27 resultados para change analysis

em Aquatic Commons


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EXECUTIVE SUMMARY: The Coastal Change Analysis Programl (C-CAP) is developing a nationally standardized database on landcover and habitat change in the coastal regions of the United States. C-CAP is part of the Estuarine Habitat Program (EHP) of NOAA's Coastal Ocean Program (COP). C-CAP inventories coastal submersed habitats, wetland habitats, and adjacent uplands and monitors changes in these habitats on a one- to five-year cycle. This type of information and frequency of detection are required to improve scientific understanding of the linkages of coastal and submersed wetland habitats with adjacent uplands and with the distribution, abundance, and health of living marine resources. The monitoring cycle will vary according to the rate and magnitude of change in each geographic region. Satellite imagery (primarily Landsat Thematic Mapper), aerial photography, and field data are interpreted, classified, analyzed, and integrated with other digital data in a geographic information system (GIS). The resulting landcover change databases are disseminated in digital form for use by anyone wishing to conduct geographic analysis in the completed regions. C-CAP spatial information on coastal change will be input to EHP conceptual and predictive models to support coastal resource policy planning and analysis. CCAP products will include 1) spatially registered digital databases and images, 2) tabular summaries by state, county, and hydrologic unit, and 3) documentation. Aggregations to larger areas (representing habitats, wildlife refuges, or management districts) will be provided on a case-by-case basis. Ongoing C-CAP research will continue to explore techniques for remote determination of biomass, productivity, and functional status of wetlands and will evaluate new technologies (e.g. remote sensor systems, global positioning systems, image processing algorithms) as they become available. Selected hardcopy land-cover change maps will be produced at local (1:24,000) to regional scales (1:500,000) for distribution. Digital land-cover change data will be provided to users for the cost of reproduction. Much of the guidance contained in this document was developed through a series of professional workshops and interagency meetings that focused on a) coastal wetlands and uplands; b) coastal submersed habitat including aquatic beds; c) user needs; d) regional issues; e) classification schemes; f) change detection techniques; and g) data quality. Invited participants included technical and regional experts and representatives of key State and Federal organizations. Coastal habitat managers and researchers were given an opportunity for review and comment. This document summarizes C-CAP protocols and procedures that are to be used by scientists throughout the United States to develop consistent and reliable coastal change information for input to the C-CAP nationwide database. It also provides useful guidelines for contributors working on related projects. It is considered a working document subject to periodic review and revision.(PDF file contains 104 pages.)

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This document, Guidance for Benthic Habitat Mapping: An Aerial Photographic Approach, describes proven technology that can be applied in an operational manner by state-level scientists and resource managers. This information is based on the experience gained by NOAA Coastal Services Center staff and state-level cooperators in the production of a series of benthic habitat data sets in Delaware, Florida, Maine, Massachusetts, New York, Rhode Island, the Virgin Islands, and Washington, as well as during Center-sponsored workshops on coral remote sensing and seagrass and aquatic habitat assessment. (PDF contains 39 pages) The original benthic habitat document, NOAA Coastal Change Analysis Program (C-CAP): Guidance for Regional Implementation (Dobson et al.), was published by the Department of Commerce in 1995. That document summarized procedures that were to be used by scientists throughout the United States to develop consistent and reliable coastal land cover and benthic habitat information. Advances in technology and new methodologies for generating these data created the need for this updated report, which builds upon the foundation of its predecessor.

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Historical definitions of what determines whether one lives in a coastal area or not have varied over time. According to Culliton (1998), a “coastal county” is defined as a county with at least 15% of its total land area located within a nation’s coastal watershed. This emphasizes the land areas within which water flows into the ocean or Great Lakes, but may be better suited for ecosystems or water quality research (Crowell et al. 2007). Some Federal Emergency Management Agency (FEMA) documents suggest that “coastal” includes shoreline-adjacent coastal counties, and perhaps even counties impacted by flooding from coastal storms. An accurate definition of “coastal” is critical in this regard since FEMA uses such definitions to revise and modernize their Flood Insurance Rate Maps (Crowell et al. 2007). A recent map published by the National Oceanic and Atmospheric Administration’s (NOAA) Coastal Services Center for the Coastal Change Analysis Program shows that the “coastal” boundary covers the entire state of New York and Michigan, while nearly all of South Carolina is considered “coastal.” The definition of “coastal” one chooses can have major implications, including a simple count of coastal population and the influence of local or state coastal policies. There is, however, one aspect of defining what is “coastal” that has often been overlooked; using atmospheric long-term climate variables to define the inland extent of the coastal zone. This definition, which incorporates temperature, precipitation, wind speed, and relative humidity, is furthermore scalable and globally applicable - even in the face of shifting shorelines. A robust definition using common climate variables should condense the large broad definition often associated with “coastal” such that completely landlocked locations would no longer be considered “coastal.” Moreover, the resulting definition, “coastal climate” or “climatology of the coast”, will help coastal resource managers make better-informed decisions on a wide range of climatologically-influenced issues. The following sections outline the methodology employed to derive some new maps of coastal boundaries in the United States. (PDF contains 3 pages)

