98 resultados para ore reserve estimation


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The contributions of hematological factors to the distribution and estimations of Eustrongylides africanus larvae densities in Clarias gariepinus and C. anguillaris of Bida floodplain of Nigeria were documented for the first time. The hematological factors making the most important contributions to the distributions of E. africanus larvae infections in clarias species are mean corpuscular haemoglobin concentration (MCHC), mean corpuscular haemoglobin (MCH), mean corpuscular volume (MCV) and neutrophils count, in descending order of magnitude; having the manifestations for the months of January, March, September, and December of the year being closely related. Five haematological factors (neutrophils, lymphocytes and eosinophils counts; MCH and MCV) having positive or negative correlation coefficient (r) between 0.50 and 0.85 contributed to the estimated of E.africanus larvae densities in the wild population of Clarias species

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Among plant protein ingredients,ipil ipil (Leucaena leucocephala) leafmeal (ILLM) is considered the most nutritive plant protein source after soybean meal in aquatic feeds. That was proven in a 21-day experiment conducted to assess the response of juvenile Monosex Nile tilapia Oreochromis niloticus with four iso-nitrogenous formulated diets: One control diet was formulated based on fishmeal, one on soybean meal and one on rice bran, ipil ipil leafmeal was also included in experimental diets.

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Abstract Growth and condition of fish are functions of available food and environmental conditions. This led to the idea of using fish as a “consumption sensor” for the measurement of food intake over a defined period of time. A bio-physical model for the estimation of food consumption was developed based on the von Bertalanffy model. Whereas some of the input variables of the model, the initial and final lengths and masses of a fish and the temperature within the time period considered can easily be measured, internal characteristics of the species have to be determined indirectly. Three internal parameters are used in the model: the maintenance consumption at 0°C, the temperature dependence of this consumption and the food efficiency, the percentage of the ingested food utilized. Estimates of the parameters for a given species can be determined by feeding experiments. Here, data from published feeding experiments on juvenile cod, Gadus morhua L., were used to validate the model. The average of the relative error for the food intake predicted by the model for individual fish was about 24 %, indicating that fish used the food with different efficiencies. However, grouping the fish according to size classes and temperature lowered the relative error of the predicted food intake for the group to typically 5 %. For a group containing all fish of the feeding experiment the relative prediction error was about 2 %. Zusammenfassung Wachstum und Kondition der Fische sind von der verfügbaren Nahrung und von Umweltbedingungen abhängig. Dies führte zur Idee, Fisch als „Konsum-Sensor“ für die Messung der Nahrungsaufnahme über einen definierten Zeitraum zu verwenden. Auf Grundlage des von Bertalanffy-Modells wurde ein bio-physikalisches Modell zur Schätzung der Futteraufnahme entwickelt. Während einige der Eingangsgrößen des Modells leicht gemessen werden können (Anfangs- und Endlänge und -körpermasse der Fische und die Temperatur innerhalb des betrachteten Zeitraum), können interne Parameter der betrachteten Art nur indirekt bestimmt werden. Drei interne Parameter werden in dem Modell verwendet: Die Erhaltungskonsumtion bei 0° C, die Temperaturabhängigkeit dieser Rate und der Wirkungsgrad der Nahrung (der Anteil der Nahrung ,der aufgenommen und verwendet und nicht ungenutzt wieder ausgeschieden wird). Die Modellparameter für eine bestimmte Art können durch Fütterungsversuche bestimmt werden. Um das Modell zu validieren wurden Daten aus veröffentlichten Fütterungsversuchen mit juvenilen Kabeljau (Gadus morhua L.) verwendet. Modell und Wirklichkeit weichen in der Regel voneinander ab. Der durchschnittliche relative Fehler der durch das Modell vorhergesagten Nahrungsaufnahme betrug für Einzelfische etwa 24%, was darauf hinweist, dass einzelne Fisch die Nahrung mit unterschiedlichen Wirkungsgraden verwerten. Allerdings senkte die Gruppierung der Fische nach Größenklassen und Temperatur den relativen Vorhersagefehler für die Nahrungsaufnahme der Gruppe auf etwa 5%. Für alle Fische im Fütterungsversuch ist der relative Vorhersagefehler etwa 2%.

