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.

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Sediment transport during flood events often reveals hysteretic patterns because flow discharge can peak before (counterclockwise hysteresis) or after (clockwise hysteresis) the peak of bedload. Hysteresis in sediment transport has been used in the literature to infer the degree of sediment availability. Counterclockwise and clockwise hysteresis have been in fact interpreted as limited and unlimited sediment supply conditions, respectively. Hysteresis has been mainly explored for the case of suspended sediment transport, but it was rarely reported for bedload transport in mountain streams. This work focuses on the temporal variability of bedload transport in an alpine catchment (Saldur basin, 18.6 km2, Italian Alps) where bedload transport was monitored by means of an acoustic pipe sensor which detects the acoustic vibrations induced by particles hitting a 0.5m‐long steel pipe. Runoff dynamics are dominated by snowmelt in late spring/early summer, mostly by glacier melt in late summer/early autumn, and by a combination of the snow and glacier melt in mid‐summer. The results indicate that hysteretic patterns during daily discharge fluctuations are predominantly clockwise during the snowmelt period, likely due to the ready availability of unpacked sediments within the channel or through bank erosion in the lower part of the basin. On the contrary, counterclockwise hysteresis tend to be more frequent during late glacier melting period, possibly due to the time lag needed for sediment provided by the glacial and peri‐glacial area to be transported to the monitoring section. However, intense rainfall events occurring during the glacier melt period generated predominantly clockwise hysteresis, thus indicating the activation of different sediment sources. These results indicate that runoff generation processes play a crucial role on sediment supply and temporal availability in mountain streams. Copyright © 2014 John Wiley & Sons, Ltd.

Against a background of increasing land use intensification on favorable agricultural areas and land abandonment on less arable areas in the Alps, the aim of this investigation was to detect whether and how 10 differently used types of grassland can be distinguished by site factors, plant species composition, and biodiversity. By using a very large number of vegetation surveys (936) that were widely distributed in the Central Alps, site parameters and species composition of the different land use types were compared by discriminant analyses and various biodiversity indices. Results showed that land use is a significant factor affecting the development of different grassland communities with site factors playing a subordinate, yet important role. The 10 land use types studied can be clearly differentiated from one another by single species as well as by species composition. Our study found that the number of plant communities along with the number of species decreases constantly and significantly with increasing land use intensity and on abandoned land. For example, on average, extensively used meadows have more than three times as many species as intensively used meadows. Further, the most even distribution of species (Evenness index) is reached in intensively used meadows, whereas on pastures and abandoned land, some species become dominant forcing other species to recede. The results confirm that due to current trends in agriculture, such as land abandonment and land use intensification, plant diversity in the Alps is decreasing considerably.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids thus fail to reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions are controlled and most terrestrial species reside. Here we provide global maps of soil temperature and bioclimatic variables at a 1-km² resolution for 0-5 and 5-15 cm depth. These maps were created by calculating the difference (i.e., offset) between in-situ soil temperature measurements, based on time series from over 1200 1-km² pixels (summarized from 8500 unique temperature sensors) across all of the world's major terrestrial biomes, and coarse-grained air temperature estimates from ERA5-Land (an atmospheric reanalysis by the European Centre for Medium-Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding 2 m gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (3.6 ± 2.3°C warmer than gridded air temperature), whereas soils in warm and humid environments are on average slightly cooler (0.7 ± 2.3°C cooler). The observed substantial and biome-specific offsets underpin that the projected impacts of climate and climate change on biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil-related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining global gaps by collecting more in-situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

Soils are vital for supporting food security and other ecosystem services. Climate change can affect soil functions both directly and indirectly. Direct effects include temperature, precipitation, and moisture regime changes. Indirect effects include those that are induced by adaptations such as irrigation, crop rotation changes, and tillage practices. Although extensive knowledge is available on the direct effects, an understanding of the indirect effects of agricultural adaptation options is less complete. A review of 20 agricultural adaptation case‐studies across Europe was conducted to assess implications to soil threats and soil functions and the link to the Sustainable Development Goals (SDGs). The major findings are as follows: (a) adaptation options reflect local conditions; (b) reduced soil erosion threats and increased soil organic carbon are expected, although compaction may increase in some areas; (c) most adaptation options are anticipated to improve the soil functions of food and biomass production, soil organic carbon storage, and storing, filtering, transforming, and recycling capacities, whereas possible implications for soil biodiversity are largely unknown; and (d) the linkage between soil functions and the SDGs implies improvements to SDG 2 (achieving food security and promoting sustainable agriculture) and SDG 13 (taking action on climate change), whereas the relationship to SDG 15 (using terrestrial ecosystems sustainably) is largely unknown. The conclusion is drawn that agricultural adaptation options, even when focused on increasing yields, have the potential to outweigh the negative direct effects of climate change on soil degradation in many European regions.

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Soil moisture retrieval is one of the most challenging problems in the context of biophysical parameter estimation from remotely sensed data. Typically, microwave signals are used thanks to their sensitivity to variations in the water content of soil. However, especially in the Alps, the presence of vegetation and the heterogeneity of topography may significantly affect the microwave signal, thus increasing the complexity of the retrieval. In this paper, the effectiveness of RADARSAT2 SAR images for the estimation of soil moisture in an alpine catchment is investigated. We first carry out a sensitivity analysis of the SAR signal to the moisture content of soil and other target properties (e.g., topography and vegetation). Then we propose a technique for estimating soil moisture based on the Support Vector Regression algorithm and the integration of ancillary data. Preliminary results are discussed both in terms of accuracy over point measurements and effectiveness in handling spatially distributed data.