897 resultados para LARGE-SCALE
Resumo:
Globally, small-scale fisheries (SSFs) are driven by climate, governance, and market factors of social-ecological change, presenting both challenges and opportunities. The ability of small-scale fishermen and buyers to adapt to changing conditions allows participants to survive economic or environmental disturbances and to benefit from optimal conditions. This study presented here identifies key large-scale factors that drive SSFs in California to shift focus among targets and that dictate long-term trends in landings. We use Elinor Ostrom’s Social-Ecological System (SES) framework to apply an interdisciplinary approach when identifying potential factors and when understanding the complex dynamics of these fisheries. We analyzed the interactions among Monterey Bay SSFs over the past four decades since the passage of the Magnuson Stevens Fisheries Conservation and Management Act of 1976. In this region, the Pacific sardine (Sardinops sagax), northern anchovy (Engraulis mordax), and market squid (Loligo opalescens) fisheries comprise a tightly linked system where shifting focus among fisheries is a key element to adaptive capacity and reduced social and ecological vulnerability. Using a cluster analysis of landings, we identified four modes from 1974 to 2012 that were dominated by squid, sardine, anchovy, or lacked any dominance, enabling us to identify external drivers attributed to a change in fishery dominance during seven distinct transition points. Overall, we show that market and climate factors drive the transitions among dominance modes. Governance phases most dictated long-term trends in landings and are best viewed as a response to changes in perceived biomass and thus a proxy for biomass. Our findings suggest that globally, small-scale fishery managers should consider enabling shifts in effort among fisheries and retaining existing flexibility, as adaptive capacity is a critical determinant for social and ecological resilience.
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Aircraft manufacturing industries are looking for solutions in order to increase their productivity. One of the solutions is to apply the metrology systems during the production and assembly processes. Metrology Process Model (MPM) (Maropoulos et al, 2007) has been introduced which emphasises metrology applications with assembly planning, manufacturing processes and product designing. Measurability analysis is part of the MPM and the aim of this analysis is to check the feasibility for measuring the designed large scale components. Measurability Analysis has been integrated in order to provide an efficient matching system. Metrology database is structured by developing the Metrology Classification Model. Furthermore, the feature-based selection model is also explained. By combining two classification models, a novel approach and selection processes for integrated measurability analysis system (MAS) are introduced and such integrated MAS could provide much more meaningful matching results for the operators. © Springer-Verlag Berlin Heidelberg 2010.
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Topographic variation, the spatial variation in elevation and terrain features, underpins a myriad of patterns and processes in geography and ecology and is key to understanding the variation of life on the planet. The characterization of this variation is scale-dependent, i.e. it varies with the distance over which features are assessed and with the spatial grain (grid cell resolution) of analysis. A fully standardized and global multivariate product of different terrain features has the potential to support many large-scale basic research and analytical applications, however to date, such technique is unavailable. Here we used the digital elevation model products of global 250 m GMTED and near-global 90 m SRTM to derive a suite of topographic variables: elevation, slope, aspect, eastness, northness, roughness, terrain roughness index, topographic position index, vector ruggedness measure, profile and tangential curvature, and 10 geomorphological landform classes. We aggregated each variable to 1, 5, 10, 50 and 100 km spatial grains using several aggregation approaches (median, average, minimum, maximum, standard deviation, percent cover, count, majority, Shannon Index, entropy, uniformity). While a global cross-correlation underlines the high similarity of many variables, a more detailed view in four mountain regions reveals local differences, as well as scale variations in the aggregated variables at different spatial grains. All newly-developed variables are available for download at http://www.earthenv.org and can serve as a basis for standardized hydrological, environmental and biodiversity modeling at a global extent.
