Interannual variation of terrestrial carbon cycle: Issues and perspectives

Woody encroachment induced earlier and extended growing season in boreal wetland ecosystems

Woody plant encroachment (WPE), a widespread ecological phenomenon globally, has significant impacts on ecosystem structure and functions. However, little is known about how WPE affects phenology in wetland ecosystems of middle and high latitudes. Here, we investigated the regional-scale effects of WPE on the start (SOS), peak (POS), end (EOS), and length (GSL) of the growing season in boreal wetland ecosystems, and their underlying mechanisms, using remote sensing dataset during 2001-2016. Our results showed that WPE advanced the annual SOS and POS, while delaying EOS and extending GSL in boreal wetlands with these impacts increasing over time. When boreal wetland ecosystems were fully encroached by woody plants, the SOS and POS were advanced by 12.17 and 5.65 days, respectively, the EOS was postponed by 2.74 days, and the GSL was extended by 15.21 days. We also found that the impacts of WPE on wetland SOS were predominantly attributed to the increased degree of WPE (α), while climatic factors played a more significant role in controlling the POS and EOS responses to WPE. Climate change not only directly influenced phenological responses of wetlands to WPE but also exerted indirect effects by regulating soil moisture and α. Winter precipitation and spring temperature primarily determined the effects of WPE on SOS, while its impacts on POS were mainly controlled by winter precipitation, summer temperature, and precipitation, and the effects on EOS were mainly determined by winter precipitation, summer temperature, and autumn temperature. Our findings offer new insights into the understanding of the interaction between WPE and wetland ecosystems, emphasizing the significance of considering WPE effects to ensure accurate assessments of phenology changes.

Multilevel ecological compensation policy design based on ecosystem service flow: A case study of carbon sequestration services in the Qinghai-Tibet Plateau

Ecological compensation is an effective means to reconcile the imbalance of eco-social development between regions and promote enthusiasm for ecological environmental protection. There is some conformity between the theory of ecosystem service flow and ecological compensation, which provides new technical support for the formulation of ecological compensation policy. This study took the Qinghai-Tibet Plateau as the research area, adopted the breaking point model to obtain the spatial characteristics of carbon sequestration flow, and formulated a multilevel ecological compensation policy with Tibet as the design object. The results showed that most of the Qinghai-Tibet Plateau has a carbon sequestration surplus; the central and eastern Qinghai-Tibet Plateau, western Sichuan are successively carbon sequestration supply areas; the Chengdu Plain and Xinjiang were listed as carbon sequestration benefit areas; and the carbon sequestration tended to flow more closely between supply and benefit areas in proximity to each other. Nyingchi, Chamdo, Naqu and Shannan in Tibet need to receive a total ecological compensation of 393.21 million USD, of which 93.71 % is from the national level, 6.02 % is from carbon sequestration benefit areas in other provinces; furthermore, Lhasa and Shigatse in Tibet need to provide the remaining ecological compensation. This study offers innovations for the formulation of ecological compensation policies and provide a new theory for ecological environment management.

The mobilization and transport of newly fixed carbon are driven by plant water use in an experimental rainforest under drought

Non-structural carbohydrates (NSCs) are building blocks for biomass and fuel metabolic processes. However, it remains unclear how tropical forests mobilize, export, and transport NSCs to cope with extreme droughts. We combined drought manipulation and ecosystem 13CO2 pulse-labeling in an enclosed rainforest at Biosphere 2, assessed changes in NSCs, and traced newly assimilated carbohydrates in plant species with diverse hydraulic traits and canopy positions. We show that drought caused a depletion of leaf starch reserves and slowed export and transport of newly assimilated carbohydrates below ground. Drought effects were more pronounced in conservative canopy trees with limited supply of new photosynthates and relatively constant water status than in those with continual photosynthetic supply and deteriorated water status. We provide experimental evidence that local utilization, export, and transport of newly assimilated carbon are closely coupled with plant water use in canopy trees. We highlight that these processes are critical for understanding and predicting tree resistance and ecosystem fluxes in tropical forest under drought.

Dry-season length affects the annual ecosystem carbon balance of a temperate semi-arid shrubland

Semi-arid ecosystems have been shown to dominate over tropical forests in determining the trend and interannual variability of land carbon (C) sink. However, the magnitude and variability of ecosystem C balance remain largely uncertain for temperate semi-arid shrublands at the decadal scale. Using eddy-covariance and micro-meteorological measurements, we quantified the interannual variation in net ecosystem production (NEP) and its components, gross primary production (GPP) and ecosystem respiration (Reco, i.e., the sum of autotrophic and heterotrophic respiration), in a semi-arid shrubland of the Mu Us Desert, northern China during 2012-2022. This shrubland was an overall weak C sink over the 11 years (NEP = 12 ± 46 g C m-2 yr-1, mean ± SD). Annual NEP ranged from -66 to 77 g C m-2 yr-1, with the ecosystem frequently switching between being an annual C sink and a C source. GPP was twice as sensitive as Reco to prolonged dry seasons, leading to a close negative relationship between annual NEP and dry-season length (R2 = 0.80, P < 0.01). Annual GPP (R2 = 0.51, P = 0.01) and NEP (R2 = 0.58, P < 0.01) were positively correlated with annual rainfall. Negative annual NEP (the ecosystem being a C source) tended to occur when the dry season exceeded 50 d yr-1 or rainfall dropped below 280 mm yr-1. Increases in dry-season length strengthened the effects of low soil moisture relative to high vapor pressure deficit in constraining NEP. Both GPP and NEP were more closely correlated with C uptake amplitude (annual maximum daily values) than with C uptake period. These findings indicate that dry-season extension under climate change may reduce the long-term C sequestration in semi-arid shrublands. Plant species adapted to prolonged dry seasons should be used in ecosystem restoration in the studied area to enhance ecosystem functions.

Slower changes in vegetation phenology than precipitation seasonality in the dry tropics

The dry tropics occupy ~40% of the tropical land surface and play a dominant role in the trend and interannual variability of the global carbon cycle. Previous studies have reported considerable changes in the dry tropical precipitation seasonality due to climate change, however, the accompanied changes in the length of the vegetation growing season (LGS)-the key period of carbon sequestration-have not been examined. Here, we used long-term satellite observations along with in-situ flux measurements to investigate phenological changes in the dry tropics over the past 40 years. We found that only ~18% of the dry tropics show a significant (p ≤ .1) increasing trend in LGS, while ~13% show a significant decreasing trend. The direction of the LGS change depended not only on the direction of precipitation seasonality change but also on the vegetation water use strategy (i.e. isohydricity) as an adaptation to the long-term average precipitation seasonality (i.e. whether the most of LGS is in the wet season or dry season). Meanwhile, we found that the rate of LGS change was on average ~23% slower than that of precipitation seasonality, caused by a buffering effect from soil moisture. This study uncovers potential mechanisms driving phenological changes in the dry tropics, offering guidance for regional vegetation and carbon cycle studies.

Satellite-observed increasing coupling between vegetation productivity and greenness in the semiarid Loess Plateau of China is not captured by process-based models

Global vegetation has experienced notable changes in greenness and productivity since the early 1980s. However, the changes in the relationship between productivity and greenness, i.e., the coupling, and its underlying mechanisms, are poorly understood. The Loess Plateau (LP) is one of China's most significant areas for vegetation greening. Yet, it remains poorly documented what changes in the coupling between productivity and greenness are and how environmental and anthropogenic factors affect this coupling in the LP over the past four decades. We investigated the interannual trend of coupling between Gross Primary Productivity (GPP) and Leaf Area Index (LAI), i.e., the GPP-LAI coupling, and its response to climate factors and afforestation in the LP using long-term remote-sensed LAI, GPP and Solar-induced Chlorophyll Fluorescence (SIF). We found a monotonically increasing trend in the GPP-LAI coupling in the LP from 1982 to 2018 (0.0043 yr-1, p < 0.05), in which the significant trend in the northwest LP was driven by increasing soil water and landcover change, e.g., increased grassland and afforestation. An ensemble of 11 state-of-the-art ecosystem models from the TRENDY project failed to capture the observed monotonically increasing trend of the GPP-LAI coupling in the LP. The consistent projection of a decreasing GPP-LAI coupling in LP during 2019-2100 by 22 Earth System Models (ESMs) under various future scenarios should be treated with caution due to the identified inherent uncertainties in the ecosystem component in ESMs and the notable biases in the simulation of future climate conditions. Our study highlights the need to enhance the key mechanisms that regulate the coupling relationships between photosynthesis and canopy structure in indigenized ecosystem models to accurately estimate the ecosystem change in drylands under global climate change.

