31 resultados para variable range hopping.


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The Kemp's ridley turtle (Lepidochelys kempii) is an endangered species whose recovery depends in part on the identification and protection of required habitats. We used radio and sonic telemetry on subadult Kemp's ridley turtles to investigate home-range size and habitat use in the coastal waters of west-central Florida from 1994 to 1996. We tracked 9 turtles during May-August up to 70 days after release and fou.ld they occupied 5-30 km2 foraging ranges. Compositional analyses indicated that turtles used rock outcroppings in their foraging ranges at a significantly higher proportion than expected. based on availability within the study area. Additionally. turtles used live bottom (e.g .• sessile invertebrates) and green macroalgae habitats significantly more than seagrass habitat. Similar studies are needed through'mt the Kemp's ridley turtles' range to investigate regional and stage-specific differences in habitat use. which can then be used to conserve important foraging areas.

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Aquaculture is currently responsible for an insignificant proportion of total fish production in Uganda. However, given the increasing demand for fresh fish in urban and peri-urban araes, and threats to the supply of fish from natural catch fisheries, the potential exists for a strong market in aquaculture. Small-scale fish farmers located relatively close to markets or all-season roads, and who can supply consistent and high quality produce, will have the widest range of marketing opportunities, and will likely be within the area of operation of potential traders and intermediaries that deliver fish to markets. Fish farmers that are not close to roads, or produce unreliable quantities and variable quality products may face high transaction costs of marketing their product, and decreasing net returns to production. The authors found that significant on-farm labor, and access to input markets are important factors leading to positive net returns to fish production. Areas with high population density and relatively low wages will be well suited to labor intensive aquaculture. The authors concluded that aquaculture development has good potential in certain areas of Uganda and should therefore be pursued as a potential development pathway. However, policy makers should consider the importance of the price of fresh fish relative to the cost of labor, as well as other factors including the importance of smallholder credit and access to extension services, when directing investments in aquaculture technology.

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The potential for growth overfishing in the white shrimp, Litopenaeus setiferus, fishery of the northern Gulf of Mexico appears to have been of limited concern to Federal or state shrimp management entities, following the cataclysmic drop in white shrimp abundance in the 1940’s. As expected from surplus production theory, a decrease in size of shrimp in the annual landings accompanies increasing fishing effort, and can eventually reduce the value of the landings. Growth overfishing can exacerbate such decline in value of the annual landings. We characterize trends in size-composition of annual landings and other annual fishery-dependent variables in this fishery to determine relationships between selected pairs of these variables and to determine whether growth overfishing occurred during 1960–2006. Signs of growth overfishing were equivocal. For example, as nominal fishing effort increased, the initially upward, decelerating trend in annual yield approached a local maximum in the 1980’s. However, an accelerating upward trend in yield followed as effort continued to increase. Yield then reached its highest point in the time series in 2006, as nominal fishing effort declined due to exogenous factors outside the control of shrimp fishery managers. The quadratic relationship between annual yield and nominal fishing effort exhibited a local maximum of 5.24(107) pounds (≈ MSY) at a nominal fishing effort level of 1.38(105) days fished. However, annual yield showed a continuous increase with decrease in size of shrimp in the landings. Annual inflation-adjusted ex-vessel value of the landings peaked in 1989, preceded by a peak in annual inflation-adjusted ex-vessel value per pound (i.e. price) in 1983. Changes in size composition of shrimp landings and their economic effects should be included among guidelines for future management of this white shrimp

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Four recognized species of menhaden, Brevoortia spp., occur in North American marine waters: Atlantic menhaden, B. tyrannus; Gulf menhaden, B. patronus; yellowfin menhaden. B. smithi; and finescale menhaden, B. gunteri. Three of the menhaden species are known to form two hybrid types. Members of the genus range from coastal waters of Veracruz, Mex., to Nova Scotia, Can. Atlantic and Gulf menhaden are extremely abundant within their respective ranges and support extensive purse-seine reduction (to fish meal and oil) fisheries. All menhaden species are estuarine dependent through late larval and juvenile stages. Depending on species and location within the range, spawning may occur within bays and sounds to a substantial distance offshore. Menhaden are considered to be filter-feeding, planktivorous omnivores as juveniles and adults. Menhaden eggs, immature developmental stages, and adults are potential prey for a large and diverse number of predators. North American menhadens, including two hybrids, are hosts for the parasitic isopod, Olencira praegustator, and the parasitic copepod, Lemaeenicus radiatus. Although the data are quite variable, a dome-shaped Ricker function is frequently used to describe the spawner-recruitment relationship for Atlantic and Gulf menhaden. Each of these species is treated as a single stock with respect to exploitation by the purse-seine reduction fishery. Estimates of instantaneous natural (other) mortality rates are O.45 for Atlantic menhaden and 1.1 for Gulf menhaden.

