Search

Peer reviewed: True, This paper reviews the modern state of the Wiener-Hopf factorization method and its generalizations. The main constructive results for matrix Wiener-Hopf problems are presented, approximate methods are outlined and the main areas of applications are mentioned. The aim of the paper is to offer an overview of the development of this method, and demonstrate the importance of bringing together pure and applied analysis to effectively employ the Wiener-Hopf technique.

Seminal fluid proteins (Sfps) modify female phenotypes and have wide-ranging evolutionary implications on fitness in many insects. However, in the Mexican fruit fly, Anastrepha ludens , a highly destructive agricultural pest, the functions of Sfps are still largely unknown. To gain insights into female phenotypes regulated by Sfps, we used nano-liquid chromatography mass spectrometry to conduct a proteomic analysis of the soluble proteins from reproductive organs of A. ludens . The proteins predicted to be transferred from males to females during copulation were 100 proteins from the accessory glands, 69 from the testes and 20 from the ejaculatory bulb, resulting in 141 unique proteins after accounting for redundancies from multiple tissues. These 141 included orthologues to Drosophila melanogaster proteins involved mainly in oogenesis, spermatogenesis, immune response, lifespan and fecundity. In particular, we found one protein associated with female olfactory response to repellent stimuli (Scribble), and two related to memory formation (aPKC and Shibire). Together, these results raise the possibility that A. ludens Sfps could play a role in regulating female olfactory responses and memory formation and could be indicative of novel evolutionary functions in this important agricultural pest.

An organism's gut microbiome can alter its fitness, yet we do not know how gut microbiomes change as their hosts evolve in the wild. We took advantage of a five-decade ‘chronosequence’ of translocated fish populations to examine associated changes in the gut microbiome. Populations of Trinidadian guppies have displayed parallel phenotypic convergence six times when moved from high predation (HP) to low predation (LP) environments. Across four drainages, we found microbiomes of fish translocated 5–6 years prior to sampling were already distinct from the microbiomes of their HP source populations. Changes in environmental conditions were most important in driving this shift, followed by phenotypic shifts in gut morphology. After 30–60 years in LP environments, microbiome composition was still distinct from native LP populations, but microbiome function was not. We found some evidence that nitrogen fixation enhanced gut nutrient absorption, but most functional shifts were not parallel across drainages. Stream-and drainage-specific signatures were present for both composition and function, despite our overall finding of consistent microbiome change across drainages. As we unravel the complexities of host–microbiome evolution in the wild, studies should consider environmental microbial colonization, host phenotypic plasticity in nature, and more realistic environmental conditions excluded from laboratory studies.

Rapid exaggeration of host and pathogen traits via arms race dynamics is one possible outcome of host–pathogen coevolution. However, the exaggerated traits are expected to incur costs in terms of resource investment in other life-history traits. The current study investigated the costs associated with evolved traits in a host–pathogen coevolution system. We used the Drosophila melanogaster (host) –Pseudomonas entomophila (pathogen) system to experimentally derive two selection regimes, one where the host and pathogen both coevolved, and the other, where only the host evolved against a non-evolving pathogen. After 17 generations of selection, we found that hosts from both selected populations had better post-infection survivorship than controls. Even though the coevolving populations tended to have better survivorship post-infection, we found no clear evidence that the two selection regimes were significantly different from each other. There was weak evidence for the coevolving pathogens being more virulent than the ancestral pathogen. We found no major cost of increased post-infection survivorship. The costs were not different between the coevolving hosts and the hosts evolving against a non-evolving pathogen. We found no evolved costs in the coevolving pathogens. Thus, our results suggest that increased host immunity and pathogen virulence may not be costly.

Parallelism between evolutionary trajectories in a trait space is often seen as evidence for repeatability of phenotypic evolution, and angles between trajectories play a pivotal role in the analysis of parallelism. However, properties of angles in multidimensional spaces have not been widely appreciated by biologists. To remedy this situation, this study provides a brief overview on geometric and statistical aspects of angles in multidimensional spaces. Under the null hypothesis that trajectory vectors have no preferred directions (i.e. uniform distribution on hypersphere), the angle between two independent vectors is concentrated around the right angle, with a more pronounced peak in a higher-dimensional space. This probability distribution is closely related to t - and beta distributions, which can be used for testing the null hypothesis concerning a pair of trajectories. A recently proposed method with eigenanalysis of a vector correlation matrix can be connected to the test of no correlation or concentration of multiple vectors, for which simple test procedures are available in the statistical literature. Concentration of vectors can also be examined by tools of directional statistics such as the Rayleigh test. These frameworks provide biologists with baselines to make statistically justified inferences for (non)parallel evolution.

