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Microbial carbon use efficiency (CUE) affects the fate and storage of carbon in terrestrial ecosystems, but its global importance remains uncertain. Accurately modeling and predicting CUE on a global scale is challenging due to inconsistencies in measurement techniques and the complex interactions of climatic, edaphic, and biological factors across scales. The link between microbial CUE and soil organic carbon relies on the stabilization of microbial necromass within soil aggregates or its association with minerals, necessitating an integration of microbial and stabilization processes in modeling approaches. In this perspective, we propose a comprehensive framework that integrates diverse data sources, ranging from genomic information to traditional soil carbon assessments, to refine carbon cycle models by incorporating variations in CUE, thereby enhancing our understanding of the microbial contribution to carbon cycling., (© 2024. The Author(s).)

Permafrost regions contain approximately half of the carbon stored in land ecosystems and have warmed at least twice as much as any other biome. This warming has influenced vegetation activity, leading to changes in plant composition, physiology, and biomass storage in aboveground and belowground components, ultimately impacting ecosystem carbon balance. Yet, little is known about the causes and magnitude of long-term changes in the above- to belowground biomass ratio of plants (η). Here, we analyzed η values using 3,013 plots and 26,337 species-specific measurements across eight sites on the Tibetan Plateau from 1995 to 2021. Our analysis revealed distinct temporal trends in η for three vegetation types: a 17% increase in alpine wetlands, and a decrease of 26% and 48% in alpine meadows and alpine steppes, respectively. These trends were primarily driven by temperature-induced growth preferences rather than shifts in plant species composition. Our findings indicate that in wetter ecosystems, climate warming promotes aboveground plant growth, while in drier ecosystems, such as alpine meadows and alpine steppes, plants allocate more biomass belowground. Furthermore, we observed a threefold strengthening of the warming effect on η over the past 27 y. Soil moisture was found to modulate the sensitivity of η to soil temperature in alpine meadows and alpine steppes, but not in alpine wetlands. Our results contribute to a better understanding of the processes driving the response of biomass distribution to climate warming, which is crucial for predicting the future carbon trajectory of permafrost ecosystems and climate feedback., Competing Interests: Competing interests statement:The authors declare no competing interest.

During extensive periods without rain, known as dry-downs, decreasing soil moisture (SM) induces plant water stress at the point when it limits evapotranspiration, defining a critical SM threshold (θ crit ). Better quantification of θ crit is needed for improving future projections of climate and water resources, food production, and ecosystem vulnerability. Here, we combine systematic satellite observations of the diurnal amplitude of land surface temperature (dLST) and SM during dry-downs, corroborated by in-situ data from flux towers, to generate the observation-based global map of θ crit . We find an average global θ crit of 0.19 m 3 /m 3 , varying from 0.12 m 3 /m 3 in arid ecosystems to 0.26 m 3 /m 3 in humid ecosystems. θ crit simulated by Earth System Models is overestimated in dry areas and underestimated in wet areas. The global observed pattern of θ crit reflects plant adaptation to soil available water and atmospheric demand. Using explainable machine learning, we show that aridity index, leaf area and soil texture are the most influential drivers. Moreover, we show that the annual fraction of days with water stress, when SM stays below θ crit , has increased in the past four decades. Our results have important implications for understanding the inception of water stress in models and identifying SM tipping points., (© 2024. The Author(s).)

Although substantial advances in predicting the ecological impacts of global change have been made, predictions of the evolutionary impacts have lagged behind. In soil ecosystems, microbes act as the primary energetic drivers of carbon cycling; however, microbes are also capable of evolving on timescales comparable to rates of global change. Given the importance of soil ecosystems in global carbon cycling, we assess the potential impact of microbial evolution on carbon-climate feedbacks in this system. We begin by reviewing the current state of knowledge concerning microbial evolution in response to global change and its specific effect on soil carbon dynamics. Through this integration, we synthesize a roadmap detailing how to integrate microbial evolution into ecosystem biogeochemical models. Specifically, we highlight the importance of microscale mechanistic soil carbon models, including choosing an appropriate evolutionary model (e.g., adaptive dynamics, quantitative genetics), validating model predictions with 'omics' and experimental data, scaling microbial adaptations to ecosystem level processes, and validating with ecosystem-scale measurements. The proposed steps will require significant investment of scientific resources and might require 10-20 years to be fully implemented. However, through the application of multi-scale integrated approaches, we will advance the integration of microbial evolution into predictive understanding of ecosystems, providing clarity on its role and impact within the broader context of environmental change., (© 2024 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

The Tibetan Plateau, housing 20% of China's wetlands, plays a vital role in the regional carbon cycle. Examining the phenological dynamics of wetland vegetation in response to climate change is crucial for understanding its impact on the ecosystem. Despite this importance, the specific effects of climate change on wetland vegetation phenology in this region remain uncertain. In this study, we investigated the influence of climate change on the end of the growing season (EOS) of marsh wetland vegetation across the Tibetan Plateau, utilizing satellite-derived Normalized Difference Vegetation Index (NDVI) data and observational climate data. We observed that the regionally averaged EOS of marsh vegetation across the Tibetan Plateau was significantly (p < .05) delayed by 4.10 days/decade from 2001 to 2020. Warming preseason temperatures were found to be the primary driver behind the delay in the EOS of marsh vegetation, whereas preseason cumulative precipitation showed no significant impact. Interestingly, the responses of EOS to climate change varied spatially across the plateau, indicating a regulatory role for hydrological conditions in marsh phenology. In the humid and cold central regions, preseason daytime warming significantly delayed the EOS. However, areas with lower soil moisture exhibited a weaker or reversed delay effect, suggesting complex interplays between temperature, soil moisture, and EOS. Notably, in the arid southwestern regions of the plateau, increased preseason rainfall directly delayed the EOS, while higher daytime temperatures advanced it. Our results emphasize the critical role of hydrological conditions, specifically soil moisture, in shaping marsh EOS responses in different regions. Our findings underscore the need to incorporate hydrological factors into terrestrial ecosystem models, particularly in cold and dry regions, for accurate predictions of marsh vegetation phenological responses to climate change. This understanding is vital for informed conservation and management strategies in the face of current and future climate challenges., (© 2023 John Wiley & Sons Ltd.)

In the northern high latitudes, warmer spring temperatures generally lead to earlier leaf onsets, higher vegetation production, and enhanced spring carbon uptake. Yet, whether this positive linkage has diminished under climate change remains debated. Here, we used atmospheric CO 2 measurements at Barrow (Alaska) during 1979-2020 to investigate the strength of temperature dependence of spring carbon uptake reflected by two indicators, spring zero-crossing date (SZC) and CO 2 drawdown (SCC). We found a fall and rise in the interannual correlation of temperature with SZC and SCC (R SZC-T and R SCC-T ), showing a recent reversal of the previously reported weakening trend of R SZC-T and R SCC-T . We used a terrestrial biosphere model coupled with an atmospheric transport model to reproduce this fall and rise phenomenon and conducted factorial simulations to explore its potential causes. We found that a strong-weak-strong spatial synchrony of spring temperature anomalies per se has contributed to the fall and rise trend in R SZC-T and R SCC-T , despite an overall unbroken temperature control on net ecosystem CO 2 fluxes at local scale. Our results provide an alternative explanation for the apparent drop of R SZC-T and R SCC-T during the late 1990s and 2000s, and suggest a continued positive linkage between spring carbon uptake and temperature during the past four decades. We thus caution the interpretation of apparent climate sensitivities of carbon cycle retrieved from spatially aggregated signals., (© 2023 John Wiley & Sons Ltd.)

