Irreversible Processes in Ecological Evolution/Statistical mechanics of microbiomes

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January 29, 2019
3:45 pm - 4:45 pm

Presenter

Robert Marsland (Boston Univ.)

Abstract

In a seminal paper in 1972, Robert May studied complex ecosystems using Random Matrix Theory. Nearly fifty years later, the rise of quantitative microbial ecology makes it possible to test and refine this approach. Random matrix models successfully capture a wide range of large-scale patterns observed in real microbial communities, including functional and family-level reproducibility, compositional clustering by environment, enterotypes, dissimilarity-overlap correlations, decreased diversity in harsh environments, compositional nestedness, succession dynamics and modularity. After describing the computational model we have developed to reproduce all these patterns, I will present a set of analytic results that explain why this works in the real world. Adding even a small amount of noise to a sufficiently diverse community induces a phase transition to a “typical” phase, where community-level properties such as diversity and rank-abundance curves are indistinguishable from those of a completely random ecosystem. I will explain how the properties of this phase are governed by “susceptibilities” describing the linear response of the ecosystem to small changes in population sizes or resource concentrations. These susceptibilities can be obtained from Random Matrix Theory, in the spirit of May’s paper, and can also be measured by subjecting a community to controlled perturbations.

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Post-meeting Reflection

Robert Marsland (Boston Univ.) Link to the source page

Questions from my talk:

True or false?

1. Classical ecological models are inadequate for understanding microbial ecosystems.

2. The large-scale, reproducible patterns we see across microbiomes are emergent features of “typical random ecosystems.”

3. Diverse communities will almost always behave like “random ecosystems.” 

Question I want to discuss

Can large-scale ecological changes over time be understood through simple general principles? (Samraat, Jacopo, Priyanga, me: flux balance/metabolic rates, random matrix theory, biochemical and morphological constraints)

Are there ecological summary statistics that change monotonically over time? (Jacopo, and some of my work that I didn't talk about -- see references)

Which properties of individual organisms are essential for predicting large-scale ecological changes?

- Pamela -- why do some vaccines fail to produce large-scale ecological change (i.e., pathogen extinction)?

- Greg -- importance of distribution of susceptibilities to dynamics of epizootic onset.

- Fernanda -- importance of adaptive foraging for understanding why pollinator systems don't collapse -- and why they might under new circumstances.

- Samraat -- taking the mechanics of inter-species interaction seriously, understanding how they affect response of ecosystem to temperature changes.

- Priyanga -- asymmetry of reaction norms for temperature variation.

What do we miss when we focus too much on equilibrium/steady states? (Prevalence of cyclic disturbance/recovery dynamics -- Greg, Samraat)

Reference Material

"The Minimum Environmental Perturbation Principle" (Marsland et al. 2019) is some new work I didn't include in my presentation, but which is possibly more relevant to the irreversibility theme. The main result is that a wide class of niche models exhibit monotonic increase in the environmental perturbation under successive invasions/evolution. I would love any feedback from the ecologists about references to add, things that are unclear, etc.

Marsland and England 2017 and Marsland et al. 2015 contain in-depth explanations of the two kinds of “thermodynamic” irreversibility I wrote up on the board.

Mehta et al. 2018 begins with a discussion of the "bias/variance tradeoff", which is extremely relevant to the use of models with many parameters to make predictions. It also has a section on dimensional reduction and clustering that might be useful to people working with high-dimensional phenotype data. (Note that the wiki didn't allow me to enter the whole author list, which should also include Marin Bukov, Charles Fisher and David Schwab.)

Momeni et al. 2017 shows some of the ways in which Lotka-Volterra can fail to capture the population dynamics of a generalized class of consumer-resource models.

Fisher and Mehta 2014 shows how both niche and neutral regimes can arise in Lotka-Volterra dynamics with immigration, depending on the parameter values.

"Available Energy Fluxes..." (Marsland et al. 2019) contains a full explanation of our microbial consumer resource model in the appendix. The Python implementation can be found at our group github: https://github.com/Emergent-Behaviors-in-Biology/community-simulator.

I have also included the original Human Microbiome Project and Earth Microbiome Project data papers, which contain the large-scale patterns I was showing in the presentation.

Gutenknust et al. 2007 explains some of the subtleties of Bayesian model fitting in a very accessible way, and strongly influenced the way I think about many-parameter models.

Goldford et al. 2018 contains some of the patterns I was talking about at the beginning of my talk, which are already captured by a preliminary version of the model.

Title	Author name	Source name	Year	Citation count From Scopus. Refreshed every 5 days.	Page views	Related file
Structure, function and diversity of the healthy human microbiome	A. Scott Durkin, Allison Griggs, Alyxandria M. Schubert, Amy L. McGuire, Anthony A. Fodor, Antonio Gonzalez, Anup A. Mahurkar, Ashlee M. Earl, Asif T. Chinwalla, Aye M. Wollam, Barbara A. Methé, Beltran Rodriguez-Mueller, Bo Liu, Bonnie P. Youmans, Brandi Herter, Brandi L. Cantarel, Brian J. Haas, Bruce W. Birren, Candace N. Farmer, Carl C. Baker, Carolyn Deal, Carsten Russ, Catherine A. Lozupone, Catherine C. Davis, Catherine Jordan, Catrina C. Fronick, Cecil M. Lewis, Cesar A. Arze, Chad M. Tomlinson, Chad Nusbaum, Chandri Yandava, Chien Chi Lo, Christian J. Buhay, Christie L. Kovar, Christina Giblin, Christopher S. Smillie, Christopher Wellington, Clinton Howarth, Craig Pohl, Cristyn Kells, Curtis Huttenhower, Dan Knights, Dana A. Busam, Daniel D. Sommer, Daniel McDonald, David J. Dooling, Dawn M. Ciulla, Dennis C. Friedrich, Diana G. Tabbaa, Diane E. Hoffmann, Dirk Gevers, Donna M. Muzny, Doyle V. Ward, Elaine R. Mardis, Elena Deych, Elizabeth A. Lobos, Elizabeth Appelbaum, Emily L. Harris, Emma Allen-Vercoe, Eric J. Alm, Erica J. Sodergren, Floyd E. Dewhirst, Gary Armitage, Gary L. Andersen, George M. Weinstock, Georgia Giannoukos, Gina A. Simone, Granger G. Sutton, Gregory A. Buck, Harindra M. Arachchi, Heather H. Creasy, Heidi H. Kong, Holli A. Hamilton, Hongyu Gao, Huaiyang Jiang, I. Min A. Chen, Indresh Singh, Ioanna Pagani, Irene Newsham, J. Fah Sathirapongsasuti, J. Paul Brooks, Jack D. Sobel, Jacques Izard, Jacques Ravel, James A. Katancik, James R. White, James Versalovic, Jamison M. McCorrison, Jane Peterson, Janet K. Jansson, Jason R. Miller, Jason Walker, Jean McEwen, Jeffery A. Schloss, Jeffrey G. Reid, Jennifer R. Wortman, Jeremy D. Zucker, Jeroen Raes, Johannes Goll, John C. Martin, Jonathan Crabtree, Jonathan Friedman, Jonathan H. Badger, Jonathan M. Goldberg, Jose C. Clemente, Joseph F. Petrosino, Joseph L. Campbell, Joshua Orvis, Julia A. Segre, Karen E. Nelson, Karoline Faust, Karthik C. Kota, Katarzyna Wilczek-Boney, Katherine H. Huang, Katherine P. Lemon, Katherine S. Pollard, Kathie A. Mihindukulasuriya, Kelvin Li, Ken Chu, Kevin P. Riehle, Kim C. Worley, Kimberley D. Delehaunty, Kjersti M. Aagaard, Konstantinos Liolios, Konstantinos Mavromatis, Kris A. Wetterstrand, Krishna Palaniappan, Kristine M. Wylie, Kymberlie Hallsworth-Pepin, Lan Zhang, Larry J. Forney, Laurie Zoloth, Lei Chen, Leslie Foster, Liang Ye, Lisa Begg, Lita M. Proctor, Lora Lewis, Lu Wang, Lucia Alvarado, Lucinda L. Fulton, Lynn Schriml, Makedonka Mitreva, Manolito Torralba, Margaret E. Priest, Maria C. Rivera, Maria Y. Giovanni, Mark A. Watson, Martin J. Blaser, Mary A. Cutting, Mathangi Thiagarajan, Matthew C. Ross, Matthew Pearson, Matthew Scholz, Michael E. Holder, Michael Feldgarden, Michael G. Fitzgerald, Michelle G. Giglio, Michelle Oglaughlin, Mihai Pop, Mina Rho, Mircea Podar, Monika Bihan, Narmada Shenoy, Nathalia Garcia, Niall Lennon, Nicholas B. King, Nicola Segata, Nihar U. Sheth, Nikos C. Kyrpides, Noam J. Davidovics, Olukemi