975 resultados para RPA statistics


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Arctic sea ice is declining rapidly, making it vital to understand the importance of different types of sea ice for ice-dependent species such as polar bears Ursus maritimus. In this study we used GPS telemetry (25 polar bear tracks obtained in Svalbard, Norway, during spring) and high-resolution synthetic aperture radar (SAR) sea-ice data to investigate fine-scale space use by female polar bears. Space use patterns differed according to reproductive state; females with cubs of the year (COYs) had smaller home ranges and used fast-ice areas more frequently than lone females. First-passage time (FPT) analysis revealed that females with COYs displayed significantly longer FPTs near (<10 km) glacier fronts than in other fast-ice areas; lone females also increased their FPTs in such areas, but they also frequently used drifting pack ice. These results clearly demonstrate the importance of fast-ice areas, in particular close to glacier fronts, especially for females with COYs. Access to abundant and predictable prey (ringed seal pups), energy conservation and reluctance to cross large open water areas are possible reasons for the observed patterns. However, glacier fronts are retracting in Svalbard, and declines in land-fast ice have been notable over the past decade. The eventual disappearance of these important habitats might become critical for the survival of polar bear cubs in Svalbard and other regions with similar habitat characteristics. Given the relatively small size of many fast-ice areas in Svalbard, the results observed in this study would not have been revealed using less accurate location data or lower-resolution sea-ice data.

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Three ice type regimes at Ice Station Belgica (ISB), during the 2007 International Polar Year SIMBA (Sea Ice Mass Balance in Antarctica) expedition, were characterized and assessed for elevation, snow depth, ice freeboard and thickness. Analyses of the probability distribution functions showed great potential for satellite-based altimetry for estimating ice thickness. In question is the required altimeter sampling density for reasonably accurate estimation of snow surface elevation given inherent spatial averaging. This study assesses an effort to determine the number of laser altimeter 'hits' of the ISB floe, as a representative Antarctic floe of mixed first- and multi-year ice types, for the purpose of statistically recreating the in situ-determined ice-thickness and snow depth distribution based on the fractional coverage of each ice type. Estimates of the fractional coverage and spatial distribution of the ice types, referred to as ice 'towns', for the 5 km**2 floe were assessed by in situ mapping and photo-visual documentation. Simulated ICESat altimeter tracks, with spot size ~70 m and spacing ~170 m, sampled the floe's towns, generating a buoyancy-derived ice thickness distribution. 115 altimeter hits were required to statistically recreate the regional thickness mean and distribution for a three-town assemblage of mixed first- and multi-year ice, and 85 hits for a two-town assemblage of first-year ice only: equivalent to 19.5 and 14.5 km respectively of continuous altimeter track over a floe region of similar structure. Results have significant implications toward model development of sea-ice sampling performance of the ICESat laser altimeter record as well as maximizing sampling characteristics of satellite/airborne laser and radar altimetry missions for sea-ice thickness.

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Despite their high abundance and their high importance for the oceanic matter flux, heterotrophic nanoflagellates are only poorly studied in the deep-sea regions. Studies on the choanoflagellate distribution during two deep-sea expeditions, to the South Atlantic (5038 m) and Antarctica (Weddell Sea, 2551 m), revealed the deepest records of choanoflagellates so far. A new species, (Lagenoeca antarctica) with a conspicuous spike structure on the theca is described from deep Antarctic waters. Lagenoeca antarctica sp. n. is a solitary unstalked free living salpingoecid-like choanoflagellate. The protoplast is surrounded by a typical theca with unique spikes only visible in SEM micrographs. The ovoid cell nearly fills the whole theca and ranges in size from 4 to 6 µm. The collar measures 2-3 µm and the flagellum 3-5 µm. A second species, Salpingoeca abyssalis sp. n., was isolated from the abyssal plain of the South Atlantic (5038 m depth). Floating and attached forms were observed. The protoplast ranges from to 2 to 4 µm in length and 1 to 2 µm in width. The collar is about the same length as the protoplast and the flagellum has 2 to 2.5 × the length of the protoplast. Phylogenetic analyses based on a fragment of SSU rDNA revealed Salpingoeca abyssalis to cluster together with a marine isolate of Salpingoeca infusionum while Lagenoeca antarctica clusters separately from the other codonosigid and salpingoecid taxa. Salpingoeca abyssalis and an undetermined Monosiga species seems to be the first choanoflagellate species recorded from the abyssal plain.

