Alexandra Konings
Associate Professor of Earth System Science, Senior Fellow at the Woods Institute for the Environment and, by courtesy, of Geophysics
Bio
Alexandra Konings leads the Remote Sensing Ecohydrology group, which studies interactions between the global carbon and water cycles. That is, her research studies how changes in hydrological conditions change ecosystems, and how this in turn feeds back to weather and climate. These interactions include studies of transpiration and root water uptake, photosynthesis, mortality, and fire processes, among others. To address these topics, the groups primarily uses the tools of model development and remote sensing (satellite) data, especially microwave remote sensing data of vegetation water content. Alex believes that a deep understanding of remote sensing techniques and how they can be used to create environmental datasets enables new opportunities for scientific insight and vice versa.
Academic Appointments
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Associate Professor, Earth System Science
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Senior Fellow, Stanford Woods Institute for the Environment
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Associate Professor (By courtesy), Geophysics
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Member, Bio-X
Administrative Appointments
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Faculty Affiliate, Stanford Woods Institute for the Environment (2016 - Present)
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Assistant Professor, Stanford Department of Earth System Science (2016 - Present)
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Visiting Postdoc, NASA Jet Propulsion Laboratory (2016 - 2016)
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Visiting Postdoc, Columbia University (2015 - 2016)
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NASA Earth and Space Science Fellow, Massachusetts Institute of Technology (2012 - 2015)
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NSF Graduate Research Fellow, Massachusetts Institute of Technology (2011 - 2011)
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NSF Graduate Research Fellow, Duke University (2009 - 2011)
Honors & Awards
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Sloan Research Fellowship, Alfred P. Sloan Foundation (2023)
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Global Environmental Change Early Career Award, AGU (2021)
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Editor's Citation for Excellence in Refereeing (Geophysical Research Letters), AGU (2020)
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CAREER, NSF (2020-2025)
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New (Early Career) Investigator Award, NASA (2018-2021)
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Group Achievement Award: AirMOSS Implementation Team, NASA (2016)
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Best Doctoral Thesis Award, MIT Department of Civil and Environmental Engineering (2015-2016)
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Earth and Space Science Fellowship, NASA (2012-2015)
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Graduate Research Fellowship, National Science Foundation (2009-2012)
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James B. Duke Fellowship, Duke University (2009-2011)
Boards, Advisory Committees, Professional Organizations
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Member, Jasper Ridge Biological Preserve Faculty Advisory Committee (2017 - Present)
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Member, AGU Hydrology Technical Committee on Remote Sensing (2016 - Present)
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Member, IEEE Geoscience and Remote Sensing Society (2010 - Present)
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Member, American Geophysical Union (2008 - Present)
Professional Education
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Ph.D., Massachusetts Institute of Technology, Hydrology (2015)
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M.S., Duke University, Environmental Science (2011)
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S.B., Massachusetts Institute of Technology, Environmental Engineering Science (2009)
2024-25 Courses
- Biosphere-Atmosphere Interactions
EARTHSYS 123A, EARTHSYS 223, ESS 123, ESS 223 (Win) - Remote Sensing of Hydrology
CEE 260D, ESS 224 (Win, Spr) -
Independent Studies (3)
- Directed Research
EARTHSYS 250 (Aut, Win, Spr) - Graduate Research
ESS 400 (Aut, Win, Spr) - Research in Geophysics
GEOPHYS 400 (Aut)
- Directed Research
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Prior Year Courses
2023-24 Courses
- Biosphere-Atmosphere Interactions
EARTHSYS 123A, EARTHSYS 223, ESS 123, ESS 223 (Win) - Remote Sensing of Hydrology
CEE 260D, ESS 224 (Win)
2022-23 Courses
- Biosphere-Atmosphere Interactions
EARTHSYS 123A, EARTHSYS 223, ESS 123, ESS 223 (Win) - Remote Sensing of Hydrology
CEE 260D, ESS 224 (Spr) - Topics in Earth System Science
ESS 301 (Aut, Win, Spr)
2021-22 Courses
- Citizenship in the 21st Century
COLLEGE 102 (Win) - Remote Sensing of Hydrology
CEE 260D, ESS 224 (Spr)
- Biosphere-Atmosphere Interactions
Stanford Advisees
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Doctoral Dissertation Reader (AC)
Kelsey Foster, Ankun Wang, Elizabeth Wig, Keani Willebrand -
Postdoctoral Faculty Sponsor
Marvin Browne, Dapeng Feng -
Doctoral (Program)
Erica McCormick, Trent Robinett, Matthew Worden
All Publications
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PSInet: A new global water potential network.
Tree physiology
2024
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: (1) 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. (2) Fostering an inclusive and diverse collaborative environment for all scientists studying water potential in various stages of their careers. (3) 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. (4) 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.
View details for DOI 10.1093/treephys/tpae110
View details for PubMedID 39190893
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Temperature Is Likely an Important Omission in Interpreting Vegetation Optical Depth
GEOPHYSICAL RESEARCH LETTERS
2024; 51 (15)
View details for DOI 10.1029/2024GL110094
View details for Web of Science ID 001279241600001
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Tree species explain only half of explained spatial variability in plant water sensitivity.
Global change biology
2024; 30 (7): e17425
Abstract
Spatiotemporal patterns of plant water uptake, loss, and storage exert a first-order control on photosynthesis and evapotranspiration. Many studies of plant responses to water stress have focused on differences between species because of their different stomatal closure, xylem conductance, and root traits. However, several other ecohydrological factors are also relevant, including soil hydraulics, topographically driven redistribution of water, plant adaptation to local climatic variations, and changes in vegetation density. Here, we seek to understand the relative importance of the dominant species for regional-scale variations in woody plant responses to water stress. We map plant water sensitivity (PWS) based on the response of remotely sensed live fuel moisture content to variations in hydrometeorology using an auto-regressive model. Live fuel moisture content dynamics are informative of PWS because they directly reflect vegetation water content and therefore patterns of plant water uptake and evapotranspiration. The PWS is studied using 21,455 wooded locations containing U.S. Forest Service Forest Inventory and Analysis plots across the western United States, where species cover is known and where a single species is locally dominant. Using a species-specific mean PWS value explains 23% of observed PWS variability. By contrast, a random forest driven by mean vegetation density, mean climate, soil properties, and topographic descriptors explains 43% of observed PWS variability. Thus, the dominant species explains only 53% (23% compared to 43%) of explainable variations in PWS. Mean climate and mean NDVI also exert significant influence on PWS. Our results suggest that studies of differences between species should explicitly consider the environments (climate, soil, topography) in which observations for each species are made, and whether those environments are representative of the entire species range.
View details for DOI 10.1111/gcb.17425
View details for PubMedID 39005206
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The Ecosystem as Super-organ/Ism, Revisited: Scaling Hydraulics to Forests under Climate Change.