Changes in the abundances of animals, such as with the ongoing concern about insect declines, are often assumed to be general across taxa. However, this assumption is largely untested. Here, we used a database of assemblage-wide long-term insect and arachnid monitoring to compare abundance trends among co-occurring pairs of taxa. We show that 60% of co-occurring taxa qualitatively showed long-term trends in the same direction—either both increasing or both decreasing. However, in terms of magnitude, temporal trends were only weakly correlated (mean freshwater r = 0.05 (±0.03), mean terrestrial r = 0.12 (±0.09)). The strongest correlation was between trends of beetles and those of moths/butterflies ( r = 0.26). Overall, even though there is some support for directional similarity in temporal trends, we find that changes in the abundance of one taxon provide little information on the changes of other taxa. No clear candidate for umbrella or indicator taxa emerged from our analysis. We conclude that obtaining a better picture of changes in insect abundances will require monitoring of multiple taxa, which remains uncommon, especially in the terrestrial realm.

As climate change threatens species' persistence, predicting the potential for species to adapt to rapidly changing environments is imperative for the development of effective conservation strategies. Eco-evolutionary individual-based models (IBMs) can be useful tools for achieving this objective. We performed a literature review to identify studies that apply these tools in marine systems. Our survey suggested that this is an emerging area of research fuelled in part by developments in modelling frameworks that allow simulation of increasingly complex ecological, genetic and demographic processes. The studies we identified illustrate the promise of this approach and advance our understanding of the capacity for adaptation to outpace climate change. These studies also identify limitations of current models and opportunities for further development. We discuss three main topics that emerged across studies: (i) effects of genetic architecture and non-genetic responses on adaptive potential; (ii) capacity for gene flow to facilitate rapid adaptation; and (iii) impacts of multiple stressors on persistence. Finally, we demonstrate the approach using simple simulations and provide a framework for users to explore eco-evolutionary IBMs as tools for understanding adaptation in changing seas.

Quadrupeds exhibit versatile and adaptive running by exploiting the flying phase during the stride cycle. Various interlimb coordination mechanisms focusing on mechanical loads during the stance phase have been proposed to understand the underlying control mechanism, and various gait patterns have been reproduced. However, the essential control mechanism required to achieve both steady running patterns and non-steady behaviours, such as jumping and landing, remains unclear. Therefore, we focus on the vertical motions of the body parts and propose a new decentralized interlimb coordination mechanism. The simulation results demonstrate that the robot can generate efficient and various running patterns in response to the morphology of the body. Furthermore, the proposed model allows the robot to smoothly change its behaviour between steady running and non-steady landing depending on the situation. These results suggest that the steady and non-steady behaviours in quadruped adaptive running may share a common simple control mechanism based on the mechanical loads and vertical velocities of the body parts.

Selection component analyses (SCA) relate individual genotype to fitness components such as viability, fecundity and mating success. SCA are based on population genetic models and yield selection estimates directly in terms of predicted allele frequency change. This paper explores the statistical properties of gSCA: experiments that apply SCA to genome-wide scoring of SNPs in field sampled individuals. Computer simulations indicate that gSCA involving a few thousand genotyped samples can detect allele frequency changes of the magnitude that has been documented in field experiments on diverse taxa. To detect selection, imprecise genotyping from low-level sequencing of large samples of individuals provides much greater power than precise genotyping of smaller samples. The simulations also demonstrate the efficacy of ‘haplotype matching’, a method to combine information from a limited collection of whole genome sequence (the reference panel) with the much larger sample of field individuals that are measured for fitness. Pooled sequencing is demonstrated as another way to increase statistical power. Finally, I discuss the interpretation of selection estimates in relation to the Beavis effect, the overestimation of selection intensities at significant loci.

Peer reviewed: True, This paper reviews the modern state of the Wiener–Hopf factorization method and its generalizations. The main constructive results for matrix Wiener–Hopf problems are presented, approximate methods are outlined and the main areas of applications are mentioned. The aim of the paper is to offer an overview of the development of this method, and demonstrate the importance of bringing together pure and applied analysis to effectively employ the Wiener–Hopf technique.

In evolutionary quantitative genetics, the genetic variance–covariance matrix, G , and the vector of directional selection gradients, β , are key parameters for predicting multivariate selection responses and genetic constraints. Historically, investigations of G and β have not overlapped with those dissecting the genetic basis of quantitative traits. Thus, it remains unknown whether these parameters reflect pleiotropic effects at individual loci. Here, we integrate multivariate genome-wide association study (GWAS) with G and β estimation in a well-studied system of multivariate constraint: sexual selection on male cuticular hydrocarbons (CHCs) in Drosophila serrata . In a panel of wild-derived re-sequenced lines, we augment genome-based restricted maximum likelihood to estimate G alongside multivariate single nucleotide polymorphism (SNP) effects, detecting 532 significant associations from 1 652 276 SNPs. Constraint was evident, with β lying in a direction of G with low evolvability. Interestingly, minor frequency alleles typically increased male CHC-attractiveness suggesting opposing natural selection on β . SNP effects were significantly misaligned with the major eigenvector of G , g max , but well aligned to the second and third eigenvectors g 2 and g 3 . We discuss potential factors leading to these varied results including multivariate stabilizing selection and mutational bias. Our framework may be useful as researchers increasingly access genomic methods to study multivariate selection responses in wild populations.

We combined participatory science data and museum records to understand long-term changes in occupancy for 29 ant species in Denmark over 119 years. Bayesian occupancy modelling indicated change in occupancy for 15 species: five increased, four declined and six showed fluctuating trends. We consider how trends may have been influenced by life-history and habitat changes. Our results build on an emerging picture that biodiversity change in insects is more complex than implied by the simple insect decline narrative.

