882 resultados para mixed stock analysis


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Motorcycles are particularly vulnerable in right-angle crashes at signalized intersections. The objective of this study is to explore how variations in roadway characteristics, environmental factors, traffic factors, maneuver types, human factors as well as driver demographics influence the right-angle crash vulnerability of motorcycles at intersections. The problem is modeled using a mixed logit model with a binary choice category formulation to differentiate how an at-fault vehicle collides with a not-at-fault motorcycle in comparison to other collision types. The mixed logit formulation allows randomness in the parameters and hence takes into account the underlying heterogeneities potentially inherent in driver behavior, and other unobserved variables. A likelihood ratio test reveals that the mixed logit model is indeed better than the standard logit model. Night time riding shows a positive association with the vulnerability of motorcyclists. Moreover, motorcyclists are particularly vulnerable on single lane roads, on the curb and median lanes of multi-lane roads, and on one-way and two-way road type relative to divided-highway. Drivers who deliberately run red light as well as those who are careless towards motorcyclists especially when making turns at intersections increase the vulnerability of motorcyclists. Drivers appear more restrained when there is a passenger onboard and this has decreased the crash potential with motorcyclists. The presence of red light cameras also significantly decreases right-angle crash vulnerabilities of motorcyclists. The findings of this study would be helpful in developing more targeted countermeasures for traffic enforcement, driver/rider training and/or education, safety awareness programs to reduce the vulnerability of motorcyclists.

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This paper addresses the challenges of flood mapping using multispectral images. Quantitative flood mapping is critical for flood damage assessment and management. Remote sensing images obtained from various satellite or airborne sensors provide valuable data for this application, from which the information on the extent of flood can be extracted. However the great challenge involved in the data interpretation is to achieve more reliable flood extent mapping including both the fully inundated areas and the 'wet' areas where trees and houses are partly covered by water. This is a typical combined pure pixel and mixed pixel problem. In this paper, an extended Support Vector Machines method for spectral unmixing developed recently has been applied to generate an integrated map showing both pure pixels (fully inundated areas) and mixed pixels (trees and houses partly covered by water). The outputs were compared with the conventional mean based linear spectral mixture model, and better performance was demonstrated with a subset of Landsat ETM+ data recorded at the Daly River Basin, NT, Australia, on 3rd March, 2008, after a flood event.

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The most difficult operation in flood inundation mapping using optical flood images is to map the ‘wet’ areas where trees and houses are partly covered by water. This can be referred to as a typical problem of the presence of mixed pixels in the images. A number of automatic information extracting image classification algorithms have been developed over the years for flood mapping using optical remote sensing images, with most labelling a pixel as a particular class. However, they often fail to generate reliable flood inundation mapping because of the presence of mixed pixels in the images. To solve this problem, spectral unmixing methods have been developed. In this thesis, methods for selecting endmembers and the method to model the primary classes for unmixing, the two most important issues in spectral unmixing, are investigated. We conduct comparative studies of three typical spectral unmixing algorithms, Partial Constrained Linear Spectral unmixing, Multiple Endmember Selection Mixture Analysis and spectral unmixing using the Extended Support Vector Machine method. They are analysed and assessed by error analysis in flood mapping using MODIS, Landsat and World View-2 images. The Conventional Root Mean Square Error Assessment is applied to obtain errors for estimated fractions of each primary class. Moreover, a newly developed Fuzzy Error Matrix is used to obtain a clear picture of error distributions at the pixel level. This thesis shows that the Extended Support Vector Machine method is able to provide a more reliable estimation of fractional abundances and allows the use of a complete set of training samples to model a defined pure class. Furthermore, it can be applied to analysis of both pure and mixed pixels to provide integrated hard-soft classification results. Our research also identifies and explores a serious drawback in relation to endmember selections in current spectral unmixing methods which apply fixed sets of endmember classes or pure classes for mixture analysis of every pixel in an entire image. However, as it is not accurate to assume that every pixel in an image must contain all endmember classes, these methods usually cause an over-estimation of the fractional abundances in a particular pixel. In this thesis, a subset of adaptive endmembers in every pixel is derived using the proposed methods to form an endmember index matrix. The experimental results show that using the pixel-dependent endmembers in unmixing significantly improves performance.

