Associations between noticing public health education campaigns about cannabis and risk perceptions in the northern Canadian territories: a cross-sectional study.

This study investigated whether noticing cannabis education campaigns was associated with increased cannabis risk perceptions in Canada's three territories following non-medical cannabis legalization. Data were from the Cannabis Policy Study in the Territories, including 2452 participants, age ≥16 years residing in Yukon, Northwest Territories and Nunavut. Poisson regression with robust standard errors were used to estimate associations between noticing cannabis education campaigns and moderate to very high risk perceptions of daily cannabis smoking, vaping, edible use and exposure to second-hand cannabis smoke, adjusting for sociodemographic characteristics and cannabis-use frequency. Results were compared with associations with risk perceptions of daily alcohol consumption and cigarette smoking, not included in cannabis education campaigns. Interactions were examined between noticing education campaigns and age group and cannabis-use frequency. Cannabis education campaigns were noticed by 40.4% of respondents, with lower awareness among those with lower education and income. Noticing campaigns was associated with higher risk perceptions of daily cannabis smoking [adjusted risk ratio (RRadj) = 1.09, 95% confidence interval (CI): 1.02-1.16] and vaping (RRadj = 1.09, 95%CI: 1.02-1.16). Significant interactions were not found with age group or cannabis-use frequency. Findings are consistent with modest effects of cannabis education campaigns. Approaches are needed to increase reach of cannabis education campaigns, including among groups with lower education and income.

A Scoping Review of the Use of Machine Learning in Health Economics and Outcomes Research: Part 1-Data From Wearable Devices.

OBJECTIVES: With the emerging use of machine learning (ML) techniques, there has been particular interest in using wearable data for health economics and outcomes research (HEOR). We aimed to understand the emerging patterns of how ML has been applied to wearable data in HEOR. METHODS: We identified studies published in PubMed between January 2016 and March 2021. Studies that included at least 1 HEOR-related Medical Subject Headings term, applied an ML, and used wearable data were eligible for inclusion. Two reviewers abstracted information including ML application types and data on which ML was applied and analyzed them using descriptive analyses. RESULTS: A total of 148 studies were identified from PubMed, among which 32 studies met the inclusion criteria. There has been an increase over time in the number of ML studies using wearable data. ML has been more frequently used for monitoring events in real time (78%) than to predict future events (22%). There has been a wide range of outcomes examined, ranging from general physical or mental health (24%) to more disease-specific outcomes (eg, disease incidence [19%] and progression [13%]) and treatment-related outcomes (eg, treatment adherence [9%] and outcomes [9%]). Data for ML models were more often derived from wearable devices with specific medical purposes (60%) than those without (40%). CONCLUSION: There has been a wide range of applications of ML to wearable data. Both medical and nonmedical wearable devices have been used as a data source, showing the potential for providing rich data for ML studies in HEOR.

Is higher school neighbourhood Walk Score associated with greater child pedestrian safety near schools?

Walk Score is a common index used to estimate how suitable the built environment is for walking. Although Walk Score has been extensively validated as a measure of walkability and walking, there are limited studies examining whether commonly used constructs of walkability are associated with traffic safety in children. This study examined the association between Walk Score and child pedestrian injury controlling for observed walking exposure in school zones in Calgary, Toronto and Montreal, Canada. Results indicate that a higher Walk Score was associated with more child pedestrian injuries in all three cities, even after controlling for walking exposure. School travel planning should consider established individual pedestrian collision risk and individual factors rather than assuming a highly walkable environment is also a safe pedestrian environment.

Leaf habit affects the distribution of drought sensitivity but not water transport efficiency in the tropics.

