995 resultados para National Agricultural Statistics Service


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"National Economics Division, Economics and Statistics Service, U.S. Dept. of Agriculture"--P. iii.

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This report presents information on the life history, diet, abundance and distribution, and length-frequency distributions of five invertebrates in Florida Bay, Everglades National Park. Collections were made with an otter trawl in basins on a bi-monthly basis. Non-parametric statistics were used to test spatial and temporal differences in the abundance of invertebrates when numbers were appropriate (i. e., $25). Invertebrate species are presented in four sections. The sections on Life History, and Diet were derived from the literature. The section on Abundance and Distribution consists of data from otter-trawl collections. In addition, comparisons with other studies are included here following our results. The section on Length-frequency Distributions consists of length measurements from all collections, except 1984-1985 when no measurements were taken. Length-frequency distributions were used, when possible, to estimate life stage captured, spawning times, recruitment into Florida Bay for those species which spawn outside the Bay, and growth. Additional material from the literature was added when appropriate. (PDF contains 39 pages)

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ADMB2R is a collection of AD Model Builder routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 ADMB2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the ADMB2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer ADMB2R to others in the hope that they will find it useful. (PDF contains 30 pages)

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C2R is a collection of C routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 C2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the C2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer C2R to others in the hope that they will find it useful. (PDF contains 27 pages)

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For2R is a collection of Fortran routines for saving complex data structures into a file that can be read in the R statistics environment with a single command.1 For2R provides both the means to transfer data structures significantly more complex than simple tables, and an archive mechanism to store data for future reference. We developed this software because we write and run computationally intensive numerical models in Fortran, C++, and AD Model Builder. We then analyse results with R. We desired to automate data transfer to speed diagnostics during working-group meetings. We thus developed the For2R interface to write an R data object (of type list) to a plain-text file. The master list can contain any number of matrices, values, dataframes, vectors or lists, all of which can be read into R with a single call to the dget function. This allows easy transfer of structured data from compiled models to R. Having the capacity to transfer model data, metadata, and results has sharply reduced the time spent on diagnostics, and at the same time, our diagnostic capabilities have improved tremendously. The simplicity of this interface and the capabilities of R have enabled us to automate graph and table creation for formal reports. Finally, the persistent storage in files makes it easier to treat model results in analyses or meta-analyses devised months—or even years—later. We offer For2R to others in the hope that they will find it useful. (PDF contains 31 pages)

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This compendium presents information on the life history, diet, and abundance and distribution of 46 of the more abundant juvenile and small resident fish species, and data on three species of seagrasses in Florida Bay, Everglades National Park. Abundance and distribution of fish data were derived from three sampling schemes: (1) an otter trawl in basins (1984–1985, 1994–2001), (2) a surface trawl in basins (1984–1985), and (3) a surface trawl in channels (1984–1985). Results from surface trawling only included pelagic species. Collections made with an otter trawl in basins on a bi-monthly basis were emphasized. Nonparametric statistics were used to test spatial and temporal differences in the abundance of species and seagrasses. Fish species accounts were presented in four sections – Life history, Diet, Abundance and distribution, and Length-frequency distributions. Although Florida Bay is a subtropical estuary, the majority of fish species (76%) had warm-temperate affinities; i.e., only 24% were solely tropical species. The five most abundant species collected, in descending order, by (1) otter trawl in basins were: Eucinostomus gula, Lucania parva, Anchoa mitchilli, Lagodon rhomboides, and Syngnathus scovelli; (2) surface trawl in basins were: Hyporhamphus unifasciatus, Strongylura notata, Chriodorus atherinoides, Anchoa hepsetus, and Atherinomorus stipes; (3) surface trawl in channels were: Hypoatherina harringtonensis, A. stipes, A. mitchelli, H. unifasciatus, and C. atherinoides. (PDF file contains 219 pages.)

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Atlantic menhaden, Brrvoortia tyrannus, the object of a major purse-seine fishery along the U.S. east coast, are landed at plants from northern Florida to central Maine. The National Marine Fisheries Service has sampled these landings since 1955 for length, weight, and age. Together with records of landings at each plant, the samples are used to estimate numbers of fish landed at each age. This report analyzes the sampling design in terms of probablity sampling theory. The design is c1assified as two-stage cluster sampling, the first stage consisting of purse-seine sets randomly selected from the population of all sets landed, and the second stage consisting of fish randomly selected from each sampled set. Implicit assumptions of this design are discussed with special attention to current sampling procedures. Methods are developed for estimating mean fish weight, numbers of fish landed, and age composition of the catch, with approximate 95% confidence intervals. Based on specific results from three ports (port Monmouth, N.J., Reedville, Va., and Beaufort, N.C.) for the 1979 fishing season, recommendations are made for improving sampling procedures to comply more exactly with assumptions of the sampling design. These recommendatlons include adopting more formal methods for randomizing set and fish selection, increasing the number of sets sampled, considering the bias introduced by unequal set sizes, and developing methods to optimize the use of funds and personnel. (PDF file contains 22 pages.)

