Using individual-based trait frequency distributions to forecast plant-pollinator network responses to environmental change.

Determining how and why organisms interact is fundamental to understanding ecosystem responses to future environmental change. To assess the impact on plant-pollinator interactions, recent studies have examined how the effects of environmental change on individual interactions accumulate to generate species-level responses. Here, we review recent developments in using plant-pollinator networks of interacting individuals along with their functional traits, where individuals are nested within species nodes. We highlight how these individual-level, trait-based networks connect intraspecific trait variation (as frequency distributions of multiple traits) with dynamic responses within plant-pollinator communities. This approach can better explain interaction plasticity, and changes to interaction probabilities and network structure over spatiotemporal or other environmental gradients. We argue that only through appreciating such trait-based interaction plasticity can we accurately forecast the potential vulnerability of interactions to future environmental change. We follow this with general guidance on how future studies can collect and analyse high-resolution interaction and trait data, with the hope of improving predictions of future plant-pollinator network responses for targeted and effective conservation.

Genomic variation in montane bumblebees in Scandinavia: High levels of intraspecific diversity despite population vulnerability.

Populations of many bumblebee species are declining, with distributions shifting northwards to track suitable climates. Climate change is considered a major contributing factor. Arctic species are particularly vulnerable as they cannot shift further north, making assessment of their population viability important. Analysis of levels of whole-genome variation is a powerful way to analyse population declines and fragmentation. Here, we use genome sequencing to analyse genetic variation in seven species of bumblebee from the Scandinavian mountains, including two classified as vulnerable. We sequenced 333 samples from across the ranges of these species in Sweden. Estimates of effective population size (NE ) vary from ~55,000 for species with restricted high alpine distributions to 220,000 for more widespread species. Population fragmentation is generally very low or undetectable over large distances in the mountains, suggesting an absence of barriers to gene flow. The relatively high NE and low population structure indicate that none of the species are at immediate risk of negative genetic effects caused by high levels of genetic drift. However, reconstruction of historical fluctuations in NE indicates that the arctic specialist species Bombus hyperboreus has experienced population declines since the last ice age and we detected one highly inbred diploid male of this species close to the southern limit of its range, potentially indicating elevated genetic load. Although the levels of genetic variation in montane bumblebee populations are currently relatively high, their ranges are predicted to shrink drastically due to the effects of climate change and monitoring is essential to detect future population declines.

Powerful gene-based testing by integrating long-range chromatin interactions and knockoff genotypes.

Gene-based tests are valuable techniques for identifying genetic factors in complex traits. Here, we propose a gene-based testing framework that incorporates data on long-range chromatin interactions, several recent technical advances for region-based tests, and leverages the knockoff framework for synthetic genotype generation for improved gene discovery. Through simulations and applications to genome-wide association studies (GWAS) and whole-genome sequencing data for multiple diseases and traits, we show that the proposed test increases the power over state-of-the-art gene-based tests in the literature, identifies genes that replicate in larger studies, and can provide a more narrow focus on the possible causal genes at a locus by reducing the confounding effect of linkage disequilibrium. Furthermore, our results show that incorporating genetic variation in distal regulatory elements tends to improve power over conventional tests. Results for UK Biobank and BioBank Japan traits are also available in a publicly accessible database that allows researchers to query gene-based results in an easy fashion.

Genomic Signatures of Recent Adaptation in a Wild Bumblebee.

Environmental changes threaten insect pollinators, creating risks for agriculture and ecosystem stability. Despite their importance, we know little about how wild insects respond to environmental pressures. To understand the genomic bases of adaptation in an ecologically important pollinator, we analyzed genomes of Bombus terrestris bumblebees collected across Great Britain. We reveal extensive genetic diversity within this population, and strong signatures of recent adaptation throughout the genome affecting key processes including neurobiology and wing development. We also discover unusual features of the genome, including a region containing 53 genes that lacks genetic diversity in many bee species, and a horizontal gene transfer from a Wolbachia bacteria. Overall, the genetic diversity we observe and how it is distributed throughout the genome and the population should support the resilience of this important pollinator species to ongoing and future selective pressures. Applying our approach to more species should help understand how they can differ in their adaptive potential, and to develop conservation strategies for those most at risk.

