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ABSTRACTAccurate evaluation of terrestrial carbon balance is essential for designing climate change mitigation policies, and capabilities of remote sensing techniques in monitoring carbon fluxes are widely recognized for their great contributions to regional and global carbon budget accounting. In this review, we synthesized satellite-based data and methodologies to estimate the main flux components of terrestrial carbon balance and their uncertainties over the past two decades. The global gross primary production (GPP) during the period 2001–2022 is 134 ± 14 PgC yr−1, and nearly half of them occurs in tropical forest regions such as South America and Africa. Less than 2% of global GPP is converted into a net carbon sink of 2.28 ± 1.12 PgC yr−1 using satellite-based atmospheric inversion during 2015–2020, and this sink is comparable to the stock change-based estimate (2.49 PgC yr−1) but twice as large as model-based estimate (1.08 ± 0.78 PgC yr−1). By decomposing satellite-derived net carbon balance into different terms including satellite-derived carbon emissions from land-use change and wildfires (3.55 PgC yr−1), we inferred that ~ 43% of global GPP would be respired through soil microbes (57.1 PgC yr−1), but which is higher than the previous bottom-up estimate (39–46 PgC yr−1). We then propose that an accurate remote sensing of terrestrial carbon balance requires to enhance representations of photosynthetic responses to rising CO2 and disturbances, develop satellite-constrained belowground carbon dynamics and separate natural fluxes from anthropogenic CO2 emissions, by integrating multi-source satellite sensors in orbit, revolutionized remote sensing capabilities with focused field campaigns in data-scarce regions.

Abstract Forest carbon sequestration capacity in China remains uncertain due to underrepresented tree demographic dynamics and overlooked of harvest impacts. In this study, we employ a process-based biogeochemical model to make projections by using national forest inventories, covering approximately 415,000 permanent plots, revealing an expansion in biomass carbon stock by 13.6 ± 1.5 Pg C from 2020 to 2100, with additional sink through augmentation of wood product pool (0.6-2.0 Pg C) and spatiotemporal optimization of forest management (2.3 ± 0.03 Pg C). We find that statistical model might cause large bias in long-term projection due to underrepresentation or neglect of wood harvest and forest demographic changes. Remarkably, disregarding the repercussions of harvesting on forest age can result in a premature shift in the timing of the carbon sink peak by 1–3 decades. Our findings emphasize the pressing necessity for the swift implementation of optimal forest management strategies for carbon sequestration enhancement.

Abstract Contemporary fire-human-climate nexus has led to a surge in publication numbers across diverse research disciplines beyond the capability of experts from a single discipline. Here, we employed a generalized large language model to capture the dynamics of wildfire research published between 1980 and 2022. More than 60,000 peer-reviewed papers were scanned and analyzed. Through integrating geographical metadata extracted by the artificial intelligence and satellite wildfire datasets, we found large disparities in geographic patterns and research themes. The hottest spot of wildfire research is western United States, accounting for 15% of publications but only 0.5% of global burnt area, while the world’s most widely burnt region, like Siberia and Africa are largely underrepresented by contemporary publications. Similar discrepancies are found between the fuel of wildfire and its ignition and climatic drivers, between socioeconomic development and wildfire mitigation, raising concerns on sustainable wildfire managements and calling for further artificial intelligence-aided transdisciplinary collaborations.

Abstract The Tibetan grassland ecosystems possess significant carbon sink potential and have room for improved carbon sequestration processes. There is a need to uncover more ambitious and coherent solutions (e.g., Nature-based Solutions) to increase carbon sequestration. Here, we investigated the rationale and urgency behind the implementation of Nature-based Solutions on sequestering carbon using literature review and meta-analysis. We also project the changes in terrestrial carbon sink of Tibetan Plateau grassland ecosystems using model simulations with different future emissions scenario. The results show that the Nature-based Solution projects are expected to increase the carbon sink of Tibetan Plateau grassland ecosystems by 15 to 21 tetragrams of carbon by 2060. We defined a conceptual framework of Nature-based Solutions that integrates initiatives for the restoration of degraded grasslands and carbon sequestration. Our framework consists of four stages: theory, identification, practice, and goal. Traditional Tibetan knowledge plays an important role in reframing the proposed Nature-based Solutions framework. We also apply this framework to optimize ecological restoration techniques and projects and to evaluate the annual changes in the carbon sink under different socioeconomic pathway scenarios.