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This report is an account of a cross-country study that covered Vietnam, Indonesia and the Philippines. Covering four sites (one each in Indonesia and Vietnam) and two sites in the Philippines, the study documented the impacts of three climate hazards affecting coastal communities, namely typhoon/flooding, coastal erosion and saltwater intrusion. It also analyzed planned adaptation options, which communities and local governments can implement, as well as autonomous responses of households to protect and insure themselves from these hazards. It employed a variety of techniques, ranging from participatory based approaches such as community hazard mapping and Focus Group Discussions (FGDs) to regression techniques, to analyze the impact of climate change and the behavior of affected communities and households.

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Climate change with its attendant geophysical hazards is well studied. A great deal of attention has gone into analyzing climate change impacts as well as searching out possible mitigating adaptive strategies. These matters are very real concerns, especially for coastal communities. Such communities are often the most vulnerable to climate change, since their citizens frequently live in abject poverty and have limited capacity to adapt to geophysical hazards. Their situation is further complicated by the prospect of dealing with a confluence of hazards in comparison with those in other ecosystems. Against this backdrop Worldfish and the Economy and Environment Program for Southeast Asia (EEPSEA) collaborated to implement the cross-country study “Climate Change Impacts, Vulnerability Assessments, Economic and Policy Analysis of Adaptation Strategies in Selected Coastal Areas in Indonesia, Philippines, and Vietnam”. As its title suggests the study covered selected sites in Vietnam, Indonesia and the Philippines. Employing a gamut of interdisciplinary methodologies -- ranging from community-based approaches such as community hazard mapping and focus group discussions (FGDs) to regression techniques -- the study documented the impacts from three climate hazards affecting coastal communities. These were typhoon/flooding, coastal erosion, and saltwater intrusion. The team also analyzed planned adaptation options suited to implementation by communities and local governments, augmenting autonomous responses of households to protect and insure themselves from these hazards.

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EXTRACT (SEE PDF FOR FULL ABSTRACT): High resolution paleobotanical records provide sufficient detail to correlate events regionally. Once correlated events can be examined in tandem to determine the underlying inputs that fashioned them. Several localities in the Great Basin have paleobotanical records of sufficient detail to generate regional reconstructions of vegetation changes for the last 2 ka and provide conclusions as to the climates that caused them.

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Introduction [pdf, 0.27 MB] Methods [pdf, 0.15 MB] Results and discussion [pdf, 2.1 MB] Conclusions [pdf, 0.12 MB] Appendix A: Data gathering review, results and balancing [pdf, 0.3 MB] Appendix B: Data tables [pdf, 0.35 MB] Appendix C: BASS Workshop on the "Development of a conceptual model of the subarctic Pacific Basin ecosystems" [pdf, 0.16 MB] Appendix D: BASS/MODEL Workshop on "Higher trohic level modeling" [pdf, 0.24 MB] Appendix E: BASS/MODEL Workshop to review ecosystem models for the subarctic Pacific gyres [pdf, 4.39 MB] Appendix F: BASS/MODEL Workshop on "Perturbation analysis" on subarctic Pacific gyre ecosystem models using ECOPATH/ECOSIM" [pdf, 0.37 MB] Appendix G: Proposal for a BASS Workshop on "Linkages between open and coastal systems" [pdf, 0.15 MB] References [pdf, 0.14 MB] (97 page document)

