Fall 2021
Click on an event to view the talk title and abstractDate and time | Speaker |
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Daniel Cooney | |
Edward Schrom | |
Victoria Junquera | |
Theo Gibbs | |
Sirio Belga Fedeli | |
No Lab Tea (Fall Recess) | |
Justin Sheen | |
Jaime Lopez | |
Yvonne Krumbeck | |
Eduardo Colombo | |
Pavel Chvykov | |
No Lab Tea (Thanksgiving Break) | |
Woi Sok Oh | |
Jessica Luo | |
Camille Carpentier |
Note: Priority is given to graduate students. A ⊛ symbol next to the speaker's name means that approval is pending for a week and graduate students can still claim the slot.
Titles and abstracts
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Modeling the Evolution of Protocells and the Origin of Chromosomes via Multilevel SelectionDaniel Cooney The evolution of complex cellular life involved two major transitions: the encapsulation of self-replicating genetic entities into cellular units and the aggregation of individual genes into a collectively replicating genome. In this talk, we will formulate a minimal model of the evolution of proto-chromosomes within protocells. We model a simple protocell composed of two types of genes: a ``fast gene'' with an advantage for gene-level self-replication and a ``slow gene'' that replicates more slowly at the gene level, but which confers an advantage for protocell-level reproduction. Protocell-level replication capacity depends on cellular composition of fast and slow genes. We use a partial differential equation to describe how the composition of genes within protocells evolves over time under within-cell and between-cell competition. We find that the gene-level advantage of fast replicators casts a long shadow on the multilevel dynamics of protocell evolution: no level of between-protocell competition can produce coexistence of the fast and slow replicators when the two genes are equally needed for protocell-level reproduction. By introducing a ``dimer replicator'' consisting of a linked pair of the slow and fast genes, we show analytically that coexistence between the two genes can be promoted in pairwise multilevel competition between fast and dimer replicators, and provide numerical evidence for coexistence in trimorphic competition between fast, slow, and dimer replicators. Our results suggest that dimerization, or the formation of a simple chromosome-like dimer replicator, can help to overcome the shadow of lower-level selection and work in concert with deterministic multilevel selection to allow for the coexistence of two genes that are complementary at the protocell-level but compete at the level of individual gene-level replication. This is joint work with Fernando Rossine, Dylan Morris, and Simon Levin.
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Borrowing from Ecology: Developing Spatial Interaction Analyses for Immunological ImagesEdward Schrom Across many scientific disciplines, technology to collect massive data sets is booming, and immunology is no different. In particular, state-of-the-art microscopy techniques allow us to image biological tissues in extraordinary detail, showing hundreds of different cell types in their native morphologies and spatial arrangements as an immune response plays out. Because organ- and organism-scale immune outcomes emerge from the local interactions of many immune cells, statistically analyzing the spatial arrangements and interactions of different cell types has become an important frontier. I will discuss my ongoing efforts to develop such analyses, highlighting the ways in which I am borrowing from (and hopefully contributing to!) more traditional ecological questions.
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Avocado expansion in Spain and globally—a look at dynamics and impactsVictoria Junquera Avocado tree plantations have significantly expanded in Spain since the crop was first adopted by innovative farmers in the 1970s. News outlets increasingly report about “avocado booms” in Spain, Portugal, Peru, South Africa, Kenya, and other regions where the fruit is rapidly expanding. In southern Spain, farmers are replacing low-productivity rainfed olive orchards with irrigated avocado trees, placing an unprecedented burden on water resources. This work applies a mixed-methods approach based on interviews, surveys (perhaps) and time-series land use maps (hopefully) to: 1) Understand the spatio-temporal dynamics of avocado expansion at various scales, exploring the role of networks (e.g., social influence, trade relations, transport infrastructure, etc.), the applicability of spread and “contagion” models, and the relevance of regime shift and tipping points frameworks; 2) Conceptualize the role and characteristics of “markets” and “the Market”, not only as places and performances of trade, but also in terms of their relational and institutional nature and their influence on farmers’ decisions; 3) Analyze the “governance quagmire” around water and irrigation rights and infrastructure, and assess the capacity of existing institutions to handle large and rapid changes such as crop booms; and 4) Examine the “physiology of globalization” by zooming out on global drivers of avocado demand and feedback mechanisms between production, demand, and prices, and zooming in on the local emergence of avocado production hotspots and their socioecological impacts. I’m at an early stage of research design and very much welcome your feedback and suggestions!
