Attitudes towards the marine environment and implications for marine resource management in Seward, Alaska

This research, conducted in 2006-2008, examines the ways in which various groups involved with the marine resources of Seward, Alaska construct attitudes towards the environment. Participant observation and semi-structured interviews are used to assess how commercial halibut fishers, tour boat operators, local residents and government officials understand the marine environment based on their previous experiences. This study also explores how ideologies relate to the current practices of each group. Two theories orient the analyses: The first, cultural modeling provided a theoretical and methodological framework for pursuing a more comprehensive analysis of resource management. The second, Theory of Reasoned Action (Ajzen and Fishbein 1980), guided the analysis of the ways in which each participant’s ideology towards the marine environment relates to their practice. Aside from contributing to a better understanding of a coastal community’s ideologies and practices, this dissertation sought to better understand the role of ecological ideologies and behaviors in fisheries management. The research illustrates certain domains where ideologies and practices concerning Pacific halibut and the marine environment differ among commercial fishers, government, and management officials, tour boat operators and residents of Seward, AK. These differences offer insights into how future collaborative efforts between government officials, managers and local marine resource users might better incorporate local ideology into management, and provide ecological information to local marine resource users in culturally appropriate ways.

Assessment of natural resource conditions in and adjacent to Biscayne National Park. Natural Resource Report NPS/BISC/NRR—2012/598

This report is an assessment of the conditions of natural resources in Biscayne National Park (BNP) based on the compilation, review and evaluation of existing information on the Park’s natural resources. This review evaluates threats and stressors, and is intended to improve understanding of BNP resources to help guide Park management to address the identified threats, which are supported by enhanced data collection, research and assessment efforts. The report is focused on broad resource components, namely terrestrial resources and aquatic systems including: wetlands, canals, bay waters, marine/reef areas and ground waters. Biotic and abiotic resource components are considered in the review.

Land Use and Climate Change Impacts on the Hydrology of the Upper Mara River Basin, Kenya: Results of a Modeling Study to Support Better Resource Management

Some of the most valued natural and cultural landscapes on Earth lie in river basins that are poorly gauged and have incomplete historical climate and runoff records. The Mara River Basin of East Africa is such a basin. It hosts the internationally renowned Mara-Serengeti landscape as well as a rich mixture of indigenous cultures. The Mara River is the sole source of surface water to the landscape during the dry season and periods of drought. During recent years, the flow of the Mara River has become increasingly erratic, especially in the upper reaches, and resource managers are hampered by a lack of understanding of the relative influence of different sources of flow alteration. Uncertainties about the impacts of future climate change compound the challenges. We applied the Soil Water Assessment Tool (SWAT) to investigate the response of the headwater hydrology of the Mara River to scenarios of continued land use change and projected climate change. Under the data-scarce conditions of the basin, model performance was improved using satellite-based estimated rainfall data, which may also improve the usefulness of runoff models in other parts of East Africa. The results of the analysis indicate that any further conversion of forests to agriculture and grassland in the basin headwaters is likely to reduce dry season flows and increase peak flows, leading to greater water scarcity at critical times of the year and exacerbating erosion on hillslopes. Most climate change projections for the region call for modest and seasonally variable increases in precipitation (5–10 %) accompanied by increases in temperature (2.5–3.5 °C). Simulated runoff responses to climate change scenarios were non-linear and suggest the basin is highly vulnerable under low (−3 %) and high (+25 %) extremes of projected precipitation changes, but under median projections (+7 %) there is little impact on annual water yields or mean discharge. Modest increases in precipitation are partitioned largely to increased evapotranspiration. Overall, model results support the existing efforts of Mara water resource managers to protect headwater forests and indicate that additional emphasis should be placed on improving land management practices that enhance infiltration and aquifer recharge as part of a wider program of climate change adaptation.

