AI Article Synopsis

  • Understanding the ecological dynamics and carbon storage potential of Atlantic tropical forests in Cameroon is essential for effective management and conservation efforts.
  • The study involved creating 12 permanent plots to analyze plant communities, collect environmental data, and assess carbon stocks by measuring trees with diameters ≥10 cm.
  • Utilizing Multivariate Regression Trees and multiple regression models, researchers identified distinct plant communities and their relations to environmental factors, revealing important insights into tree density, biomass variability, and the distribution of carbon stocks.

Article Abstract

Understanding Atlantic tropical forests' ecological dynamics and carbon storage potential in Cameroon is crucial for guiding sustainable management and conservation strategies. These forests play a significant role in carbon sequestration and biodiversity conservation. This study aimed to fill existing knowledge gaps by characterising plant communities, assessing the vegetation structure, and quantifying the potential of carbon stocks. Twelve 1-ha permanent plots were established within the Atlantic forests of Okoroba and Yingui to achieve these objectives. All the trees with diameters at breast height (DBH) ≥10 cm were inventoried, and various environmental data, including soil texture and climate information, were collected. The Multivariate Regression Trees (MRT) technique was employed to analyse species composition and identify different plant communities (PCs). Additionally, multiple regression models were used to examine the effects of environmental variables and stand size structure on non-destructive carbon stock assessments. The MRT analysis was conducted on 6425 trees spanning 317 species, 212 genera and 60 families, and it identified three distinct PCs with unique species compositions and environmental preferences. The study revealed variations in tree density, ranging from 425 to 645 N ha, and basal area, from 32 to 38 mha among PCs and forest types. Although carbon stocks did not differ significantly between the PCs, they varied in distribution, ranging from 195 to 203 Mg C.ha-. A single-factor model indicated a significant correlation between tree density with DBH ≥50 cm and aboveground biomass variability (R = 0.86). A multi-factor model, considering DBH ranges of 10-30 cm and 30-50 cm, explained 93 % and 94 % of biomass variability, respectively, incorporating elevation and other tree density factors. These findings enhance our understanding of carbon dynamics in Atlantic forests and support conservation and sustainable management practices. They highlight the importance of biodiversity protection in mitigating climate change and maintaining ecosystem health.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11700276PMC
http://dx.doi.org/10.1016/j.heliyon.2024.e41005DOI Listing

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Article Synopsis
  • Understanding the ecological dynamics and carbon storage potential of Atlantic tropical forests in Cameroon is essential for effective management and conservation efforts.
  • The study involved creating 12 permanent plots to analyze plant communities, collect environmental data, and assess carbon stocks by measuring trees with diameters ≥10 cm.
  • Utilizing Multivariate Regression Trees and multiple regression models, researchers identified distinct plant communities and their relations to environmental factors, revealing important insights into tree density, biomass variability, and the distribution of carbon stocks.
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