Composition and structure of the mixed-species flocks along the latitudinal gradient of the subtropical montane forest of the yungas, Argentina

Composition and structure of the mixed-species flocks along the latitudinal gradient of the subtropical montane forest of the yungas, Argentina

FANJUL, María E.
Instituto Vertebrados, Ornitología, Fundación Miguel Lillo y Facultad de Ciencias Naturales e IML – UNT, Argentina
mefanjul@lillo.org.ar
Mixed-species flocks (MF) are associations of different species formed as a strategy to increase the efficiency of foraging and to reduce the risk of predation. The participant species play different roles and receive various benefits from the association. The aim of the present study was to determine the variation of the composition and structure of the MF, along a latitudinal gradient in the subtropical mountain forest of the Yungas of Argentina. Eight sampling sites were studied along the 700 km of distribution of the Yungas in Argentina. At each site 10 transects were established and were visited from June to September between 2006 and 2009. It was determined the richness and abundance of the MF. 325 MF, with a total of 72 participating species and an abundance of 2480 individuals were observed. Seventeen families were represented, 15 of the order Passeriformes and two non-passerines (Trochilidae and Picidae). The major families were Tyrannidae (12 species), Furnariidae (10 species) and Thraupidae (eight species). Twelve species were omnipresent in the eight study sites, being Syndactyla rufosuperciliata, Phylloscartes ventralis, Chlorospingus flavopectus and Myioborus brunniceps the species that had the highest values of occurrence. Although multivariate statistical analyzes indicated that the latitudinal gradient would have no direct influence on the structural characteristics (number of flocks, number of species and individuals involved) of the MF, the composition of the species varied in association with latitude. Possible causes associated with the latitudinal gradient, such as local climate and vegetation characteristics, could influence the results obtained.

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