Abstract The soil carbon-climate feedback is currently the least constrained component of global warming projections, and the major source of uncertainties stems from a poor understanding of soil carbon turnover processes. Here, we assemble data from long-term temperature-controlled soil incubation studies to show that the arctic and boreal region has the shortest intrinsic soil carbon turnover time while tropical forests have the longest one, and current Earth system models overestimate intrinsic turnover time by 30 percent across active, slow and passive carbon pools. Our constraint suggests that the global soils will switch from carbon sink to source, with a loss of 0.22–0.53 petagrams of carbon per year until the end of this century from strong mitigation to worst emission scenarios, suggesting that global soils will provide a strong positive carbon feedback on warming. Such a reversal of global soil carbon balance would lead to a reduction of 66% and 15% in the current estimated remaining carbon budget for limiting global warming well below 1.5 °C and 2 °C, respectively, rendering climate mitigation much more difficult.

Abstract Accurate estimation and attribution of large‐scale changes in plant transpiration are critical to understand the impacts of vegetation dynamics on the terrestrial hydrological cycle. However, these aspects remain poorly understood due to the limited reliability of global transpiration products. Here we compile data from 101 site‐based transpiration measurements across the globe and use them to constrain three biophysically based data‐driven transpiration products. The constrained transpiration reveals a prominent increasing trend of 0.61–0.79 mm yr−2 during 1980–2021, which is overestimated by 8%–32% in unconstrained transpiration. We further find that the global transpiration increase is mainly driven by leaf area index increase (40%), followed by climate change (19%), though offset partly by CO2‐induced stomatal closure (−38%) and land use and cover change (−3%). Our refined estimates indicate a less substantial increase of global transpiration than previously thought, improving the understanding of transpiration change impact on global hydrological cycle.

Abstract Intense grazing may lead to grassland degradation on the Qinghai-Tibetan Plateau, but it is difficult to predict where this will occur and to quantify it. Based on a process-based ecosystem model, we define a productivity-based stocking rate threshold that induces extreme grassland degradation to assess whether and where the current grazing activity in the region is sustainable. We find that the current stocking rate is below the threshold in ~80% of grassland areas, but in 55% of these grasslands the stocking rate exceeds half the threshold. According to our model projections, positive effects of climate change including elevated CO2 can partly offset negative effects of grazing across nearly 70% of grasslands on the Plateau, but only in areas below the stocking rate threshold. Our analysis suggests that stocking rate that does not exceed 60% (within 50% to 70%) of the threshold may balance human demands with grassland protection in the face of climate change.

Abstract It is well known that global warming increases the atmospheric water vapor content, which results in substantial changes in the hydrological cycle. Using five observational data sets, the results show that an increasing trend of near‐surface water vapor pressure (AVP) over land and ocean was significant from 1975 to 1998, while such an increasing trend in AVP subsequently weakened from 1999 to 2019. This phenomenon is associated with decreased oceanic evaporation and land surface evapotranspiration in response to recent climate variations. One consequence of such a phenomenon is a large increase in near‐surface vapor pressure deficit (VPD), which in turn increases atmospheric demand for water vapor and thus aridity and drought over land. This result emphasizes the importance of water vapor change under global warming.

Abstract Soil moisture–atmosphere coupling (SA) amplifies greenhouse gas-driven global warming via changes in surface heat balance. The Scenario Model Intercomparison Project projects an acceleration in SA-driven warming due to the ‘warmer climate – drier soil’ feedback, which continuously warms the globe and thereby exerts an acceleration effect on global warming. The projection shows that SA-driven warming exceeds 0.5 °C over extratropical landmasses by the end of the 21st Century. The likelihood of extreme high temperatures will additionally increase by about 10% over the entire globe (excluding Antarctica) and more than 30% over large parts of North America and Europe under the high-emission scenario. This demonstrates the high sensitivity of SA to climate change, in which SA can exceed the natural range of climate variability and play a non-linear warming component role on the globe.

Abstract Forestation is regarded as an effective strategy for increasing terrestrial carbon sequestration. However, its carbon sink potential remains uncertain due to the scarcity of large-scale sampling data and limited knowledge of the linkage between plant and soil C dynamics. Here, we conduct a large-scale survey of 163 control plots and 614 forested plots involving 25304 trees and 11700 soil samples in northern China to fill this knowledge gap. We find that forestation in northern China contributes a significant carbon sink (913.19 ± 47.58 Tg C), 74% of which is stored in biomass and 26% in soil organic carbon. Further analysis reveals that the biomass carbon sink increases initially but then decreases as soil nitrogen increases, while soil organic carbon significantly decreases in nitrogen-rich soils. These results highlight the importance of incorporating plant and soil interactions, modulated by nitrogen supply in the calculation and modelling of current and future carbon sink potential.

