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Elevated CO2 (eCO2) experiments provide critical information to quantify the effects of rising CO2 on vegetation1–6. Many eCO2 experiments suggest that nutrient limitations modulate the local magnitude of the eCO2 effect on plant biomass1,3,5, but the global extent of these limitations has not been empirically quantified, complicating projections of the capacity of plants to take up CO27,8. Here, we present a data-driven global quantification of the eCO2 effect on biomass based on 138 eCO2 experiments. The strength of CO2 fertilization is primarily driven by nitrogen (N) in ~65% of global vegetation and by phosphorus (P) in ~25% of global vegetation, with N- or P-limitation modulated by mycorrhizal association. Our approach suggests that CO2 levels expected by 2100 can potentially enhance plant biomass by 12 ± 3% above current values, equivalent to 59 ± 13 PgC. The global-scale response to eCO2 we derive from experiments is similar to past changes in greenness9 and biomass10 with rising CO2, suggesting that CO2 will continue to stimulate plant biomass in the future despite the constraining effect of soil nutrients. Our research reconciles conflicting evidence on CO2 fertilization across scales and provides an empirical estimate of the biomass sensitivity to eCO2 that may help to constrain climate projections.

The majority of the Earth's terrestrial carbon is stored in the soil. If anthropogenic warming stimulates the loss of this carbon to the atmosphere, it could drive further planetary warming. Despite evidence that warming enhances carbon fluxes to and from the soil, the net global balance between these responses remains uncertain. Here we present a comprehensive analysis of warming-induced changes in soil carbon stocks by assembling data from 49 field experiments located across North America, Europe and Asia. We find that the effects of warming are contingent on the size of the initial soil carbon stock, with considerable losses occurring in high-latitude areas. By extrapolating this empirical relationship to the global scale, we provide estimates of soil carbon sensitivity to warming that may help to constrain Earth system model projections. Our empirical relationship suggests that global soil carbon stocks in the upper soil horizons will fall by 30 ± 30 petagrams of carbon to 203 ± 161 petagrams of carbon under one degree of warming, depending on the rate at which the effects of warming are realized. Under the conservative assumption that the response of soil carbon to warming occurs within a year, a business-as-usual climate scenario would drive the loss of 55 ± 50 petagrams of carbon from the upper soil horizons by 2050. This value is around 12-17 per cent of the expected anthropogenic emissions over this period. Despite the considerable uncertainty in our estimates, the direction of the global soil carbon response is consistent across all scenarios. This provides strong empirical support for the idea that rising temperatures will stimulate the net loss of soil carbon to the atmosphere, driving a positive land carbon-climate feedback that could accelerate climate change.

Plant growth is influenced by interactions with neighbouring plants. The strength and direction of the cumulative neighbourhood effect on growth can depend on neighbour properties, such as their abundance, size and proximity, as well as the degree of similarity between interacting plants and their traits, which can be captured by the species identity of neighbours. Such interactions are also influenced by the local environmental conditions that are largely determined by climate. Because neighbour and climatic effects are typically explored in isolation, particularly in long‐lived species such as trees, it is unclear how the impacts of neighbours on plant growth shift in response to temporal variation in climatic conditions.Here, we explored how neighbouring plants impact the annual growth of two eucalypts, Eucalyptus delegatensis and Eucalyptus regnans, over three growing seasons in an experimental forest in south‐east Tasmania, Australia. We assessed whether eucalypt growth rates could be described by the number, size, proximity, and species identity of neighbours, and how the strength of this effect was influenced by the growing season climatic conditions.We found that climate and neighbouring plants had an interactive impact on eucalypt growth. Neighbours had a consistent, competitive effect on the growth of both eucalypts in all three growing seasons which was strongly related to the cumulative neighbourhood biomass. The identity of neighbours was important in determining E. regnans growth only, whereby distinguishing neighbours according to functional group best described growth. Over all three growing seasons, we predicted that, on average, neighbours reduced E. delegatensis and E. regnans mean annual growth by 60.5% and 48.4%, respectively. However, the strength of the competitive effect of neighbours on eucalypt growth was related to growing season climate, being strongest when conditions were hot and dry and weakest in cool, wet conditions.Synthesis: Given the consistent results observed in two co‐occurring eucalypts, our findings suggest that drier and hotter climatic conditions increase the strength of competitive effects on tree growth. This has implications for future forest productivity given projected increased temperatures and variation in rainfall patterns globally. [ABSTRACT FROM AUTHOR]