Recent decline in tropical temperature sensitivity of atmospheric CO2 growth rate variability

A two-fold enhancement in the sensitivity of atmospheric CO2 growth rate (CGR) to tropical temperature interannual variability (Γ CGR T $$ {\varGamma}_{\mathrm{CGR}}^T $$ ) till early 2000s has been reported, which suggests a drought-induced shift in terrestrial carbon cycle responding temperature fluctuations, thereby accelerating global warming. However, using six decades long atmospheric CO2 observations, we show thatΓ CGR T $$ {\varGamma}_{\mathrm{CGR}}^T $$ has significantly declined in the last two decades, to the level during the 1960s. TheΓ CGR T $$ {\varGamma}_{\mathrm{CGR}}^T $$ decline begs the question of whether the sensitivity of ecosystem carbon cycle to temperature variations at local scale has largely decreased. With state-of-the-art dynamic global vegetation models, we further find that the recentΓ CGR T $$ {\varGamma}_{\mathrm{CGR}}^T $$ decline is barely attributed to ecosystem carbon cycle response to temperature fluctuations at local scale, which instead results from a decrease in spatial coherence in tropical temperature variability and land use change. Our results suggest that the recently reported loss of rainforest resilience has not shown marked influence on the temperature sensitivity of ecosystem carbon cycle. Nevertheless, the increasing extent of land use change as well as more frequent and intensive drought events are likely to modulate the responses of ecosystem carbon cycle to temperature variations in the future. Therefore, our study highlights the priority to continuously monitor the temperature sensitivity of CGR variability and improve Earth system model representation on land use change, in order to predict the carbon-climate feedback.

Constraining long-term model predictions for woody growth using tropical tree rings

The strength and persistence of the tropical carbon sink hinges on the long-term responses of woody growth to climatic variations and increasing CO2 . However, the sensitivity of tropical woody growth to these environmental changes is poorly understood, leading to large uncertainties in growth predictions. Here, we used tree ring records from a Southeast Asian tropical forest to constrain ED2.2-hydro, a terrestrial biosphere model with explicit vegetation demography. Specifically, we assessed individual-level woody growth responses to historical climate variability and increases in atmospheric CO2 (Ca ). When forced with historical Ca , ED2.2-hydro reproduced the magnitude of increases in intercellular CO2 concentration (a major determinant of photosynthesis) estimated from tree ring carbon isotope records. In contrast, simulated growth trends were considerably larger than those obtained from tree rings, suggesting that woody biomass production efficiency (WBPE = woody biomass production:gross primary productivity) was overestimated by the model. The estimated WBPE decline under increasing Ca based on model-data discrepancy was comparable to or stronger than (depending on tree species and size) the observed WBPE changes from a multi-year mature-forest CO2 fertilization experiment. In addition, we found that ED2.2-hydro generally overestimated climatic sensitivity of woody growth, especially for late-successional plant functional types. The model-data discrepancy in growth sensitivity to climate was likely caused by underestimating WBPE in hot and dry years due to commonly used model assumptions on carbon use efficiency and allocation. To our knowledge, this is the first study to constrain model predictions of individual tree-level growth sensitivity to Ca and climate against tropical tree-ring data. Our results suggest that improving model processes related to WBPE is crucial to obtain better predictions of tropical forest responses to droughts and increasing Ca . More accurate parameterization of WBPE will likely reduce the stimulation of woody growth by Ca rise predicted by biosphere models.

The strengthened impact of water availability at interannual and decadal time scales on vegetation GPP

Water availability (WA) is a key factor influencing the carbon cycle of terrestrial ecosystems under climate warming, but its effects on gross primary production (EWA-GPP ) at multiple time scales are poorly understood. We used ensemble empirical mode decomposition (EEMD) and partial correlation analysis to assess the WA-GPP relationship (RWA-GPP ) at different time scales, and geographically weighted regression (GWR) to analyze their temporal dynamics from 1982 to 2018 with multiple GPP datasets, including near-infrared radiance of vegetation GPP, FLUXCOM GPP, and eddy covariance-light-use efficiency GPP. We found that the 3- and 7-year time scales dominated global WA variability (61.18% and 11.95%), followed by the 17- and 40-year time scales (7.28% and 8.23%). The long-term trend also influenced 10.83% of the regions, mainly in humid areas. We found consistent spatiotemporal patterns of the EWA-GPP and RWA-GPP with different source products: In high-latitude regions, RWA-GPP changed from negative to positive as the time scale increased, while the opposite occurred in mid-low latitudes. Forests had weak RWA-GPP at all time scales, shrublands showed negative RWA-GPP at long time scales, and grassland (GL) showed a positive RWA-GPP at short time scales. Globally, the EWA-GPP , whether positive or negative, enhanced significantly at 3-, 7-, and 17-year time scales. For arid and humid zones, the semi-arid and sub-humid zones experienced a faster increase in the positive EWA-GPP , whereas the humid zones experienced a faster increase in the negative EWA-GPP . At the ecosystem types, the positive EWA-GPP at a 3-year time scale increased faster in GL, deciduous broadleaf forest, and savanna (SA), whereas the negative EWA-GPP at other time scales increased faster in evergreen needleleaf forest, woody savannas, and SA. Our study reveals the complex and dynamic EWA-GPP at multiple time scales, which provides a new perspective for understanding the responses of terrestrial ecosystems to climate change.

Temperature dependence of spring carbon uptake in northern high latitudes during the past four decades

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 CO2 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 CO2 drawdown (SCC). We found a fall and rise in the interannual correlation of temperature with SZC and SCC (RSZC-T and RSCC-T ), showing a recent reversal of the previously reported weakening trend of RSZC-T and RSCC-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 RSZC-T and RSCC-T , despite an overall unbroken temperature control on net ecosystem CO2 fluxes at local scale. Our results provide an alternative explanation for the apparent drop of RSZC-T and RSCC-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.

Multi-annual variability of pCO2(aq) and air-water CO2 flux in the mangrove-dominated Dhamra Estuary draining into the Bay of Bengal (India)

Small estuaries often remain neglected while characterizing air-water CO2 flux dynamics. This study reports the seasonal, spatial, and multi-annual variability of carbon biogeochemistry, emphasizing air-water CO2 flux from a small tropical mangrove-dominated estuary (Dhamra Estuary) of the Bay of Bengal, based on the 9-year-long sampling survey (2013 to 2021). The sampling covered twelve pre-fixed locations of this estuary. A suite of biogeochemical parameters was kept within the purview of this study to deliniate the interrelationship between CO2 fluxes and potential factors that can regulate/govern pCO2(aq) dynamics. Air water CO2 exchange rates were calculated using five globally accepted empirical gas transfer velocity equations and varied in a range of - 832.5 to 7904 μmol m-2 h-1. The estuary was a sink for CO2 in monsoon season, having the highest average flux rates of - 380.9 ± 125.5 μmol m-2 h-1, whereas a source in pre-monsoon (38.29 ± 913.1 μmol m-2 h-1) and post-monsoon (91.81 ± 1009.8 μmol m-2 h-1). The significant factors governing pCO2 were pH, salinity, total alkalinity and dissolved inorganic carbon (DIC). This long-term seasonal study emphasizes the need to include small regional estuaries for more accurate estimates of global CO2 flux to upscale the global carbon budget and its controlling mechanism.

