Current-induced two-level fluctuations in pseudo spin-valves (Co/Cu/Co) nanostructures

Two-level fluctuations of the magnetization state of pseudo spin-valve pillars Co(10 nm)/Cu(10 nm)/Co(30 nm) embedded in electrodeposited nanowires (~40 nm in diameter, 6000 nm in length) are triggered by spin-polarized currents of 10^7 A/cm^2 at room temperature. The statistical properties of the residence times in the parallel and antiparallel magnetization states reveal two effects with qualitatively different dependences on current intensity. The current appears to have the effect of a field determined as the bias field required to equalize these times. The bias field changes sign when the current polarity is reversed. At this field, the effect of a current density of 10^7 A/cm^2 is to lower the mean time for switching down to the microsecond range. This effect is independent of the sign of the current and is interpreted in terms of an effective temperature for the magnetization.Comment: 4 pages, 5 figures, revised version, to be published in Phys. Rev. Let

Biogeophysical controls on soil-atmosphere thermal differences: implications on warming Arctic ecosystems

Soil temperature (ST) has a key role in Arctic ecosystem functioning and global environmental change. However, soil thermal conditions do not necessarily follow synoptic temperature variations. This is because local biogeophysical processes can lead to a pronounced soil-atmosphere thermal offset (∆T) while altering the coupling (βT) between ST and ambient air temperature (AAT). Here, we aim to uncover the spatiotemporal variation in these parameters and identify their main environmental drivers. By deploying a unique network of 322 temperature loggers and surveying biogeophysical processes across an Arctic landscape, we found that the spatial variation in ∆T during the AAT≤0 period (mean ∆T=-0.6°C, standard deviation ± 1.0°C) was directly and indirectly constrained by local topography controlling snow depth. By contrast, during the AAT>0 period, ∆T was controlled by soil characteristics, vegetation and solar radiation (∆T=6.0°C ± 1.2°C). Importantly, ∆T was not constant throughout the seasons reflecting the influence of βT on the rate of local soil warming being stronger after (mean βT = 0.8 ± 0.1) than before (βT = 0.2 ± 0.2) snowmelt. Our results highlight the need for continuous microclimatic and local environmental monitoring, and suggest a potential for large buffering and non-uniform warming of snow-dominated Arctic ecosystems under projected temperature increase

Using species richness and functional traits predictions to constrain assemblage predictions from stacked species distribution models

Aim: Modelling species at the assemblage level is required to make effective forecast of global change impacts on diversity and ecosystem functioning. Community predictions may be achieved using macroecological properties of communities (MEM), or by stacking of individual species distribution models (S-SDMs). To obtain more realistic predictions of species assemblages, the SESAM framework suggests applying successive filters to the initial species source pool, by combining different modelling approaches and rules. Here we provide a first test of this framework in mountain grassland communities. Location: The western Swiss Alps. Methods: Two implementations of the SESAM framework were tested: a "Probability ranking" rule based on species richness predictions and rough probabilities from SDMs, and a "Trait range" rule that uses the predicted upper and lower bound of community-level distribution of three different functional traits (vegetative height, specific leaf area and seed mass) to constraint a pool of environmentally filtered species from binary SDMs predictions. Results: We showed that all independent constraints expectedly contributed to reduce species richness overprediction. Only the "Probability ranking" rule allowed slightly but significantly improving predictions of community composition. Main conclusion: We tested various ways to implement the SESAM framework by integrating macroecological constraints into S-SDM predictions, and report one that is able to improve compositional predictions. We discuss possible improvements, such as further improving the causality and precision of environmental predictors, using other assembly rules and testing other types of ecological or functional constraints

Learning from model errors: Can land use, edaphic and very high-resolution topo-climatic factors improve macroecological models of mountain grasslands?