O. Abolude, Omry Koren, Owen White, Pamela McInnes, Pamela Sankar, Patricio S. La Rosa, Patrick D. Schloss, Patrick J. Minx, Patrick S.G. Chain, Paul Spicer, Peter J. Mannon, Qiandong Zeng, R. Dwayne Lunsford, Rachel L. Erlich, Ramana Madupu, Ravi K. Sanka, Rebecca M. Truty, Richard A. Gibbs, Richard K. Wilson, Richard R. Sharp, Rob Knight, Robert C. Edgar, Robert S. Fulton, Rosamond Rhodes, Ruth E. Ley, Ruth M. Farrell, Sahar Abubucker, Sandra L. Lee, Sandra W. Clifton, Sarah K. Highlander, Sarah K. Young, Scott Anderson, Scott T. Kelley, Sean Conlan, Sean M. Sykes, Sergey Koren, Shaila Chhibba, Shane R. Canon, Shannon P. Dugan, Sharvari Gujja, Sheila Fisher, Shibu Yooseph, Shital M. Patel, Susan Kinder Haake, Susan M. Huse, Tatiana A. Vishnivetskaya, Teena Mehta, Tessa Madden, Theresa A. Hepburn, Thomas J. Sharpton, Thomas M. Schmidt, Toby Bloom, Todd J. Treangen, Todd Wylie, Todd Z. Desantis, Tsegahiwot Belachew, Tulin Ayvaz, Valentina Di Francesco, Vandita Joshi, Veena Bhonagiri, Victor M. Felix, Victor M. Markowitz, Vincent Magrini, Vivien Bonazzi, Wendy A. Keitel, Wesley Warren, William D. Shannon, Wm Michael Dunne, Xiang Qin, Yan Ding, Yanjiao Zhou, Yiming Zhu, Yu Hui Rogers, Yuanqing Wu, Yue Liu, Yuzhen Ye, Zhengyuan Wang	Nature	2012	5,565	6
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Charles, Tugrul Giray, Ulf Riebesell, Valerie McKenzie, Vanessa Ezenwa, Vanessa Hale, Vera Tai, Vincenzo Fogliano, Virginia Sanz, Walter P. MacCormack, Wayne Roundstone, Wenju Liang, William A. Walters, William Brazelton, William Van Treuren, Wyatt Oswald, Yadira Ortiz Castellano, Yeqin Yang, Yingying Ni, Yongqin Liu, Yoshiki Vázquez-Baeza, Yu Shi, Zhenjiang Zech Xu	Nature	2017	718	6
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Metabolic resource allocation in individual microbes determines ecosystem interactions and spatial dynamics	Alex Betts, Alex H. Lang, Amrita Kar, Brian R. Granger, Christopher J. Marx, Daniel Segrè, Gracia Bonilla, Ilija Dukovski, Nicholas Leiby, Pankaj Mehta, William J. Riehl, William R. Harcombe	Cell Reports	2014	264	4
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Lotka-Volterra pairwise modeling fails to capture diverse pairwise microbial interactions	Babak Momeni, Li Xie, Wenying Shou	eLife	2017	79	0
A high-bias low-variance introduction to machine learning for physicists	Alexandre G. R. Day, Ching-Hao Wang, Clint Richardson, Pankaj Mehta		2018	0	9	Download
Available energy fluxes drive a transition in the diversity, stability, and functional structure of microbial communities	Alvaro Sanchez, Joshua Goldford, Kirill Korolev, Pankaj Mehta, Robert Marsland III, Wenping Cui	PLoS Computational Biology	2019	0	1
The Minimum Environmental Perturbation Principle: A New Perspective on Niche Theory	Pankaj Mehta, Robert Marsland III, Wenping Cui		2019	0	1
Time and Irreversibility in axiomatic thermodynamics	Giovanni Valente, Harvey R. Brown, Robert Marsland III	American Journal of Physics	2015	0	0
Limits of Prediction in thermodynamic systems: a review	Jeremy England, Robert Marsland III	Reports on Progress in Physics	2017	0	1
The transition between the niche and neutral regimes in ecology	Charles K. Fisher, Pankaj Mehta	Proceedings of the National Academy of Sciences	2014	0	2
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