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Atmospheric inversions have been used for the past two decades to derive large-scale constraints on the sources and sinks of CO2 into the atmosphere. The development of dense in situ surface observation networks, such as ICOS in Europe, enables in theory inversions at a resolution close to the country scale in Europe. This has led to the development of many regional inversion systems capable of assimilating these high-resolution data, in Europe and elsewhere. The EUROCOM (European atmospheric transport inversion comparison) project is a collaboration between seven European research institutes, which aims at producing a collective assessment of the net carbon flux between the terrestrial ecosystems and the atmosphere in Europe for the period 2006–2015. It aims in particular at investigating the capacity of the inversions to deliver consistent flux estimates from the country scale up to the continental scale. The project participants were provided with a common database of in situ-observed CO2 concentrations (including the observation sites that are now part of the ICOS network) and were tasked with providing their best estimate of the net terrestrial carbon flux for that period, and for a large domain covering the entire European Union. The inversion systems differ by the transport model, the inversion approach, and the choice of observation and prior constraints, enabling us to widely explore the space of uncertainties. This paper describes the intercomparison protocol and the participating systems, and it presents the first results from a reference set of inversions, at the continental scale and in four large regions. At the continental scale, the regional inversions support the assumption that European ecosystems are a relatively small sink (-0.21±0.2 Pg C yr−1). We find that the convergence of the regional inversions at this scale is not better than that obtained in state-of-the-art global inversions. However, more robust results are obtained for sub-regions within Europe, and in these areas with dense observational coverage, the objective of delivering robust country-scale flux estimates appears achievable in the near future.

Compared to the rest of the globe, the Arctic Ocean is affected disproportionately by climate change. Despite these fast environmental changes, we currently know little about the effects of ocean acidification (OA) on marine key species in this area. Moreover, the existing studies typically test the effects of OA under constant, hence artificial, light fields. In this study, the abundant Arctic picoeukaryote Micromonas pusilla was acclimated to current (400 µatm) and future (1000 µatm) pCO2 levels under a constant as well as a dynamic light, simulating more realistic light fields as experienced in the upper mixed layer. To describe and understand the responses to these drivers, growth, particulate organic carbon (POC) production, elemental composition, photophysiology and reactive oxygen species (ROS) production were analysed. M. pusilla was able to benefit from OA on various scales, ranging from an increase in growth rates to enhanced photosynthetic capacity, irrespective of the light regime. These beneficial effects were, however, not reflected in the POC production rates, which can be explained by energy partitioning towards cell division rather than biomass build-up. In the dynamic light regime, M. pusilla was able to optimize its photophysiology for effective light usage during both low- and high-light periods. This photoacclimative response, which was achieved by modifications to photosystem II (PSII), imposed high metabolic costs leading to a reduction in growth and POC production rates when compared to constant light. There were no significant interactions observed between dynamic light and OA, indicating that M. pusilla is able to maintain effective photoacclimation without increased photoinactivation under high pCO2. Based on these findings, M. pusilla is likely to cope well with future conditions in the Arctic Ocean.

Atmospheric inverse modelling has become an increasingly useful tool for evaluating emissions of greenhouse gases including methane, nitrous oxide, and synthetic gases such as hydrofluorocarbons (HFCs). Atmospheric inversions for emissions of CO2 from fossil fuel combustion (ffCO2) are currently being developed. The aim of this paper is to investigate potential errors and uncertainties related to the spatial and temporal prior representation of emissions and modelled atmospheric transport for the inversion of ffCO2 emissions in the US state of California. We perform simulation experiments based on a network of ground-based observations of CO2 concentration and radiocarbon in CO2 (a tracer of ffCO2), combining prior (bottom-up) emission models and transport models currently used in many atmospheric studies. The potential effect of errors in the spatial and temporal distribution of prior emission estimates is investigated in experiments by using perturbed versions of the emission estimates used to create the pseudo-data. The potential effect of transport error was investigated by using three different atmospheric transport models for the prior and pseudo-data simulations. We find that the magnitude of biases in posterior total state emissions arising from errors in the spatial and temporal distribution in prior emissions in these experiments are 1 %–15 % of posterior total state emissions and are generally smaller than the 2σ uncertainty in posterior emissions. Transport error in these experiments introduces biases of −10 % to +6 % into posterior total state emissions. Our results indicate that uncertainties in posterior total state ffCO2 estimates arising from the choice of prior emissions or atmospheric transport model are on the order of 15 % or less for the ground-based network in California we consider. We highlight the need for temporal variations to be included in prior emissions and for continuing efforts to evaluate and improve the representation of atmospheric transport for regional ffCO2 inversions.

