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Associação Brasileira de Limnologia, Acta Limnologica Brasiliensia, (35), 2023

DOI: 10.1590/s2179-975x5823

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Factors associated with macrophyte beta diversity in Caxiuanã Bay, located in the Eastern Amazon

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Abstract

Abstract Aim In this study, we investigated the beta diversity of macrophytes (total, turnover, and nestedness) in Caxiuanã Bay, localized in the Eastern Amazon. We also investigated the environmental factors determining the beta diversity and its components. Methods Macrophytes and physical-chemical variables (pH, water temperature, electrical conductivity, dissolved oxygen, and water turbidity) were sampled in 45 sites in 2017. Beta diversity was calculated based on Jaccard dissimilarity (using a presence/absence matrix) and partitioned in turnover and nestedness. We performed a Generalized Dissimilarity Modeling to analyze the influence of local (physical-chemical) and spatial factors (geographic distance) on total beta diversity and its components. Results A total of 16 macrophyte species were identified belonging to five morphological groups (free-floating, emergent, submerged, epiphytes, and rooted with floating leaves). The total beta diversity of macrophytes was 0.29, the turnover component had the highest contribution to total beta compared to nestedness. The beta total was influenced by geographic distance and conductivity, turnover by geographic distance and turbidity, and nestedness was explained by conductivity and pH. Conclusions In our study, physical-chemical factors influenced the structure of the macrophyte community, indicating that niche processes (deterministic) were acting and changing species composition. However, the spatial component and the low explanatory power of the models, especially for turnover, can also indicate the influence of stochastic processes such as ecological drift and/or limitations in dispersal. Our study provides new insights into the diversity patterns of macrophytes in Amazonian ecosystems, particularly in blackwater rivers. Our data also contribute to a better understanding of the processes that structure the species composition of macrophytes in these environments.