Supplementary data for: Potential trade-off between temperature and tissue loss resistance in corals associating with algal symbionts in the genus Durusdinium. All raw data and R codes for statistical analysis are available here and the details of each file are provided on Readme, or Table S8 of the publication.

Supplementary data for: Potential trade-off between temperature and tissue loss resistance in corals associating with algal symbionts in the genus Durusdinium. All raw data and R codes for statistical analysis are available here and the details of each file are provided on Readme, or Table S8 of the publication.

When moving, animals are vulnerable to predation because movement can rapidly attract the attention of a predator. To reduce the risk of predation while moving, animals can use a variety of different strategies (e.g., erratic movement, colouration). These strategies often work in combination or may be influenced by other prey characteristics (e.g., size), but few studies have explored these interactions. Here, we investigate how movement trajectory (linear or erratic), prey size (small or large), and prey colouration (glossy or matte) interact to impact attack behaviour of giant rainforest mantids (Hierodula majuscula). We presented mantids with 3D animations of moving targets and filmed their response with a high-speed camera. As expected, mantids were more likely to track large than small targets and targets moving linearly than erratically. Counterintuitively, however, mantids were quicker to strike at erratically moving targets, perhaps because they more closely resembled preferred prey. When mantids attacked the target, their accuracy was influenced by the interaction of target trajectory and glossiness. As predicted, mantids had larger attack errors (i.e. lower accuracy) toward erratically moving glossy targets compared to linearly moving glossy targets or erratically moving matte targets. However, contrary to our prediction that linearly moving matte targets would be easiest to capture, these targets also elicited large attack errors, similar to those recorded for erratically moving glossy targets. Together, our results demonstrate that anti-predator tactics for prey in motion may interact in complex ways, and simple experimental scenarios may overlook context-dependent effects that emerge when multiple factors interact.

In the accompanying publication, we reported on the production and characterization of the broadest K. pneumoniae capsule bioconjugate vaccine to date. We tested this vaccine for its immunogenicity, functionality, efficacy, and antibody durability against a variety of K. pneumoniae isolates in a murine bacteremia model. We also established an immunocompromised murine model of bacteremia to better recapitulate human infection and tested our vaccine’s efficacy in this background. The data included in the metadata set includes ELISAs, serum bactericidal assay, opsonophagocytosis assay, and survival curves. All data was generated in mice. GraphPad Prism is needed to open the data files. To view the data, use the free viewer mode of the software.

In the accompanying publication, we reported on the production and characterization of the broadest K. pneumoniae capsule bioconjugate vaccine to date. We tested this vaccine for its immunogenicity, functionality, efficacy, and antibody durability against a variety of K. pneumoniae isolates in a murine bacteremia model. We also established an immunocompromised murine model of bacteremia to better recapitulate human infection and tested our vaccine’s efficacy in this background. The data included in the metadata set includes ELISAs, serum bactericidal assay, opsonophagocytosis assay, and survival curves. All data was generated in mice. GraphPad Prism is needed to open the data files. To view the data, use the free viewer mode of the software.

Data and code to reproduce statistical modelling, figures and tables from:The Lawn is Buzzing: Increasing insect biodiversity in urban greenspaces through low-intensity mowingAbstractGreenspaces have become the anvil where stewards and practitioners are forging innovative, evidence-based actions to meet biodiversity targets in urban environments, catalysing a wave of co-designed research/practice projects aimed at assessing the ecological changes brought about by urban greening and generating the evidence that biodiversity objectives are being met. Their full potential often remains unrealised due to entrenched management practices, as best exemplified by high-intensity mowing, which has given rise to the most ubiquitous greenspaces feature worldwide: the turfgrass lawn. Lawns are notoriously deficient at supporting insect communities due to their simplified vegetation structure and low plant diversity, and the compounded effect of frequent mowing on forb growth, which limits their capacity to come into flower and supply floral resources to pollinators and other flower visitors. Addressing these shortcomings can be readily achieved by reducing mowing intensity, resulting in greater vegetation height, flower cover and plant diversity – effectively transforming lawns into a more complex grassland-type ecosystem. This approach is particularly enticing to practitioners pursuing positive, cost-effective biodiversity outcomes while upholding their commitment to core ecological restoration and biodiversity conservation projects. Here, we demonstrate how transitioning a lawn from high- to low-intensity mowing regimes led to pronounced increases in the number of indigenous insect species, evident both for the whole community and on assemblages of functionally similar species, including detritivores, herbivores, predators, parasitoids and pollinators. We further identify a positive effect of vegetation height on the community and species-specific probabilities of occurrence of indigenous species, which was consistently strong for detritivores, herbivores and parasitoids. We also show that the number of indigenous species associated with our low-intensity mowing treatment markedly exceeded that of 43 high-intensity mowed lawns previously surveyed throughout the study area, and that the effect of vegetation height across our field experiment gradient was substantially stronger than that of the existing high-intensity lawns gradient. Our findings provide compelling evidence that reducing lawn mowing intensity yields positive ecological outcomes for functionally diverse indigenous insect communities, charting a course for stakeholders tasked with demonstrating how evidence-based greening actions can be a sound investment to meet local, regional and global biodiversity targets.Keywords: Co-design, Detritivores, Flower-visitors, Functional assemblages, Greening, Hierarchical community models, Nature in cities, Parasitoids, Pollinators, Predators, Urban ecology, Urban environments

