Download or read book Evaluating the Data poor Fishery Stock Assessment Method DB SRA written by Brandon R. Owashi and published by . This book was released on 2014 with total page 56 pages. Available in PDF, EPUB and Kindle. Book excerpt: Depletion-Based Stock Reduction Analysis (DB-SRA; Dick and MacCall, 2011) is a catch-only fisheries stock assessment model that has been developed to estimate an overfishing limit (OFL) in data-poor situations. DB-SRA projects the biomass trajectories of a stock by means of a catch time series and five parameters: the instantaneous, per annum, rate of natural mortality (M), age at 50% maturity, F[subscript MSY]/M, B[subscriptMSY]/B0, and the predicted depletion of the stock from its unfished condition. F[subscriptMSY]/M is the rate of fishing mortality associated with the maximum sustainable yield (MSY) divided by the natural mortality rate, and B[subscriptMSY]/B0 is the biomass level associated with the MSY divided by the unfished level of biomass. DB-SRA performs a Monte Carlo simulation where a large number of random parameter draws are made based on the input parameter's prior distribution. Based on the catch time series, a biomass trajectory is produced to estimate a feasible set of input parameters and an OFL. The run and corresponding set of input parameters are not retained if the biomass trajectory goes below zero. In instances where the input parameter prior distributions are unknown, Dick and MacCall (2011) proposed a set of default values for two life history types (rockfish and flatfish). Although DB-SRA has been evaluated to some extent and is currently being used for management of data-poor species on the U.S. west coast, further evaluation is warranted. Like other fisheries assessment models, DB-SRA makes several assumptions that may have large influence on outputs and have largely gone untested. First, in essence DB-SRA assumes that only mature fish are caught in the fishery; this is rarely true on the U.S. West Coast and elsewhere, particularly for species with substantial recreational catch. Second, most stock assessment methods, including DB-SRA, are applied to large regions (e.g., U.S. west coast), assuming the population dynamics and fishing behavior remain consistent across the entire area. Market demands and habitat, among other factors, can lead to heterogeneity in population dynamics and fishing behavior. For instance, immature fish are often caught in recreational fisheries, but commercial fisheries tend to target larger fish, causing fishing impact to change across regions. I developed a two-region operating model that simulated data to generate input parameter expected values and a catch time series for each region, then conducted a factorial experiment to investigate the effect of four factors on DB-SRA (version 4) results: (1) different positions of the selectivity curve (the relative vulnerability to fishing of each age class) relative to the maturity curve; (2) spatial scale (separate by region versus combined); (3) exploitation history; and (4) life history type (rockfish and flatfish). The position of the selectivity curve influences the accuracy of the OFL estimates from DB-SRA, whereas the exploitation history has little effect. The OFL estimates are overestimated when the selectivity curve is to the right of the maturity curve and underestimated when the selectivity curve is to the left of the maturity curve. DB-SRA produces higher OFL estimates when two regions are used instead of one large region. Dividing the catch data into multiple regions resulted in higher OFL estimates than one combined region when the same input parameters and catch time series were used. An updated production function, for mimicking population dynamics, was implemented in DB-SRA (version 4), creating separate time lags for mortality and production (recruitment and growth). Instead of setting the time lags for mortality and production equal to the age at 50% maturity (version 3), the time lag for mortality has been changed to one year (version 4). Although the version 4 DB-SRA model has been used for fishery management, it has not been formally evaluated against version 3 to understand the impacts of this change on model results. To investigate the two versions, I looked at different positions of the selectivity curve relative to the maturity curve, different exploitation histories, and varying spatial scale for two life history types. The OFL estimates from version 3 of DB-SRA were larger than the OFL estimates from version 4, which is also evident in the biomass trajectories. The biomass trajectories from version 3 are always greater than the respective biomass trajectories from version 4. Although the OFL estimates from version 4 are not always less biased than those from version 3, the estimates from version 4 are always more precautionary and significantly reduce the chances for overestimating the OFL. The identification of factors that influence DB-SRA OFL estimates could demonstrate how DB-SRA can be adjusted to produce less biased OFL estimates in more situations. The change made in the production function between versions 3 and 4 of DB-SRA makes OFL estimates more precautionary; but does not always reduce the bias in the median OFL estimate. The results from this study could provide information to fisheries managers so that DB-SRA could be potentially improved and is applied in appropriate situations.