System design and resource management in the next-generation integrated WLAN and 3G cellular networks

Next-generation integrated wireless local area network (WLAN) and 3G cellular networks aim to take advantage of the roaming ability in a cellular network and the high data rate services of a WLAN. To ensure successful implementation of an integrated network, many issues must be carefully addressed, including network architecture design, resource management, quality-of-service (QoS), call admission control (CAC) and mobility management. ^ This dissertation focuses on QoS provisioning, CAC, and the network architecture design in the integration of WLANs and cellular networks. First, a new scheduling algorithm and a call admission control mechanism in IEEE 802.11 WLAN are presented to support multimedia services with QoS provisioning. The proposed scheduling algorithms make use of the idle system time to reduce the average packet loss of realtime (RT) services. The admission control mechanism provides long-term transmission quality for both RT and NRT services by ensuring the packet loss ratio for RT services and the throughput for non-real-time (NRT) services. ^ A joint CAC scheme is proposed to efficiently balance traffic load in the integrated environment. A channel searching and replacement algorithm (CSR) is developed to relieve traffic congestion in the cellular network by using idle channels in the WLAN. The CSR is optimized to minimize the system cost in terms of the blocking probability in the interworking environment. Specifically, it is proved that there exists an optimal admission probability for passive handoffs that minimizes the total system cost. Also, a method of searching the probability is designed based on linear-programming techniques. ^ Finally, a new integration architecture, Hybrid Coupling with Radio Access System (HCRAS), is proposed for lowering the average cost of intersystem communication (IC) and the vertical handoff latency. An analytical model is presented to evaluate the system performance of the HCRAS in terms of the intersystem communication cost function and the handoff cost function. Based on this model, an algorithm is designed to determine the optimal route for each intersystem communication. Additionally, a fast handoff algorithm is developed to reduce the vertical handoff latency.^

Resource management and optimization in wireless mesh networks

A wireless mesh network is a mesh network implemented over a wireless network system such as wireless LANs. Wireless Mesh Networks(WMNs) are promising for numerous applications such as broadband home networking, enterprise networking, transportation systems, health and medical systems, security surveillance systems, etc. Therefore, it has received considerable attention from both industrial and academic researchers. This dissertation explores schemes for resource management and optimization in WMNs by means of network routing and network coding.^ In this dissertation, we propose three optimization schemes. (1) First, a triple-tier optimization scheme is proposed for load balancing objective. The first tier mechanism achieves long-term routing optimization, and the second tier mechanism, using the optimization results obtained from the first tier mechanism, performs the short-term adaptation to deal with the impact of dynamic channel conditions. A greedy sub-channel allocation algorithm is developed as the third tier optimization scheme to further reduce the congestion level in the network. We conduct thorough theoretical analysis to show the correctness of our design and give the properties of our scheme. (2) Then, a Relay-Aided Network Coding scheme called RANC is proposed to improve the performance gain of network coding by exploiting the physical layer multi-rate capability in WMNs. We conduct rigorous analysis to find the design principles and study the tradeoff in the performance gain of RANC. Based on the analytical results, we provide a practical solution by decomposing the original design problem into two sub-problems, flow partition problem and scheduling problem. (3) Lastly, a joint optimization scheme of the routing in the network layer and network coding-aware scheduling in the MAC layer is introduced. We formulate the network optimization problem and exploit the structure of the problem via dual decomposition. We find that the original problem is composed of two problems, routing problem in the network layer and scheduling problem in the MAC layer. These two sub-problems are coupled through the link capacities. We solve the routing problem by two different adaptive routing algorithms. We then provide a distributed coding-aware scheduling algorithm. According to corresponding experiment results, the proposed schemes can significantly improve network performance.^

Integrated assessment of water conservation practices for sustainable management strategies

