Ancient insect vision tuned for flight among rocks and plants underpins natural flower colour diversity.

Understanding the origins of flower colour signalling to pollinators is fundamental to evolutionary biology and ecology. Flower colour evolves under pressure from visual systems of pollinators, like birds and insects, to establish global signatures among flowers with similar pollinators. However, an understanding of the ancient origins of this relationship remains elusive. Here, we employ computer simulations to generate artificial flower backgrounds assembled from real material sample spectra of rocks, leaves and dead plant materials, against which to test flowers' visibility to birds and bees. Our results indicate how flower colours differ from their backgrounds in strength, and the distributions of salient reflectance features when perceived by these key pollinators, to reveal the possible origins of their colours. Since Hymenopteran visual perception evolved before flowers, the terrestrial chromatic context for its evolution to facilitate flight and orientation consisted of rocks, leaves, sticks and bark. Flowers exploited these pre-evolved visual capacities of their visitors, in response evolving chromatic features to signal to bees, and differently to birds, against a backdrop of other natural materials. Consequently, it appears that today's flower colours may be an evolutionary response to the vision of diurnal pollinators navigating their world millennia prior to the first flowers.

Assessing the carbon footprint of digital health interventions: a scoping review.

OBJECTIVE: Integration of environmentally sustainable digital health interventions requires robust evaluation of their carbon emission life-cycle before implementation in healthcare. This scoping review surveys the evidence on available environmental assessment frameworks, methods, and tools to evaluate the carbon footprint of digital health interventions for environmentally sustainable healthcare. MATERIALS AND METHODS: Medline (Ovid), Embase (Ovid). PsycINFO (Ovid), CINAHL, Web of Science, Scopus (which indexes IEEE Xplore, Springer Lecture Notes in Computer Science and ACM databases), Compendex, and Inspec databases were searched with no time or language constraints. The Systematic Reviews and Meta-analyses Extension for Scoping Reviews (PRISMA_SCR), Joanna Briggs Scoping Review Framework, and template for intervention description and replication (TiDiER) checklist were used to structure and report the findings. RESULTS: From 3299 studies screened, data was extracted from 13 full-text studies. No standardised methods or validated tools were identified to systematically determine the environmental sustainability of a digital health intervention over its full life-cycle from conception to realisation. Most studies (n = 8) adapted publicly available carbon calculators to estimate telehealth travel-related emissions. Others adapted these tools to examine the environmental impact of electronic health records (n = 2), e-prescriptions and e-referrals (n = 1), and robotic surgery (n = 1). One study explored optimising the information system electricity consumption of telemedicine. No validated systems-based approach to evaluation and validation of digital health interventions could be identified. CONCLUSION: There is a need to develop standardised, validated methods and tools for healthcare environments to assist stakeholders to make informed decisions about reduction of carbon emissions from digital health interventions.

Towards precision apiculture: Traditional and technological insect monitoring methods in strawberry and raspberry crop polytunnels tell different pollination stories.

Over one third of crops are animal pollinated, with insects being the largest group. In some crops, including strawberries, fruit yield, weight, quality, aesthetics and shelf life increase with insect pollination. Many crops are protected from extreme weather in polytunnels, but the impacts of polytunnels on insects are poorly understood. Polytunnels could reduce pollination services, especially if insects have access issues. Here we examine the distribution and activity of honeybees and non-honeybee wild insects on a commercial fruit farm. We evaluated whether insect distributions are impacted by flower type (strawberry; raspberry; weed), or distance from polytunnel edges. We compared passive pan-trapping and active quadrat observations to establish their suitability for monitoring insect distribution and behaviour on a farm. To understand the relative value of honeybees compared to other insects for strawberry pollination, the primary crop at the site, we enhanced our observations with video data analysed using insect tracking software to document the time spent by insects on flowers. The results show honeybees strongly prefer raspberry and weed flowers over strawberry flowers and that location within the polytunnel impacts insect distributions. Consistent with recent studies, we also show that pan-traps are ineffective to sample honeybee numbers. While the pan-traps and quadrat observations tend to suggest that investment in managed honeybees for strawberry pollination might be ineffective due to consistent low numbers within the crop, the camera data provides contrary evidence. Although honeybees were relatively scarce among strawberry crops, camera data shows they spent more time visiting flowers than other insects. Our results demonstrate that a commercial fruit farm is a complex ecosystem influencing pollinator diversity and abundance through a range of factors. We show that monitoring methods may differ in their valuation of relative contributions of insects to crop pollination.

