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

Sensitivity analysis of the use of Life Cycle Impact Assessment methods: a case study on building materials

The main aim of this research is to perform a sensitivity analysis of a Life Cycle Assessment (LCA) case study to understand if the use of different Life Cycle Impact Assessment (LCIA) methods may lead to different conclusions by decision makers and stakeholders. A complete LCA was applied to non-load-bearing external climate walls for comparative purposes. The LCIA phase of the case study was performed using five different Impact Assessment Methods: EDIP 97/2003 (midpoint), CML 2001 (midpoint), Impact 2002+ (endpoint and midpoint), ReCiPe (endpoint and midpoint) and the ILCD recommended practices for LCIA (midpoint). The endpoint results were compared aggregately, and the midpoint categories concerning similar potential impacts were compared individually for the analysis of possible deviations. The observations and comparisons involved mostly the decision maker's point of view and not the differences among the characterization models. The endpoint LCIA showed that the only two methods which applied such an approach (Impact 2002+ and ReCiPe) provided different results and led to different conclusions. For midpoint LCIA, the results were completely consistent for the following impact categories: General Eutrophication, Aquatic and Freshwater Ecotoxicity, Ionizing Radiation, Particulate Matter Formation, and Resources Depletion. Global Warming, Terrestrial Ecotoxicity, Human Toxicity (except for the Non-carcinogens impact category) and Land Use (except for Natural Land Transformation) showed partially consistent results and pointed out to the same worst environmental alternative, but with a slightly different impact profile among the other alternatives. Ozone Layer depletion and Photochemical Oxidant Formation categories showed discrepant results and the impact profile differences between the older and newer methods were notable. Acidification, Terrestrial and Aquatic Eutrophication, Marine Ecotoxicity and Water Depletion showed substantially inconsistent results. (C) 2015 Elsevier Ltd. All rights reserved

In situ guided tissue regeneration in musculoskeletal diseases and aging: Implementing pathology into tailored tissue engineering strategies

In situ guided tissue regeneration, also addressed as in situ tissue engineering or endogenous regeneration, has a great potential for population-wide “minimal invasive” applications. During the last two decades, tissue engineering has been developed with remarkable in vitro and preclinical success but still the number of applications in clinical routine is extremely small. Moreover, the vision of population-wide applications of ex vivo tissue engineered constructs based on cells, growth and differentiation factors and scaffolds, must probably be deemed unrealistic for economic and regulation-related issues. Hence, the progress made in this respect will be mostly applicable to a fraction of post-traumatic or post-surgery situations such as big tissue defects due to tumor manifestation. Minimally invasive procedures would probably qualify for a broader application and ideally would only require off the shelf standardized products without cells. Such products should mimic the microenvironment of regenerating tissues and make use of the endogenous tissue regeneration capacities. Functionally, the chemotaxis of regenerative cells, their amplification as a transient amplifying pool and their concerted differentiation and remodeling should be addressed. This is especially important because the main target populations for such applications are the elderly and diseased. The quality of regenerative cells is impaired in such organisms and high levels of inhibitors also interfere with regeneration and healing. In metabolic bone diseases like osteoporosis, it is already known that antagonists for inhibitors such as activin and sclerostin enhance bone formation. Implementing such strategies into applications for in situ guided tissue regeneration should greatly enhance the efficacy of tailored procedures in the future

Microautophagy of the Nucleus Coincides with a Vacuolar Diffusion Barrier at Nuclear–Vacuolar Junctions

Nuclear-vacuolar (NV) junctions are organelle contact sites in yeast. They exclude nuclear pores from the organelle interface. On the vacuolar side, a lipid-dependent process excludes specific membrane proteins, such as V-ATPase, from the contact site. This suggests that NV junctions establish selective diffusion barriers

TRY plant trait database - enhanced coverage and open access

This article has 730 authors, of which I have only listed the lead author and myself as a representative of University of HelsinkiPlant 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.Peer reviewe