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This is the report of the “DoF/NACA-STREAM/FAO Workshop on Livelihoods Approaches and Analysis” that was conducted in Yangon, Union of Myanmar from 11-15 May 2004. The purpose of the workshop was to develop and document mechanisms for training in livelihoods approaches and analysis, and to build national capacity to conduct livelihoods studies. The workshop in Yangon was the first STREAM event in Myanmar, with colleagues coming to participate from Yangon and many Divisions and States throughout the country. The workshop in Yangon was the fourth in a series, the first of which was held in Iloilo City, Philippines, in November 2003, the second in Ranchi, India, in February 2004, and the third in Vientiane, Lao PDR in March 2004. A subsequent workshop will take place in Yunnan, China. The objectives of the workshop were to: Understand issues of interest to people whose livelihoods include aquatic resources management, especially those with limited resources Build “(national) livelihoods teams” to do livelihoods analyses and training, and share their experiences with communities and other stakeholders Share understandings of livelihoods approaches and analysis using participatory methods Review current NACA-STREAM livelihoods analysis documentation, adapt and supplement, towards the drafting of a Guide for Livelihoods Analysis Experience the use of participatory tools for livelihoods analysis Plan activities for carrying out livelihoods analyses, and Consider how to build capacity in monitoring and evaluation (M&E) and “significant change”. (Pdf contains 56 pages).

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Executive Summary: Observations show that warming of the climate is unequivocal. The global warming observed over the past 50 years is due primarily to human-induced emissions of heat-trapping gases. These emissions come mainly from the burning of fossil fuels (coal, oil, and gas), with important contributions from the clearing of forests, agricultural practices, and other activities. Warming over this century is projected to be considerably greater than over the last century. The global average temperature since 1900 has risen by about 1.5ºF. By 2100, it is projected to rise another 2 to 11.5ºF. The U.S. average temperature has risen by a comparable amount and is very likely to rise more than the global average over this century, with some variation from place to place. Several factors will determine future temperature increases. Increases at the lower end of this range are more likely if global heat-trapping gas emissions are cut substantially. If emissions continue to rise at or near current rates, temperature increases are more likely to be near the upper end of the range. Volcanic eruptions or other natural variations could temporarily counteract some of the human-induced warming, slowing the rise in global temperature, but these effects would only last a few years. Reducing emissions of carbon dioxide would lessen warming over this century and beyond. Sizable early cuts in emissions would significantly reduce the pace and the overall amount of climate change. Earlier cuts in emissions would have a greater effect in reducing climate change than comparable reductions made later. In addition, reducing emissions of some shorter-lived heat-trapping gases, such as methane, and some types of particles, such as soot, would begin to reduce warming within weeks to decades. Climate-related changes have already been observed globally and in the United States. These include increases in air and water temperatures, reduced frost days, increased frequency and intensity of heavy downpours, a rise in sea level, and reduced snow cover, glaciers, permafrost, and sea ice. A longer ice-free period on lakes and rivers, lengthening of the growing season, and increased water vapor in the atmosphere have also been observed. Over the past 30 years, temperatures have risen faster in winter than in any other season, with average winter temperatures in the Midwest and northern Great Plains increasing more than 7ºF. Some of the changes have been faster than previous assessments had suggested. These climate-related changes are expected to continue while new ones develop. Likely future changes for the United States and surrounding coastal waters include more intense hurricanes with related increases in wind, rain, and storm surges (but not necessarily an increase in the number of these storms that make landfall), as well as drier conditions in the Southwest and Caribbean. These changes will affect human health, water supply, agriculture, coastal areas, and many other aspects of society and the natural environment. This report synthesizes information from a wide variety of scientific assessments (see page 7) and recently published research to summarize what is known about the observed and projected consequences of climate change on the United States. It combines analysis of impacts on various sectors such as energy, water, and transportation at the national level with an assessment of key impacts on specific regions of the United States. For example, sea-level rise will increase risks of erosion, storm surge damage, and flooding for coastal communities, especially in the Southeast and parts of Alaska. Reduced snowpack and earlier snow melt will alter the timing and amount of water supplies, posing significant challenges for water resource management in the West. (PDF contains 196 pages)

