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.

There is considerable evidence that biodiversity promotes multiple ecosystem functions (multifunctionality), thus ensuring the delivery of ecosystem services important for human well-being. However, the mechanisms underlying this relationship are poorly understood, especially in natural ecosystems. We develop a novel approach to partition biodiversity effects on multifunctionality into three mechanisms and apply this to European forest data. We show that throughout Europe, tree diversity is positively related with multifunctionality when moderate levels of functioning are required, but negatively when very high function levels are desired. For two well-known mechanisms, ‘complementarity’ and ‘selection’, we detect only minor effects on multifunctionality. Instead a third, so far overlooked mechanism, the ‘jack-of-all-trades’ effect, caused by the averaging of individual species effects on function, drives observed patterns. Simulations demonstrate that jack-of-all-trades effects occur whenever species effects on different functions are not perfectly correlated, meaning they may contribute to diversity–multifunctionality relationships in many of the world’s ecosystems.

Significance: Numerous studies have demonstrated the importance of biodiversity in maintaining multiple ecosystem functions and services (multifunctionality) at local spatial scales, but it is unknown whether similar relationships are found at larger spatial scales in real-world landscapes. Here, we show, for the first time to our knowledge, that biodiversity can also be important for multifunctionality at larger spatial scales in European forest landscapes. Both high local (α-) diversity and a high turnover in species composition between locations (high β-diversity) were found to be potentially important drivers of ecosystem multifunctionality. Our study provides evidence that it is important to conserve the landscape-scale biodiversity that is being eroded by biotic homogenization if ecosystem multifunctionality is to be maintained.

Humans require multiple services from ecosystems, but it is largely unknown whether trade‐offs between ecosystem functions prevent the realisation of high ecosystem multifunctionality across spatial scales. Here, we combined a comprehensive dataset (28 ecosystem functions measured on 209 forest plots) with a forest inventory dataset (105,316 plots) to extrapolate and map relationships between various ecosystem multifunctionality measures across Europe. These multifunctionality measures reflected different management objectives, related to timber production, climate regulation and biodiversity conservation/recreation. We found that trade‐offs among them were rare across Europe, at both local and continental scales. This suggests a high potential for ‘win‐win’ forest management strategies, where overall multifunctionality is maximised. However, across sites, multifunctionality was on average 45.8‐49.8% below maximum levels and not necessarily highest in protected areas. Therefore, using one of the most comprehensive assessments so far, our study suggests a high but largely unrealised potential for management to promote multifunctional forests.