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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.

AbstractLeymus chinensis is a dominant species in the Inner Mongolia steppe, northern China. Plant growth in northern China grassland is often limited by low soil nitrogen availability. The objective of this study is to investigate whether rhizomes of Leymus chinensis are involved in the contribution of N uptake. The N concentration, 15N concentration and 15N proportion in roots, rhizomes and shoots after 48 h exposure of roots (Lroot) and rhizomes (Lrhizo) separately and roots and rhizomes together (Lr+r) to 0.1 mM 15NHNO3 solution were measured using root‐splitting equipment and stable isotope (15N) techniques, respectively. The N content and dry mass were not affected by the labeling treatment. In contrast, the 15N concentration in shoots, rhizomes and roots was significantly increased by the labeling in rhizomes, indicating that the inorganic nitrogen was absorbed via rhizomes from the solution and can be transported to other tissues, with preference to shoots rather than roots. Meanwhile, the absolute N absorption and translocation among compartments were also calculated. The N absorption via rhizomes was much smaller than via roots; however, the uptake efficiency per surface unit via rhizomes was greater than via roots. The capacity and high efficiency to absorb N nutrient via rhizomes enable plants to use transient nutrient supplies in the top soil surface. Copyright © 2011 John Wiley & Sons, Ltd.

Aromatic hydrocarbons (AHs) are both hazardous air pollutants and important precursors to ozone and secondary organic aerosols. Here we investigated 14 C6-C9 AHs at one urban, one suburban and two rural sites in the Pearl River Delta region during November-December 2009. The ratios of individual aromatics to acetylene were compared among these contrasting sites to indicate their difference in source contributions from solvent use and vehicle emissions. Ratios of toluene to benzene (T/B) in urban (1.8) and suburban (1.6) were near that of vehicle emissions. Higher T/B of 2.5 at the rural site downwind the industry zones reflected substantial contribution of solvent use while T/B of 0.8 at the upwind rural site reflected the impact of biomass burning. Source apportionment by positive matrix factorization (PMF) revealed that solvent use, vehicle exhaust and biomass burning altogether accounted for 89-94% of observed AHs. Vehicle exhaust was the major source for benzene with a share of 43-70% and biomass burning in particular contributed 30% to benzene in the upwind rural site; toluene, C8-aromatics and C9-aromatics, however, were mainly from solvent use, with contribution percentages of 47-59%, 52-59% and 41-64%, respectively.