Development of powder diffraction apparatus for small-angle X-ray scattering measurements

A novel type of X-ray collimation system attached to commercial powder diffractometers makes the structural characterization of nanomaterials possible in a wide size range from <0.1 to 100 nm by combination of the small- and wide-angle X-ray scattering techniques. There is no dead interval in the detection between the small- and wide-angle regimes. This device can be attached to any existing 'θ/θ' powder diffractometer, providing a multi-functional small- and wide-angle X-ray scattering/diffraction (SWAXS) apparatus. After proper alignment and adjustment, the device can be removed and re-attached at any time to switch between normal and SWAXS functions. Copyright © International Union of Crystallography 2013

Using a robust multi‐settings inference framework on published datasets still reveals limited support for the abundant centre hypothesis: More testing needed on other datasets

Aim: The abundant centre hypothesis (ACH) predicts a negative relationship between species abundance and the distance to the geographical range centre. Since its formulation, empirical tests of the ACH have involved different settings (e.g. the distance to the ecological niche or to the geographical range centre), but studies found contrasting support for this hypothesis. Here, we evaluate whether these discrepancies might stem from differences regarding the context in which the ACH is tested (geographical or environmental), how distances are measured, how species envelopes are delineated, how the relationship is evaluated and which data are used. Location: The Americas. Time period: 1800–2017. Major taxa studied: Mammals, birds, fish, and tree seedlings. Methods: Using published abundance data for 801 species, together with species range maps, we tested the ACH using three distance metrics in both environmental and geographical spaces with range and niche envelopes delineated using two different algorithms, totalling 12 different settings. We then evaluated the distance–abundance relationship using correlation coefficients (traditional approach) and mixed-effect models to reduce the effect of sampling noise on parameter estimates. Results: Similar to previous studies, correlation coefficients indicated an absence of effect of distance on abundance for all taxonomic groups and settings. In contrast, mixed-effect models highlighted relationships of various strengths and shapes, with a tendency for more theoretically supported settings to provide stronger support for the ACH. The relationships were however not consistent across taxonomic groups and settings, and were sometimes even opposite to ACH expectations. Main conclusions: We found mixed and inconclusive results regarding the ACH. These results corroborate recent findings, and suggest either that our ability to predict abundances from the location of populations within geographical or environmental spaces is low, or that the data used here have a poor signal-to-noise-ratio. The latter calls for further testing on other datasets using the same range of settings and methodological framework

Modeling the distribution of coprophagous beetle species in the Western Swiss Alps

Coprophagous beetles are essential for fecal matter removal and are thus considered key ecosystem services providers. Yet, our knowledge of these beetles’ distribution and ecology remains very limited. Here, we used Species Distribution Models (SDM) to investigate the species-environment relationships (i.e. their niche) and predict the geographic distribution of coprophagous beetles in the Western Swiss Alps. We used our own sampled data and existing national data from the Swiss faunal database to calibrate, for each species, a regional and a national SDM respectively. In both models, the best predictors were temperature and rock cover proportion, while a soil characteristic (∂13C) indicating its organic content and texture was important in the regional models and precipitations in the Swiss models. The model performed better for species specialized on low or high altitudes than for generalist species occurring in a large altitudinal range. The model performances were neither influenced by the size, nor by the nesting behavior (laying eggs inside or below the excrements) of the species. We also showed that species richness decreased with altitude. This study opens new perspective for a better knowledge of coprophagous beetle’s ecology and a useful tool for their conservation in mountain regions

Rarity types among plant species with high conservation priority in Switzerland

Abstract.: Broennimann O., Vittoz P., Moser D. and Guisan A. 2005. Rarity types among plant species with high conservation priority in Switzerland. Bot. Helv. 115: 95-108. We investigated the ecogeographic characteristics of 118 Swiss plant species listed as those deserving highest conservation priority in a national conservation guide and classified them into the seven Rabinowitz' rarity types, taking geographic distribution, habitat rarity and local population size into account. Our analysis revealed that species with high conservation priority in Switzerland mostly have a very restricted geographic distribution in Switzerland and generally occur in rare habitats, but do not necessarily constitute small populations and are generally not endemics on a global scale. Moreover, species that are geographically very restricted on a regional scale are not generally restricted on a global scale. By analysing relationships between rarity and IUCN extinction risks for Switzerland, we demonstrated that species with the highest risk of extinction are those with the most restricted geographic distribution; whereas species with lower risk of extinction (but still high conservation priority) include many regional endemics. Habitat rarity and local population size appeared to be of minor importance for the assessment of extinction risk in Switzerland, but the total number of fulfilled rarity criteria still correlated positively with the severity of extinction risk. Our classification is the first preliminary assessment of the relative importance of each rarity type among endangered plant species of the Swiss flora and our results underline the need to distinguish between a regional and a global responsibility for the conservation of rare and endangered specie

High Diversity among Feather-Degrading Bacteria from a Dry Meadow Soil

The aim of this study was to determine the diversity of cultivable bacteria able to degrade feathers and present in soil under temperate climate. We obtained 33 isolates from soil samples, which clustered in 13 ARDRA groups. These isolates were able to grow on solid medium with pigeon feathers as sole carbon and nitrogen source. One representative isolate of each ARDRA group was selected for identification and feather degradation tests. The phylogenetic analysis of 16S rDNA gene fragments revealed that only 4 isolates were gram positives. Two other isolates belonged to the Cytophaga-Flavobacterium group, and the remaining to Proteobacteria. High keratinolysis activity was found for strains related to Bacillus, Cytophagales, Actinomycetales, and Proteobacteria. The 13 selected strains showed variable efficiency in degrading whole feathers and 5 strains were able to degrade maximum 40% to 98% of the whole feathers. After 4 weeks incubation, five strains grown on milled feathers produced more than 0.5 U keratinase per mL. Keratinase activities across the 13 strains were positively correlated with the percentage of feather fragmentation and protein concentratio