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ENGLISH: A two-stage sampling design is used to estimate the variances of the numbers of yellowfin in different age groups caught in the eastern Pacific Ocean. For purse seiners, the primary sampling unit (n) is a brine well containing fish from a month-area stratum; the number of fish lengths (m) measured from each well are the secondary units. The fish cannot be selected at random from the wells because of practical limitations. The effects of different sampling methods and other factors on the reliability and precision of statistics derived from the length-frequency data were therefore examined. Modifications are recommended where necessary. Lengths of fish measured during the unloading of six test wells revealed two forms of inherent size stratification: 1) short-term disruptions of existing pattern of sizes, and 2) transition zones between long-term trends in sizes. To some degree, all wells exhibited cyclic changes in mean size and variance during unloading. In half of the wells, it was observed that size selection by the unloaders induced a change in mean size. As a result of stratification, the sequence of sizes removed from all wells was non-random, regardless of whether a well contained fish from a single set or from more than one set. The number of modal sizes in a well was not related to the number of sets. In an additional well composed of fish from several sets, an experiment on vertical mixing indicated that a representative sample of the contents may be restricted to the bottom half of the well. The contents of the test wells were used to generate 25 simulated wells and to compare the results of three sampling methods applied to them. The methods were: (1) random sampling (also used as a standard), (2) protracted sampling, in which the selection process was extended over a large portion of a well, and (3) measuring fish consecutively during removal from the well. Repeated sampling by each method and different combinations indicated that, because the principal source of size variation occurred among primary units, increasing n was the most effective way to reduce the variance estimates of both the age-group sizes and the total number of fish in the landings. Protracted sampling largely circumvented the effects of size stratification, and its performance was essentially comparable to that of random sampling. Sampling by this method is recommended. Consecutive-fish sampling produced more biased estimates with greater variances. Analysis of the 1988 length-frequency samples indicated that, for age groups that appear most frequently in the catch, a minimum sampling frequency of one primary unit in six for each month-area stratum would reduce the coefficients of variation (CV) of their size estimates to approximately 10 percent or less. Additional stratification of samples by set type, rather than month-area alone, further reduced the CV's of scarce age groups, such as the recruits, and potentially improved their accuracy. The CV's of recruitment estimates for completely-fished cohorts during the 198184 period were in the vicinity of 3 to 8 percent. Recruitment estimates and their variances were also relatively insensitive to changes in the individual quarterly catches and variances, respectively, of which they were composed. SPANISH: Se usa un diseño de muestreo de dos etapas para estimar las varianzas de los números de aletas amari11as en distintos grupos de edad capturados en el Océano Pacifico oriental. Para barcos cerqueros, la unidad primaria de muestreo (n) es una bodega de salmuera que contenía peces de un estrato de mes-área; el numero de ta11as de peces (m) medidas de cada bodega es la unidad secundaria. Limitaciones de carácter practico impiden la selección aleatoria de peces de las bodegas. Por 10 tanto, fueron examinados los efectos de distintos métodos de muestreo y otros factores sobre la confiabilidad y precisión de las estadísticas derivadas de los datos de frecuencia de ta11a. Se recomiendan modificaciones donde sean necesarias. Las ta11as de peces medidas durante la descarga de seis bodegas de prueba revelaron dos formas de estratificación inherente por ta11a: 1) perturbaciones a corto plazo en la pauta de ta11as existente, y 2) zonas de transición entre las tendencias a largo plazo en las ta11as. En cierto grado, todas las bodegas mostraron cambios cíclicos en ta11a media y varianza durante la descarga. En la mitad de las bodegas, se observo que selección por ta11a por los descargadores indujo un cambio en la ta11a media. Como resultado de la estratificación, la secuencia de ta11as sacadas de todas las bodegas no fue aleatoria, sin considerar si una bodega contenía peces de un solo lance 0 de mas de uno. El numero de ta11as modales en una bodega no estaba relacionado al numero de lances. En una bodega adicional compuesta de peces de varios lances, un experimento de mezcla vertical indico que una muestra representativa del contenido podría estar limitada a la mitad inferior de la bodega. Se uso el contenido de las bodegas de prueba para generar 25 bodegas simuladas y comparar los resultados de tres métodos de muestreo aplicados a estas. Los métodos fueron: (1) muestreo aleatorio (usado también como norma), (2) muestreo extendido, en el cual el proceso de selección fue extendido sobre una porción grande de una bodega, y (3) medición consecutiva de peces durante la descarga de la bodega. EI muestreo repetido con cada método y distintas combinaciones de n y m indico que, puesto que la fuente principal de variación de ta11a ocurría entre las unidades primarias, aumentar n fue la manera mas eficaz de reducir las estimaciones de la varianza de las ta11as de los grupos de edad y el numero total de peces en los desembarcos. El muestreo extendido evito mayormente los efectos de la estratificación por ta11a, y su desempeño fue esencialmente comparable a aquel del muestreo aleatorio. Se recomienda muestrear con este método. El muestreo de peces consecutivos produjo estimaciones mas sesgadas con mayores varianzas. Un análisis de las muestras de frecuencia de ta11a de 1988 indico que, para los grupos de edad que aparecen con mayor frecuencia en la captura, una frecuencia de muestreo minima de una unidad primaria de cada seis para cada estrato de mes-área reduciría los coeficientes de variación (CV) de las estimaciones de ta11a correspondientes a aproximadamente 10% 0 menos. Una estratificación adicional de las muestras por tipo de lance, y no solamente mes-área, redujo aun mas los CV de los grupos de edad escasos, tales como los reclutas, y mejoró potencialmente su precisión. Los CV de las estimaciones del reclutamiento para las cohortes completamente pescadas durante 1981-1984 fueron alrededor de 3-8%. Las estimaciones del reclutamiento y sus varianzas fueron también relativamente insensibles a cambios en las capturas de trimestres individuales y las varianzas, respectivamente, de las cuales fueron derivadas. (PDF contains 70 pages)

