The General Data Protection Regulation and children’s rights: questions and answers for legislators, DPAs, industry, education, stakeholders and civil society. Roundtable Report.

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A different look at assessment centers: Views of assessment center users

This study aims to shed light on possible problems of assessment center users and designers when developing and implementing assessment centers. Semi-structured interviews with a representative sample of assessment center users in Flanders revealed that, besides a large variability in assessment center practice, practitioners experience problems with dimension selection and definition, exercise design, line/staff managers as assessors, distinguishing between observation and evaluation, and with the content of assessor training programs. Solutions for these problems are suggested

Influence of surface roughness sample size for C-band SAR backscatter applications on agricultural soils

Soil surface roughness determines the backscatter coefficient observed by radar sensors. The objective of this letter was to determine the surface roughness sample size required in synthetic aperture radar applications and to provide some guidelines on roughness characterization in agricultural soils for these applications. With this aim, a data set consisting of ten ENVISAT/ASAR observations acquired coinciding with soil moisture and surface roughness surveys has been processed. The analysis consisted of: 1) assessing the accuracies of roughness parameters s and l depending on the number of 1-m-long profiles measured per field; 2) computing the correlation of field average roughness parameters with backscatter observations; and 3) evaluating the goodness of fit of three widely used backscatter models, i.e., integral equation model (IEM), geometrical optics model (GOM), and Oh model. The results obtained illustrate a different behavior of the two roughness parameters. A minimum of 10-15 profiles can be considered sufficient for an accurate determination of s, while 20 profiles might still be not enough for accurately estimating l. The correlation analysis revealed a clear sensitivity of backscatter to surface roughness. For sample sizes > 15 profiles, R values were as high as 0.6 for s and similar to 0.35 for l, while for smaller sample sizes R values dropped significantly. Similar results were obtained when applying the backscatter models, with enhanced model precision for larger sample sizes. However, IEM and GOM results were poorer than those obtained with the Oh model and more affected by lower sample sizes, probably due to larger uncertainly of l

Sensitivity of C-band backscatter to surface roughness parameters measured at different scales

SAR (Synthetic Aperture Radar) sensors measure the backscatter (sigma(0)) of land covers and SAR images have a number of applications in agricultural soils (soil moisture, crop monitoring, etc.) but the surface roughness of these soils complicates their interpretation and determination of quantitative estimates of useful parameters. The aim of this study is to quantify the spatial variability of different roughness parameters and the sensitivity of. 0 to them measured at different scales. Ten Envisat/ASAR images acquired between September 2004 and January 2005 on an agricultural area with 10 control plots are analyzed. 132 roughness profiles of 5 m length were measured, and 21 different parameters were calculated. The results show considerable differences in the spatial variability of the parameters and differed depending on the type of parameter in the correlation analysis. This study can be useful to identify roughness parameters and scales that maximize their sensitivity to C-band backscatter

GLEAM v3 : satellite-based land evaporation and root-zone soil moisture

The Global Land Evaporation Amsterdam Model (GLEAM) is a set of algorithms dedicated to the estimation of terrestrial evaporation and root-zone soil moisture from satellite data. Ever since its development in 2011, the model has been regularly revised, aiming at the optimal incorporation of new satellite-observed geophysical variables, and improving the representation of physical processes. In this study, the next version of this model (v3) is presented. Key changes relative to the previous version include (1) a revised formulation of the evaporative stress, (2) an optimized drainage algorithm, and (3) a new soil moisture data assimilation system. GLEAM v3 is used to produce three new data sets of terrestrial evaporation and root-zone soil moisture, including a 36-year data set spanning 1980-2015, referred to as v3a (based on satellite-observed soil moisture, vegetation optical depth and snow-water equivalent, reanalysis air temperature and radiation, and a multi-source precipitation product), and two satellite-based data sets. The latter share most of their forcing, except for the vegetation optical depth and soil moisture, which are based on observations from different passive and active C-and L-band microwave sensors (European Space Agency Climate Change Initiative, ESA CCI) for the v3b data set (spanning 2003-2015) and observations from the Soil Moisture and Ocean Salinity (SMOS) satellite in the v3c data set (spanning 2011-2015). Here, these three data sets are described in detail, compared against analogous data sets generated using the previous version of GLEAM (v2), and validated against measurements from 91 eddy-covariance towers and 2325 soil moisture sensors across a broad range of ecosystems. Results indicate that the quality of the v3 soil moisture is consistently better than the one from v2: average correlations against in situ surface soil moisture measurements increase from 0.61 to 0.64 in the case of the v3a data set and the representation of soil moisture in the second layer improves as well, with correlations increasing from 0.47 to 0.53. Similar improvements are observed for the v3b and c data sets. Despite regional differences, the quality of the evaporation fluxes remains overall similar to the one obtained using the previous version of GLEAM, with average correlations against eddy-covariance measurements ranging between 0.78 and 0.81 for the different data sets. These global data sets of terrestrial evaporation and root-zone soil moisture are now openly available at www.GLEAM.eu and may be used for large-scale hydrological applications, climate studies, or research on land-atmosphere feedbacks

Does virulence assessment of Vibrio anguillarum using sea bass (Dicentrarchus labrax) larvae correspond with genotypic and phenotypic characterization?

