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Preserving a system’s viability in the presence of diversity erosion is critical if the goal is to sustainably support biodiversity. Reduction in population heterogeneity, whether inter- or intraspecies, may increase population fragility, either decreasing its ability to adapt effectively to environmental changes or facilitating the survival and success of ordinarily

Preserving a system’s viability in the presence of diversity erosion is critical if the goal is to sustainably support biodiversity. Reduction in population heterogeneity, whether inter- or intraspecies, may increase population fragility, either decreasing its ability to adapt effectively to environmental changes or facilitating the survival and success of ordinarily rare phenotypes. The latter may result in over-representation of individuals who may participate in resource utilization patterns that can lead to over-exploitation, exhaustion, and, ultimately, collapse of both the resource and the population that depends on it. Here, we aim to identify regimes that can signal whether a consumer–resource system is capable of supporting viable degrees of heterogeneity. The framework used here is an expansion of a previously introduced consumer–resource type system of a population of individuals classified by their resource consumption. Application of the Reduction Theorem to the system enables us to evaluate the health of the system through tracking both the mean value of the parameter of resource (over)consumption, and the population variance, as both change over time. The article concludes with a discussion that highlights applicability of the proposed system to investigation of systems that are affected by particularly devastating overly adapted populations, namely cancerous cells. Potential intervention approaches for system management are discussed in the context of cancer therapies.
Created2015-02-01
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Evolving Earth observation and change detection techniques enable the automatic identification of Land Use and Land Cover Change (LULCC) over a large extent from massive amounts of remote sensing data. It at the same time poses a major challenge in effective organization, representation and modeling of such information. This study

Evolving Earth observation and change detection techniques enable the automatic identification of Land Use and Land Cover Change (LULCC) over a large extent from massive amounts of remote sensing data. It at the same time poses a major challenge in effective organization, representation and modeling of such information. This study proposes and implements an integrated computational framework to support the modeling, semantic and spatial reasoning of change information with regard to space, time and topology. We first proposed a conceptual model to formally represent the spatiotemporal variation of change data, which is essential knowledge to support various environmental and social studies, such as deforestation and urbanization studies. Then, a spatial ontology was created to encode these semantic spatiotemporal data in a machine-understandable format. Based on the knowledge defined in the ontology and related reasoning rules, a semantic platform was developed to support the semantic query and change trajectory reasoning of areas with LULCC. This semantic platform is innovative, as it integrates semantic and spatial reasoning into a coherent computational and operational software framework to support automated semantic analysis of time series data that can go beyond LULC datasets. In addition, this system scales well as the amount of data increases, validated by a number of experimental results. This work contributes significantly to both the geospatial Semantic Web and GIScience communities in terms of the establishment of the (web-based) semantic platform for collaborative question answering and decision-making.
Created2016-10-25
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Description
The growth rate hypothesis (GRH) proposes that higher growth rate (the rate of change in biomass per unit biomass, μ) is associated with higher P concentration and lower C∶P and N∶P ratios. However, the applicability of the GRH to vascular plants is not well-studied and few studies have been done

The growth rate hypothesis (GRH) proposes that higher growth rate (the rate of change in biomass per unit biomass, μ) is associated with higher P concentration and lower C∶P and N∶P ratios. However, the applicability of the GRH to vascular plants is not well-studied and few studies have been done on belowground biomass. Here we showed that, for aboveground, belowground and total biomass of three study species, μ was positively correlated with N∶C under N limitation and positively correlated with P∶C under P limitation. However, the N∶P ratio was a unimodal function of μ, increasing for small values of μ, reaching a maximum, and then decreasing. The range of variations in μ was positively correlated with variation in C∶N∶P stoichiometry. Furthermore, μ and C∶N∶P ranges for aboveground biomass were negatively correlated with those for belowground. Our results confirm the well-known association of growth rate with tissue concentration of the limiting nutrient and provide empirical support for recent theoretical formulations.
ContributorsYu, Qiang (Author) / Wu, Honghui (Author) / He, Nianpeng (Author) / Lu, Xiaotao (Author) / Wang, Zhiping (Author) / Elser, James (Author) / Wu, Jianguo (Author) / Han, Xingguo (Author) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / Julie Ann Wrigley Global Institute of Sustainability (Contributor) / School of Sustainability (Contributor)
Created2012-03-13
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Description
Nitrogen (N) and phosphorus (P) are important limiting nutrients for plant production and consumer performance in a variety of ecosystems. As a result, the N:P stoichiometry of herbivores has received increased attention in ecology. However, the mechanisms by which herbivores maintain N:P stoichiometric homeostasis are poorly understood. Here, using a

Nitrogen (N) and phosphorus (P) are important limiting nutrients for plant production and consumer performance in a variety of ecosystems. As a result, the N:P stoichiometry of herbivores has received increased attention in ecology. However, the mechanisms by which herbivores maintain N:P stoichiometric homeostasis are poorly understood. Here, using a field manipulation experiment we show that the grasshopper Oedaleus asiaticus maintains strong N:P stoichiometric homeostasis regardless of whether grasshoppers were reared at low or high density. Grasshoppers maintained homeostasis by increasing P excretion when eating plants with higher P contents. However, while grasshoppers also maintained constant body N contents, we found no changes in N excretion in response to changing plant N content over the range measured. These results suggest that O. asiaticus maintains P homeostasis primarily by changing P absorption and excretion rates, but that other mechanisms may be more important for regulating N homeostasis. Our findings improve our understanding of consumer-driven P recycling and may help in understanding the factors affecting plant-herbivore interactions and ecosystem processes in grasslands.
ContributorsZhang, Zijia (Author) / Elser, James (Author) / Cease, Arianne (Author) / Zhang, Ximei (Author) / Yu, Qiang (Author) / Han, Xingguo (Author) / Zhang, Guangming (Author) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / Julie Ann Wrigley Global Institute of Sustainability (Contributor) / School of Sustainability (Contributor)
Created2014-08-04
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Description
A large fraction of the world grasslands and savannas are undergoing a rapid shift from herbaceous to woody-plant dominance. This land-cover change is expected to lead to a loss in livestock production (LP), but the impacts of woody-plant encroachment on this crucial ecosystem service have not been assessed. We evaluate

A large fraction of the world grasslands and savannas are undergoing a rapid shift from herbaceous to woody-plant dominance. This land-cover change is expected to lead to a loss in livestock production (LP), but the impacts of woody-plant encroachment on this crucial ecosystem service have not been assessed. We evaluate how tree cover (TC) has affected LP at large spatial scales in rangelands of contrasting social–economic characteristics in the United States and Argentina. Our models indicate that in areas of high productivity, a 1% increase in TC results in a reduction in LP ranging from 0.6 to 1.6 reproductive cows (Rc) per km[superscript 2]. Mean LP in the United States is 27 Rc per km[superscript 2], so a 1% increase in TC results in a 2.5% decrease in mean LP. This effect is large considering that woody-plant cover has been described as increasing at 0.5% to 2% per y. On the contrary, in areas of low productivity, increased TC had a positive effect on LP. Our results also show that ecological factors account for a larger fraction of LP variability in Argentinean than in US rangelands. Differences in the relative importance of ecological versus nonecological drivers of LP in Argentina and the United States suggest that the valuation of ecosystem services between these two rangelands might be different. Current management strategies in Argentina are likely designed to maximize LP for various reasons we are unable to explore in this effort, whereas land managers in the United States may be optimizing multiple ecosystem services, including conservation or recreation, alongside LP.
Created2014-09-02
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Description
We studied the microbial community structure of pilot two-stage membrane biofilm reactors (MBfRs) designed to reduce nitrate (NO[subscript 3]–) and perchlorate (ClO[subscript 4]–) in contaminated groundwater. The groundwater also contained oxygen (O[subscript 2]) and sulfate (SO[2 over 4]–), which became important electron sinks that affected the NO[subscript 3]– and ClO[subscript

