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Global net land carbon uptake or net biome production (NBP) has increased during recent decades 1 . Whether its temporal variability and autocorrelation have changed during this period, however, remains elusive, even though an increase in both could indicate an increased potential for a destabilized carbon sink 2,3 . Here, we investigate the trends and controls of net terrestrial carbon uptake and its temporal variability and autocorrelation from 1981 to 2018 using two atmospheric-inversion models, the amplitude of the seasonal cycle of atmospheric CO 2 concentration derived from nine monitoring stations distributed across the Pacific Ocean and dynamic global vegetation models. We find that annual NBP and its interdecadal variability increased globally whereas temporal autocorrelation decreased. We observe a separation of regions characterized by increasingly variable NBP, associated with warm regions and increasingly variable temperatures, lower and weaker positive trends in NBP and regions where NBP became stronger and less variable. Plant species richness presented a concave-down parabolic spatial relationship with NBP and its variability at the global scale whereas nitrogen deposition generally increased NBP. Increasing temperature and its increasing variability appear as the most important drivers of declining and increasingly variable NBP. Our results show increasing variability of NBP regionally that can be mostly attributed to climate change and that may point to destabilization of the coupled carbon-climate system., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)

Tropical secondary forests sequester carbon up to 20 times faster than old-growth forests. This rate does not capture spatial regrowth patterns due to environmental and disturbance drivers. Here we quantify the influence of such drivers on the rate and spatial patterns of regrowth in the Brazilian Amazon using satellite data. Carbon sequestration rates of young secondary forests (<20 years) in the west are ~60% higher (3.0 ± 1.0 Mg C ha -1  yr -1 ) compared to those in the east (1.3 ± 0.3 Mg C ha -1  yr -1 ). Disturbances reduce regrowth rates by 8-55%. The 2017 secondary forest carbon stock, of 294 Tg C, could be 8% higher by avoiding fires and repeated deforestation. Maintaining the 2017 secondary forest area has the potential to accumulate ~19.0 Tg C yr -1 until 2030, contributing ~5.5% to Brazil's 2030 net emissions reduction target. Implementing legal mechanisms to protect and expand secondary forests whilst supporting old-growth conservation is, therefore, key to realising their potential as a nature-based climate solution.

In Europe, three widespread extreme summer drought and heat (DH) events have occurred in 2003, 2010 and 2018. These events were comparable in magnitude but varied in their geographical distribution and biomes affected. In this study, we perform a comparative analysis of the impact of the DH events on ecosystem CO 2 fluxes over Europe based on an ensemble of 11 dynamic global vegetation models (DGVMs), and the observation-based FLUXCOM product. We find that all DH events were associated with decreases in net ecosystem productivity (NEP), but the gross summer flux anomalies differ between DGVMs and FLUXCOM. At the annual scale, FLUXCOM and DGVMs indicate close to neutral or above-average land CO 2 uptake in DH2003 and DH2018, due to increased productivity in spring and reduced respiration in autumn and winter compensating for less photosynthetic uptake in summer. Most DGVMs estimate lower gross primary production (GPP) sensitivity to soil moisture during extreme summers than FLUXCOM. Finally, we show that the different impacts of the DH events at continental-scale GPP are in part related to differences in vegetation composition of the regions affected and to regional compensating or offsetting effects from climate anomalies beyond the DH centres. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

Climate change significantly modifies terrestrial ecosystems and vegetation activity, yet little is known about how climate change and ozone pollution interact to affect forest health. Here we compared the trends of two metrics widely used to protect forests against negative impacts of ozone pollution, the AOT40 (Accumulated Ozone over Threshold of 40 ppb) which only depends on surface air ozone concentrations, and the POD (Phytotoxic Ozone Dose) which relies on the amount of ozone uptaken by plants through stomata. Using a chemistry transport model, driven by anthropogenic emission inventories, we found that European-averaged ground-level ozone concentrations significantly declined (-1.6%) over the time period 2000-2014, following successful control strategies to reduce the ozone precursors emission; as a consequence, the AOT40 metric declined (-22%). In contrast, climate change increased both growing season length (~7 days/decade) and stomatal conductance and thus enhanced the stomatal ozone uptake by forests (5.9%), leading to an overall increase of potential ozone damage on plants, despite the reduction in ozone concentrations. Our results suggest that stomatal-flux based strategies of forest protection against ozone in a changing climate require a proper consideration of the duration of the growing season with a better estimation of start and end of the growing season., (Copyright © 2019. Published by Elsevier B.V.)

