scholarly journals The assessment of fishery status depends on the condition of fish habitats

2017 ◽  
Author(s):  
Christopher J. Brown ◽  
Andrew Broadley ◽  
Fernanda Adame ◽  
Trevor A. Branch ◽  
Mischa Turschwell ◽  
...  
Keyword(s):  
Stock Assessment ◽  
Fish Habitat ◽  
Habitat Change ◽  
Reference Points ◽  
Subsistence Fisheries ◽  
Stock Status ◽  
Enhanced Production ◽  
Global Status ◽  
Fish Habitats

AbstractAt the crux of the debate over the global sustainability of fisheries is what society must do prevent overexploitation of fisheries and aid recovery of fisheries that have historically been overexploited. The focus of debates has been on controlling fishing pressure and assessments have not considered that stock production may be affected by changes in fish habitat. Fish habitats are being modified by climate change, built infrastructure, destructive fishing practices and pollution. We conceptualise how the classification of stock status can be biased by habitat change. Habitat loss can result in either overly optimistic or overly conservative assessment of stock status. The classification of stock status depends on how habitat affects fish demography and what reference points management uses to assess status. Nearly half of the 418 stocks in a global stock assessment database use seagrass, mangroves, coral reefs and macroalgae, habitats that have well documented trends. There is also considerable circumstantial evidence that habitat change has contributed to overexploitation or enhanced production of data-poor fisheries, like inland and subsistence fisheries. Globally many habitats are in decline, so the role of habitat should be considered when assessing the global status of fisheries. New methods and global databases of habitat trends, and use of habitats by fishery species are required to properly attribute the causes of decline in fisheries, and are likely to raise the profile of habitat protection as an important complementary aim for fisheries management.

Analytical reference points for age-structured models: application to data-poor fisheries

2009 ◽  
Vol 67 (1) ◽  
pp. 165-175 ◽  
Author(s):  
Elizabeth N. Brooks ◽  
Joseph E. Powers ◽  
Enric Cortés
Keyword(s):  
Stock Assessment ◽  
Meta Analysis ◽  
Reproductive Rate ◽  
Biological Data ◽  
Reference Points ◽  
Assessment Model ◽  
Shark Species ◽  
Stock Status ◽  
Age Structured ◽  
Analytical Reference

AbstractBrooks, E. N., Powers, J. E., and Cortés, E. 2010. Analytical reference points for age-structured models: application to data-poor fisheries. – ICES Journal of Marine Science, 67: 165–175. Analytical solutions for biological reference points are derived in terms of maximum lifetime reproductive rate. This rate can be calculated directly from biological parameters of maturity, fecundity, and natural mortality or a distribution for this rate can be derived from appropriate metadata. Minimal data needs and assumptions for determining stock status are discussed. The derivations lead to a re-parameterization of the common stock–recruit relationships, Beverton–Holt and Ricker, in terms of spawning potential ratio. Often, parameters in stock–recruit relationships are restricted by tight prior distributions or are fixed based on a hypothesized level of stock resilience. Fixing those parameters is equivalent to specifying the biological reference points. An ability to directly calculate reference points from biological data, or a meta-analysis, without need of a full assessment model or fisheries data, makes the method an attractive option for data-poor fisheries. The derivations reveal an explicit link between the biological characteristics of a species and appropriate management. Predicted stock status for a suite of shark species was compared with recent stock assessment results, and the method successfully identified whether each stock was overfished.

scholarly journals Assessing the Potential of Catch-Only Models to Inform on the State of Global Fisheries and the UN’s SDGs

2021 ◽  
Vol 13 (11) ◽  
pp. 6101
Author(s):  
Rishi Sharma ◽  
Henning Winker ◽  
Polina Levontin ◽  
Laurence Kell ◽  
Dan Ovando ◽  
...  
Keyword(s):  
Stock Assessment ◽  
Fishing Effort ◽  
The State ◽  
Sources Of Information ◽  
Ongoing Research ◽  
Traditional Assessment ◽  
Stock Status ◽  
Stock Assessments ◽  
Recent Developments ◽  
Measure Of Performance

