ABSTRACT
During extensive periods without rain, known as dry-downs, decreasing soil moisture (SM) induces plant water stress at the point when it limits evapotranspiration, defining a critical SM threshold (θcrit). Better quantification of θcrit is needed for improving future projections of climate and water resources, food production, and ecosystem vulnerability. Here, we combine systematic satellite observations of the diurnal amplitude of land surface temperature (dLST) and SM during dry-downs, corroborated by in-situ data from flux towers, to generate the observation-based global map of θcrit. We find an average global θcrit of 0.19 m3/m3, varying from 0.12 m3/m3 in arid ecosystems to 0.26 m3/m3 in humid ecosystems. θcrit simulated by Earth System Models is overestimated in dry areas and underestimated in wet areas. The global observed pattern of θcrit reflects plant adaptation to soil available water and atmospheric demand. Using explainable machine learning, we show that aridity index, leaf area and soil texture are the most influential drivers. Moreover, we show that the annual fraction of days with water stress, when SM stays below θcrit, has increased in the past four decades. Our results have important implications for understanding the inception of water stress in models and identifying SM tipping points.
Subject(s)
Ecosystem , Soil , Water , Soil/chemistry , Water/metabolism , Temperature , Plant Transpiration/physiology , Plants/metabolism , Dehydration , Plant Leaves/physiology , Climate , Rain , Machine LearningABSTRACT
The vulnerability of plant xylem to embolism can be described as the water potential at which xylem conductivity is lost by 50% (P50). According to the traditional hypothesis of hydraulic vulnerability segmentation, the difference in vulnerability to embolism between branches and roots is positive (P50 root-branch > 0). It is not clear whether this occurs broadly across species or how segmentation might vary across aridity gradients. We compiled hydraulic and anatomical datasets from branches and roots across 104 woody species (including new measurements from 10 species) in four biomes to investigate the relationships between P50 root-branch and environmental factors associated with aridity. We found a positive P50 root-branch relationship across species, and evidence that P50 root-branch increases with aridity. Branch xylem hydraulic conductivity transitioned from more efficient (e.g., wider conduit, higher hydraulic conductivity) to safer (e.g., narrower conduit, more negative P50) in response to the increase of aridity, while root xylem hydraulic conductivity remained unchanged across aridity gradients. Our results demonstrate that the hydraulic vulnerability difference between branches and roots is more positive in species from arid regions, largely driven by modifications to branch traits.
Subject(s)
Plant Roots , Xylem , WaterABSTRACT
A central role for nature-based solution is to identify optimal management practices to address environmental challenges, including carbon sequestration and biodiversity conservation. Inorganic fertilization increases plant aboveground biomass but often causes a tradeoff with plant diversity loss. It remains unclear, however, whether organic fertilization, as a potential nature-based solution, could alter this tradeoff by increasing aboveground biomass without plant diversity loss. Here we compile data from 537 experiments on organic and inorganic fertilization across grasslands and croplands worldwide to evaluate the responses of aboveground biomass, plant diversity, and soil organic carbon (SOC). Both organic and inorganic fertilization increase aboveground biomass by 56% and 42% relative to ambient, respectively. However, only inorganic fertilization decreases plant diversity, while organic fertilization increases plant diversity in grasslands with greater soil water content. Moreover, organic fertilization increases SOC in grasslands by 19% and 15% relative to ambient and inorganic fertilization, respectively. The positive effect of organic fertilization on SOC increases with increasing mean annual temperature in grasslands, a pattern not observed in croplands. Collectively, our findings highlight organic fertilization as a potential nature-based solution that can increase two ecosystem services of grasslands, forage production, and soil carbon storage, without a tradeoff in plant diversity loss.