Understanding how evolutionary forces interact to drive patterns of selection and distribute genetic variation across a species' range is of great interest in ecology and evolution, especially in an era of global change. While theory predicts how and when populations at range margins are likely to undergo local adaptation, empirical evidence testing these models remains sparse. Here, we address this knowledge gap by investigating the relationship between selection, gene flow and genetic drift in the yellowtail clownfish, Amphiprion clarkii, from the core to the northern periphery of the species range. Analyses reveal low genetic diversity at the range edge, gene flow from the core to the edge and genomic signatures of local adaptation at 56 single nucleotide polymorphisms in 25 candidate genes, most of which are significantly correlated with minimum annual sea surface temperature. Several of these candidate genes play a role in functions that are upregulated during cold stress, including protein turnover, metabolism and translation. Our results illustrate how spatially divergent selection spanning the range core to the periphery can occur despite the potential for strong genetic drift at the range edge and moderate gene flow from the core populations.

Genome-wide association studies provide good opportunities for studying the genetic basis of adaptive traits in wild populations. Yet, previous studies often failed to identify major effect genes. In this study, we used high-density single nucleotide polymorphism and individual fitness data from a wild non-model species. Using a whole-genome approach, we identified the MC1R gene as the sole causal gene underlying Arctic fox Vulpes lagopus fur colour. Further, we showed the adaptive importance of fur colour genotypes through measures of fitness that link ecological and evolutionary processes. We found a tendency for blue foxes that are heterozygous at the fur colour locus to have higher fitness than homozygous white foxes. The effect of genotype on fitness was independent of winter duration but varied with prey availability, with the strongest effect in years of increasing rodent populations. MC1R is located in a genomic region with high gene density, and we discuss the potential for indirect selection through linkage and pleiotropy. Our study shows that whole-genome analyses can be successfully applied to wild species and identify major effect genes underlying adaptive traits. Furthermore, we show how this approach can be used to identify knowledge gaps in our understanding of interactions between ecology and evolution.

Based on a 4 × 4 matrix spectral problem, a super Degasperis–Procesi (DP) equation is proposed. We show that under a reciprocal transformation, the super DP equation is related to the first negative flow of a super Kaup–Kupershmidt (KK) hierarchy, which turns out to be a particular reduction of a super Boussinesq hierarchy. The bi-Hamiltonian structure of the super Boussinesq hierarchy is established and subsequently produces a Hamiltonian structure, as well as a conjectured symplectic formulation of the super KK hierarchy via suitable reductions. With the help of the reciprocal transformation, the bi-Hamiltonian representation of the super DP equation is constructed from that of the super KK hierarchy. We also calculate a positive flow of the super DP hierarchy and explain its relations with the super KK equation. Infinitely many conservation laws are derived for the super DP equation, as well as its positive flow.

Recently, it has been found that JT gravity, which is a two-dimensional theory with bulk action $ -\frac{1}{2}\int {\mathrm d}^2x \sqrt g\phi(R+2)$, is dual to a matrix model, that is, a random ensemble of quantum systems rather than a specific quantum mechanical system. In this article, we argue that a deformation of JT gravity with bulk action $ -\frac{1}{2}\int {\mathrm d}^2x \sqrt g(\phi R+W(\phi))$ is likewise dual to a matrix model. With a specific procedure for defining the path integral of the theory, we determine the density of eigenvalues of the dual matrix model. There is a simple answer if $W(0)=0$, and otherwise a rather complicated answer., Comment: 37 pp

Classical field theory is about fields and how they behave in space–time. Quantum field theory, in practice, usually seems to be about particles and how they scatter. Nevertheless, classical fields must emerge from quantum field theory in appropriate limits, and Michael Duff showed how this happens for the Schwarzschild solution in perturbative quantum gravity. In a series of papers, we and others have shown how classical radiation from an accelerated charge emerges from quantum field theory when the Unruh thermal effect is taken into account. Here, we sharpen those conclusions by showing that, even at finite times, the quantum picture is meaningful and is in close agreement with the classical picture.

We introduce and study a new canonical integral, denoted I + − ε , depending on two complex parameters α 1 and α 2 . It arises from the problem of wave diffraction by a quarter-plane and is heuristically constructed to capture the complex field near the tip and edges. We establish some region of analyticity of this integral in C 2 , and derive its rich asymptotic behaviour as | α 1 | and | α 2 | tend to infinity. We also study the decay properties of the function obtained from applying a specific double Cauchy integral operator to this integral. These results allow us to show that this integral shares all of the asymptotic properties expected from the key unknown function G +− arising when the quarter-plane diffraction problem is studied via a two-complex-variables Wiener–Hopf technique (see Assier & Abrahams, SIAM J. Appl. Math. , in press). As a result, the integral I + − ε can be used to mimic the unknown function G +− and to build an efficient ‘educated’ approximation to the quarter-plane problem.

