Matching Items (54)
Description
Social insect colonies exhibit striking diversity in social organization. Included in this overwhelming variation in structure are differences in colony queen number. The number of queens per colony varies both intra- and interspecifically and has major impacts on the social dynamics of a colony and the fitness of its members. To understand the evolutionary transition from single to multi-queen colonies, I examined a species which exhibits variation both in mode of colony founding and in the queen number of mature colonies. The California harvester ant Pogonomyrmex californicus exhibits both variation in the number of queens that begin a colony (metrosis) and in the number of queens in adult colonies (gyny). Throughout most of its range, colonies begin with one queen (haplometrosis) but in some populations multiple queens cooperate to initiate colonies (pleometrosis). I present results that confirm co-foundresses are unrelated. I also map the geographic occurrence of pleometrotic populations and show that the phenomenon appears to be localized in southern California and Northern Baja California. Additionally, I provide genetic evidence that pleometrosis leads to primary polygyny (polygyny developing from pleometrosis) a phenomenon which has received little attention and is poorly understood. Phylogenetic and haplotype analyses utilizing mitochondrial markers reveal that populations of both behavioral types in California are closely related and have low mitochondrial diversity. Nuclear markers however, indicate strong barriers to gene flow between focal populations. I also show that intrinsic differences in queen behavior lead to the two types of populations observed. Even though populations exhibit strong tendencies on average toward haplo- or pleometrosis, within population variation exists among queens for behaviors relevant to metrosis and gyny. These results are important in understanding the dynamics and evolutionary history of a distinct form of cooperation among unrelated social insects. They also help to understand the dynamics of intraspecific variation and the conflicting forces of local adaptation and gene flow.
ContributorsOverson, Rick P (Author) / Gadau, Jürgen (Thesis advisor) / Fewell, Jennifer H (Committee member) / Hölldobler, Bert (Committee member) / Johnson, Robert A. (Committee member) / Liebig, Jürgen (Committee member) / Arizona State University (Publisher)
Created2011
Description
For over a century, researchers have been investigating collective cognition, in which a group of individuals together process information and act as a single cognitive unit. However, I still know little about circumstances under which groups achieve better (or worse) decisions than individuals. My dissertation research directly addressed this longstanding question, using the house-hunting ant Temnothorax rugatulus as a model system. Here I applied concepts and methods developed in psychology not only to individuals but also to colonies in order to investigate differences of their cognitive abilities. This approach is inspired by the superorganism concept, which sees a tightly integrated insect society as the analog of a single organism. I combined experimental manipulations and models to elucidate the emergent processes of collective cognition. My studies show that groups can achieve superior cognition by sharing the burden of option assessment among members and by integrating information from members using positive feedback. However, the same positive feedback can lock the group into a suboptimal choice in certain circumstances. Although ants are obligately social, my results show that they can be isolated and individually tested on cognitive tasks. In the future, this novel approach will help the field of animal behavior move towards better understanding of collective cognition.
ContributorsSasaki, Takao (Author) / Pratt, Stephen C (Thesis advisor) / Amazeen, Polemnia (Committee member) / Liebig, Jürgen (Committee member) / Janssen, Marco (Committee member) / Fewell, Jennifer (Committee member) / Hölldobler, Bert (Committee member) / Arizona State University (Publisher)
Created2013
Description
At the heart of every eusocial insect colony is a reproductive division of labor. This division can emerge through dominance interactions at the adult stage or through the production of distinct queen and worker castes at the larval stage. In both cases, this division depends on plasticity within an individual to develop reproductive characteristics or serve as a worker. In order to gain insight into the evolution of reproductive plasticity in the social insects, I investigated caste determination and dominance in the ant Harpegnathos saltator, a species that retains a number of ancestral characteristics. Treatment of worker larvae with a juvenile hormone (JH) analog induced late-instar larvae to develop as queens. At the colony level, workers must have a mechanism to regulate larval development to prevent queens from developing out of season. I identified a new behavior in H. saltator where workers bite larvae to inhibit queen determination. Workers could identify larval caste based on a chemical signal specific to queen-destined larvae, and the production of this signal was directly linked to increased JH levels. This association provides a connection between the physiological factors that induce queen development and the production of a caste-specific larval signal. In addition to caste determination at the larval stage, adult workers of H. saltator compete to establish a reproductive hierarchy. Unlike other social insects, dominance in H. saltator was not related to differences in JH or ecdysteroid levels. Instead, changes in brain levels of biogenic amines, particularly dopamine, were correlated with dominance and reproductive status. Receptor genes for dopamine were expressed in both the brain and ovaries of H. saltator, and this suggests that dopamine may coordinate changes in behavior at the neurological level with ovarian status. Together, these studies build on our understanding of reproductive plasticity in social insects and provide insight into the evolution of a reproductive division of labor.