Subject(s)
Biodiversity , Biomass , Carbon , Fertilizers , Grassland , Soil , Soil/chemistry , Fertilizers/analysis , Carbon/metabolism , Carbon/analysis , Carbon Sequestration , Ecosystem , Agriculture/methods , Crops, Agricultural/growth & development , Conservation of Natural Resources/methodsABSTRACT
Linking individual and stand-level dynamics during forest development reveals a scaling relationship between mean tree size and tree density in forest stands, which integrates forest structure and function. However, the nature of this so-called scaling law and its variation across broad spatial scales remain unquantified, and its linkage with forest demographic processes and carbon dynamics remains elusive. In this study, we develop a theoretical framework and compile a broad-scale dataset of long-term sample forest stands (n = 1,433) from largely undisturbed forests to examine the association of temporal mean tree size vs. density scaling trajectories (slopes) with biomass accumulation rates and the sensitivity of scaling slopes to environmental and demographic drivers. The results empirically demonstrate a large variation of scaling slopes, ranging from -4 to -0.2, across forest stands in tropical, temperate, and boreal forest biomes. Steeper scaling slopes are associated with higher rates of biomass accumulation, resulting from a lower offset of forest growth by biomass loss from mortality. In North America, scaling slopes are positively correlated with forest stand age and rainfall seasonality, thus suggesting a higher rate of biomass accumulation in younger forests with lower rainfall seasonality. These results demonstrate the strong association of the transient mean tree size vs. density scaling trajectories with forest demography and biomass accumulation rates, thus highlighting the potential of leveraging forest structure properties to predict forest demography, carbon fluxes, and dynamics at broad spatial scales.
ABSTRACT
Spring vegetation growth can benefit summer growth by increasing foliage area and carbon sequestration potential, or impair it by consuming additional resources needed for sustaining subsequent growth. However, the prevalent driving mechanism and its temporal changes remain unknown. Using satellite observations and long-term atmospheric CO2 records, here we show a weakening trend of the linkage between spring and summer vegetation growth/productivity in the Northern Hemisphere during 1982-2021. This weakening is driven by warmer and more extreme hot weather that becomes unfavourable for peak-season growth, shifting peak plant functioning away from earlier periods. This is further exacerbated by seasonally growing ecosystem water stress due to reduced water supply and enhanced water demand. Our finding suggests that beneficial carryover effects of spring growth on summer growth are diminishing or even reversing, acting as an early warning sign of the ongoing shift of climatic effects from stimulating to suppressing plant photosynthesis during the early to peak seasons.
Subject(s)
Ecosystem , Photosynthesis , Seasons , Carbon Sequestration , PlantsABSTRACT
Investigations into the carbon cycle and how it responds to climate change at the national scale are important for a comprehensive understanding of terrestrial carbon cycle and global change issues. Contributions of carbon fluxes to the terrestrial sink and the effects on climate change are still not fully understood. In this study, we aimed to explore the relationship between ecosystem production (GPP/SIF/NDVI) and net ecosystem carbon exchange (NEE) and to investigate the sensitivity of carbon fluxes to climate change at different spatio-temporal scales. Furthermore, we sought to delve into the carbon cycle processes driven by climate stress in China since the beginning of the 21st century. To achieve these objectives, we employed correlation and sensitivity analysis techniques, utilizing a wide range of data sources including ground-based observations, remote sensing observations, atmospheric inversions, machine learning, and model simulations. Our findings indicate that NEE in most arid regions of China is primarily driven by ecosystem production. Climate variations have a greater influence on ecosystem production than respiration. Warming has negatively impacted ecosystem production in Northeast China, as well as in subtropical and tropical regions. Conversely, increased precipitation has strengthened the terrestrial carbon sink, particularly in the northern cool and dry areas. We also found that ecosystem respiration exhibits heightened sensitivity to warming in southern China. Moreover, our analysis revealed that the control of terrestrial carbon cycle by ecosystem production gradually weakens from cold/arid areas to warm/humid areas. We identified distinct temperature thresholds (ranging from 10.5 to 13.7 °C) and precipitation thresholds (approximately 1400 mm yr-1) for the transition from production-dominated to respiration-dominated processes. Our study provides valuable insights into the complex relationship between climate change and carbon cycle in China.
ABSTRACT
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 â¼0.50, 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.
ABSTRACT
The northern hemisphere has experienced regional cooling, especially during the global warming hiatus (1998-2012) due to ocean energy redistribution. However, the lack of studies about the natural cooling effects hampers our understanding of vegetation responses to climate change. Using 15,125 ground phenological time series at 3,620 sites since the 1950s and 31-year satellite greenness observations (1982-2012) covering the warming hiatus period, we show a stronger response of leaf onset date (LOD) to natural cooling than to warming, i.e. the delay of LOD caused by 1°C cooling is larger than the advance of LOD with 1°C warming. This might be because cooling leads to larger chilling accumulation and heating requirements for leaf onset, but this non-symmetric LOD response is partially offset by warming-related drying. Moreover, spring greening magnitude, in terms of satellite-based greenness and productivity, is more sensitive to LOD changes in the warming area than in the cooling. These results highlight the importance of considering non-symmetric responses of spring greening to warming and cooling when predicting vegetation-climate feedbacks.
