Search

Aim: Ecological and anthropogenic factors shift the abundances of dominant and rare tree species within local forest communities, thus affecting species composition and ecosystem functioning. To inform forest and conservation management it is important to understand the drivers of dominance and rarity in local tree communities. We answer the following research questions: (1) What are the patterns of dominance and rarity in tree communities? (2) Which ecological and anthropogenic factors predict these patterns? And (3) what is the extinction risk of locally dominant and rare tree species?. Location: Global. Time period: 1990–2017. Major taxa studied: Trees. Methods: We used 1.2 million forest plots and quantified local tree dominance as the relative plot basal area of the single most dominant species and local rarity as the percentage of species that contribute together to the least 10% of plot basal area. We mapped global community dominance and rarity using machine learning models and evaluated the ecological and anthropogenic predictors with linear models. Extinction risk, for example threatened status, of geographically widespread dominant and rare species was evaluated. Results: Community dominance and rarity show contrasting latitudinal trends, with boreal forests having high levels of dominance and tropical forests having high levels of rarity. Increasing annual precipitation reduces community dominance, probably because precipitation is related to an increase in tree density and richness. Additionally, stand age is positively related to community dominance, due to stem diameter increase of the most dominant species. Surprisingly, we find that locally dominant and rare species, which are geographically widespread in our data, have an equally high rate of elevated extinction due to declining populations through large-scale land degradation. Main conclusions: By linking patterns and predictors of community dominance and rarity to extinction risk, our results suggest that also widespread species should be considered in large-scale management and conservation practices.

Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system1. Remote-sensing estimates to quantify carbon losses from global forests2-5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced6 and satellite-derived approaches2,7,8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151-363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea2,3,9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets.

Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17-34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling.

Abstract: The tropical forest carbon sink is known to be drought sensitive, but it is unclear which forests are the most vulnerable to extreme events. Forests with hotter and drier baseline conditions may be protected by prior adaptation, or more vulnerable because they operate closer to physiological limits. Here we report that forests in drier South American climates experienced the greatest impacts of the 2015–2016 El Niño, indicating greater vulnerability to extreme temperatures and drought. The long-term, ground-measured tree-by-tree responses of 123 forest plots across tropical South America show that the biomass carbon sink ceased during the event with carbon balance becoming indistinguishable from zero (−0.02 ± 0.37 Mg C ha−1 per year). However, intact tropical South American forests overall were no more sensitive to the extreme 2015–2016 El Niño than to previous less intense events, remaining a key defence against climate change as long as they are protected.

Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species1,2. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies3,4. Here, leveraging global tree databases5-7, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions.

1. Biodiversity is an important component of natural ecosystems, with higher species richness often correlating with an increase in ecosystem productivity. Yet, this relationship varies substantially across environments, typically becoming less pronounced at high levels of species richness. However, species richness alone cannot reflect all important properties of a community, including community evenness, which may mediate the relationship between biodiversity and productivity. If the evenness of a community correlates negatively with richness across forests globally, then a greater number of species may not always increase overall diversity and productivity of the system. Theoretical work and local empirical studies have shown that the effect of evenness on ecosystem functioning may be especially strong at high richness levels, yet the consistency of this remains untested at a global scale. 2. Here, we used a dataset of forests from across the globe, which includes composition, biomass accumulation and net primary productivity, to explore whether productivity correlates with community evenness and richness in a way that evenness appears to buffer the effect of richness. Specifically, we evaluated whether low levels of evenness in speciose communities correlate with the attenuation of the richness–productivity relationship. 3. We found that tree species richness and evenness are negatively correlated across forests globally, with highly speciose forests typically comprising a few dominant and many rare species. Furthermore, we found that the correlation between diversity and productivity changes with evenness: at low richness, uneven communities are more productive, while at high richness, even communities are more productive. 4. Synthesis. Collectively, these results demonstrate that evenness is an integral component of the relationship between biodiversity and productivity, and that the attenuating effect of richness on forest productivity might be partly explained by low evenness in speciose communities. Productivity generally increases with species richness, until reduced evenness limits the overall increases in community diversity. Our research suggests that evenness is a fundamental component of biodiversity–ecosystem function relationships, and is of critical importance for guiding conservation and sustainable ecosystem management decisions.