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One of the global phenomena with threats to environmental health and safety is artisanal mining. There are ambiguities in the manner in which an ore-processing facility operates which hinders the mining capacity of these miners in Ghana. These problems are reviewed on the basis of current socio-economic, health and safety, environmental, and use of rudimentary technologies which limits fair-trade deals to miners. This research sought to use an established data-driven, geographic information (GIS)-based system employing the spatial analysis approach for locating a centralized processing facility within the Wassa Amenfi-Prestea Mining Area (WAPMA) in the Western region of Ghana. A spatial analysis technique that utilizes ModelBuilder within the ArcGIS geoprocessing environment through suitability modeling will systematically and simultaneously analyze a geographical dataset of selected criteria. The spatial overlay analysis methodology and the multi-criteria decision analysis approach were selected to identify the most preferred locations to site a processing facility. For an optimal site selection, seven major criteria including proximity to settlements, water resources, artisanal mining sites, roads, railways, tectonic zones, and slopes were considered to establish a suitable location for a processing facility. Site characterizations and environmental considerations, incorporating identified constraints such as proximity to large scale mines, forest reserves and state lands to site an appropriate position were selected. The analysis was limited to criteria that were selected and relevant to the area under investigation. Saaty’s analytical hierarchy process was utilized to derive relative importance weights of the criteria and then a weighted linear combination technique was applied to combine the factors for determination of the degree of potential site suitability. The final map output indicates estimated potential sites identified for the establishment of a facility centre. The results obtained provide intuitive areas suitable for consideration
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Kelp forests represent some of the most productive and diverse habitats on Earth. Understanding drivers of ecological patterns at large spatial scales is critical for effective management and conservation of marine habitats. We surveyed kelp forests dominated by Laminaria hyperborea (Gunnerus) Foslie 1884 across 9° latitude and >1000 km of coastline and measured a number of physical parameters at multiple scales to link ecological structure and standing stock of carbon with environmental variables. Kelp density, biomass, morphology and age were generally greater in exposed sites within regions, highlighting the importance of wave exposure in structuring L. hyperborea populations. At the regional scale, wave-exposed kelp canopies in the cooler regions (the north and west of Scotland) were greater in biomass, height and age than in warmer regions (southwest Wales and England). The range and maximal values of estimated standing stock of carbon contained within kelp forests was greater than in historical studies, suggesting that this ecosystem property may have been previously undervalued. Kelp canopy density was positively correlated with large-scale wave fetch and fine-scale water motion, whereas kelp canopy biomass and the standing stock of carbon were positively correlated with large-scale wave fetch and light levels and negatively correlated with temperature. As light availability and summer temperature were important drivers of kelp forest biomass, effective management of human activities that may affect coastal water quality is necessary to maintain ecosystem functioning, while increased temperatures related to anthropogenic climate change may impact the structure of kelp forests and the ecosystem services they provide.
Resumo:
Kelp forests represent some of the most productive and diverse habitats on Earth. Understanding drivers of ecological patterns at large spatial scales is critical for effective management and conservation of marine habitats. We surveyed kelp forests dominated by Laminaria hyperborea (Gunnerus) Foslie 1884 across 9° latitude and >1000 km of coastline and measured a number of physical parameters at multiple scales to link ecological structure and standing stock of carbon with environmental variables. Kelp density, biomass, morphology and age were generally greater in exposed sites within regions, highlighting the importance of wave exposure in structuring L. hyperborea populations. At the regional scale, wave-exposed kelp canopies in the cooler regions (the north and west of Scotland) were greater in biomass, height and age than in warmer regions (southwest Wales and England). The range and maximal values of estimated standing stock of carbon contained within kelp forests was greater than in historical studies, suggesting that this ecosystem property may have been previously undervalued. Kelp canopy density was positively correlated with large-scale wave fetch and fine-scale water motion, whereas kelp canopy biomass and the standing stock of carbon were positively correlated with large-scale wave fetch and light levels and negatively correlated with temperature. As light availability and summer temperature were important drivers of kelp forest biomass, effective management of human activities that may affect coastal water quality is necessary to maintain ecosystem functioning, while increased temperatures related to anthropogenic climate change may impact the structure of kelp forests and the ecosystem services they provide.