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A new mixed-mode compression fracture specimen, obliquely oriented edge cracked semicircular disk (OECSD) is analyzed by extending pure opening mode configuration of edge cracked semicircular disk (ECSD) under Hertzian compression. Photoelastic experiments are conducted on two different specimens of OECSD of same size and different crack lengths and inclinations. Finite element method (FEM) is used to solve a number of cases of the problem varying crack length and crack inclination. FE results show a good match with experiments. Inclination of edge crack in OECSD can be so made as to obtain any mode-mixity ratio between zero and one and beyond for any crack length. The new specimen can be used for fracture testing under compression more conveniently than the existing ones in several ways.

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Little is known about the ocean distributions of wild juvenile coho salmon off the Oregon-Washington coast. In this study we report tag recoveries and genetic mixed-stock estimates of juvenile fish caught in coastal waters near the Columbia River plume. To support the genetic estimates, we report an allozyme-frequency baseline for 89 wild and hatchery-reared coho salmon spawning populations, extending from northern California to southern British Columbia. The products of 59 allozyme-encoding loci were examined with starch-gel electrophoresis. Of these, 56 loci were polymorphic, and 29 loci had P0.95 levels of polymorphism. Average heterozygosities within populations ranged from 0.021 to 0.046 and averaged 0.033. Multidimensional scaling of chord genetic distances between samples resolved nine regional groups that were sufficiently distinct for genetic mixed-stock analysis. About 2.9% of the total gene diversity was due to differences among populations within these regions, and 2.6% was due to differences among the nine regions. This allele-frequency data base was used to estimate the stock proportions of 730 juvenile coho salmon in offshore samples collected from central Oregon to northern Washington in June and September-October 1998−2000. Genetic mixed-stock analysis, together with recoveries of tagged or fin-clipped fish, indicates that about one half of the juveniles came from Columbia River hatcheries. Only 22% of the ocean-caught juveniles were wild fish, originating largely from coastal Oregon and Washington rivers (about 20%). Unlike previous studies of tagged juveniles, both tag recoveries and genetic estimates indicate the presence of fish from British Columbia and Puget Sound in southern waters. The most salient feature of genetic mixed stock estimates was the paucity of wild juveniles from natural populations in the Columbia River Basin. This result reflects the large decrease in the abundances of these populations in the last few decades.

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Location or stock-specific landing data are necessary to improve management of shark stocks, especially those imperiled by overexploitation as a result of the international shark fin trade. In the current absence of catch monitoring directly at extraction sites, genetic stock identification of fins collected from major market supply chain endpoints offers an overlooked but potentially useful approach for tracing the fins back to their geographical, or stock of, origin. To demonstrate the feasibility of this approach, we used mitochondrial control region (mtCR) sequences to trace the broad geographical origin of 62 Hong Kong market-derived Sphyrna lewini fins. Of these fins 21% were derived from the western Atlantic, where this species is listed as 'Endangered' by the International Union for the Conservation of Nature (IUCN). We also show that S. lewini mtCR sequences are geographically segregated in the western Atlantic (overall ΦST = 0.74, n = 177 sharks), indicating that breeding females either remain close to, or home back to, their natal region for parturition. Mixed stock analysis simulations showed that it is possible to estimate the relative contributions of these mitochondrial stocks to fin mixtures in globally sourced trade hubs. These findings underscore the feasibility of using genetic stock identification to source market-derived shark fins to obtain essential and otherwise unavailable data on exploitation levels, and thus to productively inform stock assessment and management of S. lewini and potentially also of other fished shark species. © Inter-Research 2009.

