43 resultados para Remote Sensing and LiDAR Data Precipitation Products
Resumo:
This report describes the general background to the project, defines the stations from which data sets have been obtained and lists the available data. The project had the following aims: To develop a more accurate and less labour-intensive system for the collection and processing of water temperature data from a number of stations within a stream/river system, and to use the River North Tyne downstream of the Kielder impoundment as a test bed for the system. This should yield useful information on the effects of impoundment upon downstream water temperatures.
Resumo:
We develop and test a method to estimate relative abundance from catch and effort data using neural networks. Most stock assessment models use time series of relative abundance as their major source of information on abundance levels. These time series of relative abundance are frequently derived from catch-per-unit-of-effort (CPUE) data, using general linearized models (GLMs). GLMs are used to attempt to remove variation in CPUE that is not related to the abundance of the population. However, GLMs are restricted in the types of relationships between the CPUE and the explanatory variables. An alternative approach is to use structural models based on scientific understanding to develop complex non-linear relationships between CPUE and the explanatory variables. Unfortunately, the scientific understanding required to develop these models may not be available. In contrast to structural models, neural networks uses the data to estimate the structure of the non-linear relationship between CPUE and the explanatory variables. Therefore neural networks may provide a better alternative when the structure of the relationship is uncertain. We use simulated data based on a habitat based-method to test the neural network approach and to compare it to the GLM approach. Cross validation and simulation tests show that the neural network performed better than nominal effort and the GLM approach. However, the improvement over GLMs is not substantial. We applied the neural network model to CPUE data for bigeye tuna (Thunnus obesus) in the Pacific Ocean.
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Commercial catches taken in southwestern Australian waters by trawl fisheries targeting prawns and scallops and from gillnet and longline fisheries targeting sharks were sampled at different times of the year between 2002 and 2008. This sampling yielded 33 elasmobranch species representing 17 families. Multivariate statistics elucidated the ways in which the species compositions of elasmobranchs differed among fishing methods and provided benchmark data for detecting changes in the elasmobranch fauna in the future. Virtually all elasmobranchs caught by trawling, which consisted predominantly of rays, were discarded as bycatch, as were approximately a quarter of the elasmobranchs caught by both gillnetting and longlining. The maximum lengths and the lengths at maturity of four abundant bycatch species, Heterodontus portusjacksoni, Aptychotrema vincentiana, Squatina australis, and Myliobatis australis, were greater for females than males. The L50 determined for the males of these species at maturity by using full clasper calcification as the criterion of maturity did not differ significantly from the corresponding L50 derived by using gonadal data as the criterion for maturity. The proportions of the individuals of these species with lengths less than those at which 50% reach maturity were far greater in trawl samples than in gillnet and longline samples. This result was due to differences in gear selectivity and to trawling being undertaken in shallow inshore waters that act as nursery areas for these species. Sound quantitative data on the species compositions of elasmobranchs caught by commercial fisheries and the biological characteristics of the main elasmobranch bycatch species are crucial for developing strategies for conserving these important species and thus the marine ecosystems of which they are part.
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The National Marine Fisheries Service (NMFS) Cooperative Shark Tagging Program (CSTP) is part of continuing research directed to the study of the biology of large Atlantic sharks. The CSTP was initiated in 1962 at the Sandy Hook Laboratory in New Jersey under the Department of Interior's U.S. Fish and Wildlife Service (USFWS). During the late 1950's and early 1960's, sharks were considered a liability to the economy of resort communities, of little or no commercial value, and a detriment to fishermen in areas where sharks might damage expensive fishing gear or reduce catches of more commercially valuable species.