Abstract Climate change strongly impact vegetation phenology, with considerable potential to alter land-atmosphere carbon dioxide exchange and terrestrial carbon cycle. In contrast to well-studied spring leaf-out, the timing and magnitude of autumn senescence remains poorly understood. Here, we use monthly decreases in Normalized Difference Vegetation Index satellite retrievals and their trends to surrogate the speed of autumn senescence during 1982–2018 in the Northern Hemisphere (>30°N). We find that climate warming accelerated senescence in July, but this influence usually reversed in later summer and early autumn. Interestingly, summer greening causes canopy senescence to appear later compared to an advancing trend after eliminating the greening effect. This finding suggests that summer canopy greening may counteract the intrinsic changes in autumnal leaf senescence. Our analysis of autumn vegetation behavior provides reliable guidance for developing and parameterizing land surface models that contain an interactive dynamic vegetation module for placement in coupled Earth System Models.

Grassland is one of the largest terrestrial biomes, providing critical ecosystem services such as food production, biodiversity conservation, and climate change mitigation. Global climate change and land-use intensification have been causing grassland degradation and desertification worldwide. As one of the primary medium for ecosystem energy flow and biogeochemical cycling, grassland carbon (C) cycling is the most fundamental process for maintaining ecosystem services. In this review, we first summarize recent advances in our understanding of the mechanisms underpinning spatial and temporal patterns of the grassland C cycle, discuss the importance of grasslands in regulating inter- and intra-annual variations in global C fluxes, and explore the previously unappreciated complexity in abiotic processes controlling the grassland C balance, including soil inorganic C accumulation, photochemical and thermal degradation, and wind erosion. We also discuss how climate and land-use changes could alter the grassland C balance by modifying the water budget, nutrient cycling and additional plant and soil processes. Further, we examine why and how increasing aridity and improper land use may induce significant losses in grassland C stocks. Finally, we identify several priorities for future grassland C research, including improving understanding of abiotic processes in the grassland C cycle, strengthening monitoring of grassland C dynamics by integrating ground inventory, flux monitoring, and modern remote sensing techniques, and selecting appropriate plant species combinations with suitable traits and strong resistance to climate fluctuations, which would help design sustainable grassland restoration strategies in a changing climate.

The rate, frequency and extent of forest disturbances decreased in China over 1986–2020 probably due to forest protection policies, but while they intensified in the southeast, they weakened in the northeast, according to 30 m resolution Landsat satellite data

Impacts of Tibetan Plateau darkening remain unclear. Here authors show that darkening under the RCP8.5 scenario will increase South Asian monsoon precipitation and the “South Flood-North Drought” pattern over East Asia, while lead to local glacier loss.

Abstract Soil conservation is of global importance, as accelerated soil erosion by human activity is a primary threat to ecosystem viability. However, the significance and role of soil conservation in reshaping landscape carbon (C) accounting has not been comprehensively integrated in the terrestrial C sink. Here, we present the first integrated assessment of the modified terrestrial C sink and aquatic C transport due to soil conservation for the semiarid Chinese Loess Plateau (CLP), the world's most vulnerable region to soil erosion. We show a surprisingly low terrestrial‐aquatic C transfer that offset the terrestrial net ecosystem productivity by only 7.5%, which we attribute to the effective implementation of soil conservation practices. Despite the highest soil erosion, the semiarid CLP acts as effective C sink at 43.2 ± 22.6 g C m−2 year−1, which is comparable to temperate forest in absorbing atmospheric CO2. Moreover, C burial in reservoirs has created an additional anthropogenic C sink of 2.9 ± 1.1 g C m−2 year−1. Our findings indicate that effective soil conservation can significantly increase landscape C sequestration capacity. The co‐benefits of soil conservation in erosion control and C sequestration have important implications for policy makers in other regions undergoing increasing erosion intensity to pursue environmental sustainability.

Historical latitudinal and seasonal trends in global soil moisture aridity are attributable to greenhouse gas emissions.