Potassium (K + ) is the most abundant inorganic cation in plant cells, playing a critical role in various plant functions. However, the impacts of K on natural terrestrial ecosystems have been less studied compared with nitrogen (N) and phosphorus (P). Here, we present a global meta-analysis aimed at quantifying the response of aboveground production to K addition. This analysis is based on 144 field K fertilization experiments. We also investigate the influences of climate, soil properties, ecosystem types, and fertilizer regimes on the responses of aboveground production. We find that: K addition significantly increases aboveground production by 12.3% (95% CI: 7.4-17.5%), suggesting a widespread occurrence of K limitation across terrestrial ecosystems; K limitation is more prominent in regions with humid climates, acidic soils, or weathered soils; the effect size of K addition varies among climate zones/regions, and is influenced by multiple factors; and previous N : K and K : P thresholds utilized to detect K limitation in wetlands cannot be applied to other biomes. Our findings emphasize the role of K in limiting terrestrial productivity, which should be integrated into future terrestrial ecosystems models., (© 2023 The Authors New Phytologist © 2023 New Phytologist Foundation.)

Global change ecology nowadays embraces ever-growing large observational datasets (big-data) and complex mathematical models that track hundreds of ecological processes (big-model). The rapid advancement of the big-data-big-model has reached its bottleneck: high computational requirements prevent further development of models that need to be integrated over long time-scales to simulate the distribution of ecosystems carbon and nutrient pools and fluxes. Here, we introduce a machine-learning acceleration (MLA) tool to tackle this grand challenge. We focus on the most resource-consuming step in terrestrial biosphere models (TBMs): the equilibration of biogeochemical cycles (spin-up), a prerequisite that can take up to 98% of the computational time. Through three members of the ORCHIDEE TBM family part of the IPSL Earth System Model, including versions that describe the complex interactions between nitrogen, phosphorus and carbon that do not have any analytical solution for the spin-up, we show that an unoptimized MLA reduced the computation demand by 77%-80% for global studies via interpolating the equilibrated state of biogeochemical variables for a subset of model pixels. Despite small biases in the MLA-derived equilibrium, the resulting impact on the predicted regional carbon balance over recent decades is minor. We expect a one-order of magnitude lower computation demand by optimizing the choices of machine learning algorithms, their settings, and balancing the trade-off between quality of MLA predictions and need for TBM simulations for training data generation and bias reduction. Our tool is agnostic to gridded models (beyond TBMs), compatible with existing spin-up acceleration procedures, and opens the door to a wide variety of future applications, with complex non-linear models benefit most from the computational efficiency., (© 2023 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

Soils store more carbon than other terrestrial ecosystems 1,2 . How soil organic carbon (SOC) forms and persists remains uncertain 1,3 , which makes it challenging to understand how it will respond to climatic change 3,4 . It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss 5-7 . Although microorganisms affect the accumulation and loss of soil organic matter through many pathways 4,6,8-11 , microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes 12,13 . Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved 7,14,15 . Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate., (© 2023. The Author(s).)

Terrestrial ecosystems have taken up about 32% of the total anthropogenic CO 2 emissions in the past six decades 1 . Large uncertainties in terrestrial carbon-climate feedbacks, however, make it difficult to predict how the land carbon sink will respond to future climate change 2 . Interannual variations in the atmospheric CO 2 growth rate (CGR) are dominated by land-atmosphere carbon fluxes in the tropics, providing an opportunity to explore land carbon-climate interactions 3-6 . It is thought that variations in CGR are largely controlled by temperature 7-10 but there is also evidence for a tight coupling between water availability and CGR 11 . Here, we use a record of global atmospheric CO 2 , terrestrial water storage and precipitation data to investigate changes in the interannual relationship between tropical land climate conditions and CGR under a changing climate. We find that the interannual relationship between tropical water availability and CGR became increasingly negative during 1989-2018 compared to 1960-1989. This could be related to spatiotemporal changes in tropical water availability anomalies driven by shifts in El Niño/Southern Oscillation teleconnections, including declining spatial compensatory water effects 9 . We also demonstrate that most state-of-the-art coupled Earth System and Land Surface models do not reproduce the intensifying water-carbon coupling. Our results indicate that tropical water availability is increasingly controlling the interannual variability of the terrestrial carbon cycle and modulating tropical terrestrial carbon-climate feedbacks., (© 2023. The Author(s).)

Vegetation response to soil and atmospheric drought has raised extensively controversy, however, the relative contributions of soil drought, atmospheric drought, and their compound droughts on global vegetation growth remain unclear. Combining the changes in soil moisture (SM), vapor pressure deficit (VPD), and vegetation growth (normalized difference vegetation index [NDVI]) during 1982-2015, here we evaluated the trends of these three drought types and quantified their impacts on global NDVI. We found that global VPD has increased 0.22 ± 0.05 kPa·decade -1 during 1982-2015, and this trend was doubled after 1996 (0.32 ± 0.16 kPa·decade -1 ) than before 1996 (0.16 ± 0.15 kPa·decade -1 ). Regions with large increase in VPD trend generally accompanied with decreasing trend in SM, leading to a widespread increasing trend in compound droughts across 37.62% land areas. We further found compound droughts dominated the vegetation browning since late 1990s, contributing to a declined NDVI of 64.56%. Earth system models agree with the dominant role of compound droughts on vegetation growth, but their negative magnitudes are considerably underestimated, with half of the observed results (34.48%). Our results provided the evidence of compound droughts-induced global vegetation browning, highlighting the importance of correctly simulating the ecosystem-scale response to the under-appreciated exposure to compound droughts as it will increase with climate change., (© 2023 John Wiley & Sons Ltd.)

The consistent monitoring of trees both inside and outside of forests is key to sustainable land management. Current monitoring systems either ignore trees outside forests or are too expensive to be applied consistently across countries on a repeated basis. Here we use the PlanetScope nanosatellite constellation, which delivers global very high-resolution daily imagery, to map both forest and non-forest tree cover for continental Africa using images from a single year. Our prototype map of 2019 (RMSE = 9.57%, bias = -6.9%). demonstrates that a precise assessment of all tree-based ecosystems is possible at continental scale, and reveals that 29% of tree cover is found outside areas previously classified as tree cover in state-of-the-art maps, such as in croplands and grassland. Such accurate mapping of tree cover down to the level of individual trees and consistent among countries has the potential to redefine land use impacts in non-forest landscapes, move beyond the need for forest definitions, and build the basis for natural climate solutions and tree-related studies., (© 2023. The Author(s).)

Spatial redistribution of nutrients by atmospheric transport and deposition could theoretically act as a continental-scale mechanism which counteracts declines in soil fertility caused by nutrient lock-up in accumulating biomass in tropical forests in Central Africa. However, to what extent it affects carbon sinks in forests remains elusive. Here we use a terrestrial biosphere model to quantify the impact of changes in atmospheric nitrogen and phosphorus deposition on plant nutrition and biomass carbon sink at a typical lowland forest site in Central Africa. We find that the increase in nutrient deposition since the 1980s could have contributed to the carbon sink over the past four decades up to an extent which is similar to that from the combined effects of increasing atmospheric carbon dioxide and climate change. Furthermore, we find that the modelled carbon sink responds to changes in phosphorus deposition, but less so to nitrogen deposition. The pronounced response of ecosystem productivity to changes in nutrient deposition illustrates a potential mechanism that could control carbon sinks in Central Africa. Monitoring the quantity and quality of nutrient deposition is needed in this region, given the changes in nutrient deposition due to human land use., (© 2022 The Authors. New Phytologist © 2022 New Phytologist Foundation.)

