The relative importance of seed competition, resource competition and perturbations on community structure

While the regional climate is the primary selection pressure for whether a plant strategy can survive, however, competitive interactions strongly affect the relative abundances of plant strategies within communities. Here, we investigate the relative importance of competition and perturbations on the development of vegetation community structure. To do so, we develop DIVE (Dynamics and Interactions of VEgetation), a simple general model that links plant strategies to their competitive dynamics, using growth and reproduction characteristics that emerge from climatic constraints. The model calculates population dynamics based on establishment, mortality, invasion and exclusion in the presence of different strengths of perturbations, seed and resource competition. The highest levels of diversity were found in simulations without competition as long as mortality is not too high. However, reasonable successional dynamics were only achieved when resource competition is considered. Under high levels of competition, intermediate levels of perturbations were required to obtain coexistence. Since succession and coexistence are observed in plant communities, we conclude that the DIVE model with competition and intermediate levels of perturbation represents an adequate way to model population dynamics. Because of the simplicity and generality of DIVE, it could be used to understand vegetation structure and functioning at the global scale and the response of vegetation to global change

The role of plant functional trade-offs for biodiversity changes and biome shifts under scenarios of global climatic change

The global geographic distribution of biodiversity and biomes is determined by species-specific physiological tolerances to climatic constraints. Current vegetation models employ empirical bioclimatic relationships to predict present-day vegetation patterns and to forecast biodiversity changes and biome shifts under climatic change. In this paper, we consider trade-offs in plant functioning and their responses under climatic changes to forecast and explain changes in plant functional richness and shifts in biome geographic distributions. <br><br> The Jena Diversity model (JeDi) simulates plant survival according to essential plant functional trade-offs, including ecophysiological processes such as water uptake, photosynthesis, allocation, reproduction and phenology. We use JeDi to quantify changes in plant functional richness and biome shifts between present-day and a range of possible future climates from two SRES emission scenarios (A2 and B1) and seven global climate models using metrics of plant functional richness and functional identity. <br><br> Our results show (i) a significant loss of plant functional richness in the tropics, (ii) an increase in plant functional richness at mid and high latitudes, and (iii) a pole-ward shift of biomes. While these results are consistent with the findings of empirical approaches, we are able to explain them in terms of the plant functional trade-offs involved in the allocation, metabolic and reproduction strategies of plants. We conclude that general aspects of plant physiological tolerances can be derived from functional trade-offs, which may provide a useful process- and trait-based alternative to bioclimatic relationships. Such a mechanistic approach may be particularly relevant when addressing vegetation responses to climatic changes that encounter novel combinations of climate parameters that do not exist under contemporary climate

Developments in understanding and assessment of egg and egg product quality over the last century

The hen's egg, in the form of table eggs and egg products, forms a staple part of the world's total protein consumption. In the last century, there has been considerable research effort focusing on ways of improving egg production and enhancing the quality of eggs. More recently, and with the development and application of new molecular technologies, our understanding and knowledge of how an egg is formed, what it actually consists of, in terms of its major versus minor components, and what the functional roles of each of these components might be, have been greatly enhanced. For example, new previously unknown molecules with specific activity or functional properties have been discovered in the egg albumen and yolk, some of which have potential uses in pharmaceutical and other food related applications. This review paper, which is the collaborative effort of members of Working Group 4 - Quality of Eggs and Egg Products - of the European Federation of WPSA, describes the scientific research behind a number of these major advances and provides some insight to the focus of current research in this area

Measurement of Creep Deformation across Welds in 316H Stainless Steel Using Digital Image Correlation

Spatially resolved measurement of creep deformation across weldments at high temperature cannot be achieved using standard extensometry approaches. In this investigation, a Digital Image Correlation (DIC) based system has been developed for long-term high-temperature creep strain measurement in order to characterise the material deformation behaviour of separate regions of a multi-pass weld. The optical system was sufficiently stable to allow a sequence of photographs to be taken suitable for DIC analysis of creep specimens tested at a temperature of 545 °C for over 2000 h. The images were analysed to produce local creep deformation curves from two cross-weld samples cut from contrasting regions of a multi-pass V-groove weld joining thick-section AISI Type 316H austenitic stainless steel. It is shown that for this weld, the root pass is the weakest region of the structure in creep, most likely due to the large number of thermal cycles it has experienced during the fabrication process. The DIC based measurement method offers improved spatial resolution over conventional methods and greatly reduces the amount of material required for creep characterisation of weldments

Hermansky-Pudlak syndrome type 2 manifests with fibrosing lung disease early in childhood

Background: Hermansky-Pudlak syndrome (HPS), a hereditary multisystem disorder with oculocutaneous albinism, may be caused by mutations in one of at least 10 separate genes. The HPS-2 subtype is distinguished by the presence of neutropenia and knowledge of its pulmonary phenotype in children is scarce. Methods: Six children with genetically proven HPS-2 presented to the chILD-EU register between 2009 and 2017; the data were collected systematically and imaging studies were scored blinded. Results: Pulmonary symptoms including dyspnea, coughing, need for oxygen, and clubbing started 3.3 years before the diagnosis was made at the mean age of 8.83 years (range 2-15). All children had recurrent pulmonary infections, 3 had a spontaneous pneumothorax, and 4 developed scoliosis. The frequency of pulmonary complaints increased over time. The leading radiographic pattern was ground-glass opacities with a rapid increase in reticular pattern and traction bronchiectasis between initial and follow-up Computer tomography (CT) in all subjects. Honeycombing and cysts were newly detectable in 3 patients. Half of the patients received a lung biopsy for diagnosis; histological patterns were cellular non-specific interstitial pneumonia, usual interstitial pneumonia-like, and desquamative interstitial pneumonia. Conclusions: HPS-2 is characterized by a rapidly fibrosing lung disease during early childhood. Effective treatments are required

Tools for Semi-automated Landform Classification: A Comparison in the Basilicata Region (Southern Italy)

Recent advances in spatial methods of digital elevation model (DEMs) analysis have addressed many research topics on the assessment of morphometric parameters of the landscape. Development of computer algorithms for calculating the geomorphometric properties of the Earth’s surface has allowed for expanding of some methods in the semi-automatic recognition and classification of landscape features. In such a way, several papers have been produced, documenting the applicability of the landform classification based on map algebra. The Topographic Position Index (TPI) is one of the most widely used parameters for semi-automated landform classification using GIS software. The aim was to apply the TPI classes for landform classification in the Basilicata Region (Southern Italy). The Basilicata Region is characterized by an extremely heterogeneous landscape and geological features. The automated landform extraction, starting from two different resolution DEMs at 20 and 5 m-grids, has been carried out by using three different GIS software: Arcview, Arcmap, and SAGA. Comparison of the landform maps resulting from each software at a different scale has been realized, furnishing at the end the best landform map and consequently a discussion over which is the best software implementation of the TPI method