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Irreversible Processes in Ecological Evolution/DervisCanVural

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Notes by user Dervis Can Vural (Univ. Notre Dame) for Irreversible Processes in Ecological Evolution

Post-meeting Reflection

1+ paragraphs on any combination of the following:

  • Presentation highlights
  • Open questions that came up
  • How your perspective changed
  • Impact on your own work
  • e.g. the discussion on [A] that we are having reminds me of [B] conference/[C] initiative/[D] funding call-for-proposal/[E] research group

Otto Cordero:

Succession of species on hydrogel microspheres. Otto uses spheres with four kinds of nutrition. (1) why are species either specialist (able to digest only one type of sphere) or generalist (able to digest all types). (2) Why don't the cheaters (those who do not produce digestive enzymes) take over. (3) Prima facie, I would expect cheaters to have much lower detachment rate. They should just stick onto spheres and wait for the digestive bacteria to arrive. For the bacteria doing the work a better strategy is to detach quicker, at least before cheaters arrive. Is this observed in experiments? (4) is the interaction between bacteria indirect (i.e. they compete for the same resource) or do they secrete antibiotics or consume one other? (5) what is the role of diffusion lengths? The commensalist bacteria (those who do not secrete enzymes, do not compete for the main resource, but utilize the metabolic byproducts of others) gather whatever they can within diffusion length. So we can calculate the limit the number of layers of bacteria on a surface. For resources (e.g. dead crab shells) that are smaller than the diffusion length, the shape and size of the resource will also make a difference. Also calculable.

Pamela Martinez:

Markov process to describe the spread of pathogen with multiple serotypes (a kind of SIR model). How to differentiate between different models with sparse data. Data could be equally consistent with randomly connected states or even a single Poisson process with appropriate mean. A good suggestion during the talk: generate synthetic sparse data using the model, pretend the data is real, and estimate model parameters. Do they have a similar value? (1) why does the efficacy of vaccines not show up in the population data (they do make a significant difference in controlled studies). (2) why does the vaccine work on some countries but not the others (3) Rotavirus somehow interacts with the gut microbiome. There is some literature that shows that vaccines work for people with microbiomes of the "european kind".

Annette Ostling

Starts with Lotka-Volterra type fitness function. Species are assigned traits between 0-1 and and the interaction matrix is structured such that species with similar traits antagonize each other. This is done with a gaussian kernel in the sum. Questions: (1) what determines the number of clusters. Can I use Turing analysis to solve this analytically? (2) Can I view phylogenetic branches as "clusters"? e.g. animal kingdom, plant kingdom etc. are, in some sense, clusters. And then, there are sub-clusters within these clusters, and sub-sub clusters. What feature should be added to the model to obtain sub-clusters. (3) Given an empirical distribution of features (within a species or within multiple species supposedly filling a niche) how do I distinguish between environmental filtering vs exclusion?

Priyanga Amarasekare: Her argument is, species respond to temperature in an "asymmetric way" (specifically, you hit a wall at high temperatures, but the negative response to cold is more gradual). This leads to an irreversible flow of species (via mutant invasions) from hot regions to cold ones.

Reference material notes

Some examples:

  • Here is [A] database on [B] that I pull data from to do [C] analysis that might be of interest to this group (insert link).
  • Here is a free tool for calculating [ABC] (insert link)
  • This painting/sculpture/forms of artwork is emblematic to our discussion on [X]!
  • Schwartz et al. 2017 offers a review on [ABC] migration as relate to climatic factors (add the reference as well).

Reference Materials

Title Author name Source name Year Citation count From Scopus. Refreshed every 5 days. Page views Related file
The organization and control of an evolving interdependent population Dervis C. Vural, Alexander Isakov, L. Mahadevan Journal of the Royal Society Interface 2015 3 1
Shearing in flow environment promotes evolution of social behavior in microbial populations Gurdip Uppal, Dervis Can Vural eLife 2018 0 0
Increased Network Interdependency Leads to Aging Physical Review E - Statistical, Nonlinear, and Soft Matter Physics 2013 0 0

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Cooperation and specialization in dynamic fluids

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