Miami-Dade County implemented a series of water conservation programs, which included rebate/exchange incentives to encourage the use of high efficiency aerators (AR), showerheads (SH), toilets (HET) and clothes washers (HEW), to respond to the environmental sustainability issue in urban areas. This study first used panel data analysis of water consumption to evaluate the performance and actual water savings of individual programs. Integrated water demand model has also been developed for incorporating property’s physical characteristics into the water consumption profiles. Life cycle assessment (with emphasis on end-use stage in water system) of water intense appliances was conducted to determine the environmental impacts brought by each practice. Approximately 6 to 10 % of water has been saved in the first and second year of implementation of high efficiency appliances, and with continuing savings in the third and fourth years. Water savings (gallons per household per day) for water efficiency appliances were observed at 28 (11.1%) for SH, 34.7 (13.3%) for HET, and 39.7 (14.5%) for HEW. Furthermore, the estimated contributions of high efficiency appliances for reducing water demand in the integrated water demand model were between 5 and 19% (highest in the AR program). Results indicated that adoption of more than one type of water efficiency appliance could significantly reduce residential water demand. For the sustainable water management strategies, the appropriate water conservation rate was projected to be 1 to 2 million gallons per day (MGD) through 2030. With 2 MGD of water savings, the estimated per capita water use (GPCD) could be reduced from approximately 140 to 122 GPCD. Additional efforts are needed to reduce the water demand to US EPA’s “Water Sense” conservation levels of 70 GPCD by 2030. Life cycle assessment results showed that environmental impacts (water and energy demands and greenhouse gas emissions) from end-use and demand phases are most significant within the water system, particularly due to water heating (73% for clothes washer and 93% for showerhead). Estimations of optimal lifespan for appliances (8 to 21 years) implied that earlier replacement with efficiency models is encouraged in order to minimize the environmental impacts brought by current practice.

The Rise of Native Voices Against Natural Resource Extraction in Latin America [Student's Paper Series]

Latin America, a region rich in both energy resources and native heritage, faces a rising politico-social confrontation that has been growing for over two decades. While resources like oil and gas are exploited to enhance the state’s economic growth, indigenous groups feel threatened because the operations related to this exploitation are infringing on their homelands. Furthermore, they believe that the potential resource wealth found in these environmentally-sensitive regions is provoking an “intrusion” in their ancestral territory of either government agencies or corporations allowed by governmental decree. Indigenous groups, which have achieved greater political voice over the past decade, are protesting against government violations. These protests have reached the media and received international attention, leading the discourse on topics such as civil and human rights violations. When this happens, the State finds itself “between a rock and a hard place”: In a debate between indigenous groups’ rights and economic sustainability.

Improving resource management in virtualized data centers using application performance models

The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity.^ We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. ^ This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.^

Fair and QoS-oriented resource management in heterogeneous networks

In this paper, a heterogeneous network composed of femtocells deployed within a macrocell network is considered, and a quality-of-service (QoS)-oriented fairness metric which captures important characteristics of tiered network architectures is proposed. Using homogeneous Poisson processes, the sum capacities in such networks are expressed in closed form for co-channel, dedicated channel, and hybrid resource allocation methods. Then a resource splitting strategy that simultaneously considers capacity maximization, fairness constraints, and QoS constraints is proposed. Detailed computer simulations utilizing 3GPP simulation assumptions show that a hybrid allocation strategy with a well-designed resource split ratio enjoys the best cell-edge user performance, with minimal degradation in the sum throughput of macrocell users when compared with that of co-channel operation.

Fuzzy Modeling and Control Based Virtual Machine Resource Management

Virtual machines (VMs) are powerful platforms for building agile datacenters and emerging cloud systems. However, resource management for a VM-based system is still a challenging task. First, the complexity of application workloads as well as the interference among competing workloads makes it difficult to understand their VMs’ resource demands for meeting their Quality of Service (QoS) targets; Second, the dynamics in the applications and system makes it also difficult to maintain the desired QoS target while the environment changes; Third, the transparency of virtualization presents a hurdle for guest-layer application and host-layer VM scheduler to cooperate and improve application QoS and system efficiency. This dissertation proposes to address the above challenges through fuzzy modeling and control theory based VM resource management. First, a fuzzy-logic-based nonlinear modeling approach is proposed to accurately capture a VM’s complex demands of multiple types of resources automatically online based on the observed workload and resource usages. Second, to enable fast adaption for resource management, the fuzzy modeling approach is integrated with a predictive-control-based controller to form a new Fuzzy Modeling Predictive Control (FMPC) approach which can quickly track the applications’ QoS targets and optimize the resource allocations under dynamic changes in the system. Finally, to address the limitations of black-box-based resource management solutions, a cross-layer optimization approach is proposed to enable cooperation between a VM’s host and guest layers and further improve the application QoS and resource usage efficiency. The above proposed approaches are prototyped and evaluated on a Xen-based virtualized system and evaluated with representative benchmarks including TPC-H, RUBiS, and TerraFly. The results demonstrate that the fuzzy-modeling-based approach improves the accuracy in resource prediction by up to 31.4% compared to conventional regression approaches. The FMPC approach substantially outperforms the traditional linear-model-based predictive control approach in meeting application QoS targets for an oversubscribed system. It is able to manage dynamic VM resource allocations and migrations for over 100 concurrent VMs across multiple hosts with good efficiency. Finally, the cross-layer optimization approach further improves the performance of a virtualized application by up to 40% when the resources are contended by dynamic workloads.

An Institutional, Socio-economic, and Legal Analysis of Fisheries Co-management and Regulation in the Gulf of Nicoya, Costa Rica

Marine Areas for Responsible Artisanal Fishing (AMPR) have emerged as a new model for co-managing small-scale fisheries in Costa Rica, one that involves collaboration between fishers, government agencies and NGOs. This thesis aims to examine the context for collective action and co-management by small-scale fishers; evaluate the design, implementation, and enforcement of AMPRs; and conduct a linguistic analysis of fisheries legislation. The present work relies on the analysis of several types of qualitative data, including interviews with 23 key informants, rapid rural assessments, and legal documents. Findings demonstrate the strong influence of economic factors for sustaining collective action, as well as the importance of certain types of external organizations for community development and co-management. Additionally, significant enforcement gaps and institutional deficiencies were identified in the work of regulating agencies. Legal analysis suggests that mechanisms for government accountability are unavailable and that legal discourse reflects some of the most salient problems in management.

Attitudes towards the Marine Environment and Implications for Marine Resource Management in Seward, Alaska

This research, conducted in 2006-2008, examines the ways in which various groups involved with the marine resources of Seward, Alaska construct attitudes towards the environment. Participant observation and semi-structured interviews are used to assess how commercial halibut fishers, tour boat operators, local residents and government officials understand the marine environment based on their previous experiences. This study also explores how ideologies relate to the current practices of each group. Two theories orient the analyses: The first, cultural modeling provided a theoretical and methodological framework for pursuing a more comprehensive analysis of resource management. The second, Theory of Reasoned Action (Ajzen and Fishbein 1980), guided the analysis of the ways in which each participant’s ideology towards the marine environment relates to their practice. Aside from contributing to a better understanding of a coastal community’s ideologies and practices, this dissertation sought to better understand the role of ecological ideologies and behaviors in fisheries management. The research illustrates certain domains where ideologies and practices concerning Pacific halibut and the marine environment differ among commercial fishers, government, and management officials, tour boat operators and residents of Seward, AK. These differences offer insights into how future collaborative efforts between government officials, managers and local marine resource users might better incorporate local ideology into management, and provide ecological information to local marine resource users in culturally appropriate ways.

Improving Resource Management in Virtualized Data Centers using Application Performance Models

The rapid growth of virtualized data centers and cloud hosting services is making the management of physical resources such as CPU, memory, and I/O bandwidth in data center servers increasingly important. Server management now involves dealing with multiple dissimilar applications with varying Service-Level-Agreements (SLAs) and multiple resource dimensions. The multiplicity and diversity of resources and applications are rendering administrative tasks more complex and challenging. This thesis aimed to develop a framework and techniques that would help substantially reduce data center management complexity. We specifically addressed two crucial data center operations. First, we precisely estimated capacity requirements of client virtual machines (VMs) while renting server space in cloud environment. Second, we proposed a systematic process to efficiently allocate physical resources to hosted VMs in a data center. To realize these dual objectives, accurately capturing the effects of resource allocations on application performance is vital. The benefits of accurate application performance modeling are multifold. Cloud users can size their VMs appropriately and pay only for the resources that they need; service providers can also offer a new charging model based on the VMs performance instead of their configured sizes. As a result, clients will pay exactly for the performance they are actually experiencing; on the other hand, administrators will be able to maximize their total revenue by utilizing application performance models and SLAs. This thesis made the following contributions. First, we identified resource control parameters crucial for distributing physical resources and characterizing contention for virtualized applications in a shared hosting environment. Second, we explored several modeling techniques and confirmed the suitability of two machine learning tools, Artificial Neural Network and Support Vector Machine, to accurately model the performance of virtualized applications. Moreover, we suggested and evaluated modeling optimizations necessary to improve prediction accuracy when using these modeling tools. Third, we presented an approach to optimal VM sizing by employing the performance models we created. Finally, we proposed a revenue-driven resource allocation algorithm which maximizes the SLA-generated revenue for a data center.

