Irreversible Processes in Ecological Evolution/DervisCanVural
Notes by user Dervis Can Vural (Univ. Notre Dame) for Irreversible Processes in Ecological Evolution
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
To discuss: Could we make a grocery list of all irreversible processes mentioned in the workshop? Few that come to mind immediately: (1) Priyanga's idea on hot to cold invasion (2) Ecological succession. (3) Niche filling (4) something funky happens with the lottery model when there is a big mutation event (is there a name for this? Surely it is a generic thing that can happen in many other systems) (4) formation of interdependences / mutualism / specialization (I will mention in my talk tomorrow) (5) gene duplication (I couldn't follow all there steps here). Anything else I'm missing?
More specific thoughts on individual talks:
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.
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".
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. Comments: (1) I like the idea a lot, very plausible. Here is my alternative (and quite possibly false) point of view: A high population is more evolvable, because there will be more mutants/innovation. Warmer climates have higher biomass (just because it receives more energy) and will therefore generate viable invaders at a higher rate. Maybe.
(2) She had some discussion about constraints vs selection. It's a possible to dichotomize, but I view these two things as one thing. A constrained region in phenotype space is just one with fitness=minusinfinity, so no one visits there. Possibly just a matter of semantics, but in any case, I don't see how a constraint implies irreversibility.
Jacopo Grilli: The model with three-body interactions is really an effective model of a two-body interactions. e.g. species A,B,C come together; first A interacts with B, then the winner interacts with C. (and you symmetrize this, because sometimes first A interacts with C first). As such, the outcomes of this model should reduce to a Lotka-Volterra model, (with specific structure, with specific conditions). I was not able to figure out what this structure is, and what the conditions are, but whatever these are, the stability of this system should not be a surprise if the equivalent Lotka-Volterra equations are also stable.
Reference material notes
- 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).
|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||5||1|
|Shearing in flow environment promotes evolution of social behavior in microbial populations||Gurdip Uppal, Dervis Can Vural||eLife||2018||5||0|
|Increased Network Interdependency Leads to Aging||Physical Review E - Statistical, Nonlinear, and Soft Matter Physics||2013||0||0|
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