ArticleEnvironmental management2026
Disaster Risk from Extreme Natural Events Influences Scientific Production on Riparian Forest Carbon More than Socioeconomic Variables.
Article in Environmental management, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
8 authors.
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Abstract
Riparian forests are key ecosystems for mitigating the adverse effects of climate change due to their high potential for carbon sequestration and storage. However, the dynamics of scientific production on carbon in these ecosystems remain poorly understood. This study conducted a bibliometric analysis of publications indexed in the Scopus and Web of Science databases, aiming to identify temporal trends, geographic distribution, collaboration networks, and socioeconomic factors associated with scientific production on the topic. Descriptive statistics, co-authorship network analysis, and a negative binomial regression model were used to assess the influence of variables such as GDP, life expectancy, literacy rate, greenhouse gas (GHG) emissions growth, and disaster risk from natural extreme events on global scientific production. A total of 921 studies were cataloged, with the United States (n = 92), Indonesia (n = 85), and China (n = 82) showing the highest number of studies. The United States led international collaboration. A significant positive effect of disaster risk was observed on the number of publications (β = 0.0524; p < 0.001), indicating that greater exposure to extreme natural events is associated with increased research on riparian forest carbon. GDP also showed a statistically significant association with scientific production, although with a weak effect, reflecting its role as a structural capacity factor rather than a primary driver. Other socioeconomic variables were not statistically significant. Therefore, scientific production appears to be governed by a dual mechanism, combining structural research capacity, represented by GDP, and contextual environmental pressure, represented by disaster risk.
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