The population of the United Kingdom in 2024 was estimated to be approximately 69.3 million, with over 9.6 million people living in South East England. London had the next highest population, at almost 9.1 million people, followed by the North West England at 7.7 million. With the UK's population generally concentrated in England, most English regions have larger populations than the constituent countries of Scotland, Wales, and Northern Ireland, which had populations of 5.5 million, 3.2 million, and 1.9 million respectively. English counties and cities The United Kingdom is a patchwork of various regional units, within England the largest of these are the regions shown here, which show how London, along with the rest of South East England had around 18 million people living there in this year. The next significant regional units in England are the 47 metropolitan and ceremonial counties. After London, the metropolitan counties of the West Midlands, Greater Manchester, and West Yorkshire were the biggest of these counties, due to covering the large urban areas of Birmingham, Manchester, and Leeds respectively. Regional divisions in Scotland, Wales and Northern Ireland The smaller countries that comprise the United Kingdom each have different local subdivisions. Within Scotland these are called council areas whereas in Wales the main regional units are called unitary authorities. Scotland's largest Council Area by population is that of Glasgow City at over 622,000, while in Wales, it was the Cardiff Unitary Authority at around 372,000. Northern Ireland, on the other hand, has eleven local government districts, the largest of which is Belfast with a population of around 348,000.

In 2023, almost nine million people lived in Greater London, making it the most populated ceremonial county in England. The West Midlands Metropolitan County, which contains the large city of Birmingham, was the second-largest county at 2.98 million inhabitants, followed by Greater Manchester and then West Yorkshire with populations of 2.95 million and 2.4 million, respectively. Kent, Essex, and Hampshire were the three next-largest counties in terms of population, each with around 1.89 million people. A patchwork of regions England is just one of the four countries that compose the United Kingdom of Great Britain and Northern Ireland, with England, Scotland and Wales making up Great Britain. England is therefore not to be confused with Great Britain or the United Kingdom as a whole. Within England, the next subdivisions are the nine regions of England, containing various smaller units such as unitary authorities, metropolitan counties and non-metropolitan districts. The counties in this statistic, however, are based on the ceremonial counties of England as defined by the Lieutenancies Act of 1997. Regions of Scotland, Wales, and Northern Ireland Like England, the other countries of the United Kingdom have their own regional subdivisions, although with some different terminology. Scotland’s subdivisions are council areas, while Wales has unitary authorities, and Northern Ireland has local government districts. As of 2022, the most-populated Scottish council area was Glasgow City, with over 622,000 inhabitants. In Wales, Cardiff had the largest population among its unitary authorities, and in Northern Ireland, Belfast was the local government area with the most people living there.

In 2023, the population of the United Kingdom was around **** million, with approximately **** million women and **** million men. Since 1953, the male population of the UK has grown by around *** million, while the female population has increased by approximately *** million. Throughout this provided time period, the female population of the UK has consistently outnumbered the male population. UK population one of the largest in Europe As of 2022, the population of the United Kingdom was the largest it has ever been, and with growth expected to continue, the forecasted population of the United Kingdom is expected to reach over ** million by the 2030s. Despite the relatively small size of its territory, the UK has one of the largest populations among European countries, slightly larger than France but smaller than Russia and Germany. As of 2022, the population density of the UK was approximately *** people per square kilometer, with London by far the most densely populated area, and Scotland the most sparsely populated. Dominance of London As seen in the data regarding population density, the population of the United Kingdom is not evenly distributed across the country. Within England, London has a population of almost **** million, making it significantly bigger than the next largest cities of Birmingham and Manchester. As of 2022, Scotland's largest city, Glasgow had a population of around *** million, with the largest cities in Northern Ireland, and Wales being Belfast and Cardiff, which had populations of ******* and ******* respectively.