Download or read book Review of Northeast Fishery Stock Assessments written by Committee to Review Northeast Fishery Stock Assessments and published by National Academies Press. This book was released on 1998-05-01 with total page 137 pages. Available in PDF, EPUB and Kindle. Book excerpt: The collapse of cod, flounder, and haddock fish stocks in the Northeast United States has caused widespread concern among managers and fishers in the United States and Canada. The diminishing stocks have forced managers to take strict regulatory measures. Numerous questions have been raised about the adequacy of stock assessment science used to evaluate the status of these stocks and the appropriateness of the management measures taken. Based on these concerns, Congress mandated that a scientific review of the methodology and data used to evaluate these stocks be conducted. In this volume, the committee concludes that although there are improvements to be made in data collection, modeling uncertainty, and communicating between fishers, managers, and scientists, the scientific methods used in the Northeast stock assessments are sound. Recommendations are made on how the stock assessment process can be improved.
Download or read book Improving Fish Stock Assessments written by National Research Council and published by National Academies Press. This book was released on 1998-02-27 with total page 194 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ocean harvests have plateaued worldwide and many important commercial stocks have been depleted. This has caused great concern among scientists, fishery managers, the fishing community, and the public. This book evaluates the major models used for estimating the size and structure of marine fish populations (stock assessments) and changes in populations over time. It demonstrates how problems that may occur in fisheries dataâ€"for example underreporting or changes in the likelihood that fish can be caught with a given type of gearâ€"can seriously degrade the quality of stock assessments. The volume makes recommendations for means to improve stock assessments and their use in fishery management.
Download or read book Evaluation of Data poor and Age structure Management Strategies for West Coast Rockfish written by Linsey M. Arnold and published by . This book was released on 2012 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: Management strategies to prevent overfishing while achieving optimum yield vary according to the available data and life history of the fished stock. I evaluated two sets of management strategies for Pacific coast rockfish: strategies to set harvest limits for data-poor stocks, and strategies intended to protect the age structure of fished stocks. Setting Harvest Limits for Data-poor Stocks - The collapse of canary rockfish, Sebastes pinniger, in the northeast Pacific began more than two decades before the stock was officially declared overfished. The 2006 reauthorization of the Magnuson-Stevens Fishery Conservation and Management Act requires a scientifically-based harvest limit for all fished stocks, including those with data limited to catch. Two such "data-poor" methods are currently in use for the management of west coast stocks, depletion-corrected average catch (DCAC) and depletion-based stock reduction analysis (DB-SRA). To evaluate the performance of each method when challenged with catch and biological uncertainty, I retrospectively applied the methods to the catch and biological data available at the time of the first and second canary rockfish stock assessments in 1984 and 1990. In 1980 canary rockfish would be classified as "data-poor", and in 1990 as "data-rich". To evaluate the sensitivity of DCAC and DB-SRA to error in the catch data, harvest limits were estimated using both the historic catch data from each assessment, and the reconstructed catch data from the most recent stock assessment. In addition, harvest limits were estimated using simulated catch data sets for the years 1916 to 1983 with increasing variability around the true catch. DCAC and DB-SRA estimated harvest limits were significantly lower than the catch recommended in both the data-poor and data-rich stock assessments, but higher than the "true" overfishing limit. Use of current catch data improved the estimated harvest limit when the stock was data-poor, but not when the stock was data-rich. The simple methods responded to increasing error in the catch time series with decreasing mean estimates of the harvest limit, indicating that these methods are highly precautionary for this species, when the catch time series is the only source of error. Age Structure Management Strategies - In a variable oceanographic environment, a population with many reproductive age classes benefits not only from the increased fecundity of older fish; but also, in some species, an increase in larval fitness. Older females may also spawn at different times or over longer periods than younger females, increasing the probability of larvae encountering favorable environmental conditions. Despite the accumulating evidence for the importance of age structure to long-term population viability in harvested fish populations, long-lived west coast rockfish (Genus Sebastes) are managed with a biomass-based harvest control rule. I compared three strategies for age structure management, and evaluated the strategies relative to the status quo, biomass-based harvest control rules, across three rockfish life histories. I examined the tradeoff between yield and traditional management reference points, as well as performance measures that could serve as management reference points for age structure. Yield was reduced by strategies that maintain "old growth" age structure, but annual variation in the catch and the probability of becoming overfished were also reduced. The longest-lived rockfish benefited the most from strategies that maintained older fish in the population through dome-shaped selectivity. The shorter-lived rockfish benefited from adjustments in the catch limit based on the age composition of the catch one year previous. Achieving "pretty good yield" with management strategies that also decrease the potential for overexploitation is an important goal for stocks that are well-studied and those that are poorly understood; these investigations contribute to a growing literature on alternative approaches to sustainable fisheries management.
