934 resultados para SPECIES DISTRIBUTION MODELS


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Acknowledgment This research is supported by an award made by the RCUK Digital Economy program to the University of Aberdeen’s dot.rural Digital Economy Hub (ref. EP/G066051/1).

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The study of the large-sample distribution of the canonical correlations and variates in cointegrated models is extended from the first-order autoregression model to autoregression of any (finite) order. The cointegrated process considered here is nonstationary in some dimensions and stationary in some other directions, but the first difference (the “error-correction form”) is stationary. The asymptotic distribution of the canonical correlations between the first differences and the predictor variables as well as the corresponding canonical variables is obtained under the assumption that the process is Gaussian. The method of analysis is similar to that used for the first-order process.

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Understanding spatial distributions and how environmental conditions influence catch-per-unit-effort (CPUE) is important for increased fishing efficiency and sustainable fisheries management. This study investigated the relationship between CPUE, spatial factors, temperature, and depth using generalized additive models. Combinations of factors, and not one single factor, were frequently included in the best model. Parameters which best described CPUE varied by geographic region. The amount of variance, or deviance, explained by the best models ranged from a low of 29% (halibut, Charlotte region) to a high of 94% (sablefish, Charlotte region). Depth, latitude, and longitude influenced most species in several regions. On the broad geographic scale, depth was associated with CPUE for every species, except dogfish. Latitude and longitude influenced most species, except halibut (Areas 4 A/D), sablefish, and cod. Temperature was important for describing distributions of halibut in Alaska, arrowtooth flounder in British Columbia, dogfish, Alaska skate, and Aleutian skate. The species-habitat relationships revealed in this study can be used to create improved fishing and management strategies.

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In 22 samples, 6 from Josephine Bank and 16 from the Great Meteor Bank, 14 halacarid species were found and described. Halacarus spiniger n. sp., Copidognathus magniporus n. sp., Arhodeoporus lineatus n. sp., A. brevocularis n. sp., Coloboceras karamani n. sp., Scaptognathus minutus n. sp., and Atelopsalis newelli were hithero unknown. Acaromantis squilla Trouessart & Neumann and Atelopsalis tricuspis Trouessart were redescribed. Four larvae, probably belonging to Copidognathus longips Bartsch, C. tricorneata (Lohmann), Lohmannella falcata (Hodge), and Atelopsalis newelli n. sp. were described, two Scaptognathus larvae could not be identifird. To date only three species, Copidognathus tricorneata, Lohmannella falcata, and Scaptognathus minutus, have been found on both seamounts.

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The continuous plankton recorder (CPR) survey is an upper layer plankton monitoring program that has regularly collected samples, at monthly intervals, in the North Atlantic and adjacent seas since 1946. Water from approximately 6 m depth enters the CPR through a small aperture at the front of the sampler and travels down a tunnel where it passes through a silk filtering mesh of 270 µm before exiting at the back of the CPR. The plankton filtered on the silk is analyzed in sections corresponding to 10 nautical miles (approx. 3 m**3 of seawater filtered) and the plankton microscopically identified (Richardson et al., 2006 and reference therein). In the present study we used the CPR data to investigate the current basin scale distribution of C. finmarchicus (C5-C6), C. helgolandicus (C5-C6), C. hyperboreus (C5-C6), Pseudocalanus spp. (C6), Oithona spp. (C1-C6), total Euphausiida, total Thecosomata and the presence/absence of Cnidaria and the Phytoplankton Colour Index (PCI). The PCI, which is a visual assessment of the greenness of the silk, is used as an indicator of the distribution of total phytoplankton biomass across the Atlantic basin (Batten et al., 2003). Monthly data collected between 2000 and 2009 were gridded using the inverse-distance interpolation method, in which the interpolated values were the nodes of a 2 degree by 2 degree grid. The resulting twelve monthly matrices were then averaged within the year and in the case of the zooplankton the data were log-transformed (i.e. log10 (x+1).

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"July 1976."

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Includes supplements to some of the vols.; suppl. to v. 1-5 in v. 6; suppl. to v. 11 published separately.