Comparative insights into complex adaptive systems: from cells to societies
Corina E. Tarnita @ Princeton
Abstract:
My research examines the organization and emergent properties of complex adaptive systems at multiple scales, from single cells to entire ecosystems. Central to our approach is the development of general theoretical frameworks. Simultaneously, we use empirical data to identify and catalog patterns in nature and, within the general frameworks, we develop models whose predictions we attempt to empirically test using eco-evolutionary experiments, molecular and genomic analyses, and field manipulations.
My approach is mainly theoretical and combines evolutionary dynamics, evolutionary game theory and elements of network theory but my lab works in collaboration with experimental and field ecologists, molecular biologists and evolutionary biologists to integrate modeling and empirical work. The questions I'm interested in range from multicellularity to social behaviors in bacteria, insects or humans, to the effects of population structure and spatial patterns on evolutionary and ecological dynamics, to mutualistic interactions especially in the context of multi-species networks of symbionts.
Bio:
Corina is a Professor of Ecology and Evolutionary Biology at Princeton University. She joined Princeton in February 2013 after being a Junior Fellow at the Harvard Society of Fellows from 2010 to 2012. She obtained her B.A.('06), M.A.('08) and PhD ('09) in Mathematics from Harvard University. She is an Alfred P. Sloan Research Fellow, a Kavli Frontiers of Science Fellow of the National Academy of Sciences, and an Early Career Fellow of the Ecological Society of America. Her work is centered around the emergence of complex behavior out of simple interactions, across spatial and temporal scales.
Focus: complexity of living organisms and life overall
Evolutionary substrate: Biochemistry, Biology, Culture, Technology
Major transitions in evolution: RNA, DNA, Cells, Brains
Looking at hierarchical major transitions: smaller units grouping into larger units, which become a new dominant unit of organization
Start: small groups of larger individuals
Enabled by some change in small groups that allowed them to persist or displace their smaller ancestor
E.g. multi-cellular organisms arising from single-celled, ant colonies arising from more independent individuals
Base Model
We have a set of individuals who are stressed
They need to coordinate to survive
Need mechanism to control/eliminate free-riders
The evolution of Eusociality: social organization observed in ants/wasps/bees
Why do ant workers support other ants and rear their queen’s children?
This is a very successful strategy as ants are extremely numerous
But this strategy is not common across species
If it is so effective, why not?
Ideas
Kin selection: help closer relatives more than further relatives
Worker ants pass their genes on via their mother
But they’re not that related to the males
Why would they sacrifice reproduction?
Another idea: if a mother was able to make some daughters stay behind to help, would that be favored by natural selection?
Option 1: Mother leaves eggs and they develop on their own
Option 2: Mutation that causes some daughters to stay at the nest (may or may not reproduce)
Assumptions on costs and benefits of sociality: reproductive rate and expected lifetime
Social mother is less fit when she’s on her own (because it needs to maintain eggs on her own)
Fitness rises with size of colony
Eusociality is bad if:
Too few staying daughters (not useful)
Too many staying daughters (colony doesn’t spread)
Favored by natural selection in middle range of colony migration probability
Critically, eusociality can evolve only if benefits kick in at VERY small group sizes
Experiment on real colonies of ants
Ooceraea biroi
Queen-less
All ants lay eggs, then all become workers to take care of the eggs
Reproduce asexually (everyone is clones)
Genetics of individuals are very tightly controlled
Size of colony can be controlled by number of larvae
Goal: understand how group size affects group dynamics
Result: colony of size 6 individual has same growth as larger-size colonies
Dynamics: there was a rudimentary division of labor
When there are <=4 ants, each ant does all tasks and keeps switching
When there are >=6 ants each ant does more of a single job
Each ant has a probability distribution of its task that becomes much more concentrated on one task
Distributions of different ants concentrate on different tasks
How do they decide on their jobs?
Individuals are not genetically identical and are more sensitive to different stimuli (larvae asking for help, trash piling up, etc.)
For ants transcriptomics and neuroanatomy affect sensitivity of different odorant receptors
Evolutionary studies show that basic genes that affect multi-cellularity evolved before animals and fungi evolved
Division of labor ensures that tasks don’t get neglected (each task gets more dedicated attention) and so eggs develop faster
Modeling studies that simulated larger group sizes show that this mechanism doesn’t improve growth beyond 20.
But, now we have small groups running around. What if they evolve the ability to sense each other?
Add interaction bias: individuals who specialized in the same task tend to stay together and focus more on a common task
Models of this mechanism show that division of labor increases dramatically
Observation: the above mechanisms have been proposed for driving political polarization