Theoretical Ecology Lab Tea

The Theoretical Ecology Lab Teas are informal meetings where members of affiliated lab groups give talks on their current research and receive feedback from their audience. Talks are 30 minutes long and are followed by questions and discussion.

Lab Tea typically meets Wednesdays at 12:30 pm during the fall and spring semesters. All talks this semester will be held in Eno 209 unless otherwise stated.

For the fall semester of 2016, the talk schedules and email lists will be maintained by Wenying Liao and Dylan Morris. Please contact Wenying or Dylan to have your name added to the Lab Tea email list so that you can receive reminders about upcoming meetings.

Fall 2016 schedule

Click on an event to view the talk title and abstract

Date and time Speaker
Juan-Carlos Rocha
Ed Schrom
Prof. Mary C. Stoddard
Edward Tekwa
Departmental seminar - no Lab Tea
Daniel Cooney
Georgios Artavanis
Fall break - no Lab Tea
Sarah Drohan
George Hagstrom
Thanksgiving break - no Lab Tea
Liliana Salvador
Wenying Liao
Prof. Henry Horn

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

Two brief talks on social-ecological systemsJuan-Carlos Rocha

Cascading effects of critical transitions in social-ecological systems
Critical transitions in nature and society are likely to occur more often and severe as humans increase they pressure on the world ecosystems. Yet it is largely unknown how these transitions will interact, whether the occurrence of one will increase the likelihood of another, and whether these potential teleconnections (social and ecological) correlate critical transition in distant places. Here we present a framework for exploring three types of potential cascading effects of critical transitions: forks, domino effects and inconvenient feedbacks. Drivers and feedback mechanisms are reduced to a network form that allow us to explore drivers co-occurrence (forks). Sharing drivers is likely to increase correlation in time or space among critical transitions but not necessarily interdependence. Random walks on causal networks allow us to detect and compare communities of common drivers and feedback mechanisms across different critical transitions. Domino effects and inconvenient feedbacks were identified by mapping new circular pathways on coupled networks that have not been previously reported. The method serves as a platform for hypothesis exploration of plausible new feedbacks between critical transitions in social-ecological systems; it helps to scope structural interdependence and hence an avenue for future modelling and empirical testing of regime shifts coupling.

Behavioural economics in social-ecological systems with thresholds
How does people behave when dealing with situations pervaded by thresholds? Imagine you’re a fisherman whose livelihoods depend on a resource on the brink to collapse, what would you do? and what do you think others will do? Here we report results form a field experiment with fishermen from four coastal communities in the Colombian Caribbean. A dynamic game with 256 fishermen helped us investigate behavioural responses to the existence of thresholds (probability =1 ), risk (threshold with a climate event with known probability of 0.5) and uncertainty (threshold with an unknown probability climate event). Communication was allowed during the game and the social dilemma was confronted in groups of 4 fishermen. We found that fishermen facing thresholds presented a more conservative behaviour on the exploration of the parameter space of resource exploitation. Some groups that crossed the threshold managed to recover to a regime of high fish reproduction rate. However, complementary survey data reveals that groups that collapsed the resource in the game come often from communities with high livelihood diversification, lower resource dependence and strongly exposed to infrastructure development. We speculate that the later translates on higher noise levels on resource dynamics which decouples or mask the relationship between fishing efforts and stock size encouraging a more explorative behaviour of fishing effort in real life. This context is brought to our artificial game and leave statistical signatures on resource exploitation patterns. In general, people adopt a precautionary behaviour when dealing with common pool resource dilemmas with thresholds. However, stochasticity can trigger the opposite behaviour.

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Simulating the evolution of immune system signaling networksEd Schrom

Immune systems rely on networks of interacting signaling proteins to translate the detection of a parasite into an appropriate response. From fruit flies to humans, immune signaling networks appear extraordinarily complex. However, these networks do share a simple job: balancing the urgency of clearing the parasite with the costs of immunity itself, even in the face of parasitic attempts to disrupt signaling. This summer, Joaquin Prada and I have developed a theoretical model of the evolution of immune signaling networks to investigate the underlying network structures that 1) account for the inducibility of immunity, and 2) account for robustness against parasite interference with signaling processes.

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''The Most Perfect Thing in the Universe?'' Form and Function of the Avian EggProf. Mary C. Stoddard

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Why do fisheries evolve different harvest rates?Edward Tekwa

The sustainability of renewable resources such as marine fish is strongly determined by harvest rate. Fisheries set harvest rates according to ecological, economic, enforcement, and food security considerations. In ecology, a traditional harvest rate target is one that generates the maximum sustainable yield (MSY) over the long term. In economics, the value of future harvest is discounted against an alternative rate of return, which is the opportunity cost. The higher the opportunity cost, the faster a fishery has to harvest in order to generate an equal return. However, this optimization procedure assumes that revenue can be reinvested, whereas for fishery managers, the currency for success may neither be monetary or can be reinvested. We model the change in harvest rate as a function of opportunity cost, measured as food security, in a more myopic evolutionary framework. We found that as opportunity cost increases, harvest rate evolves from MSY to a regime where MSY is unstable; instead, bistability evolves, with both high and low harvest rates attainable. Empirically, global fishery pattern appears to follow the model predictions better than traditional ecological or economic recommendations. Deviations from the predictions can be partly explained by a lack of management enforcement, leading to the open access problem where individual fishers respond to opportunity cost differently from regional managers, but where overexploitation is not the only possibility.

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Departmental seminar - no Lab Tea

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Evolutionary Game Theory with Selection at Multiple ScalesDaniel Cooney

This talk will provide an introduction to models in evolutionary game theory which simultaneously study the effects of selection within groups and selection between groups. We will review recent research that uses the frequency-independent Moran process and differential equations, and then we will introduce a frequency-dependent model that brings evolutionary game theory into play. We will then discuss potential applications of this mathematical framework to study dynamics of network-structured populations and to explore epidemic models with competition at multiple scales.