Climate warming has substantially advanced the timing of spring leaf-out of woody species at middle and high latitudes, albeit with large differences. Insights in the spatial variation of this climate warming response may therefore help to constrain future trends in leaf-out and its impact on energy, water and carbon balances at global scales. In this study, we used in situ phenology observations of 38 species from 2067 study sites, distributed across the northern hemisphere in China, Europe and the United States, to investigate the latitudinal patterns of spring leaf-out and its sensitivity (ST, advance of leaf-out dates per degree of warming) and correlation (RT, partial correlation coefficient) to temperature during the period 1980–2016. Across all species and sites, we found that ST decreased significantly by 0.15 ± 0.02 d °C−1 °N−1, and RT increased by 0.02 ± 0.001 °N−1 (both at P < 0.001). The latitudinal patterns in RT and ST were explained by the differences in requirements of chilling and thermal forcing that evolved to maximize tree fitness under local climate, particularly climate predictability and summed precipitation during the pre-leaf-out season. Our results thus showed complicated spatial differences in leaf-out responses to ongoing climate warming and indicated that spatial differences in the interactions among environmental cues need to be embedded into large-scale phenology models to improve the simulation accuracy.

The impact of land-use and cover-change (LUCC) on ecosystem carbon stock in China is poorly known due to large biases in existing databases. Here the authors develop a new LUCC database with corrected false signals and reveal that forest expansion is the dominant driver of China’s recent carbon sink.

Changes in vegetation responses to precipitation may be hydroclimate dependent. Here the authors reveal contrasting trends of vegetation sensitivity to precipitation in drylands vs. wetter ecosystems over the last 4 decades and identify increased CO2 as a major contributing factor.

The seasonal greening of Northern Hemisphere ecosystems due to extended growing periods and enhanced photosynthetic activity is, via experiments, shown to modify near-surface warming by perturbing land-atmosphere energy exchanges.

Preserving Tibet’s unique history and cultural heritage relies on the sustainability of the Tibetan croplands, which are characterized by highland barley, the only cereal crop cultivated over 4000 m above sea level. Yet it is unknown how these croplands will respond to climate change. Here, using yield statistics from 1985 to 2015, we found that the impact of temperature anomalies on the Tibetan crop yield shifted from nonsignificant (P > 0.10) in the 1980s and 1990s to significantly negative (P

Increasing atmospheric carbon dioxide levels induce vegetation physiological responses that amplify local warming through reductions in evapotranspiration according to factorial analyses of radiative and physiological effects in Earth system models.

Changing precipitation pattern has been suggested to expand tropical dry seasons. Here, the authors show that this lengthening can be even more severe when accounting for the simultaneous rise of ecosystem water demand in a warmer climate.

Abstract Recent forest fires potentially intensify flood hazards. However, forest fire amplification of floods is not well understood at a large scale due to the complex compound impacts of forest fires and climate variability, while available small‐scale cases may not represent regional changes. Here, we show that the 2019–2020 mega forest fires in southeast Australia, with unprecedented burned areas, significantly (p

The dominant driver of variations in global land carbon sink remains unclear. Here the authors show that the seasonal compensation of temperature effects on land carbon sink in the Northern Hemisphere could induce a global water dominance.

Research findings concerning the main processes influencing water resources differ substantially, and so the topic remains controversial. Recent studies indicate that the changes in water yield, expressed through the n-parameter of Budyko framework, are associated with vegetation coverage changes. Here, we use runoff measurements and outputs from 13 dynamic global vegetation models, to investigate the underlying drivers of the n-parameter changes. Unlike previous studies, we instead find that climate change is the primary driver of adjustments on water resources. Changing climatic characteristics, particularly the intensity and seasonality of rainfall, modulates the runoff generation process. Indirect effects of climate change occur through altering vegetation properties, which in turn also impact river flow. We also find that in the arid and sparse vegetation regions, water yield is more sensitive to changes in n-parameter. Thus, the Budyko framework provides a reliable parameter-sparse representation of runoff changes, and reveals that terrestrial water cycle is changing substantially under climate change. This climate forcing requires on-going investigation to generate more refined and reliable projections of future water availability.