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The Stock Identification Methods Working Group (SIMWG) worked by correspondence in 2016. The working group was chaired by Lisa Kerr (USA). The work plan for SIMWG in 2016 comprised four Terms of Reference (ToR), some of which are continuing goals for SIMWG: a ) Review recent advances in stock identification methods; b ) Build a reference database with updated information on known biological stocks for species of ICES interest; c ) Provide technical reviews and expert opinions on matters of stock identifica-tion, as requested by specific Working Groups and SCICOM; d ) Review and report on advances in mixed stock analysis, and assess their po-tential role in improving precision of stock assessment. ToR a) is an ongoing task of SIMWG in which we provide a comprehensive update on recent applications of stock identification techniques to ICES species of interest, summa-rize new approaches in stock identification, and novel combinations of existing applica-tions. ToR b) is a multi-annual ToR in which SIMWG has taking steps to build a reference data-base consisting of SIMWG reviews of issues of stock identity for ICES species. ToR c) is a key ongoing task by SIMWG in which we addresses specific requests by ICES working groups for technical advice on issues of stock identity. This year we provided advice on mackerel in the Northeast Atlantic as requested by WGWIDE. ToR d) is a multi-annual ToR that is focused on tracking developments in the application of mixed stock analysis and the integration of this information into assessment and management.

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Information is summarized on juvenile salmonid distribution, size, condition, growth, stock origin, and species and environmental associations from June and August 2000 GLOBEC cruises with particular emphasis on differences related to the regions north and south of Cape Blanco off Southern Oregon. Juvenile salmon were more abundant during the August cruise as compared to the June cruise and were mainly distributed northward from Cape Blanco. There were distinct differences in distribution patterns between salmon species: chinook salmon were found close inshore in cooler water all along the coast and coho salmon were rarely found south of Cape Blanco. Distance offshore and temperature were the dominant explanatory variables related to coho and chinook salmon distribution. The nekton assemblages differed significantly between cruises. The June cruise was dominated by juvenile rockfishes, rex sole, and sablefish, which were almost completely absent in August. The forage fish community during June comprised Pacific herring and whitebait smelt north of Cape Blanco and surf smelt south of Cape Blanco. The fish community in August was dominated by Pacific sardines and highly migratory pelagic species. Estimated growth rates of juvenile coho salmon were higher in the GLOBEC study area than in areas farther north. An unusually high percentage of coho salmon in the study area were precocious males. Significant differences in growth and condition of juvenile coho salmon indicated different oceanographic environments north and south of Cape Blanco. The condition index was higher in juvenile coho salmon to the north but no significant differences were found for yearling chinook salmon. Genetic mixed stock analysis indicated that during June, most of the Chinook salmon in our sample originated from rivers along the central coast of Oregon. In August, chinook salmon sampled south of Cape Blanco were largely from southern Oregon and northern California; whereas most chinook salmon north of Cape Blanco were from the Central Valley in California.

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Loggerhead sea turtles (Caretta caretta) are migratory, long-lived, and slow maturing. They are difficult to study because they are seen rarely and their habitats range over vast stretches of the ocean. Movements of immature turtles between pelagic and coastal developmental habitats are particularly difficult to investigate because of inadequate tagging technologies and the difficulty in capturing significant numbers of turtles at sea. However, genetic markers found in mitochondrial DNA (mtDNA) provide a basis for predicting the origin of juvenile turtles in developmental habitats. Mixed stock analysis was used to determine which nesting populations were contributing individuals to a foraging aggregation of immature loggerhead turtles (mean 63.3 cm straight carapace length [SCL]) captured in coastal waters off Hutchinson Island, Florida. The results indicated that at least three different western Atlantic loggerhead sea turtle subpopulations contribute to this group: south Florida (69%), Mexico (20%), and northeast Florida-North Carolina (10%). The conservation and management of these immature sea turtles is complicated by their multinational genetic demographics.

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A wide range of vectors is currently introducing a plethora of alien marine species into indigenous marine species assemblages. Over the past two decades, molecular studies of non-native seaweeds, including cryptic invaders, have successfully identified the species involved and their sources; we briefly review these studies. As yet, however, little research has been directed towards examining the genetic consequences of seaweed invasions. Here we provide an overview of seaweed invasions from a genetic perspective, focusing on invader species for which the greatest amount of information is available. We review invasion processes, and rationalize evolutionary and genetic consequences for the indigenous and invader species into two main groups: (1) changes in gene-pool composition, in population structure and allele frequencies; and (2) changes in genome organization at the species level through hybridization, and in individual gene expression profiles at the levels of expressed messenger RNA and the proteome (i.e., all proteins synthesized) and thus the phenotype. We draw on studies of better-known aquatic and terrestrial organisms to point the way forward in revealing the genetic consequences of seaweed invasions. We also highlight potential applications of more recent methodological and statistical approaches, such as microarray technology, assignment tests and mixed stock analysis.

