Matching Items (140)
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The relationship between biodiversity and ecosystem functioning (BEF) is a central issue in ecology, and a number of recent field experimental studies have greatly improved our understanding of this relationship. Spatial heterogeneity is a ubiquitous characterization of ecosystem processes, and has played a significant role in shaping BEF relationships.

The relationship between biodiversity and ecosystem functioning (BEF) is a central issue in ecology, and a number of recent field experimental studies have greatly improved our understanding of this relationship. Spatial heterogeneity is a ubiquitous characterization of ecosystem processes, and has played a significant role in shaping BEF relationships. The first step towards understanding the effects of spatial heterogeneity on the BEF relationships is to quantify spatial heterogeneity characteristics of key variables of biodiversity and ecosystem functioning, and identify the spatial relationships among these variables. The goal of our research was to address the following research questions based on data collected in 2005 (corresponding to the year when the initial site background information was conducted) and in 2008 (corresponding to the year when removal treatments were conducted) from the Inner Mongolia Grassland Removal Experiment (IMGRE) located in northern China: 1) What are the spatial patterns of soil nutrients, plant biodiversity, and aboveground biomass in a natural grassland community of Inner Mongolia, China? How are they related spatially? and 2) How do removal treatments affect the spatial patterns of soil nutrients, plant biodiversity, and aboveground biomass? Is there any change for their spatial correlations after removal treatments? Our results showed that variables of biodiversity and ecosystem functioning in the natural grassland community would present different spatial patterns, and they would be spatially correlated to each other closely. Removal treatments had a significant effect on spatial structures and spatial correlations of variables, compared to those prior to the removal treatments. The differences in spatial pattern of plant and soil variables and their correlations before and after the biodiversity manipulation may not imply that the results from BEF experiments like IMGRE are invalid. However, they do suggest that the possible effects of spatial heterogeneity on the BEF relationships should be critically evaluated in future studies.
ContributorsYuan, Fei (Author) / Wu, Jianguo (Thesis advisor) / Smith, Andrew T. (Committee member) / Rowe, Helen I (Committee member) / Arizona State University (Publisher)
Created2011
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In this thesis I introduce a new direction to computing using nonlinear chaotic dynamics. The main idea is rich dynamics of a chaotic system enables us to (1) build better computers that have a flexible instruction set, and (2) carry out computation that conventional computers are not good at it.

In this thesis I introduce a new direction to computing using nonlinear chaotic dynamics. The main idea is rich dynamics of a chaotic system enables us to (1) build better computers that have a flexible instruction set, and (2) carry out computation that conventional computers are not good at it. Here I start from the theory, explaining how one can build a computing logic block using a chaotic system, and then I introduce a new theoretical analysis for chaos computing. Specifically, I demonstrate how unstable periodic orbits and a model based on them explains and predicts how and how well a chaotic system can do computation. Furthermore, since unstable periodic orbits and their stability measures in terms of eigenvalues are extractable from experimental times series, I develop a time series technique for modeling and predicting chaos computing from a given time series of a chaotic system. After building a theoretical framework for chaos computing I proceed to architecture of these chaos-computing blocks to build a sophisticated computing system out of them. I describe how one can arrange and organize these chaos-based blocks to build a computer. I propose a brand new computer architecture using chaos computing, which shifts the limits of conventional computers by introducing flexible instruction set. Our new chaos based computer has a flexible instruction set, meaning that the user can load its desired instruction set to the computer to reconfigure the computer to be an implementation for the desired instruction set. Apart from direct application of chaos theory in generic computation, the application of chaos theory to speech processing is explained and a novel application for chaos theory in speech coding and synthesizing is introduced. More specifically it is demonstrated how a chaotic system can model the natural turbulent flow of the air in the human speech production system and how chaotic orbits can be used to excite a vocal tract model. Also as another approach to build computing system based on nonlinear system, the idea of Logical Stochastic Resonance is studied and adapted to an autoregulatory gene network in the bacteriophage λ.
ContributorsKia, Behnam (Author) / Ditto, William (Thesis advisor) / Huang, Liang (Committee member) / Lai, Ying-Cheng (Committee member) / Helms Tillery, Stephen (Committee member) / Arizona State University (Publisher)
Created2011
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Over the past century in the southwestern United States human actions have altered hydrological processes that shape riparian ecosystems. One change, release of treated wastewater into waterways, has created perennial base flows and increased nutrient availability in ephemeral or intermittent channels. While there are benefits to utilizing treated wastewater for

