Biology subjects

Dyer, A. G.

Publications and source records attributed to Dyer, A. G..

5 recordsLinked to original sources

bioRxiv2022

Mimicking orchids lure bees from afar with exaggerated ultraviolet signals

O_LIFlowers have many sensory traits to appeal to pollinators, including ultraviolet (UV) absorbing markings, which are well known for attracting bees at close proximity (e.g. < 1 m). While striking UV signals have been thought to attract pollinators also at greater distances of meters, how the signals impact the plant pollination success over distance remains unknown. Here we report the case of the Australian orchid Diuris brumalis, a non-rewarding species, pollinated by bees via mimicry of rewarding pea plant Daviesia decurrens. When distant from the pea plant, Diuris brumalis was hypothesized to enhance pollinator attraction by exaggerately mimicking the floral ultraviolet (UV) reflecting patterns of its model. C_LIO_LIBy experimentally modulating floral UV reflectance with a UV screening solution, we quantified the orchid pollination success at variable distance from the model plants. C_LIO_LIWe demonstrate that the deceptive orchid Diuris brumalis attracts bee pollinators by emphasizing the visual stimuli, which mimic the floral UV signalling of the rewarding model D. decurrens. Moreover, the exaggerated UV reflectance of D. brumalis flowers impacted pollinators visitation at an optimal distance from D. decurrens, and the effect decreased when orchids were too close or too far away from the model. C_LIO_LIOur findings show that salient UV flower signalling plays a functional role in visual floral mimicry, likely exploiting perceptual gaps in bee neural coding, and mediates the plant pollination success at much greater spatial scales than previously expected. C_LI

ecology↗

bioRxiv2021

Monitoring photogenic ecological phenomena: Social network site images reveal spatiotemporal phases of Japanese cherry blooms

Some ecological phenomena are visually engaging and widely celebrated. Consequently, these have the potential to generate large footprints in the online and social media image records which may be valuable for ecological research. Cherry tree blooms are one such event, especially in Japan where they are a cultural symbol (Sakura, ). For centuries, the Japanese have celebrated Hanami (flower viewing) and the historical data record of the festival allows for phenological studies over this period, one application of which is climate reconstruction. Here we analyse Flickr social network site data in an analogous way to reveal the cherry blossoms seasonal sweep from southern to northern Japan over a twelve-week period. Our method analyses data filtered using geographical constraints, multi-stage text-tag classification, and machine vision, to assess image content for relevance to our research question and use it to estimate historic cherry bloom times. We validated our estimated bloom times against official data, demonstrating the accuracy of the approach. We also investigated an out of season Autumn blooming that has gained worldwide media attention. Despite the complexity of human photographic and social media activity and the relatively small scale of this event, our method can reveal that this bloom has in fact been occurring over a decade. The approach we propose in our case study enables quick and effective monitoring of the photogenic spatiotemporal aspects of our rapidly changing world. It has the potential to be applied broadly to many ecological phenomena of widespread interest.

ecology↗

bioRxiv2020

Tracking individual honeybees among wildflower clusters with computer vision-facilitated pollinator monitoring

Monitoring animals in their natural habitat is essential for advancement of animal behavioural studies, especially in pollination studies. Non-invasive techniques are preferred for these purposes as they reduce opportunities for research apparatus to interfere with behaviour. One potentially valuable approach is image-based tracking. However, the complexity of tracking unmarked wild animals using video is challenging in uncontrolled outdoor environments. Out-of-the-box algorithms currently present several problems in this context that can compromise accuracy, especially in cases of occlusion in a 3D environment. To address the issue, we present a novel hybrid detection and tracking algorithm to monitor unmarked insects outdoors. Our software can detect an insect, identify when a tracked insect becomes occluded from view and when it re-emerges, determine when an insect exits the camera field of view, and our software assembles a series of insect locations into a coherent trajectory. The insect detecting component of the software uses background subtraction and deep learning-based detection together to accurately and efficiently locate the insect among a cluster of wildflowers. We applied our method to track honeybees foraging outdoors using a new dataset that includes complex background detail, wind-blown foliage, and insects moving into and out of occlusion beneath leaves and among three-dimensional plant structures. We evaluated our software against human observations and previous techniques. It tracked honeybees at a rate of 86.6% on our dataset, 43% higher than the computationally more expensive, standalone deep learning model YOLOv2. We illustrate the value of our approach to quantify fine-scale foraging of honeybees. The ability to track unmarked insect pollinators in this way will help researchers better understand pollination ecology. The increased efficiency of our hybrid approach paves the way for the application of deep learning-based techniques to animal tracking in real-time using low-powered devices suitable for continuous monitoring.

animal behavior and cognition↗

bioRxiv2019

Australian native flower colours: does nectar reward drive bee pollinator flower preferences?

Colour is an important signal that flowering plants use to attract insect pollinators like bees. Previous research in Germany has shown that nectar volume is higher for flower colours that are innately preferred by European bees, suggesting an important link between colour signals, bee preferences and floral rewards. In Australia, flower colour signals have evolved in parallel to the Northern hemisphere to enable easy discrimination and detection by the phylogenetically ancient trichromatic visual system of bees, and native Australian bees also possess similar innate colour preferences to European bees. We measured 59 spectral signatures from flowers present at two preserved native habitats in South Eastern Australia and tested whether there were any significant differences in the frequency of flowers presenting higher nectar rewards depending upon the colour category of the flower signals, as perceived by bees. We also tested if there was a significant correlation between chromatic contrast and the frequency of flowers presenting higher nectar rewards. For the entire sample, and for subsets excluding species in the Asteraceae and Orchidaceae, we found no significant difference among colour categories in the frequency of high nectar reward. This suggests that whilst such relationships between flower colour signals and nectar volume rewards have been observed at a field site in Germany, the effect is likely to be specific at a community level rather than a broad general principle that has resulted in the common signalling of bee flower colours around the world.

ecology↗

bioRxiv2019

Alarm tones, music and their elements: A mixed methods analysis of reported waking sounds for the prevention of sleep inertia.

Sleep inertia is a potentially dangerous reduction in human alertness and occurs 0 - 4 hours after waking. The type of sound people set as their alarm for waking has been shown to reduce the effects of sleep inertia, however, the elemental musical factors that underpin these waking sounds and their relationship remain unclear. The goal of this research is to understand how a particular sound or music chosen to assist waking may counteract sleep inertia, and more specifically, what elements of these sounds may contribute to its reduction using a mix methods analysis. Through an anonymous, self-report online questionnaire, fifty participants (N = 50) reported attributes of their preferred waking sound, their feeling towards the waking sound, and symptoms of sleep inertia after waking. This data enabled the analysis and comparison between these responses to define statistically significant interactions. Our results show that there is no significant relationship between sleep inertia and the reported waking sound, nor the subjects feeling towards this sound. However, we found that the melodicity of a chosen waking sound does effect sleep inertia. A sound that is perceived as melodic, produces less sleep inertia in comparison to a sound considered to be neutral (neither unmelodic nor melodic). Furthermore, a secondary analysis reveals that this is an important factor for waking stimulus design as it suggests that the amount of perceived rhythm will affect the perception of melody, and in turn, may influence the severity of sleep inertia on a secondary level. Our results reveal that the inclusion of detailed descriptive terms (musical elements) in addition to macro classifications (e.g. \"pop music\") for stimulus testing would benefit future research and our understanding of waking audios effects on sleep inertia.

animal behavior and cognition↗