Very high-resolution digital elevation models: are multi-scale-derived variables ecologically relevant?

1. Digital elevation models (DEMs) are often used in landscape ecology to retrieve elevation or first derivative terrain attributes such as slope or aspect in the context of species distribution modelling. However, DEM-derived variables are scale-dependent and, given the increasing availability of very high-resolution (VHR) DEMs, their ecological relevancemust be assessed for different spatial resolutions. 2. In a study area located in the Swiss Western Alps, we computed VHR DEMs-derived variables related to morphometry, hydrology and solar radiation. Based on an original spatial resolution of 0.5 m, we generated DEM-derived variables at 1, 2 and 4 mspatial resolutions, applying a Gaussian Pyramid. Their associations with local climatic factors, measured by sensors (direct and ambient air temperature, air humidity and soil moisture) as well as ecological indicators derived fromspecies composition, were assessed with multivariate generalized linearmodels (GLM) andmixed models (GLMM). 3. Specific VHR DEM-derived variables showed significant associations with climatic factors. In addition to slope, aspect and curvature, the underused wetness and ruggedness indices modelledmeasured ambient humidity and soilmoisture, respectively. Remarkably, spatial resolution of VHR DEM-derived variables had a significant influence on models' strength, with coefficients of determination decreasing with coarser resolutions or showing a local optimumwith a 2 mresolution, depending on the variable considered. 4. These results support the relevance of using multi-scale DEM variables to provide surrogates for important climatic variables such as humidity, moisture and temperature, offering suitable alternatives to direct measurements for evolutionary ecology studies at a local scale.

Predicting richness and composition in mountain insect communities at high resolution: a new test of the SESAM framework

Aim The aim of this study was to test different modelling approaches, including a new framework, for predicting the spatial distribution of richness and composition of two insect groups. Location The western Swiss Alps. Methods We compared two community modelling approaches: the classical method of stacking binary prediction obtained fromindividual species distribution models (binary stacked species distribution models, bS-SDMs), and various implementations of a recent framework (spatially explicit species assemblage modelling, SESAM) based on four steps that integrate the different drivers of the assembly process in a unique modelling procedure. We used: (1) five methods to create bS-SDM predictions; (2) two approaches for predicting species richness, by summing individual SDM probabilities or by modelling the number of species (i.e. richness) directly; and (3) five different biotic rules based either on ranking probabilities from SDMs or on community co-occurrence patterns. Combining these various options resulted in 47 implementations for each taxon. Results Species richness of the two taxonomic groups was predicted with good accuracy overall, and in most cases bS-SDM did not produce a biased prediction exceeding the actual number of species in each unit. In the prediction of community composition bS-SDM often also yielded the best evaluation score. In the case of poor performance of bS-SDM (i.e. when bS-SDM overestimated the prediction of richness) the SESAM framework improved predictions of species composition. Main conclusions Our results differed from previous findings using community-level models. First, we show that overprediction of richness by bS-SDM is not a general rule, thus highlighting the relevance of producing good individual SDMs to capture the ecological filters that are important for the assembly process. Second, we confirm the potential of SESAM when richness is overpredicted by bS-SDM; limiting the number of species for each unit and applying biotic rules (here using the ranking of SDM probabilities) can improve predictions of species composition

Retinal damage induced by commercial light emitting diodes (LEDs).

Spectra of "white LEDs" are characterized by an intense emission in the blue region of the visible spectrum, absent in daylight spectra. This blue component and the high intensity of emission are the main sources of concern about the health risks of LEDs with respect to their toxicity to the eye and the retina. The aim of our study was to elucidate the role of blue light from LEDs in retinal damage. Commercially available white LEDs and four different blue LEDs (507, 473, 467, and 449nm) were used for exposure experiments on Wistar rats. Immunohistochemical stain, transmission electron microscopy, and Western blot were used to exam the retinas. We evaluated LED-induced retinal cell damage by studying oxidative stress, stress response pathways, and the identification of cell death pathways. LED light caused a state of suffering of the retina with oxidative damage and retinal injury. We observed a loss of photoreceptors and the activation of caspase-independent apoptosis, necroptosis, and necrosis. A wavelength dependence of the effects was observed. Phototoxicity of LEDs on the retina is characterized by a strong damage of photoreceptors and by the induction of necrosis.

High-Resolution Magnetic Resonance Imaging Can Reliably Detect Orbital Tumor Recurrence after Enucleation in Children with Retinoblastoma.

PURPOSE: Orbital tumor recurrence is a rare but serious complication in children with retinoblastoma, leading to a high risk of metastasis and death. Therefore, we assume that these recurrences have to be detected and treated as early as possible. Preliminary studies used magnetic resonance imaging (MRI) to evaluate postsurgical findings in the orbit. In this study, we assessed the diagnostic accuracy of high-resolution MRI to detect orbital tumor recurrence in children with retinoblastoma in a large study cohort. DESIGN: Consecutive retrospective study (2007-2013) assessing MRI findings after enucleation. PARTICIPANTS: A total of 103 MRI examinations of 55 orbits (50 children, 27 male/23 female, mean age 16.3±12.4 months) with a median time of 8 months (range, 0-93) after enucleation for retinoblastoma. METHODS: High-resolution MRI using orbital surface coils was performed on 1.5 Tesla MRI systems to assess abnormal orbital findings. MAIN OUTCOME MEASURES: Five European experts in retinoblastoma imaging evaluated the MRI examinations regarding the presence of abnormal orbital gadolinium enhancement and judged them as "definitive tumor," "suspicious of tumor," "postsurgical condition/scar formation," or "without pathologic findings." The findings were correlated to histopathology (if available), MRI, and clinical follow-up. RESULTS: Abnormal orbital enhancement was a common finding after enucleation (100% in the first 3 months after enucleation, 64.3% >3 years after enucleation). All histopathologically confirmed tumor recurrences (3 of 55 orbits, 5.5%) were correctly judged as "definitive tumor" in MRI. Two orbits from 2 children rated as "suspicious of tumor" received intravenous chemotherapy without histopathologic confirmation; further follow-up (67 and 47 months) revealed no sign of tumor recurrence. In 90.2%, no tumor was suspected on MRI, which was clinically confirmed during follow-up (median follow-up after enucleation, 45 months; range, 8-126). CONCLUSIONS: High-resolution MRI with orbital surface coils may reliably distinguish between common postsurgical contrast enhancement and orbital tumor recurrence, and therefore may be a useful tool to evaluate orbital tumor recurrence after enucleation in children with retinoblastoma. We recommend high-resolution MRI as a potential screening tool for the orbit in children with retinoblastoma to exclude tumor recurrence, especially in high-risk patients within the critical first 2 years after enucleation.