoustic citizen science from both game interaction design and citizen science project participation perspectives. This thesis reviews current theories of playful and gameful interaction developed for collaborative learning, data analysis, and ground-truth development, describes a process for design and analysis of motivational mobile games and toys, and explores the affordances of various game elements and mechanics for engaging participation in bioacoustic citizen science. This thesis proposes research into progressions for scaffolding engagement with citizen science projects where participants interact with data collection and analysis artefacts. The research process includes the development of multiple designs, analyses of which explore the efficacy of game interactions to motivate engagement through interaction progressions, given proposed analysis frameworks. This thesis presents analysed results of experiments examining the usability of, and data-quality from, several prototypes and software artefacts, in both laboratory conditions and the field. This thesis culminates with an assessment of the efficacy of proposed design analysis frameworks, an analysis of designed artefacts, and a discussion of how these designs increase intrinsic and extrinsic motivation for participant engagement and affect resultant bioacoustic citizen science data quantity and quality.Non

Spatiotemporal dynamics of songbird breeding in arctic-boreal North America

The high northern latitudes of North America are undergoing rapid climatic change with acute impacts to the ecosystems in which millions of songbirds breed each year. The goal of this dissertation is to improve understanding of how concurrent and interacting changes in environmental and land surface conditions influence annual movements and habitat selections of long distance migratory birds who must navigate the mosaic of changing North American ecosystems. Chapter 1 presents novel automated bioacoustic methods for estimating arrival dates of the songbird community to their arctic breeding grounds. Automated acoustic networks could vastly expand the spatiotemporal coverage of wildlife observations. However, the enormous datasets that autonomous recorders typically generate demand automated analyses that remain largely undeveloped. Chapter 1 demonstrates novel machine learning and signal processing techniques for estimating songbird community arrival dates near Toolik Field Station which agreed well with traditional survey estimates and were strongly related to the landscape’s snow free dates. Daily variations in vocal activity were more strongly influenced by environmental conditions prior to egg-laying dates. The success of the approaches presented in Chapter 1 indicate that variation in songbird migratory arrival can be detected autonomously. Widespread deployment of this advance could provide avian monitoring on a scale large enough to enable global-scale understanding of how climate change influences migratory timing of avian species. Chapter 2 examines potential future changes in habitat suitability for for two songbirds breeding throughout North America’s high northern latitudes – a tundra-nesting species (Lapland Longspurs (Calcarius lapponicus)) and a shrub-nesting species (White-crowned Sparrows (Zonotrichia leucophyrs)). By the late 21st century, models based on both climate and vegetation projected habitat suitability for Lapland Longspurs decreased across nearly all of the study domain (54-96%), while that for White-crowned Sparrows decreased in 69% of North America’s high northern latitudes. For both species, currently unsuitable habitats in northern Canada and Alaska are projected to provide suitable breeding habitat in the future. In contrast, models based solely on climate showed more drastic declines in habitat suitability for both species (Lapland Longspur, ~100% and White-crowned Sparrow ~80%). This discrepancy between model projections demonstrates that the future availability of suitable songbird breeding habitat for both species will be strongly dependent on how both the vegetation and climate– as opposed to climate alone - of northern ecosystems respond to ongoing climate change. Chapter 3 investigates the environmental and ecological drivers of migratory movements of songbirds breeding at high northern latitudes. For North America alone, there is overwhelming evidence of major shifts in seasonality of meteorological conditions, snow cover, and vegetation phenology. Few studies have focused on how this suite of changes impacts long distance migratory species that annually navigate throughout the spatially and temporally dynamic mosaic of ecosystems because of technological constraints in animal tracking. However, recent advances in GPS technology have generated units small enough to be placed on songbird species. In 2016-2018 a total of 55 American robins (Turdus migratorius) were tracked during their spring migration through the Canadian boreal forest en route to their breeding grounds. We found a significant trend towards earlier arrival of robins to the Canadian boreal forest over the past quarter-century, consistent with advances in spring environmental conditions. Robin stopover timing at our tagging site was delayed in response to later seasonal snowmelt, but triggered by adverse environmental conditions. Individuals breeding in regions with shorter snow-free seasons moved faster than individuals breeding in areas with longer snow-free seasons and selected locations with less favorable environmental conditions. Overall, arrival timing to breeding grounds was negatively related to snow depth and positively related to snowmelt timing. Migratory movements and timing of American robins are highly tied to seasonal environmental dynamics en route to their breeding grounds. Our findings present a unique, mechanistic understanding of how migratory birds navigate highly dynamic ecosystems. In light of rapid global change, the use of multi-disciplinary, spatially explicit approaches similar to the ones used in this dissertation will be critical for understanding how avian taxa breeding at high northern latitudes may respond to ongoing and future change. This is important for investigating both regional and global impacts because species breeding in arctic-boreal zones perform key ecosystem services around the globe

