The synergetic effects of recent rising atmospheric CO₂ and temperature are expected to favor tree growth in boreal and temperate forests. However, recent dendrochronological studies have shown site-specific unprecedented growth enhancements or declines. The question of whether either of these trends is caused by changes in the atmosphere remains unanswered because dendrochronology alone has not been able to clarify the physiological basis of such trends. Here we combined standard dendrochronological methods with carbon isotopic analysis to investigate whether atmospheric changes enhanced water use efficiency (WUE) and growth of two deciduous and two coniferous tree species along a 9° latitudinal gradient across temperate and boreal forests in Ontario, Canada. Our results show that although trees have had around 53% increases in WUE over the past century, growth decline (measured as a decrease in basal area increment – BAI) has been the prevalent response in recent decades irrespective of species identity and latitude. Since the 1950s, tree BAI was predominantly negatively correlated with warmer climates and/or positively correlated with precipitation, suggesting warming induced water stress. However, where growth declines were not explained by climate, WUE and BAI were linearly and positively correlated, showing that declines are not always attributable to warming induced stress and additional stressors may exist. Our results show an unexpected widespread tree growth decline in temperate and boreal forests due to warming induced stress but are also suggestive of additional stressors. Rising atmospheric CO₂ levels during the past century resulted in consistent increases in water use efficiency, but this did not prevent growth decline. These findings challenge current predictions of increasing terrestrial carbon stocks under climate change scenarios.

Complex systems science has contributed to our understanding of ecology in important areas such as food webs, patch dynamics and population fluctuations. This has been achieved through the use of simple measures that can capture the difference between order and disorder and simple models with local interactions that can generate surprising behaviour at larger scales. However, close examination reveals that commonly applied definitions of complexity fail to accommodate some key features of ecological systems, a fact that will limit the contribution of complex systems science to ecology. We highlight these features of ecological complexity—such as diversity, cross-scale interactions, memory and environmental variability—that continue to challenge classical complex systems science. Further advances in these areas will be necessary before complex systems science can be widely applied to understand the dynamics of ecological systems.

Aim: Predictions of plant traits over space and time are increasingly used to improve our understanding of plant community responses to global environmental change. A necessary step forward is to assess the reliability of global trait predictions. In this study, we predict community mean plant traits at the global scale and present a systematic evaluation of their reliability in terms of the accuracy of the models, ecological realism and various sources of uncertainty.Location: Global.Time period: Present.Major taxa studied: Vascular plants.Methods: We predicted global distributions of community mean specific leaf area, leaf nitrogen concentration, plant height and wood density with an ensemble modelling approach based on georeferenced, locally measured trait data representative of the plant community. We assessed the predictive performance of the models, the plausibility of predicted trait combinations, the influence of data quality, and the uncertainty across geographical space attributed to spatial extrapolation and diverging model predictions.Results: Ensemble predictions of community mean plant height, specific leaf area and wood density resulted in ecologically plausible trait–environment relationships and trait–trait combinations. Leaf nitrogen concentration, however, could not be predicted reliably. The ensemble approach was better at predicting community trait means than any of the individual modelling techniques, which varied greatly in predictive performance and led to divergent predictions, mostly in African deserts and the Arctic, where predictions were also extrapolated. High data quality (i.e., including intraspecific variability and a representative species sample) increased model performance by 28%.Main conclusions: Plant community traits can be predicted reliably at the global scale when using an ensemble approach and high‐quality data for traits that mostly respond to large‐scale environmental factors. We recommend applying ensemble forecasting to account for model uncertainty, using representative trait data, and more routinely assessing the reliability of trait predictions.

Despite the relevance of ecosystem services (ES) to society and modern ecological research, current methods of measurement and mapping remain inconsistent and often lack primary data in estimating and modeling ES. A key player in our understanding of ES and their measurements are plant functional traits—chemical and physical aspects of plants—which are often cited as one of the drivers of ecosystem processes and functions. In order to better quantify the ES–plant functional trait indicators, we outline existing evidence of this relationship and identify gaps between the best predicted ES and the most valued ES. This study offers an up‐to‐date review of plant functional traits' direct or indirect relationships with ecosystem service provision and discusses the quantitative evidence these traits might hold as indicators. With this review, we seek to (1) offer a current summary of the quantitative evidence on ecosystem service–plant functional trait relationships, (2) identify which traits have been used to successfully indicate ecosystem services, and (3) identify research gaps, and ecosystem services or traits that receive little attention or have weak criteria as indicators. In a comprehensive literature review of the 19 services that were searched for, genetic materials, medicine, and cultural services had no relevant plant functional trait indicators, while the remaining 16 services had a range of traits associated with them. We found that functional traits showed varying relationships to ES, with some depending on the ecosystem type they were found in, while others appeared to remain consistent across ecosystems and conditions. This indicates that there could exist a subset of traits that are “universal” indicators across all ecosystem types, while others are ecosystem dependent. Our review suggests the need for more research on less clearly defined ES (such as cultural, educational, and refugium services) both by more careful definitions to make quantitative measures more applicable, and through increased quantitative and qualitative studies to better understand the nature of ES indicators for these services. This summary shows how plant functional traits can quantitatively and reliably predict and provide details on a subset of ES.

Endangered forest–grassland mosaics interspersed with expanding agriculture and silviculture occur across many parts of the world, including the southern Brazilian highlands. This natural mosaic ecosystem is thought to reflect alternative stable states driven by threshold responses of recruitment to fire and moisture regimes. The role of adaptive human behavior in such systems remains understudied, despite its pervasiveness and the fact that such ecosystems can exhibit complex dynamics. We develop a nonlinear mathematical model of coupled human–environment dynamics in mosaic systems and social processes regarding conservation and economic land valuation. Our objective is to better understand how the coupled dynamics respond to changes in ecological and social conditions. The model is parameterized with southern Brazilian data on mosaic ecology, land-use profits, and questionnaire results concerning landowner preferences and conservation values. We find that the mosaic presently resides at a crucial juncture where relatively small changes in social conditions can generate a wide variety of possible outcomes, including complete loss of mosaics; large-amplitude, long-term oscillations between land states that preclude ecosystem stability; and conservation of the mosaic even to the exclusion of agriculture/silviculture. In general, increasing the time horizon used for conservation decision making is more likely to maintain mosaic stability. In contrast, increasing the inherent conservation value of either forests or grasslands is more likely to induce large oscillations—especially for forests—due to feedback from rarity-based conservation decisions. Given the potential for complex dynamics, empirically grounded nonlinear dynamical models should play a larger role in policy formulation for human–environment mosaic ecosystems.