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.)

The distribution of dryland trees and their density, cover, size, mass and carbon content are not well known at sub-continental to continental scales 1-14 . This information is important for ecological protection, carbon accounting, climate mitigation and restoration efforts of dryland ecosystems 15-18 . We assessed more than 9.9 billion trees derived from more than 300,000 satellite images, covering semi-arid sub-Saharan Africa north of the Equator. We attributed wood, foliage and root carbon to every tree in the 0-1,000 mm year -1 rainfall zone by coupling field data 19 , machine learning 20-22 , satellite data and high-performance computing. Average carbon stocks of individual trees ranged from 0.54 Mg C ha -1 and 63 kg C tree -1 in the arid zone to 3.7 Mg C ha -1 and 98 kg tree -1 in the sub-humid zone. Overall, we estimated the total carbon for our study area to be 0.84 (±19.8%) Pg C. Comparisons with 14 previous TRENDY numerical simulation studies 23 for our area found that the density and carbon stocks of scattered trees have been underestimated by three models and overestimated by 11 models, respectively. This benchmarking can help understand the carbon cycle and address concerns about land degradation 24-29 . We make available a linked database of wood mass, foliage mass, root mass and carbon stock of each tree for scientists, policymakers, dryland-restoration practitioners and farmers, who can use it to estimate farmland tree carbon stocks from tablets or laptops., (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Synthetic Nitrogen (N) usage in agriculture has greatly increased food supply over the past century. However, the intensive use of N fertilizer is nevertheless the source of numerous environmental issues and remains a major challenge for policymakers to understand, measure, and quantify the interactions and trade-offs between ecosystem carbon and terrestrial biodiversity loss. In this study, we investigate the impacts of a public policy scenario that aims to halve N fertilizer application across European Union (EU) agriculture on both carbon (C) sequestration and biodiversity changes. We quantify the impacts by integrating two economic models with an agricultural land surface model and a terrestrial biodiversity model (that uses data from a range of taxonomic groups, including plants, fungi, vertebrates and invertebrates). Here, we show that the two economic scenarios lead to different outcomes in terms of C sequestration potential and biodiversity. Land abandonment associated with increased fertilizer price scenario facilitates higher C sequestration in soils (+ 1014 MtC) and similar species richness levels (+ 1.9%) at the EU scale. On the other hand, the more extensive crop production scenario is associated with lower C sequestration potential in soils (- 97 MtC) and similar species richness levels (- 0.4%) because of a lower area of grazing land. Our results therefore highlight the complexity of the environmental consequences of a nitrogen reduction policy, which will depend fundamentally on how the economic models used to project consequences., (© 2022. The Author(s).)

Carbon budget accounting relies heavily on Food and Agriculture Organization land-use data reported by governments. Here we develop a new land-use and cover-change database for China, finding that differing historical survey methods biased China's reported data causing large errors in Food and Agriculture Organization databases. Land ecosystem model simulations driven with the new data reveal a strong carbon sink of 8.9 ± 0.8 Pg carbon from 1980 to 2019 in China, which was not captured in Food and Agriculture Organization data-based estimations due to biased land-use and cover-change signals. The land-use and cover-change in China, characterized by a rapid forest expansion from 1980 to 2019, contributed to nearly 44% of the national terrestrial carbon sink. In contrast, climate changes (22.3%), increasing nitrogen deposition (12.9%), and rising carbon dioxide (8.1%) are less important contributors. This indicates that previous studies have greatly underestimated the impact of land-use and cover-change on the terrestrial carbon balance of China. This study underlines the importance of reliable land-use and cover-change databases in global carbon budget accounting., (© 2022. The Author(s).)

The dominance of vapor pressure deficit (VPD) and soil water content (SWC) for plant water stress is still under debate. These two variables are strongly coupled and influenced by climatic drivers. The impacts of climatic drivers on the relationships between gross primary production (GPP) and water stress from VPD/SWC and the interaction between VPD and SWC are not fully understood. Here, applying statistical methods and extreme gradient boosting models-Shapley additive explanations framework to eddy-covariance observations from the global FLUXNET2015 data set, we found that the VPD-GPP relationship was strongly influenced by climatic interactions and that VPD was more important for plant water stress than SWC across most plant functional types when we removed the effect of main climatic drivers, e.g. air temperature, incoming shortwave radiation and wind speed. However, we found no evidence for a significant influence of elevated CO 2 on stress alleviation, possibly because of the short duration of the records (approximately one decade). Additionally, the interactive effect between VPD and SWC differed from their individual effect. When SWC was high, the SHAP interaction value of SWC and VPD on GPP was decreased with increasing VPD, but when SWC was low, the trend was the opposite. Additionally, we revealed a threshold effect for VPD stress on GPP loss; above the threshold value, the stress on GPP was flattened off. Our results have important implications for independently identifying VPD and SWC limitations on plant productivity, which is meaningful for capturing the magnitude of ecosystem responses to water stress in dynamic global vegetation models., (© 2022 John Wiley & Sons Ltd.)

Vegetation is a key component in the global carbon cycle as it stores ~450 GtC as biomass, and removes about a third of anthropogenic CO 2 emissions. However, in some regions, the rate of plant carbon uptake is beginning to slow, largely because of water stress. Here, we develop a new observation-based methodology to diagnose vegetation water stress and link it to environmental drivers. We used the ratio of remotely sensed land surface to near surface atmospheric temperatures (LST/T air ) to represent vegetation water stress, and built regression tree models (random forests) to assess the relationship between LST/T air and the main environmental drivers of surface energy fluxes in the tropical Americas. We further determined ecosystem traits associated with water stress and surface energy partitioning, pinpointed critical thresholds for water stress, and quantified changes in ecosystem carbon uptake associated with crossing these critical thresholds. We found that the top drivers of LST/T air , explaining over a quarter of its local variability in the study region, are (1) radiation, in 58% of the study region; (2) water supply from precipitation, in 30% of the study region; and (3) atmospheric water demand from vapor pressure deficits (VPD), in 22% of the study region. Regions in which LST/T air variation is driven by radiation are located in regions of high aboveground biomass or at high elevations, while regions in which LST/T air is driven by water supply from precipitation or atmospheric demand tend to have low species richness. Carbon uptake by photosynthesis can be reduced by up to 80% in water-limited regions when critical thresholds for precipitation and air dryness are exceeded simultaneously, that is, as compound events. Our results demonstrate that vegetation structure and diversity can be important for regulating surface energy and carbon fluxes over tropical regions., (© 2022 John Wiley & Sons Ltd.)

