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At least 19 records

Critical Soil Moisture Thresholds of Plant Water Stress in Terrestrial Ecosystems

Plant water stress occurs at the point when soil moisture (SM) limits transpiration, defining a critical SM threshold (θ crit ). Knowledge of the spatial distribution of θ crit is crucial for future projections of climate and water resources. Here, we use global eddy covariance observations to quantify θcrit and evaporative fraction (EF) regimes. Three canonical variables describe how EF is controlled by SM: the maximum EF (EF max ), θ crit , and slope (S) between EF and SM. We find systematic differences of these three variables across biomes. Variation in θ crit , S, and EFmax is mostly explained by soil texture, vapor pressure deficit, and precipitation, respectively, as well as vegetation structure. Dryland ecosystems tend to operate at low θ crit and show adaptation to water deficits. The negative relationship between θ crit and S indicates that dryland ecosystems minimize θcrit through mechanisms of sustained SM extraction and transport by xylem. Our results further suggest an optimal adaptation of local EF-SM response that maximizes growing-season evapotranspiration and photosynthesis.

Zheng Fu↗

Stressors Reveal Ecosystems' Hidden Characteristics

Abstract Vegetation responds dynamically to local microclimates at both short and long time scales via mechanisms ranging from physiological behaviors, such as stomatal closure, to acclimation and adaptation. These responses influence the carbon, water, and energy cycles directly and are therefore crucial to understanding and predicting Earth system responses to a changing climate. Several recent studies have demonstrated that differences in microclimate can induce structural and functional acclimations, and potentially adaptations, within the same ecosystem. Such microclimate divergence can be caused by variability in slopes, disturbance history, or even localized resource availability. Ecosystem stressors such as low soil water availability, limited photoperiod, or high vapor pressure deficit have been shown to reveal the large impact of the subtle differences within these systems such as the number of sun versus shade leaves or differences in whole‐plant water acquisition and use. These findings highlight the linkages between plant canopy structure and ecosystem function, alongside the need for comprehensive analyses of vegetation within the broader context of its environment. This commentary addresses some of the key implications of ecosystem stress responses and accompanying acclimations across three ecosystem types for ecosystem ecology, plant physiology, ecohydrology and trait‐based modeling of vegetation‐climate dynamics.

Matheny, Ashley M.↗

Robust inference of ecosystem soil water stress from eddy covariance data

Eddy covariance data are invaluable for determining ecosystem water use strategies under soil water stress. However, existing stress inference methods require numerous subjective data processing and model specification assumptions whose effect on the inferred soil water stress signal is rarely quantified. These uncertainties may confound the stress inference and the generalization of ecosystem water use strategies across multiple sites and studies. In this research, we quantify the sensitivity of soil water stress signals inferred from eddy covariance data to the prevailing data and modeling assumptions (i.e., their robustness) to compile a comprehensive list of sites with robust soil water stress signals and assess the performance of current stress inference methods. To accomplish this, we identify the most prevalent assumptions from the literature and perform a digital factorial experiment to extract probability distributions of plausible soil water stress signals and model performance at 151 FLUXNET2015 and AmeriFlux-FLUXNET sites. Here, we develop a new framework that summarizes these probability distributions to classify and rank the robustness of each site’s soil water stress signal, which we display with a user-friendly heat map. We estimate that only 5%–36% of sites exhibit a robust soil water stress signal due to deficient model performance and poorly constrained ecosystem water use parameters. We also find that the lack of robustness is site-specific, which undermines grouping stress signals by broad ecosystem categories or comparing results across studies with differing assumptions. Lastly, existing stress inference methods appear better suited for eddy covariance sites with grass/annual vegetation. Our findings call for more careful and consistent inference of ecosystem water stress from eddy covariance data.

