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\"British culture today is the product of a shifting combination of tradition and experimentation, national identity and regional and ethnic diversity. These distinctive tensions are expressed in a range of cultural arenas, such as art, sport, journalism, fashion, education, and race. This Companion addresses these and other major aspects of British culture, and offers a sophisticated understanding of what it means to study and think about the diverse cultural landscapes of contemporary Britain. Each contributor looks at the language through which culture is formed and expressed, the political and institutional trends that shape culture, and at the role of culture in daily life. This interesting and informative account of modern British culture embraces controversy and debate, and never loses sight of the fact that Britain and Britishness must always be understood in relation to the increasingly international context of globalisation\"-- Provided by publisher.

Smoke from Hazard Reduction Burns (HRBs) and wildfires contains pollutants that are harmful to human health. This includes particulate matter less than 2.5 μm in diameter (PM 2.5 ), which affects human cardiovascular and respiratory systems and can lead to increased hospitalisations and premature deaths. Better models are needed to predict PM 2.5 levels associated with HRBs so that agencies can properly assess smoke pollution risk and balance smoke risk with the wildfire mitigation benefits of HRBs. Given this need, our aim was to develop a probabilistic model of daily PM 2.5 using Bayesian regression. We focused on the region around Sydney, Australia, which regularly has hazard reduction burning, wildfires and associated smoke. We developed two regional models (mean daily and maximum daily) from observed PM 2.5 , weather reanalysis and satellite fire hotspot data. The models predict that the worst PM 2.5 in Sydney occurs when PM 2.5 was high the previous day, there is low ventilation index (i.e. the product of wind speed and planetary boundary layer height), low temperature, west to northwest winds in the Blue Mountains, an afternoon sea breeze and large areas of HRBs are being conducted, particularly to the west and north of Sydney. A major benefit of our approach is that models are fast to run, require simple inputs and Bayesian predictions convey both predicted PM 2.5 and associated prediction uncertainty. Future research could include the application of similar methods to other regions, collecting more data to improve model precision and developing Bayesian PM 2.5 models for wildfires.

H omo erectus is the founding early hominin species of Island Southeast Asia, and reached Java (Indonesia) more than 1.5 million years ago 1 , 2 . Twelve H. erectus calvaria (skull caps) and two tibiae (lower leg bones) were discovered from a bone bed located about 20 m above the Solo River at Ngandong (Central Java) between 1931 and 1933 3 , 4 , and are of the youngest, most-advanced form of H. erectus 5 – 8 . Despite the importance of the Ngandong fossils, the relationship between the fossils, terrace fill and ages have been heavily debated 9 – 14 . Here, to resolve the age of the Ngandong evidence, we use Bayesian modelling of 52 radiometric age estimates to establish—to our knowledge—the first robust chronology at regional, valley and local scales. We used uranium-series dating of speleothems to constrain regional landscape evolution; luminescence, 40 argon/ 39 argon ( 40 Ar/ 39 Ar) and uranium-series dating to constrain the sequence of terrace evolution; and applied uranium-series and uranium series–electron-spin resonance (US–ESR) dating to non-human fossils to directly date our re-excavation of Ngandong 5 , 15 . We show that at least by 500 thousand years ago (ka) the Solo River was diverted into the Kendeng Hills, and that it formed the Solo terrace sequence between 316 and 31 ka and the Ngandong terrace between about 140 and 92 ka. Non-human fossils recovered during the re-excavation of Ngandong date to between 109 and 106 ka (uranium-series minimum) 16 and 134 and 118 ka (US–ESR), with modelled ages of 117 to 108 thousand years (kyr) for the H. erectus bone bed, which accumulated during flood conditions 3 , 17 . These results negate the extreme ages that have been proposed for the site and solidify Ngandong as the last known occurrence of this long-lived species. Bayesian modelling of radiometric age estimates provides a robust chronology for Homo erectus at Ngandong (Java), confirming that this site currently represents the last known occurrence of this species.

