Inverse modeling of 2010-2022 satellite observations shows that inundation of the wet tropics drove the 2020-2022 methane surge.

Atmospheric methane concentrations rose rapidly over the past decade and surged in 2020-2022 but the causes have been unclear. We find from inverse analysis of GOSAT satellite observations that emissions from the wet tropics drove the 2010-2019 increase and the subsequent 2020-2022 surge, while emissions from northern mid-latitudes decreased. The 2020-2022 surge is principally contributed by emissions in Equatorial Asia (43%) and Africa (30%). Wetlands are the major drivers of the 2020-2022 emission increases in Africa and Equatorial Asia because of tropical inundation associated with La Niña conditions, consistent with trends in the GRACE terrestrial water storage data. In contrast, emissions from major anthropogenic emitters such as the United States, Russia, and China are relatively flat over 2010-2022. Concentrations of tropospheric OH (the main methane sink) show no long-term trend over 2010-2022 but a decrease over 2020-2022 that contributed to the methane surge.

The "double jeopardy" of midlife and old age mortality trends in the United States.

Since 2010, US life expectancy growth has stagnated. Much research on US mortality has focused on working-age adults given adverse trends in drug overdose deaths, other external causes of death, and cardiometabolic deaths in midlife. We show that the adverse mortality trend at retirement ages (65+ y) has in fact been more consequential to the US life expectancy stagnation since 2010, as well as excess deaths and years of life lost in 2019, than adverse mortality trends at working ages. These results reveal that the United States is experiencing a "double jeopardy" that is driven by both mid-life and older-age mortality trends, but more so by older-age mortality. Understanding and addressing the causes behind the worsening mortality trend in older ages will be essential to returning to the pace of life expectancy improvements that the United States had experienced for decades.

Diversified farms bolster forest-bird populations despite ongoing declines in tropical forests.

While some agricultural landscapes can support wildlife in the short term, it is uncertain how well they can truly sustain wildlife populations. To compare population trends in different production systems, we sampled birds along 48 transects in mature forests, diversified farms, and intensive farms across Costa Rica from 2000 to 2017. To assess how land use influenced population trends in the 349 resident and 80 migratory species with sufficient data, we developed population models. We found, first, that 23% of species were stable in all three land use types, with the rest almost evenly split between increasing and decreasing populations. Second, in forest habitats, a slightly higher fraction was declining: 62% of the 164 species undergoing long-term population changes; nearly half of these declines occurred in forest-affiliated invertivores. Third, in diversified farms, 49% of the 230 species with population changes were declining, with 60% of these declines occurring in agriculture-affiliated species. In contrast, 51% of the species with population changes on diversified farms showed increases, primarily in forest-affiliated invertivores and frugivores. In intensive farms, 153 species showed population changes, also with similar proportions of species increasing (50%) and decreasing (50%). Declines were concentrated in agriculture-affiliated invertivores and forest-affiliated frugivores; increases occurred in many large, omnivorous species. Our findings paint a complex picture but clearly indicate that diversified farming helps sustain populations of diverse, forest-affiliated species. Despite not fully offsetting losses in forest habitats, diversified farming practices help sustain wildlife in a critical time, before possible transformation to nature-positive policies and practices.

Observation-derived 2010-2019 trends in methane emissions and intensities from US oil and gas fields tied to activity metrics.

The United States is the world's largest oil/gas methane emitter according to current national reports. Reducing these emissions is a top priority in the US government's climate action plan. Here, we use a 2010 to 2019 high-resolution inversion of surface and satellite observations of atmospheric methane to quantify emission trends for individual oil/gas production regions in North America and relate them to production and infrastructure. We estimate a mean US oil/gas methane emission of 14.8 (12.4 to 16.5) Tg a-1 for 2010 to 2019, 70% higher than reported by the US Environmental Protection Agency. While emissions in Canada and Mexico decreased over the period, US emissions increased from 2010 to 2014, decreased until 2017, and rose again afterward. Increases were driven by the largest production regions (Permian, Anadarko, Marcellus), while emissions in the smaller production regions generally decreased. Much of the year-to-year emission variability can be explained by oil/gas production rates, active well counts, and new wells drilled, with the 2014 to 2017 decrease driven by reduction in new wells and the 2017 to 2019 surge driven by upswing of production. We find a steady decrease in the oil/gas methane intensity (emission per unit methane gas production) for almost all major US production regions. The mean US methane intensity decreased from 3.7% in 2010 to 2.5% in 2019. If the methane intensity for the oil/gas supply chain continues to decrease at this pace, we may expect a 32% decrease in US oil/gas emissions by 2030 despite projected increases in production.

Tracing sources of atmospheric methane using clumped isotopes.

We apply a recently developed measurement technique for methane (CH4) isotopologues* (isotopic variants of CH4-13CH4, 12CH3D, 13CH3D, and 12CH2D2) to identify contributions to the atmospheric burden from fossil fuel and microbial sources. The aim of this study is to constrain factors that ultimately control the concentration of this potent greenhouse gas on global, regional, and local levels. While predictions of atmospheric methane isotopologues have been modeled, we present direct measurements that point to a different atmospheric methane composition and to a microbial flux with less clumping (greater deficits relative to stochastic) in both 13CH3D and 12CH2D2 than had been previously assigned. These differences make atmospheric isotopologue data sufficiently sensitive to variations in microbial to fossil fuel fluxes to distinguish between emissions scenarios such as those generated by different versions of EDGAR (the Emissions Database for Global Atmospheric Research), even when existing constraints on the atmospheric CH4 concentration profile as well as traditional isotopes are kept constant.