Toxic temperatures: Bee behaviours exhibit divergent pesticide toxicity relationships with warming.

Climate change and agricultural intensification are exposing insect pollinators to temperature extremes and increasing pesticide usage. Yet, we lack good quantification of how temperature modulates the sublethal effects of pesticides on behaviours vital for fitness and pollination performance. Consequently, we are uncertain if warming decreases or increases the severity of different pesticide impacts, and whether separate behaviours vary in the direction of response. Quantifying these interactive effects is vital in forecasting pesticide risk across climate regions and informing pesticide application strategies and pollinator conservation. This multi-stressor study investigated the responses of six functional behaviours of bumblebees when exposed to either a neonicotinoid (imidacloprid) or a sulfoximine (sulfoxaflor) across a standardised low, mid, and high temperature. We found the neonicotinoid had a significant effect on five of the six behaviours, with a greater effect at the lower temperature(s) when measuring responsiveness, the likelihood of movement, walking rate, and food consumption rate. In contrast, the neonicotinoid had a greater impact on flight distance at the higher temperature. Our findings show that different organismal functions can exhibit divergent thermal responses, with some pesticide-affected behaviours showing greater impact as temperatures dropped, and others as temperatures rose. We must therefore account for environmental context when determining pesticide risk. Moreover, we found evidence of synergistic effects, with just a 3°C increase causing a sudden drop in flight performance, despite seeing no effect of pesticide at the two lower temperatures. Our findings highlight the importance of multi-stressor studies to quantify threats to insects, which will help to improve dynamic evaluations of population tipping points and spatiotemporal risks to biodiversity across different climate regions.

Signatures of increasing environmental stress in bumblebee wings over the past century: Insights from museum specimens.

Determining when animal populations have experienced stress in the past is fundamental to understanding how risk factors drive contemporary and future species' responses to environmental change. For insects, quantifying stress and associating it with environmental factors has been challenging due to a paucity of time-series data and because detectable population-level responses can show varying lag effects. One solution is to leverage historic entomological specimens to detect morphological proxies of stress experienced at the time stressors emerged, allowing us to more accurately determine population responses. Here we studied specimens of four bumblebee species, an invaluable group of insect pollinators, from five museums collected across Britain over the 20th century. We calculated the degree of fluctuating asymmetry (FA; random deviations from bilateral symmetry) between the right and left forewings as a potential proxy of developmental stress. We: (a) investigated whether baseline FA levels vary between species, and how this compares between the first and second half of the century; (b) determined the extent of FA change over the century in the four bumblebee species, and whether this followed a linear or nonlinear trend; (c) tested which annual climatic conditions correlated with increased FA in bumblebees. Species differed in their baseline FA, with FA being higher in the two species that have recently expanded their ranges in Britain. Overall, FA significantly increased over the century but followed a nonlinear trend, with the increase starting c. 1925. We found relatively warm and wet years were associated with higher FA. Collectively our findings show that FA in bumblebees increased over the 20th century and under weather conditions that will likely increase in frequency with climate change. By plotting FA trends and quantifying the contribution of annual climate conditions on past populations, we provide an important step towards improving our understanding of how environmental factors could impact future populations of wild beneficial insects.

How competition between overlapping generations can influence optimal egg-laying strategies in annual social insects.

Annual social insects are an integral functional group of organisms, particularly in temperate environments. An emblematic part of their annual cycle is the social phase, during which the colony-founding queen rears workers that later assist her in rearing sexual progeny (gynes and drones). In many annual social insects, such as species of bees, wasps, and other groups, developing larvae are provisioned gradually as they develop (progressive provisioning) leading to multiple larval generations being reared simultaneously. We present a model for how the queen in such cases should optimize her egg-laying rate throughout the social phase depending on number-size trade-offs, colony age-structure, and energy balance. Complementing previous theory on optimal allocation between workers vs. sexuals in annual social insects and on temporal egg-laying patterns in solitary insects, we elucidate how resource competition among overlapping larval generations can influence optimal egg-laying strategies. With model parameters informed by knowledge of a common bumblebee species, the optimal egg-laying schedule consists of two temporally separated early broods followed by a more continuous rearing phase, matching empirical observations. However, eggs should initially be laid continuously at a gradually increasing rate when resources are scarce or mortality risks high and in cases where larvae are fully supplied with resources at the egg-laying stage (mass-provisioning). These factors, alongside sexual:worker body size ratios, further determine the overall trend in egg-laying rates over the colony cycle. Our analysis provides an inroad to study and mechanistically understand variation in colony development strategies within and across species of annual social insects.