Aim: Assess the potential of new predictors (land use, edaphic factors and high-resolution topographic and climatic variables, i.e., topo-climatic) to improve the prediction of plant community functional traits (specific leaf area, vegetative height and seed mass) and species richness in models of mountain grasslands. Location: The western Swiss Alps Methods: Using 912 grassland plots, we constructed predictive models for community-weighted means of plant traits and species richness using high resolution (25 m) topo-climatic predictors traditionally used in previous modelling studies in this area. In addition, 78 new plots were sampled for evaluation and error assessment in four narrower sets of homogenous conditions based on predictions by the topo-climatic models within two elevation belts (montane and alpine). New, finer-scale predictors were generated from direct field measurements or very high-resolution (5 m) numerical data. We then used multimodel inference to test the capacity of these finer predictors to explain part of the residual variance in the initial topo-climatic models. Results: We showed that the finer-scale predictors explained up to 44% of the residual variance in the classical topo-climatic models. The very high-resolution topographic position, soil C/N ratio and pH performed notably well in our analysis. Land use (farming intensity) was highlighted as potentially important in montane grasslands, but improvements were only significant for species richness predictions. Main conclusions: Compared with classical topo-climatic models, the new, finer-scale predictors significantly improved the prediction of all traits and species richness in alpine plant communities and that of specific leaf area and richness in montane grasslands. The differences in the importance of the predictors, dependent on both trait and position along the elevation gradient, highlight the different factors that shape the distribution of species and communities along elevation gradients

Spin-dependent transport in cluster-assemblednanostructures: influence of cluster size and matrix material

Abstract.: Spin-dependent transport in granular metallic nanostructures has been investigated by means of a thermoelectric measurement. Cobalt clusters of well-defined size (〈n〉 = 15-600) embedded in copper and silver matrices show magnetic field responses of up to several hundred percent at low temperature. The experimental observations are attributed to spin mixing. The influence of cluster size and matrix are discusse

Improving spatial predictions of taxonomic, functional and phylogenetic diversity

In this study, we compare two community modelling approaches to determine their ability to predict the taxonomic, functional and phylogenetic properties of plant assemblages along a broad elevation gradient and at a fine resolution. The first method is the standard stacking individual species distribution modelling (SSDM) approach, which applies a simple environmental filter to predict species assemblages. The second method couples the SSDM and macroecological modelling (MEMSSDM-MEM) approaches to impose a limit on the number of species co-occurring at each site. Because the detection of diversity patterns can be influenced by different levels of phylogenetic or functional trees, we also examine whether performing our analyses from broad to more exact structures in the trees influences the performance of the two modelling approaches when calculating diversity indices. We found that coupling the SSDM with the MEM improves the overall predictions for the three diversity facets compared with those of the SSDM alone. The accuracy of the SSDM predictions for the diversity indices varied greatly along the elevation gradient, and when considering broad to more exact structure in the functional and phylogenetic trees, the SSDM-MEM predictions were more stable. SSDM-MEM moderately but significantly improved the prediction of taxonomic diversity, which was mainly driven by the corrected number of predicted species. The performance of both modelling frameworks increased when predicting the functional and phylogenetic diversity indices. In particular, fair predictions of the taxonomic composition by SSDM-MEM led to increasingly accurate predictions of the functional and phylogenetic indices, suggesting that the compositional errors were associated with species that were functionally or phylogenetically close to the correct ones; however, this did not always hold for the SSDM predictions.Synthesis. In this study, we tested the use of a recently published approach that couples species distribution and macroecological models to provide the first predictions of the distribution of multiple facets of plant diversity: taxonomic, functional and phylogenetic. Moderate but significant improvements were obtained; thus, our results open promising avenues for improving our ability to predict the different facets of biodiversity in space and time across broad environmental gradients when functional and phylogenetic information is available

Disentangling the processes driving plant assemblages in mountain grasslands across spatial scales and environmental gradients