Wireless connectivity is no longer limited to facilitating communications between individuals, but is also required to support diverse and heterogeneous applications, services and infrastructures. Internet of things (IoT) systems will dominate future technologies, allowing any and all devices to create, share and process data. If artificial intelligence resembles the brain of IoT, then high-speed connectivity forms the nervous system that connects the devices. For IoT to safely operate autonomously, it requires highly secure and reliable wireless links. In this article, we shed light on the potential of optical wireless communications to provide high-speed secure and reliable ubiquitous access as an enabler for fifth generation and beyond wireless networks.

Sequencing technologies have fuelled a rapid rise in descriptions of microbial communities associated with hosts, but what is often harder to ascertain is the evolutionary significance of these symbioses. Here, we review the role of vertical (VT), horizontal (HT), environmental acquisition and mixed modes of transmission (MMT), in the establishment of animal host–microbe associations. We then model four properties of gut microbiota proposed as key to promoting animal host–microbe relationships: modes of transmission, host reproductive mode, host mate choice and host fitness. We found that: (i) MMT led to the highest frequencies of host–microbe associations, and that some environmental acquisition or HT of microbes was required for persistent associations to form unless VT was perfect; (ii) host reproductive mode (sexual versus asexual) and host mate choice (for microbe carriers versus non-carriers) had little impact on the establishment of host–microbe associations; (iii) host mate choice did not itself lead to reproductive isolation, but could reinforce it; and (iv) changes in host fitness due to host–microbe associations had a minimal impact upon the formation of co-associations. When we introduced a second population, into which host–microbe carriers could disperse but in which environmental acquisition did not occur, highly efficient VT was required for host–microbe co-associations to persist. Our study reveals that transmission mode is of key importance in establishing host–microbe associations.

The Event Horizon Telescope (EHT) is expected to soon produce polarimetric images of the supermassive black hole at the center of the neighboring galaxy M87. There are indications that this black hole is rapidly spinning. General relativity predicts that such a high-spin black hole has an emergent conformal symmetry near its event horizon. In this paper, we use this symmetry to analytically predict the polarized near-horizon emissions to be seen at the EHT and find a distinctive pattern of whorls aligned with the spin., Comment: 21 pages, 2 figures. v2: fixed conventions, matches published version

The possible instability of partial indices is one of the important constraints in the creation of approximate methods for the factorization of matrix functions. This paper is devoted to a study of a specific class of triangular matrix functions given on the unit circle with a stable and unstable set of partial indices. Exact conditions are derived that guarantee a preservation of the unstable set of partial indices during a perturbation of a matrix within the class. Thus, even in this probably simplest of cases, when the factorization technique is well developed, the structure of the parametric space (guiding the types of matrix perturbations) is non-trivial.

Understanding de Sitter space in supergravity - and string theory - has lead to an intense amount of work for more than two decades, largely motivated by the discovery of the accelerated expansion of the universe in 1998. In this paper, we consider a non-trivial generalisation of unimodular gravity to minimal N = 1 supergravity, which allows for de Sitter solutions without the need of introducing any matter. We formulate a superspace version of the Stuckelberg procedure, which restores diffeomorphism and local supersymmetry invariance. This introduces the goldstino associated to spontaneous breaking of supersymmetry in a natural way. The cosmological constant and gravitino mass are related to the vacuum expectation value of the components of a Lagrange multiplier imposing a super-unimodularity condition., 11 pages, version published in PRSA

We investigate a model which shows how the introduction of a perturbing dielectric close to an electromagnetic surface wave leads to radiation away from the surface through the dielectric. This resembles a surface waveguide passing through a wall or being deployed underground. Our theory, which is based on the mode-matching technique, allows quantitative determination of losses from a bound surface wave mode up to the point of its complete extinction. For a surface wave supported by a coated, conducting sheet the attenuation due to the perturbing dielectric is calculated for a number of frequencies, permittivities of the perturbation and separations between the sheet and the perturbing dielectric. The accuracy of our results is verified by simulation of the system with a full-wave numerical solution. Finally, we report experimental data of perturbed surface waves on a cable, which are in qualitative agreement with our model.

The strong-field limit for the 2-form potential on an M5-brane yields a conformal chiral 2-form electrodynamics in six dimensions, with gauge-invariant self-interactions but no adjustable coupling constant; the stress tensor is that of a null fluid. Lorentz invariance can be made manifest via an interpretation as a tensionless `space-filling M5-brane', or as a truncation of the infra-red dynamics of an M5-brane in AdS7 x S4., Comment: 31 pages. Additional minor corrections and an additional reference in V3

We introduce a new methodology to analyze the evolution of epidemic time series, which is based on the construction of epidemic networks. First, we translate the time series into ordinal patterns containing information about local fluctuations of the disease prevalence. Each pattern is associated to a node of a network, whose (directed) connections arise from consecutive appearances in the series. The analysis of the network structure and the role of each pattern, allows classifying them according to the enhancement of entropy/complexity along the series, giving a different point of view about the evolution of a given disease., 20 pages, 10 figures

Ecosystem dynamics are driven by both biotic and abiotic processes, and perturbations can push ecosystems into novel dynamical regimes. Plant–plant, plant–soil and mycorrhizal associations all affect plant ecosystem dynamics; however, the direction and magnitude of these effects vary by context and their contribution to ecosystem resilience over long time periods remains unknown. Here, using a mathematical framework, we investigate the effects of plant feedbacks and mycorrhiza on plant–nutrient interactions. We show evidence for strong nutrient controlled feedbacks, moderation by mycorrhiza and influence on ecological resilience. We use this model to investigate the resilience of a longitudinal palaeoecological birch– δ 15 N interaction to plant–soil feedbacks and mycorrhizal associations. The birch– δ 15 N system demonstrated high levels of resilience. Mycorrhiza were predicted to increase resilience by supporting plant–nitrogen uptake and immobilizing excess nitrogen; in contrast, long-term enrichment in available nitrogen by plant–soil feedbacks is expected to decrease ecological resilience.