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The method of E.V. Borutski was used for determining the production of chironomids, that is, the dynamics of the number and biomass of the larvae were analysed, their death, a calculation of emergence and the number of deposited egg layings was carried out. In addition to the method of Borutski, the authors also calculated the seasonal dynamics of the number of larvae of the younger age stages in the microbenthos.

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Growth is one of the most important characteristics of cultured species. The objective of this study was to determine the fitness of linear, log linear, polynomial, exponential and Logistic functions to the growth curves of Macrobrachium rosenbergii obtained by using weekly records of live weight, total length, head length, claw length, and last segment length from 20 to 192 days of age. The models were evaluated according to the coefficient of determination (R2), and error sum off square (ESS) and helps in formulating breeders in selective breeding programs. Twenty full-sib families consisting 400 PLs each were stocked in 20 different hapas and reared till 8 weeks after which a total of 1200 animals were transferred to earthen ponds and reared up to 192 days. The R2 values of the models ranged from 56 – 96 in case of overall body weight with logistic model being the highest. The R2 value for total length ranged from 62 to 90 with logistic model being the highest. In case of head length, the R2 value ranged between 55 and 95 with logistic model being the highest. The R2 value for claw length ranged from 44 to 94 with logistic model being the highest. For last segment length, R2 value ranged from 55 – 80 with polynomial model being the highest. However, the log linear model registered low ESS value followed by linear model for overall body weight while exponential model showed low ESS value followed by log linear model in case of head length. For total length the low ESS value was given by log linear model followed by logistic model and for claw length exponential model showed low ESS value followed by log linear model. In case of last segment length, linear model showed lowest ESS value followed by log linear model. Since, the model that shows highest R2 value with low ESS value is generally considered as the best fit model. Among the five models tested, logistic model, log linear model and linear models were found to be the best models for overall body weight, total length and head length respectively. For claw length and last segment length, log linear model was found to be the best model. These models can be used to predict growth rates in M. rosenbergii. However, further studies need to be conducted with more growth traits taken into consideration

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This article presents the results of three surveys, which were undertaken in order to estimate the levels of organic and bacterial pollutions of the Ebrié lagoon banks in the urban area of Abidjan.

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The method developed by Robson (1966) is used to standardize fishing effort of Côte d'Ivoire trawlers whose size and power are very different. This method also allows the estimation of the relative abundances in the different fishing areas. The results obtained using 10 years data show that the entire Ivorian continental shelf can be considered as a single fishery unit. The relative fishing power of vessels is well correlated with gross tonnage, brake horse power and length of the vessel. The obsolescence of the trawlers affects their fishing power.

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Study of C. nigrodigitatus slices showed evidence of seasonal formation related to rainfall and could be used for ageing. A first estimation of the growth has thus been made.

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An attempt was made to calculate zooplankton production from weights and settled volumes and from the life cycle of some copepods. Biomass data were recorded during several years from 24 monthly cruises and from a coastal station sampled biweekly. Dry weight data were directly measured or were calculated from the settled volumes using a linear regression. They range, on an average, from 0.965 to 5.56 g m-2 day-1 from the shore line to the edge of the continental shelf. The mean life-span of the cohorts of 12 species of copepods is about 20 days. It is assumed that only 1 spawn occurs per generation-time and that the standing stock is turned-over during the life span of a cohort. The production ranges from 48.2 to 278 mg dry weight m-2 day-1 or 17.9 to 103 mg C m-2 day-1, according to the depth of the studied areas. One third of carnivorous production occurs among the copepods. So, it is assumed that the herbivorous and omnivorous production is about 2/3 of the total zooplanktonic production. This would be a more accurate estimate of secondary production. The standing stock of zooplankton and fishes are in the same order of magnitude; the ratio zooplanktonic production/total fishery is 0.8%.