Considering the global intensification of aridity in tropical biomes due to climate change, we need to understand what shapes the distribution of drought sensitivity in tropical plants. We conducted a pantropical data synthesis representing 1117 species to test whether xylem-specific hydraulic conductivity (KS ), water potential at leaf turgor loss (ΨTLP ) and water potential at 50% loss of KS (ΨP50 ) varied along climate gradients. The ΨTLP and ΨP50 increased with climatic moisture only for evergreen species, but KS did not. Species with high ΨTLP and ΨP50 values were associated with both dry and wet environments. However, drought-deciduous species showed high ΨTLP and ΨP50 values regardless of water availability, whereas evergreen species only in wet environments. All three traits showed a weak phylogenetic signal and a short half-life. These results suggest strong environmental controls on trait variance, which in turn is modulated by leaf habit along climatic moisture gradients in the tropics.

Ephemeral forest regeneration limits carbon sequestration potential in the Brazilian Atlantic Forest.

Although deforestation remains widespread in the tropics, many places are now experiencing significant forest recovery (i.e., forest transition), offering an optimistic outlook for natural ecosystem recovery and carbon sequestration. Naturally regenerated forests, however, may not persist, so a more nuanced understanding of the drivers of forest change in the tropics is critical to ensure the success of reforestation efforts and carbon sequestration targets. Here we use 35 years of detailed land cover data to investigate forest trajectories in 3014 municipalities in the Brazilian Atlantic Forest (AF), a biodiversity and conservation hotspot. Although deforestation was evident in some regions, deforestation reversals, the typical forest transition trajectory, were the prevalent trend in the AF, accounting for 38% of municipalities. However, simultaneous reforestation reversals in the region (13% of municipalities) suggest that these short-term increases in native forest cover do not necessarily translate into persistent trends. In the absence of reversals in reforestation, forests in the region could have sequestered 1.75 Pg C, over three times the actual estimated carbon sequestration (0.52 Pg C). We also showed that failure to distinguish native and planted forests would have masked native forest cover loss in the region and overestimated reforestation by 3.2 Mha and carbon sequestration from natural forest regeneration by 0.37 Pg C. Deforestation reversals were prevalent in urbanized municipalities with limited forest cover and high agricultural productivity, highlighting the importance of favorable socioeconomic conditions in promoting reforestation. Successful forest restoration efforts will require development and enforcement of environmental policies that promote forest regeneration and ensure the permanence of regrowing forests. This is crucial not only for the fate and conservation of the AF, but also for other tropical nations to achieve their restoration and carbon sequestration commitments.

Glycemic Index, Glycemic Load, Fiber, and Gluten Intake and Risk of Laparoscopically Confirmed Endometriosis in Premenopausal Women.

BACKGROUND: The etiology of endometriosis is not well understood. Limited evidence suggests that dietary factors influence risk, but prospective data related to carbohydrate, fiber, and gluten consumption are scarce. Despite this, recommendations concerning fiber, gluten intake, and endometriosis are pervasive in the lay literature. OBJECTIVES: We aimed to investigate the associations of carbohydrate quality [glycemic index (GI) and glycemic load (GL)], fiber intake (total, legume, vegetable, cruciferous vegetable, fruit, cereal), and gluten intake with incident laparoscopically confirmed endometriosis. METHODS: This was a prospective cohort study using data collected from 81,961 premenopausal women in the Nurses' Health Study II (mean age = 36 y in 1991). Diet was assessed with a validated FFQ every 4 y. Cox proportional hazards models were used to calculate rate ratios (RRs) and 95% CIs. RESULTS: A total of 3810 incident cases of laparoscopically confirmed endometriosis were reported over 24 y of follow-up. Women in the highest quintile of GI had 12% (95% CI: 1.01, 1.23; Ptrend = 0.03) higher risk of endometriosis diagnosis than those in the lowest quintile. Total vegetable and cruciferous vegetable fiber intakes were also associated with higher risk (highest compared with lowest quintile RR: 1.13; 95% CI: 1.02, 1.24; Ptrend = 0.004 and RR: 1.17; 95% CI: 1.06, 1.29; Ptrend = 0.02, respectively). Higher intake of fruit fiber was associated with lower risk of endometriosis but the association was not significant after adjusting for the Alternative Healthy Eating Index. Gluten intake was also associated with lower risk (highest compared with lowest quintile RR: 0.91; 95% CI: 0.80, 1.02; Ptrend = 0.01), but these results were not consistent in direction nor statistical significance across sensitivity analyses. No association was observed for GL or total, legume, or cereal fiber intake. CONCLUSIONS: Our findings suggest that carbohydrate quality and specific types of fiber-total vegetable and cruciferous vegetable fiber-are associated with endometriosis diagnosis in premenopausal women. These results also indicate it is unlikely that gluten intake is a strong factor in the etiology or symptomatology of endometriosis.

