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Background: Determining an accurate treatment goal weight (TGW) is critical for treating eating disorders requiring weight restoration. This is challenging in adolescents since body mass index (BMI) normally increases over time. Median BMI (mBMI) is often used to determine TGW, though use of historical growth trajectories is increasingly common. Using the appropriate method to set TGW may be particularly important in treating individuals with anorexia nervosa (AN) whose prior growth was substantially above or below the median, and in atypical anorexia (AAN) where prior growth is, by definition, above the median., Objectives: (1) Compare differences between TGWs based on mBMI and historical BMI percentile (hBMI) in patients with AN and AAN. (2) Determine whether either TGW method better predicted scores on the Eating Disorder Examination (EDE), heart rate, and menstrual status during treatment., Method: Retrospective chart review of 197 adolescents with AN or AAN completing a partial hospitalization program (PHP)., Results: For AN, the within-person variation between methods varied up to 11.3 kg, though the average TGW was similar if derived from the mBMI or hBMI. In AAN, the average hBMI TGW was higher than mBMI TGW, and within-person variation was up to 19.3 kg. Associations between hBMI TGW and mBMI with heart rate, menstrual status, and EDE scores varied., Discussion: Within-person differences in TGWs derived from hBMI versus mBMI can be large, with prominent differences in AAN, where hBMI TGW is significantly higher., (© 2024 The Author(s). International Journal of Eating Disorders published by Wiley Periodicals LLC.)

Increases in hydrological extremes, including drought, are expected for Amazon forests. A fundamental challenge for predicting forest responses lies in identifying ecological strategies which underlie such responses. Characterization of species-specific hydraulic strategies for regulating water-use, thought to be arrayed along an 'isohydric-anisohydric' spectrum, is a widely used approach. However, recent studies have questioned the usefulness of this classification scheme, because its metrics are strongly influenced by environments, and hence can lead to divergent classifications even within the same species. Here, we propose an alternative approach positing that individual hydraulic regulation strategies emerge from the interaction of environments with traits. Specifically, we hypothesize that the vertical forest profile represents a key gradient in drought-related environments (atmospheric vapor pressure deficit, soil water availability) that drives divergent tree water-use strategies for coordinated regulation of stomatal conductance (gs) and leaf water potentials (ΨL) with tree rooting depth, a proxy for water availability. Testing this hypothesis in a seasonal eastern Amazon forest in Brazil, we found that hydraulic strategies indeed depend on height-associated environments. Upper canopy trees, experiencing high vapor pressure deficit (VPD), but stable soil water access through deep rooting, exhibited isohydric strategies, defined by little seasonal change in the diurnal pattern of gs and steady seasonal minimum ΨL. In contrast, understory trees, exposed to less variable VPD but highly variable soil water availability, exhibited anisohydric strategies, with fluctuations in diurnal gs that increased in the dry season along with increasing variation in ΨL. Our finding that canopy height structures the coordination between drought-related environmental stressors and hydraulic traits provides a basis for preserving the applicability of the isohydric-to-anisohydric spectrum, which we show here may consistently emerge from environmental context. Our work highlights the importance of understanding how environmental heterogeneity structures forest responses to climate change, providing a mechanistic basis for improving models of tropical ecosystems., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)

Understanding the effects of intensification of Amazon basin hydrological cycling-manifest as increasingly frequent floods and droughts-on water and energy cycles of tropical forests is essential to meeting the challenge of predicting ecosystem responses to climate change, including forest "tipping points". Here, we investigated the impacts of hydrological extremes on forest function using 12+ years of observations (between 2001-2020) of water and energy fluxes from eddy covariance, along with associated ecological dynamics from biometry, at the Tapajós National Forest. Measurements encompass the strong 2015-2016 El Niño drought and La Niña 2008-2009 wet events. We found that the forest responded strongly to El Niño-Southern Oscillation (ENSO): Drought reduced water availability for evapotranspiration (ET) leading to large increases in sensible heat fluxes (H). Partitioning ET by an approach that assumes transpiration (T) is proportional to photosynthesis, we found that water stress-induced reductions in canopy conductance (G s ) drove T declines partly compensated by higher evaporation (E). By contrast, the abnormally wet La Niña period gave higher T and lower E, with little change in seasonal ET. Both El Niño-Southern Oscillation (ENSO) events resulted in changes in forest structure, manifested as lower wet-season leaf area index. However, only during El Niño 2015-2016, we observed a breakdown in the strong meteorological control of transpiration fluxes (via energy availability and atmospheric demand) because of slowing vegetation functions (via shutdown of G s and significant leaf shedding). Drought-reduced T and G s , higher H and E, amplified by feedbacks with higher temperatures and vapor pressure deficits, signaled that forest function had crossed a threshold, from which it recovered slowly, with delay, post-drought. Identifying such tipping point onsets (beyond which future irreversible processes may occur) at local scale is crucial for predicting basin-scale threshold-crossing changes in forest energy and water cycling, leading to slow-down in forest function, potentially resulting in Amazon forests shifting into alternate degraded states., (© 2023 John Wiley & Sons Ltd.)

Objective: Though virtual outpatient psychotherapy for eating disorders is likely effective, less is known about virtual higher levels of care. The current study examined the clinical outcomes of a family-based virtual intensive outpatient program (vIOP) for youth with eating disorders which was developed in response to the COVID-19 pandemic, compared to the same institution's in-person partial hospital program (PHP)., Methods: Treatment outcomes were assessed via chart review in 102 patients between the ages of 9-23 (M = 15.2, SD = 2.5) who were predominantly cisgender female (84.3%) and primarily diagnosed with anorexia nervosa (64.7%) or atypical anorexia (23.5%). Participants were either treated in the in-person PHP before the pandemic (n = 49) or the vIOP during the pandemic (n = 53). Percent expected body weight (%EBW) was examined at baseline, end of treatment, 3-months post-treatment, and 6-months post-treatment, as well as the frequency of medical, psychiatric, and residential admissions before, during, and after vIOP or PHP participation., Results: Linear mixed models demonstrated no effect of treatment modality (in-person versus virtual) on %EBW over time. The duration of the vIOP was, on average, 12 calendar days longer, though the amount billed for the vIOP was lower. Survival analyses and Cox regression models did not suggest differences in the frequency of hospital and residential treatment admissions during treatment (vIOP: 9.4%, PHP: 10.0%) or post-treatment (vIOP: 15.0%, PHP: 10.2%)., Discussion: Findings support virtual family-based programs as suitable alternatives to in-person treatment and underscore the potential cost-effectiveness of a family-based IOP versus PHP., Public Significance: This study demonstrates that a virtual, family-based, intensive outpatient program for youth with eating disorders had similar treatment outcomes to an in-person partial hospitalization program. Specifically, the virtual and in-person programs had similar weight restoration outcomes and rates of medical, psychiatric, or residential treatment admissions during or after treatment initiation. Findings support the use of virtual treatment, even for youth requiring a high level of intervention., (© 2022 The Authors. International Journal of Eating Disorders published by Wiley Periodicals LLC.)

Background and Objectives: Emerging data suggest the coronavirus disease 2019 (COVID-19) pandemic has been associated with worsening symptoms of eating disorders (EDs) among both adults and adolescents. With this study, we sought to determine if medical admission patterns among adolescents admitted to our institution for restrictive EDs changed during the pandemic, relative to prepandemic counts of admissions per month., Methods: We performed a chart review of patients aged 10 to 23 years admitted to our children's hospital for restrictive EDs from March 2017 through March 2021 and completed an interrupted time series analysis of admission counts per month. Demographic variables for admitted patients were compared by using χ 2 , Fisher's exact, and 2-sample t tests., Results: ED-related medical admissions at our institution increased significantly during the COVID-19 pandemic. The total number of admissions during the first 12 months of the COVID-19 pandemic (April 1, 2020, through March 31, 2021, n = 125) was more than double the mean number of admissions per year for the same time frame (April 1 through March 31) for the previous 3 years (mean = 56). Patient demographics were similar before and during the pandemic, with the exception that patients admitted during the COVID-19 pandemic were less likely than those admitted before the pandemic to have public insurance., Conclusions: Medical admissions related to restrictive EDs among adolescents increased significantly during the COVID-19 pandemic. Pediatric providers in a variety of settings should be prepared to care for adolescents with restrictive EDs during the pandemic., Competing Interests: POTENTIAL CONFLICT OF INTEREST: The authors have indicated they have no potential conflicts of interest to disclose., (Copyright © 2021 by the American Academy of Pediatrics.)

Objective: Improved treatment outcome in family-based treatment (FBT) for anorexia nervosa (AN) is predicted by weight gain occurring early in the course of treatment (i.e., about 4 lbs by week 4). Although prior work suggests that early weight gain in higher levels of care (e.g., partial hospitalization programs [PHP]) predicts weight restoration at discharge, no study has examined the specific rate of gain within FBT-informed PHP programs that best predicts treatment response., Method: This study examined rate of weight gain in pounds and percent expected body weight (EBW) that predicts positive outcome in 70 patients (M age = 15.49 years, SD = 2.56) with AN who were enrolled in a family-based PHP., Results: Receiver operator characteristic analyses demonstrated that changes in %EBW during weeks 2-5 were more useful than changes in weight in predicting positive outcome. Gaining at least 8.9 pounds or over 8% of EBW in the first 4 weeks of treatment significantly predicted positive outcome., Discussion: Findings suggest that positive outcome in an FBT-informed PHP is predicted by rapid weight gain in the initial weeks of treatment. Research is needed to identify specific family and patient characteristics that facilitate weight gain and to develop corresponding interventions to improve outcome., (© 2020 Wiley Periodicals, Inc.)

Plant phenology-the timing of cyclic or recurrent biological events in plants-offers insight into the ecology, evolution, and seasonality of plant-mediated ecosystem processes. Traditionally studied phenologies are readily apparent, such as flowering events, germination timing, and season-initiating budbreak. However, a broad range of phenologies that are fundamental to the ecology and evolution of plants, and to global biogeochemical cycles and climate change predictions, have been neglected because they are "cryptic"-that is, hidden from view (e.g., root production) or difficult to distinguish and interpret based on common measurements at typical scales of examination (e.g., leaf turnover in evergreen forests). We illustrate how capturing cryptic phenology can advance scientific understanding with two case studies: wood phenology in a deciduous forest of the northeastern USA and leaf phenology in tropical evergreen forests of Amazonia. Drawing on these case studies and other literature, we argue that conceptualizing and characterizing cryptic plant phenology is needed for understanding and accurate prediction at many scales from organisms to ecosystems. We recommend avenues of empirical and modeling research to accelerate discovery of cryptic phenological patterns, to understand their causes and consequences, and to represent these processes in terrestrial biosphere models., (© 2019 John Wiley & Sons Ltd.)

Understanding the pronounced seasonal and spatial variation in leaf carboxylation capacity (V c,max ) is critical for determining terrestrial carbon cycling in tropical forests. However, an efficient and scalable approach for predicting V c,max is still lacking. Here the ability of leaf spectroscopy for rapid estimation of V c,max was tested. V c,max was estimated using traditional gas exchange methods, and measured reflectance spectra and leaf age in leaves sampled from tropical forests in Panama and Brazil. These data were used to build a model to predict V c,max from leaf spectra. The results demonstrated that leaf spectroscopy accurately predicts V c,max of mature leaves in Panamanian tropical forests (R 2  = 0.90). However, this single-age model required recalibration when applied to broader leaf demographic classes (i.e. immature leaves). Combined use of spectroscopy models for V c,max and leaf age enabled construction of the V c,max -age relationship solely from leaf spectra, which agreed with field observations. This suggests that the spectroscopy technique can capture the seasonal variability in V c,max , assuming sufficient sampling across diverse species, leaf ages and canopy environments. This finding will aid development of remote sensing approaches that can be used to characterize V c,max in moist tropical forests and enable an efficient means to parameterize and evaluate terrestrial biosphere models., (© 2019 The Authors. New Phytologist © 2019 New Phytologist Trust.)

Satellite and tower-based metrics of forest-scale photosynthesis generally increase with dry season progression across central Amazônia, but the underlying mechanisms lack consensus. We conducted demographic surveys of leaf age composition, and measured the age dependence of leaf physiology in broadleaf canopy trees of abundant species at a central eastern Amazon site. Using a novel leaf-to-branch scaling approach, we used these data to independently test the much-debated hypothesis - arising from satellite and tower-based observations - that leaf phenology could explain the forest-scale pattern of dry season photosynthesis. Stomatal conductance and biochemical parameters of photosynthesis were higher for recently mature leaves than for old leaves. Most branches had multiple leaf age categories simultaneously present, and the number of recently mature leaves increased as the dry season progressed because old leaves were exchanged for new leaves. These findings provide the first direct field evidence that branch-scale photosynthetic capacity increases during the dry season, with a magnitude consistent with increases in ecosystem-scale photosynthetic capacity derived from flux towers. Interactions between leaf age-dependent physiology and shifting leaf age-demographic composition are sufficient to explain the dry season photosynthetic capacity pattern at this site, and should be considered in vegetation models of tropical evergreen forests., (© 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.)

Leaf age structures the phenology and development of plants, as well as the evolution of leaf traits over life histories. However, a general method for efficiently estimating leaf age across forests and canopy environments is lacking. Here, we explored the potential for a statistical model, previously developed for Peruvian sunlit leaves, to consistently predict leaf ages from leaf reflectance spectra across two contrasting forests in Peru and Brazil and across diverse canopy environments. The model performed well for independent Brazilian sunlit and shade canopy leaves (R 2  = 0.75-0.78), suggesting that canopy leaves (and their associated spectra) follow constrained developmental trajectories even in contrasting forests. The model did not perform as well for mid-canopy and understory leaves (R 2  = 0.27-0.29), because leaves in different environments have distinct traits and trait developmental trajectories. When we accounted for distinct environment-trait linkages - either by explicitly including traits and environments in the model, or, even better, by re-parameterizing the spectra-only model to implicitly capture distinct trait-trajectories in different environments - we achieved a more general model that well-predicted leaf age across forests and environments (R 2  = 0.79). Fundamental rules, linked to leaf environments, constrain the development of leaf traits and allow for general prediction of leaf age from spectra across species, sites and canopy environments., (© 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.)

In evergreen tropical forests, the extent, magnitude, and controls on photosynthetic seasonality are poorly resolved and inadequately represented in Earth system models. Combining camera observations with ecosystem carbon dioxide fluxes at forests across rainfall gradients in Amazônia, we show that aggregate canopy phenology, not seasonality of climate drivers, is the primary cause of photosynthetic seasonality in these forests. Specifically, synchronization of new leaf growth with dry season litterfall shifts canopy composition toward younger, more light-use efficient leaves, explaining large seasonal increases (~27%) in ecosystem photosynthesis. Coordinated leaf development and demography thus reconcile seemingly disparate observations at different scales and indicate that accounting for leaf-level phenology is critical for accurately simulating ecosystem-scale responses to climate change., (Copyright © 2016, American Association for the Advancement of Science.)