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Stability criteria for the consumption and exchange of essential resourcesTheo Gibbs Models of pairwise interactions have informed our understanding of when ecological communities will have stable equilibria. However, these models do not explicitly include the effect of environmental context, which has the potential to refine or modify our understanding of when a group of interacting species will coexist. Recent consumer-resource models incorporating the exchange of resources alongside competition exemplify this: such models can lead to either stable or unstable equilibria, depending on the environment. On the other hand, these recent models focus on a simplified version of microbial metabolism where the depletion of resources always leads to consumer growth. Here, we model an arbitrarily large system of consumers governed by Liebig's law, where species require and deplete multiple resources, but each consumer's growth rate is only limited by a single one of these multiple resources. Consumed resources that do not lead to growth are leaked back into the environment, thereby tying the mismatch between depletion and growth to cross-feeding. For this set of dynamics, we show that feasible equilibria can be either stable or unstable, once again depending on the environmental context. We identify special consumption and production networks which protect the community from instability when resources are scarce. Using simulations, we demonstrate that the qualitative stability patterns we derive analytically apply to a broader class of network structures and resource inflow profiles, including cases in which species coexist on only one externally supplied resource. Our stability criteria bear some resemblance to classic stability results for pairwise interactions, but also demonstrate how environmental context can shape coexistence patterns when ecological mechanism is modeled directly.
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Nonlinearity-Generated Resilience in Large Randomly Assembled Complex SystemsSirio Belga Fedeli In this talk we extend the local analysis of the May model for large randomly assembled complex system. In particular, we consider a generic nonlinear model in which all higher-order terms in the expansion around the chosen fixed point (placed at the origin) are included with random Gaussian coefficients. As the size of the system grows, in correspondence of the known sharp instability-to-stability transition, the evaluation of the mean number of equilibrium points surrounding the origin reveals the emergence of a “resilience gap”. Namely, there exists a radius r*>0 for which the system is expected to be resilient to a typical initial displacement r<
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The effect of evictions on the transmission of SARS-CoV-2Justin Sheen The COVID-19 pandemic has led to surges in unemployment, which in turn have left many tenants unable to pay their rent. The current eviction crisis could have severe consequences on SARS-CoV-2 transmission. Studies show that many evicted households “double-up,” moving in with family or friends. Doubling-up shifts the distribution of household sizes upwards, facilitating SARS-Cov-2 spread. To study the effect of evictions on SARS-CoV-2 at a population level, we present an SEIR network model tracking both household and external contacts, and use it to simulate epidemic trajectories within a theoretical metropolitan area of one million individuals. We divide the simulation into temporal phases to reproduce the epidemic since early 2020: (1) an early exponential phase, followed by (2) lockdown of external contacts, (3) relaxation of lockdown of external contacts. In the fourth phase we project the course of the epidemic beyond Fall 2020 under two counterfactual scenarios, one in which evictions continue, and the other in which they are halted. In some simulations we consider a fifth phase in which lockdown is reinitiated. In a simple model, which assumes homogeneous mixing in the simulated city, we expect a 1%/month eviction rate (with all evictions resulting in doubling-up) to cause a 3-6% increase in seroprevalence vs. if evictions were prevented, and approximately 1 excess death for every 70 evicted households. The effect of evictions is even more profound in models that consider clustering of evictions and transmission in poorer neighborhoods. We also consider evictions that lead to homelessness, and relocation to shelters/encampments. Across all scenarios, we find that evictions (1) increase the total number of infected individuals, in both evicted and non-evicted households; and, (2) decrease the efficacy of a hypothetical second lockdown. The generality of our results provide a theoretical basis to assess eviction moratoriums in any city.
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Noisy metabolism can promote microbial cross-feedingJaime Lopez Cross-feeding, the exchange of nutrients between organisms, is ubiquitous in microbial communities. Despite its importance in natural and engineered microbial systems, our understanding of how cross-feeding arises is incomplete, with existing theories limited to specific scenarios. Here, we introduce a novel theory for the evolution of cross-feeding, which we term noise-averaging cooperation (NAC). NAC is based on the idea that, due to their small size, bacteria are prone to noisy regulation of metabolism which limits their growth rate. To compensate, related bacteria can share metabolites with each other to "average out'' noise and improve their collective growth. This metabolite sharing among kin then allows for the evolution of metabolic interdependencies via gene deletions (this can be viewed as a generalization of the Black Queen Hypothesis). We first characterize NAC in a simple model of cell metabolism, showing that metabolite leakage can in principle substantially increase growth rate in a community context. Next, we develop a generalized framework for estimating the potential benefits of NAC among real bacteria. Using single-cell protein abundance data, we predict that bacteria suffer from substantial noise-driven growth inefficiencies, and may therefore benefit from NAC. Finally, we review existing evidence for NAC and outline potential experimental approaches to detect NAC in microbial communities.
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Fluctuation spectra of large random dynamical systems reveal hidden structure in ecological networksYvonne Krumbeck Understanding the relationship between complexity and stability in large dynamical systems – such as ecosystems – remains a key open question in complexity theory which has inspired a rich body of work developed over more than fifty years. The vast majority of this theory addresses asymptotic linear stability around equilibrium points, but the idea of ‘stability’ in fact has other uses in the empirical ecological literature. The important notion of `temporal stability’ describes the character of fluctuations in population dynamics, driven by intrinsic or extrinsic noise. Here we apply tools from random matrix theory to the problem of temporal stability, deriving analytical predictions for the fluctuation spectra of complex ecological networks. We show that different network structures leave distinct signatures in the spectrum of fluctuations, and demonstrate the application of our theory to the analysis of ecological timeseries data of plankton abundances.
