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Tropical forests are well-known as highly productive terrestrial ecosystems, which contribute significantly to the global carbon (C) cycle. Studies indicate a correlation between the structural diversity of forests and carbon stocks in the overall forest carbon stocks, and this relationship varies across tropical ecosystems. Understanding this connection is crucial to preventing the transfer of threats to unprotected areas when safeguarding specific forests. The present study was conducted in the undisturbed natural forests of Rema Kalenga Wildlife Sanctuary, Habigonj, Bangladesh. The study aimed to estimate C stocks within the soil-vegetation system of this forest ecosystem and elucidate relationships with stand structural diversity, focusing on vertical stratification and spatial association of tree species. Stand-level C stock models, constructed through tree-level carbon stocks using allometric equations, were based on stand variables such as basal area and mean or dominant tree height. Results identified five canopy strata, with strata two and three accounting for 60% of C stocks. The importance value index of tree species demonstrated a significant association with the C stocks contribution of tree species. The total ecosystem carbon stock ranged from 185 to 220 Mg ha−1, with aboveground 103 to 132 Mg ha−1, belowground 21 to 26 Mg ha−1, litter 2.4 to 4.4 Mg ha−1, dead wood 0.5 to 4.9 Mg ha−1 and soil 11 to 44 Mg ha−1. Species diversity indices exhibited weaker relationships with C stocks, while Pielou's evenness index demonstrated a strong negative relationship (P < 0.05) to C stocks. This comprehensive assessment provides insights into the C dynamics of the forest ecosystem. It offers valuable information for policymakers devising climate change mitigation strategies through the conservation management of tropical forests as crucial C sinks.

Background: This study examined the association between media exposure and mental health during the second wave of lockdown among the general population of Bangladesh. Methods: A total of 449 adult participants were enrolled in the study to evaluate their levels of exposure to total media, electronic media, and social media. Mental health was assessed using a 7-item generalized anxiety disorder (GAD-7) scale. A multivariate logistic regression model was constructed to explore the relationships between media exposure levels and anxiety. The models included covariates such as sex, daily working hours, health problems, media distraction, and income from social media. Results: The results showed that 44.5%, 39.2%, and 16.3% of participants reported low, medium, and high levels of exposure to different media during the COVID-19 period, respectively. Additionally, 96.4%, 2.7%, and 0.9% of participants had low, medium, and high levels of exposure to electronic media, respectively, and 89.1%, 10.5%, and 0.4% of participants had low, medium, and high levels of exposure to social media, respectively. The overall prevalence of anxiety was 25.38% among the respondents. Participants with high levels of total media exposure were significantly more likely to experience anxiety, with an odds ratio of 2.75 (95% CI = 1.40–5.14, p