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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.

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]

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 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]

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]

Increasing numbers of patients are being treated for heart failure each year. One out of four of the heart failure patients who receives care in a hospital is readmitted to the hospital within 30 days of discharge. Effective discharge instruction is critical to prevent these patient readmissions. Co-production is a marketing concept whereby the customer is a partner in the delivery of a good or service. For example, a patient and nurse may partner to co-produce a patient-centered health regimen to improve patient outcomes. In this article we review the cost of treating heart failure patients and current strategies to decrease hospital readmissions for these patients along with the role of the nurse and the concept of co-producing health as related to heart failure patients. Next we describe our study assessing the degree to which discharge processes were co-produced on two hospital units having a preponderance of heart failure patients, and present our findings indicating minimal evidence of co-production. A discussion of our findings, along with clinical implications of these findings, recommendations for change, and suggestions for future research are offered. We conclude that standardized discharge plans lead to a mindset of 'one size fits all,' a mindset inconsistent with the recent call for patient-centered care. We offer co-production as a patient-centered strategy for customizing discharge teaching and improving health outcomes for heart failure patients. INSETS: What is Co-Production?;Box A. Typical Case Scenario: Mrs. Jones;Box B. Ideal Case Scenario: Co-production. [ABSTRACT FROM AUTHOR]