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Density dependence could maintain diversity in forests, but studies continue to disagree on its role. Part of the disagreement results from the fact that different studies have evaluated different responses (survival, recruitment, or growth) of different stages (seeds, seedlings, or adults) to different inputs (density of seedlings, density or distance to adults). Most studies are conducted on a single site and thus are difficult to generalize. Using USDA Forest Service's Forest Inventory and Analysis data, we analyzed over a million seedling-tosapling recruitment observations of 50 species from the eastern United States, controlling for the effects of climate. We focused on the per-seedling recruitment rate, because it is most likely to promote diversity and to be identified in observational or experimental data. To understand the prevalence of density dependence, we quantified the number of species with significant positive or negative effects. To understand the strength of density dependence, we determined the magnitude of effects among con- and heterospecifics, and how it changes with overall species abundance. We found that density dependence is pervasive among the 50 species, as the majority of them have significant effects and mostly negative. Density-dependence effects are stronger from conspecific than heterospecfic adult neighbors, consistent with the predictions of the Janzen-Connell hypothesis. Contrary to recent reports, density-dependence effects are more negative for common than rare species, suggesting disproportionately stronger population regulation in common species. We conclude that density dependence is pervasive, and it is strongest from conspecific neighbors of common species. Our analysis provides direct evidence that density dependence regulates population dynamics of tree species in eastern U.S. forests. [ABSTRACT FROM AUTHOR]

Current evidence implicates a significant association between depression and obesity and related metabolic dysfunction. The weight-adjusted-waist index (WWI) was recently identified as an ideal index that integrates total body fat, muscle mass, and bone mass. This study investigated the relationship between WWI and depressive symptoms in adults. Participants from the National Health and Nutrition Examination Survey (2005–2018) were enrolled. Depressive symptom severity was measured with the Patient Health Questionnaire-9 (PHQ-9). Survey-weighted multivariable logistic regression, subgroup analysis, and generalized additive models were used to determine the relationship between WWI and depressive symptoms. A total of 34,575 participants were included, with a mean WWI of 11.01; 2,979 participants were suspected of having depressive symptoms (PHQ-9 score ≥ 10). A significant positive association was identified between WWI and depressive symptoms (odds ratio = 1.416, 95 % confidence interval: 1.303–1.539, P < 0.0001). Subgroup analyses suggested that the association between WWI and depressive symptoms was stronger in individuals who were female, overweight, divorced, middle-aged or older (over 40 years old), and had diabetes. Furthermore, the non-linear multivariable regression revealed an inflection point for the WWI at 11.438, and the association was only significant when the WWI was higher than this point. This study was retrospective and only included participants from the United States; therefore, further validation is needed from studies in other countries, especially middle-to-low-income countries, using longitudinal cohorts. This study identified a significant positive association between WWI and depressive symptoms. • Weight-adjusted-waist-index (WWI) was an integrated index that reflect the condition of fat, muscle and bone mass. • WWI is closely related to depression, particularly in females and individuals with marital difficulties or diabetes. • The association between WWI and depressive symptom was more significant when the score of WWI was higher than 11.438. [ABSTRACT FROM AUTHOR]

Purpose: To examine the associations of healthy dietary patterns with cardiometabolic biomarkers and all-cause mortality among individuals with prediabetes. Methods: This cohort study included 8363 adults with prediabetes from the National Health and Nutrition Examination Survey 1999–2014. Healthy dietary patterns including Alternate Healthy Eating Index-2010 (AHEI-2010), Alternate Mediterranean Diet score (AMED), Dietary Approaches to Stop Hypertension score (DASH), and Healthy Eating Index-2015 (HEI-2015) were calculated based on 24-h dietary recall data. Mortality status was obtained by linkage to National Death Index records. Cardiometabolic biomarkers, including blood glucose, insulin, HbA1c, C-reactive protein (CRP), and lipids, were measured at recruitment. Results: During 61,991 person-years of follow-up, 991 deaths occurred. Comparing the extreme quartiles, the multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause mortality were 0.65 (0.49, 0.85) for AHEI-2010 (P-trend = 0.002), 0.68 (0.50, 0.92) for AMED (P-trend = 0.004), 0.72 (0.53, 0.98) for DASH (P-trend = 0.03), and 0.78 (0.58, 1.05) for HEI-2015 (P-trend = 0.08). Besides, the HRs (95% CIs) for all-cause mortality per 20-percentile increment in scores were 0.78 (0.67, 0.90) for AHEI-2010 (P = 0.001), 0.73 (0.62, 0.86) for AMED (P < 0.001), 0.84 (0.69, 1.02) for DASH (P = 0.08), and 0.86 (0.74, 1.00) for HEI-2015 (P = 0.04). In addition, higher dietary scores were associated with favorable blood glucose, insulin, HOMA-IR, blood lipids, and CRP (all P-trend < 0.05). The high-density lipoprotein cholesterol and CRP explained 1.53–9.21% of the associations between dietary patterns and all-cause mortality (P < 0.05). Conclusions: Diets with higher AHEI-2010, AMED, DASH, and HEI-2015 were associated with improved cardiometabolic factors and lower all-cause mortality among individuals with prediabetes. These findings suggest that multiple healthy dietary patterns instead of a one-size-fits-all diet plan might be beneficial and acceptable for individuals with prediabetes. [ABSTRACT FROM AUTHOR]

Many applications involve count data from a process that yields an excess number of zeros. Zero-inflated count models, in particular, zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) models, along with Poisson hurdle models, are commonly used to address this problem. However, these models struggle to explain extreme incidence of zeros (say more than 80%), especially to find important covariates. In fact, the ZIP may struggle even when the proportion is not extreme. To redress this problem we propose the class of k-ZIG models. These models allow more flexible modeling of both the zero-inflation and the nonzero counts, allowing interplay between these two components. We develop the properties of this new class of models, including reparameterization to a natural link function. The models are straightforwardly fitted within a Bayesian framework. The methodology is illustrated with simulated data examples as well as a forest seedling dataset obtained from the USDA Forest Service's Forest Inventory and Analysis program. [ABSTRACT FROM AUTHOR]

The goal of elucidating the primary mechanisms constraining the assembly and distribution of biodiversity remains among the central unresolved challenges facing the field of ecology. Simulation studies and experimental manipulations have focused on how patterns in community assembly result from bivariate relationships along productivity or environmental gradients. However, the joint influence of multiple resource gradients on the distribution of species richness in natural communities remains understudied. Using data from a large network of multiscale vegetation plots across forests and woodlands of the southeastern United States, we find significant evidence for the scale‐dependent, joint constraints of forest structure and soil resources on the distribution of vascular plant species richness. In addition to their significant partial effects on species richness, understory light levels and soil fertility positively interact, suggesting a trade‐off between the two limiting resources with species richness peaking both in high‐light, low‐fertility conditions as well as low‐light, high‐fertility settings. This finding provides a novel perspective on the biodiversity–productivity relationship that suggests a transition in limiting resources from soil nutrients to light availability when enhanced productivity results in reduced light resources for subordinate individuals. Results likewise have meaningful implications for our understanding of scale‐dependent community assembly processes as size‐asymmetric competition replaces environmental filtering as the primary assembly mechanism structuring temperate forest communities along an increasing soil fertility gradient. [ABSTRACT FROM AUTHOR]