Temperature extremes of 2022 reduced carbon uptake by forests in Europe

The year 2022 saw record breaking temperatures in Europe during both summer and fall. Similar to the recent 2018 drought, close to 30% (3.0 million km2) of the European continent was under severe summer drought. In 2022, the drought was located in central and southeastern Europe, contrasting the Northern-centered 2018 drought. We show, using multiple sets of observations, a reduction of net biospheric carbon uptake in summer (56-62 TgC) over the drought area. Specific sites in France even showed a widespread summertime carbon release by forests, additional to wildfires. Partial compensation (32%) for the decreased carbon uptake due to drought was offered by a warm autumn with prolonged biospheric carbon uptake. The severity of this second drought event in 5 years suggests drought-induced reduced carbon uptake to no longer be exceptional, and important to factor into Europe's developing plans for net-zero greenhouse gas emissions that rely on carbon uptake by forests.

Spatial variations and mechanisms for the stability of water use efficiency in China

A clearer understanding of the stability of water use efficiency (WUE) and its driving factors contributes to improving water use efficiency and strengthening water resource management. However, the stability of WUE is unclear. Based on the EEMD method, this study analyses the spatial variations and mechanisms for the stability of WUE in China, especially in the National Forest Protection Project (NFPP) areas. It is found that the stable WUE was dominated by non-significant trends and increasing trends in China, accounting for 33.59% and 34.19%, respectively. The non-significant trend of stable WUE was mainly located in the Three-North shelterbelt program area, and the increasing trend of stable WUE was in Huaihe and Taihu, Taihang Mountains, and Pearl River shelterbelt program areas. Precipitation and soil moisture promoted the stable WUE in these project areas. The unstable WUE was dominated by positive reversals or negative reversals of WUE trends. The positive reversals of unstable WUE were mainly located in the Yellow River shelterbelt program areas, which was promoted by temperature and radiation, while the negative reversals of unstable WUE were mainly distributed in the Yangtze River and Liaohe shelterbelt program areas, which were mainly induced by saturation water vapor pressure difference (VPD). Our results highlight that some ecological restoration programs need to be improved to cope with the negative climate impact on the stability of WUE.

Increasingly negative tropical water-interannual CO2 growth rate coupling

Terrestrial ecosystems have taken up about 32% of the total anthropogenic CO2 emissions in the past six decades1. Large uncertainties in terrestrial carbon-climate feedbacks, however, make it difficult to predict how the land carbon sink will respond to future climate change2. Interannual variations in the atmospheric CO2 growth rate (CGR) are dominated by land-atmosphere carbon fluxes in the tropics, providing an opportunity to explore land carbon-climate interactions3-6. It is thought that variations in CGR are largely controlled by temperature7-10 but there is also evidence for a tight coupling between water availability and CGR11. Here, we use a record of global atmospheric CO2, 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 effects9. 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.

From remotely-sensed solar-induced chlorophyll fluorescence to ecosystem structure, function, and service: Part II-Harnessing data

Although our observing capabilities of solar-induced chlorophyll fluorescence (SIF) have been growing rapidly, the quality and consistency of SIF datasets are still in an active stage of research and development. As a result, there are considerable inconsistencies among diverse SIF datasets at all scales and the widespread applications of them have led to contradictory findings. The present review is the second of the two companion reviews, and data oriented. It aims to (1) synthesize the variety, scale, and uncertainty of existing SIF datasets, (2) synthesize the diverse applications in the sector of ecology, agriculture, hydrology, climate, and socioeconomics, and (3) clarify how such data inconsistency superimposed with the theoretical complexities laid out in (Sun et al., 2023) may impact process interpretation of various applications and contribute to inconsistent findings. We emphasize that accurate interpretation of the functional relationships between SIF and other ecological indicators is contingent upon complete understanding of SIF data quality and uncertainty. Biases and uncertainties in SIF observations can significantly confound interpretation of their relationships and how such relationships respond to environmental variations. Built upon our syntheses, we summarize existing gaps and uncertainties in current SIF observations. Further, we offer our perspectives on innovations needed to help improve informing ecosystem structure, function, and service under climate change, including enhancing in-situ SIF observing capability especially in "data desert" regions, improving cross-instrument data standardization and network coordination, and advancing applications by fully harnessing theory and data.

A stronger advance of urban spring vegetation phenology narrows vegetation productivity difference between urban settings and natural environments

Climate change is posing dramatic effects on terrestrial vegetation dynamics. The links between vegetation phenology or vegetation activity (growth) and climate change have been widely reported, yet, less is known about the impacts of phenological shifts on vegetation growth. Urban settings characterized by urban heat island and CO₂ dome are often used as ideal natural laboratories to understand how vegetation responds to global climate change. Here we assessed the impacts of phenology changes on vegetation growth in China using satellite phenology metrics and gross primary production (GPP) data from 2003 to 2018 and urban-natural contrast analysis. Compared with natural environments, phenological metrics (e.g., start/end of growing season (SOS/EOS), and the length of growing season (GSL), etc.) were observed to change more dramatically in urban environments. Furthermore, we found that GPP in both settings increased over time but with a higher increment in the urban environments, and the urban-natural vegetation productivity gap had been diminishing at a rate of 16.9 ± 6.76 g C m^-2 y^-1. The narrowing of the urban-natural GPP difference over time can be attributed to a more advanced SOS and extended GSL in urban settings than their natural counterparts, particularly SOS shift. These findings suggested that the distinct urban phenological shifts would become increasingly important in offsetting the loss of vegetation productivity induced by urbanization.

Remote sensing of atmospheric and soil water stress on ecosystem carbon and water use during flash droughts over eastern China

Flash droughts are often accompanied by large soil and atmospheric moisture deficits, and the concurrence of flash droughts and high temperature may have a great impact on the ecosystem. However, the stress of soil and atmospheric moisture deficits on carbon and water use of the ecosystem during flash droughts, especially during the drought periods with hot conditions, are unclear over a large region. In this study, we decoupled the atmospheric and soil water stress over eastern China by using vegetation productivity data and photosynthetically active radiation data retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS). The analysis is conducted during flash droughts and their sub-periods that are accompanied by high temperature and intense radiation from 2003 to 2018. The results showed that soil moisture (SM) stress was significantly greater than the vapor pressure deficit (VPD) stress on vegetation productivity in the humid regions of eastern China during flash droughts. However, high VPD controlled the water stress on light use efficiency (LUE) of vegetation over 55 % of the regions. For the hot periods of flash droughts, the area subjected to VPD stress on vegetation productivity significantly increased in semi-arid and semi-humid regions. The concurrent hot and drought conditions also increased water use efficiency (WUE) for most areas, which suggests that the reduction percentage of vegetation productivity is larger than that of evapotranspiration. Our research emphasized the severe impact of compound hot and flash drought conditions on vegetation carbon and water use from a remote sensing perspective.

Ecological engineering induced carbon sinks shifting from decreasing to increasing during 1981-2019 in China

Substantial evidence shows that most of China's terrestrial ecosystems are important carbon sinks. However, the nonlinear trend of the carbon sinks and their nonlinear response to driving factors are unclear. Taking the net ecosystem productivity (NEP) as a proxy for the ecosystem carbon sink, the nonlinear relationships between the monotonically increasing trends and decreasing to increasing shifts in the carbon sink to climate change and ecological engineering were investigated based on ensemble empirical mode decomposition (EEMD) and machine learning algorithm (boosted regression tree model, BRT). The results suggest that 16.75 % of the carbon sinks in China experienced a monotonic increase. Additionally, 20.55 % of the carbon sinks shifted from decreasing to increasing trends, primarily after 1995, and these carbon sinks were located in the key ecological engineering areas, such as the middle reaches of the Yellow River shelterbelt program area, the Liaohe shelterbelt program area, the Grain to Green program area, and the Three-North Forest shelterbelt program area. Moreover, carbon sinks exhibited strong spatial autocorrelation with low-low clustering in the north and high-high clustering in the south. The increase in CO₂ (slope of CO₂ < 1.8 g/m²/s/y) and solar radiation (slope of radiation >1 w/m²/y) promoted the monotonic increase in the carbon sinks in the center of China. The increase in the areas of forest and grassland shifted the carbon sink trend from decreasing to increasing in the key ecological engineering program areas, and economic development reversed the carbon sink reduction in the Pearl River shelterbelt program area. These findings highlight the positive effect of ecological engineering on carbon sinks and provide adaptation strategies and guidance for China to achieve the "carbon neutrality" target.