Trends in treatment patterns and costs of care among patients with advanced stage cervical cancer.

BACKGROUND: Current treatments for recurrent or metastatic cervical cancer (r/mCC) do not offer satisfactory clinical benefits, with most patients progressing beyond first-line (1L) treatment. With new treatments under investigation, understanding current treatment patterns, the impact of newly approved therapies, and total costs of care for r/mCC are important. METHODS: A retrospective analysis of a US commercial insurance claims database to identify adult patients with r/mCC between 2015 and Q1-2020; defining 1L treatment as the first administration of systemic treatment without concomitant chemoradiation or surgery. Patient characteristics, treatment regimens, duration of therapy, and total costs of care were evaluated for each line of therapy. RESULTS: 1323 women initiated 1L treatment for r/mCC (mean age, 56.1 years; mean follow-up, 16.5 months). One-third (n = 438) had evidence of second-line (2L) treatment; of these, 129 (29%) had evidence of third-line (3L) treatment. No regimen represented a majority among 2L+ treatments. The 2018 approval of pembrolizumab led to increased 2L immunotherapy use (0% in 2015, 37% in 2019/Q1-2020). However, only a small proportion of patients stayed on immunotherapy for a prolonged period. Mean per-patient-per-month total costs of care during treatment were $47,387 (1L), $77,661 (2L), and $53,609 (3L), driven primarily by outpatient costs. CONCLUSIONS: No clear standard of care was observed in 2L+. Although immunotherapy is increasingly used in 2L+, only a small subset of patients stayed on immunotherapy for a prolonged period, suggesting a need for more therapeutic options. Better understanding of disease biology and the introduction of new therapies may address these unmet needs.

A Scoping Review of the Use of Machine Learning in Health Economics and Outcomes Research: Part 2-Data From Nonwearables.

OBJECTIVES: Despite the increasing interest in applying machine learning (ML) methods in health economics and outcomes research (HEOR), stakeholders face uncertainties in when and how ML can be used. We reviewed the recent applications of ML in HEOR. METHODS: We searched PubMed for studies published between January 2020 and March 2021 and randomly chose 20% of the identified studies for the sake of manageability. Studies that were in HEOR and applied an ML technique were included. Studies related to wearable devices were excluded. We abstracted information on the ML applications, data types, and ML methods and analyzed it using descriptive statistics. RESULTS: We retrieved 805 articles, of which 161 (20%) were randomly chosen. Ninety-two of the random sample met the eligibility criteria. We found that ML was primarily used for predicting future events (86%) rather than current events (14%). The most common response variables were clinical events or disease incidence (42%) and treatment outcomes (22%). ML was less used to predict economic outcomes such as health resource utilization (16%) or costs (3%). Although electronic medical records (35%) were frequently used for model development, claims data were used less frequently (9%). Tree-based methods (eg, random forests and boosting) were the most commonly used ML methods (31%). CONCLUSIONS: The use of ML techniques in HEOR is growing rapidly, but there remain opportunities to apply them to predict economic outcomes, especially using claims databases, which could inform the development of cost-effectiveness models.

