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Исследование ландшафтов всегда было традиционным научным направлением географии. В России подобная направленность исследований остаётся актуальной, несмотря на то, что термины «геоэкология» и «ландшафтная экология» сегодня более распространены в англоязычном научном сообществе. Наш краткий обзор показывает значительное ускорение антропогенных ландшафтных изменений в Европе, Центральной Азии и азиатской части России за последние пять десятилетий. Ландшафтные исследования в антропоцене должны быть направлены на достижение и сохранение устойчивости ландшафта при его высокой производительности, что включает в себя прекращение деградации ландшафтов, развитие культурных и сохранение природных ландшафтов. Чистая вода и чистый воздух, плодородные и здоровые почвы для производства продуктов питания и других экосистемных услуг, а также биологически разнообразная зеленая среда являются атрибутами ландшафтов, обеспечивающих выживание и благополучие населения. Дисциплинарные и междисциплинарные исследования должны генерировать знания, инновации и правила принятия действенных решений. Генерация знаний в глобализованном мире основана на сборе больших массивов данных и моделировании сценариев. Международные длительные полевые опыты и системы агроэкологического мониторинга будут предоставлять данные для экосистемных моделей и систем поддержки принимаемых решений. Landscape research has been a traditional scientific discipline of geography. This is still the case in Russia, whilst the terms geo-ecology and landscape ecology have become established in the English speaking scientific community. Our short review reveals huge and accelerating anthropogenic landscape transformations in Europe, Central Asia and Asian Russia since the end the 1960s. Landscape research in the Anthropocene has to focus on achieving landscape sustainability at high productivity. This includes halting landscape degradation, developing cultural landscapes, and maintaining semi-natural landscapes. Clean water and air, fertile and healthy soils for food and other ecosystem services and a green and bio-diverse environment are attributes of landscapes for the survival and well-being of humans. Research has to generate knowledge, innovations and decision rules by disciplinary, interdisciplinary and trans-disciplinary work. Knowledge generation in a globalized world is based on big data gathering and scenario modelling. International long-term experiments and agri-environmental monitoring systems will deliver data for ecosystem models and decision support systems.

Most of the world’s mountain glaciers have been retreating for more than a century in response to climate change. Glacier retreat is evident on all continents, and the rate of retreat has accelerated during recent decades. Accurate, spatially explicit information on the position of glacier margins over time is useful for analyzing patterns of glacier retreat and measuring reductions in glacier surface area. This information is also essential for evaluating how mountain ecosystems are evolving due to climate warming and the attendant glacier retreat. Here, we present a non-comprehensive spatially explicit dataset showing multiple positions of glacier fronts since the Little Ice Age (LIA) maxima, including many data from the pre-satellite era. The dataset is based on multiple historical archival records including topographical maps; repeated photographs, paintings, and aerial or satellite images with a supplement of geochronology; and own field data. We provide ESRI shapefiles showing 728 past positions of 94 glacier fronts from all continents, except Antarctica, covering the period between the Little Ice Age maxima and the present. On average, the time series span the past 190 years. From 2 to 46 past positions per glacier are depicted (on average: 7.8).

This study highlights how Chinese economic development detrimentally impacted water quality in recent decades and how this has been improved by enormous investment in environmental remediation funded by the Chinese government. To our knowledge, this study is the first to describe the variability of surface water quality in inland waters in China, the affecting drivers behind the changes, and how the government-financed conservation actions have impacted water quality. Water quality was found to be poorest in the North and the Northeast China Plain where there is greater coverage of developed land (cities + cropland), a higher gross domestic product (GDP), and higher population density. There are significant positive relationships between the concentration of the annual mean chemical oxygen demand (COD) and the percentage of developed land use (cities + cropland), GDP, and population density in the individual watersheds (p < 0.001). During the past decade, following Chinese government-financed investments in environmental restoration and reforestation, the water quality of Chinese inland waters has improved markedly, which is particularly evident from the significant and exponentially decreasing GDP-normalized COD and ammonium (NH4+-N) concentrations. It is evident that the increasing GDP in China over the past decade did not occur at the continued expense of its inland water ecosystems. This offers hope for the future, also for other industrializing countries, that with appropriate environmental investments a high GDP can be reached and maintained, while simultaneously preserving inland aquatic ecosystems, particularly through management of sewage discharge.

