931 resultados para Capture-recapture Data
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A class of growth models incorporating time-dependent factors and stochastic perturbations are introduced. The proposed model includes the existing growth models used in fisheries as special cases. Particular attention is given to growth of a population (in average weight or length) from which observations are taken randomly each time and the analysis of tag-recapture data. Two real data sets are used for illustration: (a) to estimate the seasonal effect and population density effect on growth of farmed prawn (Penaeus monodon) from weight data and (b) to assess the effect of tagging on growth of barramundi (Lates calcarifer)
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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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The von Bertalanffy growth model is extended to incorporate explanatory variables. The generalized model includes the switched growth model and the seasonal growth model as special cases, and can also be used to assess the tagging effect on growth. Distribution-free and consistent estimating functions are constructed for estimation of growth parameters from tag-recapture data in which age at release is unknown. This generalizes the work of James (1991, Biometrics 47 1519-1530) who considered the classical model and allowed for individual variability in growth. A real dataset from barramundi (Lates calcarifer) is analysed to estimate the growth parameters and possible effect of tagging on growth.
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Ecological and genetic studies of marine turtles generally support the hypothesis of natal homing, but leave open the question of the geographical scale of genetic exchange and the capacity of turtles to shift breeding sites. Here we combine analyses of mitochondrial DNA (mtDNA) variation and recapture data to assess the geographical scale of individual breeding populations and the distribution of such populations through Australasia. We conducted multiscale assessments of mtDNA variation among 714 samples from 27 green turtle rookeries and of adult female dispersal among nesting sites in eastern Australia. Many of these rookeries are on shelves that were flooded by rising sea levels less than 10 000 years (c. 450 generations) ago. Analyses of sequence variation among the mtDNA control region revealed 25 haplotypes, and their frequency distributions indicated 17 genetically distinct breeding stocks (Management Units) consisting either of individual rookeries or groups of rookeries in general that are separated by more than 500 km. The population structure inferred from mtDNA was consistent with the scale of movements observed in long-term mark-recapture studies of east Australian rookeries. Phylogenetic analysis of the haplotypes revealed five clades with significant partitioning of sequence diversity (Φ = 68.4) between Pacific Ocean and Southeast Asian/Indian Ocean rookeries. Isolation by distance was indicated for rookeries separated by up to 2000 km but explained only 12% of the genetic structure. The emerging general picture is one of dynamic population structure influenced by the capacity of females to relocate among proximal breeding sites, although this may be conditional on large population sizes as existed historically across this region.
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Patch selection by grazing animals is difficult to quantify, particularly in large, extensive paddocks like those in northern Australia. However, advances in high resolution satellite imagery now allow identification of patch types over an entire paddock which combined with GPS collars to capture positional data, can give an accurate and comprehensive picture of landscape use by cattle.
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Background: The first phase of the Queensland Pharmacist Immunisation Pilot (QPIP) ran between April and August 2014, to pilot pharmacists administering influenza vaccinations for the flu season for the first time in Australia. Aim: An aim was to investigate factors facilitating implementation of a pharmacist vaccination service in the community pharmacy setting. Method: The QPIP pharmacies were divided into two arms; the South East Queensland arm consisting of 51 Terry White Chemists (TWCs), and 29 pharmacies in the North Queensland (NQ) arm. The TWCs featured pharmacies which previously provided a vaccination service and that were experienced with using an online booking system, providing an opportunity to capture booking data. Results: The TWCs delivered 9902 (90%) of the influenza vaccinations in QPIP. Of these, 48.5% of the vaccines were delivered via appointments made using the online booking system, while 13.3% were in-store bookings. Over one-third (38.2%) of the vaccinations delivered in were “walk-ins” where the vaccination was delivered ‘on the spot’ as spontaneous or opportunistic vaccinations. The absence of a booking system meant all vaccinations delivered in the NQ arm were “walk-ins”. The online-booking data showed 10:00 am and Tuesday being the most popular time and day for vaccinations. Patients preferred having their vaccinations in private consultation rooms, over areas which used a screen to partition off a private area. Discussion: The presence of an online booking system appeared to increase the efficiency and penetration of the of vaccine service delivery. Also, as the level of privacy afforded to patients increased, the number of patients vaccinated also increased. Conclusions: As pharmacist-delivered vaccination services start to progressively roll out across Australia; these findings pave the way for more efficient and effective implementation of the service.