Over the past century in the southwestern United States human actions have altered hydrological processes that shape riparian ecosystems. One change, release of treated wastewater into waterways, has created perennial base flows and increased nutrient availability in ephemeral or intermittent channels. While there are benefits to utilizing treated wastewater for environmental flows, there are numerous unresolved ecohydrological issues regarding the efficacy of effluent to sustain groundwater-dependent riparian ecosystems. This research examined how nutrient-rich effluent, released into waterways with varying depths to groundwater, influences riparian plant community development. Statewide analysis of spatial and temporal patterns of effluent generation and release revealed that hydrogeomorphic setting significantly influences downstream riparian response. Approximately 70% of effluent released is into deep groundwater systems, which produced the lowest riparian development. A greenhouse study assessed how varying concentrations of nitrogen and phosphorus, emulating levels in effluent, influenced plant community response. With increasing nitrogen concentrations, vegetation emerging from riparian seed banks had greater biomass, reduced species richness, and greater abundance of nitrophilic species. The effluent-dominated Santa Cruz River in southern Arizona, with a shallow groundwater upper reach and deep groundwater lower reach, served as a study river while the San Pedro River provided a control. Analysis revealed that woody species richness and composition were similar between the two systems. Hydric pioneers (Populus fremontii, Salix gooddingii) were dominant at perennial sites on both rivers. Nitrophilic species (Conium maculatum, Polygonum lapathifolium) dominated herbaceous plant communities and plant heights were greatest in effluent-dominated reaches. Riparian vegetation declined with increasing downstream distance in the upper Santa Cruz, while patterns in the lower Santa Cruz were confounded by additional downstream agricultural input and a channelized floodplain. There were distinct longitudinal and lateral shifts toward more xeric species with increasing downstream distance and increasing lateral distance from the low-flow channel. Patterns in the upper and lower Santa Cruz reaches indicate that water availability drives riparian vegetation outcomes below treatment facilities. Ultimately, this research informs decision processes and increases adaptive capacity for water resources policy and management through the integration of ecological data in decision frameworks regarding the release of effluent for environmental flows.
ContributorsWhite, Margaret Susan (Author) / Stromberg, Juliet C. (Thesis advisor) / Fisher, Stuart G. (Committee member) / White, Dave (Committee member) / Holway, James (Committee member) / Wu, Jianguo (Committee member) / Arizona State University (Publisher)
Created2011
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Hydrology and biogeochemistry are coupled in all systems. However, human decision-making regarding hydrology and biogeochemistry are often separate, even though decisions about hydrologic systems may have substantial impacts on biogeochemical patterns and processes. The overarching question of this dissertation was: How does hydrologic engineering interact with the effects of nutrient