The population of the United Kingdom in 2023 was estimated to be approximately 68.3 million in 2023, with almost 9.48 million people living in South East England. London had the next highest population, at over 8.9 million people, followed by the North West England at 7.6 million. With the UK's population generally concentrated in England, most English regions have larger populations than the constituent countries of Scotland, Wales, and Northern Ireland, which had populations of 5.5 million, 3.16 million, and 1.92 million respectively. English counties and cities The United Kingdom is a patchwork of various regional units, within England the largest of these are the regions shown here, which show how London, along with the rest of South East England had around 18 million people living there in this year. The next significant regional units in England are the 47 metropolitan and ceremonial counties. After London, the metropolitan counties of the West Midlands, Greater Manchester, and West Yorkshire were the biggest of these counties, due to covering the large urban areas of Birmingham, Manchester, and Leeds respectively. Regional divisions in Scotland, Wales and Northern Ireland The smaller countries that comprise the United Kingdom each have different local subdivisions. Within Scotland these are called council areas whereas in Wales the main regional units are called unitary authorities. Scotland's largest Council Area by population is that of Glasgow City at over 622,000, while in Wales, it was the Cardiff Unitary Authority at around 372,000. Northern Ireland, on the other hand, has eleven local government districts, the largest of which is Belfast with a population of around 348,000.