IntroductionAvailable evidence is mixed concerning associations between smoking status and COVID-19 clinical outcomes. Effects of nicotine replacement therapy (NRT) and vaccination status on COVID-19 outcomes in smokers are unknown.MethodsElectronic health record data from 104 590 COVID-19 patients hospitalized February 1, 2020 to September 30, 2021 in 21 U.S. health systems were analyzed to assess associations of smoking status, in-hospital NRT prescription, and vaccination status with in-hospital death and ICU admission.ResultsCurrent (n = 7764) and never smokers (n = 57 454) did not differ on outcomes after adjustment for age, sex, race, ethnicity, insurance, body mass index, and comorbidities. Former (vs never) smokers (n = 33 101) had higher adjusted odds of death (aOR, 1.11; 95% CI, 1.06-1.17) and ICU admission (aOR, 1.07; 95% CI, 1.04-1.11). Among current smokers, NRT prescription was associated with reduced mortality (aOR, 0.64; 95% CI, 0.50-0.82). Vaccination effects were significantly moderated by smoking status; vaccination was more strongly associated with reduced mortality among current (aOR, 0.29; 95% CI, 0.16-0.66) and former smokers (aOR, 0.47; 95% CI, 0.39-0.57) than for never smokers (aOR, 0.67; 95% CI, 0.57, 0.79). Vaccination was associated with reduced ICU admission more strongly among former (aOR, 0.74; 95% CI, 0.66-0.83) than never smokers (aOR, 0.87; 95% CI, 0.79-0.97).ConclusionsFormer but not current smokers hospitalized with COVID-19 are at higher risk for severe outcomes. SARS-CoV-2 vaccination is associated with better hospital outcomes in COVID-19 patients, especially current and former smokers. NRT during COVID-19 hospitalization may reduce mortality for current smokers.ImplicationsPrior findings regarding associations between smoking and severe COVID-19 disease outcomes have been inconsistent. This large cohort study suggests potential beneficial effects of nicotine replacement therapy on COVID-19 outcomes in current smokers and outsized benefits of SARS-CoV-2 vaccination in current and former smokers. Such findings may influence clinical practice and prevention efforts and motivate additional research that explores mechanisms for these effects.

IntroductionIt is uncertain whether e-cigarettes facilitate smoking cessation in the real world. We aimed to understand whether and how transitions among cigarette, e-cigarette, and dual use are associated with sociodemographics, dependence measures, and biomarkers.Aims and methodsWe followed 380 adult daily cigarette users and dual users every 2 months for up to 2 years. We estimated transition rates between noncurrent, cigarette-only, e-cigarette-only, and dual use states using a multistate transition model. We estimated univariable hazard ratios (HR) for demographics, dependence measures for cigarettes and e-cigarettes, biomarkers, spousal or partner behaviors, and other measures.ResultsWe estimated that participants transitioned from cigarette-only to e-cigarette-only through a period of dual use. Dual users ceased smoking (transitioning to e-cigarette-only use) at a greater rate than cigarette-only users did (HR 2.44, 95% CI: 1.49, 4.02). However, of the 60% of dual users estimated to transition to single product use in 1 year, 83% would transition to cigarette-only use and only 17% to e-cigarette-only use. E-cigarette dependence measures were generally associated with reduced e-cigarette cessation rather than enhanced cigarette cessation. E-cigarette users motivated by harm or toxicity reduction or because of restrictions on where or when they could smoke had reduced rates of smoking relapse. Cigarette dependence and spousal smoking were barriers to cigarette cessation for dual users, while using e-cigarettes first in the morning, motivation to quit smoking, and sensory, social, and emotional enjoyment of e-cigarettes (secondary dependence motives) were facilitators of smoking cessation among dual users.ConclusionsTobacco control policy and interventions may be informed by the barriers and facilitators of product transitions.ImplicationsAlthough e-cigarettes have the potential to promote smoking cessation, their real-world impact is uncertain. In this cohort, dual users were more likely to quit smoking than cigarette-only users, but the overall impact was small because most dual users returned to cigarette-only use. Moreover, e-cigarette dependence promoted continued dual use rather than smoking cessation. Yet, high motivation to quit smoking and the sensory, social, and emotional enjoyment of e-cigarettes facilitated smoking cessation in dual users. Better understanding the barriers and facilitators of transitions can help to develop regulations and interventions that lead to more effective use of e-cigarettes for smoking cessation.

BackgroundThere is mixed evidence about the relations of current versus past cancer with severe COVID-19 outcomes and how they vary by patient and cancer characteristics.MethodsElectronic health record data of 104,590 adult hospitalized patients with COVID-19 were obtained from 21 United States health systems from February 2020 through September 2021. In-hospital mortality and ICU admission were predicted from current and past cancer diagnoses. Moderation by patient characteristics, vaccination status, cancer type, and year of the pandemic was examined.Results6.8% of the patients had current (n = 7,141) and 6.5% had past (n = 6,749) cancer diagnoses. Current cancer predicted both severe outcomes but past cancer did not; adjusted odds ratios (aOR) for mortality were 1.58 [95% confidence interval (CI), 1.46-1.70] and 1.04 (95% CI, 0.96-1.13), respectively. Mortality rates decreased over the pandemic but the incremental risk of current cancer persisted, with the increment being larger among younger vs. older patients. Prior COVID-19 vaccination reduced mortality generally and among those with current cancer (aOR, 0.69; 95% CI, 0.53-0.90).ConclusionsCurrent cancer, especially among younger patients, posed a substantially increased risk for death and ICU admission among patients with COVID-19; prior COVID-19 vaccination mitigated the risk associated with current cancer. Past history of cancer was not associated with higher risks for severe COVID-19 outcomes for most cancer types.ImpactThis study clarifies the characteristics that modify the risk associated with cancer on severe COVID-19 outcomes across the first 20 months of the COVID-19 pandemic. See related commentary by Egan et al., p. 3.