Technological advancements in robotic devices have the potential to transform human mobility through gait assistance. However, the integration of physical hardware and software control algorithms with users to assist with impaired gait poses several challenges, such as allowing the user to adopt a variety of gaits and the process for evaluating the efficacy and performance of these assistive devices. Here, I discuss some of the challenges in the development of assistive devices and the use of biomechanical concepts and tools for control and test validation. Several potential solutions are proposed through the case study of one project that aimed to provide gait assistance for individuals with a spinal cord injury. Further challenges and future directions are discussed, with emphasis that diverse perspectives and approaches in gait assistance will accelerate engineering solutions towards regaining mobility.

Populations within species often exhibit variation in traits that reflect local adaptation and further shape existing adaptive potential for species to respond to climate change. However, our mechanistic understanding of how the environment shapes trait variation remains poor. Here, we used common garden experiments to quantify thermal performance in eight populations of the marine snailUrosalpinx cinereaacross thermal gradients on the Atlantic and the Pacific coasts of North America. We then evaluated the relationship between thermal performance and environmental metrics derived from time-series data. Our results reveal a novel pattern of ‘mixed’ trait performance adaptation, where thermal optima were positively correlated with spawning temperature (cogradient variation), while maximum trait performance was negatively correlated with season length (countergradient variation). This counterintuitive pattern probably arises because of phenological shifts in the spawning season, whereby ‘cold’ populations delay spawning until later in the year when temperatures are warmer compared to ‘warm’ populations that spawn earlier in the year when temperatures are cooler. Our results show that variation in thermal performance can be shaped by multiple facets of the environment and are linked to organismal phenology and natural history. Understanding the impacts of climate change on organisms, therefore, requires the knowledge of how climate change will alter different aspects of the thermal environment.

Recent statements by United Nations bodies point to free, prior and informed consent (FPIC) as a potential requirement in the development of engineered gene drive applications. As a concept developed in the context of protecting Indigenous rights to self-determination in land development scenarios, FPIC would need to be extended to apply to the context of ecological editing. Without an explicit framework of application, FPIC could be interpreted as a narrowly framed process of community consultation focused on the social implications of technology, and award little formal or advisory power in decision-making to Indigenous peoples and local communities. In this paper, we argue for an articulation of FPIC that attends to issues of transparency, iterative community-scale consent, and shared power through co-development among Indigenous peoples, local communities, researchers and technology developers. In realizing a comprehensive FPIC process, researchers and developers have an opportunity to incorporate enhanced participation and social guidance mechanisms into the design, development and implementation of engineered gene drive applications.

Recent genomic and metagenomic studies have highlighted the presence of rapidly evolving microbial populations in the human gut. However, despite the fundamental implications of this intuitive finding for both basic and applied gut microbiome research, very little is known about the mode, tempo and potential functional consequences of microbial evolution in the guts of individual human hosts over a lifetime. Here I assess the potential relevance of ecological opportunity to bacterial adaptation, colonization and persistence in the neonate and germ-free mammalian gut environment as well as over the course of an individual lifetime using data emerging from mouse models as well as human studies to provide examples where possible. I then briefly outline how the continued development and application of experimental evolution approaches coupled to genomic and metagenomic analysis is essential to disentangling drift from selection and identifying specific drivers of evolution in the gut microbiome within and between individual human hosts and populations.

Gene drive is a natural process of biased inheritance that, in principle, could be used to control pest and vector populations. As with any form of pest control, attention should be paid to the possibility of resistance evolving. For nuclease-based gene drive aimed at suppressing a population, resistance could arise by changes in the target sequence that maintain function, and various strategies have been proposed to reduce the likelihood that such alleles arise. Even if these strategies are successful, it is almost inevitable that alleles will arise at the target site that are resistant to the drive but do not restore function, and the impact of such sequences on the dynamics of control has been little studied. We use population genetic modelling of a strategy targeting a female fertility gene to demonstrate that such alleles may be expected to accumulate, and thereby reduce the reproductive load on the population, if nuclease expression per se causes substantial heterozygote fitness effects or if parental (especially paternal) deposition of nuclease either reduces offspring fitness or affects the genotype of their germline. All these phenomena have been observed in synthetic drive constructs. It will, therefore, be important to allow for non-functional resistance alleles in predicting the dynamics of constructs in cage populations and the impacts of any field release.

