Soil moisture dominates dryness stress on ecosystem production globally

Forest plant indicator values for moisture reflect atmospheric vapour pressure deficit rather than soil water content

Soil moisture shapes ecological patterns and processes, but it is difficult to continuously measure soil moisture variability across the landscape. To overcome these limitations, soil moisture is often bioindicated using community-weighted means of the Ellenberg indicator values of vascular plant species. However, the ecology and distribution of plant species reflect soil water supply as well as atmospheric water demand. Therefore, we hypothesized that Ellenberg moisture values can also reflect atmospheric water demand expressed as a vapour pressure deficit (VPD). To test this hypothesis, we disentangled the relationships among soil water content, atmospheric vapour pressure deficit, and Ellenberg moisture values in the understory plant communities of temperate broadleaved forests in central Europe. Ellenberg moisture values reflected atmospheric VPD rather than soil water content consistently across local, landscape, and regional spatial scales, regardless of vegetation plot size, depth as well as method of soil moisture measurement. Using in situ microclimate measurements, we discovered that forest plant indicator values for moisture reflect an atmospheric VPD rather than soil water content. Many ecological patterns and processes correlated with Ellenberg moisture values and previously attributed to soil water supply are thus more likely driven by atmospheric water demand.

Global influence of soil texture on ecosystem water limitation

Low soil moisture and high vapour pressure deficit (VPD) cause plant water stress and lead to a variety of drought responses, including a reduction in transpiration and photosynthesis1,2. When soils dry below critical soil moisture thresholds, ecosystems transition from energy to water limitation as stomata close to alleviate water stress3,4. However, the mechanisms behind these thresholds remain poorly defined at the ecosystem scale. Here, by analysing observations of critical soil moisture thresholds globally, we show the prominent role of soil texture in modulating the onset of ecosystem water limitation through the soil hydraulic conductivity curve, whose steepness increases with sand fraction. This clarifies how ecosystem sensitivity to VPD versus soil moisture is shaped by soil texture, with ecosystems in sandy soils being relatively more sensitive to soil drying, whereas ecosystems in clayey soils are relatively more sensitive to VPD. For the same reason, plants in sandy soils have limited potential to adjust to water limitations, which has an impact on how climate change affects terrestrial ecosystems. In summary, although vegetation-atmosphere exchanges are driven by atmospheric conditions and mediated by plant adjustments, their fate is ultimately dependent on the soil.

Improving global gross primary productivity estimation using two-leaf light use efficiency model by considering various environmental factors via machine learning

Distinguishing gross primary productivity (GPP) into sunlit (GPPsu) and shaded (GPPsh) components is critical for understanding the carbon exchange between the atmosphere and terrestrial ecosystems under climate change. Recently, the two-leaf light use efficiency (TL-LUE) model has proven effective for simulating global GPPsu and GPPsh. However, no known physical method has focused on integrating the overall constraint of intricate environmental factors on photosynthetic capability, and seasonal differences in the foliage clumping index (CI), which most likely influences GPP estimation in LUE models. Here, we propose the TL-CRF model, which uses the random forest technique to integrate various environmental variables, particularly for terrestrial water storage (TWS), into the TL-LUE model. Moreover, we consider seasonal differences in CI at a global scale. Based on 267 global eddy covariance flux sites, we explored the functional response of vegetation photosynthesis to key environmental factors, and trained and evaluated the TL-CRF model. The TL-CRF model was then used to simulate global eight-day GPP, GPPsu, and GPPsh from 2002 to 2020. The results show that the relative prediction error of environmental stress factors on the maximum LUE is reduced by approximately 52 % when these factors are integrated via the RF model. Thus the accuracy of global GPP estimation (R2 = 0.87, RMSE = 0.94 g C m-2 d-1, MAE = 0.61 g C m-2 d-1) in the TL-CRF model is greater than that (R2 = 0.76, RMSE = 2.18 g C m-2 d-1, MAE = 1.50 g C m-2 d-1) in the TL-LUE model, although this accuracy awaits further investigation among the released GPP products. TWS exerts the greatest control over ecosystem photosynthesis intensity, making it a suitable water indicator. Furthermore, the results confirm an optimal minimum air temperature for photosynthesis. Overall, these findings indicate a promising method for producing a new global GPP dataset, advancing our understanding of the dynamics and interactions between photosynthesis and environmental factors.

Strong positive direct impact of soil moisture on the growth of central asian grasslands

As the issue of global climate change becomes increasingly prominent, the grassland ecosystems in Central Asia are facing severe challenges posed by the impacts of climate change. However, the dominant factors, impact pathways, and cumulative and time-lagged effects of climate factors on various grassland indices remain to be explored. This study selected data from 1988 to 2019, including Fractional Vegetation Cover (FVC), Leaf Area Index (LAI), Net Primary Productivity (NPP), and Vegetation Optical Depth (VOD), to characterize grassland coverage, greenness, biomass accumulation, and water content features. Utilizing multiple linear regression, path analysis, and correlation analysis, this study investigated the dominant effects, direct impacts, indirect influences, and cumulative and time-lagged effects of climate factors on various grassland indices from spatial and climatic zone perspectives. The research findings indicate that over time, the grassland FVC and NPP exhibited increasing trends, while the LAI and VOD showed decreasing trends. Grassland indices are primarily influenced by precipitation and soil moisture (SM). The direct impact of SM on grassland indices was higher than precipitation. Vapour pressure deficit (VPD) has a direct negative impact on grassland indices. Grassland indices are subject to positive indirect effects from precipitation via SM and negative indirect effects from VPD via SM. Precipitation and SM mainly exhibited no cumulative and time-lagged effects on the impact of grassland VOD. VPD primarily demonstrated cumulative and time-lagged effects on grassland indices. The research findings offer valuable insights for conserving grassland ecosystems in Central Asia, as well as for shaping socioeconomic strategies and formulating climate policies.

Compound hot-dry events greatly prolong the recovery time of dryland ecosystems

Compound hot-dry events cause more severe impacts on terrestrial ecosystems than dry events, while the differences in recovery time (ΔRT) between hot-dry and dry events and their contributing factors remain unclear. Both remote sensing observations and eddy covariance measurements reveal that hot-dry events prolong the recovery time compared with dry events, with greater prolongation of recovery time in drylands than in humid regions. Random forest regression modeling demonstrates that the difference in vapor pressure deficit between hot-dry and dry events, with an importance score of 35%, is the major factor contributing to ΔRT. The severity of stomatal restriction exceeds that of non-stomatal limitation, which restricts the vegetation productivity that is necessary for the recovery process. These results emphasize the negative effect of vapor pressure deficit on vegetation recovery during hot-dry events and project an extension of drought recovery time considering elevated vapor pressure deficit in a warming world.

Exploring the comprehensive link between climatic factors and vegetation productivity in China

Understanding the influence of climatic factors on vegetation dynamics and cumulative effects is critical for global sustainable development. However, the response of vegetation to climate and the underlying mechanisms in different climatic zones remains unclear. In this study, we analyzed the response of vegetation gross primary productivity (GPP) to climatic factors and the cumulative effects across various vegetation types and climatic zones, utilizing data on precipitation (Pr), temperature (Ta), and the standardized precipitation evapotranspiration index (SPEI). The results showed that: (1) GPP showed significant differences among the seven climatic zones, with the highest value observed in zone VII, reaching 1860.07 gC·m- 2, and the lowest in zone I, at 126.03 gC·m- 2. (2) GPP was significantly and positively correlated with temperature in climatic zones I, IV, V, and VI and with precipitation in climatic zones I, II, and IV. Additionally, a significant positive correlated was found between SPEI and GPP in climatic zones I, II, and IV. (3) Drought exerted a cumulative effect on GPP in 45.10% of the regions within China, with an average cumulative duration of 5 months. These effects persisted for 6-8 months in zones I, II, and VII, and for 2-4 months in zones III, IV and VI. Among different vegetation types, forests experienced longest cumulative effect time of 6 months, followed by grasslands (5 months), croplands (4 months), and shrublands (4 months). The cumulative time scale decreased with increasing annual SPEI. The varying responses and accumulation of GPP to drought among different vegetation types in various climatic zones underscore the complexity of vegetation-climate interactions the response and accumulation of GPP to drought.

The impacts of rising vapour pressure deficit in natural and managed ecosystems

An exponential rise in the atmospheric vapour pressure deficit (VPD) is among the most consequential impacts of climate change in terrestrial ecosystems. Rising VPD has negative and cascading effects on nearly all aspects of plant function including photosynthesis, water status, growth and survival. These responses are exacerbated by land-atmosphere interactions that couple VPD to soil water and govern the evolution of drought, affecting a range of ecosystem services including carbon uptake, biodiversity, the provisioning of water resources and crop yields. However, despite the global nature of this phenomenon, research on how to incorporate these impacts into resilient management regimes is largely in its infancy, due in part to the entanglement of VPD trends with those of other co-evolving climate drivers. Here, we review the mechanistic bases of VPD impacts at a range of spatial scales, paying particular attention to the independent and interactive influence of VPD in the context of other environmental changes. We then evaluate the consequences of these impacts within key management contexts, including water resources, croplands, wildfire risk mitigation and management of natural grasslands and forests. We conclude with recommendations describing how management regimes could be altered to mitigate the otherwise highly deleterious consequences of rising VPD.

Global convergence in terrestrial gross primary production response to atmospheric vapor pressure deficit

Atmospheric vapor pressure deficit (VPD) increases with climate warming and may limit plant growth. However, gross primary production (GPP) responses to VPD remain a mystery, offering a significant source of uncertainty in the estimation of global terrestrial ecosystems carbon dynamics. In this study, in-situ measurements, satellite-derived data, and Earth System Models (ESMs) simulations were analysed to show that the GPP of most ecosystems has a similar threshold in response to VPD: first increasing and then declining. When VPD exceeds these thresholds, atmospheric drought stress reduces soil moisture and stomatal conductance, thereby decreasing the productivity of terrestrial ecosystems. Current ESMs underscore CO2 fertilization effects but predict significant GPP decline in low-latitude ecosystems when VPD exceeds the thresholds. These results emphasize the impacts of climate warming on VPD and propose limitations to future ecosystems productivity caused by increased atmospheric water demand. Incorporating VPD, soil moisture, and canopy conductance interactions into ESMs enhances the prediction of terrestrial ecosystem responses to climate change.

The multidimensionality of plant drought stress: The relative importance of edaphic and atmospheric drought

Drought threatens plant growth and related ecosystem services. The emergence of plant drought stress under edaphic drought is well studied, whilst the importance of atmospheric drought only recently gained momentum. Yet, little is known about the interaction and relative contribution of edaphic and atmospheric drought on the emergence of plant drought stress. We conducted a gradient experiment, fully crossing gravimetric water content (GWC: maximum water holding capacity-permanent wilting point) and vapour pressure deficit (VPD: 1-2.25 kPa) using five wheat varieties from three species (Triticum monococcum, T. durum & T. aestivum). We quantified the occurrence of plant drought stress on molecular (abscisic acid), cellular (stomatal conductance), organ (leaf water potential) and stand level (evapotranspiration). Plant drought stress increased with decreasing GWC across all organizational levels. This effect was magnified nonlinearly by VPD after passing a critical threshold of soil water availability. At around 20%GWC (soil matric potential 0.012 MPa), plants lost their ability to regulate leaf water potential via stomata regulation, followed by the emergence of hydraulic dysfunction. The emergence of plant drought stress is characterized by changing relative contributions of soil versus atmosphere and their non-linear interaction. This highly non-linear response is likely to abruptly alter plant-related ecosystem services in a drying world.

Monitoring Soybean Soil Moisture Content Based on UAV Multispectral and Thermal-Infrared Remote-Sensing Information Fusion

By integrating the thermal characteristics from thermal-infrared remote sensing with the physiological and structural information of vegetation revealed by multispectral remote sensing, a more comprehensive assessment of the crop soil-moisture-status response can be achieved. In this study, multispectral and thermal-infrared remote-sensing data, along with soil-moisture-content (SMC) samples (0~20 cm, 20~40 cm, and 40~60 cm soil layers), were collected during the flowering stage of soybean. Data sources included vegetation indices, texture features, texture indices, and thermal-infrared vegetation indices. Spectral parameters with a significant correlation level (p < 0.01) were selected and input into the model as single- and fuse-input variables. Three machine learning methods, eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Genetic Algorithm-optimized Backpropagation Neural Network (GA-BP), were utilized to construct prediction models for soybean SMC based on the fusion of UAV multispectral and thermal-infrared remote-sensing information. The results indicated that among the single-input variables, the vegetation indices (VIs) derived from multispectral sensors had the optimal accuracy for monitoring SMC in different soil layers under soybean cultivation. The prediction accuracy was the lowest when using single-texture information, while the combination of texture feature values into new texture indices significantly improved the performance of estimating SMC. The fusion of vegetation indices (VIs), texture indices (TIs), and thermal-infrared vegetation indices (TVIs) provided a better prediction of soybean SMC. The optimal prediction model for SMC in different soil layers under soybean cultivation was constructed based on the input combination of VIs + TIs + TVIs, and XGBoost was identified as the preferred method for soybean SMC monitoring and modeling, with its R2 = 0.780, RMSE = 0.437%, and MRE = 1.667% in predicting 0~20 cm SMC. In summary, the fusion of UAV multispectral and thermal-infrared remote-sensing information has good application value in predicting SMC in different soil layers under soybean cultivation. This study can provide technical support for precise management of soybean soil moisture status using the UAV platform.

Nonlinear effects of agricultural drought on vegetation productivity in the Yellow River Basin, China

Agricultural drought (AD) is the main environmental factor affecting vegetation productivity (VP) in the Yellow River Basin (YRB). In recent years, the nonlinear effects of AD on VP in the YRB have attracted much attention. However, it is still unclear whether fluctuating AD will have complex nonlinear effects on VP in the YRB, and there are scant previous studies at large scale on whether there is a threshold for nonlinear effects of AD on VP in the YRB. Therefore, this study used a newly developed agricultural drought index to explore nonlinear effects on VP revealing the nonlinear effects of AD on VP in the YRB. First, we developed a kernel temperature vegetation drought index (kTVDI) based on kernel normalized difference vegetation index (kNDVI) and land surface temperature data to study the spatiotemporal variation of AD in the YRB. Second, we used GPP data from solar-induced chlorophyll fluorescence inversion as an indicator to explore the spatiotemporal variation of VP in the YRB. Finally, we used several statistical indicators and a distributed lag nonlinear model (DLNM) to analyze the nonlinear effect of AD on VP in the YRB. The results showed that AD decreased significantly during 2000-2020, mainly in the southeast of the Loess Plateau, while GPP increased significantly in 80.93 % of the YRB. Meanwhile, moderate and severe AD stress limited VP growth, with the negative effects gradually decreasing, while mild AD had an increasingly positive promoting effect on VP. AD stress resulted in a VP decrease of 69.78 %, and severe AD stress resulted in a VP decrease of 65.52 %, mainly distributed in the northern Loess and Ordos Plateau. AD had significant nonlinear effects on VP. The effects of moderate and severe AD on the sustained nonlinear lag of vegetation were more obvious, and those of moderate and severe AD on the nonlinear lag of VP were the largest when the lag was approximately 1 month and 7 months. The effect of AD on the nonlinear hysteresis of VP in YRB was significantly different under different vegetation types, and forests were more able to withstand longer and more severe droughts than grasslands and croplands. The results of the study provide a theoretical basis for evaluating AD and analyzing the nonlinear impact of AD on VP. This will provide scientific basis for studying the mechanism of drought effect on vegetation in other regions.

Nonlinear time effects of vegetation response to climate change: Evidence from Qilian Mountain National Park in China

Vegetation responses to climate change are typically nonlinear with varied time effects, yet current research lacks comprehensiveness and precise definitions, hindering a deeper understanding of the underlying mechanisms. This study focuses on the mountain-type Qilian Mountain National Park (QMNP), investigating the characteristics and patterns of these nonlinear time effects using a generalized additive model (GAM) based on MODIS-NDVI, growing season temperature, and precipitation data. The results show that 1) The time effects of climate change on vegetation exhibit significant spatial variations, differing across vegetation types and topographic conditions. Accounting for optimal time effects can increase the explanatory power of climate on vegetation change by 6.8 %. Precipitation responses are mainly characterized by time-lag and time-accumulation effects, notably in meadows and steppes, while temperature responses are largely cumulative, especially in steppes. The altitude and slope significantly influence the pattern of vegetation response to climate, particularly in areas with high altitudes and steep slopes. 2) There is a significant nonlinear relationship between vegetation growth and both precipitation and temperature, with the nonlinear relationship between precipitation and vegetation being stronger than that with temperature, particularly in the western and central regions of the park. Different vegetation types exhibit significant variations in their response to climate change, with deserts and steppes being more sensitive to precipitation. 3) Precipitation is the primary driver of vegetation change in the QMNP, particularly for high-elevation vegetation and herbaceous vegetation. The complex temporal patterns of vegetation response to climate change in the QMNP not only deepen the understanding of the intricate relationship between regional vegetation and climate variability but also provide a methodological reference for global studies on vegetation responses to climate change.

Grassland productivity in arid Central Asia depends on the greening rate rather than the growing season length

Climate change has induced substantial impact on the gross primary productivity (GPP) of terrestrial ecosystems by affecting vegetation phenology. Nevertheless, it remains unclear which among the mean rates of grass greening (RG), yellowing (RY), and the length of growing season (LOS) exhibit stronger explanatory power for GPP variations, and how RG and RY affect GPP variations under warming scenarios. Here, we explored the relationship between RG, RY, LOS, and GPP in arid Central Asia (ACA) from 1982 to 2019, elucidating the response mechanisms of RG, RY, and GPP to the mean temperature (TMP), vapor pressure deficit (VPD), precipitation (PRE), and soil moisture (SM). The results showed that the multi-year average length of greening (LG) in ACA was 22.7 days shorter than that of yellowing (LY) and the multi-year average GPP during LG (GPPlg) was 38.28 g C m-2 d -1 more than that of during LY (GPPly). RG and RY were positively correlated with GPPlg and GPPly, although the degree of correlation between RG and GPPlg was higher than that between RY and GPPly. Increases in RG and RY contributed to an increase in GPPlg (55.44 % of annual GPP) and GPPly (35.44 % of annual GPP). The correlation between RG and GPPlg was the strongest (0.49), followed by RY and GPPly (0.33), and LOS and GPP was the weakest (0.21). TMP, VPD, PRE, and SM primarily affected GPP by influencing RG and RY, rather than direct effects. The positive effects of TMP during LG (TMPlg), PRE during LG (PRElg), and SM during LG (SMlg) facilitated increases in RG and GPPlg, and higher VPD during LY (VPDly) and lower PRE during LY (PREly) accelerated increases in RY. Our study elucidated the impact of vegetation growth rate on GPP, thus providing an alternate method of quantifying the relationship between vegetation phenology and GPP.

Soil moisture alters the responses of alpine ecosystem productivity to environmental factors, especially VPD, on the Qinghai-Tibetan Plateau

Water availability, which can be represented by soil water content (SWC), plays a crucial role in plant growth and productivity across the cold and arid Qinghai-Tibetan Plateau. However, the indirect effects of SWC are less well understood, and a more comprehensive understanding of its regulating effects may enhance the recognition of its importance, as this factor is pivotal for accurately predicting the future response of alpine ecosystems to climate change. In this study, in situ eddy covariance observation data from typical alpine ecosystems and satellite data covering the Qinghai-Tibetan region were used to comprehensively reveal the effects of SWC on ecosystem productivity. The results indicated that SWC played an important role in regulating the responses of gross primary productivity (GPP) to other environmental factors over both time and space, especially in terms of the responses of GPP to vapor pressure deficit (VPD). The regulating effect can be summarized as follows: there was a specific SWC value (SWC = 0.24 m3 m-3 on the Qinghai-Tibetan Plateau) above which SWC was no longer the primary limiting factor. The responses of GPP to certain environmental factors shifted from negative to positive when the SWC increased above this value. The responses of GPP to VPD exhibited the highest sensitivity to the regulating effects of SWC, with a general response pattern found across different temporal and spatial scales. The findings revealed divergent responses of GPP to environmental factors under different SWC conditions and between arid and humid regions, emphasizing the importance of soil water conditions. These findings suggest that water conditions should be given primary consideration in global change studies.

Radiative trigger thresholds of foliar photoprotective pigment regulation for global vegetation

Adjustments in foliar photoprotective pigments are crucial for plant adaptation to harsh environments, serving as indicators of environmental stress. However, understanding when and where these adjustments occur across diverse biomes remains unclear due to challenges in large-scale observation. Here, we propose a novel approach to assess dynamics in photoprotective pigments at the canopy level using a new index derived from space-borne optical sensors. This approach generates a global map depicting the daily mean shortwave radiation threshold at which adjustments typically occur under prevailing climatic conditions. The global average of this threshold is 262 ± 50 W m⁻2, with lower values at high latitudes and peaks near 40° in both hemispheres. Temperature exerts a stronger influence on this latitudinal pattern than humidity. Future projections suggest a decrease in this threshold over northern high latitudes, implying exacerbated vulnerability under identical radiation levels due to negative warming responses. Based on this threshold, a high-stress zone around 60°N is identified and is predicted to shift southward in the future. These findings bridge critical gaps in photoprotection research and offer a new perspective on understanding the biogeochemical cycles of global ecosystems. This framework can also enhance our ability to predict the fate of diverse ecosystems under future climate.

The effects of solar radiation on daily and seasonal stem increment of canopy trees in European temperate old-growth forests

It is well established that solar irradiance greatly influences tree metabolism and growth through photosynthesis, but its effects acting through individual climate metrics have not yet been well quantified. Understanding these effects is crucial for assessing the impacts of climate change on forest ecosystems. To describe the effects of solar irradiance on tree growth, we installed 110 automatic dendrometers in two old-growth mountain forest reserves in Central Europe, performed detailed terrestrial and aerial laser scanning to obtain precise tree profiles, and used these to simulate the sum of solar irradiance received by each tree on a daily basis. Generalized linear mixed-effect models were applied to simulate the probability of growth and the growth intensity over seven growing seasons. Our results demonstrated various contrasting effects of solar irradiance on the growth of canopy trees. On the one hand, the highest daily growth rates corresponded with the highest solar irradiance potentials (i.e. the longest photoperiod). Intense solar irradiance significantly decreased tree growth, through an increase in the vapor pressure deficit. These effects were consistent for all species but had different magnitude. Tree growth is the most effective on long rainy/cloudy days with low solar irradiance.

Understanding the effects of flash drought on vegetation photosynthesis and potential drivers over China

Flash droughts characterized by rapid onset and intensification are expected to be a new normal under climate change and potentially affect vegetation photosynthesis and terrestrial carbon sink. However, the effects of flash drought on vegetation photosynthesis and their potential dominant driving factors remain uncertain. Here, we quantify the susceptibility and response magnitude of vegetation photosynthesis to flash drought across different ecosystems (i.e., forest, shrubland, grassland, and cropland) in China based on reanalysis and satellite observations. By employing the extreme gradient boosting model, we also identify the dominant factors that influence these flash drought-photosynthesis relationships. We show that over 51.46 % of ecosystems across China are susceptible to flash drought, and grasslands are substantially suppressed, as reflected in both sensitivity and response magnitude (with median gross primary productivity anomalies of -0.13). We further demonstrate that background climate differences (e.g., mean annual temperature and aridity) predominantly regulate the response variation in forest and shrubland, with hotter/colder or drier ecosystems being more severely suppressed by flash drought. However, in grasslands and croplands, the differential vegetation responses are attributed to the intensity of abnormal hydro-meteorological conditions during flash drought (e.g., vapor pressure deficit (VPD) and temperature anomalies). The effects of flash droughts intensify with increasing VPD and nonmonotonically relate to temperature, with colder or hotter temperatures leading to more severe vegetation loss. Our results identify the vulnerable ecological regions under flash drought and enable a better understanding of vegetation photosynthesis response to climate extremes, which may be useful for developing effective management strategies.

Long-term species-level observations indicate the critical role of soil moisture in regulating China's grassland productivity relative to phenological and climatic factors

As a sensitive indicator of climate change and a key variable in ecosystem surface-atmosphere interaction, vegetation phenology, and the growing season length, as well as climatic factors (i.e., temperature, precipitation, and sunshine duration) are widely recognized as key factors influencing vegetation productivity. Recent studies have highlighted the importance of soil moisture in regulating grassland productivity. However, the relative importance of phenology, climatic factors, and soil moisture to plant species-level productivity across China's grasslands remains poorly understood. Here, we use nearly four decades (1981 to 2018) of in situ species-level observations from 17 stations distributed across grasslands in China to examine the key mechanisms that control grassland productivity. The results reveal that soil moisture is the strongest determinant of the interannual variability in grassland productivity. In contrast, the spring/autumn phenology, the length of vegetation growing season, and climate factors have relatively minor impacts. Generally, annual aboveground biomass increases by 3.9 to 25.3 g∙m2 (dry weight) with a 1 % increase in growing season mean soil moisture across the stations. Specifically, the sensitivity of productivity to moisture in wetter and colder environments (e.g., alpine meadows) is significantly higher than that in drier and warmer environments (e.g., temperate desert steppes). In contrast, the sensitivity to the precipitation of the latter is greater than the former. The effect of soil moisture is the most pronounced during summer. Dominant herb productivity is more sensitive to soil moisture than the others. Moreover, multivariate regression analyses show that the primary climatic factors and their attributions to variations in soil moisture differ among the stations, indicating the interaction between climate and soil moisture is very complex. Our study highlights the interspecific difference in the soil moisture dependence of grassland productivity and provides guidance to climate change impact assessments in grassland ecosystems.

Characterization and drivers of water and carbon fluxes dynamics in dune ecosystems of the Horqin Sandy Land

Sandy regions constitute pivotal components of terrestrial ecosystems, exerting significant influences on global ecological equilibrium and security. This study meticulously explored water and carbon fluxes dynamics within a dune ecosystem in the Horqin Sandy Land throughout the growing seasons from 2013 to 2022 by employing an advanced eddy covariance system. The dynamic characteristics of these fluxes and their underlying driving forces were extensively analyzed, with a particular focus on the impact of precipitation. The main results are as follows: (1) During the growing seasons of 2015 and 2016, the dune ecosystem acted as a modest carbon source, while in 2013, 2014, and 2017- 2022, it transformed into a net carbon sink. Notably, the annual mean values of water use efficiency (WUE) and evapotranspiration (ET) were 5.16 gC·kg-1H2O and 255.4 mm, respectively. (2) The intensity, frequency, and temporal distribution of precipitation were found to significantly influence the carbon and water fluxes dynamics. Isolated minor precipitation events did not trigger substantial fluctuations, but substantial and prolonged precipitation events spanning multiple days or consecutive minor precipitation events resulted in notable assimilation delays. (3) Air temperature, soil temperature, and fractional vegetation cover (FVC) were found to be key factors influencing the carbon and water fluxes. Specifically, FVC exhibited a negative logarithmic correlation with net ecosystem CO2 exchange (NEE) and a power function relationship with WUE. (4) The interaction between carbon and water fluxes is exhibited by exponential increases in ecosystem respiration (Reco) and gross primary productivity (GPP) with WUE, while NEE displayed an exponential decrease in relation to WUE. These findings are of high significance in predicting the potential ramifications of climate change on the intricate carbon and water cycles, and enhance our understanding of ecosystem dynamics in sandy environments.

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.

The urgency of building soils for Middle Eastern and North African countries: Economic, environmental, and health solutions

Soil degradation is a short or long ongoing process that limits ecosystem services. Intensive land use, water scarcity, land disturbance, and global climate change have reduced the quality of soils worldwide. This degradation directly threatens most of the land in the Middle East and North Africa, while the remaining areas are at high risk of further desertification. Rehabilitation and control of these damaged environments are essential to avoid negative effects on human well-being (e.g., poverty, food insecurity, wars, etc.). Here we review constructed soils involving the use of waste materials as a solution to soil degradation and present approaches to address erosion, organic matter oxidation, water scarcity and salinization. Our analysis showed a high potential for using constructed soil as a complimentary reclamation solution in addition to traditional ones. Constructed soils could have the ability to overcome the limitations of existing solutions to tackle land degradation while contributing to the solution of waste management problems. These soils facilitate the provision of multiple ecosystem services and have the potential to address particularly challenging land degradation problems in semi and dry climates.

Spatial and temporal variations of ecosystem water use efficiency and its response to soil moisture drought in a water-limited watershed of northern China

Drought synchronously affects the water cycle and interferes with the carbon cycle in terrestrial ecosystems. Ecosystem water use efficiency (WUE), serving as a vital metric for assessing the interplay between water and carbon cycles, has found extensively use in exploring how ecosystems responses to drought. However, the effects of soil moisture drought on WUE are still poorly recognized. Taking Ziya River Basin as an example, the spatial-temporal variations of WUE from 2001 to 2020 were estimated by the Penman-Monteith-Leuning Version 2 (PML-V2) data. Based on the Standardized Soil Moisture Index (SSI) calculated from Soil Moisture of China by in situ data, version 1.0 (SMCI1.0) data, the sensitivity and thresholds of different vegetation WUE to drought magnitudes were investigated, and the influences of both lagged and cumulative effects of drought on WUE were further analyzed. Results showed that the annual mean WUE was 2.160 ± 0.975 g C kg-1 H2O-1 in the Ziya River Basin, with a significant increasing trend of 0.037 g C kg-1 H2O-1 yr-1 (p < 0.05). For all the vegetation types, the WUE reached the maximum value at a certain drought threshold (SSI = -1.5 ± 0.1). The dominant factor controlling WUE sensitivity to drought changed from evapotranspiration (ET) to gross primary production (GPP) when severe drought transformed into extreme drought. Significant lagged and cumulative effects were found in the response of WUE to drought in nearly 58.64 % (72.94 %) of the study area, with an average time scale of 6.65 and 2.11 months (p < 0.05) respectively. Drought resistance in descending order was: forest > shrub > grassland > cropland. Our findings enrich the understanding of the coupled carbon and water cycle processes in terrestrial ecosystems and their response to soil moisture drought in the context of global climate change.

Changes in vegetation in China's drylands are closely related to afforestation compared with climate change

The response of vegetation to climate change and human activities has attracted considerable attention. However, quantitative studies on the effects of climate change and human activities on dryland vegetation in different seasons remain unclear. This study investigated the impacts of precipitation, temperature, soil water storage (SWS) (top [0-7 cm], shallow [7-28 cm], and middle [28-100 cm] layers), vapor pressure deficit (VPD), and afforestation on vegetation as well as their relative contribution rates during the rainy season ([RS], June to September), dry season ([DS], November to April), transition season ([TS], May and October), and all year period (AY) in China's drylands from 2001 to 2020 using the first-difference method. Areas with precipitation and SWS showing significant positive correlation with dryland vegetation (p < 0.05) were found to be larger in RS than in DS and TS, and the positive effect of SWS increased with soil depth in the 0-28 cm interval. Increasing VPD induced a significant negative effect on vgetation during RS but it was not predominant in DS and TS. Afforestation showed an extremely significant positive correlated with dryland vegetation across >60 % of China's dryland areas (p < 0.01), but this improvement was found to be limited to regions with the highest afforestation area. Moreover, dryland vegetation dynamics were driven by afforestation in all seasons, with contribution rates of 64.23 %-71.46 %. The effects of SWS and VPD on vegetation driven by precipitation and temperature exceeded the direct effects of precipitation and temperature. Among climatic factors, VPD showed a major regulating effect on dryland vegetation at the top and shallow soil layers in almost all seasons, whereas the relative contribution rate of SWS increased with soil layer. The findings can provide a scientific reference for the sustainable development and protection of drylands under global warming.

The Role of Climate Change and Its Sensitivity on Long-Term Standardized Precipitation Evapotranspiration Index, Vegetation and Drought Changing Trends over East Asia

Droughts have become more severe and frequent due to global warming. In this context, it is widely accepted that for drought assessments, both water supply (rainfall) and demand (standardized precipitation evapotranspiration index, SPEI) should be considered. Using SPEI, we explored the spatial-temporal patterns of dry and wet annual and seasonal changes in five sub-regions of East Asia during 1902-2018. These factors are linked to excess drought frequency and severity on the regional scale, and their effect on vegetation remains an important topic for climate change studies. Our results show that the SPEI significantly improved extreme drought and mostly affected the SPEI-06 and SPEI-12 growing seasons in East Asia during 1981-2018. The dry and wet annual SPEI trends mostly affect the five sub-regions of East Asia. The annual SPEI had two extremely dry spells during 1936-1947 and 1978-2018. Japan, South Korea, and North Korea are wet in the summer compared to other regions of East Asia, with drought frequency occurring at 51.4%, respectively. The mean drought frequencies in China and Mongolia are 57.4% and 54.6%. China and Mongolia are the driest regions in East Asia due to high drought frequency and duration. The spatial seasonal analysis of solar radiation (SR), water vapor pressure (WVP), wind speed (WS), vegetation condition index (VCI), temperature condition index (TCI), and vegetation health index (VHI) have confirmed that the East Asia region suffered from maximum drought events. The seasonal variation of SPEI shows no clear drying trends during summer and autumn seasons. During the winter and spring seasons, there was a dry trend in East Asia region. During 1902-1990, a seasonal SPEI presented diverse characteristics, with clear wet trends in Japan, Mongolia, and North Korea in four different growing seasons, with dry trends in China and South Korea. During 1991-2018, seasonal SPEI presented clear dry trends in Japan, Mongolia, and North Korea in different growing seasons, while China and South Korea showed a wet trend during the spring, autumn, and winter seasons. This ecological and climatic mechanism provides a good basis for the assessment of vegetation and drought-change variations within East Asia. An understandings of long-term vegetation trends and the effects of rainfall and SPEI on droughts of varying severity is essential for water resource management and climate change adaptation. Based on the results, water resources will increase under global warming, which may alleviate the water scarcity issue in the East Asia region.

The negative-positive feedback transition thresholds of meteorological drought in response to agricultural drought and their dynamics

There are complex bidirectional feedback relationships among different types of droughts (e.g., meteorological and agricultural droughts). As agricultural drought intensifies, meteorological drought response to agricultural drought may be changed from negative to positive feedback. Nevertheless, the negative-positive feedback transition thresholds of meteorological drought in response to agricultural drought and their dynamics have remained unsolved. Herein, we proposed a new quantitative method to characterize the mutual feedback between meteorological drought and agricultural drought based on the vine copula function for the first time in this study. The negative-positive feedback transition threshold and the sensitivity of the feedback were quantified under certain drought conditions. In order to investigate the feedback relationship dynamics under a changing environment, the total study period was evenly divided into two stages: stage 1 (1982-1999) and stage 2 (2000-2018). Finally, the random forest method was used to explore the dominant factors on the transition threshold. Results indicate that: (1) the negative-positive feedback transition thresholds in August is generally lower than June and July in mainland China, the basin with large threshold is the Southwest River Basin; (2) the sensitivity of meteorological drought in response to agricultural drought was higher in positive feedback than in negative feedback; (3) the transition thresholds of stage 2 was mostly reduced, while the feedback sensitivity of positive feedback was mostly increased; and (4) compared with the single factor, the land-meteorological coupling strength (the correlation between precipitation and soil moisture) dominants the negative-positive feedback transition threshold. This study sheds new insights into droughts feedback.

A water stress factor based on normalized difference water index substantially improved the accuracy of light use efficiency model for arid and semi-arid grasslands

High-accuracy simulation of gross primary productivity (GPP) is crucial for the monitoring and evaluation of the ecosystem services and the adaptive management of grassland. The light use efficiency (LUE) model is one of the most widely-used methods to simulate GPP, given its simple structure and low input requirements. Current LUE models are less applicable to grasslands than other vegetation types and have lower overall estimation accuracy in arid and semi-arid regions. A grassland-specific light use efficiency model (GRASS-LUE), which optimizes three important parameters (the fraction of absorbed photosynthetically active radiation FPAR, optimum temperature Topt and water stress factor f(W)), has been developed to improve the accuracy of GPP simulation for grasslands along aridity gradients. GPP simulated by the GRASS-LUE agreed well with the eddy covariance (EC) GPP estimates for grasslands along the aridity gradient at 8-day (coefficient of determination (R2) = 0.85, Bias = -0.67 gC m-2 day-1), monthly (R2 = 0.88, Bias = -22.33 gC m-2 month-1) and annual time scales (R2 = 0.95, Bias = -118.91 gC m-2 year-1). Compared with five state-of-the-art GPP products (PML, MOD17, rEC-LUE, VPM and BESS), GRASS-LUE had the best and most stable performance in reproducing EC GPP, especially for semi-arid grassland, with the highest global performance indicator (GPI) value. Sensitivity tests further revealed that: 1) modifying f(W) to be based on the Normalized Difference Water Index (NDWI) substantially improved the model accuracy for arid and semi-arid grasslands and 2) using the minimum of temperature and water stress factors (i.e., min⁡(f(W),f(T))) to represent environmental stress in GRASS-LUE was better than that from the multiplication of temperature and water stress factors (i.e., f(W)×f(T)).

Fog controls biological cycling of soil phosphorus in the Coastal Cordillera of the Atacama Desert

Soils in hyper-arid climates, such as the Chilean Atacama Desert, show indications of past and present forms of life despite extreme water limitations. We hypothesize that fog plays a key role in sustaining life. In particular, we assume that fog water is incorporated into soil nutrient cycles, with the inland limit of fog penetration corresponding to the threshold for biological cycling of soil phosphorus (P). We collected topsoil samples (0-10 cm) from each of 54 subsites, including sites in direct adjacency (<10 cm) and in 1 m distance to plants, along an aridity gradient across the Coastal Cordillera. Satellite-based fog detection revealed that Pacific fog penetrates up to 10 km inland, while inland sites at 10-23 km from the coast rely solely on sporadic rainfall for water supply. To assess biological P cycling we performed sequential P fractionation and determined oxygen isotope of HCl-extractable inorganicP δ 18 O HCl - P i $$ \mathrm{P}\ \left({\updelta}^{18}{\mathrm{O}}_{\mathrm{HCl}-{\mathrm{P}}_{\mathrm{i}}}\right) $$ . Total P (Pt ) concentration exponentially increased from 336 mg kg-1 to a maximum of 1021 mg kg-1 in inland areas ≥10 km. With increasing distance from the coast, soilδ 18 O HCl - P i $$ {\updelta}^{18}{\mathrm{O}}_{\mathrm{HCl}-{\mathrm{P}}_{\mathrm{i}}} $$ values declined exponentially from 16.6‰ to a constant 9.9‰ for locations ≥10 km inland. Biological cycling of HCl-Pi near the coast reached a maximum of 76%-100%, which could only be explained by the fact that fog water predominately drives biological P cycling. In inland regions, with minimal rainfall (<5 mm) as single water source, only 24 ± 14% of HCl-Pi was biologically cycled. We conclude that biological P cycling in the hyper-arid Atacama Desert is not exclusively but mainly mediated by fog, which thus controls apatite dissolution rates and related occurrence and spread of microbial life in this extreme environment.

Climatic limitations on grassland photosynthesis over the Tibetan Plateau shifted from temperature to water

Plant photosynthesis plays an essential role in regulating the global carbon cycle. Therefore, it is essential to understand the limitations imposed by climate on plant photosynthesis to comprehend the impacts of climate change on land carbon dynamics. In this study, taking gross primary productivity as a direct representation of photosynthesis, we employed a light use efficiency model (i.e., the revised EC-LUE) and factorial analysis method to quantify the spatiotemporal variation of temperature- and water-limitations on plant photosynthesis over the Tibetan Plateau (TP) grasslands during growing season (May to October) in 1983-2018. Results revealed a clear spatiotemporal pattern of the temperature- and water-limitations: temperature is the primary climatic limiting factor in the eastern TP, while water is the primary climatic limiting factor in the western TP; the water- and temperature-limitations prevail in summer and spring/autumn, respectively. The water- and temperature-limitations intensified and alleviated, respectively, during 1983 through 2018. There also was a widespread shift from temperature-limitation to water-limitation in the TP, particularly in midsummer (August). Our findings demonstrated the shifting relative importance of climatic limitations on plant photosynthesis under changing climate, which is crucial for predicting future terrestrial carbon cycle dynamics.

Divergent impacts of VPD and SWC on ecosystem carbon-water coupling under different dryness conditions

Ecosystem water use efficiency (WUE) is an indicator of carbon-water interactions and is defined as the ratio of gross primary productivity (GPP) to evapotranspiration (ET). However, it is currently unclear how WUE responds to atmospheric and soil drought events in terrestrial ecosystems with different dryness conditions. Additionally, the contributions of GPP and ET to the WUE response remain poorly understood. Based on measurements from 26 flux tower sites distributed worldwide, the binning method and random forest model were employed to separate the sensitivities of daily ecosystem WUE, GPP, and ET to vapor pressure deficit (VPD) and soil water content (SWC) under different dryness conditions (dryness index = potential evapotranspiration/precipitation, DI). Results showed that the sensitivity of WUE to VPD was negative at humid sites (DI < 1), while the sensitivity of WUE to SWC was positive at arid sites (DI > 2). Furthermore, the contribution of GPP to VPD-induced WUE variability was 63 % at humid sites, and the contribution of ET to SWC-induced WUE variability was 68 % when SWC was less than the 60th percentile at arid sites. Consequently, one increasing VPD-induced decrease in GPP was generally linked to a decrease in WUE at humid sites, and one drying soil moisture-caused decrease in ET was linked to a WUE increase under low SWC conditions at arid sites. Finally, VPD had a stronger effect on WUE than SWC when VPD was less than the 90th percentile or SWC was greater than the 50th percentile. Our findings underscore the importance of considering ecosystem dryness when investigating the impacts of VPD and SWC on ecosystem carbon-water coupling.

Climate-dependent responses of root and shoot biomass to drought duration and intensity in grasslands-a meta-analysis

Understanding the effects of altered precipitation regimes on root biomass in grasslands is crucial for predicting grassland responses to climate change. Nonetheless, studies investigating the effects of drought on belowground vegetation have produced mixed results. In particular, root biomass under reduced precipitation may increase, decrease or show a delayed response compared to shoot biomass, highlighting a knowledge gap in the relationship between belowground net primary production and drought. To address this gap, we conducted a meta-analysis of nearly 100 field observations of grassland root and shoot biomass changes under experimental rainfall reduction to disentangle the main drivers behind grassland responses to drought. Using a response-ratio approach we tested the hypothesis that water scarcity would induce a decrease in total biomass, but an increase in belowground biomass allocation with increased drought length and intensity, and that climate (as defined by the aridity index of the study location) would be an additional predictor. As expected, meteorological drought decreased root and shoot biomass, but aboveground and belowground biomass exhibited contrasting responses to drought duration and intensity, and their interaction with climate. In particular, drought duration had negative effects on root biomass only in wet climates while more intense drought had negative effects on root biomass only in dry climates. Shoot biomass responded negatively to drought duration regardless of climate. These results show that long-term climate is an important modulator of belowground vegetation responses to drought, which might be a consequence of different drought tolerance and adaptation strategies. This variability in vegetation responses to drought suggests that physiological plasticity and community composition shifts may mediate how climate affects carbon allocation in grasslands, and thus ultimately carbon storage in soil.

Soil erodibility for water and wind erosion and its relationship to vegetation and soil properties in China's drylands

Drylands with fragile socio-ecological systems are vulnerable to soil erosion. China's drylands face the dual threat of water (WAE) and wind erosion (WIE). To mitigate soil erosion in drylands, China has implemented numerous ecological restoration measures. However, whether vegetation and soil have different effects on soil erodibility for water erosion (soil erodibility, K) and wind erosion (soil erodible fraction, EF) in drylands is unclear, hindering decision makers to develop suitable ecological restoration strategies. Here, we conducted a large-scale belt transect survey to explore the spatial variation of K and EF in China's drylands, and examined the linear and nolinear effects of aridity (aridity index), vegetation (fractional vegetation cover and below-ground biomass), and soil properties (bulk density, total nitrogen, and total phosphorus) on K and EF. The results showed in China's drylands that the K ranges from 0.02 to 0.07, with high values recorded in the northern Loess Plateau and the eastern Inner Mongolia Plateau. The EF ranges from 0.26 to 0.98, and shows longitudinal zonation with higher values in the east and lower values in the west. Aridity has a negative linear effect on K and an inverse U-shaped nonlinear effect on EF. Aridity can affect K and EF by suppressing vegetation growth and disrupting soil properties. However, K and EF had different responses to some vegetation and soil variables. K and EF had opposite relationships with soil bulk density, and EF was significantly affected by fractional vegetation cover, while K was not. Overall, the effects of aridity and soil properties on soil erodibility were more pronounced than those from vegetation, whose effect on soil erodibility was limited. This study provides relevant information to support reducing soil water and wind erosion by highlighting the hotspot areas of soil erodibility, relevant for implementing vegetation restoration and soil conservation measures in drylands.

Global diagnosis of land-atmosphere coupling based on water isotopes

Land-atmosphere coupling (LAC) plays a significant role in weather and climate and is related to droughts and heatwaves. We propose a simple and efficient LAC diagnosis method based on the analysis of water isotopes in atmospheric water vapour and precipitation. Using the method, we identify the primary LAC hotspot regions of the globe and reveal the seasonality of LAC strength. We find that LAC strength exhibits a relationship with latitude. Low latitudes present stronger LAC strength and contribute more significantly to the overall LAC area compared to boreal middle and high latitudes. It's important to note that LAC primarily manifests in the troposphere and is detected in the lower stratosphere of low latitudes, with limited influence observed in the stratosphere. However, the impact of LAC is noticeable in the upper stratosphere in boreal middle and high latitudes. Moreover, the seasonality of LAC strength is pronounced. On a global scale, the season with the strongest LAC is boreal autumn in the Northern Hemisphere but boreal summer in the Southern Hemisphere. Notably, this pattern does not exhibit a seesaw effect between the two hemispheres. Our isotope-based LAC diagnosis method captures the major LAC hotspots found in previous work and validates the seasonality of LAC within these hotspots. This substantiates the reliability and effectiveness of our isotope-based approach.

Diverse responses of gross primary production and leaf area index to drought on the Mongolian Plateau

Drought is a crucial factor regulating vegetation growth on the Mongolian Plateau (MP). Previous studies of drought effects on the MP have mainly concentrated on drought characterization, while the response of vegetation to drought remains unclear. To close this knowledge gap, we examined the response of MP vegetation to drought in terms of gross primary production (GPP) and leaf area index (LAI) from 1982 to 2018. Our findings show that intra-seasonally the frequency of drought occurrence in autumn had a greater impact on GPP (relative importance over 70 %), while the intensity of drought was more influential for LAI (relative importance approximately 60 %). Inter-seasonally, summer droughts had the most pronounced effect on vegetation (with median standardized anomalies of -0.72 for GPP and -0.4 for LAI, respectively). Additionally, we found that meteorological drought was more consistent with atmospheric aridity (high vapor pressure deficit) than soil drought (low soil moisture). This study advances knowledge of vegetation's susceptibility to climate extremes and improves the precision of predicting ecosystem response to climate change.

Warming-induced vapor pressure deficit suppression of vegetation growth diminished in northern peatlands

Recent studies have reported worldwide vegetation suppression in response to increasing atmospheric vapor pressure deficit (VPD). Here, we integrate multisource datasets to show that increasing VPD caused by warming alone does not suppress vegetation growth in northern peatlands. A site-level manipulation experiment and a multiple-site synthesis find a neutral impact of rising VPD on vegetation growth; regional analysis manifests a strong declining gradient of VPD suppression impacts from sparsely distributed peatland to densely distributed peatland. The major mechanism adopted by plants in response to rising VPD is the "open" water-use strategy, where stomatal regulation is relaxed to maximize carbon uptake. These unique surface characteristics evolve in the wet soil‒air environment in the northern peatlands. The neutral VPD impacts observed in northern peatlands contrast with the vegetation suppression reported in global nonpeatland areas under rising VPD caused by concurrent warming and decreasing relative humidity, suggesting model improvement for representing VPD impacts in northern peatlands remains necessary.

Precipitation and vegetation transpiration variations dominate the dynamics of agricultural drought characteristics in China

Agricultural drought posing a significant threat to agricultural production is subject to the complex influence of ocean, terrestrial and meteorological multi-factors. Nevertheless, which factor dominating the dynamics of agricultural drought characteristics and their dynamic impact remain equivocal. To address this knowledge gap, we used ERA5 soil moisture to calculate the standardized soil moisture index (SSI) to characterize agricultural drought. The extreme gradient boosting model was then adopted to fully examine the influence of ocean, terrestrial and meteorological multi-factors on agricultural drought characteristics and their dynamics in China. Meanwhile, the Shapley additive explanation values were introduced to quantify the contribution of multiple drivers to drought characteristics. Our analysis reveals that the drought frequency, severity and duration in China ranged from 5-70, 2.15-35.02 and 1.76-31.20, respectively. Drought duration is increasing and drought intensity is intensifying in southeast, north and northwest China. In addition, potential evapotranspiration is the most significant driver of drought characteristics at the basin scale. Regarding the dynamic evolution of drought characteristics, the percentages of raster points for drought duration and severity with evapotranspiration as the dominant factor are 30.7 % and 32.7 %, and the percentages with precipitation are 35.3 % and 35.0 %, respectively. Precipitation in northern regions has a positive effect on decreasing drought characteristics, while in southern regions, evapotranspiration dominates the dynamics in drought characteristics due to increasing vegetation transpiration. Moreover, the drought severity is exacerbated by the Atlantic Multidecadal Oscillation in the Yangtze and Pearl River basins, while the contribution of the North Atlantic Oscillation to the drought duration evolution is increasing in the Yangtze River basin. Generally, this study sheds new insights into agricultural drought evolution and driving mechanism, which are beneficial for agricultural drought early warning and mitigation.

Nitrogen addition delays the emergence of an aridity-induced threshold for plant biomass

Crossing certain aridity thresholds in global drylands can lead to abrupt decays of ecosystem attributes such as plant productivity, potentially causing land degradation and desertification. It is largely unknown, however, whether these thresholds can be altered by other key global change drivers known to affect the water-use efficiency and productivity of vegetation, such as elevated CO2 and nitrogen (N). Using >5000 empirical measurements of plant biomass, we showed that crossing an aridity (1-precipitation/potential evapotranspiration) threshold of ∼0.50, which marks the transition from dry sub-humid to semi-arid climates, led to abrupt declines in aboveground biomass (AGB) and progressive increases in root:shoot ratios, thus importantly affecting carbon stocks and their distribution. N addition significantly increased AGB and delayed the emergence of its aridity threshold from 0.49 to 0.55 (P < 0.05). By coupling remote sensing estimates of leaf area index with simulations from multiple models, we found that CO2 enrichment did not alter the observed aridity threshold. By 2100, and under the RCP 8.5 scenario, we forecast a 0.3% net increase in the global land area exceeding the aridity threshold detected under a scenario that includes N deposition, in comparison to a 2.9% net increase if the N effect is not considered. Our study thus indicates that N addition could mitigate to a great extent the negative impact of increasing aridity on plant biomass in drylands. These findings are critical for improving forecasts of abrupt vegetation changes in response to ongoing global environmental change.

Comparison, validation and improvement of empirical soil moisture models for conditions in Colombia

Modeling soil moisture as a function of meteorological data is necessary for agricultural applications, including irrigation scheduling. In this study, empirical water balance models and empirical compartment models are assessed for estimating soil moisture, for three locations in Colombia. The daily precipitation and average, maximum and minimum air temperatures are the input variables. In the water balance type models, the evapotranspiration term is based on the Hargreaves model, whereas the runoff and percolation terms are functions of precipitation and soil moisture. The models are calibrated using field data from each location. The main contributions compared to closely related studies are: i) the proposal of three models, formulated by combining an empirical water balance model with modifications in the precipitation, runoff, percolation and evapotranspiration terms, using functions recently proposed in the current literature and incorporating new modifications to these terms; ii) the assessment of the effect of model parameters on the fitting quality and determination of the parameters with higher effects; iii) the comparison of the proposed empirical models with recent empirical models from the literature in terms of the combination of fitting accuracy and number of parameters through the Akaike Information Criterion (AIC), and also the Nash-Sutcliffe (NS) coefficient and the root mean square error. The best models described soil moisture with an NS efficiency higher than 0.8. No single model achieved the highest performance for the three locations.

Study on spatio-temporal simulation and prediction of regional deep soil moisture using machine learning

Deep soil moisture (SM) plays a crucial role in vegetation restoration, particularly in semi-arid areas. However, current SM products have limited access and do not meet the spatio-temporal scale and soil depth requirements in eco-hydrological research. Thus, this study constructs a random forest prediction model for SM at different depths by identifying driving factors and quantifying the correlation effect of vertical SM based on the international SM network dataset. Subsequently, the SMAP product is integrated into the model to expand SM from point scale to regional scale, yielding an SM data product with a suitable scale and continuous time and space. The results indicate that the correlation between precipitation and SM changes into the interaction between adjacent SM layers as the depth increases. The lag time of SM in the shallow surface layer (0-3 cm) to precipitation was 1 day, and there was no delay on the daily scale in the 3-20 cm layers of the three underlying surface types. The response time of 50 cm SM to 20 cm SM was 1-2 days in cropland and grassland and 2 days in forest. Slope, land use type, clay proportion, leaf area index, potential evapotranspiration, and land surface temperature were the key driving factors of SM in the Shandian River region. The random forest model established in this study demonstrated good prediction performance for SM at both site and regional scales. The obtained daily products had higher spatial fineness than CLDAS products and could describe the SM characteristics of different underlying surfaces. This study offers new ideas and technical support for acquiring deep SM data in arid and semi-arid areas of northern China.

Disentangling the effects of vapor pressure deficit on northern terrestrial vegetation productivity

The impact of atmospheric vapor pressure deficit (VPD) on plant photosynthesis has long been acknowledged, but large interactions with air temperature (T) and soil moisture (SM) still hinder a complete understanding of the influence of VPD on vegetation production across various climate zones. Here, we found a diverging response of productivity to VPD in the Northern Hemisphere by excluding interactive effects of VPD with T and SM. The interactions between VPD and T/SM not only offset the potential positive impact of warming on vegetation productivity but also amplifies the negative effect of soil drying. Notably, for high-latitude ecosystems, there occurs a pronounced shift in vegetation productivity's response to VPD during the growing season when VPD surpasses a threshold of 3.5 to 4.0 hectopascals. These results yield previously unknown insights into the role of VPD in terrestrial ecosystems and enhance our comprehension of the terrestrial carbon cycle's response to global warming.

Enhanced dominance of soil moisture stress on vegetation growth in Eurasian drylands

Despite the mounting attention being paid to vegetation growth and their driving forces for water-limited ecosystems, the relative contributions of atmospheric and soil moisture dryness stress on vegetation growth are an ongoing debate. Here we comprehensively compare the impacts of high vapor pressure deficit (VPD) and low soil water content (SWC) on vegetation growth in Eurasian drylands during 1982-2014. The analysis indicates a gradual decoupling between atmospheric dryness and soil dryness over this period, as the former has expanded faster than the latter. Moreover, the VPD-SWC relation and VPD-greenness relation are both non-linear, while the SWC-greenness relation is near-linear. The loosened coupling between VPD and SWC, the non-linear correlations among VPD-SWC-greenness and the expanded area extent in which SWC acts as the dominant stress factor all provide compelling evidence that SWC is a more influential stressor than VPD on vegetation growth in Eurasian drylands. In addition, a set of 11 Earth system models projected a continuously growing constraint of SWC stress on vegetation growth towards 2100. Our results are vital to dryland ecosystems management and drought mitigation in Eurasia.

Decline in stability of forest productivity in the tropics as determined by canopy water content

The impacts of low soil moisture (SM) and high vapour pressure deficit (VPD) on tree's photosynthesis and productivity are ultimately realized by changing water content in the canopy leaves. In this study, variations in canopy water content (CWC) that can be detected from microwave remotely sensed vegetation optical depth (VOD) have been proposed as a promising measure of vegetation water status, and we first reported that the regulation of CWC on productivity stability is universally applicable for global forests. Results of structural equation model (SEM) also confirmed the significant negative effect of CWC on coefficient of variation (CV) of productivity, indicating that the decrease in CWC could inevitably induce the instability of forest productivity under climate change. The most significant decrease (p < 0.01) of CWC is observed primarily in evergreen broadleaf forest in the tropics, implying an increasing instability of the most important carbon sink in terrestrial ecosystem.

A multi-satellite framework to rapidly evaluate extreme biosphere cascades: The Western US 2021 drought and heatwave

The increasing frequency and intensity of climate extremes and complex ecosystem responses motivate the need for integrated observational studies at low latency to determine biosphere responses and carbon-climate feedbacks. Here, we develop a satellite-based rapid attribution workflow and demonstrate its use at a 1-2-month latency to attribute drivers of the carbon cycle feedbacks during the 2020-2021 Western US drought and heatwave. In the first half of 2021, concurrent negative photosynthesis anomalies and large positive column CO2 anomalies were detected with satellites. Using a simple atmospheric mass balance approach, we estimate a surface carbon efflux anomaly of 132 TgC in June 2021, a magnitude corroborated independently with a dynamic global vegetation model. Integrated satellite observations of hydrologic processes, representing the soil-plant-atmosphere continuum (SPAC), show that these surface carbon flux anomalies are largely due to substantial reductions in photosynthesis because of a spatially widespread moisture-deficit propagation through the SPAC between 2020 and 2021. A causal model indicates deep soil moisture stores partially drove photosynthesis, maintaining its values in 2020 and driving its declines throughout 2021. The causal model also suggests legacy effects may have amplified photosynthesis deficits in 2021 beyond the direct effects of environmental forcing. The integrated, observation framework presented here provides a valuable first assessment of a biosphere extreme response and an independent testbed for improving drought propagation and mechanisms in models. The rapid identification of extreme carbon anomalies and hotspots can also aid mitigation and adaptation decisions.

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.

Evaluating gross primary productivity over 9 ChinaFlux sites based on random forest regression models, remote sensing, and eddy covariance data

Accurate modeling of Gross Primary Productivity (GPP) in terrestrial ecosystems is a major challenge in quantifying the carbon cycle. Many light use efficiency (LUE) models have been developed, but the variables and algorithms used for environmental constraints in different models vary importantly. It is still unclear whether the models can be further improved by machine learning methods and the combination of different variables. Here, we have developed a series of RFR-LUE models, which used the random forest regression (RFR) algorithm based on variables of LUE models, to explore the potential of estimating site-level GPP. Based on remote sensing indices, eddy covariance and meteorological data, we applied RFR-LUE models to evaluate the effects of different variables combined on GPP on daily, 8-day, 16-day and monthly scales, respectively. Cross-validation analyses revealed performances of RFR-LUE models varied significantly among sites with R² of 0.52-0.97. Slopes of the regression relationship between simulated and observed GPP ranged from 0.59 to 0.95. Most models performed better in capturing the temporal changes and magnitude of GPP in mixed forests and evergreen needle-leaf forests than in evergreen broadleaf forests and grasslands. Performances were improved at the longer temporal scale, with the average R² for four-time resolutions of 0.81, 0.87, 0.88, and 0.90, respectively. Additionally, the importance of the variables showed that temperature and vegetation indices were critical variables for RFR-LUE models, followed by radiation and moisture variables. The importance of moisture variables was higher in non-forests than in forests. A comparison with four GPP products indicated that RFR-LUE model predicted GPP better matcher observed GPP across sites. The study provided an approach to deriving GPP fluxes and evaluating the extent to which variables affect GPP estimation. It may be used for predicting vegetation GPP at the regional scales and for calibration and evaluation of land surface process models.

Effects of vegetation restoration on soil properties and vegetation attributes in the arid and semi-arid regions of China

Driven by the goal of reversing desertification and recovering degraded lands, a wide range of vegetation restoration practices (such as planting and fencing) have been implemented in China's drylands. It is essential to examine the effects of vegetation restoration and environmental factors on soil nutrients to optimize restoration approaches. However, quantitative evaluation on this topic is insufficient due to a lack of long-term field monitoring data. This study evaluated the effects of sandy steppe restoration and sand dune fixation in the semi-arid desert, and natural and artificial vegetation restoration in the arid desert. It considered soil and plant characteristics using long-term (2005-2015) data from the Naiman Research Station located in the semi-arid region and Shapotou Research Station in the arid region of China's drylands. Results showed the sandy steppe had higher soil nutrient contents, vegetation biomass and rate of accumulating soil organic matter (OM) than the fixed dunes and moving dunes. Soil nutrient contents and vegetation biomass of the natural vegetation of Artemisia ordosica were higher than those of the artificial restoration of Artemisia ordosica since 1956. Artificial restoration had a higher rate of accumulating soil OM, total nitrogen (TN) and grass litter biomass than natural restoration. Soil water indirectly affected soil OM by affecting vegetation. Grass diversity was the main influencing factor on soil OM variance in the semi-arid Naiman desert while shrub diversity was the main factor in the arid Shapotou desert. These findings indicate that sand fixation in the semi-arid desert and vegetation restoration in the arid desert bring benefits for soil nutrient accumulation and vegetation improvement, and that natural restoration is preferable to artificial restoration. Results can be used to formulate sustainable vegetation restoration strategies, such as encouraging natural restoration, considering local resource constraints, and giving priority to restoring shrubs in arid areas with limited water.

Dew benefits on alpine grasslands are cancelled out by combined heatwave and drought stress

Increasing frequencies of heatwaves combined with simultaneous drought stress in Europe threaten the ecosystem water and carbon budgets of alpine grasslands. Dew as an additional water source can promote ecosystem carbon assimilation. It is known that grassland ecosystems keep high evapotranspiration as long as soil water is available. However, it is rarely being investigated whether dew can mitigate the impact of such extreme climatic events on grassland ecosystem carbon and water exchange. Here we use stable isotopes in meteoric waters and leaf sugars, eddy covariance fluxes for H₂O vapor and CO₂, in combination with meteorological and plant physiological measurements, to investigate the combined effect of dew and heat-drought stress on plant water status and net ecosystem production (NEP) in an alpine grassland (2000 m elevation) during the June 2019 European heatwave. Before the heatwave, enhanced NEP in the early morning hours can be attributed to leaf wetting by dew. However, dew benefits on NEP were cancelled out by the heatwave, due to the minor contribution of dew in leaf water. Heat-induced reduction in NEP was intensified by the combined effect of drought stress. The recovery of NEP after the peak of the heatwave could be linked to the refilling of plant tissues during nighttime. Among-genera differences of plant water status affected by dew and heat-drought stress can be attributed to differences in their foliar dew water uptake, and their reliance on soil moisture or the impact of the atmospheric evaporative demand. Our results indicate that dew influence on alpine grassland ecosystems varies according to the environmental stress and plant physiology.

Impacts of vegetation restoration on water resources and carbon sequestration in the mountainous area of Haihe River basin, China

The mountainous region of the Haihe River basin (MHRB) plays an important role in the water resource supply of its nearby mega-cities, including Beijing and Tianjin, and large areas of cropland. With the implementation of afforestation projects in recent decades, vegetation and carbon (C) uptake have greatly increased in the MHRB. In addition, the annual runoff has significantly declined, threatening regional water security. The trade-off relationship between water yield and C uptake in the MHRB remains unknown. This study employed a biogeochemical model (Biome-BGC) to simulate the natural vegetation dynamics and gross primary productivity (GPP) during 1982-2019 driven by climate forcing. A distributed hydrological model (geomorphology-based hydrological model, GBHM) was adopted to assess the impact of vegetation restoration on the hydrological processes. The results indicated that the leaf area index in the MHRB increased significantly (P < 0.01) during 1982-2019, which led to evapotranspiration increase and runoff (R) reduction. Under the influence of vegetation restoration, both the GPP and the water use efficiency (WUE) increased significantly in the MHRB during 2000-2019, however, the improvement of WUE decreased with the aridity index increasing. Our results showed that vegetation restoration can improve C sequestration efficiency in the MHRB and that the trade-off between water yield and C sequestration should be considered in planning ecological projects to achieve C neutrality.

Spatiotemporal evolution of global long-term patterns of soil moisture

Surface soil moisture (SM) is essential for existence of biotic lifeform and geophysical processes. However, with increasing global warming due to climatic changes, its spatiotemporal evolution is uncertain and largely unknown. In this study we detected long-term (40 years; 1981-2020) SM patterns of global vegetated areas through spatial timeseries clustering using the state-of-the-art ERA5-Land dataset. In addition, we also analyzed long-term patterns of precipitation (P), evapotranspiration (bare soil evaporation (BSe) and vegetation transpiration (VT)), and normalized difference vegetation index (NDVI). Our results indicate that surface SM (0-7 cm depth) of about 48 % and 9 % of the global vegetated area is showing drying and wetting pattern over the past 40 years, respectively. The detected soil drying, and wetting patterns were largely consistent across different soil depth, with 90 % and 80 % pattern similarity of surface soil layer with 2^nd soil layer (7-28 cm) and 3^rd soil layer (28-100 cm), respectively. About 80 % of areas with drying soil pattern also showed increasing evapotranspiration and/or decreasing precipitation. Specifically, decreasing P, increasing BSe and VT pattern were detected for 11 % of the soil drying pattern area. Similarly, increasing BSe and VT pattern, only decreasing P and only increasing VT pattern were detected for 17 %, 25 % and 12 % of soil drying areas, respectively. Both decreasing precipitation and increasing evapotranspiration patterns showed about 40 % similarity with decreasing soil moisture patterns. Across different landcover types, broadleaved forests, and cropland areas showed largest drying pattern. Under the future global warming scenario, the global soil water is expected to decrease as evapotranspiration would increase with inconsistent trend of global precipitation change. Our findings are of utmost importance for global soil water resource conservation and management.

Contrasting responses of peak vegetation growth to asymmetric warming: Evidences from FLUXNET and satellite observations

The peak growth of plant in summer is an important indicator of the capacity of terrestrial ecosystem productivity, and ongoing studies have shown its responses to climate warming as represented in the mean temperature. However, the impacts from the asymmetrical warming, that is, different rates in the changes of daytime (T_max ) and nighttime (T_min ) warming were mostly ignored. Using 60 flux sites (674 site-year in total) measurements and satellite observations from two independent satellite platforms (Global Inventory Monitoring and Modeling Studies [1982-2015]; MODIS [2000-2020]) over the Northern Hemisphere (≥30°N), here we show that the peak growth, as represented by both flux-based maximum primary productivity and the maximum greenness indices (maximum normalized difference vegetation index and enhanced vegetation index), responded oppositely to daytime and nighttime warming. T max - T min + (peak growth showed negative responses to T_max , but positive responses to T_min ) dominated in most ecosystems and climate types, especially in water-limited ecosystems, while T max + T min - (peak growth showed positive responses to T_max , but negative responses to T_min ) was primarily observed in high latitude regions. These contrasting responses could be explained by the strong association between asymmetric warming and water conditions, including soil moisture, evapotranspiration/potential evapotranspiration, and the vapor pressure deficit. Our results are therefore important to the understanding of the responses of peak growth to climate change, and consequently a better representation of asymmetrical warming in future ecosystem models by differentiating the contributions between daytime and nighttime warming.