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The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models skills, while the use of standard dataset facilitates models inter-comparison. North Atlantic albacore tuna is exploited all year round by longline and in summer and autumn by surface fisheries and fishery statistics compiled by the International Commission for the Conservation of Atlantic Tunas (ICCAT). Catch and effort with geographical coordinates at monthly spatial resolution of 1° or 5° squares were extracted for this species with a careful definition of fisheries and data screening. In total, thirteen fisheries were defined for the period 1956-2010, with fishing gears longline, troll, mid-water trawl and bait fishing. However, the spatialized catch effort data available in ICCAT database represent a fraction of the entire total catch. Length frequencies of catch were also extracted according to the definition of fisheries above for the period 1956-2010 with a quarterly temporal resolution and spatial resolutions varying from 1°x 1° to 10°x 20°. The resolution used to measure the fish also varies with size-bins of 1, 2 or 5 cm (Fork Length). The screening of data allowed detecting inconsistencies with a relatively large number of samples larger than 150 cm while all studies on the growth of albacore suggest that fish rarely grow up over 130 cm. Therefore, a threshold value of 130 cm has been arbitrarily fixed and all length frequency data above this value removed from the original data set.

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The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models skills, while the use of standard dataset facilitates models inter-comparison. North Atlantic albacore tuna is exploited all year round by longline and in summer and autumn by surface fisheries and fishery statistics compiled by the International Commission for the Conservation of Atlantic Tunas (ICCAT). Catch and effort with geographical coordinates at monthly spatial resolution of 1° or 5° squares were extracted for this species with a careful definition of fisheries and data screening. In total, thirteen fisheries were defined for the period 1956-2010, with fishing gears longline, troll, mid-water trawl and bait fishing. However, the spatialized catch effort data available in ICCAT database represent a fraction of the entire total catch. Length frequencies of catch were also extracted according to the definition of fisheries above for the period 1956-2010 with a quarterly temporal resolution and spatial resolutions varying from 1°x 1° to 10°x 20°. The resolution used to measure the fish also varies with size-bins of 1, 2 or 5 cm (Fork Length). The screening of data allowed detecting inconsistencies with a relatively large number of samples larger than 150 cm while all studies on the growth of albacore suggest that fish rarely grow up over 130 cm. Therefore, a threshold value of 130 cm has been arbitrarily fixed and all length frequency data above this value removed from the original data set.

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The development of the ecosystem approach and models for the management of ocean marine resources requires easy access to standard validated datasets of historical catch data for the main exploited species. They are used to measure the impact of biomass removal by fisheries and to evaluate the models skills, while the use of standard dataset facilitates models inter-comparison. North Atlantic albacore tuna is exploited all year round by longline and in summer and autumn by surface fisheries and fishery statistics compiled by the International Commission for the Conservation of Atlantic Tunas (ICCAT). Catch and effort with geographical coordinates at monthly spatial resolution of 1° or 5° squares were extracted for this species with a careful definition of fisheries and data screening. In total, thirteen fisheries were defined for the period 1956-2010, with fishing gears longline, troll, mid-water trawl and bait fishing. However, the spatialized catch effort data available in ICCAT database represent a fraction of the entire total catch. Length frequencies of catch were also extracted according to the definition of fisheries above for the period 1956-2010 with a quarterly temporal resolution and spatial resolutions varying from 1°x 1° to 10°x 20°. The resolution used to measure the fish also varies with size-bins of 1, 2 or 5 cm (Fork Length). The screening of data allowed detecting inconsistencies with a relatively large number of samples larger than 150 cm while all studies on the growth of albacore suggest that fish rarely grow up over 130 cm. Therefore, a threshold value of 130 cm has been arbitrarily fixed and all length frequency data above this value removed from the original data set.