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Abstract Grassland and other herbaceous communities cover significant portions of Earth's terrestrial surface and provide many critical services, such as carbon sequestration, wildlife habitat, and food production. Forecasts of global change impacts on these services will require predictive tools, such as process‐based dynamic vegetation models. Yet, model representation of herbaceous communities and ecosystems lags substantially behind that of tree communities and forests. The limited representation of herbaceous communities within models arises from two important knowledge gaps: first, our empirical understanding of the principles governing herbaceous vegetation dynamics is either incomplete or does not provide mechanistic information necessary to drive herbaceous community processes with models; second, current model structure and parameterization of grass and other herbaceous plant functional types limits the ability of models to predict outcomes of competition and growth for herbaceous vegetation. In this review, we provide direction for addressing these gaps by: (1) presenting a brief history of how vegetation dynamics have been developed and incorporated into earth system models, (2) reporting on a model simulation activity to evaluate current model capability to represent herbaceous vegetation dynamics and ecosystem function, and (3) detailing several ecological properties and phenomena that should be a focus for both empiricists and modelers to improve representation of herbaceous vegetation in models. Together, empiricists and modelers can improve representation of herbaceous ecosystem processes within models. In so doing, we will greatly enhance our ability to forecast future states of the earth system, which is of high importance given the rapid rate of environmental change on our planet. 

Abstract Scenarios that limit global warming to below 2 °C by 2100 assume significant land-use change to support large-scale carbon dioxide (CO₂) removal from the atmosphere by afforestation/reforestation, avoided deforestation, and Biomass Energy with Carbon Capture and Storage (BECCS). The more ambitious mitigation scenarios require even greater land area for mitigation and/or earlier adoption of CO₂removal strategies. Here we show that additional land-use change to meet a 1.5 °C climate change target could result in net losses of carbon from the land. The effectiveness of BECCS strongly depends on several assumptions related to the choice of biomass, the fate of initial above ground biomass, and the fossil-fuel emissions offset in the energy system. Depending on these factors, carbon removed from the atmosphere through BECCS could easily be offset by losses due to land-use change. If BECCS involves replacing high-carbon content ecosystems with crops, then forest-based mitigation could be more efficient for atmospheric CO₂removal than BECCS. 

Abstract Arctic‐boreal landscapes are experiencing profound warming, along with changes in ecosystem moisture status and disturbance from fire. This region is of global importance in terms of carbon feedbacks to climate, yet the sign (sink or source) and magnitude of the Arctic‐boreal carbon budget within recent years remains highly uncertain. Here, we provide new estimates of recent (2003–2015) vegetation gross primary productivity (GPP), ecosystem respiration (R_eco), net ecosystem CO₂exchange (NEE;R_eco − GPP), and terrestrial methane (CH₄) emissions for the Arctic‐boreal zone using a satellite data‐driven process‐model for northern ecosystems (TCFM‐Arctic), calibrated and evaluated using measurements from >60 tower eddy covariance (EC) sites. We used TCFM‐Arctic to obtain daily 1‐km²flux estimates and annual carbon budgets for the pan‐Arctic‐boreal region. Across the domain, the model indicated an overall average NEE sink of −850 Tg CO₂‐C year⁻¹. Eurasian boreal zones, especially those in Siberia, contributed to a majority of the net sink. In contrast, the tundra biome was relatively carbon neutral (ranging from small sink to source). Regional CH₄emissions from tundra and boreal wetlands (not accounting for aquatic CH₄) were estimated at 35 Tg CH₄‐C year⁻¹. Accounting for additional emissions from open water aquatic bodies and from fire, using available estimates from the literature, reduced the total regional NEE sink by 21% and shifted many far northern tundra landscapes, and some boreal forests, to a net carbon source. This assessment, based on in situ observations and models, improves our understanding of the high‐latitude carbon status and also indicates a continued need for integrated site‐to‐regional assessments to monitor the vulnerability of these ecosystems to climate change. 