Resumo:
The distribution and intensity of a bloom of the toxic cyanobacterium, Microcystis aeruginosa, in western Lake Erie was characterized using a combination of satellite ocean-color imagery, field data, and meteorological observations. The bloom was first identified by satellite on 14 August 2008 and persisted for more than 2 months. The distribution and intensity of the bloom was estimated using a satellite algorithm that is sensitive to near-surface concentrations of M. aeruginosa. Increases in both area and intensity were most pronounced for wind stress less than 0.05 Pa. Area increased while intensity did not change for wind stresses of 0.05–0.1 Pa, and both decreased for wind stress greater than 0.1 Pa. The recovery in intensity at the surface after strong wind events indicated that high wind stress mixed the bloom through the water column and that it returned to the surface once mixing stopped. This interaction is consistent with the understanding of the buoyancy of these blooms. Cloud cover (reduced light) may have a weak influence on intensity during calm conditions. While water temperature remained greater than 15°C, the bloom intensified if there were calm conditions. For water temperature less than 15°C, the bloom subsided under similar conditions. As a result, wind stress needs to be considered when interpreting satellite imagery of these blooms.
Resumo:
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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We used allozyme, microsatellite, and mitochondrial DNA (mtDNA) data to test for spatial and interannual genetic diversity in wall-eye pollock (Theragra chalcogramma) from six spawning aggregations representing three geographic regions: Gulf of Alaska, eastern Bering Sea, and eastern Kamchatka. Interpopulation genetic diversity was evident primarily from the mtDNA and two allozyme loci (SOD-2*, MPI*). Permutation tests ˆindicated that FST values for most allozyme and microsatellite loci were not significantly greater than zero. The microsatellite results suggested that high locus polymorphism may not be a reliable indicator of power for detecting population differentiation in walleye pollock. The fact that mtDNA revealed population structure and most nuclear loci did not suggests that the effective size of most walleye pollock populations is large (genetic drift is weak) and migration is a relatively strong homogenizing force. The allozymes and mtDNA provided mostly concordant estimates of patterns of spatial genetic variation. These data showed significant genetic variation between North American and Asian populations. In addition, two spawning aggregations in the Gulf of Alaska, in Prince William Sound, and off Middleton Island, appeared genetically distinct from walleye pollock spawning in the Shelikof Strait and may merit management as a distinct stock. Finally, we found evidence of interannual genetic variation in two of three North American spawning aggregations, similar in magnitude to the spatial variation among North American walleye pol-lock. We suggest that interannual genetic variation in walleye pollock may be indicative of one or more of the following factors: highly variable reproductive success, adult philopatry, source-sink metapopulation structure, and intraannual variation (days) in spawning timing among genetically distinct but spatially identical spawning aggregates.
Resumo:
EXTRACT (SEE PDF FOR FULL ABSTRACT): Havasu Creek is the second largest tributary of the Colorado River in Grant Canyon. Perennial streamflow in the creek seldom exceeds 2 cubic meters per second, but it supports an important riparian habitat as well as unique travertine pools and waterfalls that attract over 20,000 tourists annually. Havasu Canyon is also home to over 400 members of the Havasu Tribe. Despite a long history of habitation and recreation in Havasu Canyon, streamflow records for Havasu Creek are extremely limited, making flood prediction difficult.
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The Nutrient Enhanced Coastal Ocean Productivity (NECOP) Program is a component of NOAA's Coastal Ocean Program. The central hypothesis of this research is: Anthropogenic nutrient inputs have enhanced coastal ocean productivity with subsequent impacts on coastal ocean water quality, living resource yields, and the global marine carbon cycle. The initial study area for this program is the Mississippi/Atchafalaya River Outflow and adjacent Louisiana shelf region.
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A feeding strategy model is proposed using stomach content and resource availability data as a modification to Costello (1990) and Amundsen et al. (1996). Incorporation of feeding electivity index (E) instead of the prey-specific abundance signifies the importance of resource availability in prey selection as well as the predator's ability to specialize, generalize or avoid particular prey items at the individual and population level.
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The present paper gives a comparative account of the hydrological conditions and phytoplankton within the Continental Shelf and beyond the Continental Shelf. 54 water samples were taken for hydrological analysis and 18 surface tows for plankton.