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Get Free AccessThe relationship between biodiversity and ecosystem function is crucial for understanding the structure and processes of subtropical forest ecosystems. However, the extent to which biodiversity influences subtropical forest biomass remains unclear. This study applies Bayesian causal inference to explore causal relationships between forest Aboveground Biomass (AGB) and its potential driving factors (biodiversity factors, biotic factors and abiotic factors) based on Huangshan Forest Dynamics Plots. Furthermore, hypothetical interventions are introduced to these driving factors within the causal network to estimate their potential impact on AGB. The causal relationship network reveals that species diversity and functional diversity are the most direct factors influencing AGB, whereas phylogenetic diversity exerts only an indirect effect. Biotic and abiotic factors also contribute indirect effects on AGB, potentially by influencing other mediating indexes. Intervention analysis shows that with low-level interventions on direct influencing factors, the probability of low AGB is as high as 84%. As the intervention level increases to high, the probability of low AGB decreases by 36%. Moreover, AGB demonstrates a particularly sensitive response to changes in Rao’s quadratic entropy (RaoQ) intervention levels, more so than to other factors, highlighting its critical role in maintaining forest biomass. Therefore, we contend that functional diversity, due to its direct reflection of species’ roles in ecosystem processes, is a more accurate measure of the impact of biodiversity on biomass compared to species or phylogenetic diversity and the interplay between abiotic and biotic factors and biodiversity should not be overlooked. This approach offers a powerful tool for exploring causal relationships, thereby providing a more nuanced and accurate understanding of the relationship between biodiversity and forest ecosystem function.
Yubo Tao, Yutong Xia, Xiao Zheng, Hui Ding, Yanming Fang, Chenlei Tian, Pei Ma (2024). Application of Bayesian Causal Inference in the Study of the Relationship Between Biodiversity and Aboveground Biomass of Subtropical Forest in Eastern China. , 15(11), DOI: https://doi.org/10.3390/f15111841.
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Type
Article
Year
2024
Authors
7
Datasets
0
Total Files
0
Language
en
DOI
https://doi.org/10.3390/f15111841
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