Considerable uncertainty and debate exist in projecting the future capacity of forests to sequester atmospheric CO 2 . Here we estimate spatially explicit patterns of biomass loss by tree mortality (LOSS) from largely unmanaged forest plots to constrain projected (2015-2099) net primary productivity (NPP), heterotrophic respiration (HR) and net carbon sink in six dynamic global vegetation models (DGVMs) across continents. This approach relies on a strong relationship among LOSS, NPP, and HR at continental or biome scales. The DGVMs overestimated historical LOSS, particularly in tropical regions and eastern North America by as much as 5 Mg ha -1 y -1 . The modeled spread of DGVM-projected NPP and HR uncertainties was substantially reduced in tropical regions after incorporating the field-based mortality constraint. The observation-constrained models show a decrease in the tropical forest carbon sink by the end of the century, particularly across South America (from 2 to 1.4 PgC y -1 ), and an increase in the sink in North America (from 0.8 to 1.1 PgC y -1 ). These results highlight the feasibility of using forest demographic data to empirically constrain forest carbon sink projections and the potential overestimation of projected tropical forest carbon sinks., (© 2022. The Author(s).)

Understanding the critical soil moisture (SM) threshold (θ crit ) of plant water stress and land surface energy partitioning is a basis to evaluate drought impacts and improve models for predicting future ecosystem condition and climate. Quantifying the θ crit across biomes and climates is challenging because observations of surface energy fluxes and SM remain sparse. Here, we used the latest database of eddy covariance measurements to estimate θ crit across Europe by evaluating evaporative fraction (EF)-SM relationships and investigating the covariance between vapor pressure deficit (VPD) and gross primary production (GPP) during SM dry-down periods. We found that the θ crit and soil matric potential threshold in Europe are 16.5% and -0.7 MPa, respectively. Surface energy partitioning characteristics varied among different vegetation types; EF in savannas had the highest sensitivities to SM in water-limited stage, and the lowest in forests. The sign of the covariance between daily VPD and GPP consistently changed from positive to negative during dry-down across all sites when EF shifted from relatively high to low values. This sign of the covariance changed after longer period of SM decline in forests than in grasslands and savannas. Estimated θ crit from the VPD-GPP covariance method match well with the EF-SM method, showing this covariance method can be used to detect the θ crit . We further found that soil texture dominates the spatial variability of θ crit while shortwave radiation and VPD are the major drivers in determining the spatial pattern of EF sensitivities. Our results highlight for the first time that the sign change of the covariance between daily VPD and GPP can be used as an indicator of how ecosystems transition from energy to SM limitation. We also characterized the corresponding θ crit and its drivers across diverse ecosystems in Europe, an essential variable to improve the representation of water stress in land surface models., (© 2021 John Wiley & Sons Ltd.)

Carbon storage by the ocean and by the land is usually quantified separately, and does not fully take into account the land-to-ocean transport of carbon through inland waters, estuaries, tidal wetlands and continental shelf waters-the 'land-to-ocean aquatic continuum' (LOAC). Here we assess LOAC carbon cycling before the industrial period and perturbed by direct human interventions, including climate change. In our view of the global carbon cycle, the traditional 'long-range loop', which carries carbon from terrestrial ecosystems to the open ocean through rivers, is reinforced by two 'short-range loops' that carry carbon from terrestrial ecosystems to inland waters and from tidal wetlands to the open ocean. Using a mass-balance approach, we find that the pre-industrial uptake of atmospheric carbon dioxide by terrestrial ecosystems transferred to the ocean and outgassed back to the atmosphere amounts to 0.65 ± 0.30 petagrams of carbon per year (±2 sigma). Humans have accelerated the cycling of carbon between terrestrial ecosystems, inland waters and the atmosphere, and decreased the uptake of atmospheric carbon dioxide from tidal wetlands and submerged vegetation. Ignoring these changing LOAC carbon fluxes results in an overestimation of carbon storage in terrestrial ecosystems by 0.6 ± 0.4 petagrams of carbon per year, and an underestimation of sedimentary and oceanic carbon storage. We identify knowledge gaps that are key to reduce uncertainties in future assessments of LOAC fluxes., (© 2022. Springer Nature Limited.)

Soil phosphorus (P) availability often limits plant productivity. Classical theories suggest that total P content declines at the temporal scale of pedogenesis, and ecosystems develop toward the efficient use of scarce P during succession. However, the trajectory of ecosystem P within shorter time scales of succession remains unclear. We analyzed changes to P pools at the early (I), middle (II), and late (III) stages of growth of plantation forests (PFs) and the successional stages of natural forests (NFs) at 1969 sites in China. We found significantly lower P contents at later growth stages compared to earlier ones in the PF (p < .05), but higher contents at late successional stages than in earlier stages in the NF (p < .05). Our results indicate that increasing P demand of natural vegetation during succession, may raise, retain, and accumulate P from deeper soil layers. In contrast, ecosystem P in PF was depleted by the more rapidly increasing demand outpacing the development of a P-efficient system. We advocate for more studies to illuminate the mechanisms for determining the divergent changes, which would improve forest management and avoid the vast degradation of PF ecosystems suffering from the ongoing depletion of P., (© 2021 John Wiley & Sons Ltd.)

Our limited understanding of the impacts of drought on tropical forests significantly impedes our ability in accurately predicting the impacts of climate change on this biome. Here, we investigated the impact of drought on the dynamics of forest canopies with different heights using time-series records of remotely sensed Ku-band vegetation optical depth (Ku-VOD), a proxy of top-canopy foliar mass and water content, and separated the signal of Ku-VOD changes into drought-induced reductions and subsequent non-drought gains. Both drought-induced reductions and non-drought increases in Ku-VOD varied significantly with canopy height. Taller tropical forests experienced greater relative Ku-VOD reductions during drought and larger non-drought increases than shorter forests, but the net effect of drought was more negative in the taller forests. Meta-analysis of in situ hydraulic traits supports the hypothesis that taller tropical forests are more vulnerable to drought stress due to smaller xylem-transport safety margins. Additionally, Ku-VOD of taller forests showed larger reductions due to increased atmospheric dryness, as assessed by vapor pressure deficit, and showed larger gains in response to enhanced water supply than shorter forests. Including the height-dependent variation of hydraulic transport in ecosystem models will improve the simulated response of tropical forests to drought., (© 2021 John Wiley & Sons Ltd.)

Consistent information on the current elemental composition of vegetation at global scale and the variables that determine it is lacking. To fill this gap, we gathered a total of 30 912 georeferenced records on woody plants foliar concentrations of nitrogen (N), phosphorus (P) and potassium (K) from published databases, and produced global maps of foliar N, P and K concentrations for woody plants using neural networks at a resolution of 1 km 2 . We used data for climate, atmospheric deposition, soil and morphoclimatic groups to train the neural networks. Foliar N, P and K do not follow clear global latitudinal patterns but are consistent with the hypothesis of soil substrate age. We additionally built generalized linear mixed models to investigate the evolutionary history effect together with the effects of environmental effects. In this comparison, evolutionary history effects explained most of the variability in all cases (mostly > 60%). These results emphasize the determinant role of evolutionary history in foliar elemental composition, which should be incorporated in upcoming dynamic global vegetation models., (© 2021 The Authors. New Phytologist © 2021 New Phytologist Foundation.)