Large volcanic eruptions elucidate physiological controls of tree growth and photosynthesis

Forest productivity projections remain highly uncertain, notably because underpinning physiological controls are delicate to disentangle. Transient perturbation of global climate by large volcanic eruptions provides a unique opportunity to retrospectively isolate underlying processes. Here, we use a multi-proxy dataset of tree-ring records distributed over the Northern Hemisphere to investigate the effect of eruptions on tree growth and photosynthesis and evaluate CMIP6 models. Tree-ring isotope records denoted a widespread 2-4 years increase of photosynthesis following eruptions, likely as a result of diffuse light fertilization. We found evidence that enhanced photosynthesis transiently drove ring width, but the latter further exhibited a decadal anomaly that evidenced independent growth and photosynthesis responses. CMIP6 simulations reproduced overall tree growth decline but did not capture observed photosynthesis anomaly, its decoupling from tree growth or the climate sensitivities of either processes, highlighting key disconnects that deserve further attention to improve forest productivity projections under climate change.

Divergent effects of moderate grazing duration on carbon sequestration between temperate and alpine grasslands in China

Moderate grazing has been widely proven to improve ecosystem functioning and have profound effects on the carbon cycling and storage in grassland ecosystems, which highly depend on grazing duration and grassland type. However, the effects of moderate grazing durations on carbon sequestration with different grassland types over broad geographic scales across China remain underexplored in the context of striving for carbon neutrality. Here, we explored the probably different responses of carbon sequestration to moderate grazing duration for temperate and alpine grasslands based on 129 published literatures regarding the China's grasslands. The results showed the soil organic carbon stocks were significantly increased during short-term (<5 years) grazing duration, while significantly decreased during medium- (5-10 years) and long-term (≥ 10 years) grazing durations in temperate grasslands. However, the soil organic carbon stocks were significantly decreased during short-term grazing duration, while showed no significant changes during medium- and long-term grazing durations in alpine grasslands. The changes in soil organic stock were significantly positively correlated with the changes in belowground biomass, root:shoot, and microbial biomass carbon (P < 0.05). These findings suggest that the temperate grasslands change from carbon sink to carbon source with moderate grazing duration increasing, while the alpine grasslands present an opposite change pattern from carbon source to carbon sink, regulated by grazing-altered carbon input and microbial activities. Our study might have significant implications for future sustainable management practices for carbon sequestration of China's grasslands.

Autumn phenology of tree species in China is associated more with climate than with spring phenology and phylogeny

Both biotic and abiotic factors restrict changes in autumn phenology, yet their effects remain ambiguous, which hinders the accurate prediction of phenology under future climate change. In this study, based on the phenological records of 135 tree species at ten sites in China during 1979-2018, we first investigated the effects of climatic factors (temperature, precipitation, insolation and wind speed) and spring phenology on interannual changes in leaf coloring date (LCD) with the partial correlation analysis, and assessed the relative importance of phylogeny and native climate to LCD differences among species by using multivariate regression and phylogenetic eigenvector regression approach. The results showed that the effects of climate factors on interannual changes in LCD were more significant than spring phenology. In general, temperature played a more important role in cold regions (e.g. the northeast region), while the control of insolation on LCD was stronger in the warmer and wetter regions (e.g. the north, east and southwest regions). In addition, the effects of precipitation and wind speed were more evident in arid regions (e.g. the northwest region). We also found considerable effects of both native climate and phylogeny on the LCD differences among species, despite the contribution of native climate being almost 2~5 times greater than that of the phylogeny. Our findings confirmed and quantified the combined effects of climate, spring phenology and phylogeny on the autumn phenology of plants, which could help better understand the driving factors and influencing mechanism of plant phenology and provide a reference for the calibration and optimization of phenological models.

Identifying hotspots for ecosystem restoration across heterogeneous tropical savannah-dominated regions

There is high potential for ecosystem restoration across tropical savannah-dominated regions, but the benefits that could be gained from this restoration are rarely assessed. This study focuses on the Brazilian Cerrado, a highly species-rich savannah-dominated region, as an exemplar to review potential restoration benefits using three metrics: net biomass gains, plant species richness and ability to connect restored and native vegetation. Localized estimates of the most appropriate restoration vegetation type (grassland, savannah, woodland/forest) for pasturelands are produced. Carbon sequestration potential is significant for savannah and woodland/forest restoration in the seasonally dry tropics (net biomass gains of 58.2 ± 37.7 and 130.0 ± 69.4 Mg ha-1). Modelled restoration species richness gains were highest in the central and south-east of the Cerrado for savannahs and grasslands, and in the west and north-west for woodlands/forests. The potential to initiate restoration projects across the whole of the Cerrado is high and four hotspot areas are identified. We demonstrate that landscape restoration across all vegetation types within heterogeneous tropical savannah-dominated regions can maximize biodiversity and carbon gains. However, conservation of existing vegetation is essential to minimizing the cost and improving the chances of restoration success. This article is part of the theme issue 'Understanding forest landscape restoration: reinforcing scientific foundations for the UN Decade on Ecosystem Restoration'.

Assessing the impact of drought-land cover change on global vegetation greenness and productivity

Drought-land cover change (D-LCC) is considered to be an important stress factor that affects vegetation greenness and productivity (VG&P) in global terrestrial ecosystems. Understanding the effects of D-LCC on VG&P benefits the development of terrestrial ecosystem models and the prediction of ecosystem evolution. However, till today, the mechanism remains underexploited. In this study, based on the Theil-Sen median estimator and Mann-Kendall test, Hurst exponent evaluation and rescaled range analysis (R/S), Pearson and Partial correlation coefficient analyses, we explore the spatiotemporal distribution characteristics and future trends of Leaf area index (LAI), Net primary productivity (NPP), Solar-induced chlorophyll fluorescence (SIF), Standardized precipitation evapotranspiration index (SPEI), Soil moisture (SM), Land cover type (LC), and the impact mechanism of D-LCC on global VG&P. Our results provide four major insights. First, three independent satellite observations consistently indicate that the world is experiencing an increasing trend of VG&P: LAI (17.69 %), NPP (20.32 %) and SIF (16.46 %). Nonetheless, productivity-reducing trends are unfolding in some tropical regions, notably the Amazon rainforest and the Congo basin. Second, from 2001 to 2020, the frequency, severity, duration, and scope of global droughts have been increasing. Third, the impact of land cover change on global VG&P is region-dependent. Finally, our results indicate that the continuous growth of VG&P in the global vegetation area is likely to become more difficult to maintain.

Using functional indicators to detect state changes in terrestrial ecosystems

Indicators to predict ecosystem state change are urgently needed to cope with the degradation of ecosystem services caused by global change. With the development of new technologies for measuring ecosystem function with fine spatiotemporal resolution over broad areas, we are in the era of 'big data'. However, it is unclear how large, emerging datasets can be used to anticipate ecosystem state change. We propose the construction of indicators based on functional variables (flows) and state variables (pools) to predict future ecosystem state changes. The indicators identified here may be useful signals for doing so. In addition, functional indicators have explicit ecological meanings that can identify the ecological mechanism that is causing state changes, and can thus be used to improve ecosystem models.

Drivers of Decadal Carbon Fluxes Across Temperate Ecosystems

Long-running eddy covariance flux towers provide insights into how the terrestrial carbon cycle operates over multiple timescales. Here, we evaluated variation in net ecosystem exchange (NEE) of carbon dioxide (CO₂) across the Chequamegon Ecosystem-Atmosphere Study AmeriFlux core site cluster in the upper Great Lakes region of the USA from 1997 to 2020. The tower network included two mature hardwood forests with differing management regimes (US-WCr and US-Syv), two fen wetlands with varying levels of canopy sheltering and vegetation (US-Los and US-ALQ), and a very tall (400 m) landscape-level tower (US-PFa). Together, they provided over 70 site-years of observations. The 19-tower Chequamegon Heterogenous Ecosystem Energy-balance Study Enabled by a High-density Extensive Array of Detectors 2019 campaign centered around US-PFa provided additional information on the spatial variation of NEE. Decadal variability was present in all long-term sites, but cross-site coherence in interannual NEE in the earlier part of the record became weaker with time as non-climatic factors such as local disturbances likely dominated flux time series. Average decadal NEE at the tall tower transitioned from carbon source to sink to near neutral over 24 years. Respiration had a greater effect than photosynthesis on driving variations in NEE at all sites. Declining snowfall offset potential increases in assimilation from warmer springs, as less-insulated soils delayed start of spring green-up. Higher CO₂ increased maximum net assimilation parameters but not total gross primary productivity. Stand-scale sites were larger net sinks than the landscape tower. Clustered, long-term carbon flux observations provide value for understanding the diverse links between carbon and climate and the challenges of upscaling these responses across space.