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.

Automated calculation of spectral-reflectance marker-points to enable analysis of plant colour-signalling to pollinators.

A spectral reflectance curve for a coloured surface can be constructed from a set of radiation reflectance value measurements made across the spectrum at discrete wavelengths. The curve gives an indication of the pattern of light entering the eye of an organism viewing an illuminated object. Marker points represent the positions along a reflectance curve at which sharp transitions in reflectance occur, these being potentially important to visual perception, for instance by insects discriminating between two flowers, each of a different colour. Consequently, methods of marker point analysis have been applied in several studies evaluating flower colours. These studies have sometimes required researchers to place marker points on reflectance curves by eye, or they have used algorithms written as unreleased software. To automate the process systematically and provide open access, we implemented special-purpose software in C++. Below we provide a summary of the approach adopted in our implementation and made available online in a port to TypeScript. The main benefits of our method are summarized as being:•Automation and repeatability.•Standardisation, cross-platform compatibility and Open Access.•Interactive exploration of the effects of parameter variation.

Psychophysics of the hoverfly: categorical or continuous color discrimination?

There is increasing interest in flies as potentially important pollinators. Flies are known to have a complex visual system, including 4 spectral classes of photoreceptors that contribute to the perception of color. Our current understanding of how color signals are perceived by flies is based on data for the blowfly Lucilia sp., which after being conditioned to rewarded monochromatic light stimuli, showed evidence of a categorical color visual system. The resulting opponent fly color space has 4 distinct categories, and has been used to interpret how some fly pollinators may perceive flower colors. However, formal proof that flower flies (Syrphidae) only use a simple, categorical color process remains outstanding. In free-flying experiments, we tested the hoverfly Eristalis tenax, a Batesian mimic of the honeybee, that receives its nutrition by visiting flowers. Using a range of broadband similar-dissimilar color stimuli previously used to test color perception in pollinating hymenopteran species, we evaluated if there are steep changes in behavioral choices with continuously increasing color differences as might be expected by categorical color processing. Our data revealed that color choices by the hoverfly are mediated by a continuous monotonic function. Thus, these flies did not use a categorical processing, but showed evidence of a color discrimination function similar to that observed in several bee species. We therefore empirically provide data for the minimum color distance that can be discriminated by hoverflies in fly color space, enabling an improved understanding of plant-pollinator interactions with a non-model insect species.

Fluorescent Pan Traps Affect the Capture Rate of Insect Orders in Different Ways.

To monitor and quantify the changes in pollinator communities over time, it is important to have robust survey techniques of insect populations. Pan traps allow for the assessment of the relative insect abundance in an environment and have been promoted by the Food and Agricultural Organization (FAO) as an efficient data collection methodology. It has been proposed that fluorescent pan traps are particularly useful, as it has been suggested that they capture high numbers of insects in an unbiased fashion. We use a simultaneous presentation of fluorescent and non-fluorescent pan trap colours to assess how flower-visiting insects of different orders respond to visual stimuli and reveal a significant interaction between trap fluorescence and captured insect type. In particular, Coleoptera (beetles) and Lepidoptera (butterflies and moths) were captured significantly more frequently by fluorescent traps, whilst Dipterans (flies) were captured significantly less frequently by this type of pan trap. Hymenopterans (bees and wasps) showed no significant difference in their preference for fluorescent or non-fluorescent traps. Our results reveal that the use of fluorescent pan traps may differently bias insect capture rates when compared to the typical experience of colour flower-visiting insects in natural environments. Correction factors may, therefore, be required for interpreting insect pan trap data collected with different methodologies.

Averting robo-bees: why free-flying robotic bees are a bad idea.

Food security and the sustainability of native ecosystems depends on plant-insect interactions in countless ways. Recently reported rapid and immense declines in insect numbers due to climate change, the use of pesticides and herbicides, the introduction of agricultural monocultures, and the destruction of insect native habitat, are all potential contributors to this grave situation. Some researchers are working towards a future where natural insect pollinators might be replaced with free-flying robotic bees, an ecologically problematic proposal. We argue instead that creating environments that are friendly to bees and exploring the use of other species for pollination and bio-control, particularly in non-European countries, are more ecologically sound approaches. The computer simulation of insect-plant interactions is a far more measured application of technology that may assist in managing, or averting, 'Insect Armageddon' from both practical and ethical viewpoints.

