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Species traits and abundance influence the organization of liana–tree antagonistic interaction
Author(s) -
Sfair Julia C.,
Weiser Veridiana de L.,
Martins Fernando R.,
Vidal Mariana M.,
Guimarães Paulo R.
Publication year - 2018
Publication title -
austral ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.688
H-Index - 87
eISSN - 1442-9993
pISSN - 1442-9985
DOI - 10.1111/aec.12560
Subject(s) - liana , biology , abundance (ecology) , nestedness , ecology , relative species abundance , trait , species richness , computer science , programming language
The interaction among species can be influenced by neutral processes, in which more abundant species have high effect on the structure of interaction, or can be influenced by trait matching. Despite both variables (abundance and species traits) influencing the interaction of species in mutualistic networks, few studies showed their importance in antagonistic networks. Here, we posed the question: what are the main predictors of the liana–tree interactions: species abundance, biological traits or both? In a savanna woodland fragment in south‐eastern Brazil, we sampled lianas and trees in 1 ha, where we recorded the abundance, maximum height and bark roughness of tree species, as well as abundance, maximum diameter and climbing system of liana species. For each species, we calculated their contribution to nestedness ( n i ), which is a measure of network structure, and performed simple linear regressions between n i and abundance and species traits. Abundant species contribute more to n i than rare species, indicating that neutral processes affect interactions between lianas and trees, probably because lianas are opportunistic and climb trees in their neighbourhood. The only trait related to n i was tree height, which can indicate that light availability can have a considerable role on network structure between both growth forms. Therefore, the importance of species abundance and tree height can be related to opportunism of lianas on climbing the most suitable tree in their neighbourhood.