Regressions underestimate the direct effect of soil moisture on land carbon sink variability

Multiple linear regression (MLR) is widely used to attribute causes of the interannual variability (IAV) of land carbon uptake, yet, parameter estimation in MLR can be problematic if the predictors are strongly inter-correlated. Recently, Humphrey et al., (2021) used MLR method to conclude that the indirect effect of soil moisture (SM) via land-atmosphere coupling, rather than direct effect of SM on photosynthesis and respiration, controls the IAV of NBP. Here we assess the validity of MLR and find that the direct effect of SM on NBP-IAV is greatly underestimated by MLR, which may undermine their main conclusion.

The global decline in the sensitivity of vegetation productivity to precipitation from 2001 to 2018

The sensitivity of vegetation productivity to precipitation (S_ppt ) is a key metric for understanding the variations in vegetation productivity under changing precipitation and predicting future changes in ecosystem functions. However, a comprehensive assessment of S_ppt over all the global land is lacking. Here, we investigated spatial patterns and temporal changes of S_ppt across the global land from 2001 to 2018 with multiple streams of satellite observations. We found consistent spatial patterns of S_ppt with different satellite products: S_ppt was highest in dry regions while low in humid regions. Grassland and shrubland showed the highest S_ppt , and evergreen needle-leaf forest and wetland showed the lowest. Temporally, S_ppt showed a generally declining trend over the past two decades (p < .05), yet with clear spatial heterogeneities. The decline in S_ppt was especially noticeable in North America and Europe, likely due to the increase in precipitation. In central Russia and Australia, however, S_ppt showed an increasing trend. Biome-wise, most ecosystem types exhibited significant decrease in S_ppt , while grassland, evergreen broadleaf forest, and mixed forest showed slight increases or non-significant changes in S_ppt . Our finding of the overall decline in S_ppt implies a potential stabilization mechanism for ecosystem productivity under climate change. However, the revealed S_ppt increase for some regions and ecosystem types, in particular global grasslands, suggests that grasslands might be increasingly vulnerable to climatic variability with continuing global climate change.

Hotspots, co-occurrence, and shifts of compound and cascading extreme climate events in Eurasian drylands

Eurasian drylands are the regions that are most vulnerable to climate change. Climate extremes have caused enormous or even devastating impacts on ecosystems and the social economy in this region, and the compound climate extremes (com_CEs, two or more extreme events occurring simultaneously) and cascading climate extremes (cas_CEs, two or more extreme events occurring successively) have exacerbated these problems. However, little is known about the occurrence patterns of com_CEs and cas_CEs in the Eurasian drylands. Based on the ERA5 reanalysis data range from 1979 to 2020, we improved the methodology for the extraction of co-occurrence events and identified high-frequency types, their hotspots, and occurrence rhythms (seasonally and annually) in Eurasian drylands. Our results showed that com_CEs and cas_CEs have high similarities in the types and spatial hotspots of extreme events; however, the former has a wider geographical and spatial distribution, and the latter has a longer duration. Specifically, co-occurring drought and heatwave events (DH) frequently appear in South Asia and western mid-latitude regions during summer, while in the winter, high latitude regions should be alert to the co-occurrence of drought and low-temperature events (DT). Central Asia and the Mongolian Plateau regions are prone to frequent drought and wind events (DW), and wind and high precipitation events (WP) in the spring and autumn. We have noticed that mid-latitude may suffer from extreme events that have never occurred before, such as com_DH being scattered sporadically in the first two decades and suddenly surging in West Asia and East Asia after the year 2000, and com_DT migrating from high-latitude areas such as the Arctic Ocean coast to mid-latitudes. Our results contribute to understanding hotspots of co-occurring CEs in Eurasian drylands, where more efforts will be needed in the future, especially in mid-latitudes which may suffer extreme climate events that have never occurred before.

Persistence of increasing vegetation gross primary production under the interactions of climate change and land use changes in Northwest China

Substantial evidence suggests a widespread increase in global vegetation gross primary production (GPP) since the 1980s. If the increasing trend of GPP remains unchanged in the future, it is considered to be the persistence of increasing GPP. However, it is still unknown whether the vegetation increasing GPP is persistent under the interactive effects of climate change and land use changes in Northwest China. Using the Mann-Kendall and boosted regression tree models, we constructed the relationship between the increasing GPP and environmental variables, and further explored its persistence under the interactions between climate change and land use changes under SSP245 and SSP585 scenarios. The results indicated that: (1) Land use change (8.01%) was the most important variable for the increasing GPP. The surface net solar radiation (6.79%), and maximum temperature of the warmest month (6.78%) were also very important. Moreover, mean temperature of the warmest quarter had strong interactions with mean precipitation of the warmest quarter (9.82%) and land use change (8.24%). (2) Under the SSP245 scenario, the persistence of increasing GPP accounted for 65.06% of the area in 2100, mainly located in Qinghai, Ningxia, and Shaanxi, while it only accounted for 19.50% under the SSP585 scenario. (3) The SSP245 scenario moderate warming leads to a slight ecosystem benefit, with more areas developing an increase in GPP due to climate and land use change factors. On the other hand, under SSP585 scenario, there are widespread losses of increasing GPP, driven largely by climate change, while ecological engineering is conducive to the persistence of increasing GPP in southern Qinghai. The results highlight the importance of the interactive effects of climate change and land use changes for predicting the persistence of vegetation change.

Influencing factors of the supply-demand relationships of carbon sequestration and grain provision in China: Does land use matter the most?

The provision of ecosystem services (ESs) such as carbon sequestration and grain provision are critical components to sustainable development. Reaching carbon neutrality generally requires the growing carbon sequestration of forest land, and feeding a growing population needs an expansion of cultivated land. However, limited land resources may lead to a contradiction between the carbon sequestration and grain provision. China has proposed long-term and large-scale land use programs, and exploring whether these land use policies are effective for ES sustainable provision would be instructive for future policy implications. This study integrated multi-source data in the socioecological dimension to determine the extent by which land use and land use change influence the supply-demand mismatches of carbon (carbon sequestration and emission) and grain (grain provision and consumption) in China at the provincial level. The result showed that the total quantity of carbon emissions surpassed carbon sequestration and the grain provision could cover the consumption from 2000 to 2015. Spatially, southeastern coastal provinces had higher grain deficits and northeast provinces had higher carbon deficits. This study further detected the influencing factors of the mismatches between the supply and demand of the two ESs. Excluding land use factors, our results showed that social factors contributed 38% and 47% to the supply-demand mismatches of carbon and grain, respectively, and natural factors contributed 39% and 15%, respectively. During 2000-2005, 2005-2010, and 2010-2015, cropland changes significantly affected grain balance, while forest land changes did not significantly affect carbon balance. These results indicated that cropland protections are vital to food safety, and carbon emission reductions should be the focus for carbon balance. Finally, this study makes policy suggestions for land use and ecosystem management, and a future research framework was proposed to help mitigate ES supply-demand imbalance.

