984 resultados para Distributed vertical loads


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From 2001 to 2006, 71 pop-up satellite archival tags (PSATs) were deployed on five species of pelagic shark (blue shark [Prionace glauca]; shortfin mako [Isurus oxyrinchus]; silky shark [Carcharhinus falciformis]; oceanic whitetip shark [C. longimanus]; and bigeye thresher [Alopias superciliosus]) in the central Pacific Ocean to determine species-specific movement patterns and survival rates after release from longline fishing gear. Only a single postrelease mortality could be unequivocally documented: a male blue shark which succumbed seven days after release. Meta-analysis of published reports and the current study (n=78 reporting PSATs) indicated that the summary effect of postrelease mortality for blue sharks was 15% (95% CI, 8.5–25.1%) and suggested that catch-and-release in longline fisheries can be a viable management tool to protect parental biomass in shark populations. Pelagic sharks displayed species-specific depth and temperature ranges, although with significant individual temporal and spatial variability in vertical movement patterns, which were also punctuated by stochastic events (e.g., El Niño-Southern Oscillation). Pelagic species can be separated into three broad groups based on daytime temperature preferences by using the unweighted pair-group method with arithmetic averaging clustering on a Kolmogorov-Smirnov Dmax distance matrix: 1) epipelagic species (silky and oceanic whitetip sharks), which spent >95% of their time at temperatures within 2°C of sea surface temperature; 2) mesopelagic-I species (blue sharks and shortfin makos, which spent 95% of their time at temperatures from 9.7° to 26.9°C and from 9.4° to 25.0°C, respectively; and 3) mesopelagic-II species (bigeye threshers), which spent 95% of their time at temperatures from 6.7° to 21.2°C. Distinct thermal niche partitioning based on body size and latitude was also evident within epipelagic species.

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The stage-specific distribution of Alaska plaice (Pleuronectes quadrituberculatus) eggs in the southeastern Bering Sea was examined with collections made in mid-May in 2002, 2003, 2005, and 2006. Eggs in the early stages of development were found primarily offshore of the 40-m isobath. Eggs in the middle and late stages of development were found inshore and offshore of the 40-m isobath. There was some evidence that early-stage eggs occur deeper in the water column than late-stage eggs, although year-to-year variability in that trend was observed. Most eggs were in the later stages of development; therefore the majority of spawning is estimated to have occurred a few weeks before collection—probably April—and may be highly synchronized among local spawning areas. Results indicate that sampling with continuous underway fish egg collectors(CUFES) should be supplemented with sampling of the entire water column to ensure adequate samples of all egg stages of Alaska plaice. Data presented offer new information on the stage-dependent horizontal and vertical distribution of Alaska plaice eggs in the Bering Sea and provide further evidence that the early life history stages of this species are vulnerable to near-surface variations in hydrographical conditions and climate forcing.

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We examined the diel ver-tical distribution, concentration, and community structure of ichthyoplank-ton from a single station 69 km off the central Oregon coast in the northeast Pacific Ocean. The 74 depth-stratified samples yielded 1571 fish larvae from 20 taxa, representing 11 families, and 128 fish eggs from 11 taxa within nine families. Dominant larval taxa were Sebastes spp. (rockfishes), Stenobra-chius leucopsarus (northern lampfish), Tarletonbeania crenularis (blue lan-ternfish), and Lyopsetta exilis (slender sole), and the dominant egg taxa were Sardinops sagax (Pacific sardine), Icichthys lockingtoni (medusafish), and Chauliodus macouni (Pacific viperfish). Larval concentrations generally increased from the surface to 50 m, then decreased with depth. Larval concentrations were higher at night than during the day, and there was evidence of larval diel vertical migration. Depth stratum was the most important factor explaining variability in larval and egg concentrations.