Most climate mitigation scenarios involve negative emissions, especially those that aim to limit global temperature increase to 2°C or less. However, the carbon uptake potential in land-based climate change mitigation efforts is highly uncertain. Here, we address this uncertainty by using two land-based mitigation scenarios from two land-use models (IMAGE and MAgPIE) as input to four dynamic global vegetation models (DGVMs; LPJ-GUESS, ORCHIDEE, JULES, LPJmL). Each of the four combinations of land-use models and mitigation scenarios aimed for a cumulative carbon uptake of ~130 GtC by the end of the century, achieved either via the cultivation of bioenergy crops combined with carbon capture and storage (BECCS) or avoided deforestation and afforestation (ADAFF). Results suggest large uncertainty in simulated future land demand and carbon uptake rates, depending on the assumptions related to land use and land management in the models. Total cumulative carbon uptake in the DGVMs is highly variable across mitigation scenarios, ranging between 19 and 130 GtC by year 2099. Only one out of the 16 combinations of mitigation scenarios and DGVMs achieves an equivalent or higher carbon uptake than achieved in the land-use models. The large differences in carbon uptake between the DGVMs and their discrepancy against the carbon uptake in IMAGE and MAgPIE are mainly due to different model assumptions regarding bioenergy crop yields and due to the simulation of soil carbon response to land-use change. Differences between land-use models and DGVMs regarding forest biomass and the rate of forest regrowth also have an impact, albeit smaller, on the results. Given the low confidence in simulated carbon uptake for a given land-based mitigation scenario, and that negative emissions simulated by the DGVMs are typically lower than assumed in scenarios consistent with the 2°C target, relying on negative emissions to mitigate climate change is a highly uncertain strategy., (© 2018 John Wiley & Sons Ltd.)

No consensus has yet been reached on the major factors driving the observed increase in the seasonal amplitude of atmospheric CO 2 in the northern latitudes. In this study, we used atmospheric CO 2 records from 26 northern hemisphere stations with a temporal coverage longer than 15 years, and an atmospheric transport model prescribed with net biome productivity (NBP) from an ensemble of nine terrestrial ecosystem models, to attribute change in the seasonal amplitude of atmospheric CO 2 . We found significant (p < .05) increases in seasonal peak-to-trough CO 2 amplitude (AMP P -T ) at nine stations, and in trough-to-peak amplitude (AMP T -P ) and climate change are dominant drivers of the increase in AMP 2 concentration (eCO 2 ) and climate change are dominant drivers of the increase in AMP P -T and AMP T (39% and 42%) almost equally than by climate change (32% and 35%). The increased carbon losses during the months with a net carbon release in response to eCO -P in the high latitudes. At the Barrow station, the observed increase of AMP P -T and AMP T -P over the last 33 years is explained by eCO 2 (39% and 42%) almost equally than by climate change (32% and 35%). The increased carbon losses during the months with a net carbon release in response to eCO 2 are associated with higher ecosystem respiration due to the increase in carbon storage caused by eCO 2 during carbon uptake period. Air-sea CO 2 fluxes (10% for AMP P -T and 11% for AMP T -P ) and the impacts of land-use change (marginally significant 3% for AMP P -T and 4% for AMP T -P ) also contributed to the CO 2 measured at Barrow, highlighting the role of these factors in regulating seasonal changes in the global carbon cycle., (© 2017 John Wiley & Sons Ltd.)

Land-atmosphere exchanges influence atmospheric CO 2 . Emphasis has been on describing photosynthetic CO 2 uptake, but less on respiration losses. New global datasets describe upper canopy dark respiration (R d ) and temperature dependencies. This allows characterisation of baseline R d , instantaneous temperature responses and longer-term thermal acclimation effects. Here we show the global implications of these parameterisations with a global gridded land model. This model aggregates R d to whole-plant respiration R p , driven with meteorological forcings spanning uncertainty across climate change models. For pre-industrial estimates, new baseline R d increases R p and especially in the tropics. Compared to new baseline, revised instantaneous response decreases R p for mid-latitudes, while acclimation lowers this for the tropics with increases elsewhere. Under global warming, new R d estimates amplify modelled respiration increases, although partially lowered by acclimation. Future measurements will refine how R d aggregates to whole-plant respiration. Our analysis suggests R p could be around 30% higher than existing estimates.

