Stimulation of terrestrial plant production by rising CO ₂ concentration is projected to reduce the airborne fraction of anthropogenic CO ₂ emissions. Coupled climate–carbon cycle models are sensitive to this negative feedback on atmospheric CO ₂ , but model projections are uncertain because of the expectation that feedbacks through the nitrogen (N) cycle will reduce this so-called CO ₂ fertilization effect. We assessed whether N limitation caused a reduced stimulation of net primary productivity (NPP) by elevated atmospheric CO ₂ concentration over 11 y in a free-air CO ₂ enrichment (FACE) experiment in a deciduous Liquidambar styraciflua (sweetgum) forest stand in Tennessee. During the first 6 y of the experiment, NPP was significantly enhanced in forest plots exposed to 550 ppm CO ₂ compared with NPP in plots in current ambient CO ₂ , and this was a consistent and sustained response. However, the enhancement of NPP under elevated CO ₂ declined from 24% in 2001–2003 to 9% in 2008. Global analyses that assume a sustained CO ₂ fertilization effect are no longer supported by this FACE experiment. N budget analysis supports the premise that N availability was limiting to tree growth and declining over time —an expected consequence of stand development, which was exacerbated by elevated CO ₂ . Leaf- and stand-level observations provide mechanistic evidence that declining N availability constrained the tree response to elevated CO ₂ ; these observations are consistent with stand-level model projections. This FACE experiment provides strong rationale and process understanding for incorporating N limitation and N feedback effects in ecosystem and global models used in climate change assessments.

Summary: Tree mortality rates appear to be increasing in moist tropical forests (MTFs) with significant carbon cycle consequences. Here, we review the state of knowledge regarding MTF tree mortality, create a conceptual framework with testable hypotheses regarding the drivers, mechanisms and interactions that may underlie increasing MTF mortality rates, and identify the next steps for improved understanding and reduced prediction. Increasing mortality rates are associated with rising temperature and vapor pressure deficit, liana abundance, drought, wind events, fire and, possibly, CO₂ fertilization‐induced increases in stand thinning or acceleration of trees reaching larger, more vulnerable heights. The majority of these mortality drivers may kill trees in part through carbon starvation and hydraulic failure. The relative importance of each driver is unknown. High species diversity may buffer MTFs against large‐scale mortality events, but recent and expected trends in mortality drivers give reason for concern regarding increasing mortality within MTFs. Models of tropical tree mortality are advancing the representation of hydraulics, carbon and demography, but require more empirical knowledge regarding the most common drivers and their subsequent mechanisms. We outline critical datasets and model developments required to test hypotheses regarding the underlying causes of increasing MTF mortality rates, and improve prediction of future mortality under climate change. Contents Summary 852 I. Introduction 852 II. Increasing mortality rates in the Amazon Basin 854 III. Global and regional mortality drivers and mechanisms 855 IV. On the coupling of mortality drivers and mechanisms 859 V. Mitigating factors that may promote future survival 859 VI. The state of ESM simulations of moist tropical tree mortality 859 VII. Next steps 860 VIII. Conclusions 863 Acknowledgements 863 ORCID 863 References 863

Ecosystem responses to rising CO₂ concentrations are a major source of uncertainty in climate change projections. Data from ecosystem-scale Free-Air CO₂ Enrichment (FACE) experiments provide a unique opportunity to reduce this uncertainty. The recent FACE Model–Data Synthesis project aimed to use the information gathered in two forest FACE experiments to assess and improve land ecosystem models. A new 'assumption-centred' model intercomparison approach was used, in which participating models were evaluated against experimental data based on the ways in which they represent key ecological processes. By identifying and evaluating the main assumptions causing differences among models, the assumption-centred approach produced a clear roadmap for reducing model uncertainty. Here, we explain this approach and summarize the resulting research agenda. We encourage the application of this approach in other model intercomparison projects to fundamentally improve predictive understanding of the Earth system.7 page(s