Child pedestrian and cyclist injuries, and the built and social environment across Canadian cities: the Child Active Transportation Safety and the Environment Study (CHASE).

INTRODUCTION: Traffic injury is a leading and preventable cause of child death and disability, with child pedestrians and cyclists particularly vulnerable. Examining built environment correlates of child pedestrian and cyclist motor vehicle collisions (PCMVC) in different settings is needed to promote an evidence-based approach to road safety. METHODS: We conducted a cross-sectional study across multiple urban/suburban environments in Canada (Calgary, Toronto, Montreal, Laval, Peel Region). All public elementary schools were included (n=1030). We examined the role of land use/social environments, road environments and traffic safety interventions on the rates of child PCMVC within 1000 m of schools. Multivariable negative binomial regression was conducted for all cities and by individual city. In a subset of schools (n=389), we examined associations when controlling for active school transportation (AST). RESULTS: Mean PCMVC rate per school ranged from 0.13 collisions/year in Peel to 0.35 in Montreal. Child PCMVC were correlated with land use, social and road environments and traffic safety interventions. In fully adjusted models, social and land use features remained the most important correlates. New immigrant population had the largest positive association with child PCMVC (incidence rate ratio (IRR): 1.26, 95% CI 1.06 to 1.50), while old housing (pre-1960) density was most protective (IRR: 0.83, 95% CI 0.77 to 0.90). AST was associated with PCMVC, but it had no effect on the relationships between PCMVC and other social/environmental correlates. CONCLUSION: The built environment and social factors influence rates of child PCMVC. Opportunities to reduce child PCMVC exist through modifications to city design and road environments and implementing traffic safety interventions.

Beyond leaf habit: generalities in plant function across 97 tropical dry forest tree species.

Leaf habit has been hypothesized to define a linkage between the slow-fast plant economic spectrum and the drought resistance-avoidance trade-off in tropical forests ('slow-safe vs fast-risky'). However, variation in hydraulic traits as a function of leaf habit has rarely been explored for a large number of species. We sampled leaf and branch functional traits of 97 tropical dry forest tree species from four sites to investigate whether patterns of trait variation varied consistently in relation to leaf habit along the 'slow-safe vs fast-risky' trade-off. Leaf habit explained from 0% to 43.69% of individual trait variation. We found that evergreen and semi-deciduous species differed in their location along the multivariate trait ordination when compared to deciduous species. While deciduous species showed consistent trait values, evergreen species trait values varied as a function of the site. Last, trait values varied in relation to the proportion of deciduous species in the plant community. We found that leaf habit describes the strategies that define drought avoidance and plant economics in tropical trees. However, leaf habit alone does not explain patterns of trait variation, which suggests quantifying site-specific or species-specific uncertainty in trait variation as the way forward.

Potential Cost-Effectiveness of Risk-Based Pancreatic Cancer Screening in Patients With New-Onset Diabetes.

BACKGROUND: There are no established methods for pancreatic cancer (PAC) screening, but the NCI and the Pancreatic Cancer Action Network (PanCAN) are investigating risk-based screening strategies in patients with new-onset diabetes (NOD), a group with elevated PAC risk. Preliminary estimates of the cost-effectiveness of these strategies can provide insights about potential value and inform supplemental data collection. Using data from the Enriching New-Onset Diabetes for Pancreatic Cancer (END-PAC) risk model validation study, we assessed the potential value of CT screening for PAC in those determined to be at elevated risk, as is being done in a planned PanCAN Early Detection Initiative trial. METHODS: We created an integrated decision tree and Markov state-transition model to assess the cost-effectiveness of PAC screening in patients aged ≥50 years with NOD using CT imaging versus no screening. PAC prevalence, sensitivity, and specificity were derived from the END-PAC validation study. PAC stage distribution in the no-screening strategy and PAC survival were derived from the SEER program. Background mortality for patients with diabetes, screening and cancer care expenditure, and health state utilities were derived from the literature. Life-years (LYs), quality-adjusted LYs (QALYs), and costs were tracked over a lifetime horizon and discounted at 3% per year. Results are presented in 2020 US dollars, and we took a limited US healthcare perspective. RESULTS: In the base case, screening resulted in 0.0055 more LYs, 0.0045 more QALYs, and $293 in additional expenditures for a cost per QALY gained of $65,076. In probabilistic analyses, screening resulted in a cost per QALY gained of <$50,000 and <$100,000 in 34% and 99% of simulations, respectively. In the threshold analysis, >25% of screen-detected PAC cases needed to be resectable for the cost per QALY gained with screening to be <$100,000. CONCLUSIONS: We found that risk-based PAC screening in patients with NOD is likely to be cost-effective in the United States if even a modest fraction (>25%) of screen-detected patients with PAC are resectable. Future studies should reassess the value of this intervention once clinical trial data become available.