Identification of C2CD4A as a human diabetes susceptibility gene with a role in ß cell insulin secretion.

Fine mapping and validation of genes causing ß cell failure from susceptibility loci identified in type 2 diabetes genome-wide association studies (GWAS) poses a significant challenge. The VPS13C-C2CD4A-C2CD4B locus on chromosome 15 confers diabetes susceptibility in every ethnic group studied to date. However, the causative gene is unknown. FoxO1 is involved in the pathogenesis of ß cell dysfunction, but its link to human diabetes GWAS has not been explored. Here we generated a genome-wide map of FoxO1 superenhancers in chemically identified ß cells using 2-photon live-cell imaging to monitor FoxO1 localization. When parsed against human superenhancers and GWAS-derived diabetes susceptibility alleles, this map revealed a conserved superenhancer in C2CD4A, a gene encoding a ß cell/stomach-enriched nuclear protein of unknown function. Genetic ablation of C2cd4a in ß cells of mice phenocopied the metabolic abnormalities of human carriers of C2CD4A-linked polymorphisms, resulting in impaired insulin secretion during glucose tolerance tests as well as hyperglycemic clamps. C2CD4A regulates glycolytic genes, and notably represses key ß cell "disallowed" genes, such as lactate dehydrogenase A We propose that C2CD4A is a transcriptional coregulator of the glycolytic pathway whose dysfunction accounts for the diabetes susceptibility associated with the chromosome 15 GWAS locus.

Gull's Theorem Revisited.

In 2016, Steve Gull has outlined has outlined a proof of Bell's theorem using Fourier theory. Gull's philosophy is that Bell's theorem (or perhaps a key lemma in its proof) can be seen as a no-go theorem for a project in distributed computing with classical, not quantum, computers. We present his argument, correcting misprints and filling gaps. In his argument, there were two completely separated computers in the network. We need three in order to fill all the gaps in his proof: a third computer supplies a stream of random numbers to the two computers representing the two measurement stations in Bell's work. One could also imagine that computer replaced by a cloned, virtual computer, generating the same pseudo-random numbers within each of Alice and Bob's computers. Either way, we need an assumption of the presence of shared i.i.d. randomness in the form of a synchronised sequence of realisations of i.i.d. hidden variables underlying the otherwise deterministic physics of the sequence of trials. Gull's proof then just needs a third step: rewriting an expectation as the expectation of a conditional expectation given the hidden variables.

Schrödinger's Cat Meets Occam's Razor.

We discuss V.P. Belavkin's approach to the Schrödinger cat problem and show its close relation to ideas based on superselection and interaction with the environment developed by N.P. Landsman. The purpose of the paper is to explain these ideas in the most simple possible context, namely: discrete time and separable Hilbert spaces, in order to make them accessible to those coming from the philosophy of science and not too happy with idiosyncratic notation and terminology and sophisticated mathematical tools. Conventional elementary mathematical descriptions of quantum mechanics take "measurement" to be a primitive concept. Paradoxes arise when we choose to consider smaller or larger systems as measurement devices in their own right, by making different and apparently arbitrary choices of location of the "Heisenberg cut". Various quantum interpretations have different resolutions of the paradox. In Belavkin's approach, the classical world around us does really exist, and it evolves stochastically and dynamically in time according to probability laws following from successive applications of the Born law. It is a collapse theory. The quantum/classical distinction is determined by the arrow of time. The underlying unitary evolution of the wave-function of the universe enables the designation of a collection of beables which grows as time evolves, and which therefore can be assigned random, classical trajectories. In a slogan: the past is particles, the future is a wave. We, living in the now, are located on the cutting edge between past and future.

