Climate-induced changes in plant phenology and physiology are crucial in regulating terrestrial productivity and ecosystem functions. However, the spatiotemporal patterns of grassland phenology and its relationships with environmental factors remain unclear. We extracted phenological metrics from grasslands using the FLUXNET dataset (34 sites and 169 site-year). We then explored the spatiotemporal variations in phenological metrics, their relationships with gross primary productivity (GPP), and the driving mechanisms behind them using regression analysis and structural equation modeling methods. The start of the growing season (SOS) significantly advanced, whereas the end of the growing season (EOS) was slightly delayed (non-significant), leading to an extension of the growing season (LOS) (marginally significant) with increasing latitude northward. The multi-year averaged GPP in grassland sites was exponentially correlated with LOS and linearly correlated with maximum GPP (GPPmax). Phenological metrics exhibited linear relationships with mean annual temperature and quadratic relationships with mean annual precipitation (MAP). EOS, LOS, and GPPmax increased (SOS decreased) with MAP initially, then leveled off or decreased (SOS increased) when MAP reached a threshold of 1000 mm. Spatiotemporally, preseason soil water content (SWC) and air temperature significantly affected SOS, and wind speed was the dominant environmental driver for EOS. Structural equation modeling further suggested that decreasing wind speed might delay the EOS by reducing the atmospheric and soil dryness. In conclusion, our findings suggested that an improved grassland phenological model could project an advancing SOS, a delaying EOS, and an extension of LOS in response to decreasing wind speed and increased moisture in the future.

The high uncertainty regarding global gross primary production (GPP) remains unresolved. This study explored the relationships between phenology, physiology, and annual GPP to provide viable alternatives for accurate estimation. A statistical model of integrated phenology and physiology (SMIPP) was developed using GPP data from 145 FLUXNET sites to estimate the annual GPP for various vegetation types. By employing the SMIPP model driven by satellite-derived datasets of the global carbon uptake period (CUP) and maximal carbon uptake capacity (GPPmax), the global annual GPP was estimated for the period from 2001 to 2018. The results demonstrated that the SMIPP model accurately predicted annual GPP, with relative root mean square error values ranging from 11.20 to 19.29% for forest types and 20.49-35.71% for non-forest types. However, wetlands, shrublands, and evergreen forests exhibited relatively low accuracies. The average, trend, and interannual variation of global GPP during 2001-2018 were 132.6 Pg C yr-1, 0.25 Pg C yr-2, and 1.57 Pg C yr-1, respectively. They were within the ranges estimated in other global GPP products. Sensitivity analysis revealed that GPPmax had comparable effects to CUP in high-latitude regions but significantly greater impacts at the global scale, with sensitivity coefficients of 0.85 ± 0.23 for GPPmax and 0.46 ± 0.28 for CUP. This study provides a simple and practical method for estimating global annual GPP and highlights the influence of GPPmax and CUP on global-scale annual GPP.

BACKGROUND: Understanding temporal trends and varying responses of water use efficiency (WUE) to environmental changes of diverse ecosystems is key to predicting vegetation growth. WUE dynamics of major ecosystem types (e.g., forest, grassland and cropland) have been studied using various WUE definitions/metrics, but a comparative study on WUE dynamics and their driving forces among different ecosystem types using multiple WUE metrics is lacking. We used eddy covariance measurements for 42 FLUXNET2015 sites (396 site years) from 1997 to 2014, as well as three commonly used WUE metrics (i.e., ecosystem, inherent, and underlying WUE) to investigate the commonalities and differences in WUE trends and driving factors among deciduous broadleaf forests (DBFs), evergreen needleleaf forests (ENFs), grasslands, and croplands.
RESULTS: Our results showed that the temporal trends of WUE were not statistically significant at 73.8% of the forest, grassland and cropland sites, and none of the three WUE metrics exhibited better performance than the others in quantifying WUE. Meanwhile, the trends observed for the three WUE metrics were not significantly different among forest, grassland and cropland ecosystems. In addition, WUE was mainly driven by atmospheric carbon dioxide concentration at sites with significant WUE trends, and by vapor pressure deficit (VPD) at sites without significant trends (except cropland).
CONCLUSIONS: Our findings revealed the commonalities and differences in the application of three WUE metrics in disparate ecosystems, and further highlighted the important effect of VPD on WUE change.