BackgroundThe Cancer Center Cessation Initiative (C3I) is a National Cancer Institute (NCI) Cancer Moonshot Program that supports NCI-designated cancer centers developing tobacco treatment programs for oncology patients who smoke. C3I-funded centers implement evidence-based programs that offer various smoking cessation treatment components (e.g., counseling, Quitline referrals, access to medications). While evaluation of implementation outcomes in C3I is guided by evaluation of reach and effectiveness (via RE-AIM), little is known about technical efficiency-i.e., how inputs (e.g., program costs, staff time) influence implementation outcomes (e.g., reach, effectiveness). This study demonstrates the application of data envelopment analysis (DEA) as an implementation science tool to evaluate technical efficiency of C3I programs and advance prioritization of implementation resources.MethodsDEA is a linear programming technique widely used in economics and engineering for assessing relative performance of production units. Using data from 16 C3I-funded centers reported in 2020, we applied input-oriented DEA to model technical efficiency (i.e., proportion of observed outcomes to benchmarked outcomes for given input levels). The primary models used the constant returns-to-scale specification and featured cost-per-participant, total full-time equivalent (FTE) effort, and tobacco treatment specialist effort as model inputs and reach and effectiveness (quit rates) as outcomes.ResultsIn the DEA model featuring cost-per-participant (input) and reach/effectiveness (outcomes), average constant returns-to-scale technical efficiency was 25.66 (SD = 24.56). When stratified by program characteristics, technical efficiency was higher among programs in cohort 1 (M = 29.15, SD = 28.65, n = 11) vs. cohort 2 (M = 17.99, SD = 10.16, n = 5), with point-of-care (M = 33.90, SD = 28.63, n = 9) vs. no point-of-care services (M = 15.59, SD = 14.31, n = 7), larger (M = 33.63, SD = 30.38, n = 8) vs. smaller center size (M = 17.70, SD = 15.00, n = 8), and higher (M = 29.65, SD = 30.99, n = 8) vs. lower smoking prevalence (M = 21.67, SD = 17.21, n = 8).ConclusionMost C3I programs assessed were technically inefficient relative to the most efficient center benchmark and may be improved by optimizing the use of inputs (e.g., cost-per-participant) relative to program outcomes (e.g., reach, effectiveness). This study demonstrates the appropriateness and feasibility of using DEA to evaluate the relative performance of evidence-based programs.

BackgroundeHealth interventions appear and change so quickly that they challenge the way we conduct research. By the time a randomized trial of a new intervention is published, technological improvements and clinical discoveries may make the intervention dated and unappealing. This and the spate of health-related apps and websites may lead consumers, patients, and caregivers to use interventions that lack evidence of efficacy. ObjectiveThis paper aims to offer strategies for increasing the speed and usefulness of eHealth research. MethodsThe paper describes two types of strategies based on the authors’ own research and the research literature: those that improve the efficiency of eHealth research, and those that improve its quality. ResultsEfficiency strategies include: (1) think small: conduct small studies that can target discrete but significant questions and thereby speed knowledge acquisition; (2) use efficient designs: use such methods as fractional-factorial and quasi-experimental designs and surrogate endpoints, and experimentally modify and evaluate interventions and delivery systems already in use; (3) study universals: focus on timeless behavioral, psychological, and cognitive principles and systems; (4) anticipate the next big thing: listen to voices outside normal practice and connect different perspectives for new insights; (5) improve information delivery systems: researchers should apply their communications expertise to enhance inter-researcher communication, which could synergistically accelerate progress and capitalize upon the availability of “big data”; and (6) develop models, including mediators and moderators: valid models are remarkably generative, and tests of moderation and mediation should elucidate boundary conditions of effects and treatment mechanisms. Quality strategies include: (1) continuous quality improvement: researchers need to borrow engineering practices such as the continuous enhancement of interventions to incorporate clinical and technological progress; (2) help consumers identify quality: consumers, clinicians, and others all need to easily identify quality, suggesting the need to efficiently and publicly index intervention quality; (3) reduce the costs of care: concern with health care costs can drive intervention adoption and use and lead to novel intervention effects (eg, reduced falls in the elderly); and (4) deeply understand users: a rigorous evaluation of the consumer’s needs is a key starting point for intervention development. ConclusionsThe challenges of distinguishing and distributing scientifically validated interventions are formidable. The strategies described are meant to spur discussion and further thinking, which are important, given the potential of eHealth interventions to help patients and families.

