Abstract: A group's composition is important for its success. Colonies of the spider Anelosimus studiosus appear to have responded to this pressure by evolving the ability to maintain mixtures of docile versus aggressive individuals that help colonies avoid extinction. Here we demonstrate that colony extinction events unite the optimal group composition of all colony constituents, regardless of phenotype, with that of the colony as a whole. This is because colony extinction events explain the majority of individual mortality events in A. studiosus. Through within- and across-habitat colony manipulations, we further determined that reduction in reproductive output by individuals bearing overabundant phenotypes underlies the ability of colonies to adaptively regulate their compositions. When we experimentally created colonies with an overabundance of the docile or aggressive phenotype, individuals bearing the overabundant phenotype exhibited reduced reproductive output, which helped to move colony compositions back towards their site-specific optima. Colonies displaced from their native sites continued to recreate the patterns of reproductive output that characterized their site of origin, suggesting a genetic component to this trait. Individuals thus appear to adaptively cull their reproductive output depending on their phenotype and the composition of their colony. There is also considerable parent–offspring colony resemblance in the extent to which colonies can or do track their ideal compositions. This conveys a kind of collective heritability to this trait. Together, while group selection appears to be the principal driver of ongoing selection on group composition in A. studiosus, patterns of selection among individuals within groups appear to promote colonies' ability to track their ideal mixtures.
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Bongard's work focuses on understanding the general nature of cognition, regardless of whether it is found in humans, animals or robots. This unique approach focuses on the role that morphology and evolution plays in cognition. Addressing these questions has taken him into the fields of biology, psychology, engineering and computer science.
Danforth is an applied mathematician interested in modeling a variety of physical, biological, and social phenomenon. He has applied principles of chaos theory to improve weather forecasts as a member of the Mathematics and Climate Research Network, and developed a real-time remote sensor of global happiness using messages from Twitter: the Hedonometer. Danforth co-runs the Computational Story Lab with Peter Dodds, and helps run UVM's reading group on complexity.
Laurent studies the interaction of structure and dynamics. His research involves network theory, statistical physics and nonlinear dynamics along with their applications in epidemiology, ecology, biology, and sociology. Recent projects include comparing complex networks of different nature, the coevolution of human behavior and infectious diseases, understanding the role of forest shape in determining stability of tropical forests, as well as the impact of echo chambers in political discussions.
Hines' work broadly focuses on finding ways to make electric energy more reliable, more affordable, with less environmental impact. Particular topics of interest include understanding the mechanisms by which small problems in the power grid become large blackouts, identifying and mitigating the stresses caused by large amounts of electric vehicle charging, and quantifying the impact of high penetrations of wind/solar on electricity systems.
Bagrow's interests include: Complex Networks (community detection, social modeling and human dynamics, statistical phenomena, graph similarity and isomorphism), Statistical Physics (non-equilibrium methods, phase transitions, percolation, interacting particle systems, spin glasses), and Optimization(glassy techniques such as simulated/quantum annealing, (non-gradient) minimization of noisy objective functions).