Ecosystem is a fundamental organizational unit of the biosphere in which biological communities interact with their non-biological environment through energy flows and material cycles. Ecosystem science is the study of patterns, processes, and services of ecosystems. Since the 1990s, rising concerns regarding global climate change, biodiversity loss, ecosystem degradation, and sustainability of the human-dominated biosphere have stimulated the growth of ecosystem science, which is expected to provide systematic solutions to many of these major issues facing human societies. This paper provides a comprehensive review of the current progress in ecosystem science and identifies some key research challenges facing this discipline. We demonstrate that a key feature of the current progress in ecosystem science is its evolution from primarily theoretical explorations toward more systematic, integrative and application-oriented studies. Specifically, five major changes in the discipline over the past several decades can be identified. These include: (1) the expansion of the primary goal from understanding nature to include human activities; (2) the broadening of the research focus from single ecosystem types to macro-ecosystems comprising multiple regional ecosystems; (3) the shifting of research methods from small-scale observations and experiments to large-scale observations, network experiments, and model simulations; (4) the increasing attention to comprehensive integration of ecosystem components, processes, and scales; and (5) the shifting from a primarily biology-oriented focus to an integrated multi-disciplinary scientific field. While ecosystem science still faces many challenges in the future, these directional changes, along with the rapidly enriched research tools and data acquisition capabilities, lay a promising ground for the discipline’s future as a fundamental scientific basis for solving many environmental challenges facing human societies.

How to curb climate change is uncertain, in part because determination of allowable emissions depends on models with low accuracy. Here the authors re-analyze climate-carbon feedbacks and find that CO2 emissions could be 9 ± 7% higher and still meet Paris Agreement goals.

Plant phenology is a key parameter for accurately modeling ecosystem dynamics. Limited by scarce ground observations and benefiting from the rapid growth of satellite-based Earth observations, satellite data have been widely used for broad-scale phenology studies. Commonly used reflectance vegetation indices represent the emergence and senescence of photosynthetic structures (leaves), but not necessarily that of photosynthetic activities. Leveraging data of the recently emerging solar-induced chlorophyll fluorescence (SIF) that is directly related to photosynthesis, and the traditional MODIS Normalized Difference Vegetation Index (NDVI), we investigated the similarities and differences on the start and end of the growing season (SOS and EOS, respectively) of the Tibetan Plateau. We found similar spatiotemporal patterns in SIF-based SOS (SOSSIF) and NDVI-based SOS (SOSNDVI). These spatial patterns were mainly driven by temperature in the east and by precipitation in the west. Yet the two satellite products produced different spatial patterns in EOS, likely due to their different climate dependencies. Our work demonstrates the value of big Earth data for discovering broad-scale spatiotemporal patterns, especially on regions with scarce field data. This study provides insights into extending the definition of phenology and fosters a deeper understanding of ecosystem dynamics from big data.

Abstract Forest biomass is an important component of terrestrial carbon pools. However, how climate, biodiversity, and structural attributes co‐determine spatiotemporal variation in forest biomass remains not well known. We aimed to shed light on these drivers of forest biomass by measuring diversity and structural attributes of tree species in 400‐m2 plots located every 100 m along a 4200‐m elevational gradient in the eastern Himalayas. We applied structural equation models to test how climate, species richness, structural attributes, and their interactions influence forest biomass. Importantly, species richness was a stronger driver of biomass than environmental and structural attributes such as annual air temperature or stem density. Integrating the availability of energy and the demand for water, potential evapotranspiration was more strongly correlated with biomass than water availability, likely due to the strong influence of the Indian summer monsoon. Thus, interactions between climate and tree community composition ultimately control how much carbon is stored in woody biomass across bioclimatic gradients. This fundamental understanding will support predictive efforts of the forest carbon sink in this hydroclimatically important region and help preserving regional forests as a potent natural solution for climate change mitigation.

There are big uncertainties in the contribution of irrigation to crop yields. Here, the authors use Bayesian model averaging to combine statistical and process-based models and quantify the contribution of irrigation for wheat and maize yields, finding that irrigation alone cannot close yield gaps for a large fraction of global rainfed agriculture.

The future of terrestrial systems is influenced by their past, but this carryover effect is rarely quantified. Here, the authors provide the first quantitative evidence that a greener spring begets a greener summer and autumn, and that this carryover effect is even stronger than climate drivers.

Satellite-based land surface temperature (Ts) with continuous global coverage is increasingly used as a complementary measure for air temperature (Ta), yet whether they observe similar temporal trends remains unknown. Here, we systematically analyzed the trend of the difference between satellite-based Ts and station-based Ta (Ts–Ta) over 2003–2022. We found the global land warming rate inffered from Ts was on average 42.6% slower than that from Ta (Ts–Ta trend: −0.011 °C yr ^−1 , p = 0.06) during daytime of summer. This slower Ts-based warming was attributed to recent Earth greening, which effectively cooled canopy surface through enhancing evapotranspiration and turbulent heat transfer. However, Ts showed faster warming than Ta during summer nighttime (0.015 °C yr ^−1 , p < 0.01), winter daytime (0.0069 °C yr ^−1 , p = 0.08) and winter nighttime (0.0042 °C yr ^−1 , p = 0.16), when vegetation activity is limited by temperature and solar radiation. Our results indicate potential biases in assessments of atmospheric warming and the vegetation-air temperature feedbacks using satellite-observed surface temperature proxies.