Plant species, populations and communities are under threat from climate change, invasive pathogens, weeds and habitat fragmentation. Despite considerable research effort invested in genome engineering for crop improvement, the development of genetic tools for the management of wild plant populations has rarely been given detailed consideration. Gene drive systems that allow direct genetic management of plant populations via the spread of fitness-altering genetic modifications could be of great utility. However, despite the rapid development of synthetic tools and their enormous promise, little explicit consideration has been given to their application in plants and, to date, they remain untested. This article considers the potential utility of gene drives for the management of wild plant populations, and examines the factors that might influence the design, spread and efficacy of synthetic drives. To gain insight into optimal ways to design and deploy synthetic drive systems, we investigate the diversity of mechanisms underlying natural gene drives and their dynamics within plant populations and species. We also review potential approaches for engineering gene drives and discuss their potential application to plant genomes. We highlight the importance of considering the impact of plant life-history and genetic architecture on the dynamics of drive, investigate the potential for different types of resistance evolution, and touch on the ethical, regulatory and social challenges ahead.

Most organisms are constantly adapting to pathogens and parasites that exploit their host for their own benefit. Less studied, but perhaps more ubiquitous, are intragenomic parasites or selfish genetic elements. These include transposable elements, selfish B chromosomes and meiotic drivers that promote their own replication without regard to fitness effects on hosts. Therefore, intragenomic parasites are also a constant evolutionary pressure on hosts. Gamete-killing meiotic drive elements are often associated with large chromosomal inversions that reduce recombination between the drive and wild-type chromosomes. This reduced recombination is thought to reduce the efficacy of selection on the drive chromosome and allow for the accumulation of deleterious mutations. We tested whether gamete-killing meiotic drive chromosomes were associated with reduced immune defence against two bacterial pathogens in three species ofDrosophila. We found little evidence of reduced immune defence in lines with meiotic drive. One line carrying theDrosophila melanogasterautosomal Segregation Distorter did show reduced defence, but we were unable to attribute that reduced defence to either genotype or immune gene expression differences. Our results suggest that though gamete-killing meiotic drive chromosomes probably accumulate deleterious mutations, those mutations do not result in reduced capacity for immune defence.

House mice are a major ecosystem pest, particularly threatening island ecosystems as a non-native invasive species. Rapid advances in synthetic biology offer new avenues to control pest species for biodiversity conservation. Recently, a synthetic sperm-killing gene drive construct called t-Sry has been proposed as a means to eradicate target mouse populations owing to a lack of females. A factor that has received little attention in the discussion surrounding such drive applications is polyandry. Previous research has demonstrated that sperm-killing drivers are extremely damaging to a male’s sperm competitive ability. Here, we examine the importance of this effect on the t-Sry system using a theoretical model. We find that polyandry substantially hampers the spread of t-Sry such that release efforts have to be increased three- to sixfold for successful eradication. We discuss the implications of our finding for potential pest control programmes, the risk of drive spread beyond the target population, and the emergence of drive resistance. Our work highlights that a solid understanding of the forces that determine drive dynamics in a natural setting is key for successful drive application, and that exploring the natural diversity of gene drives may inform effective gene drive design.

Blue Carbon is a term coined in 2009 to draw attention to the degradation of marine and coastal ecosystems and the need to conserve and restore them to mitigate climate change and for the other ecosystem services they provide. Blue Carbon has multiple meanings, which we aim to clarify here, which reflect the original descriptions of the concept including (1) all organic matter captured by marine organisms, and (2) how marine ecosystems could be managed to reduce greenhouse gas emissions and thereby contribute to climate change mitigation and conservation. The multifaceted nature of the Blue Carbon concept has led to unprecedented collaboration across disciplines, where scientists, conservationists and policy makers have interacted intensely to advance shared goals. Some coastal ecosystems (mangroves, tidal marshes and seagrass) are established Blue Carbon ecosystems as they often have high carbon stocks, support long-term carbon storage, offer the potential to manage greenhouse gas emissions and support other adaptation policies. Some marine ecosystems do not meet key criteria for inclusion within the Blue Carbon framework (e.g. fish, bivalves and coral reefs). Others have gaps in scientific understanding of carbon stocks or greenhouse gas fluxes, or currently there is limited potential for management or accounting for carbon sequestration (macroalgae and phytoplankton), but may be considered Blue Carbon ecosystems in the future, once these gaps are addressed.

In dynamic systems, organisms are faced with variable selective forces that may impose trade-offs. In estuaries, salinity is a strong driver of organismal diversity, while parasites shape species distributions and demography. We tested for trade-offs between low-salinity stress and parasitism in an invasive castrating parasite and its mud crab host along salinity gradients of two North Carolina rivers. We performed field surveys every six to eight weeks over 3 years to determine factors influencing parasite prevalence, host abundance, and associated taxa diversity. We also looked for signatures of low-salinity stress in the host by examining its response (time-to-right and gene expression) to salinity. We found salinity and temperature significantly affected parasite prevalence, with low-salinity sites (less than 10 practical salinity units (PSU)) lacking infection, and populations in moderate salinities at warmer temperatures reaching prevalence as high as 60%. Host abundance was negatively associated with parasite prevalence. Host gene expression was plastic to acclimation salinity, but several osmoregulatory and immune-related genes demonstrated source-dependent salinity response. We identified a genetic marker that was strongly associated with salinity against a backdrop of no neutral genetic structure, suggesting possible selection on standing variation. Our study illuminates how selective trade-offs in naturally dynamic systems may shape host evolutionary ecology.

