Comparative Cytotoxicity Study of Silver Nanoparticles (AgNPs) in a Variety of Rainbow Trout Cell Lines (RTL-W1, RTH-149, RTG-2) and Primary Hepatocytes.

Among all classes of nanomaterials, silver nanoparticles (AgNPs) have potentially an important ecotoxicological impact, especially in freshwater environments. Fish are particularly susceptible to the toxic effects of silver ions and, with knowledge gaps regarding the contribution of dissolution and unique particle effects to AgNP toxicity, they represent a group of vulnerable organisms. Using cell lines (RTL-W1, RTH-149, RTG-2) and primary hepatocytes of rainbow trout (Oncorhynchus mykiss) as in vitro test systems, we assessed the cytotoxicity of the representative AgNP, NM-300K, and AgNO3 as an Ag+ ion source. Lack of AgNP interference with the cytotoxicity assays (AlamarBlue, CFDA-AM, NRU assay) and their simultaneous application point to the compatibility and usefulness of such a battery of assays. The RTH-149 and RTL-W1 liver cell lines exhibited similar sensitivity as primary hepatocytes towards AgNP toxicity. Leibovitz's L-15 culture medium composition (high amino acid content) had an important influence on the behaviour and toxicity of AgNPs towards the RTL-W1 cell line. The obtained results demonstrate that, with careful consideration, such an in vitro approach can provide valuable toxicological data to be used in an integrated testing strategy for NM-300K risk assessment.

Global models of planet formation and evolution

Despite the strong increase in observational data on extrasolar planets, the processes that led to the formation of these planets are still not well understood. However, thanks to the high number of extrasolar planets that have been discovered, it is now possible to look at the planets as a population that puts statistical constraints on theoretical formation models. A method that uses these constraints is planetary population synthesis where synthetic planetary populations are generated and compared to the actual population. The key element of the population synthesis method is a global model of planet formation and evolution. These models directly predict observable planetary properties based on properties of the natal protoplanetary disc, linking two important classes of astrophysical objects. To do so, global models build on the simplified results of many specialized models that address one specific physical mechanism. We thoroughly review the physics of the sub-models included in global formation models. The sub-models can be classified as models describing the protoplanetary disc (of gas and solids), those that describe one (proto)planet (its solid core, gaseous envelope and atmosphere), and finally those that describe the interactions (orbital migration and N-body interaction). We compare the approaches taken in different global models, discuss the links between specialized and global models, and identify physical processes that require improved descriptions in future work. We then shortly address important results of planetary population synthesis like the planetary mass function or the mass-radius relationship. With these statistical results, the global effects of physical mechanisms occurring during planet formation and evolution become apparent, and specialized models describing them can be put to the observational test. Owing to their nature as meta models, global models depend on the results of specialized models, and therefore on the development of the field of planet formation theory as a whole. Because there are important uncertainties in this theory, it is likely that the global models will in future undergo significant modifications. Despite these limitations, global models can already now yield many testable predictions. With future global models addressing the geophysical characteristics of the synthetic planets, it should eventually become possible to make predictions about the habitability of planets based on their formation and evolution.

Different-sized grazers have distinctive effects on plant functional composition of an African savannah

Grazing ungulates play a key role in many ecosystems worldwide and can form diverse assemblages, such as in African savannahs. In many of these ecosystems, present-day ungulate communities are impoverished subsets of once diverse assemblages. While we know that excluding all ungulates from grasslands can exert major effects on both the structure and composition of the vegetation, how different individual ungulate species may have contrasting effects on grassland communities remains poorly understood. Here, we performed a long-term ‘Russian doll’ grazing exclosure experiment in an African savannah to test for the effects of different size classes of grazers on grassland structure and composition. At five sites, grazer species of decreasing size class (ranging from white rhino to scrub hare) were excluded using four fence types, to experimentally create different realized grazer assemblages. The vegetation structure and the grass functional community composition were characterized in 6 different years over a 10-year period. Additionally, animal footprints were counted to quantify the abundance of different ungulate species in each treatment. We found that while vegetation height was mostly driven by total grazing pressure of all species together, ungulate community composition best explained the functional community composition of grasses. In the short term, smaller ungulate species (‘mesoherbivores’) had strongest effects on vegetation composition, by shifting communities towards dominance by species with low specific leaf area and low nutritional value. In the long term, large grazers had stronger but similar effects on the functional composition of the system. Surprisingly, the largest ‘mega-herbivore’, the white rhinoceros, did not have strong effects on the vegetation structure or composition. Synthesis. Our results support the idea that different size classes of grazers have varying effects on the functional composition of grassland plant communities. Therefore, the worldwide decline in the diversity of ungulate species is expected to have (had) major impacts on community composition and functioning of grassland ecosystems, even if total grazing pressure has remained constant, for example, due to replacement by livestock.