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Sablefish (Anoplopoma fimbria) are often caught incidentally in longline fisheries and discarded, but the extent of mortality after release is unknown, which creates uncertainty for estimates of total mortality. We analyzed data from 10,427 fish that were tagged in research surveys and recovered in surveys and commercial fisheries up to 19 years later and found a decrease in recapture rates for fish originally captured at shallower depths (210–319 m) during the study, sustaining severe hooking injuries, and sustaining amphipod predation injuries. The overall estimated discard mortality rate was 11.71%. This estimate is based on an assumed survival rate of 96.5% for fish with minor hooking injuries and the observed recapture rates for sablefish at each level of severity of hook injury. This estimate may be lower than what actually occurs in commercial fisheries because fish are likely not handled as carefully as those in our study. Comparing our results with data on the relative occurrence of the severity of hooking injuries in longline fisheries may lead to more accurate accounting of total mortality attributable to fishing and to improved management of this species.

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Quantification of predator-prey body size relationships is essential to understanding trophic dynamics in marine ecosystems. Prey lengths recovered from predator stomachs help determine the sizes of prey most influential in supporting predator growth and to ascertain size-specific effects of natural mortality on prey populations (Bax, 1998; Claessen et al., 2002). Estimating prey size from stomach content analyses is often hindered because of the degradation of tissue and bone by digestion. Furthermore, reconstruction of original prey size from digested remains requires species-specific reference materials and techniques. A number of diagnostic guides for freshwater (Hansel et al., 1988) and marine (Watt et al., 1997; Granadeiro and Silva, 2000) prey species exist; however they are limited to specific geographic regions (Smale et al., 1995; Gosztonyi et al., 2007). Predictive equations for reconstructing original prey size from diagnostic bones in marine fishes have been developed in several studies of piscivorous fishes of the Northwest Atlantic Ocean (Scharf et al., 1998; Wood, 2005). Conversely, morphometric relationships for cephalopods in this region are scarce despite their importance to a wide range of predators, such as finfish (Bowman et al., 2000 ; Staudinger, 2006), elasmobranchs (Kohler, 1987), and marine mammals (Gannon et al., 1997; Williams, 1999).

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Nearshore fisheries in the tropical Pacific play an important role, both culturally and as a reliable source of food security, but often remain under-reported in statistics, leading to undervaluation of their importance to communities. We re-estimated nonpelagic catches for Guam and the Commonwealth of the Northern Mariana Islands (CNMI), and summarize previous work for American Samoa for 1950−2002. For all islands combined, catches declined by 77%, contrasting with increasing trends indicated by reported data. For individual island entities, re-estima-tion suggested declines of 86%, 54%, and 79% for Guam, CNMI, and American Samoa, respectively. Except for Guam, reported data primarily represented commercial catches, and hence under-represented contributions by subsistence and recreational fisheries. Guam’s consistent use of creel surveys for data collection resulted in the most reliable reported catches for any of the islands considered. Our re-estimation makes the scale of under-reporting of total catches evident, and provides valuable baselines of likely historic patterns in fisheries catches.

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The contribution of the no-take marine reserve at Apo Island, Philippines, to local fishery yield through “spillover” (net export of adult fish) was estimated. Spatial patterns of fishing effort, yield, and catch rates around Apo Island were documented daily in 2003−2004. Catch rates were higher near the reserve (by a factor of 1.1 to 2.0), but fishing effort was often lowest there. Higher catch rates near the reserve were more likely due to spillover than to low fishing intensity. Lower fishing effort near the reserve may have been due to 1) weather patterns, 2) traditional importance of other fishing grounds, 3) high variability in catch rates, 4) lower market value of target species, and 5) social pressures. The yield taken near the reserve was only 10% of the total yield, but the actual spillover contribution was probably much less than this. This study is one of the few to estimate the spillover contribution to overall yield and to document the responses of fishermen to spil

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The need to estimate percentages and/or numbers occurs frequently during practical research work; accurate but rapid estimates can be useful when planning research programmes. Charts are provided that may be used as a visual aid to estimating numbers of animals/plants in a specific situation, for example, the number of fish fry in a subsample from a hatchery tank, or the percentage composition of a sample such as the percentage algal cover in a pond.