Download or read book Stock Assessment for Fishery Management written by Daniel D. Hoggarth and published by Food & Agriculture Org.. This book was released on 2006 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: This publication contains guidelines for fish stock assessment and fishery management using the software tools and other outputs developed by the UK Department for International Development's Fisheries Management Science Programme (FMSP) from 1992 to 2004. It includes a CD-ROM with the installation files for each of the four FMSP software tools: LFDA (Length Frequency Data Analysis), CEDA (Catch Effort Data Analysis), YIELD and ParFish (Participatory Fisheries Stock Assessment).
Download or read book Informative Data and Uncertainty in Fisheries Stock Assessment written by Arni Magnusson and published by . This book was released on 2016 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncertainty is an integral part of fisheries stock assessment. Successful resource management requires scientific analysis to evaluate the uncertainty about the status of each stock and related quantities of interest. A failure to incorporate uncertainty into management advice increases the risk of suboptimal yields and can lead to a fishery collapse. In practice, it is not always clear which features of stock assessment data make them informative or uninformative, and it is also unclear how well different statistical methods are likely to perform when evaluating uncertainty. This study uses simulation analysis to measure the performance of alternative methods, based on a large number of simulated datasets where the underlying true values are known. The methods are then applied to data from an actual fishery, and the overall inference takes into account the performance of the methods in the simulations. The results show that the historical levels of stock size and harvest rate greatly affect how informative the data are about the current stock status. The key parameters natural mortality M and stock-recruitment steepness h pose challenges when it comes to statistical estimation, and long-term management advice is likely to depend strongly on the estimated or assumed values of M and h. The most informative fishing history is one where the data include years of high and low stock size, which is informative about h, as well as high and low harvest rates, which is informative about M. The results also indicate that confidence intervals describing the uncertainty about the stock status and other quantities of interest are likely to be too narrow in general. Benchmark analysis indicates that the delta method, Markov chain Monte Carlo (MCMC), and profile likelihood approaches are likely to perform better than the bootstrap for quantifying uncertainty. A bias correction algorithm for the bootstrap improved its performance, but not enough to match the performance of the other methods. Additional approaches to evaluate the estimation uncertainty include retrospective analysis and bivariate confidence regions for the current stock status. The use of harvest control rules to incorporate uncertainty into management advice is also discussed. The main value of this study is to present a comprehensive overview and evaluation of methods to analyze uncertainty. The study concludes with a checklist of recommendations for confronting uncertainty in stock assessment.
Download or read book A Review of Length based Approaches to Assessing Fish Stocks written by J. A. Gulland and published by Food & Agriculture Org.. This book was released on 1992 with total page 112 pages. Available in PDF, EPUB and Kindle. Book excerpt: This document reviews the several fish stock assessment methods based on length-frequency analysis. Emphasis is placed on sampling and collection of length-frequency data, to the estimation of population parameters such as growth, mortality and recruitment and the estimation of catch selectivity. Attention is given to the conversion of length to age using age-length keys, slicing length-frequency composition, and using modes. It reviews long-and short-term effects of changes in selection and fishing mortality, and discusses methods for long-term assessments and for short-term projections. The manual gives several examples of the most common methods used and stresses the advantages of using personal computers and the most recent software for data processing and analysis.
Download or read book Quantitatively Defining Biological and Economic Reference Points in Data Poor Fisheries written by Shijie Zhou and published by . This book was released on 2013 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Data limited Research in Stock Assessment to Increase the Understanding of Fisheries Resources and Inform and Improve Management Efforts written by Giuseppe Scarcella and published by Frontiers Media SA. This book was released on 2023-04-10 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Fish Stock Assessment written by J. A. Gulland and published by . This book was released on 1983-07-12 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Describes the scientific techniques used in assessing fish stocks, evaluating the effect of fishing on these stocks, and the probable impact of different policies for developing and managing fisheries. Covers the techniques developed starting with simple models and continuing to more complex methods.