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A multiscale approach to spatial patterns in plankton communities: the large-scale consequences of taxis-induced mesoscale patchiness in plankton communitiesEduardo Colombo A fundamental problem in ecology is how individual-level behavior affects emergent macro-ecological patterns. In marine ecosystems, this issue is intimately related to the interaction between physical and biological forces. For example, while being advected by the turbulent ocean, plankton can actively move in search for resources, establishing a tug-of-war between behavior and turbulence. To further the understanding about this issue, we developed an agent-based model that keeps track of a grazer–resource community subjected to an external flow that mimics turbulence. We observe that, as the grazer shifts from a purely planktonic to an active behavior, mesoscale patchiness and a new phase portrait for the community dynamics emerge. The large-scale consequences of mesoscale patchiness are accessed by a coarse-graining procedure that provides us with an effective density-field description of the population. The developed framework allows for a two-way mapping between the large-scale features of spatial patterns and individual-level behavior.
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A predictive principle for self-organization in active collectives.Pavel Chvykov Self-organization is frequently observed in active collectives as varied as ant rafts and molecular motor assemblies. General principles describing self-organization away from equilibrium have been challenging to identify. We offer a unifying framework that models the behavior of complex systems as largely random while capturing their configuration-dependent response to external forcing. This allows derivation of a Boltzmann-like principle for understanding and manipulating driven self-organization. We validate our predictions experimentally, with the use of shape-changing robotic active matter, and outline a methodology for controlling collective behavior. Our findings highlight how emergent order depends sensitively on the matching between external patterns of forcing and internal dynamical response properties, pointing toward future approaches for the design and control of active particle mixtures and metamaterials.
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Rethinking over hurricane evacuation strategies in existing models: Are they really sustainable?Woi Sok Oh Existing evacuation studies—mostly by transportation engineers—suggested various evacuation policies (e.g., staged evacuation, early-warning system) to facilitate residents’ escape to a safe place before/during a hurricane. This research aims to rethink the effectiveness of evacuation policies considering decision-making processes of residents involving past hurricane experience and local culture with a case study in Galveston, Texas. This city has historically been exposed to devastating hurricanes and their consequential surges. Additionally, Galveston is renowned for its strong local culture among residents born on Galveston Island (BOI for born on the island). BOI residents often behave independently in response to risk based on their experience, not following orders from the government. Nevertheless, past studies often neglected these effects when testing evacuation policies. To capture more realistic patterns, hurricane evacuations and their management are viewed from more integrated perspectives in this work. Since this study is at the initial stage, I will be happy to hear people’s thoughts on relevant issues such as social equity, decision-making processes, experience and memory, evacuation timing dynamics, etc.
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Modeling the global scale ecological and biogeochemical impacts of gelatinous zooplanktonJessica Luo Gelatinous zooplankton (GZ), which include the jellyfish, comb jellies, and pelagic tunicates, are present in all of the world's oceans, but have long been considered relatively minor contributors to ocean biogeochemical cycling. However, recent offline studies on the role of GZ on ocean carbon cycling showed that GZ-mediated carbon export were globally significant, and among the GZ, the filter feeding pelagic tunicates were the largest contributors to carbon flux. Insights from plankton imaging suggest that pelagic tunicates, which include the appendicularians, salps, and doliolids, have been vastly underestimated by traditional methods (i.e., nets), yielding an overall underappreciation of their global abundance and contribution to ocean biogeochemical cycles relative to crustacean zooplankton. As climate change is projected to decrease the average plankton size and POC export from traditional plankton food webs, the ecological and biogeochemical role of pelagic tunicates may increase; yet, pelagic tunicates were not resolved in the previous generation of global earth system climate projections. Here we present a global modeling study using a coupled physical-biogeochemical model to assess the impact of pelagic tunicates to the pelagic food web and biogeochemical cycling. We added two tunicate groups, a large salp/doliolid and a small appendicularian to the NOAA-GFDL Carbon, Ocean Biogeochemistry, and Lower Trophics (COBALT) model, which was originally formulated to represent carbon flows to crustacean zooplankton. The new GZ-COBALT simulation was able to simultaneously satisfy new pelagic tunicate biomass constraints and existing ecosystem constraints, including crustacean zooplankton observations. Our results suggest that pelagic tunicates represent a significant source of competition against microzooplankton, and serve as a trophic and carbon export shunt away from the microbial loop.
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Predicting ecological network resistance to species lossCamille Carpentier Facing the current biodiversity crisis, it is becoming increasingly important to be able to understand and predict the consequences of species removal on ecological networks. These networks can be described using simple metrics such as the number of species, the number of interactions between them and the distribution of these interactions between the species (degree distribution). Coupling these properties allows us to predict the topological impacts of species removal and, therefore, to compute the average robustness of a network as well as its lower and upper boundaries. Furthermore, we show that our results, derived in an ecological context, should be extendable to scale-free networks in general, as they rely on the degree distribution. Taken together, our results elucidate the intricate relationships between network structure and robustness in community networks.
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