Eurasian otters are apex predators of freshwater ecosystems and a recovering species across much of their European range; investigating the dietary variation of this predator over time and space therefore provides opportunities to identify changes in freshwater trophic interactions and factors influencing the conservation of otter populations. Here we sampled faeces from 300 dead otters across England and Wales between 2007 and 2016, conducting both morphological analysis of prey remains and dietary DNA metabarcoding. Comparison of these methods showed that greater taxonomic resolution and breadth could be achieved using DNA metabarcoding but combining data from both methodologies gave the most comprehensive dietary description. All otter demographics exploited a broad range of taxa and variation likely reflected changes in prey distributions and availability across the landscape. This study provides novel insights into the trophic generalism and adaptability of otters across Britain, which is likely to have aided their recent population recovery, and may increase their resilience to future environmental changes. Methods Sample and data collection Samples and associated metadata were acquired from 300 otters collected between 2007 and 2016, obtained from the Cardiff University Otter Project, a national monitoring programme for dead otters sampled from across Great Britain (https://www.cardiff.ac.uk/otter-project). Most otters collected were killed by road traffic accidents, with a minority dying through drowning, being shot, starvation, or disease. Information on date (year and month) and location (as grid reference) of carcass collection were recorded at the site of collection. Grid references were used to plot data for spatial analysis. Detailed post-mortems were performed for each carcass during which biotic data were obtained (e.g., sex and size of individual). Faecal samples were collected from the rectum during post-mortem examination, wrapped in foil and stored at -20 °C. Following post-mortems, scaled mass index (SMI) was calculated for each individual otter using the following equation (Peig and Green 2009; Peig and Green 2010): SMI = Mi [ L0 / Li ] bSMA Mi is the body mass and Li is the length measurement of individual i, L0 is the mean length measurement for the entire study population and bSMA is the scaling exponent. Length was measured from nose to tail-tip to the nearest 5 mm. Mean length and the scaling exponent were both calculated from all otter data available as of January 2017 (n = 2477). The scaling exponent is the slope from the standard major axis regression of log-transformed values of mass against length.Otters were also classified into size categories based on their total length (nose to tail tip) using the ‘bins’ function in R (OneR v2.2 package; von Jouanne-Diedrich 2017), which applies a clustering method using Jenks natural breaks optimisation. Male and female otters were clustered separately into small (males <1046 mm, females <936 mm long), medium (males between 1046 mm and 1131 mm, females between 936 mm and 1031 mm), and large (males > 1131 mm, females > 1031 mm). Spatial data Spatial data describing proximity to the coast, urban land use, altitude, slope, and primary water habitat were collated using QGIS version 3.4.4 (QGIS Development Team 2019). Distance from the coast was calculated as the shortest distance (km) along a river from the location at which the otter was found to the low tide point of the mouth of the river (hereafter referred to as ‘river distance’), using the package RivEX (Hornby 2020), because otters tend to travel along water courses rather than across land. As most otters were found as roadkill, and not all were adjacent to rivers, each otter was first assigned to the nearest river. Locations more than 1000 m from a river were checked, and if there was more than one river along which the otter might have travelled, then river distance was calculated for all rivers and a mean distance used. All otters within 1000 m of the coast were given a distance of zero if they were closer to the coastline than a river.Otter locations were mapped as points, and circular areas of 10 km diameter (hereafter referred to as ‘buffers’) mapped around each. Faecal samples typically reflect diet from the preceding 24-72 hours (in mammals; Deagle et al. 2005; Casper et al. 2007; Thalinger et al. 2016), during which time otters can travel up to 10 km (Chanin 2003), it was therefore deemed appropriate to use this distance to reflect the land used by otters within the sample timeframe. Buffers were used to calculate proportions of urban land-use (i.e., urban and suburban land use extracted from the 25 m resolution UK land cover map from 2007; Morton et al. 2011), mean altitude and mean slope (extracted from European Digital Elevation Model (EU-DEM) map; European Environment Agency 2011). We chose to focus on urban land-use as urbanisation may affect otter diet either through changes to prey assemblages or disturbance affecting an otter's ability to forage. Longitude, altitude, and slope were highly correlated, therefore longitude was used in further analyses as a representative for the three variables.Otters in England and Wales typically feed in freshwater river systems but will opportunistically feed in lakes or at the coast if these habitats are within range (Jędrzejewska et al. 2001; Clavero et al. 2004; Parry et al. 2011). Available prey differ between lakes, coasts, and river systems, as well as between different parts of the river network (e.g., tributary, main river channel). To assess whether water habitat type influenced dietary variation, we designated each otter to one of the following: transitional water (coastal and estuarine), lake, main river channel, or tributary (based on Water Framework Directive 2000/60/EC designations mapped using GIS shapefiles provided by Natural Resources Wales and Environment Agency). Otters within 2.5 km (half of a buffer’s radius) from a lake or transitional water were assigned to that habitat, whilst those further away were assumed to be feeding primarily in the river network. The RivEX network map (Hornby 2020) was used to map all rivers, and individuals were further categorised according to whether their assumed habitat was primarily a main river or tributary. To do this, the total length of main river channels and tributaries was calculated within each 10 km buffer. The length of main channels was weighted 10 times greater to account for the greater cross-section of a main channel compared to tributaries (Benda et al. 2004) since waterways with greater areas are assumed to support more prey (Samarasin et al. 2014). The sum of weighted main river lengths and tributary lengths was calculated, and if more than 50 percent of each buffer was attributed to main river channel, the otter was assigned to the main river channel, otherwise it was assigned to tributary. Morphological analysis Each faecal sample was first thawed, homogenised by hand in a sterile container, and divided into subsamples; three samples weighing 200 mg each were collected for DNA analysis (one sample used for DNA extraction and the other two frozen as back-ups) and the remaining material was used for morphological analysis. Subsamples undergoing morphological analysis were then soaked in a solution of water and liquid biological detergent (water:detergent, 10:1) for 24 hours. Samples were passed through sieves with a 0.5 mm mesh and washed with water to ensure only hard parts remained which were air-dried for 24 hours. A record was made of any samples that did not contain any hard parts. Recognisable remains (bones, fish scales, feathers, fur) underwent microscopic identification using a range of keys (Libois and Hallet-Libois 1987; Coburn and Gaglione 1992; Prenda and Granado-Lorencio 1992; Prenda et al. 1997; Watt et al. 1997; Miranda and Escala 2002; Conroy et al. 2005; Tercerie et al. 2019; University of Nottingham 2020). Prey remains were identified to the finest possible taxonomic resolution and recorded as present within or absent from a sample. DNA metabarcoding analysis Faecal samples were processed for HTS, and subsequent bioinformatic analysis was conducted, as described in Drake et al. (2022). In summary, DNA was extracted from a subsample of faecal material and amplified using two metabarcoding primer pairs, designed to amplify regions of the 16S rRNA and cytochrome c oxidase subunit I (COI) genes, each primer having 10 base pair molecular identifier tags (MID tags) to facilitate post-bioinformatic sample identification.Two primer sets from different barcoding regions were selected to overcome biases associated with each region and broaden the range of taxa amplified: the 16S barcoding region selected for vertebrate DNA, and cytochrome c oxidase subunit I (COI) for invertebrate DNA. For 16S, the novel primer pair FN2199 (5’- yayaagacgagaagaccct -3’) and R8B7 (5’- ttatccctrgggtarcthgg -3’; modified for this study from Deagle et al. 2009) were used, which targeted a 225-267 bp amplicon (including primers). For COI, the primer pair Mod_mCOIintF (5’- ggwacwggwtgaacwgtwtaycc -3’; modified for this study from Leray et al. 2013) and HCO-2198 (5’- taaacttcagggtgaccaaaaaatca -3’; Folmer et al. 1994) were used, which targeted a 365 bp amplicon (including primers). Primers underwent in silico testing using ecoPCR (Boyer et al. 2016) and were further tested in vitro. In silico and vitro tests showed primer sets amplified desired taxa. COI primers were also found to amplify a range of vertebrate taxa but did not cover the same range as the 16S primers, therefore justifying the use of both primer sets beyond the benefit of different primer pairs exhibiting different biases.Faecal samples were processed alongside extraction and PCR negative controls, repeat samples, and mock communities, which comprised standardised mixtures of DNA of