Monsoon systems have strong impacts on precipitation and food security over large areas of the world. Here, the authors show that plant responses to rising CO2 concentrations in the atmosphere play a key role in modulating seasonal rainfall and water resources over global land monsoon regions.

Fire is a major type of disturbance that has important influences on ecosystem dynamics and carbon cycles. Yet our understanding of ecosystem fires and their carbon cycle consequences is still limited, largely due to the difficulty of large-scale fire monitoring and the complex interactions between fire, vegetation, climate, and anthropogenic factors. Here, using data from satellite-derived fire observations and ecosystem model simulations, we performed a comprehensive investigation of the spatial and temporal dynamics of China's ecosystem fire disturbances and their carbon emissions over the past two decades (1997–2016). Satellite-derived results showed that on average about 3.47 - 4.53 × 104 km2 of the land was burned annually during the past two decades, among which annual burned forest area was about 0.81 - 1.25 × 104 km2, accounting for 0.33-0.51% of the forest area in China. Biomass burning emitted about 23.02 TgC per year. Compared to satellite products, simulations from the Energy Exascale Earth System Land Model (ELM) strongly overestimated China's burned area and fire-induced carbon emissions. Annual burned area and fire-induced carbon emissions were high for boreal forest in Northeast China's Daxing'anling region and subtropical dry forest in South Yunnan, as revealed by both the satellite product and the model simulations. Our results suggest that climate and anthropogenic factors play critical roles in controlling the spatial and seasonal distribution of China's ecosystem fire disturbances. Our findings highlight the importance of multiple complementary approaches in assessing ecosystem fire disturbance and its carbon consequences. Further studies are required to improve the methods of observing and modelling China's ecosystem fire disturbances, which will provide valuable information for fire management and ecosystem sustainability in an era when both human activities and the natural environment are rapidly changing.

Summary: Relationships among productivity, leaf phenology, and seasonal variation in moisture and light availability are poorly understood for evergreen broadleaved tropical/subtropical forests, which contribute 25% of terrestrial productivity. On the one hand, as moisture availability declines, trees shed leaves to reduce transpiration and the risk of hydraulic failure. On the other hand, increases in light availability promote the replacement of senescent leaves to increase productivity. Here, we provide a comprehensive framework that relates the seasonality of climate, leaf abscission, and leaf productivity across the evergreen broadleaved tropical/subtropical forest biome. The seasonal correlation between rainfall and light availability varies from strongly negative to strongly positive across the tropics and maps onto the seasonal correlation between litterfall mass and productivity for 68 forests. Where rainfall and light covary positively, litterfall and productivity also covary positively and are always greater in the wetter sunnier season. Where rainfall and light covary negatively, litterfall and productivity are always greater in the drier and sunnier season if moisture supplies remain adequate; otherwise productivity is smaller in the drier sunnier season. This framework will improve the representation of tropical/subtropical forests in Earth system models and suggests how phenology and productivity will change as climate change alters the seasonality of cloud cover and rainfall across tropical/subtropical forests. Public summary: • Three climate-phenology regimes are identified across tropical and subtropical forest biomes • Where light and water limit plant in dry season, litterfall and productivity peak in sunny wet season • Where light or water alternately limits plant, productivity peaks in wet season with low litterfall • Where water does not limit plant, litterfall and productivity peak in sunny dry season

It has been long established that the terrestrial vegetation in spring has stronger photosynthetic capability than in autumn. However, this study challenges this consensus by comparing photosynthetic capability of terrestrial vegetation between the spring and autumn seasons based on measurements of 100 in situ eddy covariance towers over global extratropical ecosystems. At the majority of these sites, photosynthetic capability, indicated by light use efficiency (LUE) and apparent quantum efficiency, is significantly higher in autumn than in spring, due to lower atmosphere vapor pressure deficit (VPD) at the same air temperature. Seasonal VPD differences also substantially explain the interannual variability of the differences in photosynthetic capability between spring and autumn. We further reveal that VPD in autumn is significantly lower than in spring over 74.14% of extratropical areas, based on a global climate dataset. In contrast, LUE derived from a data-driven vegetation production dataset is significantly higher in autumn in over 61.02% of extratropical vegetated areas. Six Earth system models consistently projected continuous larger VPD values in spring compared with autumn, which implies that the impacts on vegetation growth will long exist and should be adequately considered when assessing the seasonal responses of terrestrial ecosystems to future climate conditions. Public summary: • Autumn VPD is lower than spring VPD at the same air temperature over majority of the extratropical vegetated land • Photosynthetic capability is significantly higher in autumn than in spring due to lower VPD • Earth System Models projected continuous larger VPD values in spring as against autumn

