Revista de Biología Tropical ISSN Impreso: 0034-7744 ISSN electrónico: 2215-2075

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Correlation Abundance Networks for analyzing biological interactions during cyanobacterial blooms
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Keywords

cyanobacterial blooms; abundance correlations; networks, monitoring
floraciones de cianobacterias; correlaciones de abundancia; monitoreo con redes

How to Cite

Lozano, V. L., Alvarez Dalinger, F. S., Borja, C., & Moraña, L. (2024). Correlation Abundance Networks for analyzing biological interactions during cyanobacterial blooms. Revista De Biología Tropical, 72(1), e56487. https://doi.org/10.15517/rev.biol.trop.v72i1.56487

Abstract

Introduction: Cyanobacterial blooms are becoming increasingly common, and understanding their dynamics can be crucial for proposing appropriate management strategies. While the physical and chemical parameters influence on blooms have been extensively studied, less attention has been put on the susceptibility of the biological communities. Objective: The purpose of this study was to analyze the phytoplankton abundance networks during blooms at different levels of intensity and how bloom-forming cyanobacteria interact with and/or impact phytoplankton community. Methods: We used 22 samplings conducted in the same reservoir located in northern Argentina, which is known for recurrent cyanobacterial blooms. Each sampling was classified into four levels based on the abundance of cyanobacteria. For each level, abundances correlation networks were constructed considering all species. Results: A pattern of decreasing statistically significant abundance correlations was observed as the intensity of the blooms increased: 219 correlations at level 1; 144 at level 2; 80 at level 3, and only 33 at level 4. Bloom-forming cyanobacteria showed to be little correlated with others species in all the levels, which could be associated to certain independence with the community. Increased bloom seems to disconnect the phytoplanktonic correlation abundances network. Conclusion: Analyzing correlation abundances networks should be a valuable tool for understanding the dynamics and development of cyanobacterial blooms, as well as identifying key species in this process.

https://doi.org/10.15517/rev.biol.trop..v72i1.56487
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