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Thirty-three skipjack tuna (Katsuwonus pelamis) (53−73 cm fork length) were caught and released with implanted archival tags in the eastern equatorial Pacific Ocean during April 2004. Six skipjack tuna were recap-tured, and 9.3 to 10.1 days of depth and temperature data were down-loaded from five recovered tags. The vertical habitat-use distributions indicated that skipjack tuna not associated with floating objects spent 98.6% of their time above the thermocline (depth=44 m) during the night, but spent 37.7% of their time below the thermocline during the day. When not associated with floating objects, skipjack tuna displayed repetitive bounce-diving behavior to depths between 50 and 300 m during the day. The deepest dive recorded was 596 m, where the ambient temperature was 7.7°C. One dive was particularly remarkable because the fish contin-uously swam for 2 hours below the thermocline to a maximum depth of 330 m. During that dive, the ambient temperature reached a low of 10.5°C, and the peritoneal cavity temperature reached a low of 15.9°C. The vertical movements and habitat use of skipjack tuna, revealed in this study, provide a much greater understanding of their ecological niche and catchability by purse-seine fisheries.

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The stone marten is a widely distributed mustelid in the Palaearctic region that exhibits variable habitat preferences in different parts of its range. The species is a Holocene immigrant from southwest Asia which, according to fossil remains, followed the expansion of the Neolithic farming cultures into Europe and possibly colonized the Iberian Peninsula during the Early Neolithic (ca. 7,000 years BP). However, the population genetic structure and historical biogeography of this generalist carnivore remains essentially unknown. In this study we have combined mitochondrial DNA (mtDNA) sequencing (621 bp) and microsatellite genotyping (23 polymorphic markers) to infer the population genetic structure of the stone marten within the Iberian Peninsula. The mtDNA data revealed low haplotype and nucleotide diversities and a lack of phylogeographic structure, most likely due to a recent colonization of the Iberian Peninsula by a few mtDNA lineages during the Early Neolithic. The microsatellite data set was analysed with a) spatial and non-spatial Bayesian individual-based clustering (IBC) approaches (STRUCTURE, TESS, BAPS and GENELAND), and b) multivariate methods [discriminant analysis of principal components (DAPC) and spatial principal component analysis (sPCA)]. Additionally, because isolation by distance (IBD) is a common spatial genetic pattern in mobile and continuously distributed species and it may represent a challenge to the performance of the above methods, the microsatellite data set was tested for its presence. Overall, the genetic structure of the stone marten in the Iberian Peninsula was characterized by a NE-SW spatial pattern of IBD, and this may explain the observed disagreement between clustering solutions obtained by the different IBC methods. However, there was significant indication for contemporary genetic structuring, albeit weak, into at least three different subpopulations. The detected subdivision could be attributed to the influence of the rivers Ebro, Tagus and Guadiana, suggesting that main watercourses in the Iberian Peninsula may act as semi-permeable barriers to gene flow in stone martens. To our knowledge, this is the first phylogeographic and population genetic study of the species at a broad regional scale. We also wanted to make the case for the importance and benefits of using and comparing multiple different clustering and multivariate methods in spatial genetic analyses of mobile and continuously distributed species.

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Multi-Agent Reinforcement Learning (MARL) algorithms face two main difficulties: the curse of dimensionality, and environment non-stationarity due to the independent learning processes carried out by the agents concurrently. In this paper we formalize and prove the convergence of a Distributed Round Robin Q-learning (D-RR-QL) algorithm for cooperative systems. The computational complexity of this algorithm increases linearly with the number of agents. Moreover, it eliminates environment non sta tionarity by carrying a round-robin scheduling of the action selection and execution. That this learning scheme allows the implementation of Modular State-Action Vetoes (MSAV) in cooperative multi-agent systems, which speeds up learning convergence in over-constrained systems by vetoing state-action pairs which lead to undesired termination states (UTS) in the relevant state-action subspace. Each agent's local state-action value function learning is an independent process, including the MSAV policies. Coordination of locally optimal policies to obtain the global optimal joint policy is achieved by a greedy selection procedure using message passing. We show that D-RR-QL improves over state-of-the-art approaches, such as Distributed Q-Learning, Team Q-Learning and Coordinated Reinforcement Learning in a paradigmatic Linked Multi-Component Robotic System (L-MCRS) control problem: the hose transportation task. L-MCRS are over-constrained systems with many UTS induced by the interaction of the passive linking element and the active mobile robots.