Refining manual annotation effort of acoustic data to estimate bird species richness and composition: The role of duration, intensity, and time

Manually annotating audio files for bird species richness estimation or machine learning validation is a time-intensive task. A premium is placed on the subselection of files that will maximize the efficiency of unique additional species identified, to be used for future analyses. Using acoustic data collected in 17 plots, we created 60 subsetting scenarios across three gradients: intensity (minutes in an hour), day phase (dawn, morning, or both), and duration (number of days) for manual annotation. We analyzed the effect of these variables on observed bird species richness and assemblage composition at both the local and entire study area scale. For reference, results were also compared to richness and composition estimated by the traditional point count method. Intensity, day phase, and duration all affected observed richness in decreasing respective order. These variables also significantly affected observed assemblage composition (in the same order of effect size), but only the day phase produced compositional dissimilarity that was due to phenological traits of individual bird species, rather than differences in species richness. All annotation scenarios requiring equal sampling effort to point counts yielded higher species richness than the point count method. Our results show that a great majority of species can be obtained by annotating files at high sampling intensities (every 3 or 6 min) in the morning period (post-dawn) over a duration of two days. Depending on a study's aim, different subsetting parameters will produce different assemblage compositions, potentially omitting rare or crepuscular species, species representing additional functional groups and natural history guilds, or species of higher conservation concern. We do not recommend one particular subsetting regime for all research objectives, but rather present multiple scenarios for researchers to understand how intensity, day phase, and duration interact to identify the best subsetting regime for one's particular research interests

Listening forward: approaching marine biodiversity assessments using acoustic methods

© The Author(s), 2020. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Mooney, T. A., Di Iorio, L., Lammers, M., Lin, T., Nedelec, S. L., Parsons, M., Radford, C., Urban, E., & Stanley, J. Listening forward: approaching marine biodiversity assessments using acoustic methods. Royal Society Open Science, 7(8), (2020): 201287, doi:10.1098/rsos.201287.Ecosystems and the communities they support are changing at alarmingly rapid rates. Tracking species diversity is vital to managing these stressed habitats. Yet, quantifying and monitoring biodiversity is often challenging, especially in ocean habitats. Given that many animals make sounds, these cues travel efficiently under water, and emerging technologies are increasingly cost-effective, passive acoustics (a long-standing ocean observation method) is now a potential means of quantifying and monitoring marine biodiversity. Properly applying acoustics for biodiversity assessments is vital. Our goal here is to provide a timely consideration of emerging methods using passive acoustics to measure marine biodiversity. We provide a summary of the brief history of using passive acoustics to assess marine biodiversity and community structure, a critical assessment of the challenges faced, and outline recommended practices and considerations for acoustic biodiversity measurements. We focused on temperate and tropical seas, where much of the acoustic biodiversity work has been conducted. Overall, we suggest a cautious approach to applying current acoustic indices to assess marine biodiversity. Key needs are preliminary data and sampling sufficiently to capture the patterns and variability of a habitat. Yet with new analytical tools including source separation and supervised machine learning, there is substantial promise in marine acoustic diversity assessment methods.Funding for development of this article was provided by the collaboration of the Urban Coast Institute (Monmouth University, NJ, USA), the Program for the Human Environment (The Rockefeller University, New York, USA) and the Scientific Committee on Oceanic Research. Partial support was provided to T.A.M. from the National Science Foundation grant OCE-1536782