Pollination in a new climate: Assessing the potential influence of flower temperature variation on insect pollinator behaviour.

Climate change has the potential to enhance or disrupt biological systems, but currently, little is known about how organism plasticity may facilitate adaptation to localised climate variation. The bee-flower relationship is an exemplar signal-receiver system that may provide important insights into the complexity of ecological interactions in situations like this. For example, several studies on bee temperature preferences show that bees prefer to collect warm nectar from flowers at low ambient temperatures, but switch their preferences to cooler flowers at ambient temperatures above about 30° C. We used temperature sensor thermal probes to measure the temperature of outdoor flowers of 30 plant species in the Southern regions of the Australian mainland, to understand how different species could modulate petal temperature in response to changes in ambient temperature and, potentially, influence the decision-making of bees in the flowering plant's favour. We found that flower petal temperatures respond in different ways to changing ambient temperature: linearly increasing or decreasing relative to the ambient temperature, dynamically changing in a non-linear manner, or varying their temperature along with the ambient conditions. For example, our investigation of the difference between ambient temperature and petal temperature (ΔT), and ambient temperature, revealed a non-linear relationship for Erysimum linifolium and Polygala grandiflora that seems suited to bee temperature preferences. The temperature profiles of species like Hibertia vestita and H. obtusifolia appear to indicate that they do not have a cooling mechanism. These species may therefore be less attractive to bee pollinators in changing climatic conditions with ambient temperatures increasingly above 30° C. This may be to the species' detriment when insect-pollinator mediated selection is considered. However, we found no evidence that flower visual characteristics used by bees to identify flowers at close range, such as colour or shape, were straightforward modulators of floral temperature. We could not identify any clear link to phylogenetic history and temperature modulation either. Mapping our test flower distribution on the Australian continent however, indicates a potential clustering that suggests different flower responses may constitute adaptations to local conditions. Our study proposes a framework for modelling the potential effects of climate change and floral temperature on flower pollination dynamics at local and global scales.

Why background colour matters to bees and flowers.

Flowers are often viewed by bee pollinators against a variety of different backgrounds. On the Australian continent, backgrounds are very diverse and include surface examples of all major geological stages of the Earth's history, which have been present during the entire evolutionary period of Angiosperms. Flower signals in Australia are also representative of typical worldwide evolutionary spectral adaptations that enable successful pollination. We measured the spectral properties of 581 natural surfaces, including rocks, sand, green leaves, and dry plant materials, sampled from tropical Cairns through to the southern tip of mainland Australia. We modelled in a hexagon colour space, how interactions between background spectra and flower-like colour stimuli affect reliable discrimination and detection in bee pollinators. We calculated the extent to which a given locus would be conflated with the loci of a different flower-colour stimulus using empirically determined colour discrimination regions for bee vision. Our results reveal that whilst colour signals are robust in homogeneous background viewing conditions, there could be significant pressure on plant flowers to evolve saliently-different colours to overcome background spectral noise. We thus show that perceptual noise has a large influence on how colour information can be used in natural conditions.

Artificial Life Art, Creativity, and Techno-hybridization (editor's introduction).

Artists and engineers have devised lifelike technology for millennia. Their ingenious devices have often prompted inquiry into our preferences, prejudices, and beliefs about living systems, especially regarding their origins, status, constitution, and behavior. A recurring fabrication technique is shared across artificial life art, science, and engineering. This involves aggregating representations or re-creations of familiar biological parts-techno-hybridization-but the motives of practitioners may differ markedly. This article, and the special issue it introduces, explores how ground familiar to contemporary artificial life science and engineering has been assessed and interpreted in parallel by (a) artists and (b) theorists studying creativity explicitly. This activity offers thoughtful, alternative perspectives on artificial life science and engineering, highlighting and sometimes undermining the fields' underlying assumptions, or exposing avenues that are yet to be explored outside of art. Additionally, art has the potential to engage the general public, supporting and exploring the findings of scientific research and engineering. This adds considerably to the maturity of a culture tackling the issues the discipline of artificial life raises.

