Replica Fourier Transforms on Ultrametric Trees, and Block-Diagonalizing Multi-Replica Matrices

The analysis of objects living on ultrametric trees, in particular the block-diagonalization of 4-replica matrices $M^{\alpha \beta ; \gamma \delta}$, is shown to be dramatically simplified through the introduction of properly chosen operations on those objects. These are the Replica Fourier Transforms on ultrametric trees. Those transformations are defined and used in the present work.Comment: Latex file, 14 page

Stability of the Mezard-Parisi solution for random manifolds

The eigenvalues of the Hessian associated with random manifolds are constructed for the general case of $R$ steps of replica symmetry breaking. For the Parisi limit $R\to\infty$ (continuum replica symmetry breaking) which is relevant for the manifold dimension $D<2$, they are shown to be non negative.Comment: LaTeX, 15 page

Functional traits reveal coastal vegetation assembly patterns in a short edaphic gradient in southern Brazil

The relationship between plant functional traits and soil variables is useful for understanding plant community composition and circumscribing plant functional groups to highlight their adaptations to environmental conditions. The principal aim of this study was to explain assembly patterns of coastal vegetation using functional traits along a short edaphic gradient. The work was carried out on the pioneer zone in the coastal lowland vegetation (foredune) in southern Brazil. We selected 40 functional traits related to the morphology and anatomy of leaves, stems and roots for 60 species recorded in 25 vegetation plots positioned along three transects from the shoreline to slacks. In each plot, floristic and soil data were collected, and functional traits measured. We analysed the relationships between species functional traits and soil factors through RLQ and fourth-corner analyses. Salinity and organic matter content were the most significant edaphic factors in the differentiation of foredune vegetation, while the most significant traits to explain plant adaptations to coastal environments were plant height, sclerenchyma, spongy parenchyma and reserves of inulin in the root. Two functional groups of plants were circumscribed: a conservative group formed by trees and shrubs dominated the Woody Community, with low values of SLA (specific leaf area), thick cuticles, high frequencies of phenolic compounds and crystals, woody stems and great plant heights, which tended to invest in permanent aerial organs; and a more heterogeneous group of herbaceous plants (found in Beach Community, Non-floodable, and Wet Communities) with acquisitive characteristics (high SLA values) or conservative strategy (rhizome and xylopodium). Finally, our results suggested that root and stem functional traits, which are infrequently taken into consideration, were useful to differentiate subtropical coastal plants and, in general, to study plant adaptations to environmental conditions in depth

Testing consumers’ acceptance for an extra-virgin olive oil with a naturally increased content in polyphenols: The case of ultrasounds extraction

Innovation is fundamental for all agri-food companies to increase competitiveness. Being extra-virgin olive oil (EVOO) a traditional food product (TFP), the main obstacle to innovation is its traditional nature. This study evaluated consumers’ acceptance for an EVOO with a naturally increased content of poliphenols, as it has been extracted through ultrasounds. This product has been compared with a set of emerging innovations that may be introduced in the next future. To this end, a choice experiment was carried out bent on the estimation of a Latent Class Model (LCM). A nationally-representative sample of EVOO consumers were involved in a web-based interview. The LCM analysis highlighted three segments of consumers: (1) innovative; (2) traditionalist; (3) cautious. Results showed that there is cluster of consumers willing to accept this innovation, therefore its introduction on the market appears to be possibly successful

Testing consumers' acceptance for an extra-virgin olive oil with a naturally increased content in polyphenols: The case of ultrasounds extraction

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Markedly Divergent Tree Assemblage Responses to Tropical Forest Loss and Fragmentation across a Strong Seasonality Gradient

We examine the effects of forest fragmentation on the structure and composition of tree assemblages within three seasonal and aseasonal forest types of southern Brazil, including evergreen, Araucaria, and deciduous forests. We sampled three southernmost Atlantic Forest landscapes, including the largest continuous forest protected areas within each forest type. Tree assemblages in each forest type were sampled within 10 plots of 0.1 ha in both continuous forests and 10 adjacent forest fragments. All trees within each plot were assigned to trait categories describing their regeneration strategy, vertical stratification, seed-dispersal mode, seed size, and wood density. We detected differences among both forest types and landscape contexts in terms of overall tree species richness, and the density and species richness of different functional groups in terms of regeneration strategy, seed dispersal mode and woody density. Overall, evergreen forest fragments exhibited the largest deviations from continuous forest plots in assemblage structure. Evergreen, Araucaria and deciduous forests diverge in the functional composition of tree floras, particularly in relation to regeneration strategy and stress tolerance. By supporting a more diversified light-demanding and stress-tolerant flora with reduced richness and abundance of shade-tolerant, old-growth species, both deciduous and Araucaria forest tree assemblages are more intrinsically resilient to contemporary human-disturbances, including fragmentation-induced edge effects, in terms of species erosion and functional shifts. We suggest that these intrinsic differences in the direction and magnitude of responses to changes in landscape structure between forest types should guide a wide range of conservation strategies in restoring fragmented tropical forest landscapes worldwide

<i>Gaia</i> Data Release 1. Summary of the astrometric, photometric, and survey properties

Context. At about 1000 days after the launch of Gaia we present the first Gaia data release, Gaia DR1, consisting of astrometry and photometry for over 1 billion sources brighter than magnitude 20.7. Aims. A summary of Gaia DR1 is presented along with illustrations of the scientific quality of the data, followed by a discussion of the limitations due to the preliminary nature of this release. Methods. The raw data collected by Gaia during the first 14 months of the mission have been processed by the Gaia Data Processing and Analysis Consortium (DPAC) and turned into an astrometric and photometric catalogue. Results. Gaia DR1 consists of three components: a primary astrometric data set which contains the positions, parallaxes, and mean proper motions for about 2 million of the brightest stars in common with the HIPPARCOS and Tycho-2 catalogues – a realisation of the Tycho-Gaia Astrometric Solution (TGAS) – and a secondary astrometric data set containing the positions for an additional 1.1 billion sources. The second component is the photometric data set, consisting of mean G-band magnitudes for all sources. The G-band light curves and the characteristics of ∼3000 Cepheid and RR-Lyrae stars, observed at high cadence around the south ecliptic pole, form the third component. For the primary astrometric data set the typical uncertainty is about 0.3 mas for the positions and parallaxes, and about 1 mas yr−1 for the proper motions. A systematic component of ∼0.3 mas should be added to the parallax uncertainties. For the subset of ∼94 000 HIPPARCOS stars in the primary data set, the proper motions are much more precise at about 0.06 mas yr−1. For the secondary astrometric data set, the typical uncertainty of the positions is ∼10 mas. The median uncertainties on the mean G-band magnitudes range from the mmag level to ∼0.03 mag over the magnitude range 5 to 20.7. Conclusions. Gaia DR1 is an important milestone ahead of the next Gaia data release, which will feature five-parameter astrometry for all sources. Extensive validation shows that Gaia DR1 represents a major advance in the mapping of the heavens and the availability of basic stellar data that underpin observational astrophysics. Nevertheless, the very preliminary nature of this first Gaia data release does lead to a number of important limitations to the data quality which should be carefully considered before drawing conclusions from the data

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives