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The 21st century evapotranspiration (ET) trends over the continental U.S. are assessed using innovative, energy‐based principles. Annual ET is projected to increase with high confidence at the rate of 20 mm for every 1℃ of rise in near‐surface air temperature, or 0.45 or 0.98 mm/year/year, depending on the emission scenario. The ET trajectory is dominated (58%) by the increase of land‐surface net radiative energy. An enhancement of the fraction of energy taken up by ET becomes a more important controller (53%) in late 21st century, under the high emission scenario. This increase is explained by the "tug of war" between atmospheric vapor demand and land‐surface ability to supply water. An assessment of future water availability (precipitation minus ET) shows no significant changes at the continental scale. This outcome nevertheless hides strong spatial variability, emphasizing the role of ET in shaping the distribution of water availability among human populations. Plain Language Summary: Water quantity in the environment is strongly controlled by its evaporation into the atmosphere from plants, soil, and water bodies—the process that is called evapotranspiration. This study calculates evapotranspiration trend over the U.S. during the 21st century and assesses factors determining its evolution. Annual evapotranspiration is predicted to grow at the rate of 20 mm for every 1° Celsius of rise in near‐surface air temperature, leading to 14%–23% increase with respect to the historic period, depending on climate scenario. This increase is due to the impacts of future greenhouse gas emissions on energy that fuels evapotranspiration, as well as interplay between the growing water vapor demand by the atmosphere and changing land‐surface water supply conditions in the warmer climate. The predicted evapotranspiration trends will result in the strengthening of uneven distribution of water quantity across the U.S. in the future. Key Points: Maximum Entropy Projection theory yields robust estimates of evapotranspiration (ET) under a warmer climateAvailable energy surplus and supply‐demand interactions result in temporally linear increase of ET over the contiguous U.SET and precipitation changes result in uneven spatial distribution of water availability (precipitation minus ET) [ABSTRACT FROM AUTHOR]

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 analog 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. [ABSTRACT FROM AUTHOR]

The fortedata R package is an open data notebook from the Forest Resilience Threshold Experiment (FoRTE) – a modeling and manipulative field experiment that tests the effects of disturbance severity and disturbance type on carbon cycling dynamics in a temperate forest. Package data consist of measurements of carbon pools and fluxes and ancillary measurements to help analyze and interpret carbon cycling over time. Currently the package includes data and metadata from the first three FoRTE field seasons, serves as a central, updatable resource for the FoRTE project team, and is intended as a resource for external users over the course of the experiment and in perpetuity. Further, it supports all associated FoRTE publications, analyses, and modeling efforts. This increases efficiency, consistency, compatibility, and productivity while minimizing duplicated effort and error propagation that can arise as a function of a large, distributed and collaborative effort. More broadly, fortedata represents an innovative, collaborative way of approaching science that unites and expedites the delivery of complementary datasets to the broader scientific community, increasing transparency and reproducibility of taxpayer-funded science. The fortedata package is available via GitHub: https://github.com/FoRTExperiment/fortedata (last access: 19 February 2021), and detailed documentation on the access, used, and applications of fortedata are available at https://fortexperiment.github.io/fortedata/ (last access: 19 February 2021). The first public release, version 1.0.1 is also archived at 10.5281/zenodo.4399601 (Atkins et al., 2020b). All data products are also available outside of the package as.csv files: 10.6084/m9.figshare.13499148.v1 (Atkins et al., 2020c). [ABSTRACT FROM AUTHOR]

The pre-disturbance vegetation characteristics that predict carbon (C) cycling responses to disturbance are not well known. To address this gap, we initiated the Forest Resilience Threshold Experiment, a manipulative study in which more than 3600 trees were stem girdled to achieve replicated factorial combinations of four levels (control, 45, 65, and 85% gross defoliation) of disturbance severity and two disturbance types (targeting upper or lower canopy strata). Applying a standardized stability framework in which initial C cycling resistance to disturbance was calculated as the first-year natural log response ratio of disturbance and control treatments, we investigated to what extent pre-disturbance levels of species diversity, aboveground woody biomass, leaf area index, and canopy rugosity—a measure of structural complexity—predict the initial responses of subcanopy light-saturated leaf CO2 assimilation (Asat), aboveground wood NPP (ANPPw), and soil respiration (Rs) to phloem-disrupting disturbance. In the year following stem girdling, we found that above-ground C cycling processes, Asat and ANPPw, were highly resistant to increases in disturbance severity, while Rs resistance declined as severity increased. Disturbance type had no effect on first-year resistance. Pre-disturbance aboveground woody biomass, and canopy rugosity were positive predictors of ANPPw resistance and, conversely, negatively related to Rs resistance. Subcanopy Asat resistance was not related to pre-disturbance vegetation characteristics. Stability of C uptake processes along with Rs declines suggest the net C sink was sustained in the initial months following disturbance. We conclude that biomass and complexity are significant, but not universal, predictors of initial C cycling resistance to disturbance. Moreover, our findings highlight the utility of standardized stability measures when comparing functional responses to disturbance. [ABSTRACT FROM AUTHOR]

The fortedata R package is an open data notebook from the Forest Resilience Threshold Experiment (FoRTE) – a modeling and manipulative field experiment that tests the effects of disturbance severity and disturbance type on carbon cycling dynamics in a temperate forest. Package data consists of measurements of carbon pools and fluxes and ancillary measurements to help users analyse and interpret carbon cycling over time. Currently the package includes data and metadata from the first two years of FoRTE, and serves as a central, updatable resource for the FoRTE project team and is intended as a resource for external users over the course of the experiment and in perpetuity. Further, it supports all associated FoRTE publications, analyses, and modeling efforts. This increases efficiency, consistency, compatibility, and productivity, while minimizing duplicated effort and error propagation that can arise as a function of a large, distributed and collaborative effort. More broadly, fortedata represents an innovative, collaborative way of approaching science that unites and expedites the delivery of complementary datasets in near real time to the broader scientific community, increasing transparency and reproducibility of taxpayer-funded science. fortedata is available via GitHub: https://github.com/FoRTExperiment/fortedata and detailed documentation on the access, used, and applications of fortedata are available at: https://fortexperiment.github.io/fortedata/. The first public release, version 1.0.1 is also archived at: https://doi.org/10.5281/zenodo.3936146 (Atkins et al., 2020b). All level one data products are also available outside of the package as .csv files: https://doi.org/10.6084/m9.figshare.12292490.v3 (Atkins et al. 2020c). [ABSTRACT FROM AUTHOR]

Adding our leaves: A community-wide perspective on research directions in ecohydrology Ecohydrology encompasses ideas and processes at the interface of hydrology and ecology acknowledging couplings and feedbacks between biology and water-related processes across a broad range of spatial and temporal scales. These papers described ecohydrology as a general concept (such as Newman et al., [53]); or review the state of ecohydrology Asbjornsen et al., [1]) or hydrology (e.g., Eagleson, [19]; Jones & Mulholland, [36]; Rodriguez-Iturbe, [61]). Given that much of ecohydrology research has been conducted under nonstationary climatic conditions, even identifying what baseline feedbacks exist between climate, hydrology, and ecology is challenging. [Extracted from the article]

Energy budget of Amazonian forests has a large influence on regional and global climate, but relevant data are scarce. A novel energy partition method based on the maximum entropy production (MEP) theory is applied to simulate evapotranspiration in Amazonia. Using site‐level eddy flux data, the MEP method shows high skill at the hourly, daily, and monthly scales. Consistent performance under different levels of land surface dryness is revealed, hinting that drought signal is appropriately resolved. The site‐level MEP‐based estimates outperform the estimates of the Moderate Resolution Imaging Spectroradiometer evapotranspiration product, which is commonly used for large‐scale assessments. At the Amazon basin scale, the two series yield similar averages but exhibit spatial differences. The parameter parsimony and demonstrated skill of the MEP method make it an attractive approach for environments with diverse strategies of water flux control. Plain Language Summary: Classical methods for estimating vapor flow from vegetated surfaces, known as the process of evapotranspiration, require input data on water vapor gradient, wind speed, and surface roughness as well as model parameters that are often difficult to obtain from in situ and remote sensing observations. The uncertainty of these variables can be especially large for the Amazon rainforest with high biodiversity, making it challenging to evaluate evapotranspiration in space and time. In this study, we assess the performance of a novel model that needs fewer input data and model parameters than classical methods. The model performance is validated through comparison with observations from nine sites across the Amazon basin and shows a better skill as compared to a commonly used evapotranspiration product. We also show that the model has a satisfactory performance in estimating evapotranspiration when satellite data are used, providing reasonable estimates at the scale of the entire Amazon basin. Key Points: Maximum entropy production theory demonstrates excellent skill in estimating evapotranspiration (ET) in the Amazon rainforestModel performance is consistent at different drought levels without using surface resistance parametersLarge differences are found with a commonly used ET product based on Moderate Resolution Imaging Spectroradiometer data [ABSTRACT FROM AUTHOR]

This article is a Commentary on Smith et al., 222: 1284–1297. [ABSTRACT FROM AUTHOR]