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A. Dejean, F. Azemar, R. Cereghino, M. Leponce, B. Corbara, J. Orivel, and A. Compin (2015)

The dynamics of ant mosaics in tropical rainforests characterized using the Self-Organizing Map algorithm

Insect Sci, . doi:10.1111/1744-7917.12208.

Ants, the most abundant taxa among canopy-dwelling animals in tropical rainforests, are mostly represented by territorially-dominant arboreal ants (TDAs) whose territories are distributed in a mosaic pattern (arboreal ant mosaics). Large TDA colonies regulate insect herbivores, with implications for forestry and agronomy. What generates these mosaics in vegetal formations, which are dynamic, still needs to be better understood. So, from empirical research based on three Cameroonian tree species (Lophira alata, Ochnaceae; Anthocleista vogelii, Gentianaceae; and Barteria fistulosa, Passifloraceae), we used the Self-Organizing Map (SOM, neural network) to illustrate the succession of TDAs as their host trees grow and age. The SOM separated the trees by species and by size for L. alata, which can reach 60 m in height and live several centuries. An ontogenic succession of TDAs from sapling to mature trees is shown, and some ecological traits are highlighted for certain TDAs. Also, because the SOM permits the analysis of data with many zeroes with no effect of outliers on the overall scatterplot distributions, we obtained ecological information on rare species. Finally, the SOM permitted us to show that functional groups cannot be selected at the genus level as congeneric species can have very different ecological niches, something particularly true for Crematogaster spp. which include a species specifically associated with B. fistulosa, non-dominant species and TDAs. Therefore, the SOM permitted the complex relationships between TDAs and their growing host trees to be analyzed, while also providing new information on the ecological traits of the ant species involved. This article is protected by copyright. All rights reserved.

Peer Review, International Redaction Board, Impact Factor
  • DOI: 10.1111/1744-7917.12208
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