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Catch rates from fishery-independent surveys often are assumed to vary in proportion to the actual abundance of a population, but this approach assumes that the catchability coefficient (q) is constant. When fish accumulate in a gear, the rate at which the gear catches fish can decline, and, as a result, catch asymptotes and q declines with longer fishing times. We used data from long-term trap surveys (1990–2011) in the southeastern U.S. Atlantic to determine whether traps saturated for 8 reef fish species because of the amount of time traps soaked or the level of fish accumulation (the total number of individuals of all fish species caught in a trap). We used a delta-generalized-additive model to relate the catch of each species to a variety of predictor variables to determine how catch was influenced by soak time and fish accumulation after accounting for variability in catch due to the other predictor variables in the model. We found evidence of trap saturation for all 8 reef fish species examined. Traps became saturated for most species across the range of soak times examined, but trap saturation occurred for 3 fish species because of fish accumulation levels in the trap. Our results indicate that, to infer relative abundance levels from catch data, future studies should standardize catch or catch rates with nonlinear regression models that incorporate soak time, fish accumulation, and any other predictor variable that may ultimately influence catch. Determination of the exact mechanisms that cause trap saturation is a critical need for accurate stock assessment, and our results indicate that these mechanisms may vary considerably among species.

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NOAA’s Center for Coastal Monitoring and Assessment’s Biogeography Branch has mapped and characterized large portions of the coral reef ecosystems inside the U.S. coastal and territorial waters, including the U.S. Caribbean. The complementary protocols used in these efforts have enabled scientists and managers to quantitatively compare different marine ecosystems in tropical U.S. waters. The Biogeography Branch used these same general protocols to generate three seamless habitat maps of the Bank/Shelf (i.e., from 0 ≤50 meters) and the Bank/Shelf Escarpment (i.e., from 50 ≤1,000 meters and from 1,000 ≤ 1,830 meters) inside Buck Island Reef National Monument (BIRNM). While this mapping effort marks the fourth time that the shallow-water habitats of BIRNM have been mapped, it is the first time habitats deeper than 30 meters (m) have been characterized. Consequently, this habitat map provides information on the distribution of mesophotic and deep-water coral reef ecosystems and serves as a spatial baseline for monitoring change in the Monument. A benthic habitat map was developed for approximately 74.3 square kilometers or 98% of the BIRNM using a combination of semi-automated and manual classification methods. The remaining 2% was not mapped due to lack of imagery in the western part of the Monument at depths ranging from 1,000 to 1,400 meters. Habitats were interpreted from orthophotographs, LiDAR (Light Detection and Ranging) imagery and four different types of MBES (Multibeam Echosounder) imagery. Three minimum mapping units (MMUs) (100, 1,000 and 5,000 square meters) were used because of the wide range of depths present in the Monument. The majority of the area that was characterized was deeper than 30 m on the Bank/Shelf Escarpment. This escarpment area was dominated by uncolonized sand which transitioned to mud as depth increased. Bedrock was exposed in some areas of the escarpment, where steep slopes prevented sediment deposition. Mesophotic corals were seen in the underwater video, but were too sparsely distributed to be reliably mapped from the source imagery. Habitats on the Bank/Shelf were much more variable than those seen on the Bank/Shelf Escarpment. The majority of this shelf area was comprised of coral reef and hardbottom habitat dominated by various forms of turf, fleshy, coralline or filamentous algae. Even though algae was the dominant biological cover type, nearly a quarter (24.3%) of the Monument’s Bank/Shelf benthos hosted a cover of 10%-<50% live coral. In total, 198 unique combinations of habitat classes describing the geography, geology and biology of the sea-floor were identified from the three types of imagery listed above. No thematic accuracy assessment was conducted for areas deeper than about 50 meters, most of which was located in the Bank/Shelf Escarpment. The thematic accuracy of classes in waters shallower than approximately 50 meters ranged from 81.4% to 94.4%. These thematic accuracies are similar to those reported for other NOAA benthic habitat mapping efforts in St. John (>80%), the Main Eight Hawaiian Islands (>84.0%) and the Republic of Palau (>80.0%). These digital maps products can be used with confidence by scientists and resource managers for a multitude of different applications, including structuring monitoring programs, supporting management decisions, and establishing and managing marine conservation areas. The final deliverables for this project, including the benthic habitat maps, source imagery and in situ field data, are available to the public on a NOAA Biogeography Branch website (http://ccma.nos.noaa.gov/ecosystems/coralreef/stcroix.aspx) and through an interactive, web-based map application (http://ccma.nos.noaa.gov/explorer/biomapper/biomapper.html?id=BUIS). This report documents the process and methods used to create the shallow to deep-water benthic habitat maps for BIRNM. Chapter 1 provides a short introduction to BIRNM, including its history, marine life and ongoing research activities. Chapter 2 describes the benthic habitat classification scheme used to partition the different habitats into ecologically relevant groups. Chapter 3 explains the steps required to create a benthic habitat map using a combination of semi-automated and visual classification techniques. Chapter 4 details the steps used in the accuracy assessment and reports on the thematic accuracy of the final shallow-water map. Chapter 5 summarizes the type and abundance of each habitat class found inside BIRNM, how these habitats compare to past habitat maps and outlines how these new habitat maps may be used to inform future management activities.