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The effect of inequality on common pool resource dynamicsGeorgios Artavanis

The sustainable management of common pool resources (CPRs) requires cooperation among the individuals of the community, otherwise overharvesting can lead to the depletion of the resource. Thus, the study of the mechanisms and conditions that allow and reinforce the evolution of robust cooperation are of great interest: unless there is a framework of well-defined rules, short-term benefits will lead individuals to harvest above the sustainable threshold.

This talk will explore the role of inequality on common pool resource dynamics using an agent-based model: In a community that shares a CPR (R1), and each individual has private shares of another resource (R2), both of which contribute to the success of the individual, inequalities in the distribution of R2 may lead to cheating with respect to R1: traditional sanctions will be less effective against individuals with larger private shares, so a different framework of rules and sanctions might be needed to achieve robust cooperation. Extensions of the agent-based model to address other questions on CPR dynamics will also be discussed.

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Fall break - no Lab Tea

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Modeling feedback loops in social-ecological systemsSarah Drohan

Understanding feedbacks is critical to identifying and explaining drivers, regime shifts, and alternative stable states in social-ecological systems. However, one must be careful when discussing the influence of positive feedback loops on the stability of a system It can be easy to conflate the existence of positive feedback loops with the prospect of switching between alternative stable states, but that is far from a necessary and sufficient condition. We need mathematical tools that allow us to quantitatively understand the impact of these loops in dynamical systems and their role in alternative stable states. One such tool from the systems dynamics community that may be useful is Loop Eigenvalue Elasticity Analysis (LEEA). Given a causal loop diagram or dynamical system, this method attempts to identify the dominant loops through their influence on the eigenvalues of the system. I will explain the mechanics and calculations and apply this method to case studies. More generally, I aim to characterize systems and find counterexamples that shed light both on this technique and the dynamics involved in alternative stable states and social-ecological systems.

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How should we make mechanistic models of the human microbiome?George Hagstrom

The human microbiome is a complex ecosystem containing a diverse array of microbes. Their ecology is influenced by nutrient availability, social interactions, human immune systems, and the environment. Anticipating the visit of the Blaser lab, we present a modeling framework that attempts to capture the key forces that structure the human microbiome.

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Thanksgiving break - no Lab Tea

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Establishing the link between search spatial patterns and behavioural processes in the model system C. elegansLiliana Salvador

Understanding animal movement patterns and their associated behavioural processes is a critical aspect of foraging ecology. Previous work on model organisms searching on a bare environment showed that they use complex search strategies while exploring the environment, in which different behavioural processes act at multiple time scales, and movement strategies arise from a balance between intrinsic and extrinsic mechanisms. However, how these time scales and behavioural mechanisms relate to the spatial patterns generated during a search event is still unknown. This talk will provide an overview of the movement properties and intermittent behaviour of C.elegans to explore the link between spatial patterns of movement and behavioural processes, and gain insight into the role of these events in searching success.

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Coupling of carbon and nitrogen cycles selects for nitrogen fixation in tropical and boreal, but not temperate forestsWenying Liao

Nitrogen (N) is an essential limiting nutrient for primary production across many ecosystems. Symbiotic N-fixing plants (''N fixers''), which form symbiosis with N-fixing bacteria to convert atmospheric N2 gas to inorganic form for plant use, can be the dominant source of N input into biosphere where they are abundant. Their distribution, therefore, can profoundly influence global capacity of carbon (C) sequestration. One of the most intriguing puzzles in ecology is the paradoxical latitudinal pattern of N fixer distribution: Traditional paradigm argues that, because of their direct access to atmospheric N pool, N fixers should be competitively advantageous in N-limited environment. However, N fixers are common in tropical and boreal forests, but rare in temperate forests, despite the increasing N limitation from the equator to the poles. Here, we use a simple model, coupling the C and N cycles along latitude to explain the emergence of the bimodal distribution pattern.

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Little Insights into Big Questions in Ecology (especially biodiversity: origin, regulation, and dynamics)Prof. Henry Horn

Some of the latest concepts in recent EEB seminars and in our Graduate Journal Club seem to fit the outline of the Ecology course that I gave in 1966 as a newly minted Boy Wonder Emeritus. So “return with us now to those thrilling days of yesteryear” to extend Hutchinson and MacArthur’s (1957) geometric metaphor of the “fundamental niche,” and explore: (1) How niche dimensionality affects competition and multivariate statistics, (2) How physical constraints may liberate intriguing biology, (3) How and why forest succession succeeds, ... sometimes, and (4) Why details of natural history are crucial to spatial patterns, dispersal, and darned near everything else.

I shall pose my little insights by faking a technical understanding far beyond my formal mathematical training (maybe I’ll even confess how pathetic that training is). My selfish goal is to ask you which insights might be worth following up, and where to find needed tools to do it.

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Links to previous schedules

  1. Fall 2000
  2. Spring 2001
  3. Fall 2001
  4. Spring 2002
  5. Fall 2002
  6. Spring 2003
  7. Fall 2003
  8. Spring 2004
  9. Fall 2004
  10. Spring 2005
  11. Fall 2005
  12. Spring 2007
  13. Fall 2007
  14. Spring 2008
  15. Fall 2008
  16. Spring 2009
  17. Fall 2009
  18. Spring 2010
  19. Fall 2010
  20. Spring 2011
  21. Fall 2011
  22. Spring 2012
  23. Fall 2012
  24. Spring 2013
  25. Fall 2013
  26. Spring 2014
  27. Fall 2014
  28. Spring 2015
  29. Fall 2015
  30. Spring 2016