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AbstractEnvironmental histories that span the last full glacial cycle and are representative of regional change in Australia are scarce, hampering assessment of environmental change preceding and concurrent with human dispersal on the continent ca. 47,000 years ago. Here we present a continuous 150,000-year record offshore south-western Australia and identify the timing of two critical late Pleistocene events: wide-scale ecosystem change and regional megafaunal population collapse. We establish that substantial changes in vegetation and fire regime occurred ∼70,000 years ago under a climate much drier than today. We record high levels of the dung fungus Sporormiella, a proxy for herbivore biomass, from 150,000 to 45,000 years ago, then a marked decline indicating megafaunal population collapse, from 45,000 to 43,100 years ago, placing the extinctions within 4,000 years of human dispersal across Australia. These findings rule out climate change, and implicate humans, as the primary extinction cause.

Abstract Weather and climate variations on subseasonal to decadal time scales can have enormous social, economic, and environmental impacts, making skillful predictions on these time scales a valuable tool for decision-makers. As such, there is a growing interest in the scientific, operational, and applications communities in developing forecasts to improve our foreknowledge of extreme events. On subseasonal to seasonal (S2S) time scales, these include high-impact meteorological events such as tropical cyclones, extratropical storms, floods, droughts, and heat and cold waves. On seasonal to decadal (S2D) time scales, while the focus broadly remains similar (e.g., on precipitation, surface and upper-ocean temperatures, and their effects on the probabilities of high-impact meteorological events), understanding the roles of internal variability and externally forced variability such as anthropogenic warming in forecasts also becomes important. The S2S and S2D communities share common scientific and technical challenges. These include forecast initialization and ensemble generation; initialization shock and drift; understanding the onset of model systematic errors; bias correction, calibration, and forecast quality assessment; model resolution; atmosphere–ocean coupling; sources and expectations for predictability; and linking research, operational forecasting, and end-user needs. In September 2018 a coordinated pair of international conferences, framed by the above challenges, was organized jointly by the World Climate Research Programme (WCRP) and the World Weather Research Programme (WWRP). These conferences surveyed the state of S2S and S2D prediction, ongoing research, and future needs, providing an ideal basis for synthesizing current and emerging developments in these areas that promise to enhance future operational services. This article provides such a synthesis.

Numerous studies show that increasing species richness leads to higher ecosystem productivity. This effect is often attributed to more efficient portioning of multiple resources in communities with higher numbers of competing species, indicating the role of resource supply and stoichiometry for biodiversity–ecosystem functioning relationships. Here, we merged theory on ecological stoichiometry with a framework of biodiversity–ecosystem functioning to understand how resource use transfers into primary production. We applied a structural equation model to define patterns of diversity–productivity relationships with respect to available resources. Meta-analysis was used to summarize the findings across ecosystem types ranging from aquatic ecosystems to grasslands and forests. As hypothesized, resource supply increased realized productivity and richness, but we found significant differences between ecosystems and study types. Increased richness was associated with increased productivity, although this effect was not seen in experiments. More even communities had lower productivity, indicating that biomass production is often maintained by a few dominant species, and reduced dominance generally reduced ecosystem productivity. This synthesis, which integrates observational and experimental studies in a variety of ecosystems and geographical regions, exposes common patterns and differences in biodiversity–functioning relationships, and increases the mechanistic understanding of changes in ecosystems productivity.

This paper analyses the environmental impacts of electric automated minibuses operated in public transportation systems. The results are based on an environmental life cycle assessment study, which uses data from a minibus producer and field data from several European cities. It is shown that electric automated minibuses promise a reduction in environmental impacts within specific conditions and in several future settings. Their environmental performance largely depends on their average utilisation, lifetime and total mileage, the electricity mix used, and the substituted means of transport. Automated components affect environmental performance but are not its most important driver. The minibus’s contribution to climate change in near-future use cases is expected at 78 g carbon dioxide equivalents per passenger kilometre on average and only 39 g at peak operation.

El Niño events are characterized by surface warming of the tropical Pacific Ocean and weakening of equatorial trade winds that occur every few years. Such conditions are accompanied by changes in atmospheric and oceanic circulation, affecting global climate, marine and terrestrial ecosystems, fisheries and human activities. The alternation of warm El Niño and cold La Niña conditions, referred to as the El Niño-Southern Oscillation (ENSO), represents the strongest year-to-year fluctuation of the global climate system. Here we provide a synopsis of our current understanding of the spatio-temporal complexity of this important climate mode and its influence on the Earth system.

Abstract Environmental as well as financial issues forces to develop clean, efficient, and sustainable vehicles which constitutes an integral part of our daily life for urban transportation. Nevertheless, exhaust emissions of conventional internal combustion engine vehicles are the major source of global warming lead greenhouse effect. One solution for this issue is hybridization/electrification of the vehicles. One of the most important tools which can help to test performances of technical solutions systematically is driving cycles representing real driving conditions for vehicle emissions testing and estimation. When the history of the driving cycles was reviewed, it can be seen that there were big changes from constructing synthetically to real world cycles and from emission-focused cycles to emission, pollution and fuel consumption focused cycles. And now, a new application such as hybridization and/or electrification has been added to driving cycles. Main aim of this study is to create a practical driving cycle for Bus Rapid Transit (BRT) vehicles. To do this, characteristic driving parameters such as speed, distance, time, acceleration have been determined first. Data acquisition from conventional vehicles running on Istanbul route was performed and then data were analysed. A driving cycle was developed by using Proportional Stratified Sampling (PSS) technique. Comparison between constructed driving cycle and the real-world data show that difference is less than 10%. And so, it can be concluded that proposed driving cycle was acceptable.