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Borges, M. E.

Publications and source records attributed to Borges, M. E..

2 recordsLinked to original sources

Consumers' active choice behavior promotes coevolutionary units

Individual behavior and local context are processes that can influence the structure and evolution of ecological interactions. In trophic interactions, consumers can increase their fitness by actively choosing resources that enhance their chances of exploring them successfully. Upon searching for potential resources, they are able to decide which one to choose according to their fitness benefit and maneuverability. Mathematical modeling is often employed in theoretical studies to understand the coevolutionary dynamics between these species. However, they often disregard the individual consumer behavior since the complexity of these systems usually requires simplifying assumptions about interaction details. Using an individual-based model, we model a community of several species that interact antagonistically. The trait of each individual is modeled explicitly and is subjected to the interaction pressure. In addition, consumers can actively choose the resources that guarantee greater fitness. We show that active consumer choice can generate coevolutionary units over time. It means that the traits of both consumers and resources converge into multiple groups with similar traits, exerting reciprocal selective pressure between them. We also observed that network structure has a greater dependence on the parameter that delimits active consumer choice than on the intensity of selective pressure. Consequently, this parameter can closely match empirical networks. Thus, we consider that the inclusion of consumers active choice behavior in the models plays an important role in the ecological and evolutionary processes that structure these communities.

ecology

Worker-behavior and behavior-behavior interaction networks in the trap-jaw ant Odontomachus chelifer (Latreille, 1802)

Division of labor is among the main factors to explain the evolutionary success of social systems, from the origins of multicellularity to complex animal societies. The remarkable ecological success of social insects seems to have been largely driven by ergonomic advantages stemming from the behavioral specialization of workers. However, little is known about how individuals and their corresponding behavioral repertoires are related to each other within a division of labor context, particularly by viewing such relationships as complex networks. Applications of network theory to the study of social insects are almost exclusively used to analyze behavioral interactions between individuals, rather than to the study of relations among individuals and behaviors. Here, we use an approach to the study of the organization of the behavioral repertoire of ant colonies that considers both individual-behavior interactions and behavior-behavior interactions, besides colony time budgets. Our study investigates the organization of division of labor in colonies of the trap-jaw ant Odontomachus chelifer (LO_SCPLOWATREILLEC_SCPLOW, 1802). All the behavioral acts (including inactivity) performed within three queenright colonies of different sizes (n = 7, 30, and 60 workers) were studied under controlled laboratory conditions. Each ant was individually marked and observed by scan sampling in 10 min intervals for 10 h each (n = 5,919 behavioral acts). We describe the network topologies in terms of centrality, specialization, modularity, and nestedness. This study shows that workers of O. chelifer are organized according to structured networks, composed of individuals exhibiting varying degrees of specialization. The observed centrality scores indicate that some behaviors could have a disproportionately larger impact on the network organization (especially self-grooming). The results underscore the potential of the use of complex networks (particularly measures of modularity and nestedness) in order to discover and study novel organizational patterns of social groups in animal behavior.

animal behavior and cognition