A micro-CT-based standard brain atlas of the bumblebee.

In recent years, bumblebees have become a prominent insect model organism for a variety of biological disciplines, particularly to investigate learning behaviors as well as visual performance. Understanding these behaviors and their underlying neurobiological principles requires a clear understanding of brain anatomy. Furthermore, to be able to compare neuronal branching patterns across individuals, a common framework is required, which has led to the development of 3D standard brain atlases in most of the neurobiological insect model species. Yet, no bumblebee 3D standard brain atlas has been generated. Here we present a brain atlas for the buff-tailed bumblebee Bombus terrestris using micro-computed tomography (micro-CT) scans as a source for the raw data sets, rather than traditional confocal microscopy, to produce the first ever micro-CT-based insect brain atlas. We illustrate the advantages of the micro-CT technique, namely, identical native resolution in the three cardinal planes and 3D structure being better preserved. Our Bombus terrestris brain atlas consists of 30 neuropils reconstructed from ten individual worker bees, with micro-CT allowing us to segment neuropils completely intact, including the lamina, which is a tissue structure often damaged when dissecting for immunolabeling. Our brain atlas can serve as a platform to facilitate future neuroscience studies in bumblebees and illustrates the advantages of micro-CT for specific applications in insect neuroanatomy.

Correction: Gill, R.D. Does Geometric Algebra Provide a Loophole to Bell's Theorem? Entropy 2020, 22, 61.

Corrections are made to my paper "Gill, R.D. Does Geometric Algebra Provide a Loophole to Bell's Theorem? Entropy 2020, 22, 61" [...].

Insecticide exposure during brood or early-adult development reduces brain growth and impairs adult learning in bumblebees.

For social bees, an understudied step in evaluating pesticide risk is how contaminated food entering colonies affects residing offspring development and maturation. For instance, neurotoxic insecticide compounds in food could affect central nervous system development predisposing individuals to become poorer task performers later-in-life. Studying bumblebee colonies provisioned with neonicotinoid spiked nectar substitute, we measured brain volume and learning behaviour of 3 or 12-day old adults that had experienced in-hive exposure during brood and/or early-stage adult development. Micro-computed tomography scanning and segmentation of multiple brain neuropils showed exposure during either of the developmental stages caused reduced mushroom body calycal growth relative to unexposed workers. Associated with this was a lower probability of responding to a sucrose reward and lower learning performance in an olfactory conditioning test. While calycal volume of control workers positively correlated with learning score, this relationship was absent for exposed workers indicating neuropil functional impairment. Comparison of 3- and 12-day adults exposed during brood development showed a similar degree of reduced calycal volume and impaired behaviour highlighting lasting and irrecoverable effects from exposure despite no adult exposure. Our findings help explain how the onset of pesticide exposure to whole colonies can lead to lag-effects on growth and resultant dysfunction.

Fire, rodent herbivory, and plant competition: implications for invasion and altered fire regimes in the Mojave Desert.

Biological invasions are responsive to changing wildfire regimes related to human activities that are altering biological communities. Our objective was to investigate how fire, rodent activity, and competition among plant species modify plant community structure, invasion patterns, and vulnerability to altered fire regimes. We imposed experimental fires, and reduced rodent density using fencing in a full factorial design and quantified competitive interactions among plant species in the northeast Mojave Desert that has experienced dramatic increases in plant invasion and fire in recent years. Vegetation surveys were conducted in the experimental plots to determine plant density, cover, and biomass of herbaceous plants over a 5-year period. Rodent exclusion increased the density, cover, and biomass of Bromus rubens, an invasive annual grass, and density of forb species. In contrast, rodent exclusion decreased the density, cover, and biomass of Schismus spp. another dominant annual invader. Fire increased Schismus spp. and forb species density, cover, and biomass but decreased B. rubens density. Negative spatial correlation between B. rubens and Schismus spp., and forbs indicated interspecific competition among the dominant plant species. Fire reduced rodent community diversity (Shannon's) 2.5-fold, which was correlated with increases in B. rubens cover and biomass, and native forb diversity. Fire, high rodent diversity, and competition from the other plant species may decrease fire potential in our study system by reducing the density and biomass of B. rubens, which because of its taller growth form tends to ignite and carry fire better than Schismus spp. and forbs.

