Directional emission of light from a nano-optical Yagi-Uda antenna

The plasmon resonance of metal nanoparticles can enhance and direct light from optical emitters in much the same way that radio frequency (RF) antennas enhance and direct the emission from electrical circuits. In the RF regime, a typical antenna design for high directivity is the Yagi-Uda antenna, which basically consists of a one-dimensional array of antenna elements driven by a single feed element. Here, we present the experimental demonstration of directional light emission from a nano-optical Yagi-Uda antenna composed of an array of appropriately tuned gold nanorods. Our results indicate that nano-optical antenna arrays are a simple but efficient tool for the spatial control of light emission.Comment: 4 pages, including 4 figure

Survey context and question wording affects self reported annoyance due to road traffic noise: a comparison between two cross-sectional studies

<p>Abstract</p> <p>Background</p> <p>Surveys are a common way to measure annoyance due to road traffic noise, but the method has some draw-backs. Survey context, question wording and answer alternatives could affect participation and answers and could have implications when comparing studies and/or performing pooled analyses. The aim of this study was to investigate the difference in annoyance reporting due to road traffic noise in two types of surveys of which one was introduced broadly and the other with the clearly stated aim of investigating noise and health.</p> <p>Methods</p> <p>Data was collected from two surveys carried out in the municipality of Malmö, southern Sweden in 2007 and 2008 (n = 2612 and n = 3810). The first survey stated an aim of investigating residential environmental exposure, especially noise and health. The second survey was a broad public health survey stating a broader aim. The two surveys had comparable questions regarding noise annoyance, although one used a 5-point scale and the other a 4-point scale. We used geographic information systems (GIS) to assess the average road and railway noise (L_Aeq,24h) at the participants' residential address. Logistic regression was used to calculate odds ratios for annoyance in relation to noise exposure.</p> <p>Results</p> <p>Annoyance at least once a week due to road traffic noise was significantly more prevalent in the survey investigating environment and health compared to the public health survey at levels > 45 dB(A), but not at lower exposure levels. However no differences in annoyance were found when comparing the extreme alternatives "never" and "every day". In the study investigating environment and health, "Noise sensitive" persons were more likely to readily respond to the survey and were more annoyed by road traffic noise compared to the other participants in that survey.</p> <p>Conclusions</p> <p>The differences in annoyance reporting between the two surveys were mainly due to different scales, suggesting that extreme alternatives are to prefer before dichotomization when comparing results between the two. Although some findings suggested that noise-sensitive individuals were more likely to respond to the survey investigating noise and health, we could not find convincing evidence that contextual differences affected either answers or participation.</p

Solar Radiation and Tidal Exposure as Environmental Drivers of Enhalus acoroides Dominated Seagrass Meadows

There is strong evidence of a global long-term decline in seagrass meadows that is widely attributed to anthropogenic activity. Yet in many regions, attributing these changes to actual activities is difficult, as there exists limited understanding of the natural processes that can influence these valuable ecosystem service providers. Being able to separate natural from anthropogenic causes of seagrass change is important for developing strategies that effectively mitigate and manage anthropogenic impacts on seagrass, and promote coastal ecosystems resilient to future environmental change. The present study investigated the influence of environmental and climate related factors on seagrass biomass in a large ≈250 ha meadow in tropical north east Australia. Annual monitoring of the intertidal Enhalus acoroides (L.f.) Royle seagrass meadow over eleven years revealed a declining trend in above-ground biomass (54% significant overall reduction from 2000 to 2010). Partial Least Squares Regression found this reduction to be significantly and negatively correlated with tidal exposure, and significantly and negatively correlated with the amount of solar radiation. This study documents how natural long-term tidal variability can influence long-term seagrass dynamics. Exposure to desiccation, high UV, and daytime temperature regimes are discussed as the likely mechanisms for the action of these factors in causing this decline. The results emphasise the importance of understanding and assessing natural environmentally-driven change when interpreting the results of seagrass monitoring programs

Global maps of soil temperature

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all the world’s major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (-0.7 ± 2.3°C). The observed substantial and biome-specific offsets emphasize that the projected impacts of climate and climate change on near-surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications

Is variety the spice of life? An experimental investigation into the effects of species richness on self-reported mental well-being.

<div><p>Losses in biodiversity and trends toward urbanisation have reduced people’s contact with biodiverse nature, yet the consequences for mental well-being are not well understood. Here, we demonstrate that greater plant and animal species richness in isolation causes an improvement in mental well-being. To do so, the present research experimentally manipulated species richness and assessed widely-used indicators of mental well-being. Participants viewed short videos of either high or low tree (Study 1) or bird (Study 2) species richness and reported on positive (i.e., vitality, positive affect) and negative (i.e., anxiety) indicators of mental well-being. Building on Study 1, Study 2 included an urban environment as a reference treatment and explored the role of giving participants information on the presented environment. We find that, in line with expectations, watching videos containing greater species richness consistently leads to higher mental well-being. We discuss findings in light of the importance of connecting people to biodiverse environments.</p></div

Dynamics of Fungal and Bacterial Biomass Carbon in Natural Ecosystems: Site-Level Applications of the CLM-Microbe Model

Explicitly representing microbial processes has been recognized as a key improvement to Earth system models for the realistic projections of soil carbon (C) and climate dynamics. The CLM-Microbe model builds upon the CLM4.5 and explicitly represents two major soil microbial groups, fungi and bacteria. Based on the compiled time-series data of fungal (FBC) and bacterial (BBC) biomass C from nine biomes, we parameterized and validated the CLM-Microbe model, and further conducted sensitivity and uncertainty analysis for simulating C cycling. The model performance was evaluated with mean absolute error (MAE), root mean square error (RMSE), and coefficient of determination (R ) for relative change in FBC and BBC. The CLM-Microbe model is able to reasonably capture the seasonal dynamics of FBC and BBC across biomes, particularly for tropical/subtropical forest, temperate broadleaf forest, and grassland, with MAE &lt;0.49 for FBC and &lt;0.36 for BBC and RMSE &lt;0.52 FBC and &lt;0.39 for BBC, while R values are relatively smaller in some biomes (e.g., shrub) due to small sample sizes. We found good consistencies between simulated and observed FBC (R &nbsp;=&nbsp;0.70, P&nbsp;&lt;&nbsp;0.001) and BBC (R &nbsp;=&nbsp;0.26, P&nbsp;&lt;&nbsp;0.05) on average across biomes, but the model is not able to fully capture the large variation in observed FBC and BBC. Sensitivity analysis shows that the most critical parameters are turnover rate and carbon-to-nitrogen ratio of fungi and bacteria and microbial assimilation efficiency. This study confirms that the explicit representation of soil microbial mechanisms enhances model performance in simulating C variables such as heterotrophic respiration and soil organic C density. The further application of the CLM-Microbe model would deepen our understanding of microbial contributions to global C cycle. 2 2 2