Detecting and Tracking Communal Bird Roosts in Weather Radar Data

The US weather radar archive holds detailed information about biological phenomena in the atmosphere over the last 20 years. Communally roosting birds congregate in large numbers at nighttime roosting locations, and their morning exodus from the roost is often visible as a distinctive pattern in radar images. This paper describes a machine learning system to detect and track roost signatures in weather radar data. A significant challenge is that labels were collected opportunistically from previous research studies and there are systematic differences in labeling style. We contribute a latent variable model and EM algorithm to learn a detection model together with models of labeling styles for individual annotators. By properly accounting for these variations we learn a significantly more accurate detector. The resulting system detects previously unknown roosting locations and provides comprehensive spatio-temporal data about roosts across the US. This data will provide biologists important information about the poorly understood phenomena of broad-scale habitat use and movements of communally roosting birds during the non-breeding season.Comment: 9 pages, 6 figures, AAAI 2020 (AI for Social Impact Track

Linking Animals Aloft with the Terrestrial Landscape

Despite using the aerosphere for many facets of their life, most flying animals (i.e., birds, bats, some insects) are still bound to terrestrial habitats for resting, feeding, and reproduction. Comprehensive broad-scale observations by weather surveillance radars of animals as they leave terrestrial habitats for migration or feeding flights can be used to map their terrestrial distributions either as point locations (e.g., communal roosts) or as continuous surface layers (e.g., animal densities in habitats across a landscape). We discuss some of the technical challenges to reducing measurement biases related to how radars sample the aerosphere and the flight behavior of animals. We highlight a recently developed methodological approach that precisely and quantitatively links the horizontal spatial structure of birds aloft to their terrestrial distributions and provides novel insights into avian ecology and conservation across broad landscapes. Specifically, we present case studies that (1) elucidate how migrating birds contend with crossing ecological barriers and extreme weather events, (2) identify important stopover areas and habitat use patterns of birds along their migration routes, and (3) assess waterfowl response to wetland habitat management and restoration. These studies aid our understanding of how anthropogenic modification of the terrestrial landscape (e.g., urbanization, habitat management), natural geographic features, and weather (e.g., hurricanes) can affect the terrestrial distributions of flying animals

Linking Animals Aloft with the Terrestrial Landscape

Despite using the aerosphere for many facets of their life, most flying animals (i.e., birds, bats, some insects) are still bound to terrestrial habitats for resting, feeding, and reproduction. Comprehensive broad-scale observations by weather surveillance radars of animals as they leave terrestrial habitats for migration or feeding flights can be used to map their terrestrial distributions either as point locations (e.g., communal roosts) or as continuous surface layers (e.g., animal densities in habitats across a landscape). We discuss some of the technical challenges to reducing measurement biases related to how radars sample the aerosphere and the flight behavior of animals. We highlight a recently developed methodological approach that precisely and quantitatively links the horizontal spatial structure of birds aloft to their terrestrial distributions and provides novel insights into avian ecology and conservation across broad landscapes. Specifically, we present case studies that (1) elucidate how migrating birds contend with crossing ecological barriers and extreme weather events, (2) identify important stopover areas and habitat use patterns of birds along their migration routes, and (3) assess waterfowl response to wetland habitat management and restoration. These studies aid our understanding of how anthropogenic modification of the terrestrial landscape (e.g., urbanization, habitat management), natural geographic features, and weather (e.g., hurricanes) can affect the terrestrial distributions of flying animals