We describe the motivation, design, and execution of the Greenhouse gAs Uk and Global Emissions (GAUGE) project. The overarching scientific objective of GAUGE was to use atmospheric data to estimate the magnitude, distribution, and uncertainty of the UK greenhouse gas (GHG, defined here as CO2, CH4, and N2O) budget, 2013–2015. To address this objective, we established a multi-year and interlinked measurement and data analysis programme, building on an established tall-tower GHG measurement network. The calibrated measurement network comprises ground-based, airborne, ship-borne, balloon-borne, and space-borne GHG sensors. Our choice of measurement technologies and measurement locations reflects the heterogeneity of UK GHG sources, which range from small point sources such as landfills to large, diffuse sources such as agriculture. Atmospheric mole fraction data collected at the tall towers and on the ships provide information on sub-continental fluxes, representing the backbone to the GAUGE network. Additional spatial and temporal details of GHG fluxes over East Anglia were inferred from data collected by a regional network. Data collected during aircraft flights were used to study the transport of GHGs on local and regional scales. We purposely integrated new sensor and platform technologies into the GAUGE network, allowing us to lay the foundations of a strengthened UK capability to verify national GHG emissions beyond the project lifetime. For example, current satellites provide sparse and seasonally uneven sampling over the UK mainly because of its geographical size and cloud cover. This situation will improve with new and future satellite instruments, e.g. measurements of CH4 from the TROPOspheric Monitoring Instrument (TROPOMI) aboard Sentinel-5P. We use global, nested, and regional atmospheric transport models and inverse methods to infer geographically resolved CO2 and CH4 fluxes. This multi-model approach allows us to study model spread in a posteriori flux estimates. These models are used to determine the relative importance of different measurements to infer the UK GHG budget. Attributing observed GHG variations to specific sources is a major challenge. Within a UK-wide spatial context we used two approaches: (1) Δ14CO2 and other relevant isotopologues (e.g. δ13CCH4) from collected air samples to quantify the contribution from fossil fuel combustion and other sources, and (2) geographical separation of individual sources, e.g. agriculture, using a high-density measurement network. Neither of these represents a definitive approach, but they will provide invaluable information about GHG source attribution when they are adopted as part of a more comprehensive, long-term national GHG measurement programme. We also conducted a number of case studies, including an instrumented landfill experiment that provided a test bed for new technologies and flux estimation methods. We anticipate that results from the GAUGE project will help inform other countries on how to use atmospheric data to quantify their nationally determined contributions to the Paris Agreement.

In this study, researchers investigated the library experiences of Black undergraduate students at Penn State in University Park, a predominately white institution. Their goal was to improve services and spaces and to highlight and validate experiences with race, racism, and microaggressions on campus and in the library. Twenty undergraduate students were interviewed and asked to talk about their experiences and how these affected their perception of the University Libraries. Using the lens of critical race theory, which sees race as a socially constructed category used to oppress people of color, this study seeks to present a counternarrative to the prevailing dominant view of the library as a neutral space. Several consistent themes were identified. The themes included, but were not limited to, a low awareness of library services, lack of Black representation in the University Libraries, and a general lack of comfort within the library space.

Broad issues associated with non-replicability have been described in experimental pharmacological and behavioral cognitive studies. Efforts to prevent biases that contribute to non-replicable scientific protocols and to improve experimental rigor for reproducibility are increasingly seen as a basic requirement for the integrity of scientific research. Synaptic plasticity, encompassing long-term potentiation (LTP), is believed to underlie mechanisms of learning and memory. The present study was undertaken in Long-Evans (LE) rats, a strain of rat commonly used in cognitive behavioral tests, to (1) compare three LTP tetanisation protocols, namely, the high-frequency stimulation (HFS), the theta-burst stimulation (TBS), and the paired-pulse facilitation (PPF) at the Schaffer collateral-CA1 stratum radiatum synapse and to (2) assess sensitivity to acute pharmacology. Results: (1) When compared to Sprague-Dawley (SD) rats, the HFS using a stimulus intensity of 50% of the maximum slope obtained from input/output (I/O) curves elicited lower and higher thresholds of synaptic plasticity responses in SD and LE rats, respectively. The 2-train TBS protocol significantly enhanced the LTP response in LE rats over the 5- and 10-train TBS protocols in both strains, and the 5×TBS protocol inducing a subthreshold LTP response was used in subsequent pharmacological studies in LE rats. The PPF protocol, investigating the locus of the LTP response, showed no difference for the selected interstimulus intervals. (2) Scopolamine, a nonspecific muscarinic antagonist, had a subtle effect, whereas donepezil, an acetylcholinesterase inhibitor, significantly enhanced the LTP response, demonstrating the sensitivity of the TBS protocol to enhanced cholinergic tone. MK-801, a noncompetitive N-methyl-D-aspartate (NMDA) antagonist, significantly reduced LTP response, while memantine, another NMDA antagonist, had no effect on LTP response, likely associated with a weaker TBS protocol. PQ10, a phosphodiesterase-10 inhibitor, significantly enhanced the TBS-induced LTP response, but did not change the PPF response. Overall, the results confirm the strain-dependent differences in the form of synaptic plasticity, replicate earlier plasticity results, and report effective protocols that generate a relatively subthreshold margin of LTP induction and maintenance, which are suitable for pharmacology in the LE rat strain mainly used in cognitive studies.