Increased meteorological drought intensity with rising atmospheric demand for water (hereafter vapor pressure deficit [VPD]) increases the risk of tree mortality and ecosystem dysfunction worldwide. Ecosystem-scale water-use strategy is increasingly recognized as a key factor in regulating drought-related ecosystem responses. However, the link between water-use strategy and ecosystem vulnerability to meteorological droughts is poorly established. Using the global flux observations, historic hydroclimatic data, remote-sensing products, and plant functional-trait archive, we identified potentially vulnerable ecosystems, examining how ecosystem water-use strategy, quantified by the percentage bias (δ) of the empirical canopy conductance sensitivity to VPD relative to the theoretical value, mediated ecosystem responses to droughts. We found that prevailing soil water availability substantially impacted δ in dryland regions where ecosystems with insufficient soil moisture usually showed conservative water-use strategy, while ecosystems in humid regions exhibited more pronounced climatic adaptability. Hyposensitive and hypersensitive ecosystems, classified based on δ falling below or above the theoretical sensitivity, respectively, achieved similar net ecosystem productivity during droughts, employing different structural and functional strategies. However, hyposensitive ecosystems, risking their hydraulic system with a permissive water-use strategy, were unable to recover from droughts as quickly as hypersensitive ones. Our findings highlight that processed-based models predicting current functions and future performance of vegetation should account for the greater vulnerability of hyposensitive ecosystems to intensifying atmospheric and soil droughts.

Transpiration makes up the bulk of total evaporation in forested environments yet remains challenging to predict at landscape-to-global scales. We harnessed independent estimates of daily transpiration derived from co-located sap flow and eddy-covariance measurement systems and applied the triple collocation technique to evaluate predictions from big leaf models requiring no calibration. In total, four models in 608 unique configurations were evaluated at 21 forested sites spanning a wide diversity of biophysical attributes and environmental backgrounds. We found that simpler models that neither explicitly represented aerodynamic forcing nor canopy conductance achieved higher accuracy and signal-to-noise levels when optimally configured (rRMSE = 20%; R 2 = 0.89). Irrespective of model type, optimal configurations were those making use of key plant functional type dependent parameters, daily LAI, and constraints based on atmospheric moisture demand over soil moisture supply. Our findings have implications for more informed water resource management based on hydrological modeling and remote sensing.

Gross primary production (GPP) by terrestrial ecosystems is a key quantity in the global carbon cycle. The instantaneous controls of leaf-level photosynthesis are well established, but there is still no consensus on the mechanisms by which canopy-level GPP depends on spatial and temporal variation in the environment. The standard model of photosynthesis provides a robust mechanistic representation for C3 species; however, additional assumptions are required to \"scale up\" from leaf to canopy. As a consequence, competing models make inconsistent predictions about how GPP will respond to continuing environmental change. This problem is addressed here by means of an empirical analysis of the light use efficiency (LUE) of GPP inferred from eddy covariance carbon dioxide flux measurements, in situ measurements of photosynthetically active radiation (PAR), and remotely sensed estimates of the fraction of PAR (fAPAR) absorbed by the vegetation canopy. Focusing on LUE allows potential drivers of GPP to be separated from its overriding dependence on light. GPP data from over 100 sites, collated over 20 years and located in a range of biomes and climate zones, were extracted from the FLUXNET2015 database and combined with remotely sensed fAPAR data to estimate daily LUE. Daytime air temperature, vapor pressure deficit, diffuse fraction of solar radiation, and soil moisture were shown to be salient predictors of LUE in a generalized linear mixed-effects model. The same model design was fitted to site-based LUE estimates generated by 16 terrestrial ecosystem models. The published models showed wide variation in the shape, the strength, and even the sign of the environmental effects on modeled LUE. These findings highlight important model deficiencies and suggest a need to progress beyond simple \"goodness of fit\" comparisons of inferred and predicted carbon fluxes toward an approach focused on the functional responses of the underlying dependencies.

Subterranean ventilation is a non-diffusive transport process that provokes the abrupt transfer of CO2 -rich air (previously stored) through water-free soil pores and cracks from the vadose zone to the atmosphere, under high-turbulence conditions. In dryland ecosystems, whose biological carbon exchanges are poorly characterized, it can strongly determine eddy-covariance CO2 fluxes that are used to validate remote sensing products and constrain models of gross primary productivity. Although subterranean ventilation episodes (VE) may occur in arid and semi-arid regions, which are unsung players in the global carbon cycle, little research has focused on the role of VE CO2 emissions in land-atmosphere CO2 exchange. This study shows clear empirical evidence of globally occurring VE. To identify VE, we used in situ quality-controlled eddy-covariance open data of carbon fluxes and ancillary variables from 145 sites in different open land covers (grassland, cropland, shrubland, savanna, and barren) across the globe. We selected the analyzed database from the FLUXNET2015, AmeriFlux, OzFlux, and AsiaFlux networks. To standardize the analysis, we designed an algorithm to detect CO2 emissions produced by VE at all sites considered in this study. Its main requirement is the presence of considerable and non-spurious correlation between the friction velocity (i.e., turbulence) and CO2 emissions. Of the sites analyzed, 34% exhibited the occurrence of VE. This vented CO2 emerged mainly from arid ecosystems (84%) and sites with hot and dry periods. Despite some limitations in data availability, this research demonstrates that VE-driven CO2 emissions occur globally. Future research should seek a better understanding of its drivers and the improvement of partitioning models, to reduce uncertainties in estimated biological CO2 exchanges and infer their contribution to the global net ecosystem carbon balance.

