1. The dilemma of binary or weighted data in interaction networks.
- Author
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Miranda, Patrícia Nakayama, Ribeiro, José Eduardo Lahoz da Silva, Luna, Pedro, Brasil, Izaias, Delabie, Jacques Hubert Charles, and Dáttilo, Wesley
- Subjects
CHEMICAL plants ,PLANT capacity ,KNOWLEDGE gap theory ,FORAGE plants ,PLANT species ,DILEMMA ,NECTARIES - Abstract
• Binary or weighted data brought out different patterns of ant-plant organization networks. • Node centrality did not differ among different types of weighted networks. • Our findings expand the discussion about data categories in network studies. Despite the increasing number of studies dealing with interaction networks in the last few years, there is still a lack of knowledge about how their structural organization are affected by changes in binary or weighted data. To fill this gap, we collected ants foraging on plants with extrafloral nectaries in 10 sites within the Brazilian Amazon to evaluate if the generality, vulnerability, nestedness, and modularity observed in these ant-plant networks could be affected by changes in data categories. Specifically, we used three matrices built by different data categories: (i) binary data (i.e., presence or absence of an interaction between a plant and an ant species); (ii) frequency data (i.e., number of times in which a plant species interacted with an ant species); and (iii) abundance data (i.e., number of workers of an ant species recorded foraging on a plant species). In general, when analyzing different matrix categories, we observed changes in the structural organization of the studied ant-plant interaction networks. Surprisingly, however, at the species level, both categories of weighted data (i.e., frequency and abundance data) seem to be equally appropriate for describing the role of ant species. Our results highlight the need to expand the discussion about data categories in ecological interaction studies to understand how different data categories may lead to different ecological interpretations. [ABSTRACT FROM AUTHOR]
- Published
- 2019
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