Download or read book Evaluating the Performance and Applicability of State space Stock Assessment Models written by Emily Morgan Liljestrand and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fisheries stock assessment models are used to estimate population demographics and dynamics such as abundance, biomass, and fishing mortality from input fishery data including total catch, composition of catch, and fishing effort. A goal of stock assessment is to accurately quantify population and fishery dynamics so stocks can be managed to achieve fishery objectives and long-term sustainability. Accurate and precise model estimates can be attained by using models and techniques that account for ecological complexity like variability in quantities across ages, years, or regions without overparameterization. The state-space framework is one such statistical technique that may allow for incorporating more stochasticity such that the model can better reflect reality. The state-space modeling framework assumes that unobserved "states" develop over time due to process error modeled as a random effect and that observed data have expected values based on these states but differ from expectations due to observation error.State-space stock assessment models (SSSAM) have experienced an outpouring of research and application in the past decade as computation processing power and novel software has facilitated the approximation of the high-level integrals necessary for SSSAM. SSSAM allows for several time-varying processes in recruitment, numbers at age, mortality, selectivity, and catchability, and has become an essential part of the contemporary fisheries modeling toolbox. With their swift advancement, it is important to understand best practices of applying state-space stock assessment models, and how data availability, the variability of process or observation error, and model structure may influence model results and accuracy.In Chapter 1 I built an age-based state-space stock assessment model that used fisheries dependent data, rather than fisheries independent surveys, as an index of abundance and was applied to Lake Michigan lake whitefish (Coregonus clupeaformis). The model predicted greater℗ abundance and lower mortality compared to the non-state-space model and domed rather than asymptotic selectivity. The state-space model also had reduced retrospective patterns in recruitment. Chapters 2 and 3 each used a simulation-estimation framework to generate catch and index data using a state-space stock assessment that assumed process variability in recruitment, expected survival (abundance), and selectivity. Simulations were based on a Gulf of Maine haddock (Melanogrammus aeglefinus) model and assumed different degrees of process and observation variance (Chapter 2) or assumed observation error likelihood distributions for the proportions at age (Chapter 3) to generate data. Simulated data were input into several estimation models with alternative assumptions about contributing sources of process variability and/or observation error distributions. The results show that state-space models which assume several sources of process variability can produce unbiased estimates even when processes are constant over time. The state-space models were able to estimate process variance in several stochastic processes under a broad range of true values. However, assuming variability in expected survival when it is deterministic can lead to the model not converging. Unbiased results are achieved when the observation likelihood is structured to account for inter-age correlation and overdispersion though such a framework may have difficulty allocating variance between process and observation sub-models.The concluding chapter places this work in the context of other age-based stock assessment models and argues for the inclusion of state-space in the modeling toolbox, as they can account for multiple time-varying processes and be used in a broad range of data contexts. This work provides a blueprint for where and how SSSAM may be best utilized in the future, particularly with data limited or data poor stocks and in cases where the process variance is unknown and should be estimated within the model.
Download or read book Quantitative Fish Dynamics written by Terrance J. Quinn and published by Oxford University Press, USA. This book was released on 1999 with total page 561 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fields of fish population dynamics and stock assessment have seen major advances in the 1980s and 1990s, creating the need for a new synthesis. This text attempts that synthesis by presenting a contemporary approach for quantitative fisheries science that incorporates modern statistical and mathematical techniques. It emphasizes the link between biology and theory by explaining the assumptions inherent in the quantitative methods and models. The book covers key topics that are often overlooked in other texts, such as optimal harvesting, migratory stocks, and complex age and size-structured models. Quantitative Fish Dynamics is an ideal textbook for graduate and undergraduate courses in fish population dynamics and stock assessment. It is an indispensable reference work for fisheries scientists and others interested in conservation biology, fish and wildlife management, population ecology, and statistical applications.
