Fall 2014 schedule
| Date and time | Speaker |
|---|---|
| Ricardo Martinez-Garcia | |
| Ariana Strandburg-Peshkin | |
| Special lab tea: Yun Tao | |
| Adam Wolf | |
| George Constable | |
| Anieke van Leeuwen | |
| No lab tea: Fall break | |
| Special lab tea: Jake Hochard | |
| David Borenstein | |
| Eleanor Brush | |
| Phillip Hannam | |
| No lab tea: Thanksgiving | |
| Pawel Romanczuk | |
| Matthieu Barbier | |
| Special lab tea: Edward W. Tekwa |
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
-
Optimizing the search for resources sharing information: the Mongolian gazelle. Ricardo Martinez-Garcia Communication among individuals frequently leads to group formation, which often has clear direct benefits such as reducing individual vulnerability to predators. Such strategies may, however, also have important incidental benefits. For example, an individual that has found a good foraging patch might try to attract conspecifics to reduce its risk of predation, but also provides its conspecifics with information on the location of good forage, thus increasing the foraging efficiency of those responding to the call.
In this presentation we will investigate the relationship between communication and search efficiency in a biological context by proposing a model of searchers with long-range pairwise interaction. After a general study of the properties of the model, we will go deeper into an application to the particular case of acoustic communication among Mongolian gazelle, for which data are available, searching for good habitat areas. Our results point out that the search is optimal (i.e. the mean first hitting time among searchers is minimum) at intermediate scales of communication, showing that both an excess and a lack of information may worsen it.
Back to schedule -
Mechanisms of decision-making and collective movement in wild baboons Ariana Strandburg-Peshkin Animal groups are often characterized by complex social structures in which individuals exhibit sophisticated use of social information. A major determinant of fitness relates to how animals in such groups make collective decisions, such as where to move to seek appropriate habitat, to forage, and to avoid predators. Baboons have been a model system for studying social living for decades, and as a result their social structure is well-characterized. Yet, due to methodological constraints, little is known about how coordinated collective movement is achieved in these, and other similarly complex, societies. When opinions conflict between group members, it remains unclear whether individuals use simple heuristics, or if they follow more complex rules based on whom they are interacting with. To reveal the underlying fine-grained structure of leadership and social decision-making in a wild baboon troop, we deployed high-resolution GPS collars on almost all adult members of the troop. By analyzing how individuals moved in relation to one another we identified and analyzed a large number of both successful, and failed, movement initiation attempts. We found that decision-making in these groups contained elements of both distributed (self-organized) control, and differential influence according to individuals’ identity. Specifically, when one option was clearly preferred by a large majority, individuals followed the majority. In contrast, when competing options were similarly-supported, specific individuals had disproportionately high influence on the decisions of followers. By studying the fine-scale movement during such decision-making events, we further found that consensus decisions are made only when the difference in directions proposed by of individuals or subgroups exceeds a critical angle, whereas individuals resolve small differences by choosing an average direction. This highlights the importance of considering explicitly the geometry of decision-making in animal groups and demonstrates how different mechanisms of leadership can operate in the same system depending on the level of spatial and numerical conflict.
Back to schedule -
Special lab tea Yun Tao (Graduate of UC Davis – Hastings Lab) Movement ecology is an emerging discipline that is essential to our understanding of the interplay between fine-scale movement mechanisms of individuals and their large-scale implications for population and communities. More importantly, theoretical development of non-equilibrium and complex adaptive movement systems such as animal home range are critical to the development of next-generation solutions to conservational challenges in a messy, interconnected, and highly variable world. The studies here present original analytical and numerical frameworks for modeling transient movement dynamics that often occur rapidly and quietly. Modal selection function, formulated from the basis of optimal foraging theory, aims to facilitate an ecologically integrated approach to predicting the seasonal expansion and collapse of animal home range. Meanwhile, a simulation platform that delivers time-varying solutions to partial differential equations is introduced as an effective remedy to the technical restrictions that have to date impeded transient movement analysis of interacting individuals. Lastly, movement is modeled from a cross-disciplinary perspective that unifies individual-based dispersal model with spatial ecology, through which the conditions for regional level movement consequence to converge on classic metapopulation predictions are starting to be identified.
Back to schedule -
An alternative economic analogy for stomatal behavior Adam Wolf In 1977, Cowan and Farquhar published a seminal work in plant biology entitled "Stomatal function in relation to leaf metabolism and the environment". This work was an attempt to move past the copious literature on what stomata did, and then to offer an explanation for why. They framed the question as a constrained optimization problem: how to optimally exploit a finite water supply over time, given fluctuations in the natural environment. The answer they found was for plants to control stomata so as to maintain constant marginal water use efficiency, that is the carbon gained per unit water lost. This understanding remains canonical to this day. And yet, there are shortcomings for this explanation for stomatal control. Chief among these is the observation that plants have a private bank account of water from which they might draw - - clearly in many ecosystems plants are drawing from a common pool of water, and do not have the luxury of saving some for later. Another weakness is that it is not clear why plants should care about water in the air, while ignoring the water availability in the soil, as Cowan and Farquar had. I will present some theoretical work that provides an alternative economic analogy for stomatal behavior, that is the classic microeconomic profit maximization where the setpoint is determined by the point at which marginal revenue equals marginal cost. This alternative analogy avoids the shortcomings that are inherent to Cowan and Farquhar's model.