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Bycatch, or the incidental catch of nontarget organisms during fi shing operations, is a major issue in U.S. shrimp trawl fisheries. Because bycatch is typically discarded at sea, total bycatch is usually estimated by extrapolating from an observed bycatch sample to the entire fleet with either mean-per-unit or ratio estimators. Using both field observations of commercial shrimp trawlers and computer simulations, I compared five methods for generating bycatch estimates that were used in past studies, a mean-per-unit estimator and four forms of the ratio estimator, respectively: 1) the mean fish catch per unit of effort, where unit effort was a proxy for sample size, 2) the mean of the individual fish to shrimp ratios, 3) the ratio of mean fish catch to mean shrimp catch, 4) the mean of the ratios of fish catch per time fished (a variable measure of effort), and 5) the ratio of mean fish catch per mean time fished. For field data, different methods used to estimate bycatch of Atlantic croaker, spot, and weakfish yielded extremely different results, with no discernible pattern in the estimates by method, geographic region, or species. Simulated fishing fleets were used to compare bycatch estimated by the fi ve methods with “actual” (simulated) bycatch. Simulations were conducted by using both normal and delta lognormal distributions of fish and shrimp and employed a range of values for several parameters, including mean catches of fish and shrimp, variability in the catches of fish and shrimp, variability in fishing effort, number of observations, and correlations between fish and shrimp catches. Results indicated that only the mean per unit estimators provided statistically unbiased estimates, while all other methods overestimated bycatch. The mean of the individual fish to shrimp ratios, the method used in the South Atlantic Bight before the 1990s, gave the most biased estimates. Because of the statistically significant two- and 3-way interactions among parameters, it is unlikely that estimates generated by one method can be converted or corrected to estimates made by another method: therefore bycatch estimates obtained with different methods should not be compared directly.

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Stock-rebuilding time isopleths relate constant levels of fishing mortality (F), stock biomass, and management goals to rebuilding times for overfished stocks. We used simulation models with uncertainty about FMSY and variability in annual intrinsic growth rates (ry) to calculate rebuilding time isopleths for Georges Bank yellowtail flounder, Limanda ferruginea, and cowcod rockfish, Sebastes levis, in the Southern California Bight. Stock-rebuilding time distributions from stochastic models were variable and right-skewed, indicating that rebuilding may take less or substantially more time than expected. The probability of long rebuilding times increased with lower biomass, higher F, uncertainty about FMSY, and autocorrelation in ry values. Uncertainty about FMSY had the greatest effect on rebuilding times. Median recovery times from simulations were insensitive to model assumptions about uncertainty and variability, suggesting that median recovery times should be considered in rebuilding plans. Isopleths calculated in previous studies by deterministic models approximate median, rather than mean, rebuilding times. Stochastic models allow managers to specify and evaluate the risk (measured as a probability) of not achieving a rebuilding goal according to schedule. Rebuilding time isopleths can be used for stocks with a range of life histories and can be based on any type of population dynamics model. They are directly applicable with constant F rebuilding plans but are also useful in other cases. We used new algorithms for simulating autocorrelated process errors from a gamma distribution and evaluated sensitivity to statistical distributions assumed for ry. Uncertainty about current biomass and fishing mortality rates can be considered with rebuilding time isopleths in evaluating and designing constant-F rebuilding plans.

