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Data from two research projects with adult literacies practitioners based in Scotland are used to illustrate how policies underpinned by ideologies based on Human Capital Theory (HCT) lead to a narrow conceptualisation of the purpose of literacies education. It is argued that HCT ideology permeates international and national policies and thus influences practice. This results in a focus on the economy, rather than the individual, leading to narrow domains of skills-focused knowledge that become accepted as normal and are difficult to challenge. The paper outlines the changes experienced by practitioners, especially those focused on employability programs, but also shows how these changes have been resisted, particularly in relation to how the curriculum is negotiated, and outcomes are assessed with learners. Practitioners were able to maintain values-based approaches and protect democratic practice through interactions with colleagues that reinforced a collective understanding of fundamental principles for delivering social justice-based literacies programs. It is concluded that, while practitioners were critically reinterpreting aspects of the dominant discourse through building on learners' experience and valuing their perspectives, social justice requires that the impact of broader social and economic inequalities on participation in education is addressed through structural changes rather than individual effort.

Community-based adult learning (CBAL) focuses on improving the quality of life for the most disadvantaged and has a different ideology, methods, and curriculum from mainstream education. This Scottish case-study investigated the main changes that had impacted on CBAL provision in the preceding three years. These were: a reduction in funding for CBAL and its undervaluing by other professions; the impact of COVID-19 on learning and teaching; the importance of CBAL in promoting wellbeing. It is argued that these Scottish issues are similar in their impact to other Western countries; negatively because COVID-19 has exacerbated inequalities in the education available to the least advantaged, and positively in that CBAL practitioners have demonstrated the value of their work especially in addressing digital inequalities and mental health issues.

This article presents the findings of a comparative study of values-based adult learning and education (ALE) fields; specifically, in Austria, critical-emancipatory adult basic education; Scotland, learner-centered, community-based adult learning; and South Tyrol, Italy, the "Winterschule," a radical-critical popular education format. We studied the voices of experienced practitioners to understand their challenges and constraints and how they resisted changes that did not reflect their values. It highlights local practices to promote visibility, create dialogue, and strengthen the understanding and recognition of these fields in which practitioners are unequivocally committed to social justice. Our findings highlighted repertoires of resistance, affirmed pedagogy as a values-based endeavor, and elucidated practitioners' commitments to holistic approaches that re-negotiate ideas of social justice for people and the planet. Our analysis shows that when ideas of social justice are shared amongst allies, practitioners can effectively maintain their values-based approaches and thus re-affirm and protect democratic ALE practice.

During summer 2020, Southern China experienced an extremely dry and hot summer, which was identified as one of the top ten domestic weather and climate extreme events in 2020 by China Meteorological Administration. Summer mean precipitation, surface air temperature (TAS), and number of hot days (NHD) were about 25% dryer, 1.5 °C warmer, and 11 days larger than the 1981–2010 climatologies. These are the 4th largest precipitation deficit, the highest TAS, and the 2nd highest NHD in the 1961–2020 record. The large-scale circulation anomalies over the West Pacific increased the likelihood of the extreme hot and dry summer. Anthropogenic influences on this extreme summerwere investigated using 525-member ensembles of the atmosphere-only HadGEM3-GA6 model and the multi-model ensembles from the Coupled Model Intercomparison Project Phase 6 (CMIP6). Anthropogenic forcings doubled (increased by 27%) the probability of precipitation deficits, and increased occurrence more than 106 times for both TAS anomaly (50 times probability higher) and NHD anomaly (6 times probability higher) in HadGEM-GA6 (CMIP6). That means that the 2020-like TAS and NHD anomalies would not occur without anthropogenic forcings, and there is weak evidence that human influences decrease rainfall over Southern China. However, the precipitation deficit increased the likelihood of exceeding the observed thresholds for both TAS and NHD by about 17 (4) and 9 (1) times in HadGEM3-GA6 (CMIP6), respectively. Under SSP2-4.5 and SSP5-8.5 scenarios in the future, 2020-like hot but wet extreme summer increases in magnitude and frequency, while the frequency of dry summer declines.