Polygenic subtype identified in ACCORD trial displays a favorable type 2 diabetes phenotype in the UKBiobank population.

INTRODUCTION: We previously identified a genetic subtype (C4) of type 2 diabetes (T2D), benefitting from intensive glycemia treatment in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. Here, we characterized the population of patients that met the C4 criteria in the UKBiobank cohort. RESEARCH DESIGN AND METHODS: Using our polygenic score (PS), we identified C4 individuals in the UKBiobank and tested C4 status with risk of developing T2D, cardiovascular disease (CVD) outcomes, and differences in T2D medications. RESULTS: C4 individuals were less likely to develop T2D, were slightly older at T2D diagnosis, had lower HbA1c values, and were less likely to be prescribed T2D medications (P < .05). Genetic variants in MAS1 and IGF2R, major components of the C4 PS, were associated with fewer overall T2D prescriptions. CONCLUSION: We have confirmed C4 individuals are a lower risk subpopulation of patients with T2D.

Baldur: Bayesian Hierarchical Modeling for Label-Free Proteomics with Gamma Regressing Mean-Variance Trends.

Label-free proteomics is a fast-growing methodology to infer abundances in mass spectrometry proteomics. Extensive research has focused on spectral quantification and peptide identification. However, research toward modeling and understanding quantitative proteomics data is scarce. Here we propose a Bayesian hierarchical decision model (Baldur) to test for differences in means between conditions for proteins, peptides, and post-translational modifications. We developed a Bayesian regression model to characterize local mean-variance trends in data, to estimate measurement uncertainty and hyperparameters for the decision model. A key contribution is the development of a new gamma regression model that describes the mean-variance dependency as a mixture of a common and a latent trend-allowing for localized trend estimates. We then evaluate the performance of Baldur, limma-trend, and t test on six benchmark datasets: five total proteomics and one post-translational modification dataset. We find that Baldur drastically improves the decision in noisier post-translational modification data over limma-trend and t test. In addition, we see significant improvements using Baldur over the other methods in the total proteomics datasets. Finally, we analyzed Baldur's performance when increasing the number of replicates and found that the method always increases precision with sample size, while showing robust control of the false positive rate. We conclude that our model vastly improves over popular data analysis methods (limma-trend and t test) in several spike-in datasets by achieving a high true positive detection rate, while greatly reducing the false-positive rate.

Trends in social mobility in postrevolution China.

In this paper, we study long-term trends in social mobility in the People's Republic of China since its inception in 1949, with two operationalizations: 1) intergenerational occupational mobility and 2) intergenerational educational mobility. We draw on an accumulation of administrative and survey data and provide comparable estimates of these measures for birth cohorts born after 1945. To help interpret the results, we compare trends in China to those in the United States for the same birth cohorts. We find an increase in intergenerational occupational mobility in China due to its rapid industrialization in recent decades. Net of industrialization, however, intergenerational occupational mobility has been declining for recent cohorts. Intergenerational educational mobility in China shows a similar declining trend. In addition, mobility patterns have differed greatly by gender, with women in earlier cohorts and from a rural origin particularly disadvantaged. We attribute the general decline in social mobility to market forces that have taken hold since China's economic reform that began in 1978. In contrast, social mobility by both measures has been relatively stable in the United States. However, while social mobility in China has trended downward, it is still higher than that in the United States, except for women's educational mobility.

Rapid wage growth at the bottom has offset rising US inequality.

US earnings inequality has not increased in the last decade. This marks the first sustained reversal of rising earnings inequality since 1980. We document this shift across eight data sources using worker surveys, employer-reported data, and administrative data. The reversal is due to a shrinking gap between low-wage and median-wage workers. In contrast, the gap between top and median workers has persisted. Rising pay for low-wage workers is not mainly due to the changing composition of workers or jobs, minimum wage increases, or workplace-specific sources of inequality. Instead, it is due to broadly rising pay in low-wage occupations, which has particularly benefited workers in tightening labor markets. Rebounding post-Great Recession labor demand at the bottom offset enduring drivers of inequality.

Ischaemic stroke in women with atrial fibrillation: temporal trends and clinical implications.

BACKGROUND AND AIMS: Female sex has been linked with higher risk of ischaemic stroke (IS) in atrial fibrillation (AF), but no prior study has examined temporal trends in the IS risk associated with female sex. METHODS: The registry-linkage Finnish AntiCoagulation in Atrial Fibrillation (FinACAF) study included all patients with AF in Finland from 2007 to 2018. Ischaemic stroke rates and rate ratios were computed. RESULTS: Overall, 229 565 patients with new-onset AF were identified (50.0% women; mean age 72.7 years). The crude IS incidence was higher in women than in men across the entire study period (21.1 vs. 14.9 events per 1000 patient-years, P < .001), and the incidence decreased both in men and women. In 2007-08, female sex was independently associated with a 20%-30% higher IS rate in the adjusted analyses, but this association attenuated and became statistically non-significant by the end of the observation period. Similar trends were observed when time with and without oral anticoagulant (OAC) treatment was analysed, as well as when only time without OAC use was considered. The decrease in IS rate was driven by patients with high IS risk, whereas in patients with low or moderate IS risk, female sex was not associated with a higher IS rate. CONCLUSIONS: The association between female sex and IS rate has decreased and become non-significant over the course of the study period from 2007 to 2018, suggesting that female sex could be omitted as a factor when estimating expected IS rates and the need for OAC therapy in patients with AF.