The terrestrial net ecosystem productivity (NEP) has increased during the past three decades, but the mechanisms responsible are still unclear. We analyzed 17 years (2001-2017) of eddy-covariance measurements of NEP, evapotranspiration (ET) and light and water use efficiency from a boreal coniferous forest in Southern Finland for trends and inter-annual variability (IAV). The forest was a mean annual carbon sink (252 [ ± 42] gC m - 2 a - 1 ), and NEP increased at rate +6.4-7.0 gC m - 2 a - 1 (or ca. +2.5% a - 1 ) during the period. This was attributed to the increasing gross-primary productivity GPP and occurred without detectable change in ET. The start of annual carbon uptake period was advanced by 0.7 d a - 1 , and increase in GPP and NEP outside the main growing season contributed ca. one-third and one-fourth of the annual trend, respectively. Meteorological factors were responsible for the IAV of fluxes but did not explain the long-term trends. The growing season GPP trend was strongest in ample light during the peak growing season. Using a multi-layer ecosystem model, we showed that direct CO 2 fertilization effect diminishes when moving from leaf to ecosystem, and only 30-40% of the observed ecosystem GPP increase could be attributed to CO 2 . The increasing trend in leaf-area index (LAI), stimulated by forest thinning in 2002, was the main driver of the enhanced GPP and NEP of the mid-rotation managed forest. It also compensated for the decrease of mean leaf stomatal conductance with increasing CO 2 and LAI, explaining the apparent proportionality between observed GPP and CO 2 trends. The results emphasize that attributing trends to their physical and physiological drivers is challenged by strong IAV, and uncertainty of LAI and species composition changes due to the dynamic flux footprint. The results enlighten the underlying mechanisms responsible for the increasing terrestrial carbon uptake in the boreal zone.

Accurate simulation of gross primary productivity (GPP) is essential for estimating the global carbon budget. However, GPP modeling is subject to various sources of uncertainties, among which the impacts of biases in climate forcing data have not been well quantified. Here, using a well-validated vegetation model, we compare site-level simulations using either ground-based meteorology or assimilated reanalyses to identify climate-driven uncertainties in the predicted GPP at 91 FLUXNET sites. Simulations yield the lowest root mean square errors (RMSE) in GPP relative to observations when all site-level meteorology and CO2 concentrations are used. Sensitivity tests conducted with Modern-Era Retrospective Analysis (MERRA) reanalyses increase GPP RMSE by 30%. Replacement of site-level CO2 with global annual average values provides limited contributions to these changes. In contrast, GPP uncertainties increase almost linearly with the biases in meteorology. Among all factors, photosynthetically active radiation (PAR), especially diffuse PAR, plays dominant roles in modulating GPP uncertainties. Simulations using all MERRA forcings but with site-level diffuse PAR help reduce over 50% of the climate-driven biases in GPP. Our study reveals that biases in meteorological forcings, especially the variabilities at diurnal to seasonal time scales, can induce significant uncertainties in the simulated GPP at FLUXET sites. We suggest cautions in simulating global GPP using climate reanalyses for dynamic global vegetation models and urgent improvements in climatic variability in reanalyses data, especially for diffuse radiation.

Drought, a natural hydrometeorological phenomenon, has been more frequent and more widespread due to climate change. Water availability strongly regulates the coupling (or trade-off) between carbon uptake via photosynthesis and water loss through transpiration, known as water-use efficiency (WUE). Understanding the effects of drought on WUE across different vegetation types and along the wet to dry gradient is paramount to achieving better understanding of ecosystem functioning in response to climate change. We explored the physiological and environmental control on ecosystem WUE in response to drought using observations for 44 eddy covariance flux sites in the Northern Hemisphere. We quantified the response of WUE to drought and the relative contributions of gross primary production (GPP) and evapotranspiration (ET) to the variations of WUE. We also examined the control of physiological and environmental factors on monthly WUE under different moisture conditions. Cropland had a peak WUE value under moderate drought conditions, while grassland, deciduous broadleaf forest (DBF), evergreen broadleaf forest (EBF), and evergreen needleleaf forest (ENF) had peak WUE under slight drought conditions. WUE was mainly driven by GPP for cropland, grassland, DBF, and ENF but was mainly driven by ET for EBF. Vapor pressure deficit (VPD) and canopy conductance (Gc) were the most important factors regulating WUE. Moreover, WUE had negative responses to air temperature, precipitation, and VPD but had a positive response to Gc and ecosystem respiration. Our findings highlight the different effects of biotic and abiotic factors on WUE among different vegetation types and the important roles of VPD and Gc in controlling ecosystem WUE in response to drought.