Abstract. Understanding and quantifying the global methane (CH4) budgetis important for assessing realistic pathways to mitigate climate change.Atmospheric emissions and concentrations of CH4 continue to increase,making CH4 the second most important human-influenced greenhouse gas interms of climate forcing, after carbon dioxide (CO2). The relativeimportance of CH4 compared to CO2 depends on its shorteratmospheric lifetime, stronger warming potential, and variations inatmospheric growth rate over the past decade, the causes of which are stilldebated. Two major challenges in reducing uncertainties in the atmosphericgrowth rate arise from the variety of geographically overlapping CH4sources and from the destruction of CH4 by short-lived hydroxylradicals (OH). To address these challenges, we have established aconsortium of multidisciplinary scientists under the umbrella of the GlobalCarbon Project to synthesize and stimulate new research aimed at improvingand regularly updating the global methane budget. Following Saunois et al. (2016), we present here the second version of the living review paperdedicated to the decadal methane budget, integrating results of top-downstudies (atmospheric observations within an atmospheric inverse-modellingframework) and bottom-up estimates (including process-based models forestimating land surface emissions and atmospheric chemistry, inventories ofanthropogenic emissions, and data-driven extrapolations). For the 2008–2017 decade, global methane emissions are estimated byatmospheric inversions (a top-down approach) to be 576 Tg CH4 yr−1 (range 550–594, corresponding to the minimum and maximumestimates of the model ensemble). Of this total, 359 Tg CH4 yr−1 or∼ 60 % is attributed to anthropogenic sources, that isemissions caused by direct human activity (i.e. anthropogenic emissions; range 336–376 Tg CH4 yr−1 or 50 %–65 %). The mean annual total emission for the new decade (2008–2017) is29 Tg CH4 yr−1 larger than our estimate for the previous decade (2000–2009),and 24 Tg CH4 yr−1 larger than the one reported in the previousbudget for 2003–2012 (Saunois et al., 2016). Since 2012, global CH4emissions have been tracking the warmest scenarios assessed by theIntergovernmental Panel on Climate Change. Bottom-up methods suggest almost30 % larger global emissions (737 Tg CH4 yr−1, range 594–881)than top-down inversion methods. Indeed, bottom-up estimates for naturalsources such as natural wetlands, other inland water systems, and geologicalsources are higher than top-down estimates. The atmospheric constraints onthe top-down budget suggest that at least some of these bottom-up emissionsare overestimated. The latitudinal distribution of atmosphericobservation-based emissions indicates a predominance of tropical emissions(∼ 65 % of the global budget, < 30∘ N)compared to mid-latitudes (∼ 30 %, 30–60∘ N)and high northern latitudes (∼ 4 %, 60–90∘ N). The most important source of uncertainty in the methanebudget is attributable to natural emissions, especially those from wetlandsand other inland waters. Some of our global source estimates are smaller than those in previouslypublished budgets (Saunois et al., 2016; Kirschke et al., 2013). In particular wetland emissions are about 35 Tg CH4 yr−1 lower due toimproved partition wetlands and other inland waters. Emissions fromgeological sources and wild animals are also found to be smaller by 7 Tg CH4 yr−1 by 8 Tg CH4 yr−1, respectively. However, the overalldiscrepancy between bottom-up and top-down estimates has been reduced byonly 5 % compared to Saunois et al. (2016), due to a higher estimate of emissions from inland waters, highlighting the need for more detailed research on emissions factors. Priorities for improving the methanebudget include (i) a global, high-resolution map of water-saturated soilsand inundated areas emitting methane based on a robust classification ofdifferent types of emitting habitats; (ii) further development ofprocess-based models for inland-water emissions; (iii) intensification ofmethane observations at local scales (e.g., FLUXNET-CH4 measurements)and urban-scale monitoring to constrain bottom-up land surface models, andat regional scales (surface networks and satellites) to constrainatmospheric inversions; (iv) improvements of transport models and therepresentation of photochemical sinks in top-down inversions; and (v) development of a 3D variational inversion system using isotopic and/orco-emitted species such as ethane to improve source partitioning. The data presented here can be downloaded fromhttps://doi.org/10.18160/GCP-CH4-2019 (Saunois et al., 2020) and from theGlobal Carbon Project.