Soil phosphatase enzymes are produced by plant roots and microorganisms and play a key role in the cycling of phosphorus (P), an often-limiting element in terrestrial ecosystems. The production of these enzymes in soil is the most important biological strategy for acquiring phosphate ions from organic molecules. Previous works showed how soil potential phosphatase activity is mainly driven by climatic conditions and soil nitrogen (N) and carbon. Nonetheless, future trends of the activity of these enzymes under global change remain little known. We investigated the influence of some of the main drivers of change on soil phosphatase activity using a meta-analysis of results from 97 published studies. Our database included a compilation of N and P fertilization experiments, manipulation experiments with increased atmospheric CO 2 concentration, warming, and drought, and studies comparing invaded and non-invaded ecosystems. Our results indicate that N fertilization leads to higher phosphatase activity, whereas P fertilization has the opposite effect. The rise of atmospheric CO 2 levels or the arrival of invasive species also exhibits positive response ratios on the activity of soil phosphatases. However, the occurrence of recurrent drought episodes decreases the activity of soil phosphatases. Our analysis did not reveal statistically significant effects of warming on soil phosphatase activity. In general, soil enzymatic changes in the reviewed experiments depended on the initial nutrient and water status of the ecosystems. The observed patterns evidence that future soil phosphatase activity will not only depend on present-day soil conditions but also on potential compensations or amplifications among the different drivers of global change. The responses of soil phosphatases to the global change drivers reported in this study and the consideration of cost-benefit approaches based on the connection of the P and N cycle will be useful for a better estimation of phosphatase production in carbon (C)-N-P models., (© 2021 John Wiley & Sons Ltd.)

The Tibetan Plateau (TP) and Arctic permafrost constitute two large reservoirs of organic carbon, but processes which control carbon accumulation within the surface soil layer of these areas would differ due to the interplay of climate, soil and vegetation type. Here, we synthesized currently available soil carbon data to show that mean organic carbon density in the topsoil (0-10 cm) in TP grassland (3.12 ± 0.52 kg C m -2 ) is less than half of that in Arctic tundra (6.70 ± 1.94 kg C m -2 ). Such difference is primarily attributed to their difference in radiocarbon-inferred soil carbon turnover times (547 years for TP grassland versus 1609 years for Arctic tundra) rather than to their marginal difference in topsoil carbon inputs. Our findings highlight the importance of improving regional-specific soil carbon turnover and its controlling mechanisms across permafrost affected zones in ecosystem models to fully represent carbon-climate feedback., Competing Interests: Conflict of interest The authors declare that they have no conflict of interest., (Copyright © 2021 Science China Press. Published by Elsevier B.V. All rights reserved.)

The 2015-2016 El Niño was one of the strongest on record, but its influence on the carbon balance is less clear. Using Northern Hemisphere atmospheric CO 2 observations, we found both detrended atmospheric CO 2 growth rate (CGR) and CO 2 seasonal-cycle amplitude (SCA) of 2015-2016 were much higher than that of other El Niño events. The simultaneous high CGR and SCA were unusual, because our analysis of long-term CO 2 observations at Mauna Loa revealed a significantly negative correlation between CGR and SCA. Atmospheric inversions and terrestrial ecosystem models indicate strong northern land carbon uptake during spring but substantially reduced carbon uptake (or high emissions) during early autumn, which amplified SCA but also resulted in a small anomaly in annual carbon uptake of northern ecosystems in 2015-2016. This negative ecosystem carbon uptake anomaly in early autumn was primarily due to soil water deficits and more litter decomposition caused by enhanced spring productivity. Our study demonstrates a decoupling between seasonality and annual carbon cycle balance in northern ecosystems over 2015-2016, which is unprecedented in the past five decades of El Niño events., (© 2021 John Wiley & Sons Ltd.)

The rising atmospheric CO 2 concentration leads to a CO 2 fertilization effect on plants-that is, increased photosynthetic uptake of CO 2 by leaves and enhanced water-use efficiency (WUE). Yet, the resulting net impact of CO 2 fertilization on plant growth and soil moisture (SM) savings at large scale is poorly understood. Drylands provide a natural experimental setting to detect the CO 2 fertilization effect on plant growth since foliage amount, plant water-use and photosynthesis are all tightly coupled in water-limited ecosystems. A long-term change in the response of leaf area index (LAI, a measure of foliage amount) to changes in SM is likely to stem from changing water demand of primary productivity in water-limited ecosystems and is a proxy for changes in WUE. Using 34-year satellite observations of LAI and SM over tropical and subtropical drylands, we identify that a 1% increment in SM leads to 0.15% (±0.008, 95% confidence interval) and 0.51% (±0.01, 95% confidence interval) increments in LAI during 1982-1998 and 1999-2015, respectively. The increasing response of LAI to SM has contributed 7.2% (±3.0%, 95% confidence interval) to total dryland greening during 1999-2015 compared to 1982-1998. The increasing response of LAI to SM is consistent with the CO 2 fertilization effect on WUE in water-limited ecosystems, indicating that a given amount of SM has sustained greater amounts of photosynthetic foliage over time. The LAI responses to changes in SM from seven dynamic global vegetation models are not always consistent with observations, highlighting the need for improved process knowledge of terrestrial ecosystem responses to rising atmospheric CO 2 concentration., (© 2021 John Wiley & Sons Ltd.)

Year-to-year changes in carbon uptake by terrestrial ecosystems have an essential role in determining atmospheric carbon dioxide concentrations 1 . It remains uncertain to what extent temperature and water availability can explain these variations at the global scale 2-5 . Here we use factorial climate model simulations 6 and show that variability in soil moisture drives 90 per cent of the inter-annual variability in global land carbon uptake, mainly through its impact on photosynthesis. We find that most of this ecosystem response occurs indirectly as soil moisture-atmosphere feedback amplifies temperature and humidity anomalies and enhances the direct effects of soil water stress. The strength of this feedback mechanism explains why coupled climate models indicate that soil moisture has a dominant role 4 , which is not readily apparent from land surface model simulations and observational analyses 2,5 . These findings highlight the need to account for feedback between soil and atmospheric dryness when estimating the response of the carbon cycle to climatic change globally 5,7 , as well as when conducting field-scale investigations of the response of the ecosystem to droughts 8,9 . Our results show that most of the global variability in modelled land carbon uptake is driven by temperature and vapour pressure deficit effects that are controlled by soil moisture.

Accurate quantification of vegetation carbon turnover time (τ veg ) is critical for reducing uncertainties in terrestrial vegetation response to future climate change. However, in the absence of global information of litter production, τ veg could only be estimated based on net primary productivity under the steady-state assumption. Here, we applied a machine-learning approach to derive a global dataset of litter production by linking 2401 field observations and global environmental drivers. Results suggested that the observation-based estimate of global natural ecosystem litter production was 44.3 ± 0.4 Pg C year -1 . By contrast, land-surface models (LSMs) overestimated the global litter production by about 27%. With this new global litter production dataset, we estimated global τ veg (mean value 10.3 ± 1.4 years) and its spatial distribution. Compared to our observation-based τ veg , modelled τ veg tended to underestimate τ veg at high latitudes. Our empirically derived gridded datasets of litter production and τ veg will help constrain global vegetation models and improve the prediction of global carbon cycle., (© 2021 John Wiley & Sons Ltd.)