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How is climate change affecting our coastal environment? How can coastal communities adapt to sea level rise and increased storm risk? These questions have garnered tremendous interest from scientists and policy makers alike, as the dynamic coastal environment is particularly vulnerable to the impacts of climate change. Over half the world population lives and works in a coastal zone less than 120 miles wide, thereby being continuously affected by the changes in the coastal environment [6]. Housing markets are directly influenced by the physical processes that govern coastal systems. Beach towns like Oak Island in North Carolina (NC) face severe erosion, and the tax assesed value of one coastal property fell by 93% in 2007 [9]. With almost ninety percent of the sandy beaches in the US facing moderate to severe erosion [8], coastal communities often intervene to stabilize the shoreline and hold back the sea in order to protect coastal property and infrastructure. Beach nourishment, which is the process of rebuilding a beach by periodically replacing an eroding section of the beach with sand dredged from another location, is a policy for erosion control in many parts of the US Atlantic and Pacific coasts [3]. Beach nourishment projects in the United States are primarily federally funded and implemented by the Army Corps of Engineers (ACE) after a benefit-cost analysis. Benefits from beach nourishment include reduction in storm damage and recreational benefits from a wider beach. Costs would include the expected cost of construction, present value of periodic maintenance, and any external cost such as the environmental cost associated with a nourishment project (NOAA). Federal appropriations for nourishment totaled $787 million from 1995 to 2002 [10]. Human interventions to stabilize shorelines and physical coastal dynamics are strongly coupled. The value of the beach, in the form of storm protection and recreation amenities, is at least partly capitalized into property values. These beach values ultimately influence the benefit-cost analysis in support of shoreline stabilization policy, which, in turn, affects the shoreline dynamics. This paper explores the policy implications of this circularity. With a better understanding of the physical-economic feedbacks, policy makers can more effectively design climate change adaptation strategies. (PDF contains 4 pages)