Arabidopsis plants engineered for high root sugar secretion enhance the diversity of soil microorganisms

Plants secrete sugars from their roots into the soil, presumably to support beneficial plant-microbe interactions. Accordingly, manipulation of sugar secretion might be a viable strategy to enhance plant health and productivity. To evaluate the effect of increased root sugar secretion on plant performance and the soil microbiome, we overexpressed glucose and sucrose-specific membrane transporters in root epidermal cells of the model plant Arabidopsis thaliana. These plants showed strongly increased rates of sugar secretion in a hydroponic culture system. When grown on soil, the transporter-overexpressor plants displayed a higher photosynthesis rate, but reduced shoot growth compared to the wild-type control. Amplicon sequencing and qPCR analysis of rhizosphere soil samples indicated a limited effect on the total abundance of bacteria and fungi, but a strong effect on community structure in soil samples associated with the overexpressors. Notable changes included the increased abundance of bacteria belonging to the genus Rhodanobacter and the fungi belonging to the genus Cutaneotrichosporon, while Candida species abundance was reduced. The potential influences of the altered soil microbiome on plant health and productivity are discussed. The results indicate that the engineering of sugar secretion can be a viable pathway to enhancing the carbon sequestration rate and optimizing the soil microbiome. This article is protected by copyright. All rights reserved.

Regional and seasonal partitioning of water and temperature controls on global land carbon uptake variability

Global fluctuations in annual land carbon uptake (NEE_IAV) depend on water and temperature variability, yet debate remains about local and seasonal controls of the global dependences. Here, we quantify regional and seasonal contributions to the correlations of globally-averaged NEE_IAV against terrestrial water storage (TWS) and temperature, and respective uncertainties, using three approaches: atmospheric inversions, process-based vegetation models, and data-driven models. The three approaches agree that the tropics contribute over 63% of the global correlations, but differ on the dominant driver of the global NEE_IAV, because they disagree on seasonal temperature effects in the Northern Hemisphere (NH, >25°N). In the NH, inversions and process-based models show inter-seasonal compensation of temperature effects, inducing a global TWS dominance supported by observations. Data-driven models show weaker seasonal compensation, thereby estimating a global temperature dominance. We provide a roadmap to fully understand drivers of global NEE_IAV and discuss their implications for future carbon–climate feedbacks.

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.

Bridge to the future: Important lessons from 20 years of ecosystem observations made by the OzFlux network

In 2020, the Australian and New Zealand flux research and monitoring network, OzFlux, celebrated its 20th anniversary by reflecting on the lessons learned through two decades of ecosystem studies on global change biology. OzFlux is a network not only for ecosystem researchers, but also for those 'next users' of the knowledge, information and data that such networks provide. Here, we focus on eight lessons across topics of climate change and variability, disturbance and resilience, drought and heat stress and synergies with remote sensing and modelling. In distilling the key lessons learned, we also identify where further research is needed to fill knowledge gaps and improve the utility and relevance of the outputs from OzFlux. Extreme climate variability across Australia and New Zealand (droughts and flooding rains) provides a natural laboratory for a global understanding of ecosystems in this time of accelerating climate change. As evidence of worsening global fire risk emerges, the natural ability of these ecosystems to recover from disturbances, such as fire and cyclones, provides lessons on adaptation and resilience to disturbance. Drought and heatwaves are common occurrences across large parts of the region and can tip an ecosystem's carbon budget from a net CO2 sink to a net CO2 source. Despite such responses to stress, ecosystems at OzFlux sites show their resilience to climate variability by rapidly pivoting back to a strong carbon sink upon the return of favourable conditions. Located in under-represented areas, OzFlux data have the potential for reducing uncertainties in global remote sensing products, and these data provide several opportunities to develop new theories and improve our ecosystem models. The accumulated impacts of these lessons over the last 20 years highlights the value of long-term flux observations for natural and managed systems. A future vision for OzFlux includes ongoing and newly developed synergies with ecophysiologists, ecologists, geologists, remote sensors and modellers.

Inter-comparisons of mean, trend and interannual variability of global terrestrial gross primary production retrieved from remote sensing approach

Many models were established to estimate gross primary production (GPP) of terrestrial ecosystems based on vegetation light use efficiency (LUE). Analysing the spatial-temporal variations of global terrestrial GPP became capable with the increasing length of satellite data. Previous studies mainly focused on evaluating the model performance or investigating the mean, the temporal trend or the interannual variability (IAV) of global terrestrial GPP based on one single or multiple models, which is difficult to identify common merits of a same cluster of GPP models. This study compared eight satellite-based LEU-type GPP models in capturing the mean, temporal trend and IAV of global GPP concurrently. Our results showed that current common-used models based on LUE methodology estimated global mean GPP ranging from 128.5 to 158.3 Pg C year^-1, and global mean IAV ranging from 0.1 to 0.35, but the trends ranging from -0.22 to 0.51 Pg C year^-1. In the context of plant functional types (PFTs) and climate classifications, no consistent feature for either of the mean, trend or IAV of GPP are identified among eight models. Future studies should integrate the latest advances on the mechanisms and associated environmental factors into models and consolidate performance of models to better understand the evolutions of terrestrial ecosystem functioning.

Soil phosphorus drives plant trait variations in a mature subtropical forest

Earth system models are implementing soil phosphorus dynamic and plant functional traits to predict functional changes in global forests. However, the linkage between soil phosphorus and plant traits lacks empirical evidence, especially in mature forests. Here, we examined the soil phosphorus constraint on plant functional traits in a mature subtropical forest based on observations of 9943 individuals from 90 species in a 5-ha forest dynamic plot and 405 individuals from 15 species in an adjacent 10-year nutrient-addition experiment. We first confirmed a pervasive phosphorus limitation on subtropical tree growth based on leaf N:P ratios. Then, we found that soil phosphorus dominated multidimensional trait variations in the 5-ha forest dynamic plot. Soil phosphorus content explained 44% and 53% of the variance in the traits defining the main functional space across species and communities, respectively. Lastly, we found much stronger phosphorus effects on most plant functional traits than nitrogen at both species and community levels in the 10-year nutrient-addition experiment. This study provides evidence for the consistent pattern of soil phosphorus constraint on plant trait variations between the species and community levels in a mature evergreen broadleaf forest in the East Asian monsoon region. These findings shed light on the predominant role of soil phosphorus on plant functional trait variations in mature subtropical forests, providing new insights for models to incorporate soil phosphorus constraint in predicting future vegetation dynamics.

Estimation of China’s Contribution to Global Greening over the Past Three Decades

China’s contribution to global greening is regulated by increasing atmospheric CO2 concentrations, climate change, and land use. Based on TRENDY project data, this study identified that the shifts in China’s contribution to the global leaf area index (LAI) trend strongly reduced during the warming hiatus, translating from 13.42 ± 26.45% during 1982–1998 into 7.91 ± 25.45% during 1999–2012. First, significant negative sensitivities of LAI to enhanced vapor pressure deficit (VPD), when only considering the climate effect derived from TRENDY models in China, were found to have shifted substantially after the late 1990s. However, globally, LAI had positive rather than negative responses to enhanced VPD. These opposing shifts in the response of LAI to enhanced VPD reduced the national contribution to global vegetation greening. Second, shifts in land-use change and their effects on the LAI trends in the two periods in China were accompanied by major changes in land cover and land management intensity, including forestry. Consequently, the contribution of land use in China reduced by −47.68% during the warming hiatus period, as compared with the warming period. Such a shift in the impact of land-use change on LAI simulated by ecosystem models might result from the models’ lack of consideration of conserving and expanding forests with the goal of mitigating climate change for China. Our results highlight the need for ecosystem models to reproduce the enhanced negative impact on global LAI and consider the shifts in man-made adaptation policies (e.g., forest management) to improve terrestrial ecosystem models in the future.