Insect abundance and diversity are declining worldwide. Although recent research found freshwater insect populations to be increasing in some regions, there is a critical lack of data from tropical and subtropical regions. Here, we examine a 20-year monitoring dataset of freshwater insects from a subtropical floodplain comprising a diverse suite of rivers, shallow lakes, channels and backwaters. We found a pervasive decline in abundance of all major insect orders (Odonata, Ephemeroptera, Trichoptera, Megaloptera, Coleoptera, Hemiptera and Diptera) and families, regardless of their functional role or body size. Similarly, Chironomidae species richness decreased over the same time period. The main drivers of this pervasive insect decline were increased concurrent invasions of non-native insectivorous fish, water transparency and changes to water stoichiometry (i.e. N : P ratios) over time. All these drivers represent human impacts caused by reservoir construction. This work sheds light on the importance of long-term studies for a deeper understanding of human-induced impacts on aquatic insects. We highlight that extended anthropogenic impact monitoring and mitigation actions are pivotal in maintaining freshwater ecosystem integrity.

Salinity conditions in oyster breeding grounds in the Gulf of Mexico are expected to drastically change due to increased precipitation from climate change and anthropogenic changes to local hydrology. We determined the capacity of the eastern oyster, Crassostrea virginica , to adapt via standing genetic variation or acclimate through transgenerational plasticity (TGP). We outplanted oysters to either a low- or medium-salinity site in Louisiana for 2 years. We then crossed adult parents using a North Carolina II breeding design, and measured body size and survival of larvae 5 dpf raised under low or ambient salinity. We found that TGP is unlikely to significantly contribute to low-salinity tolerance since we did not observe increased growth or survival in offspring reared in low salinity when their parents were also acclimated at a low-salinity site. However, we detected genetic variation for body size, with an estimated heritability of 0.68 ± 0.25 (95% CI). This suggests there is ample genetic variation for this trait to evolve, and that evolutionary adaptation is a possible mechanism through which oysters will persist with future declines in salinity. The results of this experiment provide valuable insights into successfully breeding low-salinity tolerance in this commercially important species.

We classify integrable Hamiltonian equations in 3D with the Hamiltonian operator d/dx, where the Hamiltonian density h(u, w) is a function of two variables: dependent variable u and the non-locality w such that w_x=u_y. Based on the method of hydrodynamic reductions, the integrability conditions are derived (in the form of an involutive PDE system for the Hamiltonian density h). We show that the generic integrable density is expressed in terms of the Weierstrass elliptic functions. Dispersionless Lax pairs, commuting flows and dispersive deformations of the resulting equations are also discussed., 23 pages

Despite the fact that infant gut colonization patterns have been extensively studied, we have limited knowledge about the underlying ecological processes. This particularly relates to the ecological choice of nutrient utilization strategies. The aim of the current study was therefore to compare empirically determined nutrient utilization strategies with that expected from a combinatorial game theory model. Observational analyses for 100 mother–child pairs suggested mother–child transmission of specialists with the potential to use few nutrients. Generalists, on the other hand, with the potential to use many nutrients, peaked at three months of age for the children. The level of generalists was gradually replaced with specialists up to 12 months of age. Game theory simulation revealed a competitive advantage of generalists in an expanding population, while more specialized bacteria were favoured with the maturation of the population. This suggests that the observed increase in generalists in the three-month-old children could be due to an immature, expanding gut microbiota population while the increase of specialists at 12 months could be due to population maturation. The simulated and empirical data also correspond with respect to an increased α diversity and a decreased β diversity with the number of simulations and age, respectively. Taken together, game theory simulation of nutrient utilization strategies can therefore provide novel insight into the maturation of the human gut microbiota during infancy.

In the work, we obtain an effective criterion of the stability of the partial indices for matrix polynomials under an arbitrary sufficiently small perturbation. Verification of the stability is reduced to calculation of the ranks for two explicitly defined Toeplitz matrices. Furthermore, we define a notion of the stability of the partial indices in the given class of matrix functions. This means that we will consider an allowable small perturbation such that a perturbed matrix function belong to the same class as the original one. We prove that in the class of matrix polynomials the Gohberg–Krein–Bojarsky criterion is preserved, i.e. new stability cases do not arise. Our proof of the stability criterion in this class does not use the Gohberg–Krein–Bojarsky theorem.