54 ENVIRONMENTAL SCIENCES↗

Effect of elevation, season and accelerated snowmelt on biogeochemical processes during isolated conifer needle litter decomposition

Increased drought and temperatures associated with climate change have implications for ecosystem stress with risk for enhanced carbon release in sensitive biomes. Litter decomposition is a key component of biogeochemical cycling in terrestrial ecosystems, but questions remain regarding the local response of decomposition processes to climate change. This is particularly complex in mountain ecosystems where the variable nature of the slope, aspect, soil type, and snowmelt dynamics play a role. Hence, the goal of this study was to determine the role of elevation, soil type, seasonal shifts in soil moisture, and snowmelt timing on litter decomposition processes. Experimental plots containing replicate deployments of harvested lodgepole and spruce needle litter alongside needle-free controls were established in open meadows at three elevations ranging from 2,800–3,500 m in Crested Butte, Colorado. Soil biogeochemistry variables including gas flux, porewater chemistry, and microbial ecology were monitored over three climatically variable years that shifted from high monsoon rains to drought. Results indicated that elevation and soil type influenced baseline soil biogeochemical indicators; however, needle mass loss and chemical composition were consistent across the 700 m elevation gradient. Rates of gas flux were analogously consistent across a 300 m elevation gradient. The additional variable of early snowmelt by 2–3 weeks had little impact on needle chemistry, microbial composition and gas flux; however, it did result in increased dissolved organic carbon in lodgepole porewater collections suggesting a potential for aqueous export. In contrast to elevation, needle presence and seasonal variability of soil moisture and temperature both played significant roles in soil carbon fluxes. Furthermore, during a pronounced period of lower moisture and higher temperatures, bacterial community diversity increased across elevation with new members supplanting more dominant taxa. Microbial ecological resilience was demonstrated with a return to pre-drought structure and abundance after snowmelt rewetting the following year. These results show similar decomposition processes across a 700 m elevation gradient and reveal the sensitivity but resilience of soil microbial ecology to low moisture conditions.

59 BASIC BIOLOGICAL SCIENCES↗

Pervasive alterations to snow-dominated ecosystem functions under climate change

Climate change projections consistently demonstrate that warming temperatures and dwindling seasonal snowpack will elicit cascading effects on ecosystem function and water resource availability. Despite this consensus, little is known about potential changes in the variability of ecohydrological conditions, which is also required to inform climate change adaptation and mitigation strategies. Considering potential changes in ecohydrological variability is critical to evaluating the emergence of trends, assessing the likelihood of extreme events such as floods and droughts, and identifying when tipping points may be reached that fundamentally alter ecohydrological function. Using a single-model Large Ensemble with sophisticated terrestrial ecosystem representation, we characterize projected changes in the mean state and variability of ecohydrological processes in historically snow-dominated regions of the Northern Hemisphere. Widespread snowpack reductions, earlier snowmelt timing, longer growing seasons, drier soils, and increased fire risk are projected for this century under a high-emissions scenario. In addition to these changes in the mean state, increased variability in winter snowmelt will increase growing-season water deficits and increase the stochasticity of runoff. Thus, with warming, declining snowpack loses its dependable buffering capacity so that runoff quantity and timing more closely reflect the episodic characteristics of precipitation. This results in a declining predictability of annual runoff from maximum snow water equivalent, which has critical implications for ecosystem stress and water resource management. So our results suggest that there is a strong likelihood of pervasive alterations to ecohydrological function that may be expected with climate change.

54 ENVIRONMENTAL SCIENCES↗

TARP Identifying Critical Thresholds for Acute Response of Plants and Ecosystems to Water Stress at Walker Branch Watershed, 2002-2005

This dataset contains data from a manipulative field study aimed at identifying critical thresholds for acute response of plants and ecosystems to water stress (TARP) that took place at Walker Branch Watershed in Oak Ridge, Tennessee from 2002-2005 (2002-06-20 to 2005-12-16). The study used understory tents for the removal of 100% of the growing-season throughfall and stem flow, to provide data on the impact of acute drought on mechanisms responsible for growth and mortality of deciduous forest canopy trees representative of common plant functional types (Liriodendron and Quercus). Through three years of manipulation (2003, 2004 and 2005; pretreatment measurements in 2002) various measures of tree response to surface moisture deficits were recorded including root and leaf traits, plant nonstructural carbohydrates status, hourly sapflow, basal area, and periodic observations of foliar photosynthesis and conductance. Additionally, environmental data such as air and soil temperature, soil water content, and soil matric potential were recorded. This dataset contains data 16 files in comma-separate (*.csv) format. Additional metadata are provided: 16 data dictionaries and a file-level metadata file in comma separate (*.csv) format and a user guide in PDF (*.pdf) format.

basal area↗

Experimental Soil Warming Impacts Soil Moisture and Plant Water Stress and Thereby Ecosystem Carbon Dynamics (Blodgett, CA)

This dataset contains data on daily soil temperature, moisture and flux, and soil carbon stock and root biomass across a soil profile down to 100 cm depth at Blodgett Forest Research Station, CA, USA. These data were generated to determine if modeling of an experimental soil warming of 4C showed increased soil CO2 emissions and changes in bulk soil carbon stocks with depth consistent with field observations, as part of the study: Riley et al. (2025) Experimental Soil Warming Impacts Soil Moisture and Plant Water Stress and Thereby Ecosystem Carbon Dynamics in Journal of Advances in Modeling Earth Systems. This research was performed within the framework of the TES Belowground Biogeochemistry SFA project, in particular association with a 1 m-deep experimental soil heating experiment at the University of California Blodgett Forest Research Station, California (120 ° 39′40′′W; 38 ° 54′43′′N). Continuous data were collected at the plot level, and bulk soil carbon and root biomass were sampled once a year from each plot from 0-100 cm, in 10 cm intervals. Measurements relevant to the current study include soil temperature and soil volumetric water content measured continuously at multiple depths in the top meter; fine root biomass and SOC stocks measured from annual soil cores. Soil flux was continuously monitored using a LI-8100 Automated CO2 Flux System in conjunction with the LI-8150 Multiplexer (Licor, Nebraska, USA). Soil flux was determined using SoilFluxPro software, with flux values showing an R² fit of less than 0.9 being excluded from the analysis. Data were collected from each paired plot (1-3): one control (C) and one heated (H).

54 ENVIRONMENTAL SCIENCES↗

Experimental Soil Warming Impacts Soil Moisture and Plant Water Stress and Thereby Ecosystem Carbon Dynamics

Experimental soil heating experiments have found a consistent increase in soil-surface CO 2 emissions ( F s ), but inconsistent soil organic carbon (SOC) responses. Interpretation of heating effects is complicated by spatial heterogeneity and soil moisture, nitrogen availability, and microbial and plant responses. Here we applied a mechanistic ecosystem model to interpret heating impacts on a California forest subjected to 1 m deep, 4°C heating. The model accurately simulated control-plot CO 2 fluxes, SOC stocks, fine root biomass, soil moisture, and soil temperature, and the observed increases in F s and decreases in fine root biomass. We show that a complex suite of interactions can lead to a consistent increase in F s (~17%) over the 5-year study period, with very small changes in SOC stocks (<1%). Modeled increases in leaf water stress from soil drying reduced GPP and NPP. The resulting reduction in leaf and fine root allocation increased fine root litter inputs to the soil and reduced root exudation. Soil heating led to about a 50% larger increase in root autotrophic respiration than in heterotrophic respiration, with the heating effect on both these fluxes decreasing over the simulation period. Increased heterotrophic respiration led to increased soil N availability and plant N uptake. These heating responses are mechanistically linked, of magnitudes that can affect ecosystem dynamics, and long-term observations of them are rarely made. Therefore, we conclude that a coupled observational and mechanistic modeling framework is needed to interpret manipulation experiments, and to improve projections of climate change impacts on terrestrial ecosystem carbon dynamics.

54 ENVIRONMENTAL SCIENCES↗

Evaluating ecosystem water use efficiency under drought stress: a case study of the Helan Mountain region, northwest China

Context Water use efficiency (WUE) is a fundamental ecological indicator links carbon assimilation and water loss in terrestrial ecosystems. Understanding its responses to drought stress is essential for adaptive ecosystem management, particularly in climate-sensitive mountain landscapes. Objectives This study aimed to investigate drought-driven variations in WUE across major vegetation types in the Helan Mountain region of Northwest China. Specifically, we sought to identify dominant ecological drivers of WUE variability and to disentangle their relative importance and causal pathways. Methods We quantified WUE using the Moderate Resolution Imaging Spectroradiometer (MODIS) products and the Drought Severity Index (DSI) data from 2001 to 2020. To examine WUE – drought relationships across contrasting vegetation types, we employed a spatially explicit analytical framework integrating Random Forest (RF) modeling, partial correlation analysis, and structural equation modeling (SEM). Results Regional WUE exhibited relatively stable interannual dynamics, yet pronounced spatial heterogeneity that was strongly modulated by drought conditions. Vegetation properties, particularly Leaf Area Index (LAI) and Normalized Difference Vegetation Index (NDVI), emerged as the dominant determinants of WUE, with NDVI alone explaining over 20% of its spatial variance in forest and grassland during non-drought periods. SEM analyses revealed that climate forcing influenced WUE mainly through indirect pathways mediated by soil moisture availability and vegetation structural dynamics, rather than through direct climatic controls. Among all regulating factors, LAI acted as the central control node governing ecosystem carbon–water coupling. In contrast, short-term climatic stress, especially atmospheric demand and drought duration, exerted weak or negative direct effects on WUE. Ecosystem-specific responses were observed, with croplands mainly regulated by soil water availability, whereas forests and grasslands showed more sensitive to atmospheric drought stress. Together, these results reveal a hierarchical control framework where soil–vegetation interactions mediate climate impacts on WUE, driving strong spatial heterogeneity in drought responses across mountain landscapes. Conclusions Our findings highlight the pivotal role of indirect drought effects mediated by vegetation and soil processes in shaping ecosystem WUE. The identified soil–vegetation–climate regulatory hierarchy provides mechanistic insight into landscape–scale drought sensitivity and supports integrated modeling approaches for evaluating ecosystem resilience and sustainable management in arid mountain regions.

China↗

Skillful Multi‐Month Predictions of Ecosystem Stressors in the Surface and Subsurface Ocean

Abstract Anthropogenic carbon emissions and associated climate change are driving rapid warming, acidification, and deoxygenation in the ocean, which increasingly stress marine ecosystems. On top of long‐term trends, short term variability of marine stressors can have major implications for marine ecosystems and their management. As such, there is a growing need for predictions of marine ecosystem stressors on monthly, seasonal, and multi‐month timescales. Previous studies have demonstrated the ability to make reliable predictions of the surface ocean physical and biogeochemical state months to years in advance, but few studies have investigated forecast skill of multiple stressors simultaneously or assessed the forecast skill below the surface. Here, we use the Community Earth System Model (CESM) Seasonal to Multiyear Large Ensemble (SMYLE) along with novel observation‐based biogeochemical and physical products to quantify the predictive skill of dissolved inorganic carbon (DIC), dissolved oxygen, and temperature in the surface and subsurface ocean. CESM SMYLE demonstrates high physical and biogeochemical predictive skill multiple months in advance in key oceanic regions and frequently outperforms persistence forecasts. We find up to 10 months of skillful forecasts, with particularly high skill in the Northeast Pacific (Gulf of Alaska and California Current Large Marine Ecosystems) for temperature, surface DIC, and subsurface oxygen. Our findings suggest that dynamical marine ecosystem prediction could support actionable advice for decision making.

Environmental Sciences & Ecology↗

Stem psychrometer and flux data from US-CdM

Cleaned midday and predawn water potential data from 14 stem psychrometers installed within the footprint of the US-CdM flux tower, from May-October 2021. These data were collected in order to link environmental drivers, vegetation responses to seasonal water stress, and ecosystem fluxes of carbon and water at a pinyon-juniper woodland in southeastern Utah.Data include a comma separated values file containing all water potential data used in the published paper. Data were first published in Kannenberg et al. 2023 Agricultural and Forest Meteorology (doi: 10.1016/j.agrformet.2022.109269). Flux data are publicly available from the AmeriFlux portal (doi: 10.17190/AMF/1865477). This data file and the AmeriFlux data are all that is necessary to replicate the analyses in Kannenberg et al. 2023 Agricultural and Forest Meteorology.

54 ENVIRONMENTAL SCIENCES↗

A coupled ground heat flux–surface energy balance model of evaporation using thermal remote sensing observations

Abstract. One of the major undetermined problems in evaporation (ET) retrieval using thermal infrared remote sensing is the lack of a physically based ground heat flux (G) model and its integration within the surface energy balance (SEB) equation. Here, we present a novel approach based on coupling a thermal inertia (TI)-based mechanistic G model with an analytical surface energy balance model, Surface Temperature Initiated Closure (STIC, version STIC1.2). The coupled model is named STIC-TI. The model is driven by noon–night (13:30 and 01:30 local time) land surface temperature, surface albedo, and a vegetation index from MODIS Aqua in conjunction with a clear-sky net radiation sub-model and ancillary meteorological information. SEB flux estimates from STIC-TI were evaluated with respect to the in situ fluxes from eddy covariance measurements in diverse ecosystems of contrasting aridity in both the Northern Hemisphere and Southern Hemisphere. Sensitivity analysis revealed substantial sensitivity of STIC-TI-derived fluxes due to the land surface temperature uncertainty. An evaluation of noontime G (Gi) estimates showed 12 %–21 % error across six flux tower sites, and a comparison between STIC-TI versus empirical G models also revealed the substantially better performance of the former. While the instantaneous noontime net radiation (RNi) and latent heat flux (LEi) were overestimated (15 % and 25 %), sensible heat flux (Hi) was underestimated (22 %). Overestimation (underestimation) of LEi (Hi) was associated with the overestimation of net available energy (RNi−Gi) and use of unclosed surface energy balance flux measurements in LEi (Hi) validation. The mean percent deviations in Gi and Hi estimates were found to be strongly correlated with satellite day–night view angle difference in parabolic and linear pattern, and a relatively weak correlation was found between day–night view angle difference versus LEi deviation. Findings from this parameter-sparse coupled G–ET model can make a valuable contribution to mapping and monitoring the spatiotemporal variability of ecosystem water stress and evaporation using noon–night thermal infrared observations from future Earth observation satellite missions such as TRISHNA, LSTM, and SBG.

Bhattacharya, Bimal K.↗

Root exudate composition reflects drought severity gradient in blue grama (Bouteloua gracilis)

Abstract Plant survival during environmental stress greatly affects ecosystem carbon (C) cycling, and plant–microbe interactions are central to plant stress survival. The release of C-rich root exudates is a key mechanism plants use to manage their microbiome, attracting beneficial microbes and/or suppressing harmful microbes to help plants withstand environmental stress. However, a critical knowledge gap is how plants alter root exudate concentration and composition under varying stress levels. In a greenhouse study, we imposed three drought treatments (control, mild, severe) on blue grama ( Bouteloua gracilis Kunth Lag. Ex Griffiths), and measured plant physiology and root exudate concentration and composition using GC–MS, NMR, and FTICR. With increasing drought severity, root exudate total C and organic C increased concurrently with declining predawn leaf water potential and photosynthesis. Root exudate composition mirrored the physiological gradient of drought severity treatments. Specific compounds that are known to alter plant drought responses and the rhizosphere microbiome mirrored the drought severity-induced root exudate compositional gradient. Despite reducing C uptake, these plants actively invested C to root exudates with increasing drought severity. Patterns of plant physiology and root exudate concentration and composition co-varied along a gradient of drought severity.

59 BASIC BIOLOGICAL SCIENCES↗

Water foraging with dynamic roots in E3SM; The role of roots in terrestrial ecosystem memory on intermediate timescales (Final Technical Report)

Terrestrial ecosystems can show sustained responses to stress events that may last for years after the initial perturbation. This phenomenon is referred to as legacy or memory and it emerges from a set of ecosystem processes that are poorly captured by Earth System and Land Surface Models. Consequently, these models struggle to predict the impact that extreme climate events have on surface energy, carbon and hydrological exchange once a stressor such as drought has relaxed or in response to repeated exposure to stress. In this project, we set out to test how the addition of dynamic root profiles in land surface models impact the capacity for Earth System Models, such as the Department of Energy’s E3SM, to capture realistic legacy effects. Observations have shown that vegetation shifts their root profiles during stress events to forage for water and these altered root profiles may take years to relax back to the initial state. We hypothesized that the alteration of the belowground root structures may be a source of terrestrial ecosystem legacy that is missing from models. To test this idea we undertook three core activities. (1) We developed a global-scale analysis of the impact of dynamic roots on ecosystem legacy building from a recently developed dynamic root module. (2) We developed new root dynamics in the DOE’s Energy Land Model (ELM) that allowed not only root profiles to shift their profile but also simultaneously alter carbon allocation to fine root pools. We then tested the impact of these new dynamics with intensive sensitivity analysis at four long-term AmeriFlux sites. (3) We undertook detailed isotopic analysis of tree rings from these AmeriFlux sites to assess ecophysiological and ecohydrological legacy to stress events that can be used to benchmark the sensitivity experiments with ELM. From these core activities, we report the following key findings. Firstly, on a global scale, the addition of dynamic roots led to chronically water-stressed ecosystems recovering faster to climate stress while wetter ecosystem showed enhanced legacy. This is because across ecosystems, stress events were almost universally associated with water shortages that led to the development of deeper root profiles. These deeper root profiles proved beneficial for recovery from drought stress. While the root dynamics did not universally improve the modeled representation of legacy it showed complex transient dynamics that emerge from the addition of dynamic roots. Secondly, the sensitivity analysis illustrated long term shifts in rooting depths away from the prescribed default profile suggesting that initializing of root profiles could benefit from spin-up simulations that converge on locally optimized root profiles. In addition, by enabling dynamic allocation some of the sites predicted unrealistically low allocation to roots (and high allocation to leaves). While these changes did not dramatically alter modeled gross primary productivity, they illustrated that without more sophisticated root processes in models, there is little penalty to dramatically disinvest in roots. Thirdly, the isotopic analysis of tree rings showed highly distinct legacy responses across species and sites. For example, T. canadensis showed reduced transpiration the year after stress events illustrated by sustained elevated $\delta^{18}$O. In contrast, A saccharum displayed elevated $\delta^{13}$C associated with reduced stomatal conductance in response to the previous years’ stress event. These geochemical signatures of legacy were present despite tree growth returning to normal the year after the stress. The results show the importance of species-level dynamics in legacy that are absent in modeling that assumes common traits within plant functional types. In summary, the work here established new avenues to explore root dynamics in models while illustrating how additional root processes are needed before dynamic carbon allocation can be implemented. Lastly, this project provided mentorship to a postdoctoral fellow, training for an early career scientist and multiple undergraduate students recruited from a minority serving institution.

54 ENVIRONMENTAL SCIENCES↗

PSInet: a new global water potential network

Abstract Given the pressing challenges posed by climate change, it is crucial to develop a deeper understanding of the impacts of escalating drought and heat stress on terrestrial ecosystems and the vital services they offer. Soil and plant water potential play a pivotal role in governing the dynamics of water within ecosystems and exert direct control over plant function and mortality risk during periods of ecological stress. However, existing observations of water potential suffer from significant limitations, including their sporadic and discontinuous nature, inconsistent representation of relevant spatio-temporal scales and numerous methodological challenges. These limitations hinder the comprehensive and synthetic research needed to enhance our conceptual understanding and predictive models of plant function and survival under limited moisture availability. In this article, we present PSInet (PSI—for the Greek letter Ψ used to denote water potential), a novel collaborative network of researchers and data, designed to bridge the current critical information gap in water potential data. The primary objectives of PSInet are as follows. (i) Establishing the first openly accessible global database for time series of plant and soil water potential measurements, while providing important linkages with other relevant observation networks. (ii) Fostering an inclusive and diverse collaborative environment for all scientists studying water potential in various stages of their careers. (iii) Standardizing methodologies, processing and interpretation of water potential data through the engagement of a global community of scientists, facilitated by the dissemination of standardized protocols, best practices and early career training opportunities. (iv) Facilitating the use of the PSInet database for synthesizing knowledge and addressing prominent gaps in our understanding of plants’ physiological responses to various environmental stressors. The PSInet initiative is integral to meeting the fundamental research challenge of discerning which plant species will thrive and which will be vulnerable in a world undergoing rapid warming and increasing aridification.

Forestry↗

Root Foraging Alters Global Patterns of Ecosystem Legacy From Climate Perturbations

The response of terrestrial ecosystems to climate perturbations typically persist longer than the timescale of the forcing, a phenomenon broadly referred to as legacy. Understanding the strength of legacy is critical for predicting ecosystem sensitivity to climate extremes and the extent that persistent changes in surface-atmosphere exchange might feedback onto climate. The cause of ecosystem legacy has been associated with myriad factors such as changes in aboveground biomass, however, few studies have tested how changes in the depth distribution of fine roots in response to perturbation might alter an ecosystem's recovery time. We explore this question using an Earth System Model that includes a dynamic root module where vegetation can forage for water and nutrients by altering their root profiles. The global simulations presented here show that in response to water stress events most ecosystems deepen their root profiles. In semi-arid ecosystems, this response expedites recovery (i.e., less legacy) relative to simulations without dynamics roots because access to deeper water pools after the initial event remains favorable. In wetter ecosystems, the development of deeper root profiles slows down the recovery timescale (i.e., more legacy) because the deeper root profile reduces access to nutrients and is thus unfavorable. Here, the simulations show that while the inclusion of dynamic roots might only minimally affect global patterns of Gross Primary Productivity and Evapotranspiration, the shift in root profile alters the timescale of recovery. Studies interested in the sustained response of land surfaces fluxes to climate disturbances should consider models that include dynamic root capability.

54 ENVIRONMENTAL SCIENCES↗

Global variations in critical drought thresholds that impact vegetation

ABSTRACT Identifying the thresholds of drought that, if crossed, suppress vegetation functioning is vital for accurate quantification of how land ecosystems respond to climate variability and change. We present a globally applicable framework to identify drought thresholds for vegetation responses to different levels of known soil-moisture deficits using four remotely sensed vegetation proxies spanning 2001–2018. The thresholds identified represent critical inflection points for changing vegetation responses from highly resistant to highly vulnerable in response to drought stress, and as a warning signal for substantial vegetation impacts. Drought thresholds varied geographically, with much lower percentiles of soil-moisture anomalies in vegetated areas covered by more forests, corresponding to a comparably stronger capacity to mitigate soil water deficit stress in forested ecosystems. Generally, those lower thresholds are detected in more humid climates. State-of-the-art land models, however, overestimated thresholds of soil moisture (i.e. overestimating drought impacts), especially in more humid areas with higher forest covers and arid areas with few forest covers. Based on climate model projections, we predict that the risk of vegetation damage will increase by the end of the twenty-first century in some hotspots like East Asia, Europe, Amazon, southern Australia and eastern and southern Africa. Our data-based results will inform projections on future drought impacts on terrestrial ecosystems and provide an effective tool for drought management.

54 ENVIRONMENTAL SCIENCES↗

Can Large‐Scale Satellite Products Track the Effects of Atmospheric Dryness and Soil Water Deficit on Ecosystem Productivity Under Droughts?

Drought stress, characterized by increased vapor pressure deficit (VPD) and soil water content (SWC) deficit, significantly impacts ecosystem productivity (GPP). Accurately assessing these factors in satellite remote sensing (RS) GPP products is crucial for understanding the large-scale ecological consequences of drought. However, the accuracy of RS GPP in capturing the effects of VPD and SWC deficit, compared to EC flux data, remains under-investigated. Here we evaluated 10 RS GPP products and their mean (RSmean) concerning VPD and SWC deficit across diverse ecosystems along a dryness gradient. Our results revealed that RSmean and individual products generally capture the GPP response direction (VPD: mainly negative, SWC deficit: mixed positive/negative) but consistently misestimate the absolute GPP changes. This discrepancy is ecosystem-specific and consistent across all RS products, underscoring the need to enhance RS products to better account for ecosystem-specific VPD effects and non-linear SWC deficit responses, thereby improving RS GPP accuracy under drought.

Wang, Xiaorong [Univ. of Hong Kong, Pokfulam (Hong↗