Scottish Government

Microbes play a central role in the degradation of chemical pollutants in the oceans, yet most studies investigating this are conducted in a laboratory setting which does not accurately portray and account for the prevailing physical and geochemical conditions in the deep sea. The Faroe-Shetland Channel (FSC) is a deep water, sub-Arctic region to the north of Scotland with >40-yr history of oil exploration and production. Here, we investigate the bacterioplankton community response to crude oil by enclosing water samples from ∼500 m depth in dialysis bags and incubating them in-situ to account for the role of environmental conditions. Using barcoded-amplicon 16S rRNA sequencing, the community strongly and rapidly responded to the oil within 4 days, particularly dominated by members of the genera Pseudoalteromonas, Alcanivorax, Mesonia, Alteromonas, and to a lesser extent Sulfitobacter, Vibrio and Thalassospira. Intriguingly, typical psychrophilic oil-degraders like Colwellia and Oleispira were not enriched, possibly due to being outcompeted by better adapted, more ‘aggressive’ hydrocarbon-degraders at this water depth. Using cultivation-based methods coupled with DNA-based stable isotope probing (DNA-SIP), we identified a diversity of oil-degraders, some of which (i.e. Mesonia, Spongiispira, Stutzerimonas, Vreelandella, Sulfitobacter, Paraglaciecola) had not hitherto been found in sequencing surveys or confirmed as oil-degraders in the FSC. Collectively, we show for the first time the presence of a diverse hydrocarbon-degrading community in the FSC that ‘stands at the ready’ to consume oil that may become entrained within the subsurface at depth in the event of a spill in this region.

Children with special educational needs and disabilities (SEND) are more likely to be absent from school. In Scotland, SEND are referred to as additional support needs (ASN) and include needs resulting from health and disabilities but also extend to family circumstances, the learning environment, and social-emotional needs. This paper analyses the trajectories of school absence of pupils with and without ASN. Using linked administrative data from the Scottish context, the paper follows a cohort of 49,180 pupils at publicly funded schools who started school in 2008/09 to the end of mandatory education at secondary stage S4. Multilevel modelling and zero-inflated beta regression models are used to investigate the longitudinal association between ASN and school absence, controlling for school and local authority clustering. For modelling ASN as a binary category, using a cubic time term with a random pupil-level time slope provided the best fit overall, indicating a non-linear relationship between ASN status and absence over time. A subsequent model differentiating between ASN categories was best captured using a linear time term. The results confirmed a persistent attendance gap between pupils with and without ASN. This gap is present during primary school but widens during secondary school. This widening is particularly driven by social-emotional needs, family circumstances, and other non-specified needs. Variation in absence by ASN is greatest at primary-school level, followed by secondary-school and local authority-level. These findings can inform targeted and school-stage specific support to mitigate disparities in attendance among heterogeneous groups of pupils with ASN.

Understanding biodiversity in offshore benthic ecosystems is crucial as anthropogenic pressures like offshore wind development increasingly alter marine environments. Passive acoustic monitoring (PAM), widely used for marine mammal research, offers a promising yet underexplored tool for assessing broader faunal communities. Here, we investigate whether PAM data, collected initially for marine mammal monitoring, can reveal spatial variation in benthic biodiversity along Scotland’s east coast. We analysed passive acoustic data from eight offshore sedimentary habitats, identifying 16 distinct biological sound types likely produced by fish and invertebrates. Acoustic indices were also calculated and compared with environmental variables and infaunal benthic richness derived from open-source biodiversity databases. Our results show that key habitat variables, including substrate type, current velocity, and spawning suitability, drive variation in acoustic communities. The findings of this pilot study demonstrate that PAM can be used to detect biologically meaningful patterns in benthic assemblages, and with future work focusing on investigating longer-term datasets, it could offer a cost-effective tool for biodiversity monitoring across space and time. While several acoustic indices correlated with phonic richness and benthic diversity, we currently do not recommend their use in biodiversity monitoring. This study highlights the ecological value of existing acoustic datasets and advances our understanding of soundscape ecology and species-habitat relationships in changing marine environments.

This paper explores variation in identification of Additional Support Needs (ASN) and the provision of support across Scottish schools and local authorities. Adding to existing research on Special Educational Needs and Disabilities (SEND), this paper provides a detailed analysis of pupils’ needs and formalised support responses in the Scottish context. In Scotland, ASN legislation encompasses a broader range of needs than SEND legislation in the rest of the UK which cover social-emotional needs and needs arising from family circumstances and the learning environment. Identification of ASN carries implications for access to support in the form of co-ordinated support plans (CSP), individualised educational programmes (IEP) and Child’s Plans (CP). Using linked administrative data from the Scottish Pupil Census, education and health records and the Census, this paper addresses three research questions: (1) What are the demographic and educational characteristics of pupils identified with ASN?; (2) How does support provision for pupils vary by ASN type and across schools and local authorities?; (3) How long does it take for a pupil identified with ASN to receive an ASN support plan? We use binary logistic regression to model ASN identification and multinomial regression to assess support provision. Following a pupil cohort from the first year of primary school to the end of mandatory secondary school, we employ a longitudinal approach to investigate the trajectories from ASN identification to support provision. The findings identify disparities in support responsiveness and allocation which are relevant to address by policymakers, service providers and school staff.

Traditional approaches to analyse educational outcomes frequently assume there is a linear relationship between non-attendance (via school absence and/or exclusions) and attainment, with policy implications usually focusing on the detrimental effect of non-attendance on attainment. This paper shows that implementing a non-linear approach to analyse the relationship between non-attendance and attainment can be useful to understand heterogeneous pathways of socioeconomic and health-related disadvantages into unfavourable educational outcomes. We followed a cohort of pupils in Scotland who started primary school in 2008/09 (age 4/5) and finished compulsory education in 2018/19 (age 15/16) and implemented a multilevel mixture regression model using linked population-level administrative data from Education Analytical Services (Scottish Government), Public Health Scotland (NHS) from the period between 2007-2019, and the 2011 Census (National Records Scotland). We found five unobserved groups of pupils that are distinct from each other in their patterns of attendance, exclusions and attainment, as well as their socioeconomic and health status, and level of needs. Furthermore, we found evidence that a good level of attainment could be theoretically possible without an equally good level of attendance, since the two groups with the highest attainment have markedly different profiles of attendance and exclusions, as well as distinct patterns of disadvantage in terms of attainment. We conclude that addressing the attainment gap requires a multi-layered approach that considers heterogeneous profiles of non-attendance. Policy and school guidance must also recognise the complexity of upstream and downstream factors that interact and condition children and young people’s lives, experiences and outcomes.