Economic burden of central nervous system metastases in human epidermal growth factor receptor 2-positive breast cancer.

Aim: Compare healthcare resource utilization and costs among patients with HER2+ metastatic breast cancer (MBC) with and without central nervous system (CNS) metastases. Methods: Retrospective matched cohort study using IQVIA's PharMetrics® Plus claims database. Results: Patients with CNS metastases (n = 753) experienced more outpatient, emergency room and inpatient visits versus controls (n = 753; all p < 0.05). In the post-index year, median total all-cause healthcare costs were significantly higher among patients with CNS metastases versus controls ($112,402 vs $50,835; p < 0.0001); outpatient costs primarily drove the cost differential. Conclusion: More effective therapies are needed that improve clinical outcomes and reduce economic burden associated with CNS metastases in patients with HER2+ MBC.

The use of narrative electronic prescribing instructions in pharmacoepidemiology: A scoping review for the International Society for Pharmacoepidemiology.

Narrative electronic prescribing instructions (NEPIs) are text that convey information on the administration or co-administration of a drug as directed by a prescriber. For researchers, NEPIs have the potential to advance our understanding of the risks and benefits of medications in populations; however, due to their unstructured nature, they are not often utilized. The goal of this scoping review was to evaluate how NEPIs are currently employed in research, identify opportunities and challenges for their broader application, and provide recommendations on their future use. The scoping review comprised a comprehensive literature review and a survey of key stakeholders. From the literature review, we identified 33 primary articles that described the use of NEPIs. The majority of articles (n = 19) identified issues with the quality of information in NEPIs compared with structured prescribing information; nine articles described the development of novel algorithms that performed well in extracting information from NEPIs, and five described the used of manual or simpler algorithms to extract prescribing information from NEPIs. A survey of 19 stakeholders indicated concerns for the quality of information in NEPIs and called for standardization of NEPIs to reduce data variability/errors. Nevertheless, stakeholders believed NEPIs present an opportunity to identify prescriber's intent for the prescription and to study temporal treatment patterns. In summary, NEPIs hold much promise for advancing the field of pharmacoepidemiology. Researchers should take advantage of addressing important questions that can be uniquely answered with NEPIs, but exercise caution when using this information and carefully consider the quality of the data.

Assessment of the Accuracy of Identification of Selected Disabilities and Conditions in Hospital Discharge Data for Pregnant Women.

