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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]

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Predictions of above-ground biomass and the change in above-ground biomass require attachment of uncertainty due the range of reported predictions for forests. Because above-ground biomass is seldom measured, there have been no opportunities to obtain such uncertainty estimates. Standard methods involve applying an allometric equation to each individual tree on sample plots and summing the individual values. There is uncertainty in the allometry which leads to uncertainty in biomass at the tree level. Due to interdependence between competing trees, the uncertainty at the plot level that results from aggregating individual tree biomass in this way is expected to overestimate variability. That is, the variance at the plot level should be less than the sum of the individual variances. We offer a modeling strategy to learn about change in biomass at the plot level and model cumulative uncertainty to accommodate this dependence among neighboring trees. The plot-level variance is modeled using a parametric density-dependent asymptotic function. Plot-by-time covariate information is introduced to explain the change in biomass. These features are incorporated into a hierarchical model and inference is obtain within a Bayesian framework. We analyze data for the eastern United States from the Forest Inventory and Analysis (FIA) Program of the US Forest Service. This region contains roughly 25,000 FIA monitored plots from which there are measurements of approximately 1 million trees spanning more than 200 tree species. Due to the high species richness in the FIA data, we combine species into plant functional types. We present predictions of biomass and change in biomass for two plant functional types. [ABSTRACT FROM AUTHOR]

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]

Background: Social determinants of health (SDHs) are the primary drivers of preventable health inequities, and the associations between SDHs and health outcomes among individuals with type 2 diabetes remain unclear. This study aimed to estimate the associations of combined SDHs with life expectancy and future health risks among adults with type 2 diabetes from the UK and USA., Methods: In an analysis of two nationwide cohort studies, adults with type 2 diabetes were identified from the UK Biobank from March 13, 2006, to Oct 1, 2010 (adults aged 37-73 years) and the US National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018 (adults aged ≥20 years). Participants with type 2 diabetes at baseline were included in our analysis. Participants without information on SDHs or follow-up were excluded. The UK Biobank assessed 17 SDHs and the US NHANES assessed ten SDHs, with each SDH dichotomised into advantaged and disadvantaged levels. The combined score of SDHs were calculated as the sum of the weighted scores for each SDH. Participants were then categorised into tertiles (favourable, medium, and unfavourable SDH groups). Primary outcomes were life expectancy and mortality in both cohorts, and incidences of cardiovascular disease, diabetes-related microvascular disease, dementia, and cancer in the UK Biobank. Outcomes were obtained from disease registries up until Dec 31, 2021, in the UK Biobank and Dec 31, 2019, in the US NHANES cohorts., Findings: We included 17 321 participants from the UK Biobank cohort (median age 61·0 years [IQR 56·0-65·0]; 6028 [34·8%] women and 11 293 [65·2%] men) and 7885 participants from the NHANES cohort (mean age 59·2 years [95% CI 58·7-59·6]; 3835 [49·1%, weighted] women and 4050 [50·9%, weighted] men) in our analysis. In the UK Biobank, 3235 deaths (median follow-up 12·3 years [IQR 11·5-13·2]), 3010 incident cardiovascular disease (12·1 years [10·8-13·0]), 1997 diabetes-related microvascular disease (8·0 years [7·1-8·9]), 773 dementia (12·6 years [11·8-13·5]), and 2259 cancer cases (11·3 years [10·4-12·2]) were documented; and the US NHANES documented 2278 deaths during a median follow-up of 7·0 years (3·7-11·2). After multivariable adjustment, compared with the favourable SDH group, the hazard ratio was 1·33 (95% CI 1·21-1·46) in the medium SDH group and 1·89 (1·72-2·07) in the unfavourable SDH group in the UK Biobank cohort; 1·51 (1·34-1·70) in the medium SDH group and 2·02 (1·75-2·33) in the unfavourable SDH group in the US NHANES cohort for all-cause mortality; 1·13 (1·04-1·24) in the medium SDH group and 1·40 (1·27-1·53) in the unfavourable SDH group for incident cardiovascular disease; 1·13 (1·01-1·27) in the medium SDH group and 1·41 (1·26-1·59) in the unfavourable SDH group for incident diabetes-related microvascular disease; 1·35 (1·11-1·64) in the medium SDH group and 1·76 (1·46-2·13) in the unfavourable SDH group for incident dementia; and 1·02 (0·92-1·13) in the medium SDH group and 1·17 (1·05-1·30) in the unfavourable SDH group for incident cancer in the UK Biobank cohort (p trend <0·010 for each category). At the age of 45 years, the mean life expectancy of participants was 1·6 years (0·6-2·3) shorter in the medium SDH group and 4·4 years (3·3-5·4) shorter in the unfavourable SDH group than in the favourable SDH group in the UK Biobank. In the US NHAHES cohort, the life expectancy was 1·7 years (0·6-2·7) shorter in the medium SDH group and 3·0 years (1·8-4·3) shorter in the unfavourable SDH group, compared with the favourable group., Interpretation: Combined unfavourable SDHs were associated with a greater loss of life expectancy and higher risks of developing future adverse health outcomes among adults with type 2 diabetes. These associations were similar across two nationwide cohorts from varied social contexts, and were largely consistent across populations with different demographic, lifestyle, and clinical features. Thus, assessing the combined SDHs of individuals with type 2 diabetes might be a promising approach to incorporate into diabetes care to identify socially vulnerable groups and reduce disease burden., Funding: The National Natural Science Foundation of China, the National Key R&D Program of China, and the Fundamental Research Funds for the Central Universities., Competing Interests: Declaration of interests We declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Introduction: Patients who leave against medical advice (AMA) face increased risks of negative health outcomes, presenting a challenge for healthcare systems. This study examines demographic and hospital course factors associated with patients leaving AMA after an upper extremity (UE) orthopaedic procedure., Methods: We analyzed 262,912 patients who underwent UE orthopaedic procedures between 2011 and 2020, using the Healthcare Cost and Utilization Project database. We then compared demographic and hospital course factors between patients who left AMA and those who did not leave AMA., Results: Of 262,912 UE orthopaedic patients, 0.45% (1,173) left AMA. Those more likely to leave AMA were aged 30 to 49 (OR, 5.953, P < 0.001), Black (OR, 1.708, P < 0.001), had Medicaid (OR, 3.436, P < 0.001), and were in the 1st to 25th income percentile (OR, 1.657, P < 0.001). Female patients were less likely to leave AMA than male patients (OR, 0.647, P < 0.001). Patients leaving AMA had longer stays (3.626 versus 2.363 days, P < 0.001) and longer recovery times (2.733 versus 1.977, P < 0.001)., Conclusion: We found that male, Black, younger than 49 years old, Medicaid-insured, and lowest income quartile patients are more likely to leave AMA after UE orthopaedic treatment., (Copyright © 2024 The Authors. Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Orthopaedic Surgeons.)