Lak phages with alternatively coded ∼540 kbp genomes were recently reported to replicate in Prevotella in microbiomes of humans that consume a non-Western diet, baboons, and pigs. Here, we explore Lak phage diversity and broader distribution using diagnostic polymerase chain reaction and genome-resolved metagenomics. Lak phages were detected in 13 animal types, including reptiles, and are particularly prevalent in pigs. Tracking Lak through the pig gastrointestinal tract revealed significant enrichment in the hindgut compared to the foregut. We reconstructed 34 new Lak genomes, including six curated complete genomes, all of which are alternatively coded. An anomalously large (∼660 kbp) complete genome reconstructed for the most deeply branched Lak from a horse microbiome is also alternatively coded. From the Lak genomes, we identified proteins associated with specific animal species; notably, most have no functional predictions. The presence of closely related Lak phages in diverse animals indicates facile distribution coupled to host-specific adaptation.

Climate models can produce accurate representations of the most important modes of climate variability, but they cannot be expected to follow their observed time evolution. This makes direct comparison of simulated and observed variability difficult and creates uncertainty in estimates of forced change. We investigate the role of three modes of climate variability, the North Atlantic Oscillation, El Niño–Southern Oscillation and the Southern Annular Mode, as pacemakers of climate variability since 1781, evaluating where their evolution masks or enhances forced climate trends. We use particle filter data assimilation to constrain the observed variability in a global climate model without nudging, producing a near-free-running model simulation with the time evolution of these modes similar to those observed. Since the climate model also contains external forcings, these simulations, in combination with model experiments with identical forcing but no assimilation, can be used to compare the forced response to the effect of the three modes assimilated and evaluate the extent to which these are confounded with the forced response. The assimilated model is significantly closer than the “forcing only” simulations to annual temperature and precipitation observations over many regions, in particular the tropics, the North Atlantic and Europe. The results indicate where initialised simulations that track these modes could be expected to show additional skill. Assimilating the three modes cannot explain the large discrepancy previously found between observed and modelled variability in the southern extra-tropics but constraining the El Niño–Southern Oscillation reconciles simulated global cooling with that observed after volcanic eruptions.

This study of nine Primary School teachers of Religious Education (RE) analyses the benefits of their engagement in practitioner research (PR) and shows how that engagement can be sustained. We demonstrate the importance of enhancing the social dimension of learning through forming a community-of-practice (CoP) that enables participants to gain confidence and engage in democratic dialogue. The CoP in our project was sustained because teachers built trust with each other, were willing to talk openly about their practices and, through their common commitment to RE, contributed to the knowledge base of teaching. We conclude that engaging teachers in PR can create positive changes for schools because knowledge, interrogated by critical reflection, will be rooted in teachers' professional understanding of the processes of teaching and learning. Further, that communities-of-practice, as social learning environments, assist in sustaining teachers' engagement in PR by creating opportunities for teachers' collaborative critical reflection on their taken-for-granted professional practices.

This paper investigates the influence of a professional Religious Education (RE) conference on a small group of English Primary teachers' emerging identities as teacher-researchers. It is framed by analysis of agency as a means of examining how teachers can become capable producers of knowledge as active partners in dialogue with critical others. The paper argues that attending the conference played a role in increasing teachers' professional identify and agency because it provided a novel context of action in teachers' professional lives. Teachers were made aware of a much broader professional community to which they had legitimate membership where knowledge exchange and professional validation was intensified. The conference enabled reflexive thinking that disrupted teachers' 'taken for granted' habits and beliefs by offering new ways of seeing, being and acting, and in which they could forecast teacher-research as a feasible, relevant and purposeful aspect of their professional lives.