Flower colours through the lens: quantitative measurement with visible and ultraviolet digital photography.

BACKGROUND: The study of the signal-receiver relationship between flowering plants and pollinators requires a capacity to accurately map both the spectral and spatial components of a signal in relation to the perceptual abilities of potential pollinators. Spectrophotometers can typically recover high resolution spectral data, but the spatial component is difficult to record simultaneously. A technique allowing for an accurate measurement of the spatial component in addition to the spectral factor of the signal is highly desirable. METHODOLOGY/PRINCIPAL FINDINGS: Consumer-level digital cameras potentially provide access to both colour and spatial information, but they are constrained by their non-linear response. We present a robust methodology for recovering linear values from two different camera models: one sensitive to ultraviolet (UV) radiation and another to visible wavelengths. We test responses by imaging eight different plant species varying in shape, size and in the amount of energy reflected across the UV and visible regions of the spectrum, and compare the recovery of spectral data to spectrophotometer measurements. There is often a good agreement of spectral data, although when the pattern on a flower surface is complex a spectrophotometer may underestimate the variability of the signal as would be viewed by an animal visual system. CONCLUSION: Digital imaging presents a significant new opportunity to reliably map flower colours to understand the complexity of these signals as perceived by potential pollinators. Compared to spectrophotometer measurements, digital images can better represent the spatio-chromatic signal variability that would likely be perceived by the visual system of an animal, and should expand the possibilities for data collection in complex, natural conditions. However, and in spite of its advantages, the accuracy of the spectral information recovered from camera responses is subject to variations in the uncertainty levels, with larger uncertainties associated with low radiance levels.

The practice of agent-based model visualization.

We discuss approaches to agent-based model visualization. Agent-based modeling has its own requirements for visualization, some shared with other forms of simulation software, and some unique to this approach. In particular, agent-based models are typified by complexity, dynamism, nonequilibrium and transient behavior, heterogeneity, and a researcher's interest in both individual- and aggregate-level behavior. These are all traits requiring careful consideration in the design, experimentation, and communication of results. In the case of all but final communication for dissemination, researchers may not make their visualizations public. Hence, the knowledge of how to visualize during these earlier stages is unavailable to the research community in a readily accessible form. Here we explore means by which all phases of agent-based modeling can benefit from visualization, and we provide examples from the available literature and online sources to illustrate key stages and techniques.

Molecular dynamics extended for fluctuating networks: application to water.

Molecular simulation models are increasingly important tools in efforts to understand the role that water plays in biochemical processes. However, existing models of water have limited capacity to deal with the characteristics of hydrogen bond networks. This article proposes a new fluctuating network (FN) algorithm as an extension of the standard molecular dynamics algorithm. The new algorithm allows for the simulation of a molecular system based on an underlying network, such as the hydrogen bond network in water. This algorithm distinguishes strong from weak network connections, applying a potential that best describes the specific connection behavior. We model liquid water with this new technique using a single-site, isotropic, short-range potential. We successfully reproduce liquid water's signature molecular spacing (as represented by the radial distribution function) and characterize its dynamic properties including the exponential hydrogen bond lifetime distribution, diffusion rate, and average hydrogen bonds per molecule. The FN algorithm allows exploration of the behavior of networked systems where explicit coordination limits are required. As such it could also be used to model covalent interactions, reaction dynamics, and applied to simulation of cellular networks.

Building artificial life for play.

Playthings are often engineered to replicate the character of real organisms. In the past, inventors lavished great expense on their lifelike automata, their constraints being typically related to the mechanical technology they employed and the amount of time and effort they were able to commit to the enterprise. The devices that are currently produced are usually intended for the mass market. The cost of production therefore is a major concern, even though the technology is more sophisticated and highly automated than in the past. Consequently, toymakers and engineers, as well as artists, of the past and present alike have had to think abstractly about living systems in order to construct their simulacra economically. This essay examines a number of lifelike toys to discover the properties of real organisms that their designers have attempted to recreate. That we, as users of these devices, so readily recognize in them a degree of lifelikeness demonstrates the extent to which intuition may sway our intellectual reasoning about real biology. As a result, an innovative toymaker or artist is able to manipulate us to zoomorphize even the most extreme abstractions--at least momentarily--despite our rational reluctance to accept the trickery.