Catch-only models (COMs) have been the focus of ongoing research into data-poor stock assessment methods. Two of the most recent models that are especially promising are (i) CMSY+, the latest refined version of CMSY that has progressed from Catch-MSY, and (ii) SRA+ (Stock Reduction Analysis Plus) a recent developments in field. Comparing COMs and evaluating their relative performance is essential for determining the state of regional and global fisheries that may be lacking necessary data that would be required to run traditional assessment models. In this paper we interrogate how performance of COMs can be improved by incorporating additional sources of information. We evaluate the performance of COMs on a dataset of 48 data-rich ICES (International Council for the Exploration of Seas) stock assessments. As one measure of performance, we consider the ability of the model to correctly classify stock status using FAO’s 3-tier classification that is also used for reporting on sustainable development goals to the UN. Both COMs showed notable bias when run with their inbuilt default heuristics, but as the quality of prior information increased, classification rates for the terminal year improved substantially. We conclude that although further COM refinements show some potential, most promising is the ongoing research into developing biomass or fishing effort priors for COMs in order to be able to reliably track stock status for the majority of the world’s fisheries currently lacking stock assessments.

Reference points for the length-based indicator Lmax5% for use in the assessment of data-limited stocks

2019 ◽  
Vol 76 (7) ◽  
pp. 2125-2139 ◽  
Author(s):  
Tanja Miethe ◽  
Yves Reecht ◽  
Helen Dobby
Keyword(s):  
Life Histories ◽  
Stock Assessment ◽  
Reference Points ◽  
Length Frequency ◽  
Frequency Distributions ◽  
Simulation Tools ◽  
Spawning Potential Ratio ◽  
The Mean ◽  
Commercial Sources ◽  
Length Frequency Data

Abstract In the absence of abundance indices from scientific surveys or commercial sources, reliable length frequency data from sampled commercial catches can be used to provide an indirect assessment of fishing mortality. Length-based indicators are simple metrics which describe length frequency distributions. The length-based indicator Lmax5%, the mean length of the largest 5% of individuals in the catch, combined with appropriately selected reference points, can be used to evaluate the presence of very large individuals in the catch and hence determine exploitation level. Using analytical per-recruit models, we derive reference points consistent with a spawning potential ratio of 40%. The reference points depend on the life history parameters for natural mortality, maturity, and growth (M, Lmat, L∞, k, CVL∞). Using available simulation tools, we investigate the sensitivity of the reference points to errors in these parameters and explore the usefulness of particular reference points for management purposes for stocks with different life histories. The proposed reference points are robust to uncertainty in length at first capture, Lc, and take into account the maturation schedule of a species. For those stocks with high M/k ratios (>1), Lmax5%, combined with the appropriate reference point, can be used to provide a data-limited stock assessment.

scholarly journals Stock assessment and projections incorporating discard estimates in some years: an application to the hake stock in ICES Divisions VIIIc and IXa

2010 ◽  
Vol 67 (6) ◽  
pp. 1185-1197 ◽  
Author(s):  
C. Fernández ◽  
S. Cerviño ◽  
N. Pérez ◽  
E. Jardim
Keyword(s):  
Time Series ◽  
Stock Assessment ◽  
Reference Points ◽  
Assessment Model ◽  
Marine Science ◽  
Fishing Mortality ◽  
Change Over Time ◽  
Age Structured ◽  
Available Information ◽  
Over Time

Abstract Fernández, C., Cerviño, S., Pérez, N., and Jardim, E. 2010. Stock assessment and projections incorporating discard estimates in some years: an application to the hake stock in ICES Divisions VIIIc and IXa. – ICES Journal of Marine Science, 67: 1185–1197. A Bayesian age-structured stock assessment model is developed to take into account available information on discards and to handle gaps in the time-series of discard estimates. The model incorporates mortality attributable to discarding, and appropriate assumptions about how this mortality may change over time are made. The result is a stock assessment that accounts for information on discards while, at the same time, producing a complete time-series of discard estimates. The method is applied to the hake stock in ICES Divisions VIIIc and IXa, for which the available data indicate that some 60% of the individuals caught are discarded. The stock is fished by Spain and Portugal, and for each country, there are discard estimates for recent years only. Moreover, the years for which Portuguese estimates are available are only a subset of those with Spanish estimates. Two runs of the model are performed; one assuming zero discards and another incorporating discards. When discards are incorporated, estimated recruitment and fishing mortality for young (discarded) ages increase, resulting in lower values of the biological reference points Fmax and F0.1 and, generally, more optimistic future stock trajectories under F-reduction scenarios.

scholarly journals Quirky patterns in time-series of estimates of recruitment could be artefacts