Learning to See with Minimal Human Supervision

Deep learning has significantly advanced computer vision in the past decade, paving the way for practical applications such as facial recognition and autonomous driving. However, current techniques depend heavily on human supervision, limiting their broader deployment. This dissertation tackles this problem by introducing algorithms and theories to minimize human supervision in three key areas: data, annotations, and neural network architectures, in the context of various visual understanding tasks such as object detection, image restoration, and 3D generation. First, we present self-supervised learning algorithms to handle in-the-wild images and videos that traditionally require time-consuming manual curation and labeling. We demonstrate that when a deep network is trained to be invariant to geometric and photometric transformations, representations from its intermediate layers are highly predictive of object semantic parts such as eyes and noses. This insight offers a simple unsupervised learning framework that significantly improves the efficiency and accuracy of few-shot landmark prediction and matching. We then present a technique for learning single-view 3D object pose estimation models by utilizing in-the-wild videos where objects turn (e.g., cars in roundabouts). This technique achieves competitive performance with respect to existing state-of-the-art without requiring any manual labels during training. We also contribute an Accidental Turntables Dataset, containing a challenging set of 41,212 images of cars in cluttered backgrounds, motion blur, and illumination changes that serve as a benchmark for 3D pose estimation. Second, we address variations in labeling styles across different annotators, which leads to a type of noisy label referred to as heterogeneous label. This variability in human annotation can cause subpar performance during both the training and testing phases. To mitigate this, we have developed a framework that models the labeling styles of individual annotators, reducing the impact of human annotation variations and enhancing the performance of standard object detection models. We have also applied this framework to analyze ecological data, which are often collected opportunistically across different case studies without consistent annotation guidelines. Through this application, we have obtained several insightful observations into large-scale bird migration behaviors and their relationship to climate change. Our next study explores the challenges of designing neural networks, an area that lacks a comprehensive theoretical understanding. By linking deep neural networks with Gaussian processes, we propose a novel Bayesian interpretation of the deep image prior, which parameterizes a natural image as the output of a convolutional network with random parameters and random input. This approach offers valuable insights to optimize the design of neural networks for various image restoration tasks. Lastly, we introduce several machine-learning techniques to reconstruct and edit 3D shapes from 2D images with minimal human effort. We first present a generic multi-modal generative model that bridges 2D images and 3D shapes via a shared latent space, and demonstrate its applications on versatile 3D shape generation and manipulation tasks. Additionally, we develop a framework for joint estimation of 3D neural scene representation and camera poses. This approach outperforms prior works and allows us to operate in the general SE(3) camera pose setting, unlike the baselines. The results also indicate this method can be complementary to classical structure-from-motion (SfM) pipelines as it compares favorably to SfM on low-texture and low-resolution images

Vulture flight behavior driven by uplift availability at local and continental scales

Understanding how animals move in response to their environment is a fundamental question in ecology. Soaring species, which rely on environmentally generated uplift to forage and migrate, should be especially sensitive to changing weather and climatic conditions. Changes in uplift distribution or strength can have energetic implications and restrict movement capacity for soaring species. Poor weather conditions can shorten foraging time or slow migration progress. To increase mobility, birds can switch to flapping or soar using another uplift type. Use of uplift, however, is associated with certain flight altitudes and movement speeds. Switching uplift types will affect a bird\u27s ecological interactions and how it moves through its environment. Understanding how species flight behavior is affected by variable conditions, therefore, informs how species movements change under varied environmental conditions.;Numerous studies have evaluated avian behavioral and movement responses to environmental variation. The greatest focus of these studies has been of migration movements. Yet, it is also important to study such responses during non-migratory periods; movements during the breeding and non-breeding seasons affect an individual\u27s foraging behavior and inter-specific interactions.;To better understand how soaring species behaved under variable conditions, I observed flight behavior at local- and continental-scales. I first evaluated variation in flight behavior of black (Coragyps atratus) and turkey (Cathartes aura) vultures in response to variation in environmental conditions during the breeding season. I then evaluated the relationship between flight behavior and uplift availability at a continental-scale during the breeding and non-breeding seasons.;At the local-scale, I found uplift type use influenced flight behavior and species selected uplift resources differently under the same conditions. At the global-scale, I found that flight behavior again was driven by the uplift available, as turkey vultures exhibited variable flight patterns when multiple uplift types were available but exhibited a more singular flight pattern when only one uplift type was available. My local-scale observations documented the use of a previously unidentified uplift type to soar, which is likely used by other soaring species. I also documented behavioral response to climate-scale variation in uplift availability. Different responses to uplift availability by black and turkey vultures suggest that sympatry of these species may occur because they have species-specific flight strategies. Species-specific flight strategies should cause vultures to select certain carrion types, thereby diffusing competition for carrion resources. My findings suggest the functional roles of vultures as scavengers is ultimately linked to their movement behavior

Cape Vultures (Gyps coprotheres) and the threat of wind farms: a race to extinction?