The skill of global ocean biogeochemical models, and the earth system models in which they are embedded, can be improved by systematic calibration of the parameter values against observations. However, such tuning is seldom undertaken as these models are computationally very expensive. Here we investigate the performance of DFO-LS, a local, derivative-free optimisation algorithm which has been designed for computationally expensive models with irregular model–data misfit landscapes typical of biogeochemical models. We use DFO-LS to calibrate six parameters of a relatively complex global ocean biogeochemical model (MOPS) against synthetic dissolved oxygen, phosphate and nitrate “observations” from a reference run of the same model with a known parameter configuration. The performance of DFO-LS is compared with that of CMA-ES, another derivative-free algorithm that was applied in a previous study to the same model in one of the first successful attempts at calibrating a global model of this complexity. We find that DFO-LS successfully recovers five of the six parameters in approximately 40 evaluations of the misfit function (each one requiring a 3000-year run of MOPS to equilibrium), while CMA-ES needs over 1200 evaluations. Moreover, DFO-LS reached a “baseline” misfit, defined by observational noise, in just 11–14 evaluations, whereas CMA-ES required approximately 340 evaluations. We also find that the performance of DFO-LS is not significantly affected by observational sparsity, however fewer parameters were successfully optimised in the presence of observational uncertainty. The results presented here suggest that DFO-LS is sufficiently inexpensive and robust to apply to the calibration of complex, global ocean biogeochemical models.

Abstract Ruffed grouse (Bonasa umbellus) populations are declining throughout their range, which has prompted efforts to understand drivers of the decline. Ruffed grouse monitoring efforts often rely on acoustic drumming surveys, in which a surveyor listens for the distinctive drumming sound that male ruffed grouse produce during the breeding season. Field‐based drumming surveys can fail to detect ruffed grouse when the birds drum infrequently or irregularly, making this species an excellent candidate for remote acoustic sensing with automated recording units (ARUs). An accurate automated recognition method for ruffed grouse drumming could enable effective and efficient use of ARU data for monitoring efforts; however, no such tool is currently available. Here we develop an automated method for detecting ruffed grouse drumming in audio recordings. Our detector uses a signal processing pipeline designed to recognize the accelerating pattern of drumming. We show that the automated recognition method accurately and efficiently detects drumming events in a set of labeled ARU field recordings. In a case study with 56 locations in Central Pennsylvania, we compared detections of ruffed grouse from 4 survey methods: field‐based acoustic drumming surveys, surveys conducted by humans listening to ARU recordings, and automated recognition for both a 1‐day and a 28‐day period. Field‐based surveys detected drumming at 9 of 56 locations (16%), while surveys conducted by humans listening to ARU recordings detected drumming at 8 locations (14%). Using automated recognition, the 1‐day recording period produced detections at 17 locations (30%) and the 28‐day recording period produced detections at 34 locations (61%). Our case study supports the idea that automated recognition can unlock the value of ARU datasets by temporally expanding the survey period. We provide an open‐source Python implementation of the recognition method to support further use in ruffed grouse monitoring efforts.

Plankton form the base of the marine food web and are sensitive indicators of environmental change. Plankton time series are therefore an essential part of monitoring progress towards global biodiversity goals, such as the Convention on Biological Diversity Aichi Targets, and for informing ecosystem-based policy, such as the EU Marine Strategy Framework Directive. Multiple plankton monitoring programmes exist in Europe, but differences in sampling and analysis methods prevent the integration of their data, constraining their utility over large spatio-temporal scales. The Plankton Lifeform Extraction Tool brings together disparate European plankton datasets into a central database from which it extracts abundance time series of plankton functional groups, called “lifeforms”, according to shared biological traits. This tool has been designed to make complex plankton datasets accessible and meaningful for policy, public interest, and scientific discovery. It allows examination of large-scale shifts in lifeform abundance or distribution (for example, holoplankton being partially replaced by meroplankton), providing clues to how the marine environment is changing. The lifeform method enables datasets with different plankton sampling and taxonomic analysis methodologies to be used together to provide insights into the response to multiple stressors and robust policy evidence for decision making. Lifeform time series generated with the Plankton Lifeform Extraction Tool currently inform plankton and food web indicators for the UK's Marine Strategy, the EU's Marine Strategy Framework Directive, and for the Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR) biodiversity assessments. The Plankton Lifeform Extraction Tool currently integrates 155 000 samples, containing over 44 million plankton records, from nine different plankton datasets within UK and European seas, collected between 1924 and 2017. Additional datasets can be added, and time series can be updated. The Plankton Lifeform Extraction Tool is hosted by The Archive for Marine Species and Habitats Data (DASSH) at https://www.dassh.ac.uk/lifeforms/ (last access: 22 November 2021, Ostle et al., 2021). The lifeform outputs are linked to specific, DOI-ed, versions of the Plankton Lifeform Traits Master List and each underlying dataset.