ABSTRACT
The relationship between stomatal traits and environmental drivers across plant communities has important implications for ecosystem carbon and water fluxes, but it has remained unclear. Here, we measure the stomatal morphology of 4492 species-site combinations in 340 vegetation plots across China and calculate their community-weighted values for mean, variance, skewness, and kurtosis. We demonstrate a trade-off between stomatal density and size at the community level. The community-weighted mean and variance of stomatal density are mainly associated with precipitation, while that of stomatal size is mainly associated with temperature, and the skewness and kurtosis of stomatal traits are less related to climatic and soil variables. Beyond mean climate variables, stomatal trait moments also vary with climatic seasonality and extreme conditions. Our findings extend the knowledge of stomatal trait-environment relationships to the ecosystem scale, with applications in predicting future water and carbon cycles.
Subject(s)
Ecosystem , Plants , Soil , Temperature , Water , Plant LeavesABSTRACT
Quantifying the stomatal responses of plants to global change factors is crucial for modeling terrestrial carbon and water cycles. Here we synthesize worldwide experimental data to show that stomatal conductance (gs) decreases with elevated carbon dioxide (CO2), warming, decreased precipitation, and tropospheric ozone pollution, but increases with increased precipitation and nitrogen (N) deposition. These responses vary with treatment magnitude, plant attributes (ambient gs, vegetation biomes, and plant functional types), and climate. All two-factor combinations (except warming + N deposition) significantly reduce gs, and their individual effects are commonly additive but tend to be antagonistic as the effect sizes increased. We further show that rising CO2 and warming would dominate the future change of plant gs across biomes. The results of our meta-analysis provide a foundation for understanding and predicting plant gs across biomes and guiding manipulative experiment designs in a real world where global change factors do not occur in isolation.
Subject(s)
Carbon Dioxide , Photosynthesis , Photosynthesis/physiology , Ecosystem , Climate , Plants , Climate ChangeABSTRACT
Quantifying and predicting variation in gross primary productivity (GPP) is important for accurate assessment of the ecosystem carbon budget under global change. Scaling traits to community scales for predicting ecosystem functions (i.e., GPP) remain challenging, while it is promising and well appreciated with the rapid development of trait-based ecology. In this study, we aim to integrate multiple plant traits with the recently developed trait-based productivity (TBP) theory, verify it via Bayesian structural equation modeling (SEM) and complementary independent effect analysis. We further distinguish the relative importance of different traits in explaining the variation in GPP. We apply the TBP theory based on plant community traits to a multi-trait dataset containing more than 13,000 measurements of approximately 2,500 species in Chinese forest and grassland systems. Remarkably, our SEM accurately predicts variation in annual and monthly GPP across China (R2 values of 0.87 and 0.73, respectively). Plant community traits play a key role. This study shows that integrating multiple plant functional traits into the TBP theory strengthens the quantification of ecosystem primary productivity variability and further advances understanding of the trait-productivity relationship. Our findings facilitate integration of the growing plant trait data into future ecological models.
Subject(s)
Ecology , Ecosystem , Bayes Theorem , ForestsABSTRACT
Recent rapid warming has caused uneven impacts on the composition, structure, and functioning of northern ecosystems. It remains unknown how climatic drivers control linear and non-linear trends in ecosystem productivity. Based on a plant phenology index (PPI) product at a spatial resolution of 0.05° over 2000-2018, we used an automated polynomial fitting scheme to detect and characterize trend types (i.e., polynomial trends and no-trends) in the yearly-integrated PPI (PPIINT) for northern (> 30°N) ecosystems and their dependence on climatic drivers and ecosystem types. The averaged slope for the linear trends (p < 0.05) of PPIINT was positive across all the ecosystems, among which deciduous broadleaved forests and evergreen needle-leaved forests (ENF) showed the highest and lowest mean slopes, respectively. More than 50% of the pixels in ENF, arctic and boreal shrublands, and permanent wetlands (PW) had linear trends. A large fraction of PW also showed quadratic and cubic trends. These trend patterns agreed well with estimates of global vegetation productivity based on solar-induced chlorophyll fluorescence. Across all the biomes, PPIINT in pixels with linear trends showed lower mean values and higher partial correlation coefficients with temperature or precipitation than in pixels without linear trends. Overall, our study revealed the emergence of latitudinal convergence and divergence in climatic controls on the linear and non-linear trends of PPIINT, implying that northern shifts of vegetation and climate change may potentially increase the non-linear nature of climatic controls on ecosystem productivity. These results can improve our understanding and prediction of climate-induced changes in plant phenology and productivity and facilitate sustainable management of ecosystems by accounting for their resilience and vulnerability to future climate change.
