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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
This work is an assemblage of three applied projects that address the institutional and spatial constraints to managing threatened and endangered (T & E) terrestrial species. The first project looks at the role of the Endangered Species Act (ESA) in protecting wildlife and whether banning non–conservation activities on multi-use federal lands is socially optimal. A bioeconomic model is used to identify scenarios where ESA–imposed regulations emerge as optimal strategies and to facilitate discussion on feasible long–term strategies in light of the ongoing public land–use debate. Results suggest that banning harmful activities is a preferred strategy when valued species are in decline or exposed to poor habitat quality. However such a strategy cannot be sustained in perpetuity, a switch to land–use practices characteristic of habitat conservation plans is recommended. The spatial portion of this study is motivated by the need for a more systematic quantification and assessment of landscape structure ahead of species reintroduction; this portion is further broken up into two parts. The first explores how connectivity between habitat patches promotes coexistence among multiple interacting species. An agent–based model of a two–patch metapopulation is developed with local predator–prey dynamics and density–dependent dispersal. The simulation experiment suggests that connectivity levels at both extremes, representing very little risk and high risk of species mortality, do not augment the likelihood of coexistence while intermediate levels do. Furthermore, the probability of coexistence increases and spans a wide range of connectivity levels when individual dispersal is less probabilistic and more dependent on population feedback. Second, a novel approach to quantifying network structure is developed using the statistical method of moments. This measurement framework is then used to index habitat networks and assess their capacity to drive three main ecological processes: dispersal, survival, and coexistence. Results indicate that the moments approach outperforms single summary metrics and accounts for a majority of the variation in process outcomes. The hierarchical measurement scheme is helpful for indicating when additional structural information is needed to determine ecological function. However, the qualitative trend between network indicator and function is, at times, unintuitive and unstable in certain areas of the metric space.
ContributorsSalau, Kehinde Rilwan, 1985- (Author) / Janssen, Marco A (Thesis advisor) / Fenichel, Eli P (Thesis advisor) / Anderies, John M (Committee member) / Abbott, Joshua K (Committee member) / Arizona State University (Publisher)
Created2013
Description
Climate and land use change are projected to threaten biodiversity over the coming century. However, the combined effects of these threats on biodiversity and the capacity of current conservation networks to protect species' habitat are not well understood. The goals of this study were to evaluate the effect of climate change and urban development on vegetation distribution in a Mediterranean-type ecosystem; to identify the primary source of uncertainty in suitable habitat predictions; and to evaluate how well conservation areas protect future habitat in the Southwest ecoregion of the California Floristic Province. I used a consensus-based modeling approach combining three different species distribution models to predict current and future suitable habitat for 19 plant species representing different plant functional types (PFT) defined by fire-response (obligate seeders, resprouting shrubs), and life forms (herbs, subshurbs). I also examined the response of species grouped by range sizes (large, small). I used two climate models, two emission scenarios, two thresholds, and high-resolution (90m resolution) environmental data to create a range of potential scenarios. I evaluated the effectiveness of an existing conservation network to protect suitable habitat for rare species in light of climate and land use change. The results indicate that the area of suitable habitat for each species varied depending on the climate model, emission scenario, and threshold combination. The suitable habitat for up to four species could disappear from the ecoregion, while suitable habitat for up to 15 other species could decrease under climate change conditions. The centroid of the species' suitable environmental conditions could shift up to 440 km. Large net gains in suitable habitat were predicted for a few species. The suitable habitat area for herbs has a small response to climate change, while obligate seeders could be the most affected PFT. The results indicate that the other two PFTs gain a considerable amount of suitable habitat area. Several rare species could lose suitable habitat area inside designated conservation areas while gaining suitable habitat area outside. Climate change is predicted to be more important than urban development as a driver of habitat loss for vegetation in this region in the coming century. These results indicate that regional analyses of this type are useful and necessary to understand the dynamics of drivers of change at the regional scale and to inform decision making at this scale.
