341 resultados para Callinectes ornatus
Ornatus latinae linguae seu ratio nitide ornatéque scribendi opera et studio vnius è Societate Iesu.
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Mode of access: Internet.
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Contiene: Imagines et delineamenta exterioris interiorisque ornatus Vaticanae Basilicae ... con portadilla propia tras p. 596.
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We have isolated 18 polymorphic microsatellite loci for Cophixalus ornatus from genomic libraries enriched for (AAAG)(n), (AACC)(n) and (AAGG)(n) repetitive elements. The number of alleles ranges from five to 22 per locus with the observed heterozygosity ranging from 0.10 to 0.92. These markers will be useful for the analysis of population structure in C. ornatus and testing alternative models of speciation.
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The ornate tropical rock lobster, Panulirus ornatus has substantial potential as an aquaculture species though disease outbreaks during the animal's extended larval lifecycle are major constraints for success. In order to effectively address such disease-related issues, an improved understanding of the composition and dynamics of the microbial communities in the larval rearing tanks is required. This study used flow cytometry and molecular microbial techniques (clone libraries and denaturing gradient gel electrophoresis (DGGE)) to quantify and characterise the microbial community of the water column in the early stages (developmental stage I-II) of a P. ornatus larval rearing system. DGGE analysis of a 5000 L larval rearing trial demonstrated a dynamic microbial community with distinct changes in the community structure after initial stocking (day I to day 2) and from day 4 to day 5, after which the structure was relatively stable. Flow cytometry analysis of water samples taken over the duration of the trial demonstrated a major increase in bacterial load leading up to and peaking on the first day of the initial larval moult (day 7), before markedly decreasing prior to when > 50% of larvae moulted (day 9). A clone library of a day 10 water sample taken following a mass larval mortality event reflected high microbial diversity confirmed by statistical analysis indices. Sequences retrieved from both clone library and DGGE analyses were dominated by gamma- and alpha-Proteobacteria affiliated organisms with additional sequences affiliated with beta- and epsilon-Proteobacteria, Bacteroidetes, Cytophagales and Chlamydiales groups. Vibrio affiliated species were commonly retrieved in the clone library, though absent from DGGE analysis.
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The evaluation and identification of habitats that function as nurseries for marine species has the potential to improve conservation and management. A key assessment of nursery habitat is estimating individual growth. However, the discrete growth of crustaceans presents a challenge for many traditional in situ techniques to accurately estimate growth over a short temporal scale. To evaluate the use of nucleic acid ratios (R:D) for juvenile blue crab (Callinectes sapidus), I developed and validated an R:D-based index of growth in the laboratory. R:D based growth estimates of crabs collected in the Patuxent River, MD indicated growth ranged from 0.8-25.9 (mg·g-1·d-1). Overall, there was no effect of size on growth, whereas there was a weak, but significant effect of date. These data provide insight into patterns of habitat-specific growth. These results highlight the complexity of the biological and physical factors which regulate growth of juvenile blue crabs in the field.
