<p> It is difficult to assess rangeland management practices at a hillslope scale because of the spatial and temporal variability of ecohydrological processes across a landscape. The Conservation Effects Assessment Project (CEAP) aims to provide a cost-effective method for quantifying benefits of conservation practices on rangelands. This study uses the Rangeland Hydrology and Erosion Model (RHEM) to develop a framework to assess rangeland management practices by quantifying sediment yield and runoff. Kaler Ranch, located in Eastern Arizona, was used as a study site because of their recently implemented rangeland conservation practices. Vegetation parameters were developed based on field data collected across the ranch and used to represent various rangeland management scenarios in RHEM. Peak flow and sediment yield rates were determined for each scenario using RHEM and were used as metrics to evaluate rangeland condition. RHEM provided an adequate method to evaluate the relative differences between upland rangeland management scenarios; however, it was less effective at evaluating changes in management practices within a riparian area.</p>

<p> Parcelization is an increasing concern to land managers in the rural regions of the United States. In order to protect vital ecosystem goods and services, resource managers need to account for decreasing parcel sizes. The Catskill region of New York State contains both the New York City Watershed and the Catskill Preserve. In order to maintain ecosystem functions within these sensitive areas, wise planning is needed in the development of rural lands. This study documents the change in private, rural parcel dynamics from 2004 to 2010 in the Catskill region at the township scale. A parcel density map was developed to observe trends in distribution of small parcels. The average parcel size dropped from 13.9 acres in 2004 to 13.1 acres in 2010. The distribution of small private, rural parcels is diffuse across the study region, implying the transition from resource management focused land holdings to rural residential within the Catskill region.</p>

No description available.

No description available.

No description available.

<p> This dissertation tests two methods to obtain information of the distribution and movement of cetaceans. The first method uses vessels of opportunity as platforms to conduct acoustic surveys between the main Hawaiian Islands, with the ultimate goal of providing a method that can be used in future studies to contribute to mapping distribution and habitat modeling of data-poor cetacean species in the areas of the ocean which are infrequently surveyed. The distribution of a well-studied species, the humpback whale <i> Megaptera novaeangliae</i> was mapped and analyzed in relation to remotely sensed data on ocean depth, sea surface temperature, sea surface height, wind speed, chlorophyll-A, and surface currents. The results agreed with previous research on humpback whales, indicating that acoustic surveys from vessels of opportunity are a viable method for collecting distribution data on cetaceans. The predicted species of odontocete whistles collected during vessel of opportunity surveys was determined using the Real-time Odontocete Call Classification Algorithm, and analyzed in respect to remotely sensed data. The sighting rate for odontocete surveys in this study is comparable to that of previous survey methods, and cryptic species are identified at a higher relative rate than when using visual sighting methods. The biases inherent in concentrating survey effort primarily in the calm waters on the leeward sides the Hawaiian Islands are discussed, as well as the drawbacks of relying on visual sighting methods for detecting species with low visual detection probability. In addition, the potential impacts of anthropogenic noise and ship strikes from commercial vessels are discussed during the case study of a high-speed craft. This dissertation also discusses a second methodology involving the use of DIFAR sonobuoys to track multiple singing humpback whales, with the end goal of learning more about the function about humpback song. This method is also applicable to other cetacean species.</p>