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U.S. Gulf of Mexico, pink shrimp, Farfantepenaeus duorarum, catch statistics have been collected by NOAA’s National Marine Fisheries Service, or its predecessor agency, for over 50 years. Recent events, including hurricanes and oil spills within the ecosystem of the fishery, have shown that documentation of these catch data is of primary importance. Fishing effort for this stock has fluctuated over the 50-year period analyzed, ranging from 3,376 to 31,900 days fished, with the most recent years on record, 2008 and 2009, exhibiting declines up to 90% relative to the high levels recorded in the mid 1990’s. Our quantification of F. duorarum landings and catch rates (CPUE) indicates catch have been below the long-term average of about 12 million lb for all of the last 10 years on record. In contrast to catch and effort, catch rates have increased in recent years, with record CPUE levels measured in 2008 and 2009, of 1,340 and 1,144 lb per day fished, respectively. Our regression results revealed catch was dependent upon fishing effort (F=98.48df=1, 48, p<0.001, r2=0.67), (Catch=1,623,378 + (520) × (effort)). High CPUE’s measured indicate stocks were not in decline prior to 2009, despite the decline in catch. The decrease in catch is attributed in large part to low effort levels caused by economical and not biological or habitat related conditions. Future stock assessments using these baseline data will provide further insights and management advice concerning the Gulf of Mexic

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Gulf of Mexico, white shrimp, Litopenaeus setiferus, catch statistics have been collected by NOAA’s National Marine Fisheries Service for over 50 years. Recent occurrences such as natural and manmade disasters have raised awareness for the need to publish these types of data. Here we report shrimp data collected from 1984 to 2011. These 28 years of catch history are the time series used in the most recent Gulf of Mexico white shrimp stock assessment. Fishing effort for this stock has fluctuated over the period reported, ranging from 54,675 to 162,952 days fished. Catch averaged 55.7 million pounds per year, increasing significantly over the times series. In addition, catch rates have been increasing in recent years, with CPUE levels ranging from 315 lb/day fished in 2002, to 1,175 lb/ day fished in 2008. The high CPUE’s we have measured is one indication that the stock was not in decline during this time period. Consequently, we believe the decline in effort levels is due purely to economic factors. Current stock assessments are now using these baseline data to provide managers with further insights into the Gulf L. setiferus stocks.

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Cost-sharing, which involves government-farmer partnership in the funding of agricultural extension service, is one of the reforms aimed at achieving sustainable funding for extension systems. This study examined the perceptions of farmers and extension professionals on this reform agenda in Nigeria. The study was carried out in six geopolitical zones of Nigeria. A multi-stage random sampling technique was applied in the selection of respondents. A sample size of 268 farmers and 272 Agricultural Development Programme (ADP) extension professionals participated in the study. Both descriptive and inferential statistics were used in analysing the data generated from this research. The results show that majority of farmers (80.6%) and extension professionals (85.7%) had favourable perceptions towards cost-sharing. Furthermore, the overall difference in their perceptions was not significant (t =0.03). The study concludes that the strong favourable perception held by the respondents is a pointer towards acceptance of the reform. It therefore recommends that government, extension administrators and policymakers should design and formulate effective strategies and regulations for the introduction and use of cost-sharing as an alternative approach to financing agricultural technology transfer in Nigeria.

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Volunteering is intricately woven into the fabric of our society. In 2009 alone, approximately 63.4 million Americans participated in volunteer activities, collectively donating over 8.1 billion service-hours (Corporation for National and Community Service [CNCS], 2010). Each service-hour is determined by the U.S. Bureau of Labor Statistics (2010) to be valued at $20.85/hr which translates to a national savings of $169 billion. Thus, we can clearly observe the significance of volunteer contribution to the overall benefit of society. In addition, there is now evidence that voluntary service may also benefit the actual volunteer, especially individuals who are 65+ years. As we reach 2020 this elderly class, composed of nearly 13 million (CNCS, 2010) Americans, will be of much consequence. Their potential to contribute in community-related efforts may save the U.S. billions in labor costs, and may also help reduce healthcare-related expenditures if volunteering proves to be a protective factor. In this literature review, we set out to explore the potential relationship between volunteer participation and increased mental and physical wellness. We also examined volunteer demographic characteristics and common motives for engaging in service-related activities. Analysis showed that volunteer work often combined low-impact physical activity and mental satisfaction from serving others, resulting in overall health benefit. Demographic characteristics displayed were consistent with previous studies and found that a majority of volunteers were female, White, married status, having received college degree or higher, employed, middle-high SES. In addition, age was seen to be a key characteristic in forecasting volunteer motivation and self-reported perceived health benefits.^

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Mode of access: Internet.