Subject(s)
Ecosystem , Forests , Temperature , Arctic Regions , Plants , Climate Change , SeasonsABSTRACT
The sequence of physiological events during drought strongly impacts plants' overall performance. Here, we synthesized the global data of stomatal and hydraulic traits in leaves and stems of 202 woody species to evaluate variations in the water potentials for key physiological events and their sequence along the climatic gradient. We found that the seasonal minimum water potential, turgor loss point, stomatal closure point, and leaf and stem xylem vulnerability to embolism were intercorrelated and decreased with aridity, indicating that water stress drives trait co-selection. In xeric regions, the seasonal minimum water potential occurred at lower water potential than turgor loss point, and the subsequent stomatal closure delayed embolism formation. In mesic regions, however, the seasonal minimum water potential did not pose a threat to the physiological functions, and stomatal closure occurred even at slightly more negative water potential than embolism. Our study demonstrates that the sequence of water potentials for physiological dysfunctions of woody plants varies with aridity, that is, xeric species adopt a more conservative sequence to prevent severe tissue damage through tighter stomatal regulation (isohydric strategy) and higher embolism resistance, while mesic species adopt a riskier sequence via looser stomatal regulation (anisohydric strategy) to maximize carbon uptake at the cost of hydraulic safety. Integrating both aridity-dependent sequence of water potentials for physiological dysfunctions and gap between these key traits into the hydraulic framework of process-based vegetation models would improve the prediction of woody plants' responses to drought under global climate change.
Subject(s)
Plant Leaves , Plant Stomata , Plant Stomata/physiology , Plant Leaves/physiology , Wood , Xylem , Trees , DroughtsABSTRACT
Warming of northern high latitude regions (NHL, > 50 °N) has increased both photosynthesis and respiration which results in considerable uncertainty regarding the net carbon dioxide (CO2) balance of NHL ecosystems. Using estimates constrained from atmospheric observations from 1980 to 2017, we find that the increasing trends of net CO2 uptake in the early-growing season are of similar magnitude across the tree cover gradient in the NHL. However, the trend of respiratory CO2 loss during late-growing season increases significantly with increasing tree cover, offsetting a larger fraction of photosynthetic CO2 uptake, and thus resulting in a slower rate of increasing annual net CO2 uptake in areas with higher tree cover, especially in central and southern boreal forest regions. The magnitude of this seasonal compensation effect explains the difference in net CO2 uptake trends along the NHL vegetation- permafrost gradient. Such seasonal compensation dynamics are not captured by dynamic global vegetation models, which simulate weaker respiration control on carbon exchange during the late-growing season, and thus calls into question projections of increasing net CO2 uptake as high latitude ecosystems respond to warming climate conditions.
Subject(s)
Carbon Dioxide , Permafrost , Carbon Cycle , Ecosystem , SeasonsABSTRACT
The microbial priming effect-the decomposition of soil organic carbon (SOC) induced by plant inputs-has long been considered an important driver of SOC dynamics, yet we have limited understanding about the direction, intensity, and drivers of priming across ecosystem types and biomes. This gap hinders our ability to predict how shifts in litter inputs under global change can affect climate feedbacks. Here, we synthesized 18,919 observations of CO2 effluxes in 802 soils across the globe to test the relative effects (i.e., log response ratio [RR]) of litter additions on native SOC decomposition and identified the dominant environmental drivers in natural ecosystems and agricultural lands. Globally, litter additions enhanced native SOC decomposition (RR = 0.35, 95% CI: 0.32-0.38), with greater priming effects occurring with decreasing latitude and more in agricultural soils (RR = 0.43) than in uncultivated soils (RR = 0.28). In natural ecosystems, soil pH and microbial community composition (e.g., bacteria: fungi ratio) were the best predictors of priming, with greater effects occurring in acidic, bacteria-dominated sandy soils. In contrast, the substrate properties of plant litter and soils were the most important drivers of priming in agricultural systems since soils with high C:N ratios and those receiving large inputs of low-quality litter had the highest priming effects. Collectively, our results suggest that, though different factors may control priming effects, the ubiquitous nature of priming means that alterations of litter quality and quantity owing to global changes will likely have consequences for global C cycling and climate forcing.