Seasonal and individual event-responsiveness are key determinants of carbon exchange across plant functional types.

Differentiation in physiological activity is a critical component of resource partitioning in resource-limited environments. For example, it is crucial to understand how plant physiological performance varies through time for different functional groups to forecast how terrestrial ecosystems will respond to change. Here, we tracked the seasonal progress of 13 plant species representing C3 shrub, perennial C3 and C4 grass, and annual forb functional groups of the Colorado Plateau, USA. We tested for differences in carbon assimilation strategies and how photosynthetic rates related to recent, seasonal, and annual precipitation and temperature variables. Despite seasonal shifts in species presence and activity, we found small differences in seasonally weighted annual photosynthetic rates among groups. However, differences in the timing of maximum assimilation (Anet) were strongly functional group-dependent. C3 shrubs employed a relatively consistent, low carbon capture strategy and maintained activity year-round but switched to a rapid growth strategy in response to recent climate conditions. In contrast, grasses maintained higher carbon capture during spring months when all perennials had maximum photosynthetic rates, but grasses were dormant during months when shrubs remained active. Perennial grass Anet rates were explained in part by precipitation accumulated during the preceding year and average maximum temperatures during the past 48 h, a result opposite to shrubs. These results lend insight into diverse physiological strategies and their connections to climate, and also point to the potential for shrubs to increase in abundance in response to increased climatic variability in drylands, given shrubs' ability to respond rapidly to changing conditions.

The Triangle Wave Versus the Cosine: How Classical Systems Can Optimally Approximate EPR-B Correlations.

The famous singlet correlations of a composite quantum system consisting of two two-level components in the singlet state exhibit notable features of two kinds. One kind are striking certainty relations: perfect anti-correlation, and perfect correlation, under certain joint settings. The other kind are a number of symmetries, namely invariance under a common rotation of the settings, invariance under exchange of components, and invariance under exchange of both measurement outcomes. One might like to restrict attention to rotations in the plane since those are the ones most commonly investigated experimentally. One can then also further distinguish between the case of discrete rotations (e.g., only settings which are a whole number of degrees are allowed) and continuous rotations. We study the class of classical correlation functions, i.e., generated by classical physical systems, satisfying all these symmetries, in the continuous, planar, case. We call such correlation functions classical EPR-B correlations. It turns out that if the certainty relations and rotational symmetry holds at the level of the correlations, then rotational symmetry can be imposed "for free" on the underlying classical physical model by adding an extra randomisation level. The other binary symmetries are obtained "for free". This leads to a simple heuristic description of all possible classical EPR-B correlations in terms of a "spinning bi-coloured disk" model. We deliberately use the word "heuristic" because technical mathematical problems remain wide open concerning the transition from finite or discrete to continuous. The main purpose of this paper is to bring this situation to the attention of the mathematical community. We do show that the widespread idea that "quantum correlations are more extreme than classical physics would allow" is at best highly inaccurate, through giving a concrete example of a classical correlation which satisfies all the symmetries and all the certainty relations and which exceeds the quantum correlations over a whole range of settings. It is found by a search procedure in which we randomly generate classical physical models and, for each generated model, evaluate its properties in a further Monte-Carlo simulation of the model itself.

A Nonparametric Bayesian Approach to the Rare Type Match Problem.

The "rare type match problem" is the situation in which, in a criminal case, the suspect's DNA profile, matching the DNA profile of the crime stain, is not in the database of reference. Ideally, the evaluation of this observed match in the light of the two competing hypotheses (the crime stain has been left by the suspect or by another person) should be based on the calculation of the likelihood ratio and depends on the population proportions of the DNA profiles that are unknown. We propose a Bayesian nonparametric method that uses a two-parameter Poisson Dirichlet distribution as a prior over the ranked population proportions and discards the information about the names of the different DNA profiles. This model is validated using data coming from European Y-STR DNA profiles, and the calculation of the likelihood ratio becomes quite simple thanks to an Empirical Bayes approach for which we provided a motivation.

Functional genomic characterization of the FTO locus in African Americans.

