arXiv subjects

Gabriel Ramos-Fernández

Publications and source records attributed to Gabriel Ramos-Fernández.

5 recordsLinked to original sources

arXiv2024

Strength of minority ties: the role of homophily and group composition in a weighted social network

Homophily describes a fundamental tie-formation mechanism in social networks in which connections between similar nodes occur at a higher rate than among dissimilar ones. In this article, we present an extension of the Weighted Social Network (WSN) model that, under an explicit homophily principle, quantifies the emergence of attribute-dependent properties of a social system. To test our model, we make use of empirical association data of a group of free-ranging spider monkeys in Yucatan, Mexico. Our homophilic WSN model reproduces many of the properties of the empirical association network with statistical significance, specifically, the average weight of sex-dependent interactions (female-female, female-male, male-male), the weight distribution function, as well as many weighted macro properties (node strength, weighted clustering, and weighted number of modules), even for different age group combinations (adults, subadults, and juveniles). Furthermore, by performing simulations with fitted parameters, we show that one of the main features of a spider monkey social system, namely, stronger male-male interactions over female-female or female-male ones, can be accounted for by an asymmetry in the node-type composition of a bipartisan network, independently of group size. The reinforcement of connections among members of minority groups could be a general structuring mechanism in homophilic social networks.

physics.soc-ph↗

arXiv2019

Collective learning from individual experiences and information transfer during group foraging

Living in groups brings benefits to many animals, such as a protection against predators and an improved capacity for sensing and making decisions while searching for resources in uncertain environments. A body of studies has shown how collective behaviors within animal groups on the move can be useful for pooling information about the current state of the environment. The effects of interactions on collective motion have been mostly studied in models of agents with no memory. Thus, whether coordinated behaviors can emerge from individuals with memory and different foraging experiences is still poorly understood. By means of an agent based model, we quantify how individual memory and information fluxes can contribute to improving the foraging success of a group in complex environments. In this context, we define collective learning as a coordinated change of behavior within a group resulting from individual experiences and information transfer. We show that an initially scattered population of foragers visiting dispersed resources can gradually achieve cohesion and become selectively localized in space around the most salient resource sites. Coordination is lost when memory or information transfer among individuals is suppressed. The present modelling framework provides predictions for empirical studies of collective learning and could also find applications in swarm robotics and motivate new search algorithms based on reinforcement.

q-bio.PE↗

arXiv2008

Evidence for biological Lévy flights stands

Edwards et al. [Nature 449, 1044-1048 (2007)] revisited well-known studies reporting power-laws in the frequency distribution of flight duration of wandering albatrosses, and concluded that no Lévy process could model recent observations with higher resolution. Here we show that this re-analysis suffers from a conceptual misunderstanding, and that the new albatross data remain consistent with a biological Lévy flight.

q-bio.PE↗

arXiv2006

A complex social structure with fission-fusion properties can emerge from a simple foraging model

Precisely how ecological factors influence animal social structure is far from clear. We explore this question using an agent-based model inspired by the fission-fusion society of Spider monkeys (Ateles spp). Our model introduces a realistic, complex foraging environment composed of many resource patches with size varying according to an inverse power-law frequency distribution with exponent $β$. Foragers do not interact among them and start from random initial locations. They have either a complete or partial knowledge of the environment and maximize the ratio between the size of the next visited patch and the distance traveled to it, ignoring previously visited patches. At intermediate values of $β$, when large patches are neither too scarce nor too abundant, foragers form groups (coincide at the same patch) with a similar size frequency distribution as the spider monkey's subgroups. Fission-fusion events create a network of associations that contains weak bonds among foragers that meet only rarely and strong bonds among those that repeat associations more frequently than would be expected by chance. The latter form sub-networks with the highest number of bonds and a high clustering coefficient at intermediate values of $β$. The weak bonds enable the whole social network to percolate. Some of our results are similar to those found in long-term field studies of spider monkeys and other fission-fusion species. We conclude that hypotheses about the ecological causes of fission-fusion and the origin of complex social structures should consider the heterogeneity and complexity of the environment in which social animals live.

q-bio.PE↗

arXiv2006

Scale-free foraging by primates emerges from their interaction with a complex environment

Scale-free foraging patterns are widespread among animals. These may be the outcome of an optimal searching strategy to find scarce randomly distributed resources, but a less explored alternative is that this behaviour may result from the interaction of foraging animals with a particular distribution of resources. We introduce a simple foraging model where individuals follow mental maps and choose their displacements according to a maximum efficiency criterion, in a spatially disordered environment containing many trees with a heterogeneous size distribution. We show that a particular tree size frequency distribution induces non-Gaussian movement patterns with multiple spatial scales (Lévy walks). These results are consistent with tree size variation and Spider monkey (Ateles geoffroyi) foraging patterns. We discuss the consequences that our results may have for the patterns of seed dispersal by foraging primates.

q-bio.PE↗