Strategies to mitigate climate change by reducing deforestation and forest degradation (e.g. REDD+) require country- or region-specific information on temporal changes in forest carbon (C) pools to develop accurate emission factors. The soil C pool is one of the most important C reservoirs, but is rarely included in national forest reference emission levels due to a lack of data. Here, we present the soil organic C (SOC) dynamics along 20 years of forest-to-pasture conversion in two subregions with different management practices during pasture establishment in the Colombian Amazon: high-grazing intensity (HG) and low-grazing intensity (LG) subregions. We determined the pattern of SOC change resulting from the conversion from forest (C3 plants) to pasture (C4 plants) by analysing total SOC stocks and the natural abundance of the stable isotopes (13) C along two 20-year chronosequences identified in each subregion. We also analysed soil N stocks and the natural abundance of (15) N during pasture establishment. In general, total SOC stocks at 30 cm depth in the forest were similar for both subregions, with an average of 47.1 ± 1.8 Mg C ha(-1) in HG and 48.7 ± 3.1 Mg C ha(-1) in LG. However, 20 years after forest-to-pasture conversion SOC in HG decreased by 20%, whereas in LG SOC increased by 41%. This net SOC decrease in HG was due to a larger reduction in C3-derived input and to a comparatively smaller increase in C4-derived C input. In LG both C3- and C4-derived C input increased along the chronosequence. N stocks were generally similar in both subregions and soil N stock changes during pasture establishment were correlated with SOC changes. These results emphasize the importance of management practices involving low-grazing intensity in cattle activities to preserve SOC stocks and to reduce C emissions after land-cover change from forest to pasture in the Colombian Amazon., (© 2016 John Wiley & Sons Ltd.)

The purpose of this study was to evaluate 10 process-based terrestrial biosphere models that were used for the IPCC fifth Assessment Report. The simulated gross primary productivity (GPP) is compared with flux-tower-based estimates by Jung et al. [Journal of Geophysical Research 116 (2011) G00J07] (JU11). The net primary productivity (NPP) apparent sensitivity to climate variability and atmospheric CO2 trends is diagnosed from each model output, using statistical functions. The temperature sensitivity is compared against ecosystem field warming experiments results. The CO2 sensitivity of NPP is compared to the results from four Free-Air CO2 Enrichment (FACE) experiments. The simulated global net biome productivity (NBP) is compared with the residual land sink (RLS) of the global carbon budget from Friedlingstein et al. [Nature Geoscience 3 (2010) 811] (FR10). We found that models produce a higher GPP (133 ± 15 Pg C yr(-1) ) than JU11 (118 ± 6 Pg C yr(-1) ). In response to rising atmospheric CO2 concentration, modeled NPP increases on average by 16% (5-20%) per 100 ppm, a slightly larger apparent sensitivity of NPP to CO2 than that measured at the FACE experiment locations (13% per 100 ppm). Global NBP differs markedly among individual models, although the mean value of 2.0 ± 0.8 Pg C yr(-1) is remarkably close to the mean value of RLS (2.1 ± 1.2 Pg C yr(-1) ). The interannual variability in modeled NBP is significantly correlated with that of RLS for the period 1980-2009. Both model-to-model and interannual variation in model GPP is larger than that in model NBP due to the strong coupling causing a positive correlation between ecosystem respiration and GPP in the model. The average linear regression slope of global NBP vs. temperature across the 10 models is -3.0 ± 1.5 Pg C yr(-1) °C(-1) , within the uncertainty of what derived from RLS (-3.9 ± 1.1 Pg C yr(-1) °C(-1) ). However, 9 of 10 models overestimate the regression slope of NBP vs. precipitation, compared with the slope of the observed RLS vs. precipitation. With most models lacking processes that control GPP and NBP in addition to CO2 and climate, the agreement between modeled and observation-based GPP and NBP can be fortuitous. Carbon-nitrogen interactions (only separable in one model) significantly influence the simulated response of carbon cycle to temperature and atmospheric CO2 concentration, suggesting that nutrients limitations should be included in the next generation of terrestrial biosphere models., (© 2013 Blackwell Publishing Ltd.)

Tropospheric ozone (O(3)) is a global air pollutant that causes billions of dollars in lost plant productivity annually. It is an important anthropogenic greenhouse gas, and as a secondary air pollutant, it is present at high concentrations in rural areas far from industrial sources. It also reduces plant productivity by entering leaves through the stomata, generating other reactive oxygen species and causing oxidative stress, which in turn decreases photosynthesis, plant growth, and biomass accumulation. The deposition of O(3) into vegetation through stomata is an important sink for tropospheric O(3), but this sink is modified by other aspects of environmental change, including rising atmospheric carbon dioxide concentrations, rising temperature, altered precipitation, and nitrogen availability. We review the atmospheric chemistry governing tropospheric O(3) mass balance, the effects of O(3) on stomatal conductance and net primary productivity, and implications for agriculture, carbon sequestration, and climate change.