NASA's Global Ecosystem Dynamics Investigation (GEDI) is collecting spaceborne full waveform lidar data with a primary science goal of producing accurate estimates of forest aboveground biomass density (AGBD). This paper presents the development of the models used to create GEDI's footprint-level (~25 m) AGBD (GEDI04_A) product, including a description of the datasets used and the procedure for final model selection. The data used to fit our models are from a compilation of globally distributed spatially and temporally coincident field and airborne lidar datasets, whereby we simulated GEDI-like waveforms from airborne lidar to build a calibration database. We used this database to expand the geographic extent of past waveform lidar studies, and divided the globe into four broad strata by Plant Functional Type (PFT) and six geographic regions. GEDI's waveform-to-biomass models take the form of parametric Ordinary Least Squares (OLS) models with simulated Relative Height (RH) metrics as predictor variables. From an exhaustive set of candidate models, we selected the best input predictor variables, and data transformations for each geographic stratum in the GEDI domain to produce a set of comprehensive predictive footprint-level models. We found that model selection frequently favored combinations of RH metrics at the 98th, 90th, 50th, and 10th height above ground-level percentiles (RH98, RH90, RH50, and RH10, respectively), but that inclusion of lower RH metrics (e.g. RH10) did not markedly improve model performance. Second, forced inclusion of RH98 in all models was important and did not degrade model performance, and the best performing models were parsimonious, typically having only 1-3 predictors. Third, stratification by geographic domain (PFT, geographic region) improved model performance in comparison to global models without stratification. Fourth, for the vast majority of strata, the best performing models were fit using square root transformation of field AGBD and/or height metrics. There was considerable variability in model performance across geographic strata, and areas with sparse training data and/or high AGBD values had the poorest performance. These models are used to produce global predictions of AGBD, but will be improved in the future as more and better training data become available.

Objective: The aim of this study was to examine dependence on combustible and e-cigarettes among users of both products (dual users), which may provide important insights into long-term use patterns. Method: Dual users (smoking daily for 3 months, using e-cigarettes at least once/week for the past month; N = 256; 45% women, 71% White, M age 39.0 years) not interested in quitting either product participated in a longitudinal, 2-year, observational study. At baseline, participants completed measures of combustible and e-cigarette dependence (Fagerström Test of Cigarette Dependence [FTCD], e-FTCD, Wisconsin Inventory of Smoking Dependence Motives [WISDM], e-WISDM, Penn State Cigarette Dependence Index, and Penn State E-Cigarette Dependence Index) and carried a study smartphone for 2 weeks to record cigarette and e-cigarette use events. Results: Most measures of dependence were product specific (e.g., FTCD and e-FTCD were not correlated, r = -0.003) and predicted product-specific outcomes (e.g., long-term use of that product). However, individuals used the two products for some of the same secondary dependence motives (e.g., weight control, cognitive and affective enhancement). These secondary, or instrumental, motives predicted use of both products at 1 year. Which product was used first in the morning was strongly related to product dependence scores and likelihood of continued product use at 1 year. Conclusions: Among dual users of combustible and e-cigarettes, measures of e-cigarette and cigarette dependence tended to be unrelated to one another, but dual users tended to use both products for the same instrumental motives. Which product is used first in the morning may serve as a valuable measure of relative dependence on the two products. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Main objectiveThere is limited information on how patient outcomes have changed during the COVID-19 pandemic. This study characterizes changes in mortality, intubation, and ICU admission rates during the first 20 months of the pandemic.Study design and methodsUniversity of Wisconsin researchers collected and harmonized electronic health record data from 1.1 million COVID-19 patients across 21 United States health systems from February 2020 through September 2021. The analysis comprised data from 104,590 adult hospitalized COVID-19 patients. Inclusion criteria for the analysis were: (1) age 18 years or older; (2) COVID-19 ICD-10 diagnosis during hospitalization and/or a positive COVID-19 PCR test in a 14-day window (+/- 7 days of hospital admission); and (3) health system contact prior to COVID-19 hospitalization. Outcomes assessed were: (1) mortality (primary), (2) endotracheal intubation, and (3) ICU admission.Results and significanceThe 104,590 hospitalized participants had a mean age of 61.7 years and were 50.4% female, 24% Black, and 56.8% White. Overall risk-standardized mortality (adjusted for age, sex, race, ethnicity, body mass index, insurance status and medical comorbidities) declined from 16% of hospitalized COVID-19 patients (95% CI: 16% to 17%) early in the pandemic (February-April 2020) to 9% (CI: 9% to 10%) later (July-September 2021). Among subpopulations, males (vs. females), those on Medicare (vs. those on commercial insurance), the severely obese (vs. normal weight), and those aged 60 and older (vs. younger individuals) had especially high mortality rates both early and late in the pandemic. ICU admission and intubation rates also declined across these 20 months.ConclusionsMortality, intubation, and ICU admission rates improved markedly over the first 20 months of the pandemic among adult hospitalized COVID-19 patients although gains varied by subpopulation. These data provide important information on the course of COVID-19 and identify hospitalized patient groups at heightened risk for negative outcomes.Trial registrationClinicalTrials.gov Identifier: NCT04506528 (https://clinicaltrials.gov/ct2/show/NCT04506528).