There was extensive degradation during the warm middle Holocene and permafrost area was reduced substantially. Here the authors synthesize data across the Tibetan permafrost region and find that paleoclimate is more important than modern climate in shaping current permafrost carbon distribution, and its importance increases with soil depth.

Abstract Quantifying soil organic carbon (SOC) changes is a fundamental issue in ecology and sustainable agriculture. However, the algorithm‐derived biases in comparing SOC status have not been fully addressed. Although the methods based on equivalent soil mass (ESM) and mineral‐matter mass (EMMM) reduced biases of the conventional methods based on equivalent soil volume (ESV), they face challenges in ensuring both data comparability and accuracy of SOC estimation due to unequal basis for comparison and using unconserved reference systems. We introduce the basal mineral‐matter reference systems (soils at time zero with natural porosity but no organic matter) and develop an approach based on equivalent mineral‐matter volume (EMMV). To show the temporal bias, SOC change rates were recalculated with the ESV method and modified methods that referenced to soils at time t1 (ESM, EMMM, and EMMV‐t1) or referenced to soils at time zero (EMMV‐t0) using two datasets with contrasting SOC status. To show the spatial bias, the ESV‐ and EMMV‐t0‐derived SOC stocks were compared using datasets from six sites across biomes. We found that, in the relatively C‐rich forests, SOC accumulation rates derived from the modified methods that referenced to t1 soils and from the EMMV‐t0 method were 5.7%–13.6% and 20.6% higher than that calculated by the ESV method, respectively. Nevertheless, in the C‐poor lands, no significant algorithmic biases of SOC estimation were observed. Finally, both the SOC stock discrepancies (ESV vs. EMMV‐t0) and the proportions of this unaccounted SOC were large and site‐dependent. These results suggest that although the modified methods that referenced to t1 soils could reduce the biases derived from soil volume changes, they may not properly quantify SOC changes due to using unconserved reference systems. The EMMV‐t0 method provides an approach to address the two problems and is potentially useful since it enables SOC comparability and integrating SOC datasets.

Climate change may lead to changes in elevational patterns of vegetation activitities. Here, the authors analyze global remotely sensing data collected during 1982–2015 to investigate the spatio-temporal dynamics of the elevational gradient in vegetation activities.

Abstract The terrestrial net biome production (NBP) is considered as one of the major drivers of interannual variation in atmospheric CO2 levels. However, the determinants of variability in NBP under the background climate (i.e., preindustrial conditions) remain poorly understood, especially on decadal‐to‐centennial timescales. We analyzed 1,000‐year simulations spanning 850‐1,849 from the Community Earth System Model (CESM) and found that the variability in NBP and heterotrophic respiration (RH) were largely driven by fluctuations in the net primary production (NPP) and carbon turnover rates in response to climate variability. On interannual to multidecadal timescales, variability in NBP was dominated by variation in NPP, while variability in RH was driven by variation in turnover rates. However, on centennial timescales (100‐1,000 years), the RH variability became more tightly coupled to that of NPP. The NBP variability on centennial timescales was low, due to the near cancellation of NPP and NPP‐driven RH changes arising from climate internal variability and external forcings: preindustrial greenhouse gases, volcanic eruptions, land use changes, orbital change, and solar activity. Factorial experiments showed that globally on centennial timescales, the forcing of changes in greenhouse gas concentrations were the largest contributor (51%) to variations in both NPP and RH, followed by volcanic eruptions impacting NPP (25%) and RH (31%). Our analysis of the carbon‐cycle suggests that geoengineering solutions by injection of stratospheric aerosols might be ineffective on longer timescales.

Increased extreme wet and dry years and forest growth loss from drought legacy effect lead to a question whether wetness events can conversely compensate for this loss. Here the authors report substantial growth enhancement after extreme wetness compensating for drought-induced growth loss globally.

The impacts of climate change on summer carbon cycling in the northern hemisphere remain poorly resolved. Here the authors use atmospheric CO2 records from Point Barrow (Alaska) to show that summer CO2 drawdown is significantly negatively correlated with terrestrial temperature north of 50°N between 1979–2012.