ContributorsPenick, Clint A (Author) / Liebig, Jürgen (Thesis advisor) / Brent, Colin (Committee member) / Gadau, Jürgen (Committee member) / Hölldobler, Bert (Committee member) / Rutowski, Ron (Committee member) / Arizona State University (Publisher)
Created2012
Description
Mathematical modeling of infectious diseases can help public health officials to make decisions related to the mitigation of epidemic outbreaks. However, over or under estimations of the morbidity of any infectious disease can be problematic. Therefore, public health officials can always make use of better models to study the potential implication of their decisions and strategies prior to their implementation. Previous work focuses on the mechanisms underlying the different epidemic waves observed in Mexico during the novel swine origin influenza H1N1 pandemic of 2009 and showed extensions of classical models in epidemiology by adding temporal variations in different parameters that are likely to change during the time course of an epidemic, such as, the influence of media, social distancing, school closures, and how vaccination policies may affect different aspects of the dynamics of an epidemic. This current work further examines the influence of different factors considering the randomness of events by adding stochastic processes to meta-population models. I present three different approaches to compare different stochastic methods by considering discrete and continuous time. For the continuous time stochastic modeling approach I consider the continuous-time Markov chain process using forward Kolmogorov equations, for the discrete time stochastic modeling I consider stochastic differential equations using Wiener's increment and Poisson point increments, and also I consider the discrete-time Markov chain process. These first two stochastic modeling approaches will be presented in a one city and two city epidemic models using, as a base, our deterministic model. The last one will be discussed briefly on a one city SIS and SIR-type model.
ContributorsCruz-Aponte, Maytee (Author) / Wirkus, Stephen A. (Thesis advisor) / Castillo-Chavez, Carlos (Thesis advisor) / Camacho, Erika T. (Committee member) / Kang, Yun (Committee member) / Arizona State University (Publisher)
Created2014
Description
A functioning food web is the basis of a functioning community and ecosystem. Thus, it is important to understand the dynamics that control species behaviors and interactions. Alterations to the fundamental dynamics can prove detrimental to the future success of our environment. Research and analysis focus on the global dynamics involved in intraguild predation (IGP), a three species subsystem involving both competition and predation. A mathematical model is derived using differential equations based on pre-existing models to accurately predict species behavior. Analyses provide sufficient conditions for species persistence and extinction that can be used to explain global dynamics. Dynamics are compared for two separate models, one involving a specialist predator and the second involving a generalist predator, where systems involving a specialist predator are prone to unstable dynamics. Analyses have implications in biological conservation tactics including various methods of prevention and preservation. Simulations are used to compare dynamics between models involving continuous time and those involving discrete time. Furthermore, we derive a semi-discrete model that utilizes both continuous and discrete time series dynamics. Simulations imply that Holling's Type III functional response controls the potential for three species persistence. Complicated dynamics govern the IGP subsystem involving the white-footed mouse, gypsy moth, and oak, and they ultimately cause the synchronized defoliation of forests across the Northeastern United States. Acorn mast seasons occur every 4-5 years, and they occur simultaneously across a vast geographic region due to universal cues. Research confirms that synchronization can be transferred across trophic levels to explain how this IGP system ultimately leads to gypsy moth outbreaks. Geographically referenced data is used to track and slow the spread of gypsy moths further into the United States. Geographic Information Systems (GIS) are used to create visual, readily accessible, displays of trap records, defoliation frequency, and susceptible forest stands. Mathematical models can be used to explain both changes in population densities and geographic movement. Analyses utilizing GIS softwares offer a different, but promising, way of approaching the vast topic of conservation biology. Simulations and maps are produced that can predict the effects of conservation efforts.
ContributorsWedekin, Lauren (Author) / Kang, Yun (Thesis advisor) / Green, Douglas (Committee member) / Miller, William (Committee member) / Arizona State University (Publisher)
Created2012
Description
We model communication among social insects as an interacting particle system in which individuals perform one of two tasks and neighboring sites anti-mimic one another. Parameters of our model are a probability of defection 2 (0; 1) and relative cost ci > 0 to the individual performing task i. We examine this process on complete graphs, bipartite graphs, and the integers, answering questions about the relationship between communication, defection rates and the division of labor. Assuming the division of labor is ideal when exactly half of the colony is performing each task, we nd that on some bipartite graphs and the integers it can eventually be made arbitrarily close to optimal if defection rates are sufficiently small. On complete graphs the fraction of individuals performing each task is also closest to one half when there is no defection, but is bounded by a constant dependent on the relative costs of each task.
ContributorsArcuri, Alesandro Antonio (Author) / Lanchier, Nicolas (Thesis director) / Kang, Yun (Committee member) / Fewell, Jennifer (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / Economics Program in CLAS (Contributor) / School of Mathematical and Statistical Sciences (Contributor)
Created2015-05
Description
The Axelrod Model is an agent-based adaptive model. The Axelrod Model shows the eects of a mechanism of convergent social inuence. Do local conver- gences generate global polarization ? Will it be possible for all dierences between individuals in a population comprised of neighbors to disappear ? There are many mechanisms to approach this issue ; the Axelrod Model is one of them.