Aim: Tree crowns determine light interception, carbon and water exchange. Thus, understanding the factors causing tree crown allometry to vary at the tree and stand level matters greatly for the development of future vegetation modelling and for the calibration of remote sensing products. Nevertheless, we know little about large-scale variation and determinants in tropical tree crown allometry. In this study, we explored the continental variation in scaling exponents of site-specific crown allometry and assessed their relationships with environmental and stand-level variables in the tropics. Location: Global tropics. Time period: Early 21st century. Major taxa studied: Woody plants. Methods: Using a dataset of 87,737 trees distributed among 245 forest and savanna sites across the tropics, we fitted site-specific allometric relationships between crown dimensions (crown depth, diameter and volume) and stem diameter using power-law models. Stand-level and environmental drivers of crown allometric relationships were assessed at pantropical and continental scales. Results: The scaling exponents of allometric relationships between stem diameter and crown dimensions were higher in savannas than in forests. We identified that continental crown models were better than pantropical crown models and that continental differences in crown allometric relationships were driven by both stand-level (wood density) and environmental (precipitation, cation exchange capacity and soil texture) variables for both tropical biomes. For a given diameter, forest trees from Asia and savanna trees from Australia had smaller crown dimensions than trees in Africa and America, with crown volumes for some Asian forest trees being smaller than those of trees in African forests. Main conclusions: Our results provide new insight into geographical variability, with large continental differences in tropical tree crown allometry that were driven by stand-level and environmental variables. They have implications for the assessment of ecosystem function and for the monitoring of woody biomass by remote sensing techniques in the global tropics.

Aim: Palms are an iconic, diverse and often abundant component of tropical ecosystems that provide many ecosystem services. Being monocots, tree palms are evolutionarily, morphologically and physiologically distinct from other trees, and these differences have important consequences for ecosystem services (e.g., carbon sequestration and storage) and in terms of responses to climate change. We quantified global patterns of tree palm relative abundance to help improve understanding of tropical forests and reduce uncertainty about these ecosystems under climate change. Location: Tropical and subtropical moist forests. Time period: Current. Major taxa studied: Palms (Arecaceae). Methods: We assembled a pantropical dataset of 2,548 forest plots (covering 1,191 ha) and quantified tree palm (i.e., ≥10 cm diameter at breast height) abundance relative to co-occurring non-palm trees. We compared the relative abundance of tree palms across biogeographical realms and tested for associations with palaeoclimate stability, current climate, edaphic conditions and metrics of forest structure. Results: On average, the relative abundance of tree palms was more than five times larger between Neotropical locations and other biogeographical realms. Tree palms were absent in most locations outside the Neotropics but present in >80% of Neotropical locations. The relative abundance of tree palms was more strongly associated with local conditions (e.g., higher mean annual precipitation, lower soil fertility, shallower water table and lower plot mean wood density) than metrics of long-term climate stability. Life-form diversity also influenced the patterns; palm assemblages outside the Neotropics comprise many non-tree (e.g., climbing) palms. Finally, we show that tree palms can influence estimates of above-ground biomass, but the magnitude and direction of the effect require additional work. Conclusions: Tree palms are not only quintessentially tropical, but they are also overwhelmingly Neotropical. Future work to understand the contributions of tree palms to biomass estimates and carbon cycling will be particularly crucial in Neotropical forests.

BackgroundElectronic cigarettes (e-cigarettes) have drastically changed the nicotine and tobacco product landscape. However, their potential public health impact is still unclear. A reliable and valid measure of e-cigarette dependence would likely advance assessment and prognostication of the public health impact of e-cigarettes. The aim of this research was to examine the internal consistency, structure, and validity of three e-cigarette dependence scales.MethodsAdult dual users (smokers who also vape, N = 256) enrolled in an observational cohort study (45.1% women, 70.7% white). At baseline, participants completed the e-cigarette Fagerström Test of Cigarette Dependence (e-FTCD), the e-cigarette Wisconsin Inventory of Smoking Dependence Motives (e-WISDM), and the Penn State Electronic Cigarette Dependence Index (PS-ECDI). All participants provided a urine sample for cotinine analysis and reported e-cigarette use at 1 year.ResultsThe e-WISDM subscales had the highest internal consistency (α = .81-.96), then the PS-ECDI (α = .74) and e-FTCD (α = .51). A single-factor structure for the e-FTCD and an 11-factor structure for the e-WISDM were supported, but the PS-ECDI did not have a single-factor structure. All three e-cigarette dependence scales were highly correlated with validation criteria including continued e-cigarette use at 1 year, but not with e-liquid nicotine concentration or cotinine.ConclusionsThe e-WISDM and PS-ECDI had stronger internal consistency than did the e-FTCD, despite the e-FTCD's single-factor structure, but all 3 measures appear to be valid measures of e-cigarette dependence as suggested by their significant relations with self-perceived addiction, heavy use, early use after overnight deprivation, and continued use over time.ImplicationsThis research provides empirical support for three e-cigarette dependence measures: the e-FTCD, the PS-ECDI, and the e-WISDM among dual users of e-cigarettes and combustible cigarettes. The PS-ECDI and e-WISDM are more reliable, but all three measures were strongly correlated with key dependence constructs such as heavy use and continued use over time.