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The water stored in and flowing through the subsurface is fundamental for sustaining human activities and needs, feeding water and its constituents to surface water bodies and supporting the functioning of their ecosystems. Quantifying the changes that affect the subsurface water is crucial for our understanding of its dynamics and changes driven by climate change and other changes in the landscape, such as in land-use and water-use. It is inherently difficult to directly measure soil moisture and groundwater levels over large spatial scales and long times. Models are therefore needed to capture the soil moisture and groundwater level dynamics over such large spatiotemporal scales. This thesis develops a modeling framework that allows for long-term catchment-scale screening of soil moisture and groundwater level changes. The novelty in this development resides in an explicit link drawn between catchment-scale hydroclimatic and soil hydraulics conditions, using observed runoff data as an approximation of soil water flux and accounting for the effects of snow storage-melting dynamics on that flux. Both past and future relative changes can be assessed by use of this modeling framework, with future change projections based on common climate model outputs. By direct model-observation comparison, the thesis shows that the developed modeling framework can reproduce the temporal variability of large-scale changes in soil water storage, as obtained from the GRACE satellite product, for most of 25 large study catchments around the world. Also compared with locally measured soil water content and groundwater level in 10 U.S. catchments, the modeling approach can reasonably well reproduce relative seasonal fluctuations around long-term average values. The developed modeling framework is further used to project soil moisture changes due to expected future climate change for 81 catchments around the world. The future soil moisture changes depend on the considered radiative forcing scenario (RCP) but are overall large for the occurrence frequency of dry and wet events and the inter-annual variability of seasonal soil moisture. These changes tend to be higher for the dry events and the dry season, respectively, than for the corresponding wet quantities, indicating increased drought risk for some parts of the world.
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Context: Obfuscation is a common technique used to protect software against mali- cious reverse engineering. Obfuscators manipulate the source code to make it harder to analyze and more difficult to understand for the attacker. Although different ob- fuscation algorithms and implementations are available, they have never been directly compared in a large scale study. Aim: This paper aims at evaluating and quantifying the effect of several different obfuscation implementations (both open source and commercial), to help developers and project manager to decide which one could be adopted. Method: In this study we applied 44 obfuscations to 18 subject applications covering a total of 4 millions lines of code. The effectiveness of these source code obfuscations has been measured using 10 code metrics, considering modularity, size and complexity of code. Results: Results show that some of the considered obfuscations are effective in mak- ing code metrics change substantially from original to obfuscated code, although this change (called potency of the obfuscation) is different on different metrics. In the pa- per we recommend which obfuscations to select, given the security requirements of the software to be protected.
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In today's fast-paced and interconnected digital world, the data generated by an increasing number of applications is being modeled as dynamic graphs. The graph structure encodes relationships among data items, while the structural changes to the graphs as well as the continuous stream of information produced by the entities in these graphs make them dynamic in nature. Examples include social networks where users post status updates, images, videos, etc.; phone call networks where nodes may send text messages or place phone calls; road traffic networks where the traffic behavior of the road segments changes constantly, and so on. There is a tremendous value in storing, managing, and analyzing such dynamic graphs and deriving meaningful insights in real-time. However, a majority of the work in graph analytics assumes a static setting, and there is a lack of systematic study of the various dynamic scenarios, the complexity they impose on the analysis tasks, and the challenges in building efficient systems that can support such tasks at a large scale. In this dissertation, I design a unified streaming graph data management framework, and develop prototype systems to support increasingly complex tasks on dynamic graphs. In the first part, I focus on the management and querying of distributed graph data. I develop a hybrid replication policy that monitors the read-write frequencies of the nodes to decide dynamically what data to replicate, and whether to do eager or lazy replication in order to minimize network communication and support low-latency querying. In the second part, I study parallel execution of continuous neighborhood-driven aggregates, where each node aggregates the information generated in its neighborhoods. I build my system around the notion of an aggregation overlay graph, a pre-compiled data structure that enables sharing of partial aggregates across different queries, and also allows partial pre-computation of the aggregates to minimize the query latencies and increase throughput. Finally, I extend the framework to support continuous detection and analysis of activity-based subgraphs, where subgraphs could be specified using both graph structure as well as activity conditions on the nodes. The query specification tasks in my system are expressed using a set of active structural primitives, which allows the query evaluator to use a set of novel optimization techniques, thereby achieving high throughput. Overall, in this dissertation, I define and investigate a set of novel tasks on dynamic graphs, design scalable optimization techniques, build prototype systems, and show the effectiveness of the proposed techniques through extensive evaluation using large-scale real and synthetic datasets.
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Reconstructing Northern Hemisphere ice-sheet oscillations and meltwater routing to the ocean is important to better understand the mechanisms behind abrupt climate changes. To date, research efforts have mainly focused on the North American (Laurentide) ice-sheets (LIS), leaving the potential role of the European Ice Sheet (EIS), and of the Scandinavian ice-sheet (SIS) in particular, largely unexplored. Using neodymium isotopes in detrital sediments deposited off the Channel River, we provide a continuous and well-dated record for the evolution of the EIS southern margin through the end of the last glacial period and during the deglaciation. Our results reveal that the evolution of EIS margins was accompanied with substantial ice recession (especially of the SIS) and simultaneous release of meltwater to the North Atlantic. These events occurred both in the course of the EIS to its LGM position (i.e., during Heinrich Stadial –HS– 3 and HS2; ∼31–29 ka and ∼26–23 ka, respectively) and during the deglaciation (i.e., at ∼22 ka, ∼20–19 ka and from 18.2 ± 0.2 to 16.7 ± 0.2 ka that corresponds to the first part of HS1). The deglaciation was discontinuous in character, and similar in timing to that of the southern LIS margin, with moderate ice-sheet retreat (from 22.5 ± 0.2 ka in the Baltic lowlands) as soon as the northern summer insolation increase (from ∼23 ka) and an acceleration of the margin retreat thereafter (from ∼20 ka). Importantly, our results show that EIS retreat events and release of meltwater to the North Atlantic during the deglaciation coincide with AMOC destabilisation and interhemispheric climate changes. They thus suggest that the EIS, together with the LIS, could have played a critical role in the climatic reorganization that accompanied the last deglaciation. Finally, our data suggest that meltwater discharges to the North Atlantic produced by large-scale recession of continental parts of Northern Hemisphere ice sheets during HS, could have been a possible source for the oceanic perturbations (i.e., AMOC shutdown) responsible for the marine-based ice stream purge cycle, or so-called HE's, that punctuate the last glacial period.
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The focus of this research is to explore the applications of the finite difference formulation based on the latency insertion method (LIM) to the analysis of circuit interconnects. Special attention is devoted to addressing the issues that arise in very large networks such as on-chip signal and power distribution networks. We demonstrate that the LIM has the power and flexibility to handle various types of analysis required at different stages of circuit design. The LIM is particularly suitable for simulations of very large scale linear networks and can significantly outperform conventional circuit solvers (such as SPICE).
Resumo:
Racism continues to thrive on the Internet. Yet, little is known about racism in online settings and the potential consequences. The purpose of this study was to develop the Perceived Online Racism Scale (PORS), the first measure to assess people’s perceived online racism experiences as they interact with others and consume information on the Internet. Items were developed through a multi-stage process based on literature review, focus-groups, and qualitative data collection. Based on a racially diverse large-scale sample (N = 1023), exploratory and confirmatory factor analyses provided support for a 30-item bifactor model with the following three factors: (a) 14-item PORS-IP (personal experiences of racism in online interactions), (b) 5-item PORS-V (observations of other racial/ethnic minorities being offended), and (c) 11-item PORS-I (consumption of online contents and information denigrating racial/ethnic minorities and highlighting racial injustice in society). Initial construct validity examinations suggest that PORS is significantly linked to psychological distress.