Properties of granular analogue model materials: A community wide survey

We report the material properties of 26 granular analogue materials used in 14 analogue modelling laboratories. We determined physical characteristics such as bulk density, grain size distribution, and grain shape, and performed ring shear tests to determine friction angles and cohesion, and uniaxial compression tests to evaluate the compaction behaviour. Mean grain size of the materials varied between c. 100 and 400 μm. Analysis of grain shape factors shows that the four different classes of granular materials (14 quartz sands, 5 dyed quartz sands, 4 heavy mineral sands and 3 size fractions of glass beads) can be broadly divided into two groups consisting of 12 angular and 14 rounded materials. Grain shape has an influence on friction angles, with most angular materials having higher internal friction angles (between c. 35° and 40°) than rounded materials, whereas well-rounded glass beads have the lowest internal friction angles (between c. 25° and 30°). We interpret this as an effect of intergranular sliding versus rolling. Most angular materials have also higher basal friction angles (tested for a specific foil) than more rounded materials, suggesting that angular grains scratch and wear the foil. Most materials have an internal cohesion in the order of 20–100 Pa except for well-rounded glass beads, which show a trend towards a quasi-cohesionless (C < 20 Pa) Coulomb-type material. The uniaxial confined compression tests reveal that rounded grains generally show less compaction than angular grains. We interpret this to be related to the initial packing density after sifting, which is higher for rounded grains than for angular grains. Ring-shear test data show that angular grains undergo a longer strain-hardening phase than more rounded materials. This might explain why analogue models consisting of angular grains accommodate deformation in a more distributed manner prior to strain localisation than models consisting of rounded grains.

Long-term Responses of Mountain Ecosystems to Environmental Changes: Resilience, Adjustment, and Vulnerability

The steep environmental gradients of mountain ecosystems over short distances reflect large gradients of several climatic parameters and hence provide excellent possibilities for ecological research on the effects of environmental change. To gain a better understanding of the dynamics of abiotic and biotic parameters of mountain ecosystems, long-term records are required since permanent plots in mountain regions cover in the best case about 50 - 70 years. In order to extend investigations of ecological dynamics beyond these temporal limitations of permanent plots, paleoecological approaches can be used if the sampling resolution can be adapted to ecological research questions, e.g. a sample every 10 years. Paleoecological studies in mountain ecosystems can provide new ecological insights through the combination of different spatial and temporal scales. [f we thus improve our understanding of processes across both steep environmental gradients and different time scales, we may be able to better estimate ecosystem responses to current and future environmental change (Ammann et al. 1993; Lotter et al. 1997). The complexity of ecological interactions in mountain regions forces us to concentrate on a number of sub-systems - without losing sight of the wider context. Here, we summarize a few case studies on the effects of Holocene climate change and disturbance on the vegetation of the Western Alps. To categorize the main response modes of vegetation to climatic change and disturbance in the Alps we use three classes of ecological behaviour: "resilience", "adjustment", and "vulnerability", We assume a resilient (or elastic) behaviour if vegetation is able to recover to its former state, regaining important ecosystem characteristics, such as floristic composition, biodiversity, species abundances, and biomass (e.g. Küttel 1990; Aber and Melillo 199 1). Conversely, vegetation displacements may occur in response to climatic change and/or disturbance. In some cases, this may culminate in irreversible large-scale processes such as species and/or community extinctions. Such drastic developments indicate high ecosystem vulnerability (or inelasticity or instability, for detailed definitions see Küttel 1990; Aber and Melillo 199 1) to climatic change and/or disturbance. In this sense, the "vulnerability" (or instability) of an ecosystem is expressed by the degree of failure to recover to the original state before disturbance and/or climatic change. Between these two extremes (resilience vs. vulnerability), ecosystem adjustments to climatic change and/or disturbance may occur, including the appearance of new and/or the disappearance of old species. The term "adjustment" is hence used to indicate the response of vegetational communities, which adapted to new environmental conditions without losing their main character. For forest ecosystems, we assume vegetational adjustments (rather than vulnerability) if the dominant (or co-dominant) tree species are not outnumbered or replaced by formerly unimportant plant species or new invaders. Adaptation as a genetic process is not discussed here and will require additional pbylogeographical studies (that incorporate the analysis of ancient DNA) in order to fully understand the distributions of ecotypes.

On ANOVA Decompositions of Kernels and Gaussian Random Field Paths

The FANOVA (or “Sobol’-Hoeffding”) decomposition of multivariate functions has been used for high-dimensional model representation and global sensitivity analysis. When the objective function f has no simple analytic form and is costly to evaluate, computing FANOVA terms may be unaffordable due to numerical integration costs. Several approximate approaches relying on Gaussian random field (GRF) models have been proposed to alleviate these costs, where f is substituted by a (kriging) predictor or by conditional simulations. Here we focus on FANOVA decompositions of GRF sample paths, and we notably introduce an associated kernel decomposition into 4 d 4d terms called KANOVA. An interpretation in terms of tensor product projections is obtained, and it is shown that projected kernels control both the sparsity of GRF sample paths and the dependence structure between FANOVA effects. Applications on simulated data show the relevance of the approach for designing new classes of covariance kernels dedicated to high-dimensional kriging.