1. Habitat filtering and limiting similarity are well-documented ecological assembly processes that hierarchically filter species across spatial scales, from a regional pool to local assemblages. However, information on the effects of fine-scale spatial partitioning of species, working as an additional mechanism of coexistence, on community patterns, is much scarcer. 2. In this study, we quantified the importance of fine-scale spatial partitioning, relative to habitat filtering and limiting similarity, in structuring grassland communities in the western Swiss Alps. To do so, 298 vegetation plots (2 m × 2 m ) each with five nested subplots (20 cm × 20 cm) were used for trait based assembly tests (i.e. comparisons with several alternative null expectations), examining the observed plot and subplot level α-diversity (indicating habitat filtering and limiting similarity) and the between-subplot β-diversity of traits (indicating fine-scale spatial partitioning). We further assessed variations in the detected signatures of these assembly processes along a set of environmental gradients. 3. We found habitat filtering to be the dominating assembly process at the plot level with diminished effect at the subplot level, while limiting similarity prevailed at the subplot level with weaker average effect at the plot level. Plot-level limiting similarity was positively correlated with fine-scale partitioning suggesting that the trait divergence may result from a combination of competitive exclusion between functionally similar species and environmental micro-heterogeneities. Overall, signatures of assembly processes only marginally changed along environmental gradients but the observed trends were more prominent at the plot than at the subplot scale. Synthesis: Our study emphasises the importance of considering multiple assembly processes and traits simultaneously across spatial scales and environmental gradients to understand the complex drivers of plant community composition

Self-sufficient asymmetric reduction of β-ketoesters catalysed by a novel and robust thermophilic alcohol dehydrogenase co-immobilised with NADH

β-Hydroxyesters are essential building blocks utilised by the pharmaceutical and food industries in the synthesis of functional products. Beyond the conventional production methods based on chemical catalysis or whole-cell synthesis, the asymmetric reduction of β-ketoesters with cell-free enzymes is gaining relevance. To this end, a novel thermophilic (S)-3-hydroxybutyryl-CoA dehydrogenase from Thermus thermophilus HB27 (Tt27-HBDH) has been expressed, purified and biochemically characterised, determining its substrate specificity towards β-ketoesters and its dependence on NADH as a cofactor. The immobilization of Tt27-HBDH on agarose macroporous beads and its subsequent coating with polyethyleneimine has been found the best strategy to increase the stability and workability of the heterogeneous biocatalyst. Furthermore, we have embedded NADH in the cationic layer attached to the porous surface of the carrier. Since Tt27-HBDH catalyses cofactor recycling through 2-propanol oxidation, we achieve a self-sufficient heterogeneous biocatalyst where NADH is available for the immobilised enzymes but its lixiviation to the reaction bulk is avoided. Taking advantage of the autofluorescence of NADH, we demonstrate the activity of the enzyme towards the immobilised cofactor through single-particle analysis. Finally, we tested the operational stability in the asymmetric reduction of β-ketoesters in batch, succeeding in the reuse of both the enzyme and the co-immobilised cofactor up to 10 reaction cycles

Determination of spin-dependent Seebeck coefficients of CoFeB/MgO/CoFeB magnetic tunnel junction nanopillars

We investigate the spin-dependent Seebeck coefficient and the tunneling magneto thermopower of CoFeB/MgO/CoFeB magnetic tunnel junctions (MTJ) in the presence of thermal gradients across the MTJ. Thermal gradients are generated by an electric heater on top of the nanopillars. The thermo power voltage across the MTJ is found to scale linearly with the heating power and reveals similar field dependence as the tunnel magnetoresistance. The amplitude of the thermal gradient is derived from calibration measurements in combination with finite element simulations of the heat flux. Based on this, large spin-dependent Seebeck coefficients of the order of (240 \pm 110) \muV/K are derived. From additional measurements on MTJs after dielectric breakdown, a tunneling magneto thermopower up to 90% can be derived for 1.5 nm MgO based MTJ nanopillars

A logistic map approach to economic cycles I. The best adapted companies

A birth-death lattice gas model about the influence of an environment on the fitness and concentration evolution of economic entities is analytically examined. The model can be mapped onto a high order logistic map. The control parameter is a (scalar) "business plan". Conditions are searched for growth and decay processes, stable states, upper and lower bounds, bifurcations, periodic and chaotic solutions. The evolution equation of the economic population for the best fitted companies indicates "microscopic conditions" for cycling. The evolution of a dynamic exponent is shown as a function of the business plan parameters.Comment: 10 pages, 5 postscript figure