These data consist of measures of Internet use estimated using small area estimation. The small area estimation is based on census Output Areas (OAs) using the 2013 Oxford Internet Survey (OxIS) and the 2011 British census. There is an estimate for each OA in Great Britain. By combining the 2013 OxIS survey data with the comprehensive small area coverage of the 2011 British census we can use the strengths of one to offset the gaps in the other. Specifically, we follow a two-step process. First, we use the information that is reliably available in OxIS to create model that estimates the proportion of Internet users in OAs. Second, we use the parameters from this model combined with census data to estimate the proportion of Internet users each OA in Britain. Once these estimates are available, we aggregate the estimates up to higher levels of geography. In this way we can estimate Internet use in Glasgow, Manchester and Cardiff as well as other small areas in Britain. This procedure is referred to as indirect, model-based or synthetic estimation. In recent years such SAE techniques have been widely used throughout Europe and North America. See the project website for more details.The objective of the Geography of Digital Inequality project was to explore the geographical contours of Internet use and penetration in Britain. Specifically, the project assembled from existing datasets a new dataset which contains Internet information at fine-grained geographic levels, census output areas (OAs). From OAs we were able to aggregate to higher geographic levels such as counties, Welsh and Scottish Councils, metropolitan areas, or others. Through this unique dataset we explored digital divides and the geography of the Internet, a capability possessed by no other dataset. Specifically, we explored the extent of use versus non-use of the Internet. There were 2 datasets used to assemble this dataset. First, the 2013 Oxford Internet Survey (OxIS) is a random sample of the 2657 people age 14+ from the British population (England, Scotland & Wales). Interviews were conducted face-to-face by an independent survey research company. The response rate for 2013 was 51%. The data collection was a two-stage sample. A random sample of census output areas (OAs) was selected and respondents were randomly sampled within each selected OA. For details, see "Data collection technical report.pdf" which has been uploaded. We use six variables from OxIS: Internet use, region, age, lifestage, gender and education. The questionnaire for OxIS contains about 300 variables and it is available from the OxIS website, see the URL in the "related resources" section. Second, the 2011 British Census. For information on how the census was conducted,see the census website. The URL for the 2011 census is given below in "related resources".

In 2023/24 there were estimated to be over *** million students enrolled in higher education courses in the United Kingdom, compared with 2.94 million in 2022/23, the highest number of enrolled students during this provided time period. Although the number of students in the UK fell from *** million in 2011/12 to **** by 2014/15, this trend reversed in subsequent years, reaching the peak in the most recent year. Largest UK universities At ******* students, the mainly remote, Open University had the largest number of students enrolled among UK-based higher education institutions in 2022/23. University College London had the second-highest number of students at ******, followed by the University of Manchester at ******. At the UK's two oldest and most prestigious universities, Oxford and Cambridge, there were ******, and ****** students respectively. The university with the most students in Scotland was the University of Glasgow at *******students, with Wales' being Cardiff University at ****** students, and Northern Ireland's Ulster University having ****** students. Student Debt in the UK For students that graduated from English universities in 2024, the average student loan debt incurred over the course of their studies was over ****** British pounds. Although students graduated with less debt from universities in Wales, Northern Ireland, and especially Scotland, this too has been growing recently. In 2024, students from Scottish Universities graduated with an average of ****** pounds of debt, compared with ****** in Wales, and ****** in Northern Ireland. The overall outstanding student loan debt in the UK reached over *** billion pounds in 2023/24, with the vast majority of this debt from students who studied in England.

This dataset contains information from the Office for National Statistics internal migration data for Wales, showing the migrant flows into and out of each local authority in Wales (and Wales itself) to and from other parts of the UK, and also a net position, by sex and quinary (five-year) age group. Note that data for Wales as a whole will not be the sum of individual local authority data as moves between local authorities within Wales will not contribute to the flows into or out of Wales.