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This paper presents a maximum likelihood method for estimating growth parameters for an aquatic species that incorporates growth covariates, and takes into consideration multiple tag-recapture data. Individual variability in asymptotic length, age-at-tagging, and measurement error are also considered in the model structure. Using distribution theory, the log-likelihood function is derived under a generalised framework for the von Bertalanffy and Gompertz growth models. Due to the generality of the derivation, covariate effects can be included for both models with seasonality and tagging effects investigated. Method robustness is established via comparison with the Fabens, improved Fabens, James and a non-linear mixed-effects growth models, with the maximum likelihood method performing the best. The method is illustrated further with an application to blacklip abalone (Haliotis rubra) for which a strong growth-retarding tagging effect that persisted for several months was detected. (C) 2013 Elsevier B.V. All rights reserved.
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The apparent thermal activation energy of 0.56 eV and the electron thermal capture cross section of 2.0 × 10-16 cm2 are measured for the gold related acceptor level in p+ nn+ silicon diodes by isothermal current transient and DLTS techniques. Using the emission and capture rate data and a degeneracy ratio of 2, the energy separation of the trap level from the conduction band is calculated and found to have the same temperature dependence as the band gap indicating that the acceptor level is pinned with respect to the valence band a t Ev + 0.637 eV.
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Despite considerable research on the impact of early childhood education (ECE), there is little empirical evidence about what the everyday work of educators entails. This paper reports on the development of a tool to capture generalisable data on the everyday work of educators so as to inform effective workforce policy. This tool—a taxonomy of early childhood educators’ work—was developed by drawing on the expertise of six early years’ experts from Australia and the United States of America (USA) and includes time-use diaries, focus groups and interviews with 21 early childhood educators working in long day care and preschool services. The taxonomy, which we present here, consists of 10 domains, each with a number of sub-classes. We propose that this taxonomy is a useful codification system for ascertaining the everyday work tasks, activities and actions of early childhood educators in diverse early years’ settings. It is anticipated that the taxonomy will prove a valuable tool for subsequent research investigating the early childhood workforce.
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Contributed to: III Bienal de Restauración Monumental: "Sobre la des-restauración" (Sevilla, Spain, Nov 23-25, 2006)
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The condition of soft-textured flesh in commercially harvested sablefish, Anoplopoma fimbria, from southeastern Alaska was investigated by National Marine Fisheries Service (NMFS) scientists from the Alaska Fisheries Science Center’s Auke Bay Laboratories (ABL) in Alaska and the Northwest Fisheries Science Center in Seattle, Wash. Sablefish were sampled by longline, pot, and trawl at five sites around Chichagof Island at depths of 259–988 m in the summer of 1985 and at depths of 259–913 m in the winter of 1986. At the time of capture and data collection, sablefish were categorized as being “firm” or “soft” by visual and tactile examination, individually weighed, measured for length, and sexed. Subsamples of the fish were analyzed and linear regressions and analyses of variance were performed on both the summer (n = 242) and winter (n = 439) data for combinations of chemical and physical analyses, depth of capture, weight vs. length, flesh condition, gonad condition, and sex. We successfully identified and selected sablefish with firm- and soft-textured flesh by tactile and visual methods. Abundance of firm fish in catches varied by season: 67% in winter and 40% in summer. Winter catches may give a higher yield than summer catches. Abundance of firm fish catches also varied with depth. Firm fish were routinely found shallower than soft fish. The highest percentage of firm fish were found at depths less than 365 m in summer and at 365–730 m in winter, whereas soft fish were usually more abundant at depths greater than 731 m. Catches of firm fish declined with increasing depth. More than 80% of the fish caught during winter at depths between 365 and 730 m had firm flesh, but this declined to 48% at these depths in summer. Longlines and pots caught similar proportions of firm and soft fish with both gears catching more firm than soft fish. Trawls caught a higher proportion of soft fish compared to longlines and pots in winter. Chemical composition of “firm” and “soft” fish differed. On average “soft” fish had 14% less protein, 12% more lipid, and 3% less ash than firm fish. Cooked yields from sablefish with soft-textured flesh were 31% less than cooked yields from firm fish. Sablefish flesh quality (firmness) related significantly to the biochemistry of white muscle with respect to 11 variables. Summer fish of all flesh conditions averaged 6% heavier than winter fish. Regulating depth of fishing could increase the yield from catches, but the feasibility and benefits from this action will require further evaluation and study. Results of this study provide a basis for reducing the harvest of sablefish with soft flesh and may stimulate further research into the cause and effect relationship of the sablefish soft-flesh phenomenon.