Tropical extreme droughts drive long-term increase in atmospheric CO2 growth rate variability

The terrestrial carbon sink slows the accumulation of carbon dioxide (CO2) in the atmosphere by absorbing roughly 30% of anthropogenic CO2 emissions, but varies greatly from year to year. The resulting variations in the atmospheric CO2 growth rate (CGR) have been related to tropical temperature and water availability. The apparent sensitivity of CGR to tropical temperature ([Formula: see text]) has changed markedly over the past six decades, however, the drivers of the observation to date remains unidentified. Here, we use atmospheric observations, multiple global vegetation models and machine learning products to analyze the cause of the sensitivity change. We found that a threefold increase in [Formula: see text] emerged due to the long-term changes in the magnitude of CGR variability (i.e., indicated by one standard deviation of CGR; STDCGR), which increased 34.7% from 1960-1979 to 1985-2004 and subsequently decreased 14.4% in 1997-2016. We found a close relationship (r2 = 0.75, p < 0.01) between STDCGR and the tropical vegetated area (23°S - 23°N) affected by extreme droughts, which influenced 6-9% of the tropical vegetated surface. A 1% increase in the tropical area affected by extreme droughts led to about 0.14 Pg C yr-1 increase in STDCGR. The historical changes in STDCGR were dominated by extreme drought-affected areas in tropical Africa and Asia, and semi-arid ecosystems. The outsized influence of extreme droughts over a small fraction of vegetated surface amplified the interannual variability in CGR and explained the observed long-term dynamics of [Formula: see text].

The response of net primary productivity to climate change and its impact on hydrology in a water-limited agricultural basin

Climate change has remarkably altered growing-season vegetation growth, but the impacts of vegetation variability on the regional hydrological cycle remain poorly understood. Exploring the relationships between climate change, vegetation dynamics, and hydrologic factors would contribute to the sustainable management of ecosystems. Here, we investigated the response of vegetation dynamics to climate change and its impact on hydrologic factors in a traditional agricultural basin with limited water resources in China, Nansi Lake Basin (NLB). To this end, CASA (Carnegie-Ames-Stanford Approach) model and the SWAT (Soil and Water Assessment Tool) model were applied to simulate the net primary productivity (NPP), evapotranspiration (ET), and soil water in the growing season (April-October) from 2000 to 2016. Results showed that the mean growing-season NPP (NPP_GS) exhibited an ascending trend at a rate of 2.93 g C/m²/year during the 17-year period. The intra-annual variation of NPP_GS displayed two peaks in May and July, respectively. The first peak in May was accompanied by relative deficits in soil water, which might inhibit vegetation productivity. Precipitation was the principal climatic factor controlling NPP_GS dynamics in the water-limited NLB. The positive influence of temperature on NPP_GS was relatively weak, and even future warming could negatively affect ecosystem productivity in the south-central regions of the NLB. Furthermore, a strongly positive relationship between NPP_GS and ET was detected, suggesting that increasing NPP in the future might stimulate the rise in ET and then exacerbate drought at the watershed scale. This study provides an integrated model for a comprehensive understanding of the interaction between vegetation, climate, and hydrological cycle, and highlights the importance of water-saving agriculture for future food security.

Mapping native and non-native vegetation in the Brazilian Cerrado using freely available satellite products

Native vegetation across the Brazilian Cerrado is highly heterogeneous and biodiverse and provides important ecosystem services, including carbon and water balance regulation, however, land-use changes have been extensive. Conservation and restoration of native vegetation is essential and could be facilitated by detailed landcover maps. Here, across a large case study region in Goiás State, Brazil (1.1 Mha), we produced physiognomy level maps of native vegetation (n = 8) and other landcover types (n = 5). Seven different classification schemes using different combinations of input satellite imagery were used, with a Random Forest classifier and 2-stage approach implemented within Google Earth Engine. Overall classification accuracies ranged from 88.6-92.6% for native and non-native vegetation at the formation level (stage-1), and 70.7-77.9% for native vegetation at the physiognomy level (stage-2), across the seven different classifications schemes. The differences in classification accuracy resulting from varying the input imagery combination and quality control procedures used were small. However, a combination of seasonal Sentinel-1 (C-band synthetic aperture radar) and Sentinel-2 (surface reflectance) imagery resulted in the most accurate classification at a spatial resolution of 20 m. Classification accuracies when using Landsat-8 imagery were marginally lower, but still reasonable. Quality control procedures that account for vegetation burning when selecting vegetation reference data may also improve classification accuracy for some native vegetation types. Detailed landcover maps, produced using freely available satellite imagery and upscalable techniques, will be important tools for understanding vegetation functioning at the landscape scale and for implementing restoration projects.

Interannual and Seasonal Drivers of Carbon Cycle Variability Represented by the Community Earth System Model (CESM2)

Earth system models are intended to make long-term projections, but they can be evaluated at interannual and seasonal time scales. Although the Community Earth System Model (CESM2) showed improvements in a number of terrestrial carbon cycle benchmarks, relative to its predecessor, our analysis suggests that the interannual variability (IAV) in net terrestrial carbon fluxes did not show similar improvements. The model simulated low IAV of net ecosystem production (NEP), resulting in a weaker than observed sensitivity of the carbon cycle to climate variability. Low IAV in net fluxes likely resulted from low variability in gross primary productivity (GPP)-especially in the tropics-and a high covariation between GPP and ecosystem respiration. Although lower than observed, the IAV of NEP had significant climate sensitivities, with positive NEP anomalies associated with warmer and drier conditions in high latitudes, and with wetter and cooler conditions in mid and low latitudes. We identified two dominant modes of seasonal variability in carbon cycle flux anomalies in our fully coupled CESM2 simulations that are characterized by seasonal amplification and redistribution of ecosystem fluxes. Seasonal amplification of net and gross carbon fluxes showed climate sensitivities mirroring those of annual fluxes. Seasonal redistribution of carbon fluxes is initiated by springtime temperature anomalies, but subsequently negative feedbacks in soil moisture during the summer and fall result in net annual carbon losses from land. These modes of variability are also seen in satellite proxies of GPP, suggesting that CESM2 appropriately represents regional sensitivities of photosynthesis to climate variability on seasonal time scales.

Worldwide impacts of atmospheric vapor pressure deficit on the interannual variability of terrestrial carbon sinks

Interannual variability of the terrestrial ecosystem carbon sink is substantially regulated by various environmental variables and highly dominates the interannual variation of atmospheric carbon dioxide (CO₂) concentrations. Thus, it is necessary to determine dominating factors affecting the interannual variability of the carbon sink to improve our capability of predicting future terrestrial carbon sinks. Using global datasets derived from machine-learning methods and process-based ecosystem models, this study reveals that the interannual variability of the atmospheric vapor pressure deficit (VPD) was significantly negatively correlated with net ecosystem production (NEP) and substantially impacted the interannual variability of the atmospheric CO₂ growth rate (CGR). Further analyses found widespread constraints of VPD interannual variability on terrestrial gross primary production (GPP), causing VPD to impact NEP and CGR. Partial correlation analysis confirms the persistent and widespread impacts of VPD on terrestrial carbon sinks compared to other environmental variables. Current Earth system models underestimate the interannual variability in VPD and its impacts on GPP and NEP. Our results highlight the importance of VPD for terrestrial carbon sinks in assessing ecosystems’ responses to future climate conditions.

Projected soil organic carbon loss in response to climate warming and soil water content in a loess watershed

BACKGROUND

Soil organic carbon (SOC) plays a crucial role in the global carbon cycle and terrestrial ecosystem functions. It is widely known that climate change and soil water content (SWC) could influence the SOC dynamics; however, there are still debates about how climate change, especially climate warming, and SWC impact SOC. We investigated the spatiotemporal changes in SOC and its responses to climate warming and root-zone SWC change using the coupled hydro-biogeochemical model (SWAT-DayCent) and climate scenarios data derived under the three Representative Concentration Pathways (RCPs2.6, 4.5, and 8.5) from five downscaled Global Climate Models (GCMs) in a typical loess watershed--the Jinghe River Basin (JRB) on the Chinese Loess Plateau.

RESULTS

The air temperature would increase significantly during the future period (2017-2099), while the annual precipitation would increase by 2.0-13.1% relative to the baseline period (1976-2016), indicating a warmer and wetter future in the JRB. Driven by the precipitation variation, the root-zone SWC would also increase (by up to 27.9% relative to the baseline under RCP4.5); however, the SOC was projected to decrease significantly under the future warming climate. The combined effects of climate warming and SWC change could more reasonably explain the SOC loss, and this formed hump-shaped response surfaces between SOC loss and warming-SWC interactions under both RCP2.6 and 8.5, which can help explain diverse warming effects on SOC with changing SWC.