Hydrology and biogeochemistry are coupled in all systems. However, human decision-making regarding hydrology and biogeochemistry are often separate, even though decisions about hydrologic systems may have substantial impacts on biogeochemical patterns and processes. The overarching question of this dissertation was: How does hydrologic engineering interact with the effects of nutrient loading and climate to drive watershed nutrient yields? I conducted research in two study systems with contrasting spatial and temporal scales. Using a combination of data-mining and modeling approaches, I reconstructed nitrogen and phosphorus budgets for the northeastern US over the 20th century, including anthropogenic nutrient inputs and riverine fluxes, for ~200 watersheds at 5 year time intervals. Infrastructure systems, such as sewers, wastewater treatment plants, and reservoirs, strongly affected the spatial and temporal patterns of nutrient fluxes from northeastern watersheds. At a smaller scale, I investigated the effects of urban stormwater drainage infrastructure on water and nutrient delivery from urban watersheds in Phoenix, AZ. Using a combination of field monitoring and statistical modeling, I tested hypotheses about the importance of hydrologic and biogeochemical control of nutrient delivery. My research suggests that hydrology is the major driver of differences in nutrient fluxes from urban watersheds at the event scale, and that consideration of altered hydrologic networks is critical for understanding anthropogenic impacts on biogeochemical cycles. Overall, I found that human activities affect nutrient transport via multiple pathways. Anthropogenic nutrient additions increase the supply of nutrients available for transport, whereas hydrologic infrastructure controls the delivery of nutrients from watersheds. Incorporating the effects of hydrologic infrastructure is critical for understanding anthropogenic effects on biogeochemical fluxes across spatial and temporal scales.

ContributorsHale, Rebecca Leslie (Author) / Grimm, Nancy (Thesis advisor) / Childers, Daniel (Committee member) / Vivoni, Enrique (Committee member) / York, Abigail (Committee member) / Wu, Jianguo (Committee member) / Arizona State University (Publisher)
Created2013
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Complex dynamical systems consisting interacting dynamical units are ubiquitous in nature and society. Predicting and reconstructing nonlinear dynamics of units and the complex interacting networks among them serves the base for the understanding of a variety of collective dynamical phenomena. I present a general method to address the two outstanding

Complex dynamical systems consisting interacting dynamical units are ubiquitous in nature and society. Predicting and reconstructing nonlinear dynamics of units and the complex interacting networks among them serves the base for the understanding of a variety of collective dynamical phenomena. I present a general method to address the two outstanding problems as a whole based solely on time-series measurements. The method is implemented by incorporating compressive sensing approach that enables an accurate reconstruction of complex dynamical systems in terms of both nodal equations that determines the self-dynamics of units and detailed coupling patterns among units. The representative advantages of the approach are (i) the sparse data requirement which allows for a successful reconstruction from limited measurements, and (ii) general applicability to identical and nonidentical nodal dynamics, and to networks with arbitrary interacting structure, strength and sizes. Another two challenging problem of significant interest in nonlinear dynamics: (i) predicting catastrophes in nonlinear dynamical systems in advance of their occurrences and (ii) predicting the future state for time-varying nonlinear dynamical systems, can be formulated and solved in the framework of compressive sensing using only limited measurements. Once the network structure can be inferred, the dynamics behavior on them can be investigated, for example optimize information spreading dynamics, suppress cascading dynamics and traffic congestion, enhance synchronization, game dynamics, etc. The results can yield insights to control strategies design in the real-world social and natural systems. Since 2004, there has been a tremendous amount of interest in graphene. The most amazing feature of graphene is that there exists linear energy-momentum relationship when energy is low. The quasi-particles inside the system can be treated as chiral, massless Dirac fermions obeying relativistic quantum mechanics. Therefore, the graphene provides one perfect test bed to investigate relativistic quantum phenomena, such as relativistic quantum chaotic scattering and abnormal electron paths induced by klein tunneling. This phenomenon has profound implications to the development of graphene based devices that require stable electronic properties.
ContributorsYang, Rui (Author) / Lai, Ying-Cheng (Thesis advisor) / Duman, Tolga M. (Committee member) / Akis, Richard (Committee member) / Huang, Liang (Committee member) / Arizona State University (Publisher)
Created2012
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What can classical chaos do to quantum systems is a fundamental issue highly relevant to a number of branches in physics. The field of quantum chaos has been active for three decades, where the focus was on non-relativistic quantumsystems described by the Schr¨odinger equation. By developing an efficient method to