BACKGROUND: Linked birth certificate-hospital discharge records are a valuable resource for examining pregnancy outcomes among women with disability conditions. Few studies relying on these data have been able to assess the accuracy of identification of preexisting disability conditions. We assessed the accuracy of International Classification of Diseases version 9 (ICD9) codes for identifying selected physical, sensory, and intellectual conditions that may result in disability. As ICD9 codes were utilized until recently in most states, this information is useful to inform analyses with these records. METHODS: We reviewed 280 of 311 (90%) medical records of pregnant women with disabilities based on ICD9 codes and 390 of 8,337 (5%) records of pregnant women without disabilities who had deliveries at a large university medical center. We estimated sensitivity, specificity, and positive predictive values (PPV) using the medical record as gold standard. We adjusted for verification bias using inverse probability weighting and imputation. RESULTS: The estimated sensitivity of ICD9 codes to identify women with disabilities with deliveries 2009-2012 was 44%; PPV was 98%, improving over time. Although sensitivity was <50% for some conditions, PPVs were 87%-100% for all conditions except intellectual disability (67%). Many physical conditions had complete verification and no underreporting. CONCLUSIONS: These results are helpful for new studies using historical data comparing outcomes among women with and without these conditions and to inform interpretation of results from earlier studies. Assessment of the accuracy of disabilities as identified by ICD version 10 codes is warranted.

A catastrophic tropical drought kills hydraulically vulnerable tree species.

Drought-related tree mortality is now a widespread phenomenon predicted to increase in magnitude with climate change. However, the patterns of which species and trees are most vulnerable to drought, and the underlying mechanisms have remained elusive, in part due to the lack of relevant data and difficulty of predicting the location of catastrophic drought years in advance. We used long-term demographic records and extensive databases of functional traits and distribution patterns to understand the responses of 20-53 species to an extreme drought in a seasonally dry tropical forest in Costa Rica, which occurred during the 2015 El Niño Southern Oscillation event. Overall, species-specific mortality rates during the drought ranged from 0% to 34%, and varied little as a function of tree size. By contrast, hydraulic safety margins correlated well with probability of mortality among species, while morphological or leaf economics spectrum traits did not. This firmly suggests hydraulic traits as targets for future research.

Combination of Rapamycin and Resveratrol for Treatment of Bladder Cancer.

Loss of TSC1 function, a crucial negative regulator of mTOR signaling, is a common alteration in bladder cancer. Mutations in other members of the PI3K pathway, leading to mTOR activation, are also found in bladder cancer. This provides rationale for targeting mTOR for treatment of bladder cancer characterized by TSC1 mutations and/or mTOR activation. In this study, we asked whether combination treatment with rapamycin and resveratrol could be effective in concurrently inhibiting mTOR and PI3K signaling and inducing cell death in bladder cancer cells. In combination with rapamycin, resveratrol was able to block rapamycin-induced Akt activation, while maintaining mTOR pathway inhibition. In addition, combination treatment with rapamycin and resveratrol induced cell death specifically in TSC1-/- MEF cells, and not in wild-type MEFs. Similarly, resveratrol alone or in combination with rapamycin induced cell death in human bladder cancer cell lines. These data indicate that administration of resveratrol together with rapamycin may be a promising therapeutic option for treatment of bladder cancer. J. Cell. Physiol. 232: 436-446, 2017. © 2016 Wiley Periodicals, Inc.

Fragmentation increases wind disturbance impacts on forest structure and carbon stocks in a western Amazonian landscape.

Tropical second-growth forests could help mitigate climate change, but the degree to which their carbon potential is achieved will depend on exposure to disturbance. Wind disturbance is common in tropical forests, shaping structure, composition, and function, and influencing successional trajectories. However, little is known about the impacts of extreme winds on second-growth forests in fragmented landscapes, though these ecosystems are often located in mosaics of forest, pasture, cropland, and other land cover types. Indirect evidence suggests that fragmentation increases risk of wind damage in tropical forests, but no studies have found such impacts following severe storms. In this study, we ask whether fragmentation and forest type (old vs. second growth) were associated with variation in wind damage after a severe convective storm in a fragmented production landscape in western Amazonia. We applied linear spectral unmixing to Landsat 8 imagery from before and after the storm, and combined it with field observations of damage to map wind effects on forest structure and biomass. We also used Landsat 8 imagery to map land cover with the goals of identifying old- and second-growth forest and characterizing fragmentation. We used these data to assess variation in wind disturbance across 95,596 ha of forest, distributed over 6,110 patches. We find that fragmentation is significantly associated with wind damage, with damage severity higher at forest edges and in edgier, more isolated patches. Damage was also more severe in old-growth than in second-growth forests, but this effect was weaker than that of fragmentation. These results illustrate the importance of considering landscape context in planning tropical forest restoration and natural regeneration projects. Assessments of long-term carbon sequestration potential need to consider spatial variation in disturbance exposure. Where risk of extreme winds is high, minimizing fragmentation and isolation could increase carbon sequestration potential.