Back to schedule -
Fast timescales in stochastic population dynamics George Constable If a model exhibits a separation of timescales, it is sometimes possible to extricate the dynamics happening on a fast timescale from those occurring on a slow timescale. A reduction in the dimensionality of the system can thus achieved, which may make analytic progress possible or simply improve our intuition as to how the system behaves.
In deterministic systems this approach is widely utilised. For instance, the Holling’s functional responses can be derived using timescale separation arguments. In stochastic systems however, the standard mathematical techniques used to obtain such approximations become much more involved.
In this talk I will present a more straightforward method of fast variable elimination for stochastic systems derived from individual based models. Its use is illustrated with reference to a metapopulation Moran model and a Lotka-Volterra competition model. In both cases the approximation technique leads to an effective one-dimensional system which is amenable to analysis. The reduced systems capture the behaviour of the full systems with high precision in the relevant regimes.
Back to schedule -
Trophically transmitted parasites in a size-structured predator-prey system Anieke van Leeuwen The realization of the role parasites play in ecosystems has shed an entirely new light on much of what is known about food web structure and food web dynamics. In terms of numbers of interactions, parasitic species dominate over free-living species. In terms of biomass, the component present in parasites can exceed that of top predators, as is observed in several Californian salt marsh systems. Snails as host species, interacting with parasites, were highlighted in food web studies and provide an example of the ecological interconnectedness of trophically transmitted parasite life stages and intra- and interspecific interactions. We ask the question how the size-specific population dynamics of a common host species (Cerithidea californica) is affected by the interplay of castrating parasitism, intraspecific resource competition and interspecific predation and competition by crabs (Pachygrapsus crassipes). Extensive field surveys and data from previous studies show a characteristic pattern concerning the size-specific pattern of parasite prevalence within the snail population. The signature in this data is of high parasite prevalence in large individuals (>25mm) and extremely high parasite prevalence in the largest individuals (>35mm) in the population. The current study seeks to address the question what causes this prevalence pattern and to what extent non-parasitic trophic interactions contribute to the snail population size-distribution and the size-specific parasite prevalence pattern. We find that size-specific predation and in particular size-specific intra-guild predation exerted by crabs are essential elements to explain the size-specific prevalence pattern in snails and overall snail population structure.
Back to schedule -
Special lab tea: Using behavioral ecology for management of ecosystem services Jake Hochard Bioeconomic models routinely account for the joint-determinedness of ecological and economic systems. Ecological systems provide benefits, or ecosystem services, to humans and human actions influence the provisioning of those services. To analyze tradeoffs in management, these services are often combined in a welfare function. Simplifying assumptions, designed to preserve model tractability, are common. These assumptions, in some cases, limit the scope of the resulting policy recommendations. We show that analytical tractability can be preserved and policy recommendations improved when finer ecological detail is employed in the specification of ecosystem services. Using a game-theoretic approach, an application of this concept is made by modeling three foundations of the behavioral ecology of wolves: refuge-seeking behavior, optimal foraging group size and territoriality. These behavioral patterns allow us to predict the density of wolves within and across management jurisdictions, which enables us to specify visitor congestion effects on public land, frequency of wildlife viewing, harvest success rates, the number of recreation days within a harvest season and harvest season length. This approach makes a notable contribution by examining management tradeoffs not only between but also within competing consumptive and non-consumptive ecosystem services.
Back to schedule -
Type VI Secretion as a Defensive Strategy David Borenstein Type VI secretion (T6S) is a cell-to-cell microbial weapon that is homologous to a phage delivery system. Genes for T6S are widespread in nature, and experimental evidence links it to both host-pathogen and intermicrobial interactions. What advantages does T6S offer in the context of bacterial interspecies competition? To explore this question, we used our novel modeling language (http://www.ecoprogramming.org) to develop a computational model of a growing microbial community in which individual cells can attack and kill cells of different species, but not of their own species. In simulations pairing two otherwise identical T6S+ species against one another, we find that the majority species benefits greatly from high attack rates. However, when T6S+ invaders attack a T6S- resident population, T6S attack provides only a marginal benefit to the attackers. In addition, an arbitrarily small growth advantage can allow T6S- individuals to dominate in competition with T6S+ individuals. Finally, given a sufficiently large resident T6S- population with a growth rate advantage, T6S+ invasion never succeeds in displacing the resident T6S- population. We conclude that T6S can be an effective defense against invasion, but offers limited benefit to an invader.
