989 resultados para Chapman, Donald


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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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Little is known about the ocean distributions of wild juvenile coho salmon off the Oregon-Washington coast. In this study we report tag recoveries and genetic mixed-stock estimates of juvenile fish caught in coastal waters near the Columbia River plume. To support the genetic estimates, we report an allozyme-frequency baseline for 89 wild and hatchery-reared coho salmon spawning populations, extending from northern California to southern British Columbia. The products of 59 allozyme-encoding loci were examined with starch-gel electrophoresis. Of these, 56 loci were polymorphic, and 29 loci had P0.95 levels of polymorphism. Average heterozygosities within populations ranged from 0.021 to 0.046 and averaged 0.033. Multidimensional scaling of chord genetic distances between samples resolved nine regional groups that were sufficiently distinct for genetic mixed-stock analysis. About 2.9% of the total gene diversity was due to differences among populations within these regions, and 2.6% was due to differences among the nine regions. This allele-frequency data base was used to estimate the stock proportions of 730 juvenile coho salmon in offshore samples collected from central Oregon to northern Washington in June and September-October 1998−2000. Genetic mixed-stock analysis, together with recoveries of tagged or fin-clipped fish, indicates that about one half of the juveniles came from Columbia River hatcheries. Only 22% of the ocean-caught juveniles were wild fish, originating largely from coastal Oregon and Washington rivers (about 20%). Unlike previous studies of tagged juveniles, both tag recoveries and genetic estimates indicate the presence of fish from British Columbia and Puget Sound in southern waters. The most salient feature of genetic mixed stock estimates was the paucity of wild juveniles from natural populations in the Columbia River Basin. This result reflects the large decrease in the abundances of these populations in the last few decades.

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Although subsampling is a common method for describing the composition of large and diverse trawl catches, the accuracy of these techniques is often unknown. We determined the sampling errors generated from estimating the percentage of the total number of species recorded in catches, as well as the abundance of each species, at each increase in the proportion of the sorted catch. We completely partitioned twenty prawn trawl catches from tropical northern Australia into subsamples of about 10 kg each. All subsamples were then sorted, and species numbers recorded. Catch weights ranged from 71 to 445 kg, and the number of fish species in trawls ranged from 60 to 138, and invertebrate species from 18 to 63. Almost 70% of the species recorded in catches were “rare” in subsamples (less than one individual per 10 kg subsample or less than one in every 389 individuals). A matrix was used to show the increase in the total number of species that were recorded in each catch as the percentage of the sorted catch increased. Simulation modelling showed that sorting small subsamples (about 10% of catch weights) identified about 50% of the total number of species caught in a trawl. Larger subsamples (50% of catch weight on average) identified about 80% of the total species caught in a trawl. The accuracy of estimating the abundance of each species also increased with increasing subsample size. For the “rare” species, sampling error was around 80% after sorting 10% of catch weight and was just less than 50% after 40% of catch weight had been sorted. For the “abundant” species (five or more individuals per 10 kg subsample or five or more in every 389 individuals), sampling error was around 25% after sorting 10% of catch weight, but was reduced to around 10% after 40% of catch weight had been sorted.

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Otoliths from blue rockfish (Sebastes mystinus), were aged by using a combination of surface and break-and-burn methods. The samples were collected between 1978 and 1998 off central and northern California. Annual growth increments in the otoliths were validated by using edge analysis for females up to age 23 and for males to age 25.The first annual growth increment was identified by comparing the diameter of the otolith from fish known to be one year old collected in May (when translucent zone formation was completed) to the mean diameter of the first translucent zone in the otoliths from older fish. Our estimated maxi-mum ages of 44 years for males and 41 years for females were much older than those reported in previous studies. Von Bertalanffy growth models were developed for each sex. Females grew faster and reached larger maximum length than males. The growth models were similar to those generated in other studies of this species in southern and central California. Fish from northern and central California had similar maximum sizes, maximum ages, and growth model parameters.

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Life-history dynamics of pinfish (Lagodon rhomboides) were examined from data derived from random station surveys conducted in Tampa Bay and adjacent Gulf of Mexico waters during 1993–97. In addition, patterns in spatial distribution and abundance in Gulf of Mexico waters were investigated. Ages determined from whole otoliths ranged from 0 to 7 years, and von Bertalanffy growth models for males and females were not significantly different. Von Bertalanffy growth model parameters were L∞=219.9 mm SL, k =0.33/yr, and t0 =–1.10 years for all fish combined. High gonadosomatic indices during October–December indicated that some spawning may occur in Tampa Bay. Estimated lengths at 50% maturity were 132 mm SL for males and 131 mm SL for females. Total instantaneous mortality rates derived from the Chapman-Robson estimator ranged from 0.88 to 1.08/yr, and natural mortality was estimated to be 0.78/yr. In Gulf of Mexico waters, pinfish catch rates declined with increasing depth, and most pinfish were caught in <17 m of water. Length distributions showed that pinfish segregate by size with increasing depth.

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EXTRACT (SEE PDF FOR FULL ABSTRACT): Four cores recovered from Little Packer Lake in Glenn County, California, have provided a paleoflood record for the past 800 years. ... The sequence of flood deposits in the top 2 meters of the record shows a reasonable agreement with the known history of floods during the past 150 years. At least three major flood events are indicated for AD 1400-1525, although these dates may have to be revised when more dates become available.

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The food value of marine algae lies mainly in their minerals and vitamins content (Chapman and Chapman, 1980). They are good source of vitamins like A,D,E,B series and C. Pakistan has a rich marine flora, so far more than 200 species of seaweeds have been reported (Shameel and Tanaka, 1992).