The rising atmospheric concentration of carbon dioxide (C[O.sub.2]) should stimulate ecosystem productivity, but to what extent is highly uncertain, particularly when combined with changing temperature and precipitation (1). Ecosystem response to C[O.sub.2] is complicated by biogeochemical feedbacks (2) but must be understood if carbon storage and associated dampening of climate warming are to be predicted (3). Feedbacks through the hydrological cycle are particularly important (4) and the physiology is well known; elevated C[O.sub.2] reduces stomatal conductance and increases plant water use efficiency (the amount of water required to produce a unit of plant dry matter) (5). The C[O.sub.2] response should consequently be strongest when water is limiting (6); although this has been shown in some experiments (7), it is absent from many (8-11). Here we show that large annual variation in the stimulation of aboveground biomass by elevated C[O.sub.2] in a mixed [C.sub.3]/[C.sub.4] temperate grassland can be predicted accurately using seasonal rainfall totals; summer rainfall had a positive effect but autumn and spring rainfall had negative effects on the C[O.sub.2] response. Thus, the elevated C[O.sub.2] effect mainly depended upon the balance between summer and autumn/spring rainfall. This is partly because high rainfall during cool, moist seasons leads to nitrogen limitation, reducing or even preventing biomass stimulation by elevated C[O.sub.2]. Importantly, the prediction held whether plots were warmed by 2°C or left unwarmed, and was similar for [C.sub.3] plants and total biomass, allowing us to make a powerful generalization about ecosystem responses to elevated C[O.sub.2]. This new insight is particularly valuable because climate projections predict large changes in the timing of rainfall, even where annual totals remain static (12). Our findings will help resolve apparent differences in the outcomes of C[O.sub.2] experiments and improve the formulation and interpretation of models that are insensitive to differences in the seasonal effects of rainfall on the C[O.sub.2] response (7,13,14)., Anthropogenic emissions of C[O.sub.2] have been increasing, reaching 9.7billion tonnes of carbon (C) in 2012 (ref. 15). The biosphere absorbs approximately 50% of anthropogenically emitted carbon per annum (16), so [...]

Summary: Vulnerability to xylem cavitation is a strong predictor of drought‐induced damage in forest communities. However, biotic features of the community itself can influence water availability at the individual tree‐level, thereby modifying patterns of drought damage.Using an experimental forest in Tasmania, Australia, we determined the vulnerability to cavitation (leaf P50) of four tree species and assessed the drought‐induced canopy damage of 2944 6‐yr‐old trees after an extreme natural drought episode. We examined how individual damage was related to their size and the density and species identity of neighbouring trees.The two co‐occurring dominant tree species, Eucalyptus delegatensis and Eucalyptus regnans, were the most vulnerable to drought‐induced xylem cavitation and both species suffered significantly greater damage than neighbouring, subdominant species Pomaderris apetala and Acacia dealbata. While the two eucalypts had similar leaf P50 values, E. delegatensis suffered significantly greater damage, which was strongly related to the density of neighbouring P. apetala. Damage in E. regnans was less impacted by neighbouring plants and smaller trees of both eucalypts sustained significantly more damage than larger trees.Our findings demonstrate that natural drought damage is influenced by individual plant physiology as well as the composition, physiology and density of the surrounding stand. [ABSTRACT FROM AUTHOR]

The vegetation's response to climate change is a significant source of uncertainty in future terrestrial biosphere model projections. Constraining climate-carbon cycle feedbacks requires improving our understanding of direct, as well as long-term, plant physiological responses to climate. In particular, the timescales and strength of memory effects arising from both extreme events (i.e., droughts and heatwaves) and structural lags in the systems have largely been overlooked in the development of models. This is despite the knowledge that plant responses to climatic drivers occur across multiple timescales (seconds to decades), with the impact of climate extremes resonating for many years. Using data from 13 eddy covariance sites, covering two rainfall gradients (256 to 1491 mm yr-1) in Australia, in combination with a hierarchical Bayesian model, we characterised the timescales and magnitude of influence of antecedent drivers on daily net ecosystem exchange (NEE) and latent heat flux (λE). Model fit varied considerably across sites when modelling NEE, with R2 values of between 0.30 and 0.83. Latent heat was considerably more predictable across sites, with R2 values ranging from 0.56 to 0.95. When considered at a continental scale, both fluxes were more predictable when memory effects were included in the model. These memory effects accounted for an average of 17 % of the NEE predictability and 15 % for λE. The importance of environmental memory in predicting fluxes increased as site water availability declined (ρ = -0.72, p < 0.01 for NEE, ρ = -0.62, p < 0.05 for λE). However, these relationships did not necessarily hold when sites were grouped by vegetation type. We also tested a k-means clustering plus regression model to confirm the suitability of the Bayesian model for modelling these sites. The k-means approach performed similarly to the Bayesian model in terms of model fit, demonstrating the robustness of the Bayesian framework for exploring the role of environmental memory. Our results underline the importance of capturing memory effects in models used to project future responses to climate change, especially in water-limited ecosystems. Finally, we demonstrate a considerable variation in individual site predictability, driven to a notable degree by environmental memory, and this should be considered when evaluating model performance across ecosystems. [ABSTRACT FROM AUTHOR]