Assessment of the effects of forest fragmentation on aerial insectivorous bats in the Amazonian rainforest

Land use change and habitat fragmentation are among the most severe threats to biodiversity, especially in the tropics. In the Amazon, the abandonment of formerly deforested areas allowed the expansion of secondary regrowth, a type of habitat where bats are known to provide important ecosystem services. Amongst them, aerial insectivorous bats have been neglected in most Neotropical studies and remain poorly studied. However, the current upsurge in acoustic technology makes them easy targets to be monitored using ultrasound detectors. The aim of this thesis was to reveal the diversity of aerial insectivorous bats and quantify the effects of forest fragmentation on this ensemble within the Biological Dynamics Forest Fragments Project, a whole ecosystem experiment in the Amazon, currently composed of a mosaic of unflooded rainforest with continuous forest, and forest fragments embedded in a matrix of secondary regrowth. As part of this thesis, the first “Field Guide to the Bats of the Amazon” was published. A custom-built classifier was developed which was able to identify a large proportion of files to sonotype level (with > 90% accuracy), leaving the rest (<25%) to be manually classified. I also tested 20 different recording schemes and provided guidelines to optimize protocols for acoustic studies. In forest fragments and their adjoining secondary forests, taxonomic, phylogenetic and functional α diversity became gradually poorer with decreasing fragment size. In terms of β diversity, bat assemblage composition in secondary forests after ~30 years of recovery was still significantly different from that in continuous forest. However, forest edges harboured highly diverse bat assemblages due to the opening of cluttered areas, and the increase of less-sensitive species. Responses towards fragmentation were species-specific and strongly related to their functional traits. The results of this thesis highlight the irreplaceable value of tropical primary forests due to the long time required to recover fragmented ecosystems.Fundação de Amparo à Pesquisa do Estado do Amazonas [FAPEAM 062.01173 / 2015] (Paulo ED Bobrowiec)Bolsa de estudos do CNPq [160049 / 2013-0] (Paulo ED Bobrowiec

Heterogeneous recognition of bioacoustic signals for human-machine interfaces

Human-machine interfaces (HMI) provide a communication pathway between man and machine. Not only do they augment existing pathways, they can substitute or even bypass these pathways where functional motor loss prevents the use of standard interfaces. This is especially important for individuals who rely on assistive technology in their everyday life. By utilising bioacoustic activity, it can lead to an assistive HMI concept which is unobtrusive, minimally disruptive and cosmetically appealing to the user. However, due to the complexity of the signals it remains relatively underexplored in the HMI field. This thesis investigates extracting and decoding volition from bioacoustic activity with the aim of generating real-time commands. The developed framework is a systemisation of various processing blocks enabling the mapping of continuous signals into M discrete classes. Class independent extraction efficiently detects and segments the continuous signals while class-specific extraction exemplifies each pattern set using a novel template creation process stable to permutations of the data set. These templates are utilised by a generalised single channel discrimination model, whereby each signal is template aligned prior to classification. The real-time decoding subsystem uses a multichannel heterogeneous ensemble architecture which fuses the output from a diverse set of these individual discrimination models. This enhances the classification performance by elevating both the sensitivity and specificity, with the increased specificity due to a natural rejection capacity based on a non-parametric majority vote. Such a strategy is useful when analysing signals which have diverse characteristics, false positives are prevalent and have strong consequences, and when there is limited training data available. The framework has been developed with generality in mind with wide applicability to a broad spectrum of biosignals. The processing system has been demonstrated on real-time decoding of tongue-movement ear pressure signals using both single and dual channel setups. This has included in-depth evaluation of these methods in both offline and online scenarios. During online evaluation, a stimulus based test methodology was devised, while representative interference was used to contaminate the decoding process in a relevant and real fashion. The results of this research provide a strong case for the utility of such techniques in real world applications of human-machine communication using impulsive bioacoustic signals and biosignals in general