Download or read book Adressing the Reliability of Data poor Stock Assessment Methods to Provide Advice on the Status of Small scale Fisheries written by John Gabriel Ramírez Téllez and published by . This book was released on 2020 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Small-scale fishers are often identified as key players in the recovery of overexploited fish and invertebrate stocks supplying food for rural people and contributing to achieving healthy marine ecosystems. Stocks harvested by small-scale fisheries tend to be largely unassessed, but methods based on the data-limited toolbox exist that help provide information on exploitation status for fished stocks that do not have historical time series of catches, as usually occur in small-scale fisheries. Many of the data-limited methods follow length-based assessment approaches, which assume steady state, use at least length structure derived from fishery and knowledge on the life history parameters of the fished species. Accordingly, this thesis aimed at addressing the reliability of data-poor stock assessment methods in providing advice on the status of small-scale fisheries lacking knowledge of catch history. The data-rich bottom trawl fishery for European hake (Merluccius merluccius) in GSA 06 (Northwest Mediterranean Sea) was assumed as data-limited. This case study allowed me to test the performance of the pseudo-cohort Virtual Population Analysis (VPA) when input data are considered well known and unbiased. The same fishery but held in GSA 01 (Southwest Mediterranean Sea) was used as data-limited case study to introduce the uncertainty derived from parameterizing the length-based spawning potential ratio (LB-SPR) model with two contrasting growth hypotheses. Acknowledging challenges faced by stock assessment of small-scale fisheries around the world, I considered high input-data bias and large outputs uncertainty. The effect of biases in fishery data and uncertainty in life-history parameters on the outputs of the pseudo-cohort VPA model was explored by assessing the small-scale Wayuu fisheries for lane snapper (Lutjanus synagris) and white grunt (Haemulon plumierii) in the northern Colombian Caribbean Sea. An extreme, but common, case of uncertainty in small-scale fisheries was explored through assessing the beach fishery of the Peruvian grunt (Anisotremus scapularis) in the central coast of Peru on the Pacific Ocean, holding poor information on life-history parameters and catches. My findings indicate that the pseudo-cohort VPA may offer useful information regarding the exploitation trend but the absolute values of the indicators do not accurately express the fishing mortality and stock size among years for the European hake. The SPR estimates for this species is not specially linked to the growth hypothesis, and estimates of the ratio of fishing mortality to natural mortality (F/M) and the SPR value depend on the sample size and representation of the stock structure. The contribution of the information derived from the participatory monitoring of small-scale fisheries in Colombia, instead of using only official fishery data, largely demonstrated an improving picture of the exploitation of the lane snapper and white grunt. The uncertainty related to estimates of the von Bertalanffy growth parameters and natural mortality of the Peruvian grunt could be addressed but an accurate definition of SPR was not straightforwardly achieved. This thesis highlights that the data-limited methods assuming a steady state might contribute to defining the status of the small-scale fisheries. However, the stock status is importantly affected by bias in the input data, the available knowledge on the assessed fisheries and how fishery fit the model assumptions." -- TDX.
Download or read book Accounting for Variability and Biases in Data limited Fisheries Stock Assessment written by Merrill B. Rudd and published by . This book was released on 2017 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many regions of the world have very few stocks assessed, often due to limited data quality or quantity or lack of trained scientists to apply and interpret stock assessments. These same areas with fewer assessments perform worse across fishery management attributes, including research capacity, management, enforcement, and socioeconomics. Some studies have used the limited data available to approximate the status of these “unassessed” stocks and find them to be declining compared to assessed stocks. Global assessments of “unassessed” stocks are informed by many attributes of the stock, one of which is the trend in reported catch to the U.N. Food and Agriculture Organization. These assessments assume that the catch data are accurate, at least in trend if not in magnitude. However, quantifying catch is a major challenge due to commonly misreported sectors such as discards, small-scale, recreational, and illegal, unreported, unregulated fisheries. One approach is to improve catch data by improving monitoring programs or conducting catch reconstructions. Another approach is to collect alternative data types to conduct stock assessments. Stocks that are not assessed because they have the lowest information or research capacity appear more likely to be unsustainable, and further research and management action is required to improve the status of the data- and research-capacity-limited fisheries. This dissertation addresses issues of data quality in the monitoring process and data limitation in the assessment process. Chapter 1 addresses an issue of data quality in asking, “does unreported catch lead to overfishing?” We used simulation analysis to demonstrate that if catch is misreported at a constant rate, surplus production models can still estimate unbiased stock status and would avoid overfishing with effective management. If catch misreporting is increasing over time, stock assessments would recommend harvest limits that would lead to under-exploitation, while decreasing reporting