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Blue marlin, Makaira nigricans, tag and recapture data are summarized for 1954-1988. During this period, 8,447 fish have been tagged and only 30 (0.35 percent) have been returned. Results of the tagging program indicate that blue marlin not only travel considerable distances (7,OOO km from the U. S. Virgin Islands to the Ivory Coast of West Africa), but have remained at large for up to 8 years. Seasonal movements, however, are difficult to determine accurately.
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The growth of red sea urchins (Strongylocentrotus franciscanus) was modeled by using tag-recapture data from northern California. Red sea urchins (n=211) ranging in test diameter from 7 to 131 mm were examined for changes in size over one year. We used the function Jt+1 = Jt + f(Jt) to model growth, in which Jt is the jaw size (mm) at tagging, and Jt+1 is the jaw size one year later. The function f(Jt), represents one of six deterministic models: logistic dose response, Gaussian, Tanaka, Ricker, Richards, and von Bertalanffy with 3, 3, 3, 2, 3, and 2 minimization parameters, respectively. We found that three measures of goodness of fi t ranked the models similarly, in the order given. The results from these six models indicate that red sea urchins are slow growing animals (mean of 7.2 ±1.3 years to enter the fishery). We show that poor model selection or data from a limited range of urchin sizes (or both) produces erroneous growth parameter estimates and years-to-fishery estimates. Individual variation in growth dominated spatial variation at shallow and deep sites (F=0.246, n=199, P=0.62). We summarize the six models using a composite growth curve of jaw size, J, as a function of time, t: J = A(B – e–Ct) + Dt, in which each model is distinguished by the constants A, B, C, and D. We suggest that this composite model has the flexibility of the other six models and could be broadly applied. Given the robustness of our results regarding the number of years to enter the fishery, this information could be incorporated into future fishery management plans for red sea urchins in northern California.
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© 2015 John P. Cunningham and Zoubin Ghahramani. Linear dimensionality reduction methods are a cornerstone of analyzing high dimensional data, due to their simple geometric interpretations and typically attractive computational properties. These methods capture many data features of interest, such as covariance, dynamical structure, correlation between data sets, input-output relationships, and margin between data classes. Methods have been developed with a variety of names and motivations in many fields, and perhaps as a result the connections between all these methods have not been highlighted. Here we survey methods from this disparate literature as optimization programs over matrix manifolds. We discuss principal component analysis, factor analysis, linear multidimensional scaling, Fisher's linear discriminant analysis, canonical correlations analysis, maximum autocorrelation factors, slow feature analysis, sufficient dimensionality reduction, undercomplete independent component analysis, linear regression, distance metric learning, and more. This optimization framework gives insight to some rarely discussed shortcomings of well-known methods, such as the suboptimality of certain eigenvector solutions. Modern techniques for optimization over matrix manifolds enable a generic linear dimensionality reduction solver, which accepts as input data and an objective to be optimized, and returns, as output, an optimal low-dimensional projection of the data. This simple optimization framework further allows straightforward generalizations and novel variants of classical methods, which we demonstrate here by creating an orthogonal-projection canonical correlations analysis. More broadly, this survey and generic solver suggest that linear dimensionality reduction can move toward becoming a blackbox, objective-agnostic numerical technology.
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Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility.