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

Stability of gross primary productivity and its sensitivity to climate variability in China

Identifying the stability and sensitivity of land ecosystems to climate change is vital for exploring nature-based solutions. However, the underlying mechanisms governing ecosystem stability and sensitivity, especially in regions with overlapping ecological projects, remain unclear. based on Mann-Kendall, stability analysis method, and multiple regression method, this study quantified the stability and sensitivity of gross primary productivity (GPP) to climate variables [temperature, vapor pressure deficit (VPD), soil moisture, and radiation] in China from 1982 to 2019. Our findings revealed the following: (1) GPP demonstrated an increased trend with lower stability in Eastern regions, whereas a decreasing trend with higher stability was observed in Western and Southwest China. Notably, the stability of GPP was highest (74.58%) in areas with five overlapping ecological projects: Grain to Green, Natural Forest Resource Protection Project, Three-River Ecological Conservation and Restoration Project, Return Grazing to Grassland Project, and Three-North Shelter Forestation Project. (2) In regions with minimal or no overlapping ecological projects, temperature and radiation jointly dominated GPP variations. In contrast, water-related factors (VPD and soil moisture) significantly affected GPP in areas with multiple overlapping ecological projects. (3) In the southwestern and northeastern regions, GPP exhibited the highest sensitivity to climate change, whereas, in the eastern coastal areas and Tibet, GPP showed low sensitivity to climate change. In the Loess Plateau, where five ecological projects overlap extensively, carbon sinks primarily demonstrate a monotonic increasing trend, high stability, and low sensitivity to climate change. This study aimed to assess the stability of the land ecosystems and delineate their sensitivity to climate changes, thereby laying the groundwork for understanding ecosystem resilience.

Atmospheric drought dominates changes in global water use efficiency

Water use efficiency (defined as the ratio of gross primary productivity to plant transpiration, WUET) describes the tradeoff between ecosystem carbon uptake and water loss. However, a comprehensive understanding of the impact of soil and atmospheric moisture deficits on WUET across large regions remains incomplete. Solar-induced chlorophyll fluorescence (SIF) serves as an effective signal for measuring both terrestrial vegetation photosynthesis and transpiration, thereby enabling a rapid response to changes in the physiological status of plants under water stress. The objectives of this study were to: 1) mechanistically calculate WUET using top-of-canopy SIF data and meteorological information by using the revised mechanistic light response model and the Penman-Monteith equation; 2) analyze the effects of atmospheric and soil water deficits on SIF-based WUET by using decoupled soil water content (SWC) and vapor pressure deficit (VPD); 3) evaluate estimated SIF-based WUET against data from 28 eddy covariance (EC) flux sites representing eight different vegetation types. Results indicated that the model performed well in ecosystems with dense canopies, explaining 56 % of the daily variability in EC tower-based WUET. For the years 2019-2020, the global average WUET derived from SIF was 3.49 g C/kg H2O. Notably, this value exceeded 4 g C/kg H2O in tropical rainforest regions near the equator and went beyond 5 g C/kg H2O in the high-latitude regions of the Northern Hemisphere. We found that SIF-based WUET was primarily influenced by VPD rather than SWC in over 90 % of the global vegetated area. The model used in this study increased our ability to mechanistically estimate WUET with SIF at the global scale, thereby highlighting the significance of the global response of SIF-based WUET to water stress, and also enhancing our understanding of the water‑carbon cycle in terrestrial ecosystems.

An optimal ensemble of the CoLM for simulating the carbon and water fluxes over typical forests in China

Stomatal conductance (gs) and compensatory water uptake (CWU) are crucial processes in land surface models, as they directly influence the exchange of carbon and water fluxes between terrestrial ecosystems and the atmosphere. In this study, we integrated a new stomatal scheme derived from optimal stomatal theory (Medlyn's gs model), and an empirical CWU scheme into the Common Land Model (CoLM). Assessing the impacts on modeling gross primary productivity (GPP) and latent flux (LE) through observations obtained from eddy covariance (EC) measurements at three forest sites in China. Our results show that replacing the Ball-Berry's gs model (termed BB) with Medlyn's gs model (termed MED) did not bring about significant changes (had neutral impacts) in the performance of CoLM simulations at three forest sites. Considering the climate factors of annual mean precipitation to optimize key fitting parameters in gs exhibited improvement in model simulations. The average coefficient of determination (R2) achieved to 0.65 for GPP and LE at three sites, and the normalized root mean squared error (NRMSE) decreased from 0.83 to 0.77 at those sites. Besides, incorporating CWU into the model improved its performance. The R2 increased to 0.84 and RMSE decreased to 4.84 μmol m-2 s-1 for GPP, and the R2 increased to 0.62 and RMSE decreased to 55.64 W m-2 for LE. Therefore, modifying the model process of both contributed more to enhancing the model simulations than relying solely on one of these functions. Our study highlights that the response of plant functional types (PFTs) to water stress can be effectively represented in gs models when coupled with biochemical capacity to quantify carbon and water fluxes in forest ecosystems or other ecosystems.

High resolution climate change observations and projections for the evaluation of heat-related extremes

The Climate Hazards Center Coupled Model Intercomparison Project Phase 6 climate projection dataset (CHC-CMIP6) was developed to support the analysis of climate-related hazards, including extreme humid heat and drought conditions, over the recent past and in the near-future. Global daily high resolution (0.05°) grids of the Climate Hazards InfraRed Temperature with Stations temperature product, the Climate Hazards InfraRed Precipitation with Stations precipitation product, and ERA5-derived relative humidity form the basis of the 1983-2016 historical record, from which daily Vapor Pressure Deficits (VPD) and maximum Wet Bulb Globe Temperatures (WBGTmax) were derived. Large CMIP6 ensembles from the Shared Socioeconomic Pathway 2-4.5 and SSP 5-8.5 scenarios were then used to develop high resolution daily 2030 and 2050 'delta' fields. These deltas were used to perturb the historical observations, thereby generating 0.05° 2030 and 2050 projections of daily precipitation, temperature, relative humidity, and derived VPD and WBGTmax. Finally, monthly counts of frequency of extremes for each variable were derived for each time period.

Drivers of contemporary and future changes in Arctic seasonal transition dates for a tundra site in coastal Greenland

Climate change has had a significant impact on the seasonal transition dates of Arctic tundra ecosystems, causing diverse variations between distinct land surface classes. However, the combined effect of multiple controls as well as their individual effects on these dates remains unclear at various scales and across diverse land surface classes. Here we quantified spatiotemporal variations of three seasonal transition dates (start of spring, maximum normalized difference vegetation index (NDVImax ) day, end of fall) for five dominating land surface classes in the ice-free Greenland. Using a distributed snow model, structural equation modeling, and a random forest model, based on ground observations and remote sensing data, we assessed the indirect and direct effects of climate, snow, and terrain on seasonal transition dates. We then presented new projections of likely changes in seasonal transition dates under six future climate scenarios. The coupled climate, snow cover, and terrain conditions explained up to 61% of seasonal transition dates across different land surface classes. Snow ending day played a crucial role in the start of spring and timing of NDVImax . A warmer June and a decline in wind could advance the NDVImax day. Increased precipitation and temperature during July-August are the most important for delaying the end of fall. We projected that a 1-4.5°C increase in temperature and a 5%-20% increase in precipitation would lengthen the spring-to-fall period for all five land surface classes by 2050, thus the current order of spring-to-fall lengths for the five land surface classes could undergo notable changes. Tall shrubs and fens would have a longer spring-to-fall period under the warmest and wettest scenario, suggesting a competitive advantage for these vegetation communities. This study's results illustrate controls on seasonal transition dates and portend potential changes in vegetation composition in the Arctic under climate change.

The influence of variations in actual evapotranspiration on drought in China's Southeast River basin

Revealing changes in actual evapotranspiration is essential to understanding regional extreme hydrological events (e.g., droughts). This study utilized the Global Land Evaporation Amsterdam Model (GLEAM) to analyse the spatial and temporal characteristics of actual evapotranspiration over 40 years in the Southeast River basin of China. The relationship between changes in actual evapotranspiration and the drought index was quantified. The results indicated a significant increase in actual evapotranspiration in the Southeast River basin from 1981 to 2020 (2.51 mm/year, p < 0.01). The actual evapotranspiration components were dominated by vegetation transpiration (73.45%) and canopy interception (18.26%). The actual evapotranspiration was closely related to the normalised difference vegetation index (r = 0.78, p < 0.01), and vegetation changes could explain 10.66% of the increase of actual evapotranspiration in the Southeast River basin since 2000. Meanwhile, actual evapotranspiration and standardised precipitation evapotranspiration index (SPEI) showed a highly significant negative spatial correlation, with a Moran's I index of - 0.513. The rise in actual evapotranspiration is an important trigger factor for seasonal droughts in the region. Therefore, these results help deepen the understanding of hydro-climatic process changes in the southeastern coastal region of China.

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.

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.

Effects of soil moisture, net radiation, and atmospheric vapor pressure deficit on surface evaporation fraction at a semi-arid grass site

Surface energy partitioning is one of the most important aspects of the land-atmosphere coupling. The objective of this study is to examine how soil moisture (SM) and atmospheric conditions (net radiation, Rn and vapor pressure deficit, VPD) affect surface evaporation fraction (EF, determined by LE/(LE + H), where LE and H are latent and sensible heat flux, respectively) with measurements at a semi-arid grass site in China during the mid-growing season, 2020. The three factors (SM, Rn, and VPD) were divided into different levels, and then their effects on EF were investigated qualitatively using a combinatorial stratification method and quantificationally using a path analysis. Generally, the results indicated that the effect of one factor of SM, Rn and VPD on EF was influenced by the other two factors. EF tended to increase with increasing SM. Increased VPD (Rn) enhanced (weakened) the SM-EF relationship. When soil was dry, EF tended to decrease with increasing VPD; when soil was wet, EF initially levelled off and then decreased with increasing VPD. Increased Rn enhanced (weakened) the positive (negative) effect of VPD on EF when soil was wet (dry). In terms of Rn effect, EF tended to decrease as Rn increases. Further, path analysis suggested that SM, Rn, and VPD not only directly affected EF, but also indirectly affected EF, mainly through canopy conductance (Gs) and temperature difference between land surface and air (∆T). The direct effect of SM accounted for >50 % of its total effect on EF, while the total effects of Rn and VPD on EF were dominated by their indirect effects. These observational evidences may have implications for improving representation of land-atmosphere coupling in atmospheric general circulation models over the semi-arid regions covered by grass.

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.