2014 ◽  
Vol 72 (1) ◽  
pp. 111-116 ◽  
Author(s):  
M. Dickey-Collas ◽  
N. T. Hintzen ◽  
R. D. M. Nash ◽  
P-J. Schön ◽  
M. R. Payne
Keyword(s):  
Time Series ◽  
Stock Assessment ◽  
Meta Analysis ◽  
Reference Points ◽  
Fish Stocks ◽  
Stock Recruitment ◽  
Modelling Assumptions ◽  
Meta Analyses ◽  
Recruitment Model ◽  
Recruitment Time

Abstract The accessibility of databases of global or regional stock assessment outputs is leading to an increase in meta-analysis of the dynamics of fish stocks. In most of these analyses, each of the time-series is generally assumed to be directly comparable. However, the approach to stock assessment employed, and the associated modelling assumptions, can have an important influence on the characteristics of each time-series. We explore this idea by investigating recruitment time-series with three different recruitment parameterizations: a stock–recruitment model, a random-walk time-series model, and non-parametric “free” estimation of recruitment. We show that the recruitment time-series is sensitive to model assumptions and this can impact reference points in management, the perception of variability in recruitment and thus undermine meta-analyses. The assumption of the direct comparability of recruitment time-series in databases is therefore not consistent across or within species and stocks. Caution is therefore required as perhaps the characteristics of the time-series of stock dynamics may be determined by the model used to generate them, rather than underlying ecological phenomena. This is especially true when information about cohort abundance is noisy or lacking.

Relationships between riverine fish and woody debris: implications for lowland rivers

1999 ◽  
Author(s):  
D. A. Crook ◽  
A. I. Robertson
Keyword(s):  
Woody Debris ◽  
Fish Habitat ◽  
Reference Points ◽  
Positive Development ◽  
Lowland River ◽  
Predator Prey ◽  
Lowland Rivers ◽  
Habitat Features ◽  
Surface Areas ◽  
Riverine Fish

This paper reviews studies of relationships between riverine fish and woody debris at micro- and meso-habitat scales, and discusses the potential functions of instream structure for lowland river fish. Experimental research, mainly in North America, has identified three main functions of woody debris as microhabitat for fish in upland streams: overhead cover that decreases predation risk both vertically and horizontally; horizontal visual isolation that reduces contact between fish; and velocity refuge which minimizes energetic costs. As with habitat features in other aquatic environments, increasing spatial complexity of woody debris may modify predator–prey interactions and provide greater surface areas for the growth of prey items. Woody debris may also provide spatial reference points for riverine fish to assist them in orienting within their surroundings. Lowland rivers differ from upland streams in terms of a number of physical variables, including turbidity, depth and water turbulence. Relationships between fish and woody debris in lowland rivers are likely to rely on mechanisms different to those in upland streams. Recent initiatives involving the reintroduction of woody debris into previously cleared lowland rivers to replace lost fish habitat are a positive development for lowland river restoration. However, if woody debris reintroduction is to maximally benefit lowland river fisheries, there is a requirement for better understanding of the ecological functions of woody debris in lowland rivers.

AZOV SEA VIMBA INDICATOR ASSESSMENT OF THE STATE OF FISH POPULATION IN TERMS OF LACK OF BIOLOGICAL DATA BY LBI MODEL

Fisheries ◽  
2021 ◽  
Vol 2021 (3) ◽  
pp. 68-75
Author(s):  
Inna Kozobrod ◽  
M. Pyatinsky ◽  
Elena Vlasenko
Keyword(s):  
Stock Assessment ◽  
Fish Population ◽  
Maximum Sustainable Yield ◽  
Biological Data ◽  
Reference Points ◽  
Population Characteristics ◽  
Small Scale ◽  
Assessment Procedure ◽  
Indicator Method ◽  
Yield Level

Stock assessment of vimba population Vimba vimba (Linnaeus, 1758) in period 2015–2020 was performed by qualitative indicator method LBI (Length-Based Indicators) that allows to assess qualitative characteristics of the population and fisheries and MSY biological reference points. The indicator, qualitative approach to stock assessment was applied due to absence vimba population of stable stock-recruitment relationship (due to artificial reproduction exist), which makes impossible to apply surplus production approach to solve production equation dB/dt. LBI model was performed based on available length-weight vimba frequencies dynamics information, which allows to evaluate qualitative population characteristics and fisheries impact. Model results shows no overexploitation signals: in period 2015–2020 fisheries are carried out in maximum sustainable yield level. Indicator results according to reference points indicate no significant signals of reduction optimal length class (Lopt), small-size or large-size class. In 2016 and 2018 uncertain overexploitation of small-scale classes leads to no significant changes was underlined. In terms of biological and fisheries data lacking, LBI methods allow to perform stock assessment procedure more stable and robust then surplus or cohort approach, and output scientific advice to fisheries management.

