Biology subjects

Francisco, F. A.

Publications and source records attributed to Francisco, F. A..

5 recordsLinked to original sources

bioRxiv2025

Synchronization of the collective air-breathing behavior in juvenile Arapaima gigas

Animal collectives are capable of performing behaviors with high degrees of synchrony though their members might differ consistently and substantially in the focal behavior when alone. It is thus not entirely understood how these consistent differences in behavior at the individual level can be (socially) integrated into synchronized behaviors at the collective level. Here we show an unprecedented synchronized behavior in fish - the collective air-breathing of juvenile Arapaima gigas. Individuals of this obligate air-breathing fish from South America differed in their time between consecutive breaths when recorded alone in an aquaculture facility. However, when together in a shoal of about 200 same aged individuals, breathing is executed by a substantial portion of the shoal - within the same second. Our analysis of the individual and collective breathing patterns supported by stochastic individual-based simulations of inherently non-periodic coupled oscillators revealed that this degree of collective synchronization could be achieved by having some kind of assortative interaction rules where individuals respond towards one cluster/subgroup members stronger than to other cluster/subgroup members. By integrating this cluster synchrony rule we could successfully simulate highly synchronized collective behavior with varying proportions of otherwise diverse individuals taking part, matching our experimental observations and providing a mechanism to synchronize agents that differ consistently in the behavior in focus when in isolation.

animal behavior and cognition↗

bioRxiv2025

A tale of two birds: cognitive simplicity drives collective route improvements in homing pigeons

Cognitive abilities are central to how animals navigate complex environments. Beyond individual cognition, group living can also enhance navigation by pooling individually acquired information. One way this may be achieved is by following experienced leaders, which requires recognizing expertise within group members. Alternatively, accurate decisions could also emerge without expert opinions, through simpler mechanisms like the wisdom of crowds principle that average out individual biases. Consequently, collective navigation strategies range from cognitively complex to simple, and yet, the prevalence or interplay of different collective strategies in nature remains unexplored. In this study, we asked: what is the navigation mechanism, requiring minimal cognitive demands, that is necessary and sufficient to quantitatively replicate the experimental results of a 2017 study on homing pigeons (Columba livia), which showed that sequential chains of bird pairs flying home -- similar to a game of telephone -- led to shorter homing routes compared to control birds flying individually or in fixed pairs. Our results show that the experimental data aligns closely with the simplest strategy -- route averaging. Surprisingly, the complex mechanism of selectively propagating the best flight through social learning offered no additional advantage. We further observed that mixed strategies, although not supported by the experimental data, in theory combined advantages from both averaging and active selection of better routes, resulting in even greater performance. Hence, our results highlight the potential for future research to investigate selective pressures shaping the evolution of cultural learning and trade-offs among different decision mechanisms theoretically available to social animals in nature.

animal behavior and cognition↗

bioRxiv2022

Experienced social partners hinder learning performance in naive clonal fish

Social learning is widely assumed to enhance individual learning efficiency, particularly when naive observers have access to skilled demonstrators, yet the conditions under which this assumption holds remain poorly understood. Here, we investigated how individual learning is influenced by the skill level of social partners. We predicted that naive individuals would benefit from observing experienced conspecifics, yet found the opposite: trained partners significantly impaired naive individuals learning performance, while trained individuals remained unaffected by their partners skill level. We conducted experiments in near-identical individuals, using the all-female clonal Amazon molly (Poecilia formosa) to test whether these fish can learn an operant foraging task, whether individuals differ consistently in learning ability, and whether partner skill level influences learning performance. Using an operant conditioning paradigm over five days, half of the fish were trained to locate food inside a cylinder, whereas the remaining individuals received food randomly dispersed within their tank. Trained individuals subsequently visited the cylinder more frequently than randomly fed individuals and exhibited consistent individual differences in learning performance. In a second phase, fish were allowed to observe a conspecific while individual training was either continued (for trained individuals) or initiated (for naive individuals). We found that trained individuals did not benefit from the presence of a partner, regardless of the partners proficiency, but consistently outperformed naive individuals. In contrast, naive individuals showed reduced learning performance when paired with experienced partners, but not with naive partners. Together, our results indicate that Amazon mollies achieve this foraging task through individual learning and exhibit stable differences in learning ability. Moreover, social learning depends on both the learners own skill level and that of the social partner, such that observing an experienced conspecific may, in some cases, impede rather than enhance learning.

animal behavior and cognition↗

bioRxiv2022

Discovery of a new but established population of the guppy in Germany

Feral populations of tropical fish species in temperate climates like Central Europe are a rare but repeatedly observed phenomenon. Due to the influence of industrial or geothermal heated water, released tropical fish may be able to survive harsh winter conditions. Here we characterize a newly discovered thermally polluted river, with an established population of the guppy (Poecilia reticulata) co-occurring with native species. Through a mark-recapture approach, we estimated the population size of the guppies close to the warm water inflow to be around 2000 individuals during summer and we further provide descriptive demographics of this population which allow us to assume it is well established in that river. Further, we found some of the sampled specimen being parasitized by Camallanus roundworms, thus showing the guppies host potential for this genus of internal parasites. The popularity and widespread distribution of guppies as ornamental fish often leads to their intentional or unintentional release into the wild where they are often pioneer species in anthropogenically heavily modified habitats. Guppies threaten native species through niche competition and transmission of diseases. Accordingly, early awareness and knowledge on the status of non-native populations is crucial for effective management strategies.

ecology↗

bioRxiv2019

A low-cost, open-source framework for tracking and behavioural analysis of animals in aquatic ecosystems

Although methods for tracking animals underwater exist, they frequently involve costly infrastructure investment, or capture and manipulation of animals to affix or implant tags. These practical concerns limit the taxonomic coverage of aquatic movement ecology studies and implementation in areas where high infrastructure investment is impossible. Here we present a method based on deep-learning and structure-from-motion, with which we can accurately determine the 3D location of animals, the structure of the environment in which they are moving. Further behavioural decomposition of the body position and contour of animals subsequently allow quantifying the behavioural states of each interacting animal. This approach can be used with minimal infrastructure and without confining animals to to a fixed area, or capturing and interfering with them in any way. With this approach, we are able to track single individuals (Conger Eel, Conger oceanus), small heterospecific groups (Mullus surmuletus, Diplodus sp.), and schools of animals (Tanganyikan cichlids Lamprologus callipterus) in freshwater and marine systems, and in habitats ranging in environmental complexity. Positional information was highly accurate, with errors as low as 1.67% of body length. Tracking data was embedded in 3D environmental models that could be used to examine collective decision making, obstacle avoidance, and visual connectivity of groups. By analyzing body contour and position, we were also able to use unsupervised classification to quantify the kinematic behavioural states of each animal. The proposed framework allows us to understand animal behaviour in aquatic systems at an unprecedented resolution and a fraction of the cost of established methodologies, with minimal domain expertise at the data acquisition or analysis phase required. Implementing this method, research can be conducted in a wide range of field contexts to collect laboratory standard data, vastly expanding both the taxonomic and environmental coverage of quantitative animal movement analysis with a low-cost, open-source solution.

animal behavior and cognition↗