ContributorsYu, Yili (Author) / Lanchier, Nicolas (Thesis director) / Kang, Yun (Committee member) / Brooks, Dan (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Finance (Contributor)
Created2013-05
Description
This thesis explores and explains a stochastic model in Evolutionary Game Theory introduced by Dr. Nicolas Lanchier. The model is a continuous-time Markov chain that maps the two-dimensional lattice into the strategy space {1,2}. At every vertex in the grid there is exactly one player whose payoff is determined by its strategy and the strategies of its neighbors. Update times are exponential random variables with parameters equal to the absolute value of the respective cells' payoffs. The model is connected to an ordinary differential equation known as the replicator equation. This differential equation is analyzed to find its fixed points and stability. Then, by simulating the model using Java code and observing the change in dynamics which result from varying the parameters of the payoff matrix, the stochastic model's phase diagram is compared to the replicator equation's phase diagram to see what effect local interactions and stochastic update times have on the evolutionary stability of strategies. It is revealed that in the stochastic model altruistic strategies can be evolutionarily stable, and selfish strategies are only evolutionarily stable if they are more selfish than their opposing strategy. This contrasts with the replicator equation where selfishness is always evolutionarily stable and altruism never is.
ContributorsWehn, Austin Brent (Author) / Lanchier, Nicolas (Thesis director) / Kang, Yun (Committee member) / Motsch, Sebastien (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of International Letters and Cultures (Contributor)
Created2013-12
Description
Honeybees are important pollinators worldwide and pollinate about one-third of the food we consume. Recently though, honeybee colonies have been under increasing stress due to changing environments, pesticides, mites, and viruses, which has increased the incidence of
colony collapse. This paper aims to understand how these different factors contribute to the decline of honeybee populations by using two separate approaches: data analysis and mathematical modeling. The data analysis examines the relative impacts of mites, pollen, mites, and viruses on honeybee populations and colony collapse. From the data, low initial bee populations lead to collapse in September while mites and viruses can lead to collapse in December. Feeding bee colonies also has a mixed effect, where it increases both bee and mite populations. For the model, we focus on the population dynamics of the honeybee-mite interaction. Using a system of delay differential equations with five population components, we find that bee colonies can collapse from mites, coexist with mites, and survive without them. As long as bees produce more pupa than the death rate of pupa and mites produce enough phoretic mites compared to their death rates, bees and mites can coexist. Thus, it is possible for honeybee colonies to withstand mites, but if the parasitism is too large, the colony will collapse. Provided
this equilibrium exists, the addition of mites leads to the colony moving to the interior equilibrium. Additionally, population oscillations are persistent if they occur and are connected to the interior equilibrium. Certain parameter values destabilize bee populations, leading to large
oscillations and even collapse. From these parameters, we can develop approaches that can help us prevent honeybee colony collapse before it occurs.
colony collapse. This paper aims to understand how these different factors contribute to the decline of honeybee populations by using two separate approaches: data analysis and mathematical modeling. The data analysis examines the relative impacts of mites, pollen, mites, and viruses on honeybee populations and colony collapse. From the data, low initial bee populations lead to collapse in September while mites and viruses can lead to collapse in December. Feeding bee colonies also has a mixed effect, where it increases both bee and mite populations. For the model, we focus on the population dynamics of the honeybee-mite interaction. Using a system of delay differential equations with five population components, we find that bee colonies can collapse from mites, coexist with mites, and survive without them. As long as bees produce more pupa than the death rate of pupa and mites produce enough phoretic mites compared to their death rates, bees and mites can coexist. Thus, it is possible for honeybee colonies to withstand mites, but if the parasitism is too large, the colony will collapse. Provided
this equilibrium exists, the addition of mites leads to the colony moving to the interior equilibrium. Additionally, population oscillations are persistent if they occur and are connected to the interior equilibrium. Certain parameter values destabilize bee populations, leading to large
oscillations and even collapse. From these parameters, we can develop approaches that can help us prevent honeybee colony collapse before it occurs.
ContributorsSweeney, Brian Felix (Author) / Kang, Yun (Thesis director) / Mubayi, Anuj (Committee member) / College of Integrative Sciences and Arts (Contributor) / Economics Program in CLAS (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
For colonies of ponerine ant species, sterility regulation after a founding queen's death is not totally achieved in the worker caste, and the possibility of sexual reproduction is opened to workers. The persisting survival of these colonies is dependent on capturing the optimal reproductive ratio; yet, an informational gap bounds the mechanisms detailing the selection of new reproductives and the suppression of ovarian development in rejected reproductives. We investigated the mechanisms of worker policing, one of the primary methods of ovarian suppression, through continuous video observation for a period of five days at the start of colony instability. Observations suggest policing in H. saltator is performed by a majority of a colony, including potential reproductives, and requires multiple events to fully discourage ovarian growth.
ContributorsChien, Jeffrey (Co-author) / Barat Ali, Fatima (Co-author) / Kang, Yun (Thesis director) / Liebig, Juergen (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12