The development of wind energy is increasing globally and is often considered more environmentally friendly when compared to fossil fuel technologies. However, one of the ecological drawbacks of wind energy are the collisions of wildlife with turbine blades. In addition, the resulting anthropogenic landscape transformation can negatively impact populations. The Cape Vulture (Gyps coprotheres), a large endangered southern African endemic species, thus may be at risk from turbine development. The species has decreased dramatically in the past 50 years and understanding how additional mortalities from wind turbine impacts affect the population is needed to ensure effective conservation efforts. This study aimed to determine the population response to this emerging threat. This study first reviewed the species-, site- and wind farm- specific traits that make Gyps species vulnerable to collision with wind energy infrastructure. It examined the monitoring practices employed during the pre- and post-construction phase and mitigation measures in South Africa and compared it with international standards. Furthermore, wind energy development may disrupt landscape connectivity and understanding which, and how habitat patches are used is needed. Using network theory combined with telemetry data from tagged individuals across three age classes, habitat patch use was identified. Further, environmental variables associated with identified habitat patches were identified. Additionally, considering the wind energy industry is expanding in South Africa, exploring how the Cape Vulture population will respond to this novel and emerging threat may aid future conservation management plans. Therefore, using a population viability analysis approach, the study explored how present and future wind turbine mortality scenarios impact the Cape Vulture population and how the population will respond to increased wind turbine development.Thesis (PhD) -- Faculty of Science, School of Environmental Sciences, 202

Cape Vultures (Gyps coprotheres) and the threat of wind farms: a race to extinction?

The development of wind energy is increasing globally and is often considered more environmentally friendly when compared to fossil fuel technologies. However, one of the ecological drawbacks of wind energy are the collisions of wildlife with turbine blades. In addition, the resulting anthropogenic landscape transformation can negatively impact populations. The Cape Vulture (Gyps coprotheres), a large endangered southern African endemic species, thus may be at risk from turbine development. The species has decreased dramatically in the past 50 years and understanding how additional mortalities from wind turbine impacts affect the population is needed to ensure effective conservation efforts. This study aimed to determine the population response to this emerging threat. This study first reviewed the species-, site- and wind farm- specific traits that make Gyps species vulnerable to collision with wind energy infrastructure. It examined the monitoring practices employed during the pre- and post-construction phase and mitigation measures in South Africa and compared it with international standards. Furthermore, wind energy development may disrupt landscape connectivity and understanding which, and how habitat patches are used is needed. Using network theory combined with telemetry data from tagged individuals across three age classes, habitat patch use was identified. Further, environmental variables associated with identified habitat patches were identified. Additionally, considering the wind energy industry is expanding in South Africa, exploring how the Cape Vulture population will respond to this novel and emerging threat may aid future conservation management plans. Therefore, using a population viability analysis approach, the study explored how present and future wind turbine mortality scenarios impact the Cape Vulture population and how the population will respond to increased wind turbine development.Thesis (PhD) -- Faculty of Science, School of Environmental Sciences, 202

Ecology and conservation of the Cape vulture in the Eastern Cape Province, South Africa.

Ph. D. in Zoology. University of KwaZulu-Natal, Pietermaritzburg 2016.Abstract available in PDF file

Workshop on research p riorities for migrant pests of agriculture in Southern Africa, Plant Protection Research Institute, Pretoria, South Africa, 24–26 March 1999

The Workshop was held at the Agricultural Research Council – Plant Protection Research Institute, Pretoria, from 24 to 26 March 1999 and was attended by 66 delegates from Botswana, Malawi, Namibia, South Africa, Sudan, Swaziland, Tanzania, United Kingdom, Zimbabwe, the International Red Locust Control Organisation for Central and Southern Africa (IRLCO-CSA) and the Food and Agriculture Organization of the United Nations (FAO) (see pages xiii–xvi for list of delegates). The first day focused on presenting a synopsis of current research on the three main migrant pests in southern Africa – armyworm, locusts and quelea – and described the national, regional (IRLCO-CSA, Southern African Development Community, SADC) and international (FAO) infrastructures for dealing with them. On the second and third days, after consideration of the issues to be addressed to ensure uptake of research findings by resource-poor farmers, the Workshop divided into three groups according to pest species. Each group adopted a generalised Logical Framework approach to identifying research priorities, constraints, risks and linkages. Four Logical Frameworks, covering armyworm, locust, quelea and cross-cutting research priorities were developed and an informal ad hoc steering committee (names annotated in list, pages xiii–xvi) undertook to bring together the Workshop’s findings in a Summary Report and to make recommendations on further actions