Atmospheric carbon dioxide concentration ([CO 2 ]) is increasing, which increases leaf-scale photosynthesis and intrinsic water-use efficiency. These direct responses have the potential to increase plant growth, vegetation biomass, and soil organic matter; transferring carbon from the atmosphere into terrestrial ecosystems (a carbon sink). A substantial global terrestrial carbon sink would slow the rate of [CO 2 ] increase and thus climate change. However, ecosystem CO 2 responses are complex or confounded by concurrent changes in multiple agents of global change and evidence for a [CO 2 ]-driven terrestrial carbon sink can appear contradictory. Here we synthesize theory and broad, multidisciplinary evidence for the effects of increasing [CO 2 ] (iCO 2 ) on the global terrestrial carbon sink. Evidence suggests a substantial increase in global photosynthesis since pre-industrial times. Established theory, supported by experiments, indicates that iCO 2 is likely responsible for about half of the increase. Global carbon budgeting, atmospheric data, and forest inventories indicate a historical carbon sink, and these apparent iCO 2 responses are high in comparison to experiments and predictions from theory. Plant mortality and soil carbon iCO 2 responses are highly uncertain. In conclusion, a range of evidence supports a positive terrestrial carbon sink in response to iCO 2 , albeit with uncertain magnitude and strong suggestion of a role for additional agents of global change., (© 2020 The Authors New Phytologist Foundation © 2020 New Phytologist.)

The CONterminous United States (CONUS) presents a large range of climate conditions and biomes where terrestrial primary productivity and its inter-annual variability are controlled regionally by rainfall and/or temperature. Here, the response of ecosystem productivity to those climate variables was investigated across different biomes from 2010 to 2018 using three climate datasets of precipitation, air temperature or drought severity, combined with several proxies of ecosystem productivity: a remote sensing product of aboveground biomass, an net primary productivity (NPP) remote sensing product, an NPP model-based product and four gross primary productivity products. We used an asymmetry index (AI) where positive AI indicates a greater increase of ecosystem productivity in wet years compared to the decline in dry years, and negative AI indicates a greater decline of ecosystem productivity in dry years compared to the increase in wet years. We found consistent spatial patterns of AI across the CONUS for the different products, with negative asymmetries over the Great Plains and positive asymmetries over the southwestern CONUS. Shrubs and, to a lesser extent, evergreen forests show a persistent positive asymmetry, whilst (natural) grasslands appear to have transitioned from positive to negative anomalies during the last decade. The general tendency of dominant negative asymmetry response for ecosystem productivity across the CONUS appears to be influenced by the negative asymmetry of precipitation anomalies. AI was found to be a function of mean rainfall: more positive AIs were found in dry areas where plants are adapted to drought and take advantage of rainfall pulses, and more negative AIs were found in wet areas, with a threshold delineating the two regimes corresponding to a mean annual rainfall of 200-400 mm/year., (© 2020 John Wiley & Sons Ltd.)

The terrestrial carbon cycle has been strongly influenced by human-induced CO 2 increase, climate change, and land use change since the industrial revolution. These changes alter the carbon balance of ecosystems through changes in vegetation productivity and ecosystem carbon turnover time (τ eco ). Even though numerous studies have drawn an increasingly clear picture of global vegetation productivity changes, global changes in τ eco are still unknown. In this study, we analyzed the changes of τ eco between the 1860s and the 2000s and their drivers, based on theory of dynamic carbon cycle in non-steady state and process-based ecosystem model. Results indicate that τ eco has been reduced (i.e., carbon turnover has accelerated) by 13.5% from the 1860s (74 years) to the 2000s (64 years), with reductions of 1 year of carbon residence times in vegetation (r veg ) and of 9 years in soil (r soil ). Additionally, the acceleration of τ eco was examined at biome scale and grid scale. Among different driving processes, land use change and climate change were found to be the major drivers of turnover acceleration. These findings imply that carbon fixed by plant photosynthesis is being lost from ecosystems to the atmosphere more quickly over time, with important implications for the climate-carbon cycle feedbacks., (© 2020 John Wiley & Sons Ltd.)

Changes in rainfall amounts and patterns have been observed and are expected to continue in the near future with potentially significant ecological and societal consequences. Modelling vegetation responses to changes in rainfall is thus crucial to project water and carbon cycles in the future. In this study, we present the results of a new model-data intercomparison project, where we tested the ability of 10 terrestrial biosphere models to reproduce the observed sensitivity of ecosystem productivity to rainfall changes at 10 sites across the globe, in nine of which, rainfall exclusion and/or irrigation experiments had been performed. The key results are as follows: (a) Inter-model variation is generally large and model agreement varies with timescales. In severely water-limited sites, models only agree on the interannual variability of evapotranspiration and to a smaller extent on gross primary productivity. In more mesic sites, model agreement for both water and carbon fluxes is typically higher on fine (daily-monthly) timescales and reduces on longer (seasonal-annual) scales. (b) Models on average overestimate the relationship between ecosystem productivity and mean rainfall amounts across sites (in space) and have a low capacity in reproducing the temporal (interannual) sensitivity of vegetation productivity to annual rainfall at a given site, even though observation uncertainty is comparable to inter-model variability. (c) Most models reproduced the sign of the observed patterns in productivity changes in rainfall manipulation experiments but had a low capacity in reproducing the observed magnitude of productivity changes. Models better reproduced the observed productivity responses due to rainfall exclusion than addition. (d) All models attribute ecosystem productivity changes to the intensity of vegetation stress and peak leaf area, whereas the impact of the change in growing season length is negligible. The relative contribution of the peak leaf area and vegetation stress intensity was highly variable among models., (© 2020 John Wiley & Sons Ltd.)

Plants use only a fraction of their photosynthetically derived carbon for biomass production (BP). The biomass production efficiency (BPE), defined as the ratio of BP to photosynthesis, and its variation across and within vegetation types is poorly understood, which hinders our capacity to accurately estimate carbon turnover times and carbon sinks. Here, we present a new global estimation of BPE obtained by combining field measurements from 113 sites with 14 carbon cycle models. Our best estimate of global BPE is 0.41 ± 0.05, excluding cropland. The largest BPE is found in boreal forests (0.48 ± 0.06) and the lowest in tropical forests (0.40 ± 0.04). Carbon cycle models overestimate BPE, although models with carbon-nitrogen interactions tend to be more realistic. Using observation-based estimates of global photosynthesis, we quantify the global BP of non-cropland ecosystems of 41 ± 6 Pg C/year. This flux is less than net primary production as it does not contain carbon allocated to symbionts, used for exudates or volatile carbon compound emissions to the atmosphere. Our study reveals a positive bias of 24 ± 11% in the model-estimated BP (10 of 14 models). When correcting models for this bias while leaving modeled carbon turnover times unchanged, we found that the global ecosystem carbon storage change during the last century is decreased by 67% (or 58 Pg C)., (© 2019 John Wiley & Sons Ltd.)

Robust estimates of CO 2 budget, CO 2 exchanged between the atmosphere and terrestrial biosphere, are necessary to better understand the role of the terrestrial biosphere in mitigating anthropogenic CO 2 emissions. Over the past decade, this field of research has advanced through understanding of the differences and similarities of two fundamentally different approaches: "top-down" atmospheric inversions and "bottom-up" biosphere models. Since the first studies were undertaken, these approaches have shown an increasing level of agreement, but disagreements in some regions still persist, in part because they do not estimate the same quantity of atmosphere-biosphere CO 2 exchange. Here, we conducted a thorough comparison of CO 2 budgets at multiple scales and from multiple methods to assess the current state of the science in estimating CO 2 budgets. Our set of atmospheric inversions and biosphere models, which were adjusted for a consistent flux definition, showed a high level of agreement for global and hemispheric CO 2 budgets in the 2000s. Regionally, improved agreement in CO 2 budgets was notable for North America and Southeast Asia. However, large gaps between the two methods remained in East Asia and South America. In other regions, Europe, boreal Asia, Africa, South Asia, and Oceania, it was difficult to determine whether those regions act as a net sink or source because of the large spread in estimates from atmospheric inversions. These results highlight two research directions to improve the robustness of CO 2 budgets: (a) to increase representation of processes in biosphere models that could contribute to fill the budget gaps, such as forest regrowth and forest degradation; and (b) to reduce sink-source compensation between regions (dipoles) in atmospheric inversion so that their estimates become more comparable. Advancements on both research areas will increase the level of agreement between the top-down and bottom-up approaches and yield more robust knowledge of regional CO 2 budgets., (© 2019 John Wiley & Sons Ltd.)

Carbonyl sulfide (COS) has been proposed as a proxy for carbon dioxide (CO2) taken up by plants at the leaf and ecosystem scales. However, several additional production and removal processes have been identified which could complicate its use at larger scales, among which are soil uptake, dark uptake by plants, and soil and anthropogenic emissions. This study evaluates the significance of these processes at the regional scale through a top-down approach based on atmospheric COS measurements at Gif-sur-Yvette (GIF), a suburban site near Paris (France). Over a period of four and a half years, hourly measurements at 7 m above ground level were performed by gas chromatography and combined with 222Radon measurements to calculate nocturnal COS fluxes using the Radon-Tracer Method. In addition, the vertical distribution of COS was investigated at a second site, 2 km away from GIF, where a fast gas analyzer deployed on a 100 m tower for several months during winter 2015-2016 recorded mixing ratios at 3 heights (15, 60 and 100 m). COS appears to be homogeneously distributed both horizontally and vertically in the sampling area. The main finding is that the area is a persistent COS sink even during wintertime episodes of strong pollution. Nighttime net uptake rates ranged from -1.5 to -32.8 pmol m-2 s-1, with an average of -7.3 ± 4.5 pmol m-2 s-1 (n = 253). However, episodes of biogenic emissions happened each year in June-July (11.9 ± 6.2 pmol m-2 s-1, n = 24). Preliminary analyses of simulated footprints of source areas influencing the recorded COS data suggest that long-range transport of COS from anthropogenic sources located in Benelux, Eastern France and Germany occasionally impacts the Paris area during wintertime. These production and removal processes may limit the use of COS to assess regional-scale CO2 uptake in Europe by plants through inverse modeling., Competing Interests: The authors have declared that no competing interest exist.

Severe drought and extreme heat associated with the 2015-2016 El Niño event have led to large carbon emissions from the tropical vegetation to the atmosphere. With the return to normal climatic conditions in 2017, tropical forest aboveground carbon (AGC) stocks are expected to partly recover due to increased productivity, but the intensity and spatial distribution of this recovery are unknown. We used low-frequency microwave satellite data (L-VOD) to feature precise monitoring of AGC changes and show that the AGC recovery of tropical ecosystems was slow and that by the end of 2017, AGC had not reached predrought levels of 2014. From 2014 to 2017, tropical AGC stocks decreased by 1.3 1.2 1.5 Pg C due to persistent AGC losses in Africa ( - 0.9 - 1.1 - 0.8 Pg C) and America ( - 0.5 - 0.6 - 0.4 Pg C). Pantropically, drylands recovered their carbon stocks to pre-El Niño levels, but African and American humid forests did not, suggesting carryover effects from enhanced forest mortality., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

Earlier vegetation greening under climate change raises evapotranspiration and thus lowers spring soil moisture, yet the extent and magnitude of this water deficit persistence into the following summer remain elusive. We provide observational evidence that increased foliage cover over the Northern Hemisphere, during 1982-2011, triggers an additional soil moisture deficit that is further carried over into summer. Climate model simulations independently support this and attribute the driving process to be larger increases in evapotranspiration than in precipitation. This extra soil drying is projected to amplify the frequency and intensity of summer heatwaves. Most feedbacks operate locally, except for a notable teleconnection where extra moisture transpired over Europe is transported to central Siberia. Model results illustrate that this teleconnection offsets Siberian soil moisture losses from local spring greening. Our results highlight that climate change adaptation planning must account for the extra summer water and heatwave stress inherited from warming-induced earlier greening., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC).)

With accumulation of carbon cycle observations and model developments over the past decades, exploring interannual variation (IAV) of terrestrial carbon cycle offers the opportunity to better understand climate-carbon cycle relationships. However, despite growing research interest, uncertainties remain on some fundamental issues, such as the contributions of different regions, constituent fluxes and climatic factors to carbon cycle IAV. Here we overviewed the literature on carbon cycle IAV about current understanding of these issues. Observations and models of the carbon cycle unanimously show the dominance of tropical land ecosystems to the signal of global carbon cycle IAV, where tropical semiarid ecosystems contribute as much as the combination of all other tropical ecosystems. Vegetation photosynthesis contributes more than ecosystem respiration to IAV of the global net land carbon flux, but large uncertainties remain on the contribution of fires and other disturbance fluxes. Climatic variations are the major drivers to the IAV of net land carbon flux. Although debate remains on whether the dominant driver is temperature or moisture variability, their interaction,that is, the dependence of carbon cycle sensitivity to temperature on moisture conditions, is emerging as key regulators of the carbon cycle IAV. On timescales from the interannual to the centennial, global carbon cycle variability will be increasingly contributed by northern land ecosystems and oceans. Therefore, both improving Earth system models (ESMs) with the progressive understanding on the fast processes manifested at interannual timescale and expanding carbon cycle observations at broader spatial and longer temporal scales are critical to better prediction on evolution of the carbon-climate system., (© 2019 John Wiley & Sons Ltd.)

Plant phenology-the timing of cyclic or recurrent biological events in plants-offers insight into the ecology, evolution, and seasonality of plant-mediated ecosystem processes. Traditionally studied phenologies are readily apparent, such as flowering events, germination timing, and season-initiating budbreak. However, a broad range of phenologies that are fundamental to the ecology and evolution of plants, and to global biogeochemical cycles and climate change predictions, have been neglected because they are "cryptic"-that is, hidden from view (e.g., root production) or difficult to distinguish and interpret based on common measurements at typical scales of examination (e.g., leaf turnover in evergreen forests). We illustrate how capturing cryptic phenology can advance scientific understanding with two case studies: wood phenology in a deciduous forest of the northeastern USA and leaf phenology in tropical evergreen forests of Amazonia. Drawing on these case studies and other literature, we argue that conceptualizing and characterizing cryptic plant phenology is needed for understanding and accurate prediction at many scales from organisms to ecosystems. We recommend avenues of empirical and modeling research to accelerate discovery of cryptic phenological patterns, to understand their causes and consequences, and to represent these processes in terrestrial biosphere models., (© 2019 John Wiley & Sons Ltd.)

Direct quantification of terrestrial biosphere responses to global change is crucial for projections of future climate change in Earth system models. Here, we synthesized ecosystem carbon-cycling data from 1,119 experiments performed over the past four decades concerning changes in temperature, precipitation, CO 2 and nitrogen across major terrestrial vegetation types of the world. Most experiments manipulated single rather than multiple global change drivers in temperate ecosystems of the USA, Europe and China. The magnitudes of warming and elevated CO 2 treatments were consistent with the ranges of future projections, whereas those of precipitation changes and nitrogen inputs often exceeded the projected ranges. Increases in global change drivers consistently accelerated, but decreased precipitation slowed down carbon-cycle processes. Nonlinear (including synergistic and antagonistic) effects among global change drivers were rare. Belowground carbon allocation responded negatively to increased precipitation and nitrogen addition and positively to decreased precipitation and elevated CO 2 . The sensitivities of carbon variables to multiple global change drivers depended on the background climate and ecosystem condition, suggesting that Earth system models should be evaluated using site-specific conditions for best uses of this large dataset. Together, this synthesis underscores an urgent need to explore the interactions among multiple global change drivers in underrepresented regions such as semi-arid ecosystems, forests in the tropics and subtropics, and Arctic tundra when forecasting future terrestrial carbon-climate feedback.