What can classical chaos do to quantum systems is a fundamental issue highly relevant to a number of branches in physics. The field of quantum chaos has been active for three decades, where the focus was on non-relativistic quantumsystems described by the Schr¨odinger equation. By developing an efficient method to solve the Dirac equation in the setting where relativistic particles can tunnel between two symmetric cavities through a potential barrier, chaotic cavities are found to suppress the spread in the tunneling rate. Tunneling rate for any given energy assumes a wide range that increases with the energy for integrable classical dynamics. However, for chaotic underlying dynamics, the spread is greatly reduced. A remarkable feature, which is a consequence of Klein tunneling, arise only in relativistc quantum systems that substantial tunneling exists even for particle energy approaching zero. Similar results are found in graphene tunneling devices, implying high relevance of relativistic quantum chaos to the development of such devices. Wave propagation through random media occurs in many physical systems, where interesting phenomena such as branched, fracal-like wave patterns can arise. The generic origin of these wave structures is currently a matter of active debate. It is of fundamental interest to develop a minimal, paradigmaticmodel that can generate robust branched wave structures. In so doing, a general observation in all situations where branched structures emerge is non-Gaussian statistics of wave intensity with an algebraic tail in the probability density function. Thus, a universal algebraic wave-intensity distribution becomes the criterion for the validity of any minimal model of branched wave patterns. Coexistence of competing species in spatially extended ecosystems is key to biodiversity in nature. Understanding the dynamical mechanisms of coexistence is a fundamental problem of continuous interest not only in evolutionary biology but also in nonlinear science. A continuous model is proposed for cyclically competing species and the effect of the interplay between the interaction range and mobility on coexistence is investigated. A transition from coexistence to extinction is uncovered with a non-monotonic behavior in the coexistence probability and switches between spiral and plane-wave patterns arise. Strong mobility can either promote or hamper coexistence, while absent in lattice-based models, can be explained in terms of nonlinear partial differential equations.
ContributorsNi, Xuan (Author) / Lai, Ying-Cheng (Thesis advisor) / Huang, Liang (Committee member) / Yu, Hongbin (Committee member) / Akis, Richard (Committee member) / Arizona State University (Publisher)
Created2012
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It is important to consider factors that contribute to successful fertilization and the development of viable offspring. Better understanding the factors that contribute to infertility can be used to assist in the development of viable offspring, especially for human beings looking to successfully reproduce. Identifying paternal effect genes, genes that

It is important to consider factors that contribute to successful fertilization and the development of viable offspring. Better understanding the factors that contribute to infertility can be used to assist in the development of viable offspring, especially for human beings looking to successfully reproduce. Identifying paternal effect genes, genes that come from the father, introduces more targets that can be manipulated to produce specific reproductive effects. Use of Drosophila melanogaster as a model to study reproduction has increased, in part, due to the use of the GAL4 system. In this system, the GAL4 gene encodes an 881 amino acid protein that binds to the 4-site Upstream Activating Sequence (UAS) to induce transcription of the gene of interest. These sequences constitute the two components of the system: the driver (GAL4) and the responder (gene of interest) \u2014 each of which is maintained as a separate parental line. Effects of the GAL4 driver line "driving" transcription of the responder can be assessed by examining the offspring. One of the more common uses of the GAL4 system involves analyzing phenotypic effects of reducing or eliminating expression of a target gene through the induction of RNAi transcription, which often results in toxicity, lethality, or reduced viability. Utilizing these principles, we strove to demonstrate the effect of knocking down the expression of testis-specific sperm-leucyl-aminopeptidases gene CG13340 on progeny by inducing expression of RNAi with two distinct GAL4 driver lines - one with a nonspecific actin-binding activation sequence and the other with a testis-specific activation sequence. Comparison of both GAL4 driver lines to crosses using N01 wild type ("wt") flies verify that inducing RNAi transcription using the GAL4 system results in reduction of proper offspring development. Further studies using D. melanogaster and the GAL4 system can improve knowledge of factors contributing to male fertility and also be applied to better understand mammalian, specifically human, fertility.
ContributorsEvans, Donna Marie (Author) / Karr, Timothy L. (Thesis director) / Roland, Kenneth (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor) / Department of English (Contributor)
Created2014-05
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China’s South–North Water Transfer Project (SNWTP) has the potential to transfer as much as 44.8 km3 year-1 of water from the Yangtze River basin to the Yellow River basin. However, the SNWTP has not been assessed from a sustainability perspective. Thus, in this study we evaluated the SNWTP’s economic, social,

