Preliminary optical design for the common fore optics of METIS

METIS is the Mid-infrared E-ELT Imager and Spectrograph, which will provide outstanding observing capabilities, focusing on high angular and spectral resolution. It consists of two diffraction-limited imagers operating in the LM and NQ bands respectively and an IFU fed diffraction-limited high-resolution (R=100,000) LM band spectrograph. These science subsystems are preceded by the common fore optics (CFO), which provides the following essential functionalities: calibration, chopping, image de-rotation, thermal background and stray light reduction. We show the evolution of the CFO optical design from the conceptual design to the preliminary optical design, detail the optimization steps and discuss the necessary trade-offs

Effects of near-infrared light on well-being and health in human subjects with mild sleep-related complaints:A double-blind, randomized, placebo-controlled study

Modern urban human activities are largely restricted to the indoors, deprived of direct sunlight containing visible and near-infrared (NIR) wavelengths at high irradiance levels. Therapeutic exposure to doses of red and NIR, known as photobiomodulation (PBM), has been effective for a broad range of conditions. In a double-blind, randomized, placebo-controlled study, we aimed to assess the effects of a PBM home set-up on various aspects of well-being, health, sleep, and circadian rhythms in healthy human subjects with mild sleep complaints. The effects of three NIR light (850 nm) doses (1, 4, or 6.5 J·cm−2) were examined against the placebo. Exposure was presented five days per week between 9:30 am and 12:30 pm for four consecutive weeks. The study was conducted in both summer and winter to include seasonal variation. The results showed PBM treatment only at 6.5 J·cm−2 to have consistent positive benefits on well-being and health, specifically improving mood, reducing drowsiness, reducing IFN-γ, and resting heart rate. This was only observed in winter. No significant effects on sleep or circadian rhythms were noted. This study provides further evidence that adequate exposure to NIR, especially during low sunlight conditions, such as in the winter, can be beneficial for human health and wellness.</p

Differential Influence of Clonal Integration on Morphological and Growth Responses to Light in Two Invasive Herbs

Background and aims: In contrast to seeds, high sensitivity of vegetative fragments to unfavourable environments may limit the expansion of clonal invasive plants. However, clonal integration promotes the establishment of propagules in less suitable habitats and may facilitate the expansion of clonal invaders into intact native communities. Here, we examine the influence of clonal integration on the morphology and growth of ramets in two invasive plants, Alternanthera philoxeroides and Phyla canescens, under varying light conditions. Methods: In a greenhouse experiment, branches, connected ramets and severed ramets of the same mother plant were exposed under full sun and 85 % shade and their morphological and growth responses were assessed. Key results: The influence of clonal integration on the light reaction norm (connection6light interaction) of daughter ramets was species-specific. For A. philoxeroides, clonal integration evened out the light response (total biomass, leaf mass per area, and stem number, diameter and length) displayed in severed ramets, but these connection6light interactions were largely absent for P. canescens. Nevertheless, for both species, clonal integration overwhelmed light effect in promoting the growth of juvenile ramets during early development. Also, vertical growth, as an apparent shade acclimation response, was more prevalent in severed ramets than in connected ramets. Finally, unrooted branches displayed smaller organ size and slower growth than connected ramets, but the pattern of light reaction was similar, suggesting mothe

What are the key drivers of spread in invasive plants: Dispersal, demography or landscape: And how can we use this knowledge to aid management?

Invasive plants disrupt ecosystems from local to landscape scales. Reduction or reversal of spread is an important goal of many invasive plant management strategies, but few general guidelines exist on how to achieve this aim. We identified the main drivers of spread, and thus potential targets for management, using a spatially explicit simulation model tested on different life history categories in different spread and landscape scenarios. We used boosted regression trees to determine the parameters that most affected spread. Additionally, we analysed how spread reacted to changes in those parameters over a broad realistic range. From our results we deduce four simple management guidelines: (1) Manage dispersal if possible, as mean dispersal distance was an important driver of spread for all life history categories; (2) short bursts of rapid spread or more usual year on year spread can have different drivers, therefore managers need to decide what type of spread they want to slow; (3) efforts to manage spread will have variable outcomes due to interactions between, and non-linear responses to, key drivers of spread; and (4) the most useful demographic rates to target depend on dispersal ability, life history and how spread is measured. Fecundity was found to be important for driving spread only when reduced to low levels and particularly when the species was short lived. For longer lived species management should target survival, or age of maturity, especially when dispersal ability is limited

Scale-appropriate spatial modelling to support area-wide management of a polyphagous fruit fly (Diptera: Tephritidae)

Control of mobile pests frequently requires area-wide management (AWM) that spans commercial and non-commercial habitats. Spatial modelling of habitat suitability can guide investment and implementation of AWM, but current approaches rarely capture population drivers, including local foraging, at an appropriate spatial resolution. To support the development of AWM for the fruit fly pest, Bactrocera tryoni (Tephritidae), we developed a habitat suitability model for the three premier fruit-growing regions in south-eastern Australia (~34,780 km2). Expert elicitation and published literature was used to develop a Bayesian network to model the drivers of B. tryoni habitat suitability, as determined by the ability of populations to persist and increase. The effect of uncertainty was tested through sensitivity analysis. The model was then linked with spatially explicit data (at 10 m resolution) to generate risk maps, using moving windows to capture local foraging movement. Habitat suitability was most strongly influenced by host availability within a distance of 200 m. Climate stress, and soil moisture for pupation, was also limiting. Experts were uncertain regarding the relative importance of drivers of host availability (host preference, host density, fruit seasonality), but this did not greatly affect model outputs. Independent trapping data supported model predictions, but their value was limited as traps were placed almost exclusively in optimal or suitable habitat. Amenability to AWM, when assessed as the ratio of suitable or optimal habitat that was under non-horticultural versus horticultural land-uses, differed by region (0.15–1.17). However, risk-mapping did identify where ratios were locally most favourable (lowest). Also, predominantly local dispersal by B. tryoni suggests AWM for pest suppression could be applied at a landscape-scale. Results show that a relatively simple model could capture the multi-scale drivers of population dynamics and the complexity of landscapes sufficiently to guide AWM of a mobile pest.</p

Spread rate of each species (n = 155) including high impact species in each sector.

<p>High impact species in each sector are highlighted in separate panels (black dots). Data points are randomly jittered across the y-axis to make visualisation clearer. The very large outlier is explained in the bottom panel.</p

Comparison of all species and high-impact species by sector.

<p>Only predictors (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0068678#pone-0068678-t001" target="_blank">Table 1</a>) that differed between sectors (see text) are included. Statistical analysis was only possible for environmental and pastoral weeds, and only for a subset of parameters (#). The most influential predictors are indicated in bold. Proportions are given in brackets.</p>*<p>mean ± SE.</p

Best models predicting high-impact species using a statistical learning approach.

<p>Model weighting assumption was tested by comparing true positives and false negatives equally (<i>w</i> = 0.5) (comparable to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0068678#pone-0068678-t002" target="_blank">Table 2</a>) and weighting true positives more heavily than false negatives) (<i>w</i> = 0.9). <i>Weuc</i> is expressed as a proportion of the maximum possible value given the value of <i>w</i>, thus in both cases a perfect classifier would have a <i>Weuc</i> of 0, and a classifier that is guessing randomly will have a <i>Weuc</i> of 1.</p