Data and code to reproduce statistical modelling, figures and tables from:The Lawn is Buzzing: Increasing insect biodiversity in urban greenspaces through low-intensity mowingAbstractGreenspaces have become the anvil where stewards and practitioners are forging innovative, evidence-based actions to meet biodiversity targets in urban environments, catalysing a wave of co-designed research/practice projects aimed at assessing the ecological changes brought about by urban greening and generating the evidence that biodiversity objectives are being met. Their full potential often remains unrealised due to entrenched management practices, as best exemplified by high-intensity mowing, which has given rise to the most ubiquitous greenspaces feature worldwide: the turfgrass lawn. Lawns are notoriously deficient at supporting insect communities due to their simplified vegetation structure and low plant diversity, and the compounded effect of frequent mowing on forb growth, which limits their capacity to come into flower and supply floral resources to pollinators and other flower visitors. Addressing these shortcomings can be readily achieved by reducing mowing intensity, resulting in greater vegetation height, flower cover and plant diversity – effectively transforming lawns into a more complex grassland-type ecosystem. This approach is particularly enticing to practitioners pursuing positive, cost-effective biodiversity outcomes while upholding their commitment to core ecological restoration and biodiversity conservation projects. Here, we demonstrate how transitioning a lawn from high- to low-intensity mowing regimes led to pronounced increases in the number of indigenous insect species, evident both for the whole community and on assemblages of functionally similar species, including detritivores, herbivores, predators, parasitoids and pollinators. We further identify a positive effect of vegetation height on the community and species-specific probabilities of occurrence of indigenous species, which was consistently strong for detritivores, herbivores and parasitoids. We also show that the number of indigenous species associated with our low-intensity mowing treatment markedly exceeded that of 43 high-intensity mowed lawns previously surveyed throughout the study area, and that the effect of vegetation height across our field experiment gradient was substantially stronger than that of the existing high-intensity lawns gradient. Our findings provide compelling evidence that reducing lawn mowing intensity yields positive ecological outcomes for functionally diverse indigenous insect communities, charting a course for stakeholders tasked with demonstrating how evidence-based greening actions can be a sound investment to meet local, regional and global biodiversity targets.Keywords: Co-design, Detritivores, Flower-visitors, Functional assemblages, Greening, Hierarchical community models, Nature in cities, Parasitoids, Pollinators, Predators, Urban ecology, Urban environments

Spectral machine vision collects spectral and spatial information as dense 3D hypercubes and digitally processes them into scene recognition, which causes a data bottleneck, limiting power efficiency, frame rate, and spectral-spatial resolution. This work introduces a device architecture called spectral kernel machines (SKM) to overcome these bottlenecks. SKM directly compresses spectral analysis through the output photocurrent and learns from example objects to identify and classify new samples in a 'sniff-and-seek' mode. We experimentally demonstrated SKM with electrically tunable bipolar black phosphorous (bP)-MoS2 photodiodes in the near/mid-infrared band and silicon photoconductors in the visible band, performing versatile intelligent tasks from chemometrics to semiconductor metrology. This architecture consumes significantly lower power and is more than an order of magnitude faster than existing solutions for hyperspectral image analysis, defining an intelligent imaging and sensing paradigm with intriguing possibilities.

Respirometry data

Respirometry data