Back to schedule -
Conflict and strategy in collective computation Eleanor Brush Collective computations occur in many biological systems, ranging in size from a brain made of billions of neurons to social groups made up of tens of monkeys. In each of these systems, a group-level output emerges from the behavior of individuals making decisions in noisy environments. In particular, in the brain and in primate social groups, pairs of individuals must make decisions about their relative quality or ability. I use a leaky integrator model, a set of stochastic differential equations describing the dynamics of two decision variables, to model this decision process. The decisions made between each pair form a directed network over the whole group. The degree of consensus in the group about each individual's value, as determined by the decision network, is a collective computation that is informative about the individuals' true values. First, I will show that the same model can be used to describe both neural and social systems. Next, I will discuss how conflicts of interest in the decision process affect individuals in different positions the group, what measures of consensus are most informative and under what conditions, and how the shape of the distribution of consensus scores is determined by the waiting costs of the decisions.
Back to schedule -
Deepening climate cooperation with a proliferation of small agreements Phillip Hannam Countries forming an inclusive, legally-binding, post-2020 global climate framework in Paris next year are unlikely to agree to emissions targets sufficient to avert the most serious anticipated impacts of climate change. Where no supranational authority exists, country interests differ widely, and there are incentives to free ride, cooperation is initially easier in smaller coalitions with more homogenous interests, or through club agreements where benefits to participation are more excludable. Relative to a top-down approach, case study and model results lend some optimism for the potential of coalitions that start small but grow over time to substantially deepen provision of global public goods. Drawing motivation from issues ranging from nuclear non-proliferation and liberalized trade to maritime governance and transboundary air pollution, we use an evolutionary-game-theoretic model to analyze public goods provision (in this case greenhouse gas mitigation) in a dynamic cooperative regime initially motivated by domestic interests. We explore the dynamics of the system, including the construction of the regime, the co-existence of cooperators and free-riders, and overshoot in the number of cooperators. Our results indicate that cooperation in small club configurations yields larger non-excludable public goods benefits than cooperation in more inclusive forums (like the UN). A proliferation of small agreements may actually be more effective (not just more likely) in addressing climate change than a strictly top-down approach.
Back to schedule -
Catching a target with directed run and tumble motion – optimal intermittent directed search Pawel Romanczuk During Zebrafish development, progenitor cells are required to arrive with high temporal and spatial precision at specific targets sites. On the one hand this directed migration is associated with the presence of chemical cues, and on the other hand it was reported to consist of phases of persistent motion (“runs”) interrupted by reorientation events associated with cell repolarization (“tumbles”). We consider a minimal model of chasing agents undergoing directed migration towards a target with noisy information on the target position, e.g. due to chemotactic sensing. The chaser moves by switching between two phases of motion (run and tumble), reorienting itself towards the target during tumble phases, and performing a persistent random walk during run phases. We show that the chaser average run time can be adjusted to minimize the catching time or the spatial dispersion of the chasers. We obtain analytical results for the catching time and for the spatial dispersion in the limits of small and large ratios of run time to tumble time, and scaling laws for the optimal run times. Finally, we discuss the possibility of an optimal chemotactic strategy in animal cell migration by analyzing in-vivo experiments together with simulation of a more detailed stochastic model fitted to experimental data.
Back to schedule -
Fisherman's friends, or the value of information Matthieu Barbier For ecologists, fishers are social predators searching for preys. For economists, they are playing out a common-pool resource problem with imperfect information. The most immediate aspect of their sociality is thus information sharing, which has visible effets on their spatial behavior. On this level, fishing communities vary wildly, from cooperation to secrecy or spying, depending on ecological, economic and other factors that have yet to be elucidated. The work I will present explores some of this range of behaviors and seeks to understand both the causes and consequences of these social interactions, with numerical results from an Agent Based Model and the outline of corresponding analytics.
Back to schedule -
Special lab tea: Spatial clustering mediates the evolution of cooperation and population outcomes Edward W. Tekwa The evolution of cooperation has been implicated for the major evolutionary transitions and the increase in biotic complexity, including the rise of multicellular organisms and societies. However, the question of how cooperation between individuals affects population abundances has rarely been addressed theoretically and empirically. It may seem that cooperation necessarily leads to a higher population abundance, but a preliminary evolution model shows that this is not so when both are mediated by spatial clustering. In addition, apparently simple organisms continue to outnumber complex cooperative ones, indicating that high cooperation levels may not be dominant in term of global abundance. It is of fundamental interest to map out and theoretically explore the distribution of population abundance and cooperation level across taxa, for this may partly explain the co-existence of simple microbes and complex societies on Earth.
Back to schedule