Background: Vibriosis is one of the most ubiquitous fish diseases caused by bacteria belonging to the genus Vibrio such as Vibrio (Listonella) anguillarum. Despite a lot of research efforts, the virulence factors and mechanism of V. anguillarum are still insufficiently known, in part because of the lack of standardized virulence assays. Methodology/Principal Findings: We investigated and compared the virulence of 15 V. anguillarum strains obtained from different hosts or non-host niches using a standardized gnotobiotic bioassay with European sea bass (Dicentrarchus labrax L.) larvae as model hosts. In addition, to assess potential relationships between virulence and genotypic and phenotypic characteristics, the strains were characterized by random amplified polymorphic DNA (RAPD) and repetitive extragenic palindromic PCR (rep-PCR) analyses, as well as by phenotypic analyses using Biolog's Phenotype MicroArray (TM) technology and some virulence factor assays. Conclusions/Significance: Virulence testing revealed ten virulent and five avirulent strains. While some relation could be established between serotype, genotype and phenotype, no relation was found between virulence and genotypic or phenotypic characteristics, illustrating the complexity of V. anguillarum virulence. Moreover, the standardized gnotobiotic system used in this study has proven its strength as a model to assess and compare the virulence of different V. anguillarum strains in vivo. In this way, the bioassay contributes to the study of mechanisms underlying virulence in V. anguillarum

Limited effects of plant-beneficial fungi on plant volatile composition and host-choice behavior of Nesidiocoris tenuis

Biological control using plant-beneficial fungi has gained considerable interest as a sustainable method for pest management, by priming the plant for enhanced defense against pathogens and insect herbivores. However, despite promising outcomes, little is known about how different fungal strains mediate these beneficial effects. In this study, we evaluated whether inoculation of tomato seeds with the plant-beneficial fungi Beauveria bassiana ARSEF 3097, Metarhizium brunneum ARSEF 1095 and Trichoderma harzianum T22 affected the plant’s volatile organic compound (VOC) profile and the host-choice behavior of Nesidiocoris tenuis, an emerging pest species in NW-European tomato cultivation, and the related zoophytophagous biocontrol agent Macrolophus pygmaeus. Results indicated that fungal inoculation did not significantly alter the VOC composition of tomato plants. However, in a two-choice cage assay where female insects were given the option to select between control plants and fungus-inoculated plants, N. tenuis preferred control plants over M. brunneum-inoculated plants. Nearly 72% of all N. tenuis individuals tested chose the control treatment. In all other combinations tested, no significant differences were found for none of the insects. We conclude that inoculation of tomato with plant-beneficial fungi had limited effects on plant volatile composition and host-choice behavior of insects. However, the observation that N. tenuis was deterred from the crop when inoculated with M. brunneum and attracted to non-inoculated plants may provide new opportunities for future biocontrol based on a push-pull strategy

Fungal strain and crop cultivar affect growth of sweet pepper plants after root inoculation with entomopathogenic fungi

As endophytes, entomopathogenic fungi can protect plants against biotic and abiotic stresses and at the same time promote plant growth and plant health. To date, most studies have investigated whether Beauveria bassiana can enhance plant growth and plant health, while only little is known about other entomopathogenic fungi. In this study, we evaluated whether root inoculation of the entomopathogenic fungi Akanthomyces muscarius ARSEF 5128, B. bassiana ARSEF 3097 and Cordyceps fumosorosea ARSEF 3682 can promote plant growth of sweet pepper (Capsicum annuum L.), and whether effects are cultivar-dependent. Plant height, stem diameter, number of leaves, canopy area, and plant weight were assessed four weeks following inoculation in two independent experiments using two cultivars of sweet pepper (cv. ‘IDS RZ F1’ and cv. ‘Maduro’). Results showed that the three entomopathogenic fungi were able to enhance plant growth, particularly canopy area and plant weight. Further, results showed that effects significantly depended on cultivar and fungal strain, with the strongest fungal effects obtained for cv. ‘IDS RZ F1’, especially when inoculated with C. fumosorosea. We conclude that inoculation of sweet pepper roots with entomopathogenic fungi can stimulate plant growth, but effects depend on fungal strain and crop cultivar

Sentinel-1 detects firn aquifers in the Greenland ice sheet

Firn aquifers in Greenland store liquid water within the upper ice sheet and impact the hydrological system. Their location and area have been estimated with airborne radar sounder surveys (Operation IceBridge, OIB). However, the OIB coverage is limited to narrow flight lines, offering an incomplete view. Here, we show the ability of satellite radar measurements from Sentinel-1 to map firn aquifers across all of Greenland at 1 km(2) resolution. The detection of aquifers relies on a delay in the freezing of meltwater within the firn above the water table, causing a distinctive pattern in the radar backscatter. The Sentinel-1 aquifer locations are in very good agreement with those detected along the OIB flight lines (Cohen's kappa = 0.84). The total aquifer area is estimated at 54,800 km(2). With continuity of Sentinel-1 ensured until 2030, our study lays a foundation for monitoring the future response of firn aquifers to climate change