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Rising global temperatures threaten the survival of many plant and animal species. Having already risen at an unprecedented rate in the past century, temperatures are predicted to rise between 0.3 and 7.5C in North America over the next 100 years (Hawkes et al. 2007). Studies have documented the effects of climate warming on phenology (timing of seasonal activities), with observations of early arrival at breeding grounds, earlier ends to the reproductive season, and delayed autumnal migrations (Pike et al. 2006). In addition, for species not suited to the physiological demands of cold winter temperatures, increasing temperatures could shift tolerable habitats to higher latitudes (Hawkes et al. 2007). More directly, climate warming will impact thermally sensitive species like sea turtles, who exhibit temperature-dependent sexual determination. Temperatures in the middle third of the incubation period determine the sex of sea turtle offspring, with higher temperatures resulting in a greater abundance of female offspring. Consequently, increasing temperatures from climate warming would drastically change the offspring sex ratio (Hawkes et al. 2007). Of the seven extant species of sea turtles, three (leatherback, Kemp’s ridley, and hawksbill) are critically endangered, two (olive ridley and green) are endangered, and one (loggerhead) is threatened. Considering the predicted scenarios of climate warming and the already tenuous status of sea turtle populations, it is essential that efforts are made to understand how increasing temperatures may affect sea turtle populations and how these species might adapt in the face of such changes. In this analysis, I seek to identify the impact of changing climate conditions over the next 50 years on the availability of sea turtle nesting habitat in Florida given predicted changes in temperature and precipitation. I predict that future conditions in Florida will be less suitable for sea turtle nesting during the historic nesting season. This may imply that sea turtles will nest at a different time of year, in more northern latitudes, to a lesser extent, or possibly not at all. It seems likely that changes in temperature and precipitation patterns will alter the distribution of sea turtle nesting locations worldwide, provided that beaches where the conditions are suitable for nesting still exist. Hijmans and Graham (2006) evaluate a range of climate envelope models in terms of their ability to predict species distributions under climate change scenarios. Their results suggested that the choice of species distribution model is dependent on the specifics of each individual study. Fuller et al. (2008) used a maximum entropy approach to model the potential distribution of 11 species in the Arctic Coastal Plain of Alaska under a series of projected climate scenarios. Recently, Pike (in press) developed Maxent models to investigate the impacts of climate change on green sea turtle nest distribution and timing. In each of these studies, a set of environmental predictor variables (including climate variables), for which ‘current’ conditions are available and ‘future’ conditions have been projected, is used in conjunction with species occurrence data to map potential species distribution under the projected conditions. In this study, I will take a similar approach in mapping the potential sea turtle nesting habitat in Florida by developing a Maxent model based on environmental and climate data and projecting the model for future climate data. (PDF contains 5 pages)

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Small freshwater pelagic fisheries in closed lakes are very important to millions of people in sub-Saharan Africa providing livelihoods and nutritional security. However, returns from these fisheries have been shown to �uctuate in response to climatic variability. In order to understand the impact of these fluctuations on the livelihoods of people dependant on these fisheries, there is a need for information on how the fish value chain is organized and how it functions in response to variation in supplies. The results will feed into strategies that build resilience in fishing households against the uncertainties arising from unstable ecosystems. The Lake Chilwa fishery value chain is composed of fishers, processors, traders, fish transporters, boat owners, owners of fish processing shades, fisheries associations, gear owners, gear makers, firewood sellers, and traders of fishing gear and equipment. The value chain employs many people and local authorities can consider using this information in the design of rural development strategies for employment generation in small-scale fishing communities. The findings from this study have a number of implications for the improvement of the livelihood of fishers and enhancing their capacity to mitigate against the effects of climate change.

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Errors in growth estimates can affect drastically the spawner-perrecruit threshold used to recommend quotas for commercial fish catches. Growth parameters for sablefish (Anoplopoma fimbria) in Alaska have not been updated for stock assessment purposes for more than 20 years, although aging of sablefish has continued. In this study, length-stratified data (1981–93 data from the annual longline survey conducted cooperatively by the Fisheries Agency of Japan and the Alaska Fisheries Science Center of the National Marine Fisheries Service) were updated and corrected for discovered sampling bias. In addition, more recent, randomly collected samples (1996–2004 data from the annual longline survey conducted by the Alaska Fisheries Science Center) were analyzed and new length-at-age and weight-at-age parameters were estimated. Results were similar between this analysis with length-at-age data from 1981 to 2004 and analysis with updated longline survey data through 2010; therefore, we used our initial results from analysis done with data through 2004. We found that, because of a stratified sampling scheme, growth estimates of sablefish were overestimated with the older data (1981–93), and growth parameters used in the Alaskan sablefish assessment model were, thus, too large. In addition, a comparison of the bias-corrected 1981–93 data and the 1996–2004 data showed that, in more recent years, sablefish grew larger and growth differed among regions. The updated growth information improves the fit of the data to the sablefish stock assessment model with biologically reasonable results. These findings indicate that when the updated growth data (1996–2004) are used in the existing sablefish assessment model, estimates of fishing mortality increase slightly and estimates of female spawning biomass decrease slightly. This study provides evidence of the importance of periodically revisiting biological parameter estimates, especially as data accumulate, because the addition of more recent data often will be more biologically realistic. In addition, it exemplifies the importance of correcting biases from sampling that may contribute to erroneous parameter estimates.

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Shepherd's "weekly parametric" method for estimating the parameter L sub( infinity ) and K of the von Bertalanffy growth function from length-frequency data often fails to converge, and usually overestimates K. It is shown that this is due to overcounting of the frequencies associated with large, slow growing fish, and that both of these problems can be completely overcome by a simple change in the way the scoring function is formulated.