Accurate assessment of anthropogenic carbon dioxide (CO₂) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the global carbon budget – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO₂ emissions from fossil fuels and industry (E_FF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (E_LUC), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO₂ concentration is measured directly and its rate of growth (G_ATM) is computed from the annual changes in concentration. The ocean CO₂ sink (S_OCEAN) and terrestrial CO₂ sink (S_LAND) are estimated with global process models constrained by observations. The resulting carbon budget imbalance (B_IM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the last decade available (2007–2016), E_FF was 9.4 ± 0.5 GtC yr⁻¹, E_LUC 1.3 ± 0.7 GtC yr⁻¹, G_ATM 4.7 ± 0.1 GtC yr⁻¹, S_OCEAN 2.4 ± 0.5 GtC yr⁻¹, and S_LAND 3.0 ± 0.8 GtC yr⁻¹, with a budget imbalance B_IM of 0.6 GtC yr⁻¹ indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in E_FF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr⁻¹. Also for 2016, E_LUC was 1.3 ± 0.7 GtC yr⁻¹, G_ATM was 6.1 ± 0.2 GtC yr⁻¹, S_OCEAN was 2.6 ± 0.5 GtC yr⁻¹, and S_LAND was 2.7 ± 1.0 GtC yr⁻¹, with a small B_IM of −0.3 GtC. G_ATM continued to be higher in 2016 compared to the past decade (2007–2016), reflecting in part the high fossil emissions and the small S_LAND consistent with El Niño conditions. The global atmospheric CO₂ concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data for the first 6–9 months indicate a renewed growth in E_FF of +2.0 % (range of 0.8 to 3.0 %) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017).

A decline in the carbon fertilization effect: One source of uncertainty in climate science is how the carbon fertilization effect (CFE) will contribute to mitigation of anthropogenic climate change. Wang et al. explored the temporal dynamics of CFE on vegetation photosynthesis at the global scale. There has been a decline over recent decades in the contribution of CFE to vegetation photosynthesis, perhaps owing to the limiting effects of plant nutrients such as nitrogen and phosphorus. This declining trend has not been adequately accounted for in carbon cycle models. CFE thus has limitations for long-term mitigation of climate change, and future warming might currently be underestimated. Science , this issue p. 1295

Summary: Accumulating evidence highlights increased mortality risks for trees during severe drought, particularly under warmer temperatures and increasing vapour pressure deficit (VPD). Resulting forest die‐off events have severe consequences for ecosystem services, biophysical and biogeochemical land–atmosphere processes. Despite advances in monitoring, modelling and experimental studies of the causes and consequences of tree death from individual tree to ecosystem and global scale, a general mechanistic understanding and realistic predictions of drought mortality under future climate conditions are still lacking. We update a global tree mortality map and present a roadmap to a more holistic understanding of forest mortality across scales. We highlight priority research frontiers that promote: (1) new avenues for research on key tree ecophysiological responses to drought; (2) scaling from the tree/plot level to the ecosystem and region; (3) improvements of mortality risk predictions based on both empirical and mechanistic insights; and (4) a global monitoring network of forest mortality. In light of recent and anticipated large forest die‐off events such a research agenda is timely and needed to achieve scientific understanding for realistic predictions of drought‐induced tree mortality. The implementation of a sustainable network will require support by stakeholders and political authorities at the international level.

Summary: Drought has promoted large‐scale, insect‐induced tree mortality in recent years, with severe consequences for ecosystem function, atmospheric processes, sustainable resources and global biogeochemical cycles. However, the physiological linkages among drought, tree defences, and insect outbreaks are still uncertain, hindering our ability to accurately predict tree mortality under on‐going climate change. Here we propose an interdisciplinary research agenda for addressing these crucial knowledge gaps. Our framework includes field manipulations, laboratory experiments, and modelling of insect and vegetation dynamics, and focuses on how drought affects interactions between conifer trees and bark beetles. We build upon existing theory and examine several key assumptions: (1) there is a trade‐off in tree carbon investment between primary and secondary metabolites (e.g. growth vs defence); (2) secondary metabolites are one of the main component of tree defence against bark beetles and associated microbes; and (3) implementing conifer‐bark beetle interactions in current models improves predictions of forest disturbance in a changing climate. Our framework provides guidance for addressing a major shortcoming in current implementations of large‐scale vegetation models, the under‐representation of insect‐induced tree mortality.