A semi-infinite crack in an infinite square lattice is subjected to a wave coming from infinity, thereby leading to its scattering by the crack surfaces. A partially damaged zone ahead of the crack tip is modelled by an arbitrarily distributed stiffness of the damaged links. While an open crack, with an atomically sharp crack tip, in the lattice has been solved in closed form with the help of the scalar Wiener–Hopf formulation (Sharma 2015 SIAM J. Appl. Math. , 75 , 1171–1192 ( doi:10.1137/140985093 ); Sharma 2015 SIAM J. Appl. Math. 75 , 1915–1940. ( doi:10.1137/15M1010646 )), the problem considered here becomes very intricate depending on the nature of the damaged links. For instance, in the case of a partially bridged finite zone it involves a 2 × 2 matrix kernel of formidable class. But using an original technique, the problem, including the general case of arbitrarily damaged links, is reduced to a scalar one with the exception that it involves solving an auxiliary linear system of N × N equations, where N defines the length of the damage zone. The proposed method does allow, effectively, the construction of an exact solution. Numerical examples and the asymptotic approximation of the scattered field far away from the crack tip are also presented.

In this work, the classical Wiener–Hopf method is incorporated into the emerging deep neural networks for the study of certain wave problems. The essential idea is to use the first-principle-based analytical method to efficiently produce a large volume of datasets that would supervise the learning of data-hungry deep neural networks, and to further explain the working mechanisms on underneath. To demonstrate such a combinational research strategy, a deep feed-forward network is first used to approximate the forward propagation model of a duct acoustic problem, which can find important aerospace applications in aeroengine noise tests. Next, a convolutional type U-net is developed to learn spatial derivatives in wave equations, which could help to promote computational paradigm in mathematical physics and engineering applications. A couple of extensions of the U-net architecture are proposed to further impose possible physical constraints. Finally, after giving the implementation details, the performance of the neural networks are studied by comparing with analytical solutions from the Wiener–Hopf method. Overall, the Wiener–Hopf method is used here from a totally new perspective and such a combinational research strategy shall represent the key achievement of this work.

Blue carbon did not originally include macroalgal ecosystems; however evidence is mounting that macroalgal ecosystems function in marine carbon sequestration. The great majority of present day marine macroalgal net primary productivity (NPP) involves haptophytic algae on eroding shores. For these organisms the long-term storage of particulate organic carbon involves export from the site of production of biomass that has evaded parasites and grazers, and that some of the exported biomass is sedimented and stored rather than being mineralized en route by detritivores (microbes and fauna). Export from eroding shores, and subsequent storage, of haptophytic marine macroalgal particulate organic carbon could have started by 1.6 Ga. Storage on depositing shores close to the site of NPP by rhizophytic macroalgae and then by rhizophytic coastal seagrasses, tidal marshes and mangroves began not less than 209 Ma ago. Future increases in surface ocean temperatures may bring tropical marine macroalgae to their upper temperature limit, while temperate marine macroalgae will migrate poleward, in both cases assuming that temperature increases faster than genetic adaptation to higher temperature. Increased CO 2 in the surface ocean will generally favour uncalcified over calcified marine macroalgae. This results in decreased CO 2 release from decreased calcification, as well as decreased ballasting by CaCO 3 of exported particulate organic carbon resulting in decreasing sedimentation. While much more work is needed, the available information suggests that macroalgae play a significant role in marine organic carbon storage.

The blue carbon paradigm has evolved in recognition of the high carbon storage and sequestration potential of mangrove, saltmarsh and seagrass ecosystems. However, fluxes of the potent greenhouse gases CH 4 and N 2 O, and lateral export of carbon are often overlooked within the blue carbon framework. Here, we show that the export of dissolved inorganic carbon (DIC) and alkalinity is approximately 1.7 times higher than burial as a long-term carbon sink in a subtropical mangrove system. Fluxes of methane offset burial by approximately 6%, while the nitrous oxide sink was approximately 0.5% of burial. Export of dissolved organic carbon and particulate organic carbon to the coastal zone is also significant and combined may account for an atmospheric carbon sink similar to burial. Our results indicate that the export of DIC and alkalinity results in a long-term atmospheric carbon sink and should be incorporated into the blue carbon paradigm when assessing the role of these habitats in sequestering carbon and mitigating climate change.

Increasing urbanization offers a unique opportunity to study adaptive responses to rapid environmental change. Numerous studies have demonstrated phenotypic divergence between urban and rural organisms. However, comparing the direction and magnitude of natural selection between these environments has rarely been attempted. Using seven years of monitoring of great tits ( Parus major ) breeding in nest-boxes across the city of Montpellier and in a nearby oak forest, we find phenotypic divergence in four morphological and two life-history traits between urban and forest birds. We then measure reproductive selection on these traits, and compare selection between the habitats. Urban birds had significantly smaller morphological features than their rural counterparts, with a shorter tarsus, lower body mass, and smaller wing and tail lengths relative to their overall body size. While urban female tarsus length was under stabilizing selection, and forest males show positive selection for tarsus length and negative selection for body mass, selection gradients were significantly divergent between habitats only for body mass. Urban great tits also had earlier laying dates and smaller clutches. Surprisingly, we found selection for earlier laying date in the forest but not in the city. Conversely, we detected no linear selection on clutch size in the forest, but positive selection on clutch size in the urban habitat. Overall, these results do not support the hypothesis that contemporary reproductive selection explains differences in morphology and life history between urban- and forest-breeding great tits. We discuss how further experimental approaches will help confirm whether the observed divergence is maladaptive while identifying the environmental drivers behind it.