Objective: This study examined whether college students with and without depression or anxiety differed in subjective cognitive concerns, academic self-efficacy, and cognitive strategy use. Participants: Participants included 582 college students (M = 19.0 ± 1.0 years-old, 79.4% women, 81.9% White). Methods: Participants completed online self-report questionnaires on subjective cognitive functioning, academic self-efficacy, cognitive strategy use, and depression and anxiety symptoms, which were used to categorize participants as having anxiety or depression based on established clinical cutoffs. Results: Participants with anxiety or depression reported greater subjective cognitive concerns and lower academic self-efficacy compared to participants without anxiety or depression, but these groups differed only modestly in cognitive strategy use. Conclusions: Despite greater cognitive concerns, participants with anxiety or depression reported only modestly greater cognitive strategy use. Future research should evaluate interventions to increase strategy use among college students with anxiety or depression, tailoring these interventions for modern students by incorporating telehealth approaches and smartphone use.

A method is presented which can be used to obtain analytical solutions for boundary value problems (BVPs) using the matrix exponential and Maple. Systems of second order, linear differential equations are expressed as two or more first order equations in matrix form, and their solutions are obtained using the matrix exponential, matrix integration, and matrix inverse methods using Maple. The solution process is illustrated for single and multiple domains with different types of boundary conditions and constraints when necessary due to the boundary conditions. The method is easier to use and could be extended to include partial differential equations (PDEs).

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Background Access to sample-level metadata is important when selecting public metagenomic sequencing datasets for reuse in new biological analyses. The Standards, Precautions, and Advances in Ancient Metagenomics community (SPAAM, https://spaam-community.org) has previously published AncientMetagenomeDir, a collection of curated and standardised sample metadata tables for metagenomic and microbial genome datasets generated from ancient samples. However, while sample-level information is useful for identifying relevant samples for inclusion in new projects, Next Generation Sequencing (NGS) library construction and sequencing metadata are also essential for appropriately reprocessing ancient metagenomic data. Currently, recovering information for downloading and preparing such data is difficult when laboratory and bioinformatic metadata is heterogeneously recorded in prose-based publications. Methods Through a series of community-based hackathon events, AncientMetagenomeDir was updated to provide standardised library-level metadata of existing and new ancient metagenomic samples. In tandem, the companion tool 'AMDirT' was developed to facilitate rapid data filtering and downloading of ancient metagenomic data, as well as improving automated metadata curation and validation for AncientMetagenomeDir. Results AncientMetagenomeDir was extended to include standardised metadata of over 6000 ancient metagenomic libraries. The companion tool 'AMDirT' provides both graphical- and command-line interface based access to such metadata for users from a wide range of computational backgrounds. We also report on errors with metadata reporting that appear to commonly occur during data upload and provide suggestions on how to improve the quality of data sharing by the community. Conclusions Together, both standardised metadata reporting and tooling will help towards easier incorporation and reuse of public ancient metagenomic datasets into future analyses.

Undergraduate research offers a significant avenue for enhancing the engagement and skill development of underrepresented students, particularly those from BIPOC backgrounds. This study conducted at Penn State University aimed to illuminate the challenges faced by BIPOC students in their pursuit of undergraduate research opportunities and promote diversity and inclusivity within research programs. Through interviews and surveys, the research team discovered that students often grapple with uncertainty when seeking research prospects, with disparities in access to information. They also highlighted the importance of faculty mentorship, particularly from individuals with shared backgrounds. Although opinions on the influence of race or ethnicity on research experiences varied, the study emphasized the need for tailored support and proactive outreach efforts to improve the accessibility of undergraduate research resources.

Background: Access to sample-level metadata is important when selecting public metagenomic sequencing datasets for reuse in new biological analyses. The Standards, Precautions, and Advances in Ancient Metagenomics community (SPAAM, https://spaam-community.github.io) has previously published AncientMetagenomeDir, a collection of curated and standardised sample metadata tables for metagenomic and microbial genome datasets generated from ancient samples. However, while sample-level information is useful for identifying relevant samples for inclusion in new projects, Next Generation Sequencing (NGS) library construction and sequencing metadata are also essential for appropriately reprocessing ancient metagenomic data. Currently, recovering information for downloading and preparing such data is difficult when laboratory and bioinformatic metadata is heterogeneously recorded in prose-based publications. Methods: Through a series of community-based hackathon events, AncientMetagenomeDir was updated to provide standardised library-level metadata of existing and new ancient metagenomic samples. In tandem, the companion tool 'AMDirT' was developed to facilitate automated metadata curation and data validation, as well as rapid data filtering and downloading. Results: AncientMetagenomeDir was extended to include standardised metadata of over 5000 ancient metagenomic libraries. The companion tool 'AMDiRT' provides both graphical- and command-line interface based access to such metadata for users from a wide range of computational backgrounds. We also report on errors with metadata reporting that appear to commonly occur during data upload and provide suggestions on how to improve the quality of data sharing by the community. Conclusions: Together, both standardised metadata and tooling will help towards easier incorporation and reuse of public ancient metagenomic datasets into future analyses.