New insights into postglacial vegetation dynamics and environmental conditions of Península Avellaneda, southwest Patagonia, revealed by plant macrofossils and pollen analysis

Reconstruction of the history of past events becomes more objective when considering an increased number of possible indicators. Combining plant macrofossil analysis with pollen analysis has the potential to give a more detailed picture of the composition of the local vegetation. Patagonia has been the focus of several palaeoclimatic studies, in particular of latitudinal variations in southern westerly winds, which have global implications. However, palaeoecological reconstructions using plant macrofossils in conjunction with pollen analysis are still scarce. We analysed the plant macrofossils contained in two peat sequences from Península Avellaneda (located in the Lago Argentino basin, southwest Patagonia) and integrate these results with pollen information. Plant macrofossils and pollen records provide a well-resolved history of vegetation and catchment conditions starting from ca. 13,000 cal yrs BP. We also investigated the development of plant communities following the retreat of glaciers, with emphasis on the expansion of Nothofagus species (which were restricted under glacial climates) and particular reference to Nothofagus pumilio. These results provide an example of how plant macrofossil analysis (taxonomic, taphonomic and statistical) in combination with pollen analysis results in a better understanding of postglacial environmental history

Macroscopic Dynamics of Multi-Lane Traffic

We present a macroscopic model of mixed multi-lane freeway traffic that can be easily calibrated to empirical traffic data, as is shown for Dutch highway data. The model is derived from a gas-kinetic level of description, including effects of vehicular space requirements and velocity correlations between successive vehicles. We also give a derivation of the lane-changing rates. The resulting dynamic velocity equations contain non-local and anisotropic interaction terms which allow a robust and efficient numerical simulation of multi-lane traffic. As demonstrated by various examples, this facilitates the investigation of synchronization patterns among lanes and effects of on-ramps, off-ramps, lane closures, or accidents.Comment: For related work see http://www.theo2.physik.uni-stuttgart.de/helbing.htm

The VANDELS ESO public spectroscopic survey

VANDELS is a uniquely deep spectroscopic survey of high-redshift galaxies with the VIMOS spectrograph on ESO’s Very Large Telescope (VLT). The survey has obtained ultradeep optical (0.48 < λ < 1.0 μ m) spectroscopy of ≃2100 galaxies within the redshift interval 1.0 ≤ z ≤ 7.0, over a total area of ≃0.2 deg2 centred on the CANDELS Ultra Deep Survey and Chandra Deep Field South fields. Based on accurate photometric redshift pre-selection, 85 per cent of the galaxies targeted by VANDELS were selected to be at z ≥ 3. Exploiting the red sensitivity of the refurbished VIMOS spectrograph, the fundamental aim of the survey is to provide the high-signal-to-noise ratio spectra necessary to measure key physical properties such as stellar population ages, masses, metallicities, and outflow velocities from detailed absorption-line studies. Using integration times calculated to produce an approximately constant signal-to-noise ratio (20 < tint< 80 h), the VANDELS survey targeted: (a) bright star-forming galaxies at 2.4 ≤ z ≤ 5.5, (b) massive quiescent galaxies at 1.0 ≤ z ≤ 2.5, (c) fainter star-forming galaxies at 3.0 ≤ z ≤ 7.0, and (d) X-ray/Spitzer-selected active galactic nuclei and Herschel-detected galaxies. By targeting two extragalactic survey fields with superb multiwavelength imaging data, VANDELS will produce a unique legacy data set for exploring the physics underpinning high-redshift galaxy evolution. In this paper, we provide an overview of the VANDELS survey designed to support the science exploitation of the first ESO public data release, focusing on the scientific motivation, survey design, and target selection

Avaliação de fluxos de calor e evapotranspiração pelo modelo SEBAL com uso de dados do sensor ASTER

O objetivo deste trabalho foi avaliar a eficiência da aplicação do modelo SEBAL em estimar os fluxos de energia em superfície e a evapotranspiração diária, numa extensa área de cultivo de arroz irrigado, no município de Paraíso do Sul, RS, tendo como parâmetros dados do sensor ASTER. As variáveis estudadas constituem importantes parâmetros do tempo e do clima em estudos agrometeorológicos e de racionalização no uso da água. As metodologias convencionais de estimativa desses parâmetros são pontuais e geralmente apresentam incertezas, que aumentam quando o interesse é o comportamento espacial desses parâmetros. Aplicou-se o algoritmo “Surface Energy Balance Algorithm for Land” (SEBAL), em uma imagem do sensor “Advanced Spaceborne Thermal Emission and Reflection Radiometer” (ASTER). As estimativas obtidas foram comparadas com medições em campo, realizadas por uma estação micrometeorológica localizada no interior da área de estudo. As estimativas mais precisas foram as de fluxo de calor sensível e de evapotranspiração diária, e a estimativa que apresentou maior erro foi a do fluxo de calor no solo. A metodologia empregada foi capaz de reproduzir os fluxos de energia em superfície de maneira satisfatória para estudos agrometeorológicos e de rendimento de culturas.The objective of this study was to evaluate the efficiency of SEBAL model in estimating soil surface energy fluxes and daily evapotranspiration for a large area of irrigated rice farms, near the municipality of Paraíso do Sul, RS, Brazil, using data from ASTER sensor. The evaluated variables are important weather and climatic parameters for agrometeorological studies and rationalization of water use. The conventional methodologies for estimating these parameters generally present uncertainties, which increase when concern is in the spatial behavior of such parameters. The Surface Energy Balance Algorithm for Land (SEBAL) was applied in an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) scene and the estimates were compared to micrometeorological data retrieved from a station located in the studied area. The most accurate modeled parameter estimatives were sensitive heat and evapotranspiration, and the one which presented the highest error was soil heat flux. The adopted methodology was able to reproduce surface energy fluxes for agrometeorological and crop yield studies

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

Evidence confirms an anthropic origin of Amazonian Dark Earths

Archaeology of the America