BackgroundDual use of combustible and electronic cigarettes (e-cigarettes) is a growing use pattern; more than half of e-cigarette users are dual users. However, little is known regarding the course of dual use; for example, the likelihood of discontinuation of either combustible or e-cigarettes or both.MethodsAdult daily smokers and dual users (daily smokers who also vaped at least once per week) who did not intend to quit use of either product in the next 30 days participated in a longitudinal, observational study (N = 322, 51.2% women, 62.7% white, mean age = 42.27 [SD = 14.05]). At baseline, participants completed demographics and smoking and vaping history assessments. They also reported daily cigarette and e-cigarette use via timeline follow-back assessment and provided a breath sample for carbon monoxide assay at 4-month intervals for 1 year.ResultsOf those who completed the year 1 follow-up, 1.9% baseline smokers and 8.0% dual users achieved biochemically confirmed seven-day point-prevalence abstinence from combustible cigarettes (χ2 = 4.57, p = .03). Of initial dual users, by 1 year 43.9% were smoking only, 48.8% continued dual use, 5.9% were vaping only, and 1.4% abstained from both products. Among baseline smokers, 92.3% continued as exclusive smokers. Baseline dual users who continued e-cigarette use were more likely to be white and report higher baseline e-cigarette dependence.ConclusionsIn this community sample, the majority of dual users transitioned to exclusive smoking. A higher percentage of dual users quit smoking than smokers, but attrition and baseline differences between the groups compromise strong conclusions. Sustained e-cigarette use was related to baseline e-cigarette dependence.ImplicationsThis research suggests that dual use of combustible and e-cigarettes is not a sustained pattern for the majority of dual users, but it is more likely to be a continued pattern if the user is more dependent on e-cigarettes. There was evidence that dual users were more likely to quit smoking than exclusive smokers, but this may be due to factors other than their dual use.

Many proteins exist naturally as symmetrical homooligomers or homopolymers1. The emergent structural and functional properties of such protein assemblies have inspired extensive efforts in biomolecular design2-5. As synthesized by ribosomes, proteins are inherently asymmetric. Thus, they must acquire multiple surface patches that selectively associate to generate the different symmetry elements needed to form higher-order architectures1,6-a daunting task for protein design. Here we address this problem using an inorganic chemical approach, whereby multiple modes of protein-protein interactions and symmetry are simultaneously achieved by selective, 'one-pot' coordination of soft and hard metal ions. We show that a monomeric protein (protomer) appropriately modified with biologically inspired hydroxamate groups and zinc-binding motifs assembles through concurrent Fe3+ and Zn2+ coordination into discrete dodecameric and hexameric cages. Our cages closely resemble natural polyhedral protein architectures7,8 and are, to our knowledge, unique among designed systems9-13 in that they possess tightly packed shells devoid of large apertures. At the same time, they can assemble and disassemble in response to diverse stimuli, owing to their heterobimetallic construction on minimal interprotein-bonding footprints. With stoichiometries ranging from [2 Fe:9 Zn:6 protomers] to [8 Fe:21 Zn:12 protomers], these protein cages represent some of the compositionally most complex protein assemblies-or inorganic coordination complexes-obtained by design.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

IntroductionThe availability of electronic cigarettes (e-cigarettes) has profoundly changed the tobacco product landscape. In the United States, almost 6 million adults use both combustible and e-cigarettes (ie, dual users). The goal of this study was to understand how smokers and dual users differ in terms of demographics, cigarette dependence, and exposure to carcinogens.MethodsAn observational cohort (smokers, n = 166, ≥5 cigarettes/day for 6 months and no e-cigarette use in 3 months; dual users, n = 256, smoked daily for 3 months and used e-cigarettes at least once/week for the past 3 months) completed baseline assessments of demographics, tobacco use, and dependence. They also provided breath samples for carbon monoxide (CO) assay and urine samples for cotinine, 3-hydroxycotinine, and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL) assays.ResultsCompared to smokers, dual users (mean e-cigarette use = 5.5 days/week [SD = 1.9]) were significantly younger and more likely to be white, have more education, report a history of psychiatric co-morbidity, and smoke fewer cigarettes per day. There were no differences in CO, cotinine, or 3-hydroxycotinine levels; however, dual users had significantly lower levels of NNAL than did smokers. Most smokers and dual users had no plans to quit smoking within the next year; 91% of dual users planned to continue using e-cigarettes for at least the next year.ConclusionsIn this community sample, dual users are supplementing their smoking with e-cigarette use. Dual users, versus smokers, smoked fewer cigarettes per day and delayed their first cigarette of the day, but did not differ in quitting intentions.ImplicationsThis comparison of a community sample of established dual users and exclusive smokers addresses key questions of dependence and health risks of dual use in real-world settings. Dual users were more likely to be white, younger, have more than a high school education and have a psychiatric history. Dual users also smoked significantly fewer cigarettes and had lower levels of NNAL (a carcinogen), but they did not differ from exclusive smokers in CO or cotinine levels, suggesting that they supplemented their nicotine intake via e-cigarettes.

Group II introns are a class of retroelements that invade DNA through a copy-and-paste mechanism known as retrotransposition. Their coordinated activities occur within a complex that includes a maturase protein, which promotes splicing through an unknown mechanism. The mechanism of splice site exchange within the RNA active site during catalysis also remains unclear. We determined two cryo-EM structures at 3.6-Å resolution of a group II intron reverse splicing into DNA. These structures reveal that the branch-site domain VI helix swings 90°, enabling substrate exchange during DNA integration. The maturase assists catalysis through a transient RNA-protein contact with domain VI that positions the branch-site adenosine for lariat formation during forward splicing. These findings provide the first direct evidence of the role the maturase plays during group II intron catalysis. The domain VI dynamics closely parallel spliceosomal branch-site helix movement and provide strong evidence for a retroelement origin of the spliceosome.

Enterovirus D68 (EV-D68) undergoes structural transformation between mature, cell-entry intermediate (A-particle) and empty forms throughout its life cycle. Structural information for the various forms and antibody-bound capsids will facilitate the development of effective vaccines and therapeutics against EV-D68 infection, which causes childhood respiratory and paralytic diseases worldwide. Here, we report the structures of three EV-D68 capsid states representing the virus at major phases. We further describe two original monoclonal antibodies (15C5 and 11G1) with distinct structurally defined mechanisms for virus neutralization. 15C5 and 11G1 engage the capsid loci at icosahedral three-fold and five-fold axes, respectively. To block viral attachment, 15C5 binds three forms of capsids, and triggers mature virions to transform into A-particles, mimicking engagement by the functional receptor ICAM-5, whereas 11G1 exclusively recognizes the A-particle. Our data provide a structural and molecular explanation for the transition of picornavirus capsid conformations and demonstrate distinct mechanisms for antibody-mediated neutralization.

The co-self-assembly of proteins and nucleic acids (NAs) produces complex biomolecular machines (e.g., ribosomes and telomerases) that represent some of the most daunting targets for biomolecular design. Despite significant advances in protein and DNA or RNA nanotechnology, the construction of artificial nucleoprotein complexes has largely been limited to cases that rely on the NA-mediated spatial organization of protein units, rather than a cooperative interplay between protein- and NA-mediated interactions that typify natural nucleoprotein assemblies. We report here a structurally well-defined synthetic nucleoprotein assembly that forms through the synergy of three types of intermolecular interactions: Watson-Crick base pairing, NA-protein interactions, and protein-metal coordination. The fine thermodynamic balance between these interactions enables the formation of a crystalline architecture under highly specific conditions.

Coxsackievirus A10 (CVA10) recently emerged as a major pathogen of hand, foot, and mouth disease and herpangina in children worldwide, and lack of a vaccine or a cure against CVA10 infections has made therapeutic antibody identification a public health priority. By targeting a local isolate, CVA10-FJ-01, we obtained a potent antibody, 2G8, against all three capsid forms of CVA10. We show that 2G8 exhibited both 100% preventive and 100% therapeutic efficacy against CVA10 infection in mice. Comparisons of the near-atomic cryo-electron microscopy structures of the three forms of CVA10 capsid and their complexes with 2G8 Fab reveal that a single Fab binds a border region across the three capsid proteins (VP1 to VP3) and explain 2G8's remarkable cross-reactivities against all three capsid forms. The atomic structures of this first neutralizing antibody of CVA10 should inform strategies for designing vaccines and therapeutics against CVA10 infections.

Single-particle cryogenic electron microscopy (cryo-EM) provides a powerful methodology for structural biologists, but the resolutions typically attained with experimentally determined structures have lagged behind microscope capabilities. Here, we exploit several technical advances to improve resolution, including per-particle contrast transfer function (CTF) refinement and correction for Ewald sphere curvature. The latter is demonstrated with several experimental samples and should become more standard as resolutions increase or at lower microscope accelerating voltages. The combined application of the described methods to micrographs recorded on a Titan Krios enables structure determination at ~1.86-Å resolution of an adeno-associated virus serotype 2 variant (AAV2), an important gene-delivery vehicle. The resulting structural details provide an improved model for understanding the biology of AAV that will guide future vector development for gene therapy.

Genome ejection proteins are required to facilitate transport of bacteriophage P22 double-stranded DNA safely through membranes of Salmonella. The structures and locations of all proteins in the context of the mature virion are known, with the exception of three ejection proteins. Furthermore, the changes that occur to the proteins residing in the mature virion upon DNA release are not fully understood. We used cryogenic electron microscopy to obtain what is, to our knowledge, the first asymmetric reconstruction of mature bacteriophage P22 after double-stranded DNA has been extruded from the capsid-a state representative of one step during viral infection. Results of icosahedral and asymmetric reconstructions at estimated resolutions of 7.8 and 12.5 Å resolutions, respectively, are presented. The reconstruction shows tube-like protein density extending from the center of the tail assembly. The portal protein does not revert to the more contracted, procapsid state, but instead maintains an extended and splayed barrel structure. These structural details contribute to our understanding of the molecular mechanism of P22 phage infection and also set the foundation for future exploitation serving engineering purposes.

Single-particle cryogenic electron microscopy (cryo-EM) provides a powerful methodology for structural biologists, but the resolutions typically attained with experimentally determined structures have lagged behind microscope capabilities. Here, we have exploited several technical solutions to improve resolution, including sub-Angstrom pixelation, per-particle CTF refinement, and most notably a correction for Ewald sphere curvature. The application of these methods on micrographs recorded on a base model Titan Krios enabled structure determination at ∼1.86-Å resolution of an adeno-associated virus serotype 2 variant (AAV2), an important gene-delivery vehicle.

Persistent, high-risk human papillomavirus (HPV) infection is the primary cause of cervical cancer. Neutralizing antibodies elicited by L1-only virus-like particles (VLPs) can block HPV infection; however, the lack of high-resolution structures has limited our understanding of the mode of virus infection and the requirement for type specificity at the molecular level. Here, we describe two antibodies, A12A3 and 28F10, that specifically bind to and neutralize HPV58 and HPV59, respectively, through two distinct binding stoichiometries. We show that the epitopes of A12A3 are clustered in the DE loops of two adjacent HPV58 L1 monomers, whereas 28F10 recognizes the HPV59 FG loop of a single monomer. Via structure-based mutagenesis and analysis of antibody binding, we further identified the residues HPV58 D154, S168, and N170 and HPV59 M267, Q270, E273, Y276, K278, and R283, which play critical roles in virus infection. By substituting these strategic epitope residues into other HPV genotypes, we could then redirect the type-specific binding of the antibodies to these genotypes, thus highlighting the importance of these specific residues, HPV58 R161, S168, and N308 and HPV59 Q270, E273, and D281. Overall, our findings provide molecular insights into potential structural determinants of HPV required for infectivity and type specificity.IMPORTANCE High-risk human papillomaviruses (HPVs) are considered the major causative pathogens of cancers that affect epithelial mucosa, such as cervical cancer. However, because of the lack of high-resolution structural information on the sites of neutralization, we have yet to determine the precise mode of HPV infection and how different types of HPV cause infection. Our crystal structures in this study have uncovered discrete binding stoichiometries for two different antibodies. We show that one A12A3 Fab binds to the center of one HPV58 pentamer, whereas five 28F10 Fabs bind along the top fringe of one HPV59 pentamer. Furthermore, through targeted epitope analysis, we show that 6 to 7 discontinuous residues of the L1 major capsid protein of HPV are determinants, at least in part, for virus infection and type specificity. This knowledge will help us to unravel the process of HPV infection and can potentially be used to drive the development of therapeutics that target neutralization-sensitive sites.

LuIII, a protoparvovirus pathogenic to rodents, replicates in human mitotic cells, making it applicable for use to kill cancer cells. This virus group includes H-1 parvovirus (H-1PV) and minute virus of mice (MVM). However, LuIII displays enhanced oncolysis compared to H-1PV and MVM, a phenotype mapped to the major capsid viral protein 2 (VP2). This suggests that within LuIII VP2 are determinants for improved tumor lysis. To investigate this, the structure of the LuIII virus-like-particle was determined using single particle cryo-electron microscopy and image reconstruction to 3.17 Å resolution, and compared to the H-1PV and MVM structures. The LuIII VP2 structure, ordered from residue 37 to 587 (C-terminal), had the conserved VP topology and capsid morphology previously reported for other protoparvoviruses. This includes a core β-barrel and α-helix A, a depression at the icosahedral 2-fold and surrounding the 5-fold axes, and a single protrusion at the 3-fold axes. Comparative analysis identified surface loop differences among LuIII, H-1PV, and MVM at or close to the capsid 2- and 5-fold symmetry axes, and the shoulder of the 3-fold protrusions. The 2-fold differences cluster near the previously identified MVM sialic acid receptor binding pocket, and revealed potential determinants of protoparvovirus tumor tropism.