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Difference between revisions of "Irreversible Processes in Ecological Evolution/JacopoGrilli"

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Stochastic open competitive communities. Niche/unique opportunities/deterministic forces vs chance/neutral/stochastic forces.  Finding niche differences is a challenge. Stochastic Lotka-Volterra on 1dim niche axis . Cluster emerge. 1) Metric. What is a good measure of clustering and how is that affected by different mechanisms? 2) Data. BCI and regional pool.
 
Stochastic open competitive communities. Niche/unique opportunities/deterministic forces vs chance/neutral/stochastic forces.  Finding niche differences is a challenge. Stochastic Lotka-Volterra on 1dim niche axis . Cluster emerge. 1) Metric. What is a good measure of clustering and how is that affected by different mechanisms? 2) Data. BCI and regional pool.
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'''Greg Dwyer'''
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Gipsy moth & virus/fungi. Inference of parameters from time-series. Key ingredient: variability of susceptibility between individuals. Works in reproducing data (but it is hard to predict)
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'''Otto Cordero'''
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Hyper-diversity of microbial communities. How do we interpret that diversity? Patches of organic matters (~detritus) are hotspots of diversity: multiple species are recruited. Lab experiment: biopolymers, 100 species. -Omics + culturing + phenotyping in order to recostruct dynamics. Observed successions (are true successions? Can also be explained by variability in growth/dilution rate). How succession depends on niche-breadth? Idea: niche breadth is bimodal (small niche  breadth: early colonizers, specialized. Large niche breadth: late colonizers, cannot be grown in culture). He then looks at the metabolic networks: close to the central metabolism everything is more homogeneous, close to the periphery everything is more heterogenous (high variability in copy number). He then plots #of chitinases vs the # of coevolved modules. Early colonizers are high in both. Late colonizers are low in both. Free loaders have high # of coevolved modules but low #chitinases (can eat what free riders eat). Ecological dyanmics is consistent with this classification (degraders grow initially and then decay, cheaters and cross-feeders grow later)
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'''Robert Marsland'''
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Two facts: A) Microbiome is very diverse. B) Taxa is unstable, function is stable (robust patterns). Assumptions: 1) classical ecological models are inadequate for understanding ecosystems 2) large / diverse ecosystems are typically random. (Random) Chemostat model predicts many patterns. Why random works well? Above stability threshold random works very well.
 
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Revision as of 16:57, February 27, 2019

Notes by user Jacopo Grilli (ICTP) 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

Pamela Martinez

Connection between population dynamics and strain diversity. What is the response to pathogen intervention? (clear in a Chessonian framework, unclear when there is strong strain diversity). 1) Rotavirus. Robust antigenic diversity. Estimate of the parameters from cases: G-type strong specific immune response, P-type strong general immune response (concern: very few data, enough statistical power). Surprising: no effect of vaccine/intervention. 2) S. pneumonia. Frequency of strains. How does frequency change after intervention? Replicator model, predicted fitness from genes (how? Not clear): can predict frequencies after intervation (which again does not work). Questions: 1) what determines the equilibrium frequencies of genes? Why loci are under negative frequency negative dependent selection?

Annette Ostling

Stochastic open competitive communities. Niche/unique opportunities/deterministic forces vs chance/neutral/stochastic forces. Finding niche differences is a challenge. Stochastic Lotka-Volterra on 1dim niche axis . Cluster emerge. 1) Metric. What is a good measure of clustering and how is that affected by different mechanisms? 2) Data. BCI and regional pool.

Greg Dwyer

Gipsy moth & virus/fungi. Inference of parameters from time-series. Key ingredient: variability of susceptibility between individuals. Works in reproducing data (but it is hard to predict)

Otto Cordero

Hyper-diversity of microbial communities. How do we interpret that diversity? Patches of organic matters (~detritus) are hotspots of diversity: multiple species are recruited. Lab experiment: biopolymers, 100 species. -Omics + culturing + phenotyping in order to recostruct dynamics. Observed successions (are true successions? Can also be explained by variability in growth/dilution rate). How succession depends on niche-breadth? Idea: niche breadth is bimodal (small niche breadth: early colonizers, specialized. Large niche breadth: late colonizers, cannot be grown in culture). He then looks at the metabolic networks: close to the central metabolism everything is more homogeneous, close to the periphery everything is more heterogenous (high variability in copy number). He then plots #of chitinases vs the # of coevolved modules. Early colonizers are high in both. Late colonizers are low in both. Free loaders have high # of coevolved modules but low #chitinases (can eat what free riders eat). Ecological dyanmics is consistent with this classification (degraders grow initially and then decay, cheaters and cross-feeders grow later)

Robert Marsland

Two facts: A) Microbiome is very diverse. B) Taxa is unstable, function is stable (robust patterns). Assumptions: 1) classical ecological models are inadequate for understanding ecosystems 2) large / diverse ecosystems are typically random. (Random) Chemostat model predicts many patterns. Why random works well? Above stability threshold random works very well.

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

Presenter on the following Agenda items

Higher-order interactions, stability across timescales, and macroecological patterns

Presentation file
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