Integrative and comparative biology
2024
Abstract
Classic debates in community ecology focused on the complexities of considering an ecosystem as a super-organ or organism. New consideration of such perspectives could clarify mechanisms underlying the dynamics of forest carbon dioxide (CO2) uptake and water vapor loss, important for predicting and managing the future of Earth's ecosystems and climate system. Here, we provide a rubric for considering ecosystem traits as aggregated, systemic, or emergent, i.e., representing the ecosystem as an aggregate of its individuals, or as a metaphorical or literal super-organ or organism. We review recent approaches to scaling-up plant water relations (hydraulics) concepts developed for organs and organisms to enable and interpret measurements at ecosystem-level. We focus on three community scale versions of water relations traits that have potential to provide mechanistic insight into climate change responses of CO2 and H2O gas exchange and forest productivity: leaf water potential (Ψcanopy), pressure volume curves (eco-PV), and hydraulic conductance (Keco). These analyses can reveal additional ecosystem-scale parameters analogous to those typically quantified for leaves or plants (e.g., wilting point and hydraulic vulnerability) that may act as thresholds in forest responses to drought including growth cessation, mortality and flammability. We unite these concepts in a novel framework to predict Ψcanopy and its approaching of critical thresholds during drought, using measurements of Keco and eco-PV curves. We thus delineate how extension of water relations concepts from organ- and organism-scales can reveal the hydraulic constraints on the interaction of vegetation and climate, and provide new mechanistic understanding and prediction of forest water use and productivity.
View details for DOI 10.1093/icb/icae073
View details for PubMedID 38886119
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Inferred drought-induced plant allocation shifts and their impact on drought legacy at a tropical forest site.
Global change biology
2024; 30 (5): e17287
Abstract
While droughts predominantly induce immediate reductions in plant carbon uptake, they can also exert long-lasting effects on carbon fluxes through associated changes in leaf area, soil carbon, etc. Among other mechanisms, shifts in carbon allocation due to water stress can contribute to the legacy effects of drought on carbon fluxes. However, the magnitude and impact of these allocation shifts on carbon fluxes and pools remain poorly understood. Using data from a wet tropical flux tower site in French Guiana, we demonstrate that drought-induced carbon allocation shifts can be reliably inferred by assimilating Net Biosphere Exchange (NBE) and other observations within the CARbon DAta MOdel fraMework. This model-data fusion system allows inference of optimized carbon and water cycle parameters and states from multiple observational data streams. We then examined how these inferred shifts affected the duration and magnitude of drought's impact on NBE during and after the extreme event. Compared to a static allocation scheme analogous to those typically implemented in land surface models, dynamic allocation reduced average carbon uptake during drought recovery by a factor of 2.8. Additionally, the dynamic model extended the average recovery time by 5months. The inferred allocation shifts influenced the post-drought period by altering foliage and fine root pools, which in turn modulated gross primary productivity and heterotrophic respiration for up to a decade. These changes can create a bust-boom cycle where carbon uptake is enhanced some years after a drought, compared to what would have occurred under drought-free conditions. Overall, allocation shifts accounted for 65% [45%-75%] of drought legacy effects in modeled NBE. In summary, drought-induced carbon allocation shifts can play a substantial role in the enduring influence of drought on cumulative land-atmosphere CO2 exchanges and should be accounted for in ecosystem models.
View details for DOI 10.1111/gcb.17287
View details for PubMedID 38695768
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Plant responses to changing rainfall frequency and intensity
NATURE REVIEWS EARTH & ENVIRONMENT
2024
View details for DOI 10.1038/s43017-024-00534-0
View details for Web of Science ID 001199160200001
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Ecosystem Water-Saving Timescale Varies Spatially With Typical Drydown Length
AGU ADVANCES
2024; 5 (2)
View details for DOI 10.1029/2023AV001113
View details for Web of Science ID 001193239300001
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Investigating Diurnal and Seasonal Cycles of Vegetation Optical Depth Retrieved From GNSS Signals in a Broadleaf Forest
GEOPHYSICAL RESEARCH LETTERS
2024; 51 (6)
View details for DOI 10.1029/2023GL107121
View details for Web of Science ID 001187006300001
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A new empirical framework to quantify the hydraulic effects of soil and atmospheric drivers on plant water status
GLOBAL CHANGE BIOLOGY
2024; 30 (3): e17222
Abstract
Metrics to quantify regulation of plant water status at the daily as opposed to the seasonal scale do not presently exist. This gap is significant since plants are hypothesised to regulate their water potential not only with respect to slowly changing soil drought but also with respect to faster changes in air vapour pressure deficit (VPD), a variable whose importance for plant physiology is expected to grow because of higher temperatures in the coming decades. We present a metric, the stringency of water potential regulation, that can be employed at the daily scale and quantifies the effects exerted on plants by the separate and combined effect of soil and atmospheric drought. We test our theory using datasets from two experiments where air temperature and VPD were experimentally manipulated. In contrast to existing metrics based on soil drought that can only be applied at the seasonal scale, our metric successfully detects the impact of atmospheric warming on the regulation of plant water status. We show that the thermodynamic effect of VPD on plant water status can be isolated and compared against that exerted by soil drought and the covariation between VPD and soil drought. Furthermore, in three of three cases, VPD accounted for more than 5 MPa of potential effect on leaf water potential. We explore the significance of our findings in the context of potential future applications of this metric from plant to ecosystem scale.
View details for DOI 10.1111/gcb.17222
View details for Web of Science ID 001179968800001
View details for PubMedID 38450813
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The impacts of rising vapour pressure deficit in natural and managed ecosystems.
Plant, cell & environment
2024
Abstract
An exponential rise in the atmospheric vapour pressure deficit (VPD) is among the most consequential impacts of climate change in terrestrial ecosystems. Rising VPD has negative and cascading effects on nearly all aspects of plant function including photosynthesis, water status, growth and survival. These responses are exacerbated by land-atmosphere interactions that couple VPD to soil water and govern the evolution of drought, affecting a range of ecosystem services including carbon uptake, biodiversity, the provisioning of water resources and crop yields. However, despite the global nature of this phenomenon, research on how to incorporate these impacts into resilient management regimes is largely in its infancy, due in part to the entanglement of VPD trends with those of other co-evolving climate drivers. Here, we review the mechanistic bases of VPD impacts at a range of spatial scales, paying particular attention to the independent and interactive influence of VPD in the context of other environmental changes. We then evaluate the consequences of these impacts within key management contexts, including water resources, croplands, wildfire risk mitigation and management of natural grasslands and forests. We conclude with recommendations describing how management regimes could be altered to mitigate the otherwise highly deleterious consequences of rising VPD.
View details for DOI 10.1111/pce.14846
View details for PubMedID 38348610
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Water Stress Dominates 21st-Century Tropical Land Carbon Uptake
GLOBAL BIOGEOCHEMICAL CYCLES
2023; 37 (12)
View details for DOI 10.1029/2023GB007702
View details for Web of Science ID 001129420000001
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Impacts of climate timescale on the stability of trait-environment relationships.
The New phytologist
2023
Abstract
Predictive relationships between plant traits and environmental factors can be derived at global and regional scales, informing efforts to reorient ecological models around functional traits. However, in a changing climate, the environmental variables used as predictors in such relationships are far from stationary. This could yield errors in trait-environment model predictions if timescale is not accounted for. Here, the timescale dependence of trait-environment relationships is investigated by regressing in situ trait measurements of specific leaf area, leaf nitrogen content, and wood density on local climate characteristics summarized across several increasingly long timescales. We identify contrasting responses of leaf and wood traits to climate timescale. Leaf traits are best predicted by recent climate timescales, while wood density is a longer term memory trait. The use of sub-optimal climate timescales reduces the accuracy of the resulting trait-environment relationships. This study concludes that plant traits respond to climate conditions on the timescale of tissue lifespans rather than long-term climate normals, even at large spatial scales where multiple ecological and physiological mechanisms drive trait change. Thus, determining trait-environment relationships with temporally relevant climate variables may be critical for predicting trait change in a nonstationary climate system.
View details for DOI 10.1111/nph.19416
View details for PubMedID 38037289
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Constraining Plant Hydraulics With Microwave Radiometry in a Land Surface Model: Impacts of Temporal Resolution
WATER RESOURCES RESEARCH
2023; 59 (11)
View details for DOI 10.1029/2023WR035481
View details for Web of Science ID 001108791100001
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Diagnosing evapotranspiration responses to water deficit across biomes using deep learning
NEW PHYTOLOGIST
2023; 240 (3): 968-983
Abstract
Accounting for water limitation is key to determining vegetation sensitivity to drought. Quantifying water limitation effects on evapotranspiration (ET) is challenged by the heterogeneity of vegetation types, climate zones and vertically along the rooting zone. Here, we train deep neural networks using flux measurements to study ET responses to progressing drought conditions. We determine a water stress factor (fET) that isolates ET reductions from effects of atmospheric aridity and other covarying drivers. We regress fET against the cumulative water deficit, which reveals the control of whole-column moisture availability. We find a variety of ET responses to water stress. Responses range from rapid declines of fET to 10% of its water-unlimited rate at several savannah and grassland sites, to mild fET reductions in most forests, despite substantial water deficits. Most sensitive responses are found at the most arid and warm sites. A combination of regulation of stomatal and hydraulic conductance and access to belowground water reservoirs, whether in groundwater or deep soil moisture, could explain the different behaviors observed across sites. This variety of responses is not captured by a standard land surface model, likely reflecting simplifications in its representation of belowground water storage.
View details for DOI 10.1111/nph.19197
View details for Web of Science ID 001063590100001
View details for PubMedID 37621238
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Global patterns of water storage in the rooting zones of vegetation
NATURE GEOSCIENCE
2023
View details for DOI 10.1038/s41561-023-01125-2
View details for Web of Science ID 000931745700001
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Global patterns of water storage in the rooting zones of vegetation.
Nature geoscience
2023; 16 (3): 250-256
Abstract
The rooting-zone water-storage capacity-the amount of water accessible to plants-controls the sensitivity of land-atmosphere exchange of water and carbon during dry periods. How the rooting-zone water-storage capacity varies spatially is largely unknown and not directly observable. Here we estimate rooting-zone water-storage capacity globally from the relationship between remotely sensed vegetation activity, measured by combining evapotranspiration, sun-induced fluorescence and radiation estimates, and the cumulative water deficit calculated from daily time series of precipitation and evapotranspiration. Our findings indicate plant-available water stores that exceed the storage capacity of 2-m-deep soils across 37% of Earth's vegetated surface. We find that biome-level variations of rooting-zone water-storage capacities correlate with observed rooting-zone depth distributions and reflect the influence of hydroclimate, as measured by the magnitude of annual cumulative water-deficit extremes. Smaller-scale variations are linked to topography and land use. Our findings document large spatial variations in the effective root-zone water-storage capacity and illustrate a tight link among the climatology of water deficits, rooting depth of vegetation and its sensitivity to water stress.
View details for DOI 10.1038/s41561-023-01125-2
View details for PubMedID 36920146
View details for PubMedCentralID PMC10005945
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Remotely Sensed Soil Moisture Can Capture Dynamics Relevant to Plant Water Uptake
WATER RESOURCES RESEARCH
2023; 59 (2)
View details for DOI 10.1029/2022WR033814
View details for Web of Science ID 000949533300001
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Attributing Past Carbon Fluxes to CO2 and Climate Change: Respiration Response to CO2 Fertilization Shifts Regional Distribution of the Carbon Sink
Global Biogeochemical Cycles
2023
View details for DOI 10.1029/2022GB007478
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Global net biome CO2 exchange predicted comparably well using parameter-environment relationships and plant functional types.
Global change biology
2022
Abstract
Accurate estimation and forecasts of net biome CO2 exchange (NBE) are vital for understanding the role of terrestrial ecosystems in a changing climate. Prior efforts to improve NBE predictions have predominantly focused on increasing models' structural realism (and thus complexity), but parametric error and uncertainty are also key determinants of model skill. Here, we investigate how different parameterization assumptions propagate into NBE prediction errors across the globe, pitting the traditional plant functional type (PFT)-based approach against a novel top-down, machine learning-based "environmental filtering" (EF) approach. To do so, we simulate these contrasting methods for parameter assignment within a flexible model-data fusion framework of the terrestrial carbon cycle (CARDAMOM) at global scale. In the PFT-based approach, model parameters from a small number of select locations are applied uniformly within regions sharing similar land cover characteristics. In the EF-based approach, a pixel's parameters are predicted based on underlying relationships with climate, soil, and canopy properties. To isolate the role of parametric from structural uncertainty in our analysis, we benchmark the resulting PFT-based and EF-based NBE predictions with estimates from CARDAMOM's Bayesian optimization approach (whereby "true" parameters consistent with a suite of data constraints are retrieved on a pixel-by-pixel basis). When considering the mean absolute error of NBE predictions across time, we find that the EF-based approach matches or outperforms the PFT-based approach at 55% of pixels-a narrow majority. However, NBE estimates from the EF-based approach are susceptible to compensation between errors in component flux predictions, and predicted parameters can align poorly with the assumed "true" values. Overall, though, the EF-based approach is comparable to conventional approaches and merits further investigation to better understand and resolve these limitations. This work provides insight into the relationship between TBM performance and parametric uncertainty, informing efforts to improve model parameterization via PFT-free and trait-based approaches.
View details for DOI 10.1111/gcb.16574
View details for PubMedID 36560840
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Evapotranspiration frequently increases during droughts
NATURE CLIMATE CHANGE
2022
View details for DOI 10.1038/s41558-022-01505-3
View details for Web of Science ID 000876031500006
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Can We Use the Water Budget to Infer Upland Catchment Behavior? The Role of Data Set Error Estimation and Interbasin Groundwater Flow
WATER RESOURCES RESEARCH
2022; 58 (9)
View details for DOI 10.1029/2021WR030966
View details for Web of Science ID 000858992300001
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Canopy Height and Climate Dryness Parsimoniously Explain Spatial Variation of Unstressed Stomatal Conductance
GEOPHYSICAL RESEARCH LETTERS
2022; 49 (15)
View details for DOI 10.1029/2022GL099339
View details for Web of Science ID 000838218100001
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Soil hydrology in the Earth system
NATURE REVIEWS EARTH & ENVIRONMENT
2022; 3 (9): 573-587
View details for DOI 10.1038/s43017-022-00324-6
View details for Web of Science ID 000836416900002
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Quantifying the Global Power Needed for Sap Ascent in Plants
JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
2022; 127 (8)
View details for DOI 10.1029/2022JG006922
View details for Web of Science ID 000848238200001
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Climate change-induced peatland drying in Southeast Asia
ENVIRONMENTAL RESEARCH LETTERS
2022; 17 (7)
View details for DOI 10.1088/1748-9326/ac7969
View details for Web of Science ID 000820455600001
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Intra-Specific Variability in Plant Hydraulic Parameters Inferred From Model Inversion of Sap Flux Data
JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
2022; 127 (6)
View details for DOI 10.1029/2021JG006777
View details for Web of Science ID 000812192200001
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Historically inconsistent productivity and respiration fluxes in the global terrestrial carbon cycle.
Nature communications
2022; 13 (1): 1733
Abstract
The terrestrial carbon cycle is a major source of uncertainty in climate projections. Its dominant fluxes, gross primary productivity (GPP), and respiration (in particular soil respiration, RS), are typically estimated from independent satellite-driven models and upscaled in situ measurements, respectively. We combine carbon-cycle flux estimates and partitioning coefficients to show that historical estimates of global GPP and RS are irreconcilable. When we estimate GPP based on RS measurements and some assumptions about RS:GPP ratios, we found the resulted global GPP values (bootstrap mean [Formula: see text] Pg C yr-1) are significantly higher than most GPP estimates reported in the literature ([Formula: see text] Pg C yr-1). Similarly, historical GPP estimates imply a soil respiration flux (RsGPP, bootstrap mean of [Formula: see text] Pg C yr-1) statistically inconsistent with most published RS values ([Formula: see text] Pg C yr-1), although recent, higher, GPP estimates are narrowing this gap. Furthermore, global RS:GPP ratios are inconsistent with spatial averages of this ratio calculated from individual sites as well as CMIP6 model results. This discrepancy has implications for our understanding of carbon turnover times and the terrestrial sensitivity to climate change. Future efforts should reconcile the discrepancies associated with calculations for GPP and Rs to improve estimates of the global carbon budget.
View details for DOI 10.1038/s41467-022-29391-5
View details for PubMedID 35365658
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Confronting the water potential information gap.
Nature geoscience
2022; 15 (3): 158-164
Abstract
Water potential directly controls the function of leaves, roots, and microbes, and gradients in water potential drive water flows throughout the soil-plant-atmosphere continuum. Notwithstanding its clear relevance for many ecosystem processes, soil water potential is rarely measured in-situ, and plant water potential observations are generally discrete, sparse, and not yet aggregated into accessible databases. These gaps limit our conceptual understanding of biophysical responses to moisture stress and inject large uncertainty into hydrologic and land surface models. Here, we outline the conceptual and predictive gains that could be made with more continuous and discoverable observations of water potential in soils and plants. We discuss improvements to sensor technologies that facilitate in situ characterization of water potential, as well as strategies for building new networks that aggregate water potential data across sites. We end by highlighting novel opportunities for linking more representative site-level observations of water potential to remotely-sensed proxies. Together, these considerations offer a roadmap for clearer links between ecohydrological processes and the water potential gradients that have the 'potential' to substantially reduce conceptual and modeling uncertainties.
View details for DOI 10.1038/s41561-022-00909-2
View details for PubMedID 35300262
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Plant-water sensitivity regulates wildfire vulnerability.
Nature ecology & evolution
2022
Abstract
Extreme wildfires extensively impact human health and the environment. Increasing vapour pressure deficit (VPD) has led to a chronic increase in wildfire area in the western United States, yet some regions have been more affected than others. Here we show that for the same increase in VPD, burned area increases more in regions where vegetation moisture shows greater sensitivity to water limitation (plant-water sensitivity; R2=0.71). This has led to rapid increases in human exposure to wildfire risk, both because the population living in areas with high plant-water sensitivity grew 50% faster during 1990-2010 than in other wildland-urban interfaces and because VPD has risen most rapidly in these vulnerable areas. As plant-water sensitivity is strongly linked to wildfire vulnerability, accounting for ecophysiological controls should improve wildfire forecasts. If recent trends in VPD and demographic shifts continue, human wildfire risk will probably continue to increase.
View details for DOI 10.1038/s41559-021-01654-2
View details for PubMedID 35132185
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SIDE-FACING UHF-BAND RADAR SYSTEM TO MONITOR TREE WATER STATUS
IEEE. 2022: 5559-5562
View details for DOI 10.1109/IGARSS46834.2022.9883620
View details for Web of Science ID 000920916605160
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Achieving Breakthroughs in Global Hydrologic Science by Unlocking the Power of Multisensor, Multidisciplinary Earth Observations
AGU ADVANCES
2021; 2 (4)
View details for DOI 10.1029/2021AV000455
View details for Web of Science ID 000736630100005
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Atmospheric variability contributes to increasing wildfire weather but not as much as global warming.
Proceedings of the National Academy of Sciences of the United States of America
2021; 118 (46)
View details for DOI 10.1073/pnas.2117876118
View details for PubMedID 34764227
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Opportunities, challenges and pitfalls in characterizing plant water-use strategies
FUNCTIONAL ECOLOGY
2021
View details for DOI 10.1111/1365-2435.13945
View details for Web of Science ID 000710008900001
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Detecting Forest Response to Droughts with Global Observations of Vegetation Water Content.
Global change biology
2021
Abstract
Droughts in a warming climate have become more common and more extreme, making understanding forest responses to water stress increasingly pressing. Analysis of water stress in trees has long focused on water potential in xylem and leaves, which influences stomatal closure and water flow through the soil-plant-atmosphere continuum. At the same time, changes of vegetation water content (VWC) are linked to a range of tree responses, including fluxes of water and carbon, mortality, flammability, and more. Unlike water potential, which requires demanding in situ measurements, VWC can be retrieved from remote sensing measurements, particularly at microwave frequencies using radar and radiometry. Here, we highlight key frontiers through which VWC has the potential to significantly increase our understanding of forest responses to water stress. To validate remote sensing observations of VWC at landscape scale and to better relate them to data assimilation model parameters, we introduce an ecosystem-scale analogue of the pressure-volume curve, the non-linear relationship between average leaf or branch water potential and water content commonly used in plant hydraulics. The sources of variability in these ecosystem-scale pressure-volume curves and their relationship to forest response to water stress are discussed. We further show to what extent diel, seasonal, and decadal dynamics of VWC reflect variations in different processes relating the tree response to water stress. VWC can also be used for inferring belowground conditions - which are difficult to impossible to observe directly. Lastly, we discuss how a dedicated geostationary spaceborne observational system for VWC, when combined with existing datasets, can capture diel and seasonal water dynamics to advance the science and applications of global forest vulnerability to future droughts.
View details for DOI 10.1111/gcb.15872
View details for PubMedID 34478589
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Interannual Variations of Vegetation Optical Depth are Due to Both Water Stress and Biomass Changes
GEOPHYSICAL RESEARCH LETTERS
2021; 48 (16)
View details for DOI 10.1029/2021GL095267
View details for Web of Science ID 000688759800043
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Extreme wet events as important as extreme dry events in controlling spatial patterns of vegetation greenness anomalies
ENVIRONMENTAL RESEARCH LETTERS
2021; 16 (7)
View details for DOI 10.1088/1748-9326/abfc78
View details for Web of Science ID 000667939300001
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Global Coordination in Plant Physiological and Rooting Strategies in Response to Water Stress
GLOBAL BIOGEOCHEMICAL CYCLES
2021; 35 (7)
View details for DOI 10.1029/2020GB006758
View details for Web of Science ID 000677815700006
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Global ecosystem-scale plant hydraulic traits retrieved using model-data fusion
HYDROLOGY AND EARTH SYSTEM SCIENCES
2021; 25 (5): 2399-2417
View details for DOI 10.5194/hess-25-2399-2021
View details for Web of Science ID 000651041700001
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Optimal model complexity for terrestrial carbon cycle prediction
BIOGEOSCIENCES
2021; 18 (8): 2727-2754
View details for DOI 10.5194/bg-18-2727-2021
View details for Web of Science ID 000646696300003
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Promoting Connectivity of Network-Like Structures by Enforcing Region Separation.
IEEE transactions on pattern analysis and machine intelligence
2021; PP
Abstract
We propose a novel, connectivity-oriented loss function for training deep convolutional networks to reconstruct network-like structures, like roads and irrigation canals, from aerial images. The main idea behind our loss is to express the connectivity of roads, or canals, in terms of disconnections that they create between background regions of the image. In simple terms, a gap in the predicted road causes two background regions, that lie on the opposite sides of a ground truth road, to touch in prediction. Our loss function is designed to prevent such unwanted connections between background regions, and therefore close the gaps in predicted roads. It also prevents predicting false positive roads and canals by penalizing unwarranted disconnections of background regions. In order to capture even short, dead-ending road segments, we evaluate the loss in small image crops. We show, in experiments on two standard road benchmarks and a new data set of irrigation canals, that convnets trained with our loss function recover road connectivity so well that it suffices to skeletonize their output to produce state of the art maps. A distinct advantage of our approach is that the loss can be plugged in to any existing training setup without further modifications.
View details for DOI 10.1109/TPAMI.2021.3074366
View details for PubMedID 33881988
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Satellite Observations of the Tropical Terrestrial Carbon Balance and Interactions With the Water Cycle During the 21st Century
REVIEWS OF GEOPHYSICS
2021; 59 (1)
View details for DOI 10.1029/2020RG000711
View details for Web of Science ID 000635222000004
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Patterns of plant rehydration and growth following pulses of soil moisture availability
BIOGEOSCIENCES
2021; 18 (3): 831-847
View details for DOI 10.5194/bg-18-831-2021
View details for Web of Science ID 000618241600001
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Empirical estimates of regional carbon budgets imply reduced global soil heterotrophic respiration
NATIONAL SCIENCE REVIEW
2021; 8 (2)
View details for DOI 10.1093/nsr/nwaa145
View details for Web of Science ID 000632214600007
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L-band vegetation optical depth as an indicator of plant water potential in a temperate deciduous forest stand
BIOGEOSCIENCES
2021; 18 (2): 739-753
View details for DOI 10.5194/bg-18-739-2021
View details for Web of Science ID 000617355500001
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Global-scale assessment and inter-comparison of recently developed/reprocessed microwave satellite vegetation optical depth products
REMOTE SENSING OF ENVIRONMENT
2021; 253
View details for DOI 10.1016/j.rse.2020.112208
View details for Web of Science ID 000604328800004
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Empirical estimates of regional carbon budgets imply reduced global soil heterotrophic respiration.
National science review
2021; 8 (2): nwaa145
Abstract
Resolving regional carbon budgets is critical for informing land-based mitigation policy. For nine regions covering nearly the whole globe, we collected inventory estimates of carbon-stock changes complemented by satellite estimates of biomass changes where inventory data are missing. The net land-atmospheric carbon exchange (NEE) was calculated by taking the sum of the carbon-stock change and lateral carbon fluxes from crop and wood trade, and riverine-carbon export to the ocean. Summing up NEE from all regions, we obtained a global 'bottom-up' NEE for net land anthropogenic CO2 uptake of -2.2 ± 0.6 PgC yr-1 consistent with the independent top-down NEE from the global atmospheric carbon budget during 2000-2009. This estimate is so far the most comprehensive global bottom-up carbon budget accounting, which set up an important milestone for global carbon-cycle studies. By decomposing NEE into component fluxes, we found that global soil heterotrophic respiration amounts to a source of CO2 of 39 PgC yr-1 with an interquartile of 33-46 PgC yr-1-a much smaller portion of net primary productivity than previously reported.
View details for DOI 10.1093/nsr/nwaa145
View details for PubMedID 34691569
View details for PubMedCentralID PMC8288404
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Leaf surface water, not plant water stress, drives diurnal variation in tropical forest canopy water content.
The New phytologist
2021
Abstract
Variation in canopy water content (CWC) that can be detected from microwave remote sensing of vegetation optical depth (VOD) has been proposed as an important measure of vegetation water stress. However, the contribution of leaf surface water (LWs ), arising from dew formation and rainfall interception, to CWC is largely unknown, particularly in tropical forests and other high-humidity ecosystems. We compared the AMSR-E VOD and CWC predicted by a plant hydro-dynamics model at four tropical sites in Brazil spanning a rainfall gradient. We assessed how LWs influenced the relationship between VOD and CWC. The analysis indicates that while CWC is strongly correlated with VOD (R2 =0.62 across all sites), LWs accounts for 61-76% of the diurnal variation in CWC despite being less than 10% of CWC. Ignoring LWs weakens the near-linear relationship between CWC and VOD and reduces the consistency in diurnal variation. The contribution of LWs to CWC variation, however, decreases at longer, seasonal to interannual, time scales. Our results demonstrate that diurnal patterns of dew formation and rainfall interception can be an important driver of diurnal variation in CWC and VOD over tropical ecosystems and therefore should be accounted for when inferring plant diurnal water stress from VOD measurements.
View details for DOI 10.1111/nph.17254
View details for PubMedID 33539544
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Drainage Canals in Southeast Asian Peatlands Increase Carbon Emissions
AGU Advances
2021; 2 (1): 1-14
View details for DOI 10.1029/2020AV000321
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Lagged effects regulate the inter-annual variability of the tropical carbon balance
BIOGEOSCIENCES
2020; 17 (24): 6393–6422
View details for DOI 10.5194/bg-17-6393-2020
View details for Web of Science ID 000604823600002
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Interannual variability of ecosystem iso/anisohydry is regulated by environmental dryness.
The New phytologist
2020
Abstract
Plants are characterized by the iso/anisohydry continuum depending on how they regulate leaf water potential (PsiL ). However, how iso/anisohydry changes over time in response to year-to-year variations in environmental dryness and how such responses vary across different regions remains poorly characterized. We investigated how dryness, represented by aridity index, affects the interannual variability of ecosystem iso/anisohydry at the regional scale, estimated using satellite microwave vegetation optical depth (VOD) observations. This ecosystem-level analysis was further complemented with published field observations of species-level PsiL . We found different behaviors in the directionality and sensitivity of isohydricity (sigma) with respect to the interannual variation of dryness in different ecosystems. These behaviors can largely be differentiated by the average dryness of the ecosystem itself: in mesic ecosystems, sigma decreases in drier years with a higher sensitivity to dryness; in xeric ecosystems, sigma increases in drier years with a lower sensitivity to dryness. These results were supported by the species-level synthesis. Our study suggests that how plants adjust their water use across years - as revealed by their interannual variability in isohydricity - depends on the dryness of plants' living environment. This finding advances our understanding of plant responses to drought at regional scales.
View details for DOI 10.1111/nph.17040
View details for PubMedID 33118166
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SMAP Detects Soil Moisture Under Temperate Forest Canopies
GEOPHYSICAL RESEARCH LETTERS
2020; 47 (19)
View details for DOI 10.1029/2020GL089697
View details for Web of Science ID 000584669000053
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Divergent forest sensitivity to repeated extreme droughts
NATURE CLIMATE CHANGE
2020
View details for DOI 10.1038/s41558-020-00919-1
View details for Web of Science ID 000573420000001
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Data-driven estimates of evapotranspiration and its controls in the Congo Basin
HYDROLOGY AND EARTH SYSTEM SCIENCES
2020; 24 (8): 4189–4211
View details for DOI 10.5194/hess-24-4189-2020
View details for Web of Science ID 000566701000001
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SAR-enhanced mapping of live fuel moisture content
REMOTE SENSING OF ENVIRONMENT
2020; 245
View details for DOI 10.1016/j.rse.2020.111797
View details for Web of Science ID 000537687300004
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Plant hydraulics accentuates the effect of atmospheric moisture stress on transpiration
NATURE CLIMATE CHANGE
2020
View details for DOI 10.1038/s41558-020-0781-5
View details for Web of Science ID 000537042800011
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Carbon Flux Variability from a Relatively Simple Ecosystem Model with Assimilated Data is Consistent with Terrestrial Biosphere Model Estimates
Journal of Advances in Modeling Earth Systems
2020; 12: e2019MS001889
View details for DOI 10.1029/2019MS001889
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SMAP VALIDATION EXPERIMENT 2019-2021 (SMAPVEX19-21): DETECTION OF SOIL MOISTURE UNDER FOREST CANOPY
IEEE. 2020: 3338-3340
View details for DOI 10.1109/IGARSS39084.2020.9323889
View details for Web of Science ID 000664335303084
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Validation practices for satellite soil moisture retrievals: What are (the) errors?
Remote Sensing of Environment
2020; 224: 111806
View details for DOI 10.1016/j.rse.2020.111806
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Satellite-based vegetation optical depth as an indicator of drought-driven tree mortality
REMOTE SENSING OF ENVIRONMENT
2019; 227: 125–36
View details for DOI 10.1016/j.rse.2019.03.026
View details for Web of Science ID 000468720300009
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Global satellite-driven estimates of heterotrophic respiration
BIOGEOSCIENCES
2019; 16 (11): 2269–84
View details for DOI 10.5194/bg-16-2269-2019
View details for Web of Science ID 000470702100002
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Macro to Micro: Microwave Remote Sensing of Plant Water Content for Physiology and Ecology.
The New phytologist
2019
Abstract
Although primarily valued for their suitability for oceanographic applications and soil moisture estimation, microwave remote sensing observations are also sensitive to plant water content (Mw ). Since Mw depends on both plant water status and biomass, these observations have the potential to be useful for a range of plant drought response studies. In this paper, we introduce the principles behind microwave remote sensing observations to illustrate how they are sensitive to plant water content and discuss the relationship between landscape-scale Mw and common stand-scale metrics, including plant-scale relative water content, live fuel moisture content and leaf water potential. Lastly, we discuss how various sensor types can be leveraged for specific applications depending on the spatio-temporal resolution needed. This article is protected by copyright. All rights reserved.
View details for PubMedID 30919449
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Physics-Based Modeling of Active and Passive Microwave Covariations Over Vegetated Surfaces
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
2019; 57 (2): 788–802
View details for DOI 10.1109/TGRS.2018.2860630
View details for Web of Science ID 000456936500012
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Satellite soil moisture observatins predict burned area in Southeast Asian peatlands
ENVIRONMENTAL RESEARCH LETTERS
2019; 14
View details for DOI 10.1088/1748-9326/ab3891
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Simultaneous retrieval of global-scale vegetation optical depth, surface roughness, and soil moisture using X-band AMSR-E observations
Remote Sensing of Environment
2019; 234: 111473
View details for DOI 10.1016/j.rse.2019.111473
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Macro to micro: microwave remote sensing of plant water content for physiology and ecology
NEW PHYTOLOGIST
2019; 223: 1166-1172
Abstract
Although primarily valued for their suitability for oceanographic applications and soil moisture estimation, microwave remote sensing observations are also sensitive to plant water content (Mw ). Since Mw depends on both plant water status and biomass, these observations have the potential to be useful for a range of plant drought response studies. In this paper, we introduce the principles behind microwave remote sensing observations to illustrate how they are sensitive to plant water content and discuss the relationship between landscape-scale Mw and common stand-scale metrics, including plant-scale relative water content, live fuel moisture content and leaf water potential. Lastly, we discuss how various sensor types can be leveraged for specific applications depending on the spatio-temporal resolution needed.
View details for DOI 10.1111/nph.15808
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Beyond soil water potential: An expanded view on isohydricity including land–atmosphere interactions and phenology
PLANT, CELL, AND ENVIRONMENT
2019; 42: 1802-1815
Abstract
Over the past decade, the concept of iso/anisohydry, which describes the link between soil water potential (ΨS ), leaf water potential (ΨL ), and stomatal conductance (gS ), has soared in popularity. However, its utility has recently been questioned, and a surprising lack of coordination between the dynamics of ΨL and gS across biomes has been reported. Here, we offer a more expanded view of the isohydricity concept that considers effects of vapor pressure deficit (VPD) and leaf area index (AL ) on the apparent sensitivities of ΨL and gs to drought. After validating the model with tree and ecosystem scale data, we find that within a site, isohydricity is a strong predictor of limitations to stomatal function, though variation in VPD and leaf area, among other factors, can challenge its diagnosis. Across sites, the theory predicts that the degree of isohydricity is a good predictor of the sensitivity of gs to declining soil water in the absence of confounding effects from other drivers. However, if VPD effects are significant, they alone are sufficient to decouple the dynamics of ΨL and gs entirely. We conclude with a set of practical recommendations for future applications of the isohydricity framework within and across sites.
View details for DOI 10.1111/pce.13517
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Moisture pulse-reserve in the soil-plant continuum observed across biomes
NATURE PLANTS
2018; 4 (12): 1026–33
Abstract
The degree to which individual pulses of available water drive plant activity across diverse biomes and climates is not well understood. It has previously only been investigated in a few dryland locations. Here, plant water uptake following pulses of surface soil moisture, an indicator for the pulse-reserve hypothesis, is investigated across South America, Africa and Australia with satellite-based estimates of surface soil and canopy water content. Our findings show that this behaviour is widespread: occurring over half of the vegetated landscapes. We estimate spatially varying soil moisture thresholds at which plant water uptake ceases, noting dependence on soil texture and proximity to the wilting point. The soil type and biome-dependent soil moisture threshold and the plant soil water uptake patterns at the scale of Earth system models allow a unique opportunity to test and improve model parameterization of vegetation function under water limitation.
View details for DOI 10.1038/s41477-018-0304-9
View details for Web of Science ID 000454576600012
View details for PubMedID 30518832
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Characterization of vegetation and soil scattering mechanisms across different biomes using P-band SAR polarimetry
REMOTE SENSING OF ENVIRONMENT
2018: 107-117
View details for DOI 10.1016/j.rse.2018.02.032
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Hydraulic diversity of forests regulates ecosystem resilience during drought
NATURE
2018; 561: 538-541
Abstract
Plants influence the atmosphere through fluxes of carbon, water and energy1, and can intensify drought through land-atmosphere feedback effects2-4. The diversity of plant functional traits in forests, especially physiological traits related to water (hydraulic) transport, may have a critical role in land-atmosphere feedback, particularly during drought. Here we combine 352 site-years of eddy covariance measurements from 40 forest sites, remote-sensing observations of plant water content and plant functional-trait data to test whether the diversity in plant traits affects the response of the ecosystem to drought. We find evidence that higher hydraulic diversity buffers variation in ecosystem flux during dry periods across temperate and boreal forests. Hydraulic traits were the predominant significant predictors of cross-site patterns in drought response. By contrast, standard leaf and wood traits, such as specific leaf area and wood density, had little explanatory power. Our results demonstrate that diversity in the hydraulic traits of trees mediates ecosystem resilience to drought and is likely to have an important role in future ecosystem-atmosphere feedback effects in a changing climate.
View details for DOI 10.1038/s41586-018-0539-7
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Tall Amazonian forests are less sensitive to precipitation variability
NATURE GEOSCIENCE
2018: 405-409
View details for DOI 10.1038/s41561-018-0133-5
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L-band vegetation optical depth seasonal metrics for crop yield assessment
REMOTE SENSING OF ENVIRONMENT
2018
View details for DOI 10.1016/j.rse.2018.04.049
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Global-scale assessment and combination of SMAP with ASCAT (active) and AMSR2 (passive) soil moisture products
REMOTE SENSING OF ENVIRONMENT
2018; 204: 260-275
View details for DOI 10.1016/j.rse.2017.10.026
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Active microwave observations of diurnal and seasonal variations of canopy water content across the humid African tropical forests
GEOPHYSICAL RESEARCH LETTERS
2017; 44 (5): 2290-2299
View details for DOI 10.1002/2016GL072388
View details for Web of Science ID 000398183700028
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Active microwave observations of diurnal and seasonal variations of canopy water content across the humid African tropical forests
GEOPHYSICAL RESEARCH LETTERS
2017; 44: 2290-2299
View details for DOI 10.1002/2016GL072388
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Water, Energy, and Carbon with Artificial Neural Networks (WECANN): a statistically based estimate of global surface turbulent fluxes and gross primary productivity using solar-induced fluorescence
BIOGEOSCIENCES
2017; 14: 4101-4124
Abstract
A new global estimate of surface turbulent fluxes, latent heat flux (LE) and sensible heat flux (H), and gross primary production (GPP) is developed using a machine learning approach informed by novel remotely sensed Solar-Induced Fluorescence (SIF) and other radiative and meteorological variables. This is the first study to jointly retrieve LE, H and GPP using SIF observations. The approach uses an artificial neural network (ANN) with a target dataset generated from three independent data sources, weighted based on triple collocation (TC) algorithm. The new retrieval, named Water, Energy, and Carbon with Artificial Neural Networks (WECANN), provides estimates of LE, H and GPP from 2007 to 2015 at 1° × 1° spatial resolution and on monthly time resolution. The quality of ANN training is assessed using the target data, and the WECANN retrievals are evaluated using eddy covariance tower estimates from FLUXNET network across various climates and conditions. When compared to eddy covariance estimates, WECANN typically outperforms other products, particularly for sensible and latent heat fluxes. Analysing WECANN retrievals across three extreme drought and heatwave events demonstrates the capability of the retrievals in capturing the extent of these events. Uncertainty estimates of the retrievals are analysed and the inter-annual variability in average global and regional fluxes show the impact of distinct climatic events - such as the 2015 El Niño - on surface turbulent fluxes and GPP.
View details for DOI 10.5194/bg-14-4101-2017
View details for PubMedCentralID PMC5744880
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Estimating global ecosystem iso/anisohydry using active and passive microwave satellite data
JOURNAL OF GEOPHYSICAL RESEARCH - BIOGEOSCIENCES
2017; 122
View details for DOI 10.1002/2017JG003958
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Regionally strong feedbacks between the atmosphere and terrestrial biosphere
NATURE GEOSCIENCE
2017; 10: 410–414
View details for DOI 10.1038/ngeo2957
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L-band vegetation optical depth and scattering albedo estimation from SMAP
REMOTE SENSING OF ENVIRONMENT
2017; 198: 460-470
View details for DOI 10.1016/j.rse.2017.06.037
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Relationship between vegetation microwave optical depth and cross-polarized backscatter from multi-year Aquarius observations.
IEEE JOURNAL OF SELECTED TOPICS IN EARTH OBSERVATIONS AND REMOTE SENSING
2017
View details for DOI 10.1109/JSTARS.2017.2716638
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Interacting effects of leaf water potential and biomass on vegetation optical depth
JOURNAL OF GEOPHYSICAL RESEARCH - BIOGEOSCIENCES
2017; 122
View details for DOI 10.1002/2017JG004145
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The global distribution and dynamics of surface soil moisture
NATURE GEOSCIENCE
2017; 10: 100-104
View details for DOI 10.1038/ngeo2868
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Global variations in ecosystem scale isohydricity
GLOBAL CHANGE BIOLOGY
2017; 23 (2): 891-905
Abstract
Droughts are expected to become more frequent and more intense under climate change. Plant mortality rates and biomass declines in response to drought depend on stomatal and xylem flow regulation. Plants operate on a continuum of xylem and stomatal regulation strategies from very isohydric (strict regulation) to very anisohydric. Coexisting species may display a variety of isohydricity behaviors. As such, it can be difficult to predict how to model the degree of isohydricity at the ecosystem scale by aggregating studies of individual species. This is nonetheless essential for accurate prediction of ecosystem drought resilience. In this study, we define a metric for the degree of isohydricity at the ecosystem scale in analogy with a recent metric introduced at the species level. Using data from the AMSR-E satellite, this metric is evaluated globally based on diurnal variations in microwave vegetation optical depth (VOD), which is directly related to leaf water potential. Areas with low annual mean radiation are found to be more anisohydric. Except for evergreen broadleaf forests in the tropics, which are very isohydric, and croplands, which are very anisohydric, land cover type is a poor predictor of ecosystem isohydricity, in accordance with previous species-scale observations. It is therefore also a poor basis for parameterizing water stress response in land-surface models. For taller ecosystems, canopy height is correlated with higher isohydricity (so that rainforests are mostly isohydric). Highly anisohydric areas show either high or low underlying water use efficiency. In seasonally dry locations, most ecosystems display a more isohydric response (increased stomatal regulation) during the dry season. In several seasonally dry tropical forests, this trend is reversed, as dry-season leaf-out appears to coincide with a shift toward more anisohydric strategies. The metric developed in this study allows for detailed investigations of spatial and temporal variations in plant water behavior.
View details for DOI 10.1111/gcb.13389
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Sensitivity of grassland productivity to aridity controlled by stomatal and xylem regulation
NATURE GEOSCIENCE
2017; 10: 284-288
View details for DOI 10.1038/ngeo2903
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Triple collocation for binary and categorical variables: Application to validating landscape freeze/thaw retrievals
REMOTE SENSING OF ENVIRONMENT
2016; 176: 31-42
View details for DOI 10.1016/j.rse.2016.01.010
View details for Web of Science ID 000372383200003
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Vegetation optical depth and scattering albedo retrieval using time series of dual-polarized L-band radiometer observations
REMOTE SENSING OF ENVIRONMENT
2016; 172: 178-189
View details for DOI 10.1016/j.rse.2015.11.009
View details for Web of Science ID 000366764500014
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L-Band Radar Soil Moisture Retrieval Without Ancillary Information
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
2015; 8 (12): 5526-5540
View details for DOI 10.1109/JSTARS.2015.2496326
View details for Web of Science ID 000370519700014
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How Many Parameters Can Be Maximally Estimated From a Set of Measurements?
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
2015; 12 (5): 1081-1085
View details for DOI 10.1109/LGRS.2014.2381641
View details for Web of Science ID 000351412200033
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Characterization of precipitation product errors across the United States using multiplicative triple collocation
HYDROLOGY AND EARTH SYSTEM SCIENCES
2015; 19 (8): 3489-3503
View details for DOI 10.5194/hess-19-3489-2015
View details for Web of Science ID 000360653600011
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The Effect of Variable Soil Moisture Profiles on P-Band Backscatter
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
2014; 52 (10): 6315-6325
View details for DOI 10.1109/TGRS.2013.2296035
View details for Web of Science ID 000337173200026
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Extended triple collocation: Estimating errors and correlation coefficients with respect to an unknown target
GEOPHYSICAL RESEARCH LETTERS
2014; 41 (17): 6229-6236
View details for DOI 10.1002/2014GL061322
View details for Web of Science ID 000342757400023
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Thermodynamics of an idealized hydrologic cycle
WATER RESOURCES RESEARCH
2012; 48
View details for DOI 10.1029/2011WR011264
View details for Web of Science ID 000304253400002
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A phenomenological model for the flow resistance over submerged vegetation
WATER RESOURCES RESEARCH
2012; 48
View details for DOI 10.1029/2011WR011000
View details for Web of Science ID 000300829700003
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Mean Velocity Profile in a Sheared and Thermally Stratified Atmospheric Boundary Layer
PHYSICAL REVIEW LETTERS
2011; 107 (26)
Abstract
A stability correction function φ(m)(ζ) that accounts for distortions to the logarithmic mean velocity profile (MVP) in the lower atmosphere caused by thermal stratification was proposed by Monin and Obukhov in the 1950s using dimensional analysis. Its universal character was established from many field experiments. However, theories that describe the canonical shape of φ(m)(ζ) are still lacking. A previous link between the spectrum of turbulence and the MVP is expanded here to include the effects of thermal stratification on the turbulent kinetic energy dissipation rate and eddy-size anisotropy. The resulting theory provides a novel explanation for the power-law exponents and coefficients already reported for φ(m)(ζ) from numerous field experiments.
View details for DOI 10.1103/PhysRevLett.107.268502
View details for Web of Science ID 000298609000019
View details for PubMedID 22243189
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Drought sensitivity of patterned vegetation determined by rainfall-land surface feedbacks
JOURNAL OF GEOPHYSICAL RESEARCH-BIOGEOSCIENCES
2011; 116
View details for DOI 10.1029/2011JG001748
View details for Web of Science ID 000296150900001
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Unsteady overland flow on flat surfaces induced by spatial permeability contrasts
ADVANCES IN WATER RESOURCES
2011; 34 (8): 1049-1058
View details for DOI 10.1016/j.advwatres.2011.05.012
View details for Web of Science ID 000293320700010
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Comparative hydrology across AmeriFlux sites: The variable roles of climate, vegetation, and groundwater
WATER RESOURCES RESEARCH
2011; 47
View details for DOI 10.1029/2010WR009797
View details for Web of Science ID 000292844600003
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Effect of Radiative Transfer Uncertainty on L-Band Radiometric Soil Moisture Retrieval
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
2011; 49 (7): 2686-2698
View details for DOI 10.1109/TGRS.2011.2105495
View details for Web of Science ID 000292111800018
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The rainfall-no rainfall transition in a coupled land-convective atmosphere system
GEOPHYSICAL RESEARCH LETTERS
2010; 37
View details for DOI 10.1029/2010GL043967
View details for Web of Science ID 000280584700003
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Conditioning Stochastic Rainfall Replicates on Remote Sensing Data
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
2009; 47 (8): 2436-2449
View details for DOI 10.1109/TGRS.2009.2016413
View details for Web of Science ID 000268166500004