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China is confronted with an unprecedented water crisis regarding its quantity and quality. In this study, we quantified the dynamics of China?s embodied water use and chemical oxygen demand (COD) discharge from 2010 to 2015. The analysis was conducted with the latest available water use data across sectors in primary, secondary and tertiary industries and input?output models. The results showed that (1) China?s water crisis was alleviated under urbanisation. Urban consumption occupied the largest percentages (over 30%) of embodied water use and COD discharge, but embodied water intensities in urban consumption were far lower than those in rural consumption. (2) The ?new normal? phase witnessed the optimisation of China?s water use structures. Embodied water use in light-manufacturing and tertiary sectors increased while those in heavy-manufacturing sectors (except chemicals and transport equipment) dropped. (3) Transformation of China?s international market brought positive effects on its domestic water use. China?s water use (116?80 billion tonnes (Bts))(9) and COD discharge (3.95?2.22 million tonnes (Mts)) embodied in export tremendously decreased while its total export values (11?25 trillion CNY) soared. Furthermore, embodied water use and COD discharge in relatively low-end sectors, such as textile, started to transfer from international to domestic markets when a part of China?s production activities had been relocated to other developing countries.

What present-day foragers do for their living and what they eat have long been privileged areas for exploring human behavior, global health, and human evolution. While many studies have focused on hunting and meat acquisition, less attention has been given to gathering and plant foods. Despite evidence of variation in both nutritional quality and energetic costs of gathering different plants, the overall effort spent on gathering in relation to other subsistence tasks is still under explored. In the current context of economic, climate, and social changes, many forager societies also rely on other subsistence strategies, including agriculture and wage labor. In this study, we aim to explore the place of gathering in the livelihood of a mixed economy society, the Baka forager-horticulturalists of southeastern Cameroon, by comparing the involvement and the costs of activities related to food acquisition. From a pool of 153 adult participants (97 women and 56 men), we collected 246 daily records using a GPS (Global Positioning System) tracker combined with heart rate monitor and time allocation recalls. We compared the duration, distance traveled, and the intensity of work, measured by calculating the metabolic equivalent of task (MET), of subsistence activities related to food acquisition. Results from this work show that gathering activities, performed by both women and men, are energetically costly, with higher MET values than hunting and fishing activities. Furthermore, the MET values vary depending on the targeted plant foods. We discuss these insights in the overall framework of subsistence patterns, merging them with the socio-cultural and environmental factors that might explain Baka livelihood and subsistence strategy.

The functional trait framework provides a powerful corpus of integrated concepts and theories to assess how environmental factors influence ecosystem functioning through community assembly. While common in plant ecology, this approach is under-used in microbial ecology. After an introduction of this framework in the context of microbial ecology and enzymology, we propose an approach 1) to elucidate new links between soil microbial community composition and microbial traits; and 2) to disentangle mechanisms underlying “total” potential enzyme activity in soil (sum of 7 hydrolase potential activities). We address these objectives using a terrestrial grassland ecosystem model experiment with intact soil monoliths from three European countries (Switzerland, France and Portugal) and two management types (Conventional-intensive and Ecological-intensive), subjected to 4 rain regimes (Dry, Wet, Intermittent and Normal) under controlled conditions in a common climate chamber. We found tight associations between proxies of microbial ecoenzymatic community-weighted mean traits (enzymatic stoichiometry and biomass-specific activity) and community composition, bringing new information on resource acquisition strategy associated with fungi, Gram positive and Gram negative bacteria. We demonstrate that microbial biomass explained most of the total enzyme activity before altered rain regimes, whereas adjustments in biomass-specific activity (enzyme activity per unit of microbial biomass) explained most variation under altered rain regime scenarios. Furthermore, structural equation models revealed that the variation of community composition was the main driver of the variation in biomass-specific enzyme activity prior to rain perturbation, whereas physiological acclimation or evolutionary adaptation became an important driver only under altered rain regimes. This study presents a promising trait-based approach to investigate soil microbial community response to environmental changes and potential consequences for ecosystem functioning. We argue that the functional trait framework should be further implemented in microbial ecology to guide experimental and analytical design.

Abstract. This paper aims to assess the spatial variability in the response of CO2 exchange to irradiance across the Arctic tundra during peak season using light response curve (LRC) parameters. This investigation allows us to better understand the future response of Arctic tundra under climatic change. Peak season data were collected during different years (between 1998 and 2010) using the micrometeorological eddy covariance technique from 12 circumpolar Arctic tundra sites, in the range of 64–74° N. The LRCs were generated for 14 days with peak net ecosystem exchange (NEE) using an NEE–irradiance model. Parameters from LRCs represent site-specific traits and characteristics describing the following: (a) NEE at light saturation (Fcsat), (b) dark respiration (Rd), (c) light use efficiency (α), (d) NEE when light is at 1000 μmol m−2 s−1 (Fc1000), (e) potential photosynthesis at light saturation (Psat) and (f) the light compensation point (LCP). Parameterization of LRCs was successful in predicting CO2 flux dynamics across the Arctic tundra. We did not find any trends in LRC parameters across the whole Arctic tundra but there were indications for temperature and latitudinal differences within sub-regions like Russia and Greenland. Together, leaf area index (LAI) and July temperature had a high explanatory power of the variance in assimilation parameters (Fcsat, Fc1000 and Psat, thus illustrating the potential for upscaling CO2 exchange for the whole Arctic tundra. Dark respiration was more variable and less correlated to environmental drivers than were assimilation parameters. This indicates the inherent need to include other parameters such as nutrient availability, substrate quantity and quality in flux monitoring activities.

In the future, the Baltic Sea ecosystem will be impacted both by climate change and by riverine and atmospheric nutrient inputs. Multi-model ensemble simulations comprising one IPCC scenario (A1B), two global climate models, two regional climate models, and three Baltic Sea ecosystem models were performed to elucidate the combined effect of climate change and changes in nutrient inputs. This study focuses on the occurrence of extreme events in the projected future climate. Results suggest that the number of days favoring cyanobacteria blooms could increase, anoxic events may become more frequent and last longer, and salinity may tend to decrease. Nutrient load reductions following the Baltic Sea Action Plan can reduce the deterioration of oxygen conditions.

The declaration of 2014-2024 as the Decade of Sustainable Energy for All has catalyzed actions towards achieving universal electricity access. The high costs of building electric infrastructure are a major impediment to improved access, making stand-alone photovoltaic (PV) systems an attractive solution in remote areas. Here, we analyze the cost-effective electrification solution for Kenya comparing grid extension with stand-alone PV systems. We use micro-data from a national household survey to estimate electricity demand for households that are within reach of electricity infrastructure and to predict latent demand in unconnected households. These regional demands are used in a spatially explicit supply model to seek for a least cost electrification solution. Our results suggest that decentralized PV systems can make an important contribution in areas, with low demand and high connection costs. We find that up to 17% of the population can be reached cost-effectively by off-grid PV systems till 2020.