Effect of CO2 concentrations on entomopathogen fitness and insect-pathogen interactions

Numerous insect species and their associated microbial pathogens are exposed to elevated CO2 concentrations in both artificial and natural environments. However, the impacts of elevated CO2 on the fitness of these pathogens and the susceptibility of insects to pathogen infections are not well understood. The yellow mealworm, Tenebrio molitor, is commonly produced for food and feed purposes in mass-rearing systems, which increases risk of pathogen infections. Additionally, entomopathogens are used to control T. molitor, which is also a pest of stored grains. It is therefore important to understand how elevated CO2 may affect both the pathogen directly and impact on host-pathogen interactions. We demonstrate that elevated CO2 concentrations reduced the viability and persistence of the spores of the bacterial pathogen Bacillus thuringiensis. In contrast, conidia of the fungal pathogen Metarhizium brunneum germinated faster under elevated CO2. Pre-exposure of the two pathogens to elevated CO2 prior to host infection did not affect the survival probability of T. molitor larvae. However, larvae reared at elevated CO2 concentrations were less susceptible to both pathogens compared to larvae reared at ambient CO2 concentrations. Our findings indicate that whilst elevated CO2 concentrations may be beneficial in reducing host susceptibility in mass-rearing systems, they may potentially reduce the efficacy of the tested entomopathogens when used as biological control agents of T. molitor larvae. We conclude that CO2 concentrations should be carefully selected and monitored as an additional environmental factor in laboratory experiments investigating insect-pathogen interactions

A mathematical model of biofilm growth and spread within plant xylem: case study of Xylella fastidiosa in olive trees

Xylem-limited bacterial pathogens cause some of the most destructive plant diseases. Though imposed measures to control these pathogens are generally ineffective, even among susceptible taxa, some hosts can limit bacterial loads and symptom expression. Mechanisms by which this resistance is achieved are poorly understood. In particular, it is still unknown how differences in vascular structure may influence biofilm growth and spread within a host. To address this, we developed a novel theoretical framework to describe biofilm behaviour within xylem vessels, adopting a polymer-based modelling approach. We then parameterised the model to investigate the relevance of xylem vessel diameters on Xylella fastidiosa resistance among olive cultivars. The functionality of all vessels was severely reduced under infection, with hydraulic flow reductions of 2–3 orders of magnitude. However, results suggest wider vessels act as biofilm incubators; allowing biofilms to develop over a long time while still transporting them through the vasculature. By contrast, thinner vessels become blocked much earlier, limiting biofilm spread. Using experimental data on vessel diameter distributions, we were able to determine that a mechanism of resistance in the olive cultivar Leccino is a relatively low abundance of the widest vessels, limiting X. fastidiosa spread

Unlocking the potential of sensors for our environment : a call to action from a NERC writing retreat

Funded by UK Research and Innovation (UKRI), the Constructing a Digital Environment Strategic Priorities Fund (CDE) programme aspired to support the development of a comprehensive ‘digital environment’ ecosystem that best served scientists, policymakers, businesses, and communities. Emphasising multi-disciplinary and inter-disciplinary collaboration, CDE supported a team of challenge-focused researchers from a variety of disciplines to bring to the fore current and future digital advances in sensors that are critical to addressing environmental concerns. From March 2023 to January 2024, the team worked together to develop frameworks that sought to optimise the benefits of both existing and emerging sensor network technologies and their related infrastructure. Central to the development of these frameworks was a co-creation writing retreat in July 2023, where we came together to discuss the environmental sensing ecosystems unmet needs and challenges around five themes: Values, Changes, Barriers, Tools, and Lessons. The resultant findings and call for action suggest that: A. Focusing on People, Places and Ethics when making decisions on the whole sensor systems lifecycle (sensor design, deployment, application, and uptake) can ensure that research is more holistic, relevant, ethically sound, innovative, and, at the same time, has the potential for real-world impact. B. There is a clear need for a better-enabled sensor ‘development and use’ ecosystem (i.e., frameworks, methodologies, designs, communities) that has strong foundations and support for collaborative and interdisciplinary research to drive ambition for responsible innovation and resilient research communities. Overall, the findings highlight the vast potential offered by increased sensor utilisation for science and society, as well as broader concerns around data practices and innovation and specific challenges to sensors and sensing for the environment. There is a greater need for responsible data sharing, standardisation and quality assurance, as well as enhanced interdisciplinary collaboration and knowledge transfer between academia and industry. Furthermore, sector-specific barriers to recruitment and retention (particularly from those traditionally underrepresented in the sector) need to be addressed if transformative research is to be delivered and sustainable ecosystems that are diverse and inclusive are to be created

Surface Heat Fluxes Drive a Two‐Phase Response in Southern Ocean Mode Water Stratification

Subantarctic mode waters have low stratification and are formed through subduction from thick winter mixed layers in the Southern Ocean. To investigate how surface forcing affects the stratification in mode water formation regions in the Southern Ocean, a set of adjoint sensitivity experiments are conducted. The objective function is the annual-average stratification over the mode water formation region, which is evaluated from potential temperature and salinity adjoint sensitivity experiments. The analysis of impacts, from the product of sensitivities and forcing variability, identifies the separate effects of the wind stress, heat flux, and freshwater flux, revealing that the dominant control on stratification is from surface heat fluxes, as well as a smaller effect from zonal wind stress. The adjoint sensitivities of stratification to surface heat flux reveal a surprising change in sign over 2 years lead time: surface cooling leads to the expected initial local decrease in stratification, but there is a delayed response leading to an increase in stratification. This delayed response in stratification involves effective atmospheric damping of the surface thermal contribution, so that eventually the oppositely-signed advective haline contribution dominates. This two-phase response of stratification is found to hold over mode water formation regions in the South Indian and Southeast Pacific sectors of the Southern Ocean, where there are strong advective flows linked to the Antarctic Circumpolar Current