The production of anthropogenic reactive nitrogen (N) has grown so much in the last century that quantifying the effect of N enrichment on plant growth has become a central question for carbon (C) cycle research. Numerous field experiments generally found that N enrichment increased site-scale plant biomass, although the magnitude of the response and sign varied across experiments. We quantified the response of terrestrial natural vegetation biomass to N enrichment in the Northern Hemisphere (>30° N) by scaling up data from 773 field observations (142 sites) of the response of biomass to N enrichment using machine-learning algorithms. N enrichment had a significant and nonlinear effect on aboveground biomass (AGB), but a marginal effect on belowground biomass. The most influential variables on the AGB response were the amount of N applied, mean biomass before the experiment, the treatment duration and soil phosphorus availability. From the machine learning models, we found that N enrichment due to increased atmospheric N deposition during 1993–2010 has enhanced total biomass by 1.1 ± 0.3 Pg C, in absence of losses from harvest and disturbances. The largest effect of N enrichment on plant growth occurred in northeastern Asia, where N deposition markedly increased. These estimates were similar to the range of values provided by state-of-the-art C–N ecosystem process models. This work provides data-driven insights into hemisphere-scale N enrichment effect on plant biomass growth, which allows to constrain the terrestrial ecosystem process model used to predict future terrestrial C storage.

Recent studies have reported a 9% decrease in global carbon emissions during the COVID-19 lockdown period; however, its impact on the variation of atmospheric CO _2 level remains under question. Using atmospheric CO _2 observed at Anmyeondo station (AMY) in South Korea, downstream of China, this study examines whether the decrease in China’s emissions due to COVID-19 can be detected from the enhancement of CO _2 mole fraction (ΔCO _2 ) relative to the background value. The Weather Research and Forecasting–Stochastic Time-Inverted Lagrangian Transport model was applied to determine when the observed mole fractions at AMY were affected by air parcels from China. Atmospheric observations at AMY showed up to a −20% (−1.92 ppm) decrease in ΔCO _2 between February and March 2020 compared to the same period in 2018 and 2019, particularly with a −34% (−3.61 ppm) decrease in March. ΔCO, which was analyzed to explore the short-term effect of emission reductions, had a decrease of −43% (−80.66 ppb) during the lockdown in China. Particularly in East China, where emissions are more concentrated than in Northeast China, ΔCO _2 and ΔCO decreased by −44% and −65%, respectively. The ΔCO/ΔCO _2 ratio (24.8 ppb ppm ^−1 ), which is the indicator of emission characteristics, did not show a significant difference before and after the COVID-19 lockdown period ( α = 0.05), suggesting that this decrease in ΔCO _2 and ΔCO was associated with emission reductions rather than changes in emission sources or combustion efficiency in China. Reduced carbon emissions due to limited human activity resulted in a decrease in the short-term regional enhancement to the observed atmospheric CO _2 .

Abstract With the increasing pressure from population growth and economic development, northern China (NC) faces a grand challenge of water scarcity, which can be further exacerbated by climatic and societal changes. The South‐to‐North Water Diversion (SNWD) project is designed to mitigate the water scarcity in NC. However, few studies have quantified the impact of the SNWD on water scarcity within the context of climatic and societal changes and its potential effects on economic and agricultural food in the region. We used water supply stress index (WaSSI) to quantify water scarcity within the context of environmental change in NC and developed a method to estimate the economic and agricultural impacts of the SNWD. Focuses were put on alleviating the water supply shortage and economic and agricultural benefits for the water‐receiving NC. We find that societal changes, especially economic growth, are the major contributors to water scarcity in NC during 2009–2099. To completely mitigate the water scarcity of NC, at least an additional water supply of 13 billion m3/year (comparable to the annual diversion water by SNWD Central Route) will be necessary. Although SNWD alone cannot provide the full solution to NC's water shortage in next few decades, it can significantly alleviate the water supply stress in NC (particularly Beijing), considerably increasing the agricultural production (more than 115 Tcal/year) and bringing economic benefits (more than 51 billion RMB/year) through supplying industrial and domestic water use. Additionally, the transfer project could have impacts on the ecological environment in the exporting regions.

Afforestation is often used to increase terrestrial carbon sequestration and restore ecosystem services. Here, the authors show that afforestation can also neutralize soil pH by lowering pH in alkaline soil but raising pH in acid soil, thus further promoting the restoration of ecosystem functions.