Hyperdominance and rarity in Amazonian secondary forests
Fernando EliasiD, Joice FerreiraiD, Érika BerengueriD, Rodrigo Oliveira do NascimentoiD, Leonardo MirandaiD, Divino Vicente SilvérioiD, Ima Célia Guimarães VieiraiD, Luiz E. O. C. AragãoiD, Gustavo SchwartziD, Jos BarlowiD
Abstract
Recent studies have shown that a few tree species dominate abundance and carbon storage in undisturbed Amazonian forests. However, this pattern remains poorly understood in forests regrowing after deforestation. Understanding dominance patterns in secondary forests is important as it could improve insights into their functioning and guide management and restoration efforts. We used unweighted and novel plot-weighted approaches to assess hyperdominance in abundance and carbon storage of trees and palms during secondary forest recovery, using data from 102 plots across four regions in the eastern Amazon, separated by an average distance of 600 km (range: 150-1,000 km). Secondary forests show extreme hyperdominance in all approaches, with just 16-25 species ([~]3.6-5.6%) accounting for over 50% of abundance and carbon storage. A small subset of species ([~]9%) were found across all regions and successional stages, highlighting their key role in ecosystem structure and function during forest regrowth. Annona exsucca, Cecropia palmata, Tapirira guianensis, Inga alba, Attalea maripa, Amphiodon effusus, Banara guianensis, and Vismia guianensis consistently emerged as hyperdominant across stem size classes, approaches, and metrics, jointly accounting for roughly 16-27% of total abundance and carbon in Amazonian secondary forests. For larger stems >10cm DBH, hyperdominant species exhibited lower wood density compared to non-hyperdominant species across all successional stages, suggesting these specialist pioneers have distinct ecological strategies from the rest of the community. Our findings indicate that secondary forest functioning can be largely predicted by a relatively limited set of species, providing a framework for future research ranging from ecophysiology to remote sensing of canopy traits and restoration planning.
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