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. Geosphere-Biosphere Program (IGBP) and DIVERSITAS, the TRY database (TRY-not an acronym, rather a statement of sentiment; https ://www.try-db.org; Kattge et al., 2011) was proposed with the explicit assignment to improve the availability and accessibility of plant trait data for ecology and earth system sciences. The Max Planck Institute for Biogeochemistry (MPI-BGC) offered to host the database and the different groups joined forces for this community-driven program. Two factors were key to the success of TRY: the support and trust of leaders in the field of functional plant ecology submitting large databases and the long-term funding by the Max Planck Society, the MPI-BGC and the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, which has enabled the continuous development of the TRY database.

Lysenko 91,92 | Armin Macanović 93 | Parastoo Mahdavi 94 | Peter Manning 35 | Corrado Marcenò 13 | Vassiliy Martynenko 95 | Maurizio Mencuccini 96 | Vanessa Minden 97 | Jesper Erenskjold Moeslund 54 | Marco Moretti 98 | Jonas V. Müller 99 | Abstract Aims: Vegetation-plot records provide information on the presence and cover or abundance of plants co-occurring in the same community. Vegetation-plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level.Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community-weighted means and variances of traits using gap-filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community-weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale. K E Y W O R D S biodiversity, community ecology, ecoinformatics, functional diversity, global scale, macroecology, phylogenetic diversity, plot database, sPlot, taxonomic diversity, vascular plant, vegetation relevé 166 |

Summary1. Macroecology has prospered in recent years due in part to the wide array of climatic data, such as those provided by the WorldClim and CliMond data sets, which has become available for research. However, important environmental variables have still been missing, including spatial data sets on UV-B radiation, an increasingly recognized driver of ecological processes. 2. We developed a set of global UV-B surfaces (glUV) suitable to match common spatial scales in macroecology. Our data set is based on remotely sensed records from NASA's Ozone Monitoring Instrument (Aura-OMI). Following a similar approach as for the WorldClim and CliMond data sets, we processed daily UV-B measurements acquired over a period of eight years into monthly mean UV-B data and six ecologically meaningful UV-B variables with a 15-arc minute resolution. These bioclimatic variables represent Annual Mean UV-B, UV-B Seasonality, Mean UV-B of Highest Month, Mean UV-B of Lowest Month, Sum of Monthly Mean UV-B during Highest Quarter and Sum of Monthly Mean UV-B during Lowest Quarter. We correlated our data sets with selected variables of existing bioclimatic surfaces for land and with Terra-MODIS Sea Surface Temperature for ocean regions to test for relations to known gradients and patterns. 3. UV-B surfaces showed a distinct seasonal variance at a global scale, while the intensity of UV-B radiation decreased towards higher latitudes and was modified by topographic and climatic heterogeneity. UV-B surfaces were correlated with global mean temperature and annual mean radiation data, but exhibited variable spatial associations across the globe. UV-B surfaces were otherwise widely independent of existing bioclimatic surfaces. 4. Our data set provides new climatological information relevant for macroecological analyses. As UV-B is a known driver of numerous biological patterns and processes, our data set offers the potential to generate a better understanding of these dynamics in macroecology, biogeography, global change research and beyond. The glUV data set containing monthly mean UV-B data and six derived UV-B surfaces is freely available for download at: http://www.ufz.de/gluv.

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Encounters of regenerating goldfish retinal axons with oligodendrocytes and CNS myelin of mammals and fish were monitored in in vitro assays. Upon contact with highly branched rat oligodendrocytes, goldfish axons collapsed or grew around but never crossed these cells. However, in the presence of the antibody IN-1 against the oligodendrocyte-associated growth-inhibitory proteins, axons did grow over highly branched oligodencrocytes. In contrast to the mammalian oligodendrocytes, goldfish optic nerve/tract-derived oligodendrocytelike cells allowed the growth of axons across their surface and even along their processes. The fish growth cones avoided entering the region of rat CNS myelin applied to polylysine/laminin-coated coverslips or failed to elongate on this substrate. They were, however, able to pass over CNS myelin of fish. When exposed to rat CNS myelin as the sole substrate, axonal outgrowth from fish retinal explants was inhibited almost entirely. However, outgrowth on fish CNS myelin was substantial, but many more axons extended on fish or rat brain membranes that were depleted of myelin. Thus, goldfish retinal axons are sensitive to the axon-growth-inhibiting cell-surface molecules of mammalian oligodendrocytes as well as CNS myelin. Fish optic nerve oligodendrocytelike cells and fish CNS myelin lack these inhibitory properties and are growth permissive. These in vitro experiments suggest that the success of axonal regeneration in the fish optic nerve is causally related to the presence of growth-permissive properties and to the absence of growth inhibitors on fish optic nerve/tract oligodendrocytelike cells.

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Most current research on land-use intensification addresses its potential to either threaten biodiversity or to boost agricultural production. However, little is known about the simultaneous effects of intensification on biodiversity and yield. To determine the responses of species richness and yield to conventional intensification, we conducted a global meta-analysis synthesizing 115 studies which collected data for both variables at the same locations. We extracted 449 cases that cover a variety of areas used for agricultural (crops, fodder) and silvicultural (wood) production. We found that, across all production systems and species groups, conventional intensification is successful in increasing yield (grand mean + 20.3%), but it also results in a loss of species richness (−8.9%). However, analysis of sub-groups revealed inconsistent results. For example, small intensification steps within low intensity systems did not affect yield or species richness. Within high-intensity systems species losses were non-significant but yield gains were substantial (+15.2%). Conventional intensification within medium intensity systems revealed the highest yield increase (+84.9%) and showed the largest loss in species richness (−22.9%). Production systems differed

Summary1. Ecological and evolutionary research increasingly uses quantitative synthesis of primary research studies (meta-analysis) for answering fundamental questions, informing environmental policy and summarizing results for decision makers. 2. Knowing how meta-analysis works is important for researchers so that their research can have broader impact. Meta-analytic thinking encourages scientists to see single primary research studies as substantial contributions to a larger picture. 3. To facilitate inclusion in a meta-analysis, relevant primary research studies must be found and basic information about the methods and results must be thoroughly, clearly and transparently reported. While many published papers provide this information, it is common for essential data to be omitted, leading to study exclusion from meta-analyses. 4. We provide guidelines for correctly reporting basic data needed from primary studies in ecology and evolutionary biology so that they can be included in meta-analyses, together with examples that show how data should be reported to enable calculation and analysis of effect sizes, and how data should be made accessible. 5. These guidelines are important for reporting research results in general, whether or not results are included in subsequent meta-analyses, because they are necessary for the interpretation and assessment of study outcomes. Increased implementation of these guidelines by authors, editors and publishers, and reinforcement by funders, will foster higher quality and more inclusive syntheses, further the goals of transparency and reproducibility in science, and improve the quality and value of primary research studies.