Effects of combining rapamycin and resveratrol on apoptosis and growth of TSC2-deficient xenograft tumors.

Lymphangioleiomyomatosis (LAM) is a rare neoplastic metastatic disease affecting women of childbearing age. LAM is caused by hyperactivation of the mechanistic target of rapamycin complex 1 (mTORC1) as a consequence of tuberous sclerosis complex (TSC) 1/2 inactivation. Clinically, LAM results in cystic lung destruction. mTORC1 inhibition using rapamycin analogs (rapalogs) is partially effective in reducing disease progression and improving lung function. However, cessation of treatment results in continued progression of the disease. In the present study, we investigated the effectiveness of the combination of rapamycin treatment with resveratrol, an autophagy inhibitor, in the TSC2-null xenograft tumor model. We determined that this combination inhibits phosphatidylinositol-4,5-bisphosphate 3-kinase PI3K/Akt/mTORC1 signaling and activates apoptosis. Therefore, the combination of rapamycin and resveratrol may be an effective clinical strategy for treatment of LAM and other diseases with mTORC1 hyperactivation.

The combination of rapamycin and resveratrol blocks autophagy and induces apoptosis in breast cancer cells.

Hyperactivation of the mechanistic target of rapamycin complex 1 (mTORC1) is a frequent event in breast cancer and current efforts are aimed at targeting the mTORC1 signaling pathway in combination with other targeted therapies. However, patients often develop drug resistance in part due to activation of the oncogenic Akt signaling and upregulation of autophagy, which protects cancer cells from apoptosis. In the present study we investigated the effects of combination therapy of rapamycin (an allosteric mTORC1 inhibitor) together with resveratrol (a phytoestrogen that inhibits autophagy). Our results show that combination of these drugs maintains inhibition of mTORC1 signaling, while preventing upregulation of Akt activation and autophagy, causing apoptosis. Additionally, this combination was effective in estrogen receptor positive and negative breast cancer cells, underscoring its versatility.

Ontogenetic shifts in trait-mediated mechanisms of plant community assembly.

Identifying the processes that maintain highly diverse plant communities remains a central goal in ecology. Species variation in growth and survival rates across ontogeny, represented by tree size classes and life history stage-specific niche partitioning, are potentially important mechanisms for promoting forest diversity. However, the role of ontogeny in mediating competitive dynamics and promoting functional diversity is not well understood, particular in high-diversity systems such as tropical forests. The interaction between interspecific functional trait variation and ontogenetic shifts in competitive dynamics may yield insights into the ecophysiological mechanisms promoting community diversity. We investigated how functional trait (seed size, maximum height, SLA, leaf N, and wood density) associations with growth, survival, and response to competing neighbors differ among seedlings and two size classes of trees in a subtropical rain forest in Puerto Rico. We used a hierarchical Bayes model of diameter growth and survival to infer trait relationships with ontogenetic change in competitive dynamics. Traits were more strongly associated with average growth and survival than with neighborhood interactions, and were highly consistent across ontogeny for most traits. The associations between trait values and tree responses to crowding by neighbors showed significant shifts as trees grew. Large trees exhibited greater growth as the difference in species trait values among neighbors increased, suggesting trait-associated niche partitioning was important for the largest size class. Our results identify potential axes of niche partitioning and performance-equalizing functional trade-offs across ontogeny, promoting species coexistence in this diverse forest community.