Informing landscape-scale management of the greater horseshoe bat Rhinolophus ferrumequinum

Global land use is changing at an unprecedented rate and has been identified as a key driver of habitat loss, fragmentation and species decline in the natural environment. Understanding how land use influences spatial patterns in species abundance, and habitat connectivity at a landscape scale is critical for the survival of wildlife populations. The focal species of my research is the rare greater horseshoe bat (Rhinolophus ferrumequinum), which was once widespread across southern England and Wales. However, owing to changes in agricultural land management and the expansion of urban areas, its range has contracted considerably over the last century. Using a series of ecological techniques, including a novel predictive modelling approach, field experiments and social network analysis, this thesis aims to identify which ecological factors affect their activity and movement at a landscape scale. The work also provides conservation practitioners the ability to identify the locations of these impacts, pinch-points, in the wider environment; where strategic planning and mitigation measures can be applied to increase their overall occurrence and abundance in the wider environment. Using a field experiment, I examined how traffic noise can influence the relative activity levels of free-living bats. Overall, I showed that traffic noise can significantly reduce the activity levels of R. ferrumequinum, as well as other bat species, along linear feature. Using a separate field experiment, I determined that the sonic spectrum had a greater negative effect on bat activity than the ultrasonic spectrum. These results therefore suggest that the mode of action is likely to be through general deterrence and avoidance rather than through the masking of echolocation calls. R. ferrumequinum are widely considered to be dependent on linear landscape features such as woodland edges and hedgerows. My research supported this view, and highlighted the particular importance of treelines, which were associated with greater activity than even sympathetically managed hedgerows. However, an important novel finding from my research was that about a third of all activity recorded at paired detectors was derived from the middle of fields. It is therefore important to consider these more open habitats, as well as hedgerows, treelines and woodland edges, when designing and conducting ecological impact assessments for future developments. Bats use the landscape at a large spatial scale, and responses to any particular challenge (such as a new lighting scheme or urban development) are likely to depend on their context within a landscape. For example, the disruption of a commuting route is likely to have a greater impact where only one suitable route exists, compared with scenarios where there are numerous alternatives. To understand better how R. ferrumequinum interacts with the British landscape, I therefore created models of predicted functional connectivity around four maternity roosts using Circuitscape software. Using non-invasive static bat detectors as a method of ground validation, I created robust models predicting R. ferrumequinum movement; which allowed the identification of pinch-points in the landscape, either those areas limiting species movement or highly important for the species conservation. While most research, and the work of ecological practitioners, focuses on the maternity season, hibernation ecology has received much less attention. Yet given that horseshoe bats are known to move roost location frequently during the hibernation period, it is important to understand more about this behaviour. Using social network analysis, I demonstrate that adult males are significantly more central (connected to a higher number of individual bats) in the network during the hibernation period. I found that movements between hibernacula were associated with both age and degree centrality of individual bats, with those more geographically isolated hibernacula playing an important role for the movement of certain individuals at a landscape scale. This highlights that despite low activity in some of these smaller roost locations, they are a conservation priority to decrease the risk of fragmentation and loss of connectivity within the wider landscape. The results of my meta-analysis, which was based on 22 studies, demonstrated the significant negative effects endectocides on Aphodiinae dung beetles. My results suggest that ivermectin has the highest negative effect on the abundance of both adult and large Aphodiinae dung beetles. However, contrasting results were observed for dung beetle occurrence, with adult beetles showing an attraction to dung with endectocides and larvae showing the complete opposite, with poor survival rates and impaired development. Over time this could have significant negative effects on dung beetle populations. The results of this thesis indicate that the landscape-scale conservation of R. ferrumequinum is complex. Considerations need to be given to a suite of factors ranging from the prey items they consume to the physical habitat structures which they utilise. From this research, specific locations and features which have impacts on their movement and activity can be identified, allowing the outputs to be used by decision-makers as a tool to inform local management strategies. The prioritisation of conservation activity for the species can be aided by spatially-explicit models, such as the one I developed using Circuitscape, which bring together multiple input layers to create outputs readily interpretable to practitioners. However, to achieve a successful outcome for this priority species, collaborative efforts from many stakeholders, across boundaries, are required