The genome sequence of the straw underwing, Thalpophila matura (Hufnagel, 1766)

We present a genome assembly from an individual male Thalpophila matura (the Straw Underwing; Arthropoda; Insecta; Lepidoptera; Noctuidae). The genome sequence is 520.4 megabases in span. Most of the assembly is scaffolded into 31 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled and is 15.52 kilobases in length. Gene annotation of this assembly on Ensembl identified 19,185 protein coding genes

A 6 year assessment of low sea-ice impacts on emperor penguins [Short Note]

Sea ice, and particularly land-fast sea ice, is crucial for emperor penguins as a breeding and moulting platform and foraging habitat (Barbraud & Weimerskirch 2001). Emperor penguins use land-fast sea ice as a breeding platform to raise their chicks, from egg hatching in late July to mid-August until fledging, typically between mid-December and early January

The genome sequence of the marbled rockcod, Notothenia rossii Richardson, 1844 [Data Note]

We present a genome assembly from an individual Notothenia rossii (the marbled rockcod; Chordata; Actinopterygii; Perciformes; Nototheniidae). The genome sequence is 1,042.9 megabases in span. Most of the assembly is scaffolded into 12 chromosomal pseudomolecules. The mitochondrial genome has also been assembled and is 21.68 kilobases in length. Gene annotation of this assembly on Ensembl identified 24,432 protein coding genes

The challenge to understand the zoo of particle transport regimes during resonant wave-particle interactions for given survey-mode wave spectra

Quasilinear theories have been shown to well describe a range of transport phenomena in magnetospheric, space, astrophysical and laboratory plasma “weak turbulence” scenarios. It is well known that the resonant diffusion quasilinear theory for the case of a uniform background field may formally describe particle dynamics when the electromagnetic wave amplitude and growth rates are sufficiently “small”, and the bandwidth is sufficiently “large”. However, it is important to note that for a given wave spectrum that would be expected to give rise to quasilinear transport, the quasilinear theory may indeed apply for given range of resonant pitch-angles and energies, but may not apply for some smaller, or larger, values of resonant pitch-angle and energy. That is to say that the applicability of the quasilinear theory can be pitch-angle dependent, even in the case of a uniform background magnetic field. If indeed the quasilinear theory does apply, the motion of particles with different pitch-angles are still characterised by different timescales. Using a high-performance test-particle code, we present a detailed analysis of the applicability of quasilinear theory to a range of different wave spectra that would otherwise “appear quasilinear” if presented by e.g., satellite survey-mode data. We present these analyses as a function of wave amplitude, wave coherence and resonant particle velocities (energies and pitch-angles), and contextualise the results using theory of resonant overlap and small amplitude criteria. In doing so, we identify and classify five different transport regimes that are a function of particle pitch-angle. The results in our paper demonstrate that there can be a significant variety of particle responses (as a function of pitch-angle) for very similar looking survey-mode electromagnetic wave products, even if they appear to satisfy all appropriate quasilinear criteria. In recent years there have been a sequence of very interesting and important results in this domain, and we argue in favour of continuing efforts on: (i) the development of new transport theories to understand the importance of these, and other, diverse electron responses; (ii) which are informed by statistical analyses of the relationship between burst- and survey-mode spacecraft data

Minimum-entropy velocity estimation from GPS position time series

We propose a nonparametric minimum entropy method for estimating an optimal velocity from position time series, which may contain unknown noise, data gaps, loading effects, transients, outliers and step discontinuities. Although nonparametric, the proposed method is based on elementary statistical concepts familiar to least-squares and maximum-likelihood users. It seeks a constant velocity with a best possible (realistic) variance rather than a best variable velocity fit to the closest position data. We show, based on information theory, synthetic and real data, that minimum-entropy velocity estimation: (1) accounts for colored noise without assumptions about its distribution or the extent of its temporal correlations; (2) is unaffected by the series deterministic content such as an initial position and the heights of step discontinuities and insensitive to small-amplitude periodic variations and transients; (3) is robust against outliers and, for long time series, against step discontinuities and even slight non-stationarity of the noise; (4) does not involve covariance matrices or eigen/singular value analysis, thus can be implemented by a short and efficient software; (5) under no circumstances results in a velocity variance that decays as 1/N, where N is the number of observations. The proposed method is verified based on synthetic data and then applied to a few hundred NGL (Nevada Geodetic Lab) position time series of different characteristics, and the results are compared to those of the Median Interannual Difference Adjusted for Skewness (MIDAS) algorithm. The compared time series include continuous and linear ones used to test the agreement between the two methods in the presence of unknown noise, data gaps and loading effects, discontinuous but linear series selected to include the effect of a few (1–4) discontinuities, and nonlinear but continuous time series selected for including the effects of transients. Both the minimum-entropy and MIDAS methods are nonparametric in the sense that they only extract the velocity from a position time series with hardly any explicit assumptions about its noise distribution or correlation structure. Otherwise, the two methods differ in every single possible technical sense. Other than pointing to a close agreement between the derived velocities, the comparisons consistently revealed that minimum-entropy velocity uncertainties suggest a smaller degree of temporal correlations in the NGL time series than the MIDAS does