Resumo:
A landing obligation was formally implemented in the European Union (EU) for the first time, as part of the recent reform of the EU Common Fisheries Policy (CFP). Given the reasonable success of the landing obligation in some countries such as the Faroe Islands, Iceland and Norway, this policy is seen as a viable approach to tackle the long-recognized discarding problem in EU waters. However, there has been some debate on whether there is sufficient evidence to support the feasibility of such a measure in the EU-CFP. The EU landing obligation will implicitly include all small-scale fisheries (SSF) provided the species captured are subject to catch limits or minimum sizes (in the case of the Mediterranean). SSF were included irrespective of the fact that the discarding problem in the EU has been historically associated with medium- to large-scale fleets (in particular largely mixed species trawl fisheries). Additionally, past experiences with a discard ban policy are still limited to specific countries and/or specific fisheries. This paper examined the appropriateness and feasibility of the recently implemented EU landing obligation in SSF. The effects in the long-term are unpredictable, but available evidence suggests that in the short to medium-term a landing obligation is likely to bring more negative social, economic and ecological impacts than benefits. (C) 2015 Elsevier Ltd. All rights reserved.
Resumo:
Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (λET) and evaporation (λEE) flux components of the terrestrial latent heat flux (λE), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on λET and λEE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, λET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on λET during the wet (rainy) seasons where λET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80 % of the variances of λET. However, biophysical control on λET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65 % of the variances of λET, and indicates λET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between λET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales.
Resumo:
Canopy and aerodynamic conductances (gC and gA) are two of the key land surface biophysical variables that control the land surface response of land surface schemes in climate models. Their representation is crucial for predicting transpiration (?ET) and evaporation (?EE) flux components of the terrestrial latent heat flux (?E), which has important implications for global climate change and water resource management. By physical integration of radiometric surface temperature (TR) into an integrated framework of the Penman?Monteith and Shuttleworth?Wallace models, we present a novel approach to directly quantify the canopy-scale biophysical controls on ?ET and ?EE over multiple plant functional types (PFTs) in the Amazon Basin. Combining data from six LBA (Large-scale Biosphere-Atmosphere Experiment in Amazonia) eddy covariance tower sites and a TR-driven physically based modeling approach, we identified the canopy-scale feedback-response mechanism between gC, ?ET, and atmospheric vapor pressure deficit (DA), without using any leaf-scale empirical parameterizations for the modeling. The TR-based model shows minor biophysical control on ?ET during the wet (rainy) seasons where ?ET becomes predominantly radiation driven and net radiation (RN) determines 75 to 80?% of the variances of ?ET. However, biophysical control on ?ET is dramatically increased during the dry seasons, and particularly the 2005 drought year, explaining 50 to 65?% of the variances of ?ET, and indicates ?ET to be substantially soil moisture driven during the rainfall deficit phase. Despite substantial differences in gA between forests and pastures, very similar canopy?atmosphere "coupling" was found in these two biomes due to soil moisture-induced decrease in gC in the pasture. This revealed the pragmatic aspect of the TR-driven model behavior that exhibits a high sensitivity of gC to per unit change in wetness as opposed to gA that is marginally sensitive to surface wetness variability. Our results reveal the occurrence of a significant hysteresis between ?ET and gC during the dry season for the pasture sites, which is attributed to relatively low soil water availability as compared to the rainforests, likely due to differences in rooting depth between the two systems. Evaporation was significantly influenced by gA for all the PFTs and across all wetness conditions. Our analytical framework logically captures the responses of gC and gA to changes in atmospheric radiation, DA, and surface radiometric temperature, and thus appears to be promising for the improvement of existing land?surface?atmosphere exchange parameterizations across a range of spatial scales.