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Lake Victoria, besides being the second largest in the world after Lake Superior, is the largest tropical lake. Its waters are shared by Kenya (6% of the surface area), Uganda (43%), and Tanzania (51%). Before dramatic structural and functional changes manifested in the lake's ecosystem especially in the 1980s, fish life flourished in the lake's entire water column at all times of the year. Currently, the situation is much more different from what it was in the past. The exponential increase in the introduced Nile perch (Lates niloticus) and Nile tilapia (Oreochromis niloticus) stocks, siltation, wetland degradation and eutrophication have characterised the lake ecosystem. The two exotic species and the small native cyprinid (Rastrineobola argentea) form the basis of the commercial fishery that was once dominated by two native tilapiines (Oreochromis esculentus and Oreochromis variabilis) and five other large-bodied endemic fishes. Severe deoxygenation observed at shallow depths (Ochumba 1990; Hecky et al., 1994) indicates that a large volume of the lake is unable to sustain fish life. The Lake Victoria catchment is one of the most densely populated areas in East Africa, encompassing a population of about 30 million people. Widespread poverty resulting from high inflation rates, lack of opportunities and general unemployment have characterised the lakeside communities over much of the last two decades. The biophysical environment in which Lake Victoria exists makes the lake particularly susceptible to changes that occur as a result of human modification to the watershed or the lake itself, thus rendering benefits from the lake unsustainable.

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Over the past 50 years, economic and technological developments have dramatically increased the human contribution to ambient noise in the ocean. The dominant frequencies of most human-made noise in the ocean is in the low-frequency range (defined as sound energy below 1000Hz), and low-frequency sound (LFS) may travel great distances in the ocean due to the unique propagation characteristics of the deep ocean (Munk et al. 1989). For example, in the Northern Hemisphere oceans low-frequency ambient noise levels have increased by as much as 10 dB during the period from 1950 to 1975 (Urick 1986; review by NRC 1994). Shipping is the overwhelmingly dominant source of low-frequency manmade noise in the ocean, but other sources of manmade LFS including sounds from oil and gas industrial development and production activities (seismic exploration, construction work, drilling, production platforms), and scientific research (e.g., acoustic tomography and thermography, underwater communication). The SURTASS LFA system is an additional source of human-produced LFS in the ocean, contributing sound energy in the 100-500 Hz band. When considering a document that addresses the potential effects of a low-frequency sound source on the marine environment, it is important to focus upon those species that are the most likely to be affected. Important criteria are: 1) the physics of sound as it relates to biological organisms; 2) the nature of the exposure (i.e. duration, frequency, and intensity); and 3) the geographic region in which the sound source will be operated (which, when considered with the distribution of the organisms will determine which species will be exposed). The goal in this section of the LFA/EIS is to examine the status, distribution, abundance, reproduction, foraging behavior, vocal behavior, and known impacts of human activity of those species may be impacted by LFA operations. To focus our efforts, we have examined species that may be physically affected and are found in the region where the LFA source will be operated. The large-scale geographic location of species in relation to the sound source can be determined from the distribution of each species. However, the physical ability for the organism to be impacted depends upon the nature of the sound source (i.e. explosive, impulsive, or non-impulsive); and the acoustic properties of the medium (i.e. seawater) and the organism. Non-impulsive sound is comprised of the movement of particles in a medium. Motion is imparted by a vibrating object (diaphragm of a speaker, vocal chords, etc.). Due to the proximity of the particles in the medium, this motion is transmitted from particle to particle in waves away from the sound source. Because the particle motion is along the same axis as the propagating wave, the waves are longitudinal. Particles move away from then back towards the vibrating source, creating areas of compression (high pressure) and areas of rarefaction (low pressure). As the motion is transferred from one particle to the next, the sound propagates away from the sound source. Wavelength is the distance from one pressure peak to the next. Frequency is the number of waves passing per unit time (Hz). Sound velocity (not to be confused with particle velocity) is the impedance is loosely equivalent to the resistance of a medium to the passage of sound waves (technically it is the ratio of acoustic pressure to particle velocity). A high impedance means that acoustic particle velocity is small for a given pressure (low impedance the opposite). When a sound strikes a boundary between media of different impedances, both reflection and refraction, and a transfer of energy can occur. The intensity of the reflection is a function of the intensity of the sound wave and the impedances of the two media. Two key factors in determining the potential for damage due to a sound source are the intensity of the sound wave and the impedance difference between the two media (impedance mis-match). The bodies of the vast majority of organisms in the ocean (particularly phytoplankton and zooplankton) have similar sound impedence values to that of seawater. As a result, the potential for sound damage is low; organisms are effectively transparent to the sound – it passes through them without transferring damage-causing energy. Due to the considerations above, we have undertaken a detailed analysis of species which met the following criteria: 1) Is the species capable of being physically affected by LFS? Are acoustic impedence mis-matches large enough to enable LFS to have a physical affect or allow the species to sense LFS? 2) Does the proposed SURTASS LFA geographical sphere of acoustic influence overlap the distribution of the species? Species that did not meet the above criteria were excluded from consideration. For example, phytoplankton and zooplankton species lack acoustic impedance mis-matches at low frequencies to expect them to be physically affected SURTASS LFA. Vertebrates are the organisms that fit these criteria and we have accordingly focused our analysis of the affected environment on these vertebrate groups in the world’s oceans: fishes, reptiles, seabirds, pinnipeds, cetaceans, pinnipeds, mustelids, sirenians (Table 1).

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