Cloud computing has become a powerful enabler for many IT services and new technolo-gies. It provides access to an unprecedented amount of resources in a fine-grained andon-demand manner. To deliver such a service, cloud providers should be able to efficientlyand reliably manage their available resources. This becomes a challenge for the manage-ment system as it should handle a large number of heterogeneous resources under diverseworkloads with fluctuations. In addition, it should also satisfy multiple operational require-ments and management objectives in large scale data centers.Autonomic computing techniques can be used to tackle cloud resource managementproblems. An autonomic system comprises of a number of autonomic elements, which arecapable of automatically organizing and managing themselves rather than being managedby external controllers. Therefore, they are well suited for decentralized control, as theydo not rely on a centrally managed state. A decentralized autonomic system benefits fromparallelization of control, faster decisions and better scalability. They are also more reliableas a failure of one will not affect the operation of the others, while there is also a lower riskof having faulty behaviors on all the elements, all at once. All these features are essentialrequirements of an effective cloud resource management.This thesis investigates algorithms, models, and techniques to autonomously managejobs, services, and virtual resources in a cloud data center. We introduce a decentralizedresource management framework, that automates resource allocation optimization and ser-vice consolidation, reliably schedules jobs considering probabilistic failures, and dynam-icly scales and repacks services to achieve cost efficiency.As part of the framework, we introduce a decentralized scheduler that provides andmaintains durable allocations with low maintenance costs for data centers with dynamicworkloads. The scheduler assigns resources in response to virtual machine requests andmaintains the packing efficiency while taking into account migration costs, topologicalconstraints, and the risk of resource contention, as well as fluctuations of the backgroundload.We also introduce a scheduling algorithm that considers probabilistic failures as part ofthe planning for scheduling. The aim of the algorithm is to achieve an overall job reliabil-ity, in presence of correlated failures in a data center. To do so, we study the impacts ofstochastic and correlated failures on job reliability in a virtual data center. We specificallyfocus on correlated failures caused by power outages or failure of network components onjobs running large number of replicas of identical tasks.Additionally, we investigate the trade-offs between vertical and horizontal scaling. Theresult of the investigations is used to introduce a repacking technique to automatically man-age the capacity required by an elastic service. The repacking technique combines thebenefits of both scaling strategies to improve its cost-efficiency. / Datormoln har kommit att bli kraftfulla möjliggörare för många nya IT-tjänster. De ger tillgång till mycket storskaliga datorresurser på ett finkornigt och omedelbart sätt. För att tillhandahålla sådana resurser krävs att de underliggande datorcentren kan hantera sina resurser på ett tillförlitligt och effektivt sätt. Frågan hur man ska designa deras resurshanteringssystem är en stor utmaning då de ska kunna hantera mycket stora mängder heterogena resurser som i sin tur ska klara av vitt skilda typer av belastning, ofta med väldigt stora variationer över tid. Därtill ska de typiskt kunna möta en mängd olika krav och målsättningar för hur resurserna ska nyttjas. Autonomiska system kan med fördel användas för att realisera sådana system. Ett autonomt system innehåller ett antal autonoma element som automatiskt kan organisera och hantera sig själva utan stöd av externa regulatorer. Förmågan att hantera sig själva gör dem mycket lämpliga som komponenter i distribuerade system, vilka i sin tur kan bidra till snabbare beslutsprocesser, bättre skalbarhet och högre feltolerans. Denna avhandling fokuserar på algoritmer, modeller och tekniker för autonom hantering av jobb och virtuella resurser i datacenter. Vi introducerar ett decentraliserat resurshanteringssystem som automatiserar resursallokering och konsolidering, schedulerar jobb tillförlitligt med hänsyn till korrelerade fel, samt skalar resurser dynamiskt för att uppnå kostnadseffektivitet. Som en del av detta ramverk introducerar vi en decentraliserad schedulerare som allokerar resurser med hänsyn till att tagna beslut ska vara bra för lång tid och ge låga resurshanteringskostnader för datacenter med dynamisk belastning. Scheduleraren allokerar virtuella maskiner utifrån aktuell belastning och upprätthåller ett effektivt nyttjande av underliggande servrar genom att ta hänsyn till migrationskostnader, topologiska bivillkor och risk för överutnyttjande. Vi introducerar också en resursallokeringsalgoritm som tar hänsyn till korrelerade fel som ett led i planeringen. Avsikten är att kunna uppnå specificerade tillgänglighetskrav för enskilda tjänster trots uppkomst av korrelerade fel. Vi fokuserar främst på korrelerade fel som härrör från problem med elförsörjning och från felande nätverkskomponenter samt deras påverkan på jobb bestående av många identiska del-jobb. Slutligen studerar vi även hur man bäst ska kombinera horisontell och vertikal skalning av resurser. Resultatet är en process som ökar kostnadseffektivitet genom att kombinera de två metoderna och därtill emellanåt förändra fördelning av storlekar på virtuella maskiner.

Energy and water are closely related to each other, yet management of the two resources has historically been independent. Water resources planning and management often ignores increases in energy consumption in response to securing drinking water supplies. At the same time, policies concerning power generation, including emission of greenhouse gases, can dramatically increase water consumption for electricity. As a result, tradeoffs often exist between energy and water resources policies. This work collectively describes and analyzes the nexus of energy and water within the state of Texas, with some extension to the rest of the United States. By aggregating Texas-specific data and national average values reported in literature, a snapshot of the energy-water nexus in Texas is presented, showing water use for thermoelectric power generation and electricity use for water and wastewater systems. Case studies then illustrate the energy and water implications of five policy and resource management scenarios: 1) statewide implementation of municipal water conservation and reuse, 2) installation of alternative thermoelectric cooling technologies to mitigate water scarcity, 3) use of desalination and long-haul water transfer as a drinking water supply for Dallas, Texas, 4) integration of wind power with brackish groundwater desalination as a water supply, and 5) energy recovery from municipal wastewater treatment plants. These analyses combine to reveal the intricacies of the energy-water nexus in Texas and its implications for future resource management. / text

No description available.

Fundamental issues of natural resource management revolve around diverse worldviews, knowledges and practices, which cannot all be captured within the policy framework. The Western worldview, which reflects mainly the utilitarian, economistic view of resources, has influenced and shaped the trend management of natural resources has taken world-wide. The Western worldview contrasts with local knowledges, which are uniquely innovative, highly dynamic, tacit, contextual and/or locality-specific. This thesis explores the fuelwood problem in Nyando Division of Kisumu District in Kenya, seeking both a holistic understanding and an emphasis on the interface between official policy and local rural practice, including the varying knowledges. The study focused on two case study clans, Muga and Kadhier in Awasi and Kochogo Locations, respectively. Most fuelwood in the study areas is from on-farm and multiple accessible sources. This contradicts the 'fuelwood orthodoxy' school which associates fuelwood consumption with deforestation and 'woodfuel crisis'. Aerospace imageries clearly illustrated a change and decline in stand density of the woody vegetation cover in Nyando Division over time. Differences in fuelwood availability and inequalities in endowment of wood/tree resources in and between the study localities exemplify critical questions of entitlement in the face of 'abundance'. Tree planting was not seen to be synonymous with fuelwood availability. This scenario promotes the fuelwood trade, high dependence on fuelwood purchase and supplements of crop residues by local households. Land privatisation has exacerbated the situation. Distances travelled to collect fuelwood have decreased as people turn to alternative and purchased fuels. Opportunities in the study area for the resolution of the fuelwood problem include promotion of less culturally restricted and less economically valuable trees, and a more farmer-sensitive approach from government and NGOs which recognises farmers as active partners in the interface between policy and rural practice.