Plants control the seasonal dynamics of microbial N cycling in a beech forest soil by belowground C allocation

Soil microbes in temperate forest ecosystems are able to cycle several hundreds of kilograms of N per hectare per year and are therefore of paramount importance for N retention. Belowground C allocation by trees is an important driver of seasonal microbial dynamics and may thus directly affect N transformation processes over the course of the year. Our study aimed at unraveling plant controls on soil N cycling in a temperate beech forest at a high temporal resolution over a time period of two years, by investigating the effects of tree girdling on microbial N turnover. In both years of the experiment, we discovered (1) a summer N mineralization phase (between July and August) and (2) a winter N immobilization phase (November-February). The summer mineralization phase was characterized by a high N mineralization activity, low microbial N uptake, and a subsequent high N availability in the soil. During the autumn/winter N immobilization phase, gross N mineralization rates were low, and microbial N uptake exceeded microbial N mineralization, which led to high levels of N in the microbial biomass and low N availability in the soil. The observed immobilization phase during the winter may play a crucial role for ecosystem functioning, since it could protect dissolved N that is produced by autumn litter degradation from being lost from the ecosystem during the phase when plants are mostly inactive. The difference between microbial biomass N levels in winter and spring equals 38 kg N/ha and may thus account for almost one-third of the annual plant N demand. Tree girdling strongly affected annual N cycling: the winter N immobilization phase disappeared in girdled plots (microbial N uptake and microbial biomass N were significantly reduced, while the amount of available N in the soil solution was enhanced). This was correlated to a reduced fungal abundance in autumn in girdled plots. By releasing recently fixed photosynthates to the soil, plants may thus actively control the annual microbial N cycle. Tree belowground C allocation increases N accumulation in microorganisms during the winter which may ultimately feed back on plant N availability in the following growing season.     

Inside the radar: select elements in nanomaterials and sustainable nanotechnology

Rare earth elements and several metals formerly uncommon in commerce are being introduced into new products, particularly as nanoscaled materials. Until recently, little attention has been paid to their sustainability issues. This perspective addresses these elements, their commercial uses, health and environment issues, sustainability, and suggests a path forward.     

Human Adaptation to Work in Two Different Climates

The processes of acclimation to hot-dry and to warm-humid climates were studied using two approaches: a quantitative analysis of literature data and an experimental study in the laboratory concerning the physiological parameters of heart rate, rectal temperature, sweat loss, and subjective assessment.

Analysis o f literature data: Data from 62 experiments with a total of 813 participants were pooled and recalculated. The experiments ranged from 6 to 24 days, air temperatures from 30.4 to 50.0°C, water vapor pressures from 1.5 to 6.5 kPa, and wet bulb globe temperatures (WBGT) from 27.4 to 38.6°C.

Laboratory studies: In the laboratory, 8 participants were acclimated during 15 consecutive days to a hot-dry climate and to a warm-humid climate, which were equivalent in terms of the WBGT (33.5 and 33.6°C, respectively). The participants walked four times for 25 min on a treadmill at a speed of 4 km/h. The hot-dry climate caused somewhat greater strain than the warm-humid condition. In the course of acclimation to the hot-dry climate, heart rate and rectal temperature started at higher levels, decreased slightly steeper but remained on a higher level throughout. Nevertheless, the differences between both thermal conditions were small, and both physiologic functions reached the point of acclimation almost at the same time under warm-humid and under hot-dry exposure. Sweat loss, which is not regarded as a valid predictor for acclimation, was considerably higher but increased less in the hot-dry than in the warm-humid climate.     

Heat Gain From Thermal Radiation Through Protective Clothing With Different Insulation,Reflectivity and Vapour Permeability

The heat transferred through protective clothing under long wave radiation compared to a reference condition without radiant stress was determined in thermal manikin experiments. The influence of clothing insulation and reflectivity, and the interaction with wind and wet underclothing were considered. Garments with different outer materials and colours and additionally an aluminised reflective suit were combined with different number and types of dry and pre-wetted underwear layers. Under radiant stress, whole body heat loss decreased, i.e., heat gain occurred compared to the reference. This heat gain increased with radiation intensity, and decreased with air velocity and clothing insulation. Except for the reflective outer layer that showed only minimal heat gain over the whole range of radiation intensities, the influence of the outer garments’ material and colour was small with dry clothing. Wetting the underclothing for simulating sweat accumulation, however, caused differing effects with higher heat gain in less permeable garments.     

Architectural scoring framework for the creation and evaluation of System-Aware Cyber Security solutions

As cyber security threats have evolved, system protection strategies have been forced to as well. The field of System-Aware Cyber Security has introduced a variety of protection strategies and this has prompted the need for a decision support tool set to provide guidance to the system designers. This paper outlines an architectural scoring framework that supports the design and selection of architectural candidates and provides a rigorous quantitative method for the evaluation to aid in the selection of a final architecture. Additionally, this paper outlines the recognized limitations of the proposed approach and provides a brief overview of how those areas for improvement are guiding future research.     

Immunotoxicity of carbon black nanoparticles to blue mussel hemocytes

The potential for human and ecological toxicity associated with nanomaterials is a growing area of investigation. In mammalian cells, nanoparticles have been shown to induce inflammation and oxidative stress, and changes in cell signalling and gene expression. As the nanotechnology industries increase production, nanoscale products and by products will enter the aquatic environment, posing a possible threat to aquatic organisms. In particular, filter-feeding organisms may represent a unique target group for nanoparticle toxicology. In this work, the effects of commercial nanosized carbon black (NCB) on the immune cells, the hemocytes, of the bivalve mollusc Mytilus, and the possible mechanisms involved were investigated. The results demonstrate that NCB (1, 5, and 10 microg/ml), did not induce significant lysosomal membrane destabilization, as evaluated by the NR retention time assay. A concentration-dependent uptake of NCB by hemocytes was observed and it was associated by a rapid increase in extracellular lysozyme release, extracellular oxyradical production, and nitric oxide (NO) release. Moreover, at the highest concentration tested, NCB induced significant changes in mitochondrial parameters (decrease mitochondrial mass/number and membrane potential), as evaluated by flow cytometry. The effects of NCB were mediated by rapid activation of the stress-activated MAPKs (Mitogen Activated Protein Kinases) p38 and JNKs, that play a key role in immune and inflammatory responses. The results demonstrate that in mussel hemocytes like in mammalian cells NCB exposure can induce inflammatory processes, and indicate that bivalve immunocytes can represent a suitable model for investigating the effects and modes of action of nanoparticles in the cells of aquatic invertebrates.     

Coastal flood protection: What perspective in a changing climate? The THESEUS approach

Coastal areas are vital economic hubs in terms of settlement, industry, agriculture, trade and tourism to mention some key sectors. There are already many coastal problems including erosion, flood risk and long-term habitat deterioration. As economies continue to develop the asset base at risk will grow, while accelerating climate change will increase the likelihood of damaging extreme events, as well as accelerate habitat decline. Existing coastal management and defence approaches are not well tuned to these challenges as they assume a static situation.THESEUS project is developing a systematic approach to delivering both a low-risk coast for human use and healthy habitats for evolving coastal zones subject to multiple change factors. The project examines innovative mitigation and adaptation technologies and integrate the best of these technical measures in a strategic policy context through overarching guidelines. THESEUS activities are carried out within a multidisciplinary framework using 8 study sites across Europe, with specific attention to the most vulnerable coastal environments such as deltas, estuaries and wetlands, where many large cities and industrial areas are located.This paper describes THESEUS approach, and specifically: the Source-Pathway-Receptor-Consquence model for coastal risk assessment; the engineering, social, economic and ecological mitigation measures under analysis; the participatory approach with end users and coastal authorities for the selection and identification of the appropriate defence strategy to be planned in sudy sites.     

Indicators of deforestation in the Southern Brazilian Pre-Amazon

In recent years, Amazonian deforestation has become a question of global concern. Deforestation in Amazon is a complex phenomenon in nature and has been related to traditional agriculture expansion. In this work, land use, socioeconomic and conservation indicators, combined with statistical analysis, were used to understand forces associated with patterns of deforestation. This approach was applied in Southern Brazilian Pre-Amazon in Mato Grosso State, which represents an extensive rain forest-savanna ecotone, located in the south border of Amazon biome. Based on data from the last two agricultural censuses (1995/1996–2006), we compared agricultural expansion in this area and Mato Grosso state. Results have shown that 85 % of state deforestation was concentrated in Southern Pre-Amazon and was closely related to increase in number of cattle and pasture area. PCA results pointed that population (92 %), number of cattle (86.5 %), pastures (84.2 %) and tractors (78.4 %) were variables with highest positive correlation to deforestation. It showed that GDP contributes to an individual axis and has a low correlation to deforestation (37.8 %). Conservation units and indigenous reserves also contribute to a single axis and were negatively correlated to temporary crops area. Results revealed a significant reduction in production and commercialization of extractive products in the region, revealing that the main, almost only conservation policy in Mato Grosso remains the creation of Special Areas. We suggest that further studies are necessary to screen development alternatives to simple cutting trees down. It is important to diversify strategies for deforestation control, and development aspects must be more seriously considered to reach a sustainable deforestation control policy.     

Statistical and Hybrid Methods Implemented in a Web Application for Predicting Reservoir Inflows during Flood Events

Reservoir management is a critical component of flood management, and information on reservoir inflows is particularly essential for reservoir managers to make real‐time decisions given that flood conditions change rapidly. This study's objective is to build real‐time data‐driven services that enable managers to rapidly estimate reservoir inflows from available data and models. We have tested the services using a case study of the Texas flooding events in the Lower Colorado River Basin in November 2014 and May 2015, which involved a sudden switch from drought to flooding. We have constructed two prediction models: a statistical model for flow prediction and a hybrid statistical and physics‐based model that estimates errors in the flow predictions from a physics‐based model. The study demonstrates that the statistical flow prediction model can be automated and provides acceptably accurate short‐term forecasts. However, for longer term prediction (2 h or more), the hybrid model fits the observations more closely than the purely statistical or physics‐based prediction models alone. Both the flow and hybrid prediction models have been published as Web services through Microsoft's Azure Machine Learning (AzureML) service and are accessible through a browser‐based Web application, enabling ease of use by both technical and nontechnical personnel.