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Salinity, fresh water and sea level data from the Negombo Lagoon with respect to oceanic sea level and salinity data were considered. The open ocean spring tidal range was 0.57 m, whereas the neap tidal range was 0.10 m. In lagoon, the corresponding spring tidal range was 0.13 m and neap tidal range is 0.05 m. The lagoon tide was strongly choked because of the restricted inlet channel, through which only a limited water exchange could take place over a tidal cycle. Mean water exchange and the residence times for variable fresh water supplies were calculated. These calculations were based on fortnightly measurements of salinity and river discharges in 1993. During this year, salinity varied from 30-5‰ depending on the river inputs which were 20-225 m³ sˉ¹. Corresponding residence times varied from 11-2 days and the tide is dominated the exchange during low discharges of freshwater.

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The acute toxicity and effects of diazinon on some haematological parameters of kutum (Rutilus frisii kutum, Kamensky, 1901) weighing 613.33 g±157.06 g were studied under static water quality conditions at 15°C ± 2ºC in winter and spring 2009. The effective physical and chemical parameters of water were pH= 7-8.2, dh= 300mg/L (caco3), DO= 7 ppm and T= 15°C±2ºC. The first test was primarily to determine the effects of acute toxicity (LC5096 h) of the agricultural toxicant diazinon (emulsion 60%) on kutum male brood stocks. For this purpose, 4 treatments were used to test toxicity; each treatment was repeated in 3 tanks with 9 fish per treatment and with 180 litres water capacity. After obtaining the final results, the information was analysed statistically with Probit version 1.5 (USEPA, 1985), and we determined the LC10, LC50 and LC90 values at 24 hours, 48 hours, 72 hours and 96 hours; the maximum allowable concentration value (LC5096 h divided by 10) (TRC, 1984); and the degree of toxicity. The second stage of testing consists of four treatments: LC0= 0 as experimental treatment, treatment A with a concentration of LC1= 0.107 mg/L, treatment B with concentration of LC5= 0.157 mg/L, treatment C with concentration of MAC value= 0.04 mg/L. Male brood stocks of kutum were treated with these concentrations for 45 days. Experiments were carried out under static conditions based on the standard TRC, 1984 method over 45 days. Our results show that long-term exposure to diazinon causes a decrease in the erythrocyte count (RBC), haemoglobin (Hb), haematocrit (PCV), mean corpuscular volume (MCV), mean corpuscular haemoglobin (MCH), mean corpuscular haemoglobin concentration (MCHC), leucocyte count (WBC), lymphocyte, testosterone, iron (Fe), sodium (Na), lactate dehydrogenase (LDH), and cholinesterase (CHeS). In addition, diazinon also causes an increase in prolymphocyte, aspartate aminotransferase (AST), cholesterol, alkaline phosphatase (ALP) and adrenaline (P<0.05). There are no significant effects on monocyte, eosinophil, magnesium (Mg), chloride (Cl), glucose (BS), urea (BUN), uric acid (U.A), triglyceride (TG), calcium (Ca), albumin (Alb), total protein (TP), cortisol, noradrenaline and high density lipoprotein (HDL) levels in kutum male brood stocks (P>0.05). Pathology results showed toxin diazinon no effect on average weight and fish body length, the average weight of heart, brain, spleen, liver, kidney and liver index but caueses decrease of gonad weigth and gonad index and also, cause complications of tissue necrosis, vascular congestion, inflammation in the liver, a sharp reduction in the number of glomeruli, necrosis, vascular congestion and haemorage in the kidney, capsule thickening and fibrosis, atrophy, vascular congestion, macrophages release increased, increasing sediment Hemosiderine and thickening of artery walls in the spleen, atrophy, fibrosis and necrosis in testis , vascular congestion, increased distance between the myocardium and fibrous string in heart and neuronal loss, vascular congestion and edema in the brain of kutum male brood stocks.