CONCLUSIONS

The study showed a significant potential carbon source under the future warmer and wetter climate in the JRB, and the SOC loss was largely controlled by future climate warming and the root-zone SWC as well. The hump-shaped responses of the SOC loss to climate warming and SWC change demonstrated that the SWC could mediate the warming effects on SOC loss, but this mediation largely depended on the SWC changing magnitude (drier or wetter soil conditions). This mediation mechanism about the effect of SWC on SOC would be valuable for enhancing soil carbon sequestration in a warming climate on the Loess Plateau.

Unusual characteristics of the carbon cycle during the 2015-2016 El Niño

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 CO₂ observations, we found both detrended atmospheric CO₂ growth rate (CGR) and CO₂ 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 CO₂ 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.

Dynamic characteristics and driving factors of vegetation greenness under changing environments in Xinjiang, China

Global environment changes rapidly alter regional hydrothermal conditions, which undoubtedly affects the spatiotemporal dynamics of vegetation, especially in arid and semi-arid areas. However, identifying and quantifying the dynamic evolution and driving factors of vegetation greenness under the changing environment are still a challenge. In this study, gradual trend analysis was applied to calculate the overall spatiotemporal trend of the normalized difference vegetation index (NDVI) time series of Xinjiang province in China, the abrupt change analysis was used to detect the timing of breakpoint and trend shift, and two machine learning methods (boosted regression tree and random forest) were used to quantify the key factors of vegetation change and their relative contribution rate. The results have shown that vegetation has experienced overall recovery over the past 20 years in Xinjiang, and greenness increased at a rate of 17.83 10^-4 year^-1. Cropland, grassland, and sparse vegetation were the main biome types where vegetation restoration is happening. Nearly 10% of the pixels (about 166000 km²) were detected to have breakpoints from 2004 to 2016 of the monthly NDVI, and most of the breakpoints were concentrated in the ecotone of various biomes. CO₂ concentration was the most prevalent environmental factor to increase vegetation greenness, because continuous emission of CO₂ greatly enhanced the fertilization effect, further promoted vegetation growth. Besides, cropland expansion and desertification control were the vital anthropogenic factors to vegetation turning "green" in Xinjiang, and most areas under anthropogenic were mainly in oasis areas. These findings provide new insights and measures for the regional response strategies and terrestrial ecosystem protection.

Interannual variation in rainfall modulates temperature sensitivity of carbon allocation and flux in a tropical montane wet forest

Tropical forests exert a disproportionately large influence on terrestrial carbon (C) balance but projecting the effects of climate change on C cycling in tropical forests remains uncertain. Reducing this uncertainty requires improved quantification of the independent and interactive effects of variable and changing temperature and precipitation regimes on C inputs to, cycling within and loss from tropical forests. Here, we quantified aboveground litterfall and soil-surface CO₂ efflux ("soil respiration"; F_S ) in nine plots organized across a highly constrained 5.2°C mean annual temperature (MAT) gradient in tropical montane wet forest. We used five consecutive years of these measurements, during which annual rainfall (AR) steadily increased, in order to: (a) estimate total belowground C flux (TBCF); (b) examine how interannual variation in AR alters the apparent temperature dependency (Q₁₀ ) of above- and belowground C fluxes; and (c) quantify stand-level C allocation responses to MAT and AR. Averaged across all years, F_S , litterfall, and TBCF increased positively and linearly with MAT, which accounted for 49, 47, and 46% of flux rate variation, respectively. Rising AR lowered TBCF and F_S , but increased litterfall, with patterns representing interacting responses to declining light. The Q₁₀ of F_S , litterfall, and TBCF all decreased with increasing AR, with peak sensitivity to MAT in the driest year and lowest sensitivity in the wettest. These findings support the conclusion that for this tropical montane wet forest, variations in light, water, and nutrient availability interact to strongly influence productivity (litterfall+TBCF), the sensitivity of above- and belowground C fluxes to rising MAT (Q₁₀ of F_S , litterfall, and TBCF), and C allocation patterns (TBCF:[litterfall+TBCF]).

Dynamics and Drivers of Grasslands in the Eurasian Steppe during 2000–2014

The Eurasian steppe (EAS) is the largest contiguous grassland worldwide. Quantitative evaluations of the relative impacts of climate change and human activities on grasslands are significant for understanding grassland degradation mechanisms and controlling degraded grasslands. In this study, we analyzed the grassland productivity based on multiple forms of net primary productivity (NPP), including climate NPP (CNPP), actual NPP (ANPP), and human-caused NPP (HNPP) during 2000–2014. The results demonstrate that the average value of annual ANPP in the EAS was 47.36 gC/(m2·year), with a weak decrease (−0.02 gC/(m2·year)) during the study period. The area of grassland degradation account for 48.52% of the total grassland area in EAS, while the area of grassland recovery account for 51.48%. Restorative grassland was mainly distributed in Mongolia and China, while worse grassland was mainly distributed in the Kazakh steppe regions. Grassland degradation in China was mainly caused by climate change, whereas it was mainly caused by human activities in Mongolia. Grassland recovery in Kazakh steppe regions was mainly caused by human activities, but in Mongolia, it was mainly caused by climate change. Compared with temperature, precipitation played a more significant role on grassland productivity.

Greening of the earth does not compensate for rising soil heterotrophic respiration under climate change

Stability of the soil carbon (C) pool under decadal scale variability in temperature and precipitation is an important source of uncertainty in our understanding of land-atmosphere climate feedbacks. This depends on how two opposing C-fluxes-influx from net primary production (NPP) and efflux from heterotrophic soil respiration (R_h )-respond to covariation in temperature and precipitation. There is scant evidence to judge whether field experiments which manipulate both temperature and precipitation align with Earth System Models, or not. As a result, even though the world is generally greening, whether the resultant gains in NPP can offset climate change impacts on R_h , where, and by how much, remains uncertain. Here, we use decadal-scale global time-series datasets on NPP, R_h , temperature, and precipitation to estimate the two opposing C-fluxes and address whether one can outpace the other. We implement machine-learning tools on recent (2001-2019) and near-future climate scenarios (2020-2040) to assess the response of both C-fluxes to temperature and precipitation variation. We find that changes in C-influx may not compensate for C-efflux, particularly in wetter and warmer conditions. Soil-C loss can occur in both tropics and at high latitudes since C-influx from NPP can fall behind C-efflux from R_h . Precipitation emerges as the key determinant of soil-C vulnerability in a warmer world, implying that hotspots for soil-C loss/gain can shift rapidly and highlighting that soil-C is vulnerable to climate change despite widespread greening of the world. The direction of covariation between change in temperature and precipitation, rather than their magnitude, can help conceptualize highly variable patterns in C-fluxes to guide soil-C stewardship.

Escherichia coli γ-carbonic anhydrase: characterisation and effects of simple aromatic/heterocyclic sulphonamide inhibitors

Carbonic anhydrases (CAs, EC 4.2.1.1) are ubiquitous metalloenzymes involved in biosynthetic processes, transport, supply, and balance of CO₂/HCO₃^- into the cell. In Bacteria, CAs avoid the depletion of the dissolved CO₂/HCO₃^- from the cell, providing them to the central metabolism that is compromised without the CA activity. The involvement of CAs in the survival, pathogenicity, and virulence of several bacterial pathogenic species is recent. Here, we report the kinetic properties of the recombinant γ-CA (EcoCAγ) encoded in the genome of Escherichia coli. EcoCAγ is an excellent catalyst for the physiological CO₂ hydration reaction to bicarbonate and protons, with a k_cat of 5.7 × 10⁵ s⁻¹ and k_cat/K_M of 6.9 × 10⁶ M⁻¹ s⁻¹. The EcoCAγ inhibition profile with a broad series of known CA inhibitors, the substituted benzene-sulphonamides, and clinically licenced drugs was explored. Benzolamide showed a K_I lower than 100 nM. Our study reinforces the hypothesis that the synthesis of new drugs capable of interfering selectively with the bacterial CA activity, avoiding the inhibition of the human α -CAs, is achievable and may lead to novel antibacterials.