Geospatial Data Indexing Analysis and Visualization via Web Services with Autonomic Resource Management

With the exponential growth of the usage of web-based map services, the web GIS application has become more and more popular. Spatial data index, search, analysis, visualization and the resource management of such services are becoming increasingly important to deliver user-desired Quality of Service. First, spatial indexing is typically time-consuming and is not available to end-users. To address this, we introduce TerraFly sksOpen, an open-sourced an Online Indexing and Querying System for Big Geospatial Data. Integrated with the TerraFly Geospatial database [1-9], sksOpen is an efficient indexing and query engine for processing Top-k Spatial Boolean Queries. Further, we provide ergonomic visualization of query results on interactive maps to facilitate the user’s data analysis. Second, due to the highly complex and dynamic nature of GIS systems, it is quite challenging for the end users to quickly understand and analyze the spatial data, and to efficiently share their own data and analysis results with others. Built on the TerraFly Geo spatial database, TerraFly GeoCloud is an extra layer running upon the TerraFly map and can efficiently support many different visualization functions and spatial data analysis models. Furthermore, users can create unique URLs to visualize and share the analysis results. TerraFly GeoCloud also enables the MapQL technology to customize map visualization using SQL-like statements [10]. Third, map systems often serve dynamic web workloads and involve multiple CPU and I/O intensive tiers, which make it challenging to meet the response time targets of map requests while using the resources efficiently. Virtualization facilitates the deployment of web map services and improves their resource utilization through encapsulation and consolidation. Autonomic resource management allows resources to be automatically provisioned to a map service and its internal tiers on demand. v-TerraFly are techniques to predict the demand of map workloads online and optimize resource allocations, considering both response time and data freshness as the QoS target. The proposed v-TerraFly system is prototyped on TerraFly, a production web map service, and evaluated using real TerraFly workloads. The results show that v-TerraFly can accurately predict the workload demands: 18.91% more accurate; and efficiently allocate resources to meet the QoS target: improves the QoS by 26.19% and saves resource usages by 20.83% compared to traditional peak load-based resource allocation.

Vegetation dynamics and their implications for the management of wetlands in the lowlands of Nepal

The maintenance of species richness is often a priority in the management of nature reserves, where consumptive use of resources is generally prohibited. The purpose of this research was to improve management by understanding the vegetation dynamics in the lowlands of Nepal. The objectives were to determine vegetation associations in relation to environments and human-induced disturbances that affect vegetation dynamics on floodplains, where upstream barrages had altered flooding patterns, and consumptive use of plant resources was influencing natural processes. Floodplain vegetation in relation to physical environments and disturbances were studied along transects, perpendicular to the course of the Mahakali River in the western Terai, Nepal. Forest structural changes were studied for three years in ten plots. A randomized split-block experiment with nine burning and grazing treatments was performed in seasonally flooded grasslands. A semi-structured questionnaire was used to assess people's socio-economic status, natural resource use patterns and conservation attitudes. ^ Elevation, soil organic matter, nitrogen, percentage of sand and grazing intensity were significant in delineating herbaceous vegetation assemblages, whereas elevation and livestock grazing were significant in defining forest type boundaries. On the floodplain islands, highly grazed Dalbergia sissoo-Acacia catechu forests were devoid of understory woody vegetation, but the lightly grazed D. sissoo-mixed forests had a well-developed second canopy layer, comprising woody species other than D. sissoo and A. catechu. In grasslands, species richness and biomass production were highest at intermediate disturbance level represented by the lightly grazed and ungrazed early-burned treatments. Ethnicity, education and resource use patterns were important in influencing conservation attitudes. A succession towards the mixed forests would occur in D. sissoo-dominated floodplain forests, where dams and barrages reduce flooding and associated fluvial processes, and if livestock grazing is stopped, as occasionally suggested by nature conservationists. In seasonally flooded grasslands, early burning with moderate grazing would enhance the species diversity and productivity. There is a need to implement a participatory integrated wetland management plan, to include community development, education and off farm income generation, to assure participatory conservation and management of wetlands in Nepal. ^