Aim  Despite their importance for predicting fluxes to and from terrestrial ecosystems, dynamic global vegetation models have insufficient realism because of their use of plant functional types (PFTs) with constant attributes. Based on recent advances in community ecology, we explore the merits of a traits‐based vegetation model to deal with current shortcomings.Location  Global.Methods  A research review of current concepts and information, providing a new perspective, supported by quantitative analysis of a global traits database.Results  Continuous and process‐based trait–environment relations are central to a traits‐based approach and allow us to directly calculate fluxes based on functional characteristics. By quantifying community assembly concepts, it is possible to predict trait values from environmental drivers, although these relations are still imperfect. Through the quantification of these relations, effects of adaptation and species replacement upon environmental changes are implicitly accounted for. Such functional links also allow direct calculation of fluxes, including those related to feedbacks through the nitrogen and water cycle. Finally, a traits‐based model allows the prediction of new trait combinations and no‐analogue ecosystem functions projected to arise in the near future, which is not feasible in current vegetation models. A separate calculation of ecosystem fluxes and PFT occurrences in traits‐based models allows for flexible vegetation classifications.Main conclusions  Given the advantages described above, we argue that traits‐based modelling deserves consideration (although it will not be easy) if one is to aim for better climate projections.

In ecology, strategy schemes based on propositions about the selection of plant attributes are common, but quantification of such schemes in relation to nutrient and water supply is lacking. Through structural equation modeling, we tested whether plant strategies related to nutrient and water/oxygen supply are reflected in a coordination of traits in natural communities. Structural equation models, based on accepted ecological concepts, were tested with measured plant traits of 105 different species across 50 sites in mesic to wet plant communities in the Netherlands. For each site, nutrient and water supply were measured and modeled. Hypothesized multivariate strategy models only partly reflected current theoretical schemes. Alternative models were consistent, showing that lack of consistency of the original models was because of (i) strong correlations among traits that supposedly belong to different strategy components; (ii) poor understanding of mechanisms determining the covariation of plant maximum height, leaf size, and stem density; and (iii) lack of integrative and long-term measures of nutrient supply needed to predict coordinated plant trait responses. Our main conclusion is that a combination of trade-offs (partly) across different plant organs and diverging effects of resource supply ultimately determines the coordination of plant traits needed to "make a living."

The 2018–2019 drought in north-western and central Europe caused severe damage to a wide range of sectors. It also emphasised the fact that, even in countries with temperate climates, adaptations are needed to cope with increasing future drought frequencies. A crucial component of drought management strategies is to monitor the status of groundwater resources. However, providing up-to-date assessments of regional groundwater drought development remains challenging due to the limited availability of high-quality data. This limits many studies to small selections of groundwater monitoring sites, giving an incomplete image of drought dynamics. In this study, a time series modelling-based method for data preparation was developed and applied to map the spatio-temporal development of the 2018–2019 groundwater drought in the south-eastern Netherlands, based on a large set of monitoring data. The data preparation method was evaluated for its usefulness and reliability for data validation, simulation, and regional groundwater drought assessment. The analysis showed that the 2018–2019 meteorological drought caused extreme groundwater drought throughout the south-eastern Netherlands, breaking 30-year records almost everywhere. Drought onset and duration were strongly variable in space, and higher-elevation areas suffered from severe drought well into 2020. Groundwater drought development appeared to be governed dominantly by the spatial distribution of rainfall and the landscape type. The time series modelling-based data preparation method was found to be a useful tool to enable a spatially detailed record of regional groundwater drought development. The automated time series modelling-based data validation improved the quality and quantity of useable data, although optimal validation parameters are probably context dependent. The time series simulations were generally found to be reliable; however, the use of time series simulations rather than direct measurement series can bias drought estimations, especially at a local scale, and underestimate spatial variability. Further development of time-series-based validation and simulation methods, combined with accessible and consistent monitoring data, will be valuable to enable better groundwater drought monitoring in the future.