BACKGROUND: SNPs in the first intron of the fat mass and obesity-associated (FTO) gene represent the strongest genome-wide associations with adiposity [body mass index (BMI)]; the molecular basis for these associations is under intense investigation. In European populations, the focus of most genome-wide association studies conducted to date, the single nucleotide polymorphisms (SNPs) have indistinguishable associations due to the high level of linkage disequilibrium (LD). However, in African American (AA) individuals, reduced LD and increased haplotype diversity permit finer distinctions among obesity-associated SNPs. Such distinctions are important to mechanistic inferences and for selection of disease SNPs relevant to specific populations. METHODS: To identify specific FTO SNP(s) directly related to adiposity, we performed: 1) haplotype analyses of individual-level data in 3,335 AAs from the Atherosclerosis Risk in Communities Cohort (ARIC) study; as well as 2) statistical fine-mapping using summary statistics from a study of FTO in over 20 000 AAs and over 1000 functional genomic annotations. RESULTS: Our haplotype analyses suggest that in AAs at least two distinct signals underlie the intron 1 FTO-adiposity signal. Fine mapping showed that two SNPs have the highest posterior probability of association (PPA) with BMI: rs9927317 (PPA = 0.94) and rs62033405 (PPA = 0.99). These variants overlap possible enhancer sites and the 5'-regions of transcribed genes in the substantia nigra, chondrocytes, and white adipocytes. CONCLUSIONS: We found two SNPs in FTO with the highest probability of direct association with BMI in AAs, as well as tissue-specific mechanisms by which these variants may contribute to the pathogenesis of obesity.

CO2 enrichment and soil type additively regulate grassland productivity.

Atmospheric CO2 enrichment usually increases the aboveground net primary productivity (ANPP) of grassland vegetation, but the magnitude of the ANPP-CO2 response differs among ecosystems. Soil properties affect ANPP via multiple mechanisms and vary over topographic to geographic gradients, but have received little attention as potential modifiers of the ANPP-CO2 response. We assessed the effects of three soil types, sandy loam, silty clay and clay, on the ANPP response of perennial C3 /C4 grassland communities to a subambient to elevated CO2 gradient over 10 yr in Texas, USA. We predicted an interactive, rather than additive, effect of CO2 and soil type on ANPP. Contrary to prediction, CO2 and soil additively influenced grassland ANPP. Increasing CO2 by 250 µl l-1 increased ANPP by 170 g m-2 across soil types. Increased clay content from 10% to 50% among soils reduced ANPP by 50 g m-2 . CO2 enrichment increased ANPP via a predominant direct effect, accompanied by a smaller indirect effect mediated by a successional shift to increased dominance of the C4 tallgrass Sorghastrum nutans. Our results indicate a large, positive influence of CO2 enrichment on grassland productivity that resulted from the direct physiological benefits of CO2 augmented by species succession, and was expressed similarly across soils of differing physical properties.

Caste- and pesticide-specific effects of neonicotinoid pesticide exposure on gene expression in bumblebees.

Social bees are important insect pollinators of wildflowers and agricultural crops, making their reported declines a global concern. A major factor implicated in these declines is the widespread use of neonicotinoid pesticides. Indeed, recent research has demonstrated that exposure to low doses of these neurotoxic pesticides impairs bee behaviours important for colony function and survival. However, our understanding of the molecular-genetic pathways that lead to such effects is limited, as is our knowledge of how effects may differ between colony members. To understand what genes and pathways are affected by exposure of bumblebee workers and queens to neonicotinoid pesticides, we implemented a transcriptome-wide gene expression study. We chronically exposed Bombus terrestriscolonies to either clothianidin or imidacloprid at field-realistic concentrations while controlling for factors including colony social environment and worker age. We reveal that genes involved in important biological processes including mitochondrial function are differentially expressed in response to neonicotinoid exposure. Additionally, clothianidin exposure had stronger effects on gene expression amplitude and alternative splicing than imidacloprid. Finally, exposure affected workers more strongly than queens. Our work demonstrates how RNA-Seq transcriptome profiling can provide detailed novel insight on the mechanisms mediating pesticide toxicity to a key insect pollinator.