rates lead to over-exploitation. This question is relevant to fisheries around the world dealing with uncertainties in catch reporting in their stock assessment, as well as current debates over the use of catch reconstructions. In Chapter 2 stock assessments are examined for fisheries that only have length composition data and biological information, since it is often easier to collect length measurements than to quantify total catch. Length measurements from samples of the catch, referred to as length composition data, can be contrasted with expected length composition in an unfished state to reveal information about fishing mortality, recruitment, and selectivity. Most data-poor length-based stock assessment methods assume the population is in equilibrium, i.e. that fishing mortality and recruitment have not changed within one generation of the species. In this chapter we present a Length-based Integrated Mixed Effects (LIME) model that relaxes this equilibrium assumption and directly estimates variable fishing mortality and recruitment using the same data inputs as other length-based methods. Using simulation testing we demonstrated LIME performs best for life history types with a maximum age of less than 20 years, and is unbiased across a range of recruitment and fishing mortality patterns, provided individual growth parameters are known. LIME also has the capability of including multiple years of length data, abundance indices, and catch time series when available. LIME is a flexible new tool for stock assessments of fish usually caught as bycatch and other small-scale fisheries. Chapter 3 applies LIME and the equilibrium-based Length-Based Spawning Potential Ratio (LB-SPR) methods to assess a medium-lived Costa Rican spotted rose snapper, Lutjanus guttatus, and short-lived Kenyan rabbitfish, Siganus sutor. LIME estimated the Costa Rican snapper fishery to be overfished in the most recent year of data after a period of full exploitation, whereas LB-SPR estimated more variability in stock status throughout the time series but the fishery was above the target reference point in the most recent year of data. LIME estimated the rabbitfish fishery to have undergone a period of overexploitation in the late 1990s and early 2000s, but fishing mortality has continually decreased over time resulted in a recovered stock in the most recent year of data. Alternatively, LB-SPR estimated the stock slightly less than the SPR target. Chapter 3 presented the first empirical LIME assessment and comparison with a commonly-used alternative method, and presented guidelines for future LIME applications.
Download or read book Stock Assessment written by Vincent F. Gallucci and published by CRC Press. This book was released on 2023-05-31 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stock Assessment: Quantitative Methods and Applications for Small Scale Fisheries is a book about stock assessment as it is practiced. It focuses on applications for small scale or artisanal fisheries in developing countries, however it is not limited in applicability to tropical waters and should also be considered a resource for students of temperate fishery management problems. It incorporates a careful sample design, various mathematical models as a basis for predicting consequences for stock exploitation, and discusses the impact of exploitation on non-targeted species. This was a unique concept involving a collaborative effort between U.S. and host country scientists to address issues of regional and global concern through innovative research. Unlike other books on stock assessment that show mathematical models, this is the only book of its kind that discusses how an assessment is carried out. It looks at the field as a whole and includes sampling, age determination and acoustics. The book represents the culmination of a nine-year program financed by the United States Agency for International Development to provide new or improved methods of stock assessment for artisanal fisheries.
Download or read book Stock Assessment written by Vincent F. Gallucci and published by CRC Press. This book was released on 1995-10-25 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stock Assessment: Quantitative Methods and Applications for Small Scale Fisheries is a book about stock assessment as it is practiced. It focuses on applications for small scale or artisanal fisheries in developing countries, however it is not limited in applicability to tropical waters and should also be considered a resource for students of temperate fishery management problems. It incorporates a careful sample design, various mathematical models as a basis for predicting consequences for stock exploitation, and discusses the impact of exploitation on non-targeted species. This was a unique concept involving a collaborative effort between U.S. and host country scientists to address issues of regional and global concern through innovative research. Unlike other books on stock assessment that show mathematical models, this is the only book of its kind that discusses how an assessment is carried out. It looks at the field as a whole and includes sampling, age determination and acoustics. The book represents the culmination of a nine-year program financed by the United States Agency for International Development to provide new or improved methods of stock assessment for artisanal fisheries.
Download or read book Fish Stock Assessment Manual written by Emygdio L. Cadima and published by Food & Agriculture Org.. This book was released on 2003 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: This manual examines mathematical models applied in fish stock assessment, including models and variation rates; cohort models and analyses; stock fishing patterns, components, stock-recruitment relations, short- and long-term stock projections; fisheries resources management with regards to biological reference points and regulation measures; production models; estimation of parameters; and exercises.