ContributorsBeltrán Villarreal, Bray de Jesús (Author) / Franklin, Janet (Thesis advisor) / Fenichel, Eli P (Committee member) / Kinzig, Ann P (Committee member) / Collins, James P. (Committee member) / Arizona State University (Publisher)
Created2012
Description
The spread of invasive species may be greatly affected by human responses to prior species spread, but models and estimation methods seldom explicitly consider human responses. I investigate the effects of management responses on estimates of invasive species spread rates. To do this, I create an agent-based simulation model of an insect invasion across a county-level citrus landscape. My model provides an approximation of a complex spatial environment while allowing the "truth" to be known. The modeled environment consists of citrus orchards with insect pests dispersing among them. Insects move across the simulation environment infesting orchards, while orchard managers respond by administering insecticide according to analyst-selected behavior profiles and management responses may depend on prior invasion states. Dispersal data is generated in each simulation and used to calculate spread rate via a set of estimators selected for their predominance in the empirical literature. Spread rate is a mechanistic, emergent phenomenon measured at the population level caused by a suite of latent biological, environmental, and anthropogenic. I test the effectiveness of orchard behavior profiles on invasion suppression and evaluate the robustness of the estimators given orchard responses. I find that allowing growers to use future expectations of spread in management decisions leads to reduced spread rates. Acting in a preventative manner by applying insecticide before insects are actually present, orchards are able to lower spread rates more than by reactive behavior alone. Spread rates are highly sensitive to spatial configuration. Spatial configuration is hardly a random process, consisting of many latent factors often not accounted for in spread rate estimation. Not considering these factors may lead to an omitted variables bias and skew estimation results. The ability of spread rate estimators to predict future spread varies considerably between estimators, and with spatial configuration, invader biological parameters, and orchard behavior profile. The model suggests that understanding the latent factors inherent to dispersal is important for selecting phenomenological models of spread and interpreting estimation results. This indicates a need for caution when evaluating spread. Although standard practice, current empirical estimators may both over- and underestimate spread rate in the simulation.
ContributorsShanafelt, David William (Author) / Fenichel, Eli P (Thesis advisor) / Richards, Timothy (Committee member) / Janssen, Marco (Committee member) / Arizona State University (Publisher)
Created2012
Description
Collective decision making in social organism societies involves a large network of communication systems. Studying the processes behind the transmission of information allows for greater understanding of the decision making capabilities of a group. For Temnothorax rugatulus colonies, information is commonly spread in the form of tandem running, a linear recruitment pattern where a leading ant uses a short-ranged pheromone to direct a following ant to a target location (in tandem).The observed phenomenon of reverse tandem running (RTR), where a follower is lead from a target back to the home nest, has not been as extensively studied as forward tandem running and transportation recruitment activities. This study seeks to explain a potential reason for the presence of the RTR behavior; more specifically, the study explores the idea that reverse tandem run followers are being shown a specific route to the home nest by a highly experienced and efficient leading ant. Ten colonies had migrations induced experimentally in order to generate some reverse tandem running activity. Once an RTR has been observed, the follower and leader were studied for behavior and their pathways were analyzed. It was seen that while RTR paths were quite efficient (1.4x a straight line distance), followers did not experience a statistically significant improvement in their pathways between the home and target nests (based on total distance traveled) when compared to similar non-RTR ants. Further, RTR leading ants were no more efficient than other non-RTR ants. It was observed that some followers began recruiting after completion of an RTR, but the number than changed their behavior was not significant. Thus, the results of this experiment cannot conclusively show that RTR followers are utilizing reverse tandem runs to improve their routes between the home and target nests.
ContributorsColling, Blake David (Author) / Pratt, Stephen (Thesis director) / Liebig, Juergen (Committee member) / Sasaki, Takao (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2014-12
Description
Evolutionary theory predicts that animal behavior is generally governed by decision rules (heuristics) which adhere to ecological rationality: the tendency to make decisions that maximize fitness in most situations the animal encounters. However, the particular heuristics used by ant colonies of the genus Temnothorax and their propensity towards ecological rationality are up for debate. These ants are adept at choosing a nest site, making a collective decision based on complex interactions between the many individual choices made by workers. Colonies will migrate between nests either upon the destruction of their current home or the discovery of a sufficiently superior nest. This study offers a descriptive analysis of the heuristics potentially used in nest-site decision-making. Colonies were offered a choice of nests characterized by the Ebbinghaus Illusion: a perceptual illusion which effectively causes the viewer to perceive a circle as larger when it is surrounded by small circles than when that same circle is surrounded by large circles. Colonies were separated into two conditions: in one, they were given the option to move to a high-quality nest surrounded by poor-quality nests, and in the other they were given the option to move to a high-quality nest surrounded by medium-quality nests. The colonies in the poor condition were found to be more likely to move to the good nest than were colonies in the medium condition at a statistically significant level. That is, they responded to the Ebbinghaus Effect in the way that is normally expected. This result was discussed in terms of its implications for the ecological rationality of the nest-site choice behavior of these ants.