scholarly journals Integrating spatial synchrony/asynchrony of population distribution into stock assessment models: a spatial hierarchical Bayesian statistical catch-at-age approach

2016 ◽  
Vol 73 (7) ◽  
pp. 1725-1738 ◽  
Author(s):  
Yan Jiao ◽  
Rob O'Reilly ◽  
Eric Smith ◽  
Don Orth ◽  
Keyword(s):  
Relative Abundance ◽  
Bayesian Model ◽  
Population Distribution ◽  
Stock Assessment ◽  
Spatial Models ◽  
Reference Points ◽  
Hierarchical Bayesian ◽  
Hierarchical Bayesian Model ◽  
Spatial Synchrony ◽  
Abundance Indices

Abstract In many marine fisheries assessments, population abundance indices from surveys collected by different states and agencies do not always agree with each other. This phenomenon is often due to the spatial synchrony/asynchrony. Those indices that are asynchronous may result in discrepancies in the assessment of temporal trends. In addition, commonly employed stock assessment models, such as the statistical catch-at-age (SCA) models, do not account for spatial synchrony/asynchrony associated with spatial autocorrelation, dispersal, and environmental noise. This limits the value of statistical inference on key parameters associated with population dynamics and management reference points. To address this problem, a set of geospatial analyses of relative abundance indices is proposed to model the indices from different surveys using spatial hierarchical Bayesian models. This approach allows better integration of different surveys with spatial synchrony and asynchrony. We used Atlantic weakfish (Cynoscion regalis) as an example for which there are state-wide surveys and expansive coastal surveys. We further compared the performance of the proposed spatially structured hierarchical Bayesian SCA models with a commonly used Bayesian SCA model that assumes relative abundance indices are spatially independent. Three spatial models developed to mimic different potential spatial patterns were compared. The random effect spatially structured hierarchical Bayesian model was found to be better than the commonly used SCA model and the other two spatial models. A simulation study was conducted to evaluate the uncertainty resulting from model selection and the robustness of the recommended model. The spatially structured hierarchical Bayesian model was shown to be able to integrate different survey indices with/without spatial synchrony. It is suggested as a useful tool when there are surveys with different spatial characteristics that need to be combined in a fisheries stock assessment.

scholarly journals Cutoff points of BMI for classification of nutritional status using bioelectrical impedance analysis

2018 ◽  
Vol 9 (1) ◽  
pp. 24-30
Author(s):  
Mirele S. Mialich ◽  
Bruna R. Silva ◽  
Alceu A. Jordao
Keyword(s):  
Nutritional Status ◽  
Bioelectrical Impedance Analysis ◽  
Bioelectrical Impedance ◽  
Impedance Analysis ◽  
Reference Points ◽  
North India ◽  
Cross Sectional ◽  
Men And Women ◽  
Cutoff Points

Abstract The objective of this study was to improve the cutoff points of the traditional classification of nutritional status and overweight / obesity based on the BMI in a Brazilian sample. A cross-sectional study was conducted on 1301 individuals of both genders aged 18 to 60 years. The subjects underwent measurement of weight and height and bioelectrical impedance analysis. Simple linear regression was used for statistical analysis, with the level of significance set at p < 0.05. The sample consisted of 29.7% men and 70.3% women aged on averaged 35.7 ± 17.6 years; mean weight was 67.6 ± 16.0 kg, mean height was 164.9 ± 9.5 cm, and mean BMI was 24.9 ± 5.5 kg/m2. As expected, lower cutoffs were found for BMI than the classic reference points traditionally adopted by the WHO for the classification of obesity, i.e., 27.15 and 27.02 kg/m2 for obesity for men and women, respectively. Other authors also follow this tendency, Romero-Corral et al. (2008) suggested 25.8 to 25.5 kg/m2 for American men and women as new values for BMI classification of obesity. Gupta and Kapoor (2012) proposed 22.9 and 28.8 kg/m2 for men and women of North India. The present investigation supports other literature studies which converge in reducing the BMI cutoff points for the classification of obesity. Thus, we emphasize the need to conduct similar studies for the purpose of defining these new in populations of different ethnicities.

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