The river-floodplain network plays an important role in the carbon (C) cycle of the Amazon basin, as it transports and processes a significant fraction of the C fixed by terrestrial vegetation, most of which evades as CO 2 from rivers and floodplains back to the atmosphere. There is empirical evidence that exceptionally dry or wet years have an impact on the net C balance in the Amazon. While seasonal and interannual variations in hydrology have a direct impact on the amounts of C transferred through the river-floodplain system, it is not known how far the variation of these fluxes affects the overall Amazon C balance. Here, we introduce a new wetland forcing file for the ORCHILEAK model, which improves the representation of floodplain dynamics and allows us to closely reproduce data-driven estimates of net C exports through the river-floodplain network. Based on this new wetland forcing and two climate forcing datasets, we show that across the Amazon, the percentage of net primary productivity lost to the river-floodplain system is highly variable at the interannual timescale, and wet years fuel aquatic CO 2 evasion. However, at the same time overall net ecosystem productivity (NEP) and C sequestration are highest during wet years, partly due to reduced decomposition rates in water-logged floodplain soils. It is years with the lowest discharge and floodplain inundation, often associated with El Nino events, that have the lowest NEP and the highest total (terrestrial plus aquatic) CO 2 emissions back to atmosphere. Furthermore, we find that aquatic C fluxes display greater variation than terrestrial C fluxes, and that this variation significantly dampens the interannual variability in NEP of the Amazon basin. These results call for a more integrative view of the C fluxes through the vegetation-soil-river-floodplain continuum, which directly places aquatic C fluxes into the overall C budget of the Amazon basin., (© 2019 John Wiley & Sons Ltd.)

The global distribution of the optimum air temperature for ecosystem-level gross primary productivity ([Formula: see text]) is poorly understood, despite its importance for ecosystem carbon uptake under future warming. We provide empirical evidence for the existence of such an optimum, using measurements of in situ eddy covariance and satellite-derived proxies, and report its global distribution. [Formula: see text] is consistently lower than the physiological optimum temperature of leaf-level photosynthetic capacity, which typically exceeds 30 °C. The global average [Formula: see text] is estimated to be 23 ± 6 °C, with warmer regions having higher [Formula: see text] values than colder regions. In tropical forests in particular, [Formula: see text] is close to growing-season air temperature and is projected to fall below it under all scenarios of future climate, suggesting a limited safe operating space for these ecosystems under future warming.

Every living creature on Earth is made of atoms of the various bioelements that are harnessed in the construction of molecules, tissues, organisms, and communities, as we know them. Organisms need these bioelements in specific quantities and proportions to survive and grow. Distinct species have different functions and life strategies, and have therefore developed distinct structures and adopted a certain combination of metabolic and physiological processes. Each species is thus also expected to have different requirements for each bioelement. We therefore propose that a "biogeochemical niche" can be associated with the classical ecological niche of each species. We show from field data examples that a biogeochemical niche is characterized by a particular elementome defined as the content of all (or at least most) bioelements. The differences in elementome among species are a function of taxonomy and phylogenetic distance, sympatry (the bioelemental compositions should differ more among coexisting than among non-coexisting species to avoid competitive pressure), and homeostasis with a continuum between high homeostasis/low plasticity and low homeostasis/high plasticity. This proposed biogeochemical niche hypothesis has the advantage relative to other associated theoretical niche hypotheses that it can be easily characterized by actual quantification of a measurable trait: the elementome of a given organism or a community, being potentially applicable across taxa and habitats. The changes in bioelemental availability can determine genotypic selection and therefore have a feedback on ecosystem function and organization, and, at the end, become another driving factor of the evolution of life and the environment., (© 2019 by the Ecological Society of America.)

The glacierized Tien Shan - Pamir - Karakoram mountain complex supplies water to about 42 million people. Yet, the knowledge about future glacial runoff in response to future climate is limited. Here, we address this issue using a hydrological model, that includes the three components of glacial runoff: ice melt, snowmelt and the runoff of rainfall over ice. The model is forced by climate projections of the CMIP5 models. We find that the three components exhibit different long-term trajectories, sometimes opposite in sign to the long-term trend in glacier impacts. For the eastern slope basins, streamflow is projected to increase by 28% (ranging from 9 to 44%, from climate model variation (CMV)) by the late 21 st century, under the representative concentration pathway, RCP8.5. Ice melt contributes 39% (25 to 65%, CMV) of the total streamflow increase. However, streamflow from the western slopes is projected to decrease by 5% (-24 to 16%, CMV), due to the smaller contribution of ice melt, less precipitation and higher evapotranspiration. Increasing water supply from the eastern slopes suggests more water availability for currently degraded downstream ecosystems in the Xinjiang province of China, while the likely decreasing streamflow in Central Asian rivers on the western slopes indicates new regulations will be needed.

Evaluating the response of the land carbon sink to the anomalies in temperature and drought imposed by El Niño events provides insights into the present-day carbon cycle and its climate-driven variability. It is also a necessary step to build confidence in terrestrial ecosystems models' response to the warming and drying stresses expected in the future over many continents, and particularly in the tropics. Here we present an in-depth analysis of the response of the terrestrial carbon cycle to the 2015/2016 El Niño that imposed extreme warming and dry conditions in the tropics and other sensitive regions. First, we provide a synthesis of the spatio-temporal evolution of anomalies in net land-atmosphere CO 2 fluxes estimated by two in situ measurements based on atmospheric inversions and 16 land-surface models (LSMs) from TRENDYv6. Simulated changes in ecosystem productivity, decomposition rates and fire emissions are also investigated. Inversions and LSMs generally agree on the decrease and subsequent recovery of the land sink in response to the onset, peak and demise of El Niño conditions and point to the decreased strength of the land carbon sink: by 0.4-0.7 PgC yr -1 (inversions) and by 1.0 PgC yr -1 (LSMs) during 2015/2016. LSM simulations indicate that a decrease in productivity, rather than increase in respiration, dominated the net biome productivity anomalies in response to ENSO throughout the tropics, mainly associated with prolonged drought conditions.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'., (© 2018 The Authors.)

Understanding ecosystem dynamics and predicting directional changes in ecosystem in response to global changes are ongoing challenges in ecology. Here we present a framework that links productivity dynamics and ecosystem state transitions based on a spatially continuous dataset of aboveground net primary productivity (ANPP) from the temperate grassland of China. Across a regional precipitation gradient, we quantified spatial patterns in ANPP dynamics (variability, asymmetry and sensitivity to rainfall) and related these to transitions from desert to semi-arid to mesic steppe. We show that these three indices of ANPP dynamics displayed distinct spatial patterns, with peaks signalling transitions between grassland types. Thus, monitoring shifts in ANPP dynamics has the potential for predicting ecosystem state transitions in the future. Current ecosystem models fail to capture these dynamics, highlighting the need to incorporate more nuanced ecological controls of productivity in models to forecast future ecosystem shifts., (© 2018 John Wiley & Sons Ltd/CNRS.)