China’s South–North Water Transfer Project (SNWTP) has the potential to transfer as much as 44.8 km3 year-1 of water from the Yangtze River basin to the Yellow River basin. However, the SNWTP has not been assessed from a sustainability perspective. Thus, in this study we evaluated the SNWTP’s economic, social, and environmental impacts by reviewing the English literature published in journals that are part of the Web of Science database. We then synthesized this literature using a Triple Bottom Line framework of sustainability assessment. Our study has led to three main findings: (1) whether the SNWTP is economically beneficial depends largely on model assumptions, meaning that economic gains at the regional and national level are uncertain; (2) the SNWTP requires the resettlement of hundreds of thousands of people and challenges existing water management institutions, suggesting possible social concerns beyond the short term; and (3) evidently large environmental costs in water-providing areas and uncertain environmental benefits in water-receiving areas together point to an uncertain environmental future for the geographic regions involved. Thus, the overall sustainability of SNWTP is seriously questionable. Although much work has been done studying individual aspects of SNWTP’s sustainability, few studies have utilized the multi-scale, transdisciplinary approaches that such a project demands. To minimize environmental risks, ensure social equity, and sustain economic benefits, we suggest that the project be continuously monitored in all three dimensions, and that integrated sustainability assessments and policy improvements be carried out periodically.

ContributorsWilson, Maxwell (Author) / Li, Xiao-Yan (Author) / Ma, Yu-Jun (Author) / Smith, Andrew (Author) / Wu, Jianguo (Author) / College of Liberal Arts and Sciences (Contributor)
Created2017-08-22
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The highly-social plateau pika (Lagomorpha: Ochotona curzoniae) excavates vast burrow complexes in alpine meadows on the Tibetan Plateau. Colonies of over 300 individuals/ha have been reported. As an ecosystem engineer, their burrowing may positively impact ecosystem health by increasing plant species diversity, enhancing soil mixing, and boosting water infiltration. However,

The highly-social plateau pika (Lagomorpha: Ochotona curzoniae) excavates vast burrow complexes in alpine meadows on the Tibetan Plateau. Colonies of over 300 individuals/ha have been reported. As an ecosystem engineer, their burrowing may positively impact ecosystem health by increasing plant species diversity, enhancing soil mixing, and boosting water infiltration. However, pikas are commonly regarded as pests, and are heavily poisoned throughout their range. The underlying assumption of eradication programs is that eliminating pikas will improve rangeland quality and decrease soil erosion. This dissertation explores the link between plateau pikas and the alpine meadow ecosystem in Qinghai Province, PRC. This research uses both comparative field studies and theoretical modeling to clarify the role of pika disturbance. Specifically, these studies quantify the impact of pikas on nutrient cycling (via nutrient concentrations of vegetation and soil), hydrology (via water infiltration), local landscape properties (via spatial pattern description), and vascular plant communities (via species richness and composition). The competitive relationship between livestock and pikas is examined with a mathematical model. Results of this research indicate that pika colonies have both local and community level effects on water infiltration and plant species richness. A major contribution of pika disturbance is increased spatial heterogeneity, which likely underlies differences in the plant community. These findings suggest that the positive impact of plateau pikas on rangeland resources has been undervalued. In concurrence with other studies, this work concludes that plateau pikas provide valuable ecosystem services on the Tibetan Plateau.
ContributorsHogan, Brigitte Wieshofer (Author) / Smith, Andrew T. (Thesis advisor) / Anderies, J. Marty (Committee member) / Briggs, John M. (Committee member) / Stromberg, Juliet C. (Committee member) / Wu, Jianguo (Committee member) / Arizona State University (Publisher)
Created2010
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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

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.
Created2015-12-01