New excavations in Liang Bua, where the remains of the ‘Hobbit’ ( Homo floresiensis ) were discovered, show that this diminutive human species used this cave between 190,000 and 50,000 years ago, and not until as recently as 12,000 years ago as previously interpreted; modern humans have been present in Australia since around 50,000 years ago, so whether Homo floresiensis survived long enough to witness the arrival of modern humans is still an open question. An earlier date for Homo floresiensis The discovery in Liang Bua cave on the island of Flores in Indonesia of the diminutive Homo floresiensis , an archaic member of the human family commonly known as the 'Hobbit', was an archaeological sensation in 2004. A source of considerable debate was the fact that it lived in Liang Bua cave between 95,000 and 12,000 years ago, after modern humans had colonized the area (around 50,000 years ago). Thomas Sutikna and colleagues — including many of the original research team — have gone back to Liang Bua, where new excavations have exposed previously unexplored parts of the cave. They have found that the layers of sediment in the cave are not deposited evenly, and it now seems that the H. floresiensis -bearing strata are older than was thought. New radiometric dating places the H. floresiensis remains and stone artefacts to between 190,000 and 50,000 years ago. Whether H. floresiensis survived long enough to witness the arrival of modern humans is an open question. Homo floresiensis , a primitive hominin species discovered in Late Pleistocene sediments at Liang Bua (Flores, Indonesia) 1 , 2 , 3 , has generated wide interest and scientific debate. A major reason this taxon is controversial is because the H. floresiensis -bearing deposits, which include associated stone artefacts 2 , 3 , 4 and remains of other extinct endemic fauna 5 , 6 , were dated to between about 95 and 12 thousand calendar years (kyr) ago 2 , 3 , 7 . These ages suggested that H. floresiensis survived until long after modern humans reached Australia by ~50 kyr ago 8 , 9 , 10 . Here we report new stratigraphic and chronological evidence from Liang Bua that does not support the ages inferred previously for the H. floresiensis holotype (LB1), ~18 thousand calibrated radiocarbon years before present (kyr cal. bp ), or the time of last appearance of this species (about 17 or 13–11 kyr cal. bp ) 1 , 2 , 3 , 7 , 11 . Instead, the skeletal remains of H. floresiensis and the deposits containing them are dated to between about 100 and 60 kyr ago, whereas stone artefacts attributable to this species range from about 190 to 50 kyr in age. Whether H. floresiensis survived after 50 kyr ago—potentially encountering modern humans on Flores or other hominins dispersing through southeast Asia, such as Denisovans 12 , 13 —is an open question.

We analysed the influence of wildfire area, topography, fuel, surface weather and upper-level weather conditions on long-distance spotting during wildfires. The analysis was based on a large dataset of 338 observations, from aircraft-acquired optical line scans, of spotting wildfires in south-east Australia between 2002 and 2018. Source fire area (a measure of fire activity) was the most important predictor of maximum spotting distance and the number of long-distance spot fires produced (i.e. >500 m from a source fire). Weather (surface and upper-level), vegetation and topographic variables had important secondary effects. Spotting distance and number of long-distance spot fires increased strongly with increasing source fire area, particularly under strong winds and in areas containing dense forest and steep slopes. General vegetation descriptors better predicted spotting compared with bark hazard and presence variables, suggesting systems that measure and map bark spotting potential need improvement. The results from this study have important implications for the development of predictive spotting and wildfire behaviour models.

New excavations in Sulawesi, where in situ stone artefacts associated with fossil remains of megafauna have been recovered from stratified deposits between 200,000 and 100,000 years ago, suggest that Sulawesi was host to a long-established population of archaic hominins. Sulawesi is the largest and oldest island within Wallacea, a vast zone of oceanic islands separating continental Asia from the Pleistocene landmass of Australia and Papua (Sahul). By one million years ago an unknown hominin lineage had colonized Flores immediately to the south 1 , and by about 50 thousand years ago, modern humans ( Homo sapiens ) had crossed to Sahul 2 , 3 . On the basis of position, oceanic currents and biogeographical context, Sulawesi probably played a pivotal part in these dispersals 4 . Uranium-series dating of speleothem deposits associated with rock art in the limestone karst region of Maros in southwest Sulawesi has revealed that humans were living on the island at least 40 thousand years ago (ref. 5 ). Here we report new excavations at Talepu in the Walanae Basin northeast of Maros, where in situ stone artefacts associated with fossil remains of megafauna ( Bubalus sp., Stegodon and Celebochoerus ) have been recovered from stratified deposits that accumulated from before 200 thousand years ago until about 100 thousand years ago. Our findings suggest that Sulawesi, like Flores, was host to a long-established population of archaic hominins, the ancestral origins and taxonomic status of which remain elusive.

Spotting is thought to increase wildfire rate of spread (ROS) and in some cases become the main mechanism for spread. The role of spotting in wildfire spread is controlled by many factors including fire intensity, number of and distance between spot fires, weather, fuel characteristics and topography. Through a set of 30 laboratory fire experiments on a 3 m x 4 m fuel bed, subject to air flow, we explored the influence of manually ignited spot fires (0, 1 or 2), the presence or absence of a model hill and their interaction on combined fire ROS (i.e. ROS incorporating main fire and merged spot fires). During experiments conducted on a flat fuel bed, spot fires (whether 1 or 2) had only a small influence on combined ROS. Slowest combined ROS was recorded when a hill was present and no spot fires were ignited, because the fires crept very slowly downslope and downwind of the hill. This was up to, depending on measurement interval, 5 times slower than ROS in the flat fuel bed experiments. However, ignition of 1 or 2 spot fires (with hill present) greatly increased combined ROS to similar levels as those recorded in the flat fuel bed experiments (depending on spread interval). The effect was strongest on the head fire, where spot fires merged directly with the main fire, but significant increases in off-centre ROS were also detected. Our findings suggest that under certain topographic conditions, spot fires can allow a fire to overcome the low spread potential of downslopes. Current models may underestimate wildfire ROS and fire arrival time in hilly terrain if the influence of spot fires on ROS is not incorporated into predictions.

