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.

Specific root length (SRL, m g⁻¹) is probably the most frequently measured morphological parameter of fine roots. It is believed to characterize economic aspects of the root system and to be indicative of environmental changes. The main objectives of this paper were to review and summarize the published SRL data for different tree species throughout Europe and to assess SRL under varying environmental conditions. Meta-analysis was used to summarize the response of SRL to the following manipulated environmental conditions: fertilization, irrigation, elevated temperature, elevated CO₂, Al-stress, reduced light, heavy metal stress and physical disturbance of soil. SRL was found to be strongly dependent on the fine root classes, i.e. on the ectomycorrhizal short roots (ECM), and on the roots <0.5 mm, <1 mm, <2 mm and 1 – 2 mm in diameter SRL was largest for ECM and decreased with increasing diameter. Changes in soil factors influenced most strongly the SRL of ECM and roots <0.5 mm. The variation in the SRL components, root diameter and root tissue density, and their impact on the SRL value were computed. Meta-analyses showed that SRL decreased significantly under fertilization and Al-stress; it responded negatively to reduced light, elevated temperature and CO_2. We suggest that SRL can be used successfully as an indicator of nutrient availability to trees in experimental conditions.

DNA sequences accumulating in the International Nucleotide Sequence Databases (INSD) form a rich source of information for taxonomic and ecological meta-analyses. However, these databases include many erroneous entries, and the data itself is poorly annotated with metadata, making it difficult to target and extract entries of interest with any degree of precision. Here we describe the web-based workbench PlutoF, which is designed to bridge the gap between the needs of contemporary research in biology and the existing software resources and databases. Built on a relational database, PlutoF allows remote-access rapid submission, retrieval, and analysis of study, specimen, and sequence data in INSD as well as for private datasets though web-based thin clients. In contrast to INSD, PlutoF supports internationally standardized terminology to allow very specific annotation and linking of interacting specimens and species. The sequence analysis module is optimized for identification and analysis of environmental ITS sequences of fungi, but it can be modified to operate on any genetic marker and group of organisms. The workbench is available at http://plutof.ut.ee .

Fine roots (<2 mm) are very dynamic and play a key role in forest ecosystem carbon and nutrient cycling and accumulation. We reviewed root biomass data of three main European tree species European beech, (Fagus sylvatica L.), Norway spruce (Picea abies L. Karst.) and Scots pine (Pinus sylvestris L.), in order to identify the differences between species, and within and between vegetation zones, and to show the relationships between root biomass and the climatic, site and stand factors. The collected literature consisted of data from 36 beech, 71 spruce and 43 pine stands. The mean fine root biomass of beech was 389 g m⁻², and that of spruce and pine 297 g m⁻² and 277 g m⁻², respectively. Data from pine stands supported the hypothesis that root biomass is higher in the temperate than in the boreal zone. The results indicated that the root biomass of deciduous trees is higher than that of conifers. The correlations between root biomass and site fertility characteristics seemed to be species specific. There was no correlation between soil acidity and root biomass. Beech fine root biomass decreased with stand age whereas pine root biomass increased with stand age. Fine root biomass at tree level correlated better than stand level root biomass with stand characteristics. The results showed that there exists a strong relationship between the fine root biomass and the above-ground biomass.

Forest trees directly contribute to carbon cycling in forest soils through the turnover of their fine roots. In this study we aimed to calculate root turnover rates of common European forest tree species and to compare them with most frequently published values.