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Consistent individual differences in behavior, known as behavioral individuality, are pervasive across the animal world and have major ecological and evolutionary consequences. Nevertheless, we still have a limited understanding of what drives individuality and how it emerges during ontogeny. Here, we subjected clonal individuals to a ubiquitous yet critical environmental challenge—the threat of predation—to disentangle the developmental mechanisms of individuality. Under such a salient environmental stressor, among-individual differences may collapse or expand depending on whether there is a single or multiple optimal strategies, demonstrating that individuality itself is a developmentally plastic trait. If, however, the environment does not impact among-individual variation, this suggests that individuality is determined before birth. We continuously tracked the behavior of genetically identical fish (Amazon mollies, Poecilia formosa), reared with or without predation stress, from birth through their first month of life. Predation shifted mean-level behaviors, with predator-exposed individuals swimming more slowly and spending more time near their refuges. However, the magnitude of individuality (as evidenced by repeatability) increased similarly over development in both treatments, indicating that individuality crystallizes robustly over time, even under stress and in a vacuum of genetic variation. Predator-reared fish also exhibited greater within-individual variability in refuge use, suggesting increased behavioral flexibility or disrupted developmental canalization in response to stress. Surprisingly, maternal identity, but not maternal behavior, was the strongest predictor of swimming speed, pointing to non-behavioral maternal effects as a key pre-birth source of behavioral variation. Refuge use however was not at all predicted by maternal identity, indicating that major fitness-related behaviors can have entirely different developmental mechanisms. Collectively, we show that individuality persists despite environmental stress and is seeded before birth through non-genetic factors. Even in the face of a shared environmental challenge, the behavioral trajectories of individuals are unique.
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A framework for studying behavioral evolution by reconstructing ancestral repertoires
Although different animal species often exhibit extensive variation in many behaviors, typically scientists examine one or a small number of behaviors in any single study. Here, we propose a new framework to simultaneously study the evolution of many behaviors. We measured the behavioral repertoire of individuals from six species of fruit flies using unsupervised techniques and identified all stereotyped movements exhibited by each species. We then fit a Generalized Linear Mixed Model to estimate the intra- and inter-species behavioral covariances, and, by using the known phylogenetic relationships among species, we estimated the (unobserved) behaviors exhibited by ancestral species. We found that much of intra-specific behavioral variation has a similar covariance structure to previously described long-time scale variation in an individual’s behavior, suggesting that much of the measured variation between individuals of a single species in our assay reflects differences in the status of neural networks, rather than genetic or developmental differences between individuals. We then propose a method to identify groups of behaviors that appear to have evolved in a correlated manner, illustrating how sets of behaviors, rather than individual behaviors, likely evolved. Our approach provides a new framework for identifying co-evolving behaviors and may provide new opportunities to study the mechanistic basis of behavioral evolution.
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- Award ID(s):
- 1806833
- PAR ID:
- 10559761
- Publisher / Repository:
- Elife
- Date Published:
- Journal Name:
- Evolutionary BiologyPhysics of Living Systems
- Volume:
- 10
- ISSN:
- 2050-084X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.7554/eLife.61806