Subject(s)
Ecosystem , Soil , Soil/chemistry , Carbon , Carbon Cycle , Soil Microbiology , PlantsABSTRACT
Considerable uncertainty and debate exist in projecting the future capacity of forests to sequester atmospheric CO2. Here we estimate spatially explicit patterns of biomass loss by tree mortality (LOSS) from largely unmanaged forest plots to constrain projected (2015-2099) net primary productivity (NPP), heterotrophic respiration (HR) and net carbon sink in six dynamic global vegetation models (DGVMs) across continents. This approach relies on a strong relationship among LOSS, NPP, and HR at continental or biome scales. The DGVMs overestimated historical LOSS, particularly in tropical regions and eastern North America by as much as 5 Mg ha-1 y-1. The modeled spread of DGVM-projected NPP and HR uncertainties was substantially reduced in tropical regions after incorporating the field-based mortality constraint. The observation-constrained models show a decrease in the tropical forest carbon sink by the end of the century, particularly across South America (from 2 to 1.4 PgC y-1), and an increase in the sink in North America (from 0.8 to 1.1 PgC y-1). These results highlight the feasibility of using forest demographic data to empirically constrain forest carbon sink projections and the potential overestimation of projected tropical forest carbon sinks.
Subject(s)
Carbon Sequestration , Ecosystem , Biomass , Carbon , South America , UncertaintyABSTRACT
In natural forests at a demographic equilibrium state, the size frequency distribution (SFD) of trees is linked with their size-dependent growth and mortality rates. While the mean growth rate (MGR) of each size class is generally used for determining the SFD, the variance in the growth rate (VGR) has always been ignored. Here, based on the analyses with Kolmogorov forward equation, we show that in general, the VGR can flatten the slope of the SFD and, in particular, can address the contradiction between the size-dependent MGR and the -2 power-law SFD in the metabolic scaling theory. We traced the origin of the VGR to the intrinsic stochasticity in the allometric growth coefficients of trees and deduced its functional form based on variance propagation. Using the forest censuses data from Barro Colorado Island, we verified the prediction of the VGR and indicated its indispensability in the theory of forest size-structure formation.
Subject(s)
Forests , TreesABSTRACT
Nocturnal transpiration is widely observed across species and biomes, and may significantly impact global water, carbon, and energy budgets. However, it remains elusive why plants lose water at night and how to model it at large scales. We hypothesized that plants optimize nighttime leaf diffusive conductance (gwn ) to balance potential daytime photosynthetic benefits and nocturnal transpiration benefits. We quantified nighttime benefits from respiratory reductions due to evaporative leaf cooling. We described nighttime costs in terms of a reduced carbon gain during the day because of water use at night. We measured nighttime stomatal responses and tested our model with water birch (Betula occidentalis) saplings grown in a glasshouse. The gwn of water birch decreased with drier soil, higher atmospheric CO2 , wetter air, lower leaf temperature, and lower leaf respiration rate. Our model predicted all these responses correctly, except for the response of gwn to air humidity. Our results also suggested that the slow decrease in gwn after sunset could be associated with decreasing leaf respiration. The optimality-based nocturnal transpiration model smoothly integrates with daytime stomatal optimization approaches, and thus has the potential to quantitatively predict nocturnal transpiration across space and time.
Subject(s)
Photosynthesis , Plant Transpiration , Plant Leaves , Plant Stomata , Soil , WaterABSTRACT
Biocrusts cover ~30% of global drylands with a prominent role in the biogeochemical cycles. Theoretically, biocrusts, vascular plants, and bare soil can represent multiple stable states in drylands. However, no empirical evidence for the existence of a biocrust stable state has been reported. Here, using a global drylands dataset, we found that biocrusts form an alternative stable state (biocrust cover, ~80%; vascular cover, ≤10%) besides bare soil (both biocrust and vascular cover, ≤10%) and vascular plants (vascular cover, >50%; biocrust cover, ~5%). The pattern of multiple stable states associated with biocrusts differs from the classic fold bifurcation, and values of the aridity index in the range of 0 to 0.6 define a bistable region where multiple stable states coexist. This study empirically demonstrates the existence and thresholds of multiple stable states associated with biocrusts along climatic gradients and thus may greatly contribute to conservation and restoration of global drylands.