More than range exposure: global otters’ vulnerability to climate change

Climate change impact on species is commonly assessed by predicting species’ range change, a measure of a species’ extrinsic exposure. However, this is only one dimension of species’ vulnerability to climate change. Spatial arrangement of suitable habitats (e.g., fragmentation), their degree of protection or human disturbance, as well as species’ intrinsic sensitivity, such as climatic tolerances, are often neglected. Here, we consider components of species’ intrinsic sensitivity to climate change (climatic niche specialization and marginality) together with components of extrinsic exposure (changes in range extent, fragmentation, coverage of protected areas, and human footprint) to develop an integrated vulnerability index to climate change for world’s freshwater otters. As top freshwater predators, otters are among the most vulnerable mammals, with most species being threatened by habitat loss and degradation. All dimensions of climate change exposure were based on present and future predictions of species distributions. Annual mean temperature, mean diurnal temperature range, mean temperature of the wettest quarter, precipitation during the wettest quarter, and precipitation seasonality prove the most important variables for otters. All species are vulnerable to climate change, with global vulnerability index ranging from -0,19 for Lontra longicaudis to -36,9 for Aonyx congicus. However, we found that, for a given species, climate change can have both positive and negative effects on different components of extrinsic exposure, and that measures of species’ sensitivity are not necessarily congruent with measures of exposure. For instance, the range of all African species would be negatively affected by climate change, but their different sensitivity offers a more (Hydrictis maculicollis, Aonyx capensis) or less (Aonyx congicus) pessimistic perspective on their ability to cope with climate change. Also, highly sensitive species like the South-American Pteronura brasiliensis, Lontra provocax, and Lutra perspicillata might face no exposure to climate change. For the Asian Lutra sumatrana, climate change would instead lead to an increased, less fragmented, and more protected range extent, but the range extent would also be shifted into areas with higher human disturbances. Our study represents a balanced example of how to develop an index aimed at comparatively evaluating vulnerability to climate change of different species by combining different aspects of sensitivity and exposure, providing additional information on which to base more efficient conservation strategies

Unifying niche shift studies: insights from biological invasions.

Assessing whether the climatic niche of a species may change between different geographic areas or time periods has become increasingly important in the context of ongoing global change. However, approaches and findings have remained largely controversial so far, calling for a unification of methods. Here, we build on a review of empirical studies of invasion to formalize a unifying framework that decomposes niche change into unfilling, stability, and expansion situations, taking both a pooled range and range-specific perspective on the niche, while accounting for climatic availability and climatic analogy. This framework provides new insights into the nature of climate niche shifts and our ability to anticipate invasions, and may help in guiding the design of experiments for assessing causes of niche changes

Selecting predictors to maximize the transferability of species distribution models: lessons from cross-continental plant invasions

Aim: Niche-based models of species distribution (SDMs) are commonly used to predict impacts of global change on biodiversity but the reliability of these predictions in space and time depends on their transferability. We tested how the strategy to choose predictors impacts the SDMs' transferability at a cross-continental scale. Location: North America, Eurasia and Australia Method: We used a systematic approach including 50 Holarctic plant invaders and 27 initial predictor variables, considering 10 different strategies to variable selection, accounting for predictors' proximality, multicollinearity and climate analogy. We compared the average performance per strategy, some of them using a large number of random predictor combinations. Next, we looked for the single best model for each species across all possible predictor combinations, by pooling models across all strategies. Transferability was considered as the predictive success of SDMs calibrated in native range and projected onto the invaded range. Results: Two strategies showed better SDMs' transferability on average: a set of predictors known for their ecologically-meaningful effects on plant distribution, and the two first axes of a principal component analysis calibrated on all predictor variables (Spc2). From the &gt;2000 combinations of predictors per species across strategies, the best set of predictors yielded SDMs with good transferability for 45 species (90%). These best combinations consisted in a random selection of 8 predictors (45 sp) and in Spc2 (5 sp). We also found that internal cross-validation was not sufficient to fully inform about SDMs' transferability to a distinct range. Main conclusion: Transferring SDMs at the macroclimatic scale, and thus anticipating invasions, is possible for the large majority of invasive plants considered in this study, but the predictions' accuracy relies strongly on the choice of predictors. From our results, we recommend including either the state-of-the-art proximal variables or a reduced and orthogonalised set to obtain robust SDMs' projections

Snow cover persistence as a useful predictor of alpine plant distributions

Aim: We examine whether the addition of snow cover persistence in plant species distribution models (SDMs) improves their predictive power. We investigate the link between species’ ecology and SDM improvements by the addition of various snow cover persistence predictors. Location: Western Swiss Alps. Taxon: 206 alpine flowering plants (Angiospermes). Methods: We produced three maps of landsat satellite-based snow cover persistence indices over an entire mountain region, one of them using an online open access platform allowing quick and easy replication and used them as a predictor in plant SDMs alongside commonly used predictors. We tested whether this improved the predictive performance of plant SDMs. Results: All three snow cover persistence indices improved the overall SDM predictive accuracy, but the overall improvement was potentially limited by their correlation with other climatic predictors. Alpine plant species known for their dependence on snow benefited more from the additional snow information. Main conclusions: Snow cover persistence should be used for predicting at least the distribution of alpine, snow related plant species. Given that adding snow cover improves SDMs and that snow duration decreases as climate warms, future predictions of alpine plant distributions should account for both snow predictor and associated snow change scenarios