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Regulations on the exploitation of populations of commercially important fish species and the ensuing consumer interest in sustainable products have increased the need to accurately identify the population of origin of fish and fish products. Although genomics-based tools have proven highly useful, there are relatively few examples in marine fish displaying accurate origin assignment. We synthesize data for 156 single-nucleotide polymorphisms typed in 1039 herring, Clupea harengus L., spanning the Northeast Atlantic to develop a tool that allows assignment of individual herring to their regional origin. We show the method's suitability to address specific biological questions, as well as management applications. We analyse temporally replicated collections from two areas, the Skagerrak (n = 81, 84, 66) and the western Baltic (n = 52, 52). Both areas harbour heavily fished mixed-origin stocks, complicating management issues. We report novel genetic evidence that herring from the Baltic Sea contribute to catches in the North Sea, and find support that western Baltic feeding aggregations mainly constitute herring from the western Baltic with contributions from the Eastern Baltic. Our study describes a general approach and outlines a database allowing individual assignment and traceability of herring across a large part of its East Atlantic distribution.

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The Adriatic Sea is considered a feeding and developmental area for Mediterranean loggerhead turtles, but this area is severely threatened by human impacts. In the Adriatic Sea loggerhead turtles are often found stranded or floating, but they are also recovered as by-catch from fishing activities. Nevertheless, information about population structuring and origin of individuals found in the Adriatic Sea are still limited. Cooperation with fishermen and a good network of voluntary collaborators are essential for understanding their distribution, ecology and for developing conservation strategies in the Adriatic Sea. In this study, a comparative analysis of biometric data and DNA sequence polymorphism of the long fragment of the mitochondrial control region was carried out on ninety-three loggerheads recovered from three feeding areas in the Adriatic Sea: North-western, North-eastern and South Adriatic. Differences in turtles body sizes (e.g. Straight Carapace Length) among the three recovery areas and relationship between SCL and the type of recovery were investigated. The origin of turtles from Mediterranean rookeries and the use of the Adriatic feeding habitats by loggerheads in different life-stages were assessed to understand the migratory pathway of the species. The analysis of biometric data revealed a significant difference in turtle sizes between the Southern and the Northern Adriatic. Moreover, size of captured turtles resulted significantly different from the size of stranded and floating individuals. Actually, neritic sub-adults and adults are more affected by incidental captures than juveniles because of their feeding behavior. The Bayesian mixed-stock analysis showed a strong genetic relationship between the Adriatic aggregates and Mediterranean rookeries, while a low pro¬portion of individuals of Atlantic origin were detected in the Adriatic feeding grounds. The presence of migratory pathways towards the Adriatic Sea due to the surface current system was reinforced by the finding of individuals bearing haplotypes endemic to the nesting populations of Libya, Greece and Israel. A relatively high contribution from Turkey and Cyprus to the Northwest and South Adriatic populations was identified when the three sampled areas were analyzed independently. These results have to be taken in account in a conservative perspective, since coastal hazards, affecting the population of turtles feeding in the Adriatic Sea may also affect the nesting populations of the Eastern Mediterranean with a unique genetic pattern.

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Variation at 14 microsatellite loci was examined in 34 chum salmon (Oncorhynchus keta) populations from Russia and evaluated for its use in the determination of population structure and stock composition in simulated mixed-stock fishery samples. The genetic differentiation index (Fst) over all populations and loci was 0.017, and individual locus values ranged from 0.003 to 0.054. Regional population structure was observed, and populations from Primorye, Sakhalin Island, and northeast Russia were the most distinct. Microsatellite variation provided evidence of a more fine-scale population structure than those that had previously been demonstrated with other genetic-based markers. Analysis of simulated mixed-stock samples indicated that accurate and precise regional estimates of stock composition were produced when the microsatellites were used to estimate stock compositions. Microsatellites can be used to determine stock composition in geographically separate Russian coastal chum salmon fisheries and provide a greater resolution of stock composition and population structure than that previously provided with other techniques.