Forests are integral to the global land carbon sink, which has sequestered ~30% of anthropogenic carbon emissions over recent decades. The persistence of this sink depends on the balance of positive drivers that increase ecosystem carbon storage-e.g., CO 2 fertilization-and negative drivers that decrease it-e.g., intensifying disturbances. The net response of forest productivity to these drivers is uncertain due to the challenge of separating their effects from background disturbance-regrowth dynamics. We fit non-linear models to US forest inventory data (113,806 plot remeasurements in non-plantation forests from ~1999 to 2020) to quantify productivity trends while accounting for stand age, tree mortality, and harvest. Productivity trends were generally positive in the eastern United States, where climate change has been mild, and negative in the western United States, where climate change has been more severe. Productivity declines in the western United States cannot be explained by increased mortality or harvest; these declines likely reflect adverse climate-change impacts on tree growth. In the eastern United States, where data were available to partition biomass change into age-dependent and age-independent components, forest maturation and increasing productivity (likely due, at least in part, to CO 2 fertilization) contributed roughly equally to biomass carbon sinks. Thus, adverse effects of climate change appear to overwhelm any positive drivers in the water-limited forests of the western United States, whereas forest maturation and positive responses to age-independent drivers contribute to eastern US carbon sinks. The future land carbon balance of forests will likely depend on the geographic extent of drought and heat stress., Competing Interests: Competing interests statement:The authors declare no competing interest.