Wildfires and hazard reduction burns produce smoke that contains pollutants including particulate matter. Particulate matter less than 2.5 µm in diameter (PM2.5) is harmful to human health, potentially causing cardiovascular and respiratory issues that can lead to premature deaths. PM2.5 levels depend on environmental conditions, fire behaviour and smoke dispersal patterns. Fire management agencies need to understand and predict PM2.5 levels associated with a particular fire so that pollution warnings can be sent to communities and/or hazard reduction burns can be timed to avoid the worst conditions for PM2.5 pollution. We modelled PM2.5, measured at air quality stations in New South Wales (Australia) from ∼ 1400 d when individual fires were burning near air quality stations, as a function of fire and weather variables. Using Visible Infrared Imaging Radiometer Suite (VIIRS) satellite hotspots, we identified days when one fire was burning within 150 km of at least 1 of 48 air quality stations. We extracted ERA5 gridded weather data and daily active fire area estimates from the hotspots for our modelling. We created random forest models for afternoon, night and morning PM2.5 levels to understand drivers of and predict PM2.5. Fire area and boundary layer height were important predictors across the models, with temperature, wind speed and relative humidity also being important. There was a strong increase in PM2.5 with decreasing distance, with a sharp increase when the fire was within 20 km. The models improve our understanding of the drivers of PM2.5 from individual fires and demonstrate a promising approach to PM2.5 model development. However, although the models predicted well overall, there were several large under-predictions of PM2.5 that mean further model development would be required for the models to be deployed operationally.

The Toba supereruption in Sumatra, ∼74 thousand years (ka) ago, was the largest terrestrial volcanic event of the Quaternary. Ash and sulfate aerosols were deposited in both hemispheres, forming a time-marker horizon that can be used to synchronize late Quaternary records globally. A precise numerical age for this event has proved elusive, with dating uncertainties larger than the millennial-scale climate cycles that characterized this period. We report an astronomically calibrated ⁴⁰Ar/ ³⁹Ar age of 73.88 ± 0.32 ka (1σ, full external errors) for sanidine crystals extracted from Toba deposits in the Lenggong Valley, Malaysia, 350 km from the eruption source and 6 km from an archaeological site with stone artifacts buried by ash. If these artifacts were made by Homo sapiens , as has been suggested, then our age indicates that modern humans had reached Southeast Asia by ∼74 ka ago. Our ⁴⁰Ar/ ³⁹Ar age is an order-of-magnitude more precise than previous estimates, resolving the timing of the eruption to the middle of the cold interval between Dansgaard–Oeschger events 20 and 19, when a peak in sulfate concentration occurred as registered by Greenland ice cores. This peak is followed by a ∼10 °C drop in the Greenland surface temperature over ∼150 y, revealing the possible climatic impact of the eruption. Our ⁴⁰Ar/ ³⁹Ar age also provides a high-precision calibration point for other ice, marine, and terrestrial archives containing Toba sulfates and ash, facilitating their global synchronization at unprecedented resolution for a critical period in Earth and human history beyond the range of ¹⁴C dating.

Landscape fires emit smoke that contains particulate matter (PM) that can be harmful to human health. Prescribed fires or hazard reduction burns (HRBs) and wildfires can substantially reduce air quality in populated areas. While HRBs reduce the size and PM output of future wildfires, they also produce PM. There is a critical question of whether conducting HRBs adds to or reduces the total PM (prescribed + wildfire PM) exposure of populations, which has important community health implications. We modelled mean 24 h PM2.5 in Sydney from fire type, 24 h active regional fire area and weather predictors. We compared HRB and wildfire area effects via an interaction between fire area and fire type, and we found that a non-linear effect of fire area was most appropriate. We conducted a trade-off analysis by using the model to predict increased HRB area scenarios and calculated the number of HRB and wildfire days with ‘Fair’ or worse air quality under each scenario. Regional HRBs and wildfire areas had similar effects on PM2.5 in Sydney. Increasing regional HRB area produced substantial increases in HRB exceedance days (>12.5 µgm−3) in Sydney but only a small reduction in wildfire exceedance days. Our results indicate that small fires in the region have a higher per-hectare impact on PM levels in Sydney, and consequently, increasing regional HRB area would result in more poor air quality days overall (HRB + wildfire days) in Sydney.