ContributorsTalken, Lucas Warren (Author) / Pratt, Stephen (Thesis director) / Sasaki, Takao (Committee member) / Liebig, Juergen (Committee member) / Barrett, The Honors College (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Department of Psychology (Contributor) / Economics Program in CLAS (Contributor)
Created2014-05
DescriptionThis paper provides an analysis of the differences in impacts made by companies that promote their sustainability efforts. A comparison of companies reveals that the ones with greater supply chain influence and larger consumer bases can make more concrete progress in terms of accomplishment for the sustainability realm.
ContributorsBeaubien, Courtney Lynn (Author) / Anderies, John (Thesis director) / Allenby, Brad (Committee member) / Janssen, Marco (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2013-05
Description
The evolution of cooperation is a fundamental problem in biology, especially for non-relatives, where indirect fitness benefits cannot counter within-group inequalities. Multilevel selection models show how cooperation can evolve if it generates a group-level advantage, even when cooperators are disadvantaged within their group. This allows the possibility of group selection, but few examples have been described in nature. Here we show that group selection can explain the evolution of cooperative nest founding in the harvester ant Pogonomyrmex californicus. Through most of this species’ range, colonies are founded by single queens, but in some populations nests are instead founded by cooperative groups of unrelated queens. In mixed groups of cooperative and single-founding queens, we found that aggressive individuals had a survival advantage within their nest, but foundress groups with such non-cooperators died out more often than those with only cooperative members. An agent-based model shows that the between-group advantage of the cooperative phenotype drives it to fixation, despite its within-group disadvantage, but only when population density is high enough to make between-group competition intense. Field data show higher nest density in a population where cooperative founding is common, consistent with greater density driving the evolution of cooperative foundation through group selection.
ContributorsShaffer, Zachary (Author) / Sasaki, Takao (Author) / Haney, Brian (Author) / Janssen, Marco (Author) / Pratt, Stephen (Author) / Fewell, Jennifer (Author) / College of Liberal Arts and Sciences (Contributor)
Created2016-07-28
Description
Climate change presents the urgent need for effective sustainable water management that is capable of preserving natural resources while maintaining economical stability. States like California rely heavily on groundwater pumping for agricultural use, contributing to land subsidence and insufficient returns to water resources. The recent California drought has impacted agricultural production of certain crops. In this thesis, we present an agent-based model of farmers adapting to drought conditions by making crop choice decisions, much like the decisions Californian farmers have made. We use the Netlogo platform to capture the 2D spatial view of an agricultural system with changes in annual rainfall due to drought conditions. The goal of this model is to understand some of the simple rules farmers may follow to self-govern their consumption of a water resource. Farmer agents make their crop decisions based on deficit irrigation crop production function and a net present value discount rate. The farmers choose between a thirsty crop with a high production cost and a dry crop with a low production cost. Simulations results show that farmers switch crops in accordance with limited water and land resources. Farmers can maintain profit and yield by following simple rules of crop switching based on future yields and optimal irrigation. In drought conditions, individual agents expecting lower annual rainfall were able to increase their total profits. The maintenance of crop yield and profit is evidence of successful adaptation when farmers switch to crops that require less water.
ContributorsGokool, Rachael Shanta (Author) / Janssen, Marco (Thesis director) / Eakin, Hallie (Committee member) / School of Human Evolution and Social Change (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Mathematical epidemiology, one of the oldest and richest areas in mathematical biology, has significantly enhanced our understanding of how pathogens emerge, evolve, and spread. Classical epidemiological models, the standard for predicting and managing the spread of infectious disease, assume that contacts between susceptible and infectious individuals depend on their relative frequency in the population. The behavioral factors that underpin contact rates are not generally addressed. There is, however, an emerging a class of models that addresses the feedbacks between infectious disease dynamics and the behavioral decisions driving host contact. Referred to as “economic epidemiology” or “epidemiological economics,” the approach explores the determinants of decisions about the number and type of contacts made by individuals, using insights and methods from economics. We show how the approach has the potential both to improve predictions of the course of infectious disease, and to support development of novel approaches to infectious disease management.
ContributorsPerrings, Charles (Author) / Castillo-Chavez, Carlos (Author) / Chowell-Puente, Gerardo (Author) / Daszak, Peter (Author) / Fenichel, Eli P. (Author) / Finnoff, David (Author) / Horan, Richard D. (Author) / Kilpatrick, A. Marm (Author) / Kinzig, Ann (Author) / Kuminoff, Nicolai (Author) / Levin, Simon (Author) / Morin, Benjamin (Author) / Smith, Katherine F. (Author) / Springborn, Michael (Author) / Simon M. Levin Mathematical, Computational and Modeling Sciences Center (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / W.P. Carey School of Business (Contributor) / Economics (Contributor) / Julie Ann Wrigley Global Institute of Sustainability (Contributor)
Created2015-12-01