Irreversible Processes in Ecological Evolution/SamraatPawar
Notes by user Samraat Pawar (Imperial College London) 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
It was encouraging to see that people were intrigued by and interested in the issue of non-equilibrium/steady-state dynamics. Dervis asked a very pertinent question about the appropriateness of the Arrhenius equation for the temperature dependence of population growth rate and other "higher-level" processes.
Fascinating work -- the mathematical model opens up interesting new avenues for theoretical development for microbial ecosystem theory. The statistical mechanical approach, and the discussion about links to Lotka-Volterra type models and random matrix theory (including Robert May's results) were very insightful. The possible links to Otto Cordero's empirical results were exciting to see. Later Bobby and I discussed the possibility of of including temperature and size-scaling effects, and extensions of the model to include phytoplankton as well. These papers are relevant from this perspective:
- https://www.biorxiv.org/content/10.1101/524264v1.abstract (An analysis of thermal responses of bacterial and archaeal growth rates)
- DeLong, J. P., Okie, J. G., Moses, M. E., Sibly, R. M. & Brown, J. H. Shifts in metabolic scaling, production, and efficiency across major evolutionary transitions of life. Proc. Natl. Acad. Sci. U. S. A. 107, 12941–12945 (2010). (size scaling of microbial metabolic and growth rates)
- Tang, S., Pawar, S. & Allesina, S. Correlation between interaction strengths drives stability in large ecological networks. Ecology Letters 17, 1094–1100 (2014). (example of using metabolic constraints to parameterize random matrix theory/model).
Intriguing results about inconsistency between data and inferences that have been drawn in the past about the efficacy of antibiotics. This paper might be interesting/useful:
- Cruz-Loya, M. et al. Stressor interaction networks suggest antibiotic resistance co-opted from stress responses to temperature. ISME J. (2018). doi:10.1038/s41396-018-0241-7
The clustering of trait values on nice axes is a cool result. I think constraining the Niche-Neutral assembly model's parameters using ecological metabolic theory (especially, size-scaling) would provide further insights, and could lead to more precise predictions about the clustering of traits. I know Annette has published one on neutral theory constrained by size scaling (O'Dwyer, J. P., Lake, J. K., Ostling, a, Savage, V. M. & Green, J. L. An integrative framework for stochastic, size-structured community assembly. Proc. Natl. Acad. Sci. U. S. A. 106, 6170–5 (2009)). More to do along those lines, especially as competitive interactions too are strongly determined by size scaling and thermal responses. Our recent paper on phytoplankton competition is relevant:
- Bestion, E., García-Carreras, B., Schaum, C.-E., Pawar, S. & Yvon-Durocher, G. Metabolic traits predict the effects of warming on phytoplankton. Ecol. Lett. 21, 655–664 (2018).
Fascinating study -- remarkably detailed modelling and model fitting to data! Raised in my mind again the (seemingly eternal) question question that biologists face about models: specific or general? The problem of Fungus vs Virus would benefit by characterizing their temperature-dependence in vitro.
Very interesting study. Particularly useful to me as my lab is increasingly focusing on microbial ecosystem dynamics. The idea of using artificial nutrient particles/spheres is really innovative! The repeatability of bacterial community/network assembly / succession / turnover is striking. The low efficiency (~20%!) of uptake/use of metabolic byproducts was interesting to hear about -- looks like diffusion/turbulence/mixing plays a big role. Makes me wonder about the effect of turbulence/mixing on these dynamics (something we are particularly focused on in our modelling). The fact that early succession bacteria are more motile was also very interesting. Some of the detail about strategies adopted by generalist bacteria was particularly interesting.
The Hawaiian Tree-creeper example was a great start to open a real debate! I guess the question is about irreversibility of timescales -- given enough time, is a reversal of beak morphology really impossible? I think the evidence for traits such as attack rates, which occur and are measurable at short timescales have a less right-skewed was not quite convincing. I don't quite understand why attack rates should be hormonally regulated - the onset of foraging by a consumer may be hormonally regulated, but once a consumer is foraging, the interaction rate should be under biochemical (enzyme kinetic) control. However, I do agree that the temperature-dependence of certain rates/traits that are the result of an organismal process integrated over a longer timescale, may have a different, potentially less right-skewed response because of hormonal and other type of regulation. Worth doing a detailed analysis, using a wider range of organisms, I think. the new version of BioTraits would be suitable for this. I have invited Priyanga to participate in this year's VectorBiTE meeting (vectorbite.org) in Italy which I am co-organizing, where we could discuss this further and perhaps undertake such an analysis.
Very interesting model with interesting results! I found it strange that plants can produce nectar without cost. Perhaps as Fernanda said, this is a negligible factor, but would have been good to see some evidence for this, and some exploration of the model's structural robustness. But the approach of modeling the rewards as a separate pool with its own dynamics and imposing adaptive foraging altogether provided me with interesting new insights. I think that using movement biomechanics for bounding the interaction/visitation rates of pollinators would be worthwhile.
Very cool work. I absolutely agree that a mechanical approach towards understanding microbial interactions and evolution/co-evolution is the way forward. I raised the point (maybe too many times!) that organismal properties (locomotion) and environmental temperature need to be added to such modelling/theory. Also, why no turbulence? But overall, I found the results really insightful. I agree with Dervis' idea/claim that a general theoretical framework that allows the physical environment's properties to constrain interactions (and their ecological/evolutionary outcomes) within and between populations is possible and necessary. This is also the message I was trying to deliver in my talk.
Much-needed formalization of higher-order interactions, with compelling results. Would need some work to reconcile/test with empirical data, but a important step forward, I thought. The issue of indirect (e.g., trophic cascades) vs higher-order interactions (e.g., modification of a pairwise interaction by a third agent) came up. There is considerable confusion in the literature and even among us as to what the two terms entail. Indirect interactions are not the same as higher-order interactions, but ecologists very often use them interchangeably. There is a recent Ecology Letters paper that also tries to get at the distinction between the two:
Terry, J. C. D., Morris, R. J. & Bonsall, M. B. Trophic interaction modifications: an empirical and theoretical framework. Ecol. Lett. 20, 1219–1230 (2017).
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).
Temperature-dependence and size scaling of Microbial metabolism
The question of the temperature-dependence of bacterial metabolism came up in multiple talks. This manuscript from our lab provides some general empirical insights into this: https://www.biorxiv.org/content/10.1101/524264v1.abstract
This paper on size-scaling might also be relevant to some: 10.1073/pnas.1007783107
Natural experiments on effect of temperature on ecosystem structure and function
Some relevant papers:
- Yvon-Durocher, G., Allen, A. & Cellamare, M. Five Years of Experimental Warming Increases the Biodiversity and Productivity of Phytoplankton. PLoS Biol (2015).
- Dossena, M. et al. Warming alters community size structure and ecosystem functioning. Proc. R. Soc. B Biol. Sci. 279, 3011–3019 (2012).
- Schaum, C.-E. et al. Adaptation of phytoplankton to a decade of experimental warming linked to increased photosynthesis. Nat. Ecol. Evol. 1, 0094 (2017).
- Yvon-Durocher, G., Montoya, J. M., Woodward, G., Jones, J. I. & Trimmer, M. Warming increases the proportion of primary production emitted as methane from freshwater mesocosms. Glob. Chang. Biol. 17, 1225–1234 (2011).
Assembly/Succession/Evolution of microbial/bacterial networks/communities
1. Lawrence, D. et al. Species interactions alter evolutionary responses to a novel environment. PLoS Biol. 10, e1001330 (2012).
2. Rivett, D. W. et al. Elevated success of multispecies bacterial invasions impacts community composition during ecological succession. Ecology Letters 21, 516–524 (2018).
|Title||Author name||Source name||Year||Citation count From Scopus. Refreshed every 5 days.||Page views||Related file|
|Temperature dependence of trophic interactions are driven by asymmetry of species responses and foraging strategy||Anthony I. Dell, Samraat Pawar, Van M. Savage||Journal of Animal Ecology||2014||247||0|
|Species interactions alter evolutionary responses to a novel environment||Diane Lawrence, Francesca Fiegna, Volker Behrends, Jacob G. Bundy, Albert B. Phillimore, Thomas Bell, Timothy G. Barraclough||PLoS Biology||2012||217||3|
|Five Years of Experimental Warming Increases the Biodiversity and Productivity of Phytoplankton||Gabriel Yvon-Durocher, Andrew P. Allen, Maria Cellamare, Matteo Dossena, Kevin J. Gaston, Maria Leitao, José M. Montoya, Daniel C. Reuman, Guy Woodward, Mark Trimmer||PLoS Biology||2015||74||0|
|Correlation between interaction strengths drives stability in large ecological networks||Si Tang, Samraat Pawar, Stefano Allesina||Ecology Letters||2014||66||0|
|Stressor interaction networks suggest antibiotic resistance co-opted from stress responses to temperature||Mauricio Cruz-Loya, Tina Manzhu Kang, Natalie Ann Lozano, Rina Watanabe, Elif Tekin, Robert Damoiseaux, Van M. Savage, Pamela J. Yeh||ISME Journal||2018||23||1|
|Metabolic traits predict the effects of warming on phytoplankton competition||Elvire Bestion, Bernardo García-Carreras, Charlotte Elisa Schaum, Samraat Pawar, Gabriel Yvon-Durocher||Ecology Letters||2018||23||1|
|Elevated success of multispecies bacterial invasions impacts community composition during ecological succession||Damian W. Rivett, Matt L. Jones, Josep Ramoneda, Shorok B. Mombrikotb, Emma Ransome, Thomas Bell||Ecology Letters||2018||22||1|
|Trophic interaction modifications: an empirical and theoretical framework||J. Christopher D. Terry, Rebecca J. Morris, Michael B. Bonsall||Ecology Letters||2017||22||0|
|The Role of Body Size Variation in Community Assembly||Samraat Pawar||Advances in Ecological Research||2015||13||0|
|Pawar systematic variation||0||4|
|Systematic variation in the temperature dependence of physiological and ecological traits||Proceedings of the National Academy of Sciences||2011||0||0|
|Shifts in metabolic scaling, production, and efficiency across major evolutionary transitions of life||Proceedings of the National Academy of Sciences||2010||0||0|
|Metabolic traits predict the effects of warming on phytoplankton||0||1|
Presenter on the following Agenda items
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