Strangeness nuclear physics: a critical review on selected topics

Selected topics in strangeness nuclear physics are critically reviewed. This includes production, structure and weak decay of $\Lambda$--Hypernuclei, the $\bar K$ nuclear interaction and the possible existence of $\bar K$ bound states in nuclei. Perspectives for future studies on these issues are also outlined.Comment: 63 pages, 51 figures, accepted for publication on European Physical Journal

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

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

Broad anatomical variation within a narrow wood density range : a study of twig wood across 69 Australian angiosperms

Objectives: Just as people with the same weight can have different body builds, woods with the same wood density can have different anatomies. Here, our aim was to assess the magnitude of anatomical variation within a restricted range of wood density and explore its potential ecological implications. Methods: Twig wood of 69 angiosperm tree and shrub species was analyzed. Species were selected so that wood density varied within a relatively narrow range (0.38–0.62 g cm-3). Anatomical traits quantified included wood tissue fractions (fibres, axial parenchyma, ray parenchyma, vessels, and conduits with maximum lumen diameter below 15 μm), vessel properties, and pith area. To search for potential ecological correlates of anatomical variation the species were sampled across rainfall and temperature contrasts, and several other ecologically-relevant traits were measured (plant height, leaf area to sapwood area ratio, and modulus of elasticity). Results: Despite the limited range in wood density, substantial anatomical variation was observed. Total parenchyma fraction varied from 0.12 to 0.66 and fibre fraction from 0.20 to 0.74, and these two traits were strongly inversely correlated (r = -0.86, P < 0.001). Parenchyma was weakly (0.24 ≤|r|≤ 0.35, P < 0.05) or not associated with vessel properties nor with height, leaf area to sapwood area ratio, and modulus of elasticity (0.24 ≤|r|≤ 0.41, P < 0.05). However, vessel traits were fairly well correlated with height and leaf area to sapwood area ratio (0.47 ≤|r|≤ 0.65, all P < 0.001). Modulus of elasticity was mainly driven by fibre wall plus vessel wall fraction rather than by the parenchyma component. Conclusions: Overall, there seem to be at least three axes of variation in xylem, substantially independent of each other: a wood density spectrum, a fibre-parenchyma spectrum, and a vessel area spectrum. The fibre-parenchyma spectrum does not yet have any clear or convincing ecological interpretation

A response to Bittencourt et al.'s (2016) comment ‘On xylem hydraulic efficiencies, wood space-use and the safety–efficiency tradeoff’

A response to Bittencourt et al.'s (2016) comment 'On xylem hydraulic efficiencies, wood space-use and the safety-efficiency tradeoff': in this issue of New Phytologist, pp. 1152-11553 page(s

Weak tradeoff between xylem safety and xylem-specific hydraulic efficiency across the world's woody plant species

* The evolution of lignified xylem allowed for the efficient transport of water under tension, but also exposed the vascular network to the risk of gas emboli and the spread of gas between xylem conduits, thus impeding sap transport to the leaves. A well-known hypothesis proposes that the safety of xylem (its ability to resist embolism formation and spread) should trade off against xylem efficiency (its capacity to transport water). * We tested this safety–efficiency hypothesis in branch xylem across 335 angiosperm and 89 gymnosperm species. Safety was considered at three levels: the xylem water potentials where 12%, 50% and 88% of maximal conductivity are lost. * Although correlations between safety and efficiency were weak (r2 < 0.086), no species had high efficiency and high safety, supporting the idea for a safety–efficiency tradeoff. However, many species had low efficiency and low safety. Species with low efficiency and low safety were weakly associated (r2 < 0.02 in most cases) with higher wood density, lower leaf- to sapwood-area and shorter stature. * There appears to be no persuasive explanation for the considerable number of species with both low efficiency and low safety. These species represent a real challenge for understanding the evolution of xylem.Fil: Gleason, Sean M.. Macquarie University. Department of Biological Sciences ; Australia. USDA-ARS. Water Management Research; Estados UnidosFil: Westoby, Mark. Macquarie University. Department of Biological Sciences; AustraliaFil: Jansen, Steven. Ulm University. Institute of Systematic Botany and Ecology; AlemaniaFil: Choat, Brendan. Western Sydney University. Hawkesbury Institute for the Environment; AustraliaFil: Hacke, Uwe G.. University of Alberta. Department of Renewable Resources; CanadáFil: Pratt, Robert B.. California State University. Department of Biology; Estados UnidosFil: Bhaskar, Radika. Haverford College. Department of Biology; Estados UnidosFil: Brodibb, Tim J.. University of Tasmania. School of Biological Sciences; AustraliaFil: Bucci, Sandra Janet. Universidad Nacional de la Patagonia Austral. Centro de Investigaciones y Transferencia Golfo San Jorge. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro de Investigaciones y Transferencia Golfo San Jorge. Universidad Nacional de la Patagonia "san Juan Bosco". Centro de Investigaciones y Transferencia Golfo San Jorge; ArgentinaFil: Cao, Kun-Fang. Guangxi University. College of Forestry. Utilization of Subtropical Agro-Bioresources ; ChinaFil: Cochard, Hervé. Clermont Université. Université Blaise Pascal. UMR547 PIAF; Francia. Institut National de la Recherche Agronomique; FranciaFil: Delzon, Sylvain. Institut National de la Recherche Agronomique; FranciaFil: Domec, Jean-Christophe. Duke University, Durham. Nicholas School of the Environment; Estados Unidos. Institut National de la Recherche Agronomique; FranciaFil: Fan, Ze-Xin. Chinese Academy of Sciences. Xishuangbanna Tropical Botanical Garden. Key Laboratory of Tropical Forest Ecology; ChinaFil: Feild, Taylor S.. James Cook University. School of Marine and Tropical Biology; AustraliaFil: Jacobsen, Anna L.. California State University. Department of Biology; Estados UnidosFil: Johnson, Daniel M.. University of Idaho. Rangeland and Fire Sciences. Department of Forest; Estados UnidosFil: Lens, Frederic. Leiden University. Naturalis Biodiversity Center; Países BajosFil: Maherali, Hafiz. University of Guelph. Department of Integrative Biology; CanadáFil: Martínez-Viralta, Jordi. CREAF; España. Institució Catalana de Recerca i Estudis Avancats; EspañaFil: Mayr, Stefan. University of Innsbruck. Department of Botany; AustriaFil: McCulloh, Katherine A.. University of Wisconsin-Madison. Department of Botany; Estados UnidosFil: Mencuccini, Maurizio. University of Edinburgh. School of GeoSciences; Reino Unido. Institució Catalana de Recerca i Estudis Avancats; EspañaFil: Mitchell, Patrick J.. CSIRO Land and Water Flagship; AustraliaFil: Morris, Hugh. Ulm University. Institute of Systematic Botany and Ecology ; AlemaniaFil: Nardini, Andrea. Università Trieste. Dipartimento Scienze della Vita ; ItaliaFil: Pittermann, Jarmila. University of California. Department of Ecology and Evolutionary Biology; Estados UnidosFil: Plavcová, Lenka. Ulm University. Institute of Systematic Botany and Ecology; Alemania. University of Alberta. Department of Renewable Resources; CanadáFil: Schreiber, Stefan G.. University of Alberta. Department of Renewable Resources; CanadáFil: Sperry, John S.. University of Utah. Department of Biology; Estados UnidosFil: Wright, Ian J.. Macquarie University. Department of Biological Sciences; AustraliaFil: Zanne, Ami E.. George Washington University. Department of Biological Sciences; Estados Unido