Abstract Algae have been considered as a promising biodiesel feedstock. One of the major factors affecting large-scale algae technology application is poor wintering cultivation performance. In this study, an integrated approach is investigated combining freshwater microalgae Chlorella zofingiensis wintering cultivation in pilot-scale photobioreactors with artificial wastewater treatment. Mixotrophic culture with the addition of acetic acid (pH-regulation group) and autotrophic culture (control group) were designed, and the characteristics of algal growth, lipid and biodiesel production, and nitrogen and phosphate removal were examined. The results showed that, by using acetic acid three times per day to regulate pH at between 6.8 and 7.2, the total nitrogen (TN) and total phosphate (TP) removal could be increased from 45.2% to 73.5% and from 92.2% to 100%, respectively. Higher biomass productivity of 66.94 mg L−1 day−1 with specific growth rate of 0.260 day−1 was achieved in the pH-regulation group. The lipid content was much higher when using acetic acid to regulate pH, and the relative lipid productivity reached 37.48 mg L−1 day−1. The biodiesel yield in the pH-regulated group was 19.44% of dry weight, with 16–18 carbons as the most abundant composition for fatty acid methyl esters. The findings of the study prove that pH adjustment using acetic acid is efficient in cultivating C. zofingiensis in wastewater in winter for biodiesel production and nutrient reduction.

AbstractBecause of its low level of energy consumption and the small scale of its industrial development, the Tibet Autonomous Region has historically been excluded from China's reported energy statistics, including those regarding CO2 emissions. In this paper, we estimate Tibet's energy consumption using limited online documents, and we calculate the 2014 energy‐related and process‐related CO2 emissions of Tibet and its seven prefecture‐level administrative divisions for the first time. Our results show that 5.52 million tons of CO2 were emitted in Tibet in 2014; 33% of these emissions are associated with cement production. Tibet's emissions per capita amounted to 1.74 tons in 2014, which is substantially lower than the national average, although Tibet's emission intensity is relatively high at 0.60 tons per thousand yuan in 2014. Among Tibet's seven prefecture‐level administrative divisions, Lhasa City and Shannan Region are the two largest CO2 contributors and have the highest per capita emissions and emission intensities. The Nagqu and Nyingchi regions emit little CO2 due to their farming/pasturing‐dominated economies. This quantitative measure of Tibet's regional CO2 emissions provides solid data support for Tibet's actions on climate change and emission reductions.

AbstractClimate change globally affects soil microbial community assembly across ecosystems. However, little is known about the impact of warming on the structure of soil microbial communities or underlying mechanisms that shape microbial community composition in subtropical forest ecosystems. To address this gap, we utilized natural variation in temperature via an altitudinal gradient to simulate ecosystem warming. After 6 years, microbial co‐occurrence network complexity increased with warming, and changes in their taxonomic composition were asynchronous, likely due to contrasting community assembly processes. We found that while stochastic processes were drivers of bacterial community composition, warming led to a shift from stochastic to deterministic drivers in dry season. Structural equation modelling highlighted that soil temperature and water content positively influenced soil microbial communities during dry season and negatively during wet season. These results facilitate our understanding of the response of soil microbial communities to climate warming and may improve predictions of ecosystem function of soil microbes in subtropical forests.

Abstract The optimized green-grey infrastructures are promising solutions to combat the urban flood and water quality problems which have been severe owe to the increasing urbanization and climate change. However, the focusses in existing researches have been either on finding the best strategy by scenario analysis method or optimal design of LID practices under the hypothesis of unchanged grey infrastructures. Little is known regarding the synergistic effect of synchronous optimization design of both green and grey infrastructures. In the study, we conduct green-grey infrastructures synchronous optimization by modifying the decision variables of traditional simulation-optimization frameworks and investigate how external uncertainties will affect their performance. The methodology was applied to a case study in Suzhou, China. The results showed that although the cost of green-grey synchronous optimized scenarios is lower than that of green optimized only scenarios by 1.69–4.19 thousand USD per km2, the runoff/pollutants reductions of green-grey synchronous optimized scenarios are 0.11%–5.24% higher than that of green optimized only scenarios. In the green-grey synchronous optimized scenarios, green infrastructures can contribute to runoff/pollutants control by 50%–63%/62%–70%, while grey infrastructures can contribute to the remaining part by 37%–50%/30%–38%.