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The contemporary methodology for growth models of organisms is based on continuous trajectories and thus it hinders us from modelling stepwise growth in crustacean populations. Growth models for fish are normally assumed to follow a continuous function, but a different type of model is needed for crustacean growth. Crustaceans must moult in order for them to grow. The growth of crustaceans is a discontinuous process due to the periodical shedding of the exoskeleton in moulting. The stepwise growth of crustaceans through the moulting process makes the growth estimation more complex. Stochastic approaches can be used to model discontinuous growth or what are commonly known as "jumps" (Figure 1). However, in stochastic growth model we need to ensure that the stochastic growth model results in only positive jumps. In view of this, we will introduce a subordinator that is a special case of a Levy process. A subordinator is a non-decreasing Levy process, that will assist in modelling crustacean growth for better understanding of the individual variability and stochasticity in moulting periods and increments. We develop the estimation methods for parameter estimation and illustrate them with the help of a dataset from laboratory experiments. The motivational dataset is from the ornate rock lobster, Panulirus ornatus, which can be found between Australia and Papua New Guinea. Due to the presence of sex effects on the growth (Munday et al., 2004), we estimate the growth parameters separately for each sex. Since all hard parts are shed too often, the exact age determination of a lobster can be challenging. However, the growth parameters for the aforementioned moult processes from tank data being able to estimate through: (i) inter-moult periods, and (ii) moult increment. We will attempt to derive a joint density, which is made up of two functions: one for moult increments and the other for time intervals between moults. We claim these functions are conditionally independent given pre-moult length and the inter-moult periods. The variables moult increments and inter-moult periods are said to be independent because of the Markov property or conditional probability. Hence, the parameters in each function can be estimated separately. Subsequently, we integrate both of the functions through a Monte Carlo method. We can therefore obtain a population mean for crustacean growth (e. g. red curve in Figure 1). [GRAPHICS]
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James (1991, Biometrics 47, 1519-1530) constructed unbiased estimating functions for estimating the two parameters in the von Bertalanffy growth curve from tag-recapture data. This paper provides unbiased estimating functions for a class of growth models that incorporate stochastic components and explanatory variables. a simulation study using seasonal growth models indicates that the proposed method works well while the least-squares methods that are commonly used in the literature may produce substantially biased estimates. The proposed model and method are also applied to real data from tagged rack lobsters to assess the possible seasonal effect on growth.
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In the analysis of tagging data, it has been found that the least-squares method, based on the increment function known as the Fabens method, produces biased estimates because individual variability in growth is not allowed for. This paper modifies the Fabens method to account for individual variability in the length asymptote. Significance tests using t-statistics or log-likelihood ratio statistics may be applied to show the level of individual variability. Simulation results indicate that the modified method reduces the biases in the estimates to negligible proportions. Tagging data from tiger prawns (Penaeus esculentus and Penaeus semisulcatus) and rock lobster (Panulirus ornatus) are analysed as an illustration.
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Project is a continuation of a series of externally funded projects aimed at developing aquaculture technology for the production of tropical rock lobster, Panulirus ornatus.
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Organismal survival in marine habitats is often positively correlated with habitat structural complexity at local (within-patch) spatial scales. Far less is known, however, about how marine habitat structure at the landscape scale influences predation and other ecological processes, and in particular, how these processes are dictated by the interactive effect of habitat structure at local and landscape scales. The relationship between survival and habitat structure can be modeled with the habitat-survival function (HSF), which often takes on linear, hyperbolic, or sigmoid forms. We used tethering experiments to determine how seagrass landscape structure influenced the HSF for juvenile blue crabs Callinectes sapidus Rathbun in Back Sound, North Carolina, USA. Crabs were tethered in artificial seagrass plots of 7 different shoot densities embedded within small (1 – 3 m2) or large (>100 m2) seagrass patches (October 1999), and within 10 × 10 m landscapes containing patchy (<50% cover) or continuous (>90% cover) seagrass (July 2000). Overall, crab survival was higher in small than in large patches, and was higher in patchy than in continuous seagrass. The HSF was hyperbolic in large patches and in continuous seagrass, indicating that at low levels of habitat structure, relatively small increases in structure resulted in substantial increases in juvenile blue crab survival. However, the HSF was linear in small seagrass patches in 1999 and was parabolic in patchy seagrass in 2000. A sigmoid HSF, in which a threshold level of seagrass structure is required for crab survival, was never observed. Patchy seagrass landscapes are valuable refuges for juvenile blue crabs, and the effects of seagrass structural complexity on crab survival can only be fully understood when habitat structure at larger scales is considered.
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Presentation to elected officials [and American Fisheries Society] on the wealth of research to be done in the Chesapeake Bay. Citing drop in oyster production from a high of 17,000,000 bushels in 1885 to 2,000,000 bushels in 1925 or one-eighth of its one-time abundance. Citing water studies through the late 1880's-90's. Report of experiments with the Japanese Oyster O. gigas. Also addresses Crab, Callinectes sapidus and classes held. (PDF contains 7 pages)