The future of tropical forests has become one of the iconic issues in climate-change science. A number of studies that have explored this subject have tended to focus on the output from one or a few climate models, which work at low spatial resolution, whereas society and conservation-relevant assessment of potential impacts requires a finer scale. This study focuses on the role of climate on the current and future distribution of humid tropical forests (HTFs). We first characterize their contemporary climatological niche using annual rainfall and maximum climatological water stress, which also adequately describe the current distribution of other biomes within the tropics. As a first-order approximation of the potential extent of HTFs in future climate regimes defined by global warming of 2°C and 4°C, we investigate changes in the niche through a combination of climate-change anomaly patterns and higher resolution (5 km) maps of current climatology. The climate anomalies are derived using data from 17 coupled Atmosphere-Ocean General Circulation Models (AOGCMs) used in the Fourth Assessment of the Intergovernmental Panel for Climate Change. Our results confirm some risk of forest retreat, especially in eastern Amazonia, Central America and parts of Africa, but also indicate a potential for expansion in other regions, for example around the Congo Basin. The finer spatial scale enabled the depiction of potential resilient and vulnerable zones with practically useful detail. We further refine these estimates by considering the impact of new environmental regimes on plant water demand using the UK Met Office land-surface scheme (of the HadCM3 AOGCM). The CO(2)-related reduction in plant water demand lowers the risk of die-back and can lead to possible niche expansion in many regions. The analysis presented here focuses primarily on hydrological determinants of HTF extent. We conclude by discussing the role of other factors, notably the physiological effects of higher temperature.

*The large-scale loss of Amazonian rainforest under some future climate scenarios has generally been considered to be driven by increased drying over Amazonia predicted by some general circulation models (GCMs). However, the importance of rainfall relative to other drivers has never been formally examined. *Here, we conducted factorial simulations to ascertain the contributions of four environmental drivers (precipitation, temperature, humidity and CO(2)) to simulated changes in Amazonian vegetation carbon (C(veg)), in three dynamic global vegetation models (DGVMs) forced with climate data based on HadCM3 for four SRES scenarios. *Increased temperature was found to be more important than precipitation reduction in causing losses of Amazonian C(veg) in two DGVMs (Hyland and TRIFFID), and as important as precipitation reduction in a third DGVM (LPJ). Increases in plant respiration, direct declines in photosynthesis and increases in vapour pressure deficit (VPD) all contributed to reduce C(veg) under high temperature, but the contribution of each mechanism varied greatly across models. Rising CO(2) mitigated much of the climate-driven biomass losses in the models. *Additional work is required to constrain model behaviour with experimental data under conditions of high temperature and drought. Current models may be overly sensitive to long-term elevated temperatures as they do not account for physiological acclimation.

We examine the evidence for the possibility that 21st-century climate change may cause a large-scale "dieback" or degradation of Amazonian rainforest. We employ a new framework for evaluating the rainfall regime of tropical forests and from this deduce precipitation-based boundaries for current forest viability. We then examine climate simulations by 19 global climate models (GCMs) in this context and find that most tend to underestimate current rainfall. GCMs also vary greatly in their projections of future climate change in Amazonia. We attempt to take into account the differences between GCM-simulated and observed rainfall regimes in the 20th century. Our analysis suggests that dry-season water stress is likely to increase in E. Amazonia over the 21st century, but the region tends toward a climate more appropriate to seasonal forest than to savanna. These seasonal forests may be resilient to seasonal drought but are likely to face intensified water stress caused by higher temperatures and to be vulnerable to fires, which are at present naturally rare in much of Amazonia. The spread of fire ignition associated with advancing deforestation, logging, and fragmentation may act as nucleation points that trigger the transition of these seasonal forests into fire-dominated, low biomass forests. Conversely, deliberate limitation of deforestation and fire may be an effective intervention to maintain Amazonian forest resilience in the face of imposed 21st-century climate change. Such intervention may be enough to navigate E. Amazonia away from a possible "tipping point," beyond which extensive rainforest would become unsustainable.

Predictions of future climate change require complex computer models of the climate system to represent the full range of processes and interactions that influence climate. The Met Office Hadley Centre uses ‘families’ of models as part of the Met Office Unified Model Framework to address different classes of problems. The HadGEM family is a suite of state-of-the-art global environment models that are used to reduce uncertainty and represent and predict complex feedbacks. The HadCM3 family is a suite of well established but cheaper models that are used for multiple simulations, for example, to quantify uncertainty or to test the impact of multiple emissions scenarios. [ABSTRACT FROM AUTHOR]