We studied the microbial community structure of pilot two-stage membrane biofilm reactors (MBfRs) designed to reduce nitrate (NO[subscript 3]–) and perchlorate (ClO[subscript 4]–) in contaminated groundwater. The groundwater also contained oxygen (O[subscript 2]) and sulfate (SO[2 over 4]–), which became important electron sinks that affected the NO[subscript 3]– and ClO[subscript 4]– removal rates. Using pyrosequencing, we elucidated how important phylotypes of each “primary” microbial group, i.e., denitrifying bacteria (DB), perchlorate-reducing bacteria (PRB), and sulfate-reducing bacteria (SRB), responded to changes in electron-acceptor loading. UniFrac, principal coordinate analysis (PCoA), and diversity analyses documented that the microbial community of biofilms sampled when the MBfRs had a high acceptor loading were phylogenetically distant from and less diverse than the microbial community of biofilm samples with lower acceptor loadings. Diminished acceptor loading led to SO[2 over 4]– reduction in the lag MBfR, which allowed Desulfovibrionales (an SRB) and Thiothrichales (sulfur-oxidizers) to thrive through S cycling. As a result of this cooperative relationship, they competed effectively with DB/PRB phylotypes such as Xanthomonadales and Rhodobacterales. Thus, pyrosequencing illustrated that while DB, PRB, and SRB responded predictably to changes in acceptor loading, a decrease in total acceptor loading led to important shifts within the “primary” groups, the onset of other members (e.g., Thiothrichales), and overall greater diversity.
Created2014-07-01
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Description

The City of Phoenix Street Transportation Department partnered with the Rob and Melani Walton Sustainability Solutions Service at Arizona State University (ASU) and researchers from various ASU schools to evaluate the effectiveness, performance, and community perception of the new pavement coating. The data collection and analysis occurred across multiple neighborhoods

The City of Phoenix Street Transportation Department partnered with the Rob and Melani Walton Sustainability Solutions Service at Arizona State University (ASU) and researchers from various ASU schools to evaluate the effectiveness, performance, and community perception of the new pavement coating. The data collection and analysis occurred across multiple neighborhoods and at varying times across days and/or months over the course of one year (July 15, 2020–July 14, 2021), allowing the team to study the impacts of the surface treatment under various weather conditions.

Created2021-09
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Description
Solar energy has become one of the most popular renewable energy in human’s life because of its abundance and environment friendliness. To achieve high solar energy conversion efficiency, it usually requires surfaces to absorb selectivity within one spectral range of interest and reflect strongly over the rest of the spectrum.

Solar energy has become one of the most popular renewable energy in human’s life because of its abundance and environment friendliness. To achieve high solar energy conversion efficiency, it usually requires surfaces to absorb selectivity within one spectral range of interest and reflect strongly over the rest of the spectrum. An economic method is always desired to fabricate spectrally selective surfaces with improved energy conversion efficiency. Colloidal lithography is a recently emerged way of nanofabrication, which has advantages of low-cost and easy operation.

In this thesis, aluminum metasurface structures are proposed based on colloidal lithography method. High Frequency Structure Simulator is used to numerically study optical properties and design the aluminum metasurfaces with selective absorption. Simulation results show that proposed aluminum metasurface structure on aluminum oxide thin film and aluminum substrate has a major reflectance dip, whose wavelength is tunable within the near-infrared and visible spectrum with metasurface size. As the metasurface is opaque due to aluminum film, it indicates strong wavelength-selective optical absorption, which is due to the magnetic resonance between the top metasurface and bottom Al film within the aluminum oxide layer.

The proposed sample is fabricated based on colloidal lithography method. Monolayer polystyrene particles of 500 nm are successfully prepared and transferred onto silicon substrate. Scanning electron microscope is used to check the surface topography. Aluminum thin film with 20-nm or 50-nm thickness is then deposited on the sample. After monolayer particles are removed, optical properties of samples are measured by micro-scale optical reflectance and transmittance microscope. Measured and simulated reflectance of these samples do not have frequency selective properties and is not sensitive to defects. The next step is to fabricate the Al metasurface on Al_2 O_3 and Al films to experimentally demonstrate the selective absorption predicted from the numerical simulation.
ContributorsGuan, Chuyun (Author) / Wang, Liping (Thesis advisor) / Azeredo, Bruno (Committee member) / Wang, Robert (Committee member) / Arizona State University (Publisher)
Created2019
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Description
Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination

Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination of simpler behaviors. It is tempting to apply similar idea such that simpler behaviors can be combined in a meaningful way to tailor the complex combination. Such an approach would enable faster learning and modular design of behaviors. Complex behaviors can be combined with other behaviors to create even more advanced behaviors resulting in a rich set of possibilities. Similar to RL, combined behavior can keep evolving by interacting with the environment. The requirement of this method is to specify a reasonable set of simple behaviors. In this research, I present an algorithm that aims at combining behavior such that the resulting behavior has characteristics of each individual behavior. This approach has been inspired by behavior based robotics, such as the subsumption architecture and motor schema-based design. The combination algorithm outputs n weights to combine behaviors linearly. The weights are state dependent and change dynamically at every step in an episode. This idea is tested on discrete and continuous environments like OpenAI’s “Lunar Lander” and “Biped Walker”. Results are compared with related domains like Multi-objective RL, Hierarchical RL, Transfer learning, and basic RL. It is observed that the combination of behaviors is a novel way of learning which helps the agent achieve required characteristics. A combination is learned for a given state and so the agent is able to learn faster in an efficient manner compared to other similar approaches. Agent beautifully demonstrates characteristics of multiple behaviors which helps the agent to learn and adapt to the environment. Future directions are also suggested as possible extensions to this research.
ContributorsVora, Kevin Jatin (Author) / Zhang, Yu (Thesis advisor) / Yang, Yezhou (Committee member) / Praharaj, Sarbeswar (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Biogas’s potential as a renewable fuel source has been an area of increased research in recent years. One issue preventing wide-spread use of biogas as a fuel is the trace amounts of impurities that damage fuel-burning equipment by depositing silicon, sulfur, calcium and other elements on their surface. This study

Biogas’s potential as a renewable fuel source has been an area of increased research in recent years. One issue preventing wide-spread use of biogas as a fuel is the trace amounts of impurities that damage fuel-burning equipment by depositing silicon, sulfur, calcium and other elements on their surface. This study aims to analyze the effects of a high concentration of L4 linear siloxane on solid oxide fuel cell performance until failure occurs. L4 siloxane has not been extensively researched previously, and this investigation aims to provide new data to support similar, though slower, degradation compared to D4, D5 and other siloxanes in solid oxide fuel cells. The experiments were conducted inside a furnace heated to 800℃ with an Ni-YSZ-supported (Nickel-yttria-stabilized zirconia) fuel cell. A fuel source with a flow rate of 20 mL/min of hydrogen gas, 10 mL/min of nitrogen gas and 0.15 mL/min of L4 siloxane was used. Air was supplied to the cathode. The effects of siloxane deposition on cell voltage and power density degradation and resistance increase were studied by using techniques like the current-voltage method, electrochemical impedance spectroscopy, and gas chromatography. The results of the experiment after reduction show roughly constant degradation of 8.35 mV/hr, followed after approximately 8 hours by an increasing degradation until cell failure of 130.45 mV/hr. The initial degradation and stagnation match previous research in siloxane deposition on SOFCs, but the sharp decline to failure does not. A mechanism for solid oxide fuel cell failure is proposed based on the data.
ContributorsRiley, Derall M. (Author) / Milcarek, Ryan J (Thesis advisor) / Wang, Liping (Committee member) / Phelan, Patrick E (Committee member) / Arizona State University (Publisher)
Created2021