scholarly journals Data for Fish Stock Assessment Obtained from the CMSY Algorithm for all Global FAO Datasets

Data ◽  
2019 ◽  
Vol 4 (2) ◽  
pp. 78 ◽  
Author(s):  
Arnaud Hélias
Keyword(s):  
Stock Assessment ◽  
Reference Points ◽  
Fish Stock ◽  
Fish Stocks ◽  
Food And Agriculture ◽  
Food And Agriculture Organization ◽  
Fish Catch ◽  
The Absolute ◽  
Fish Stock Assessment

Assessing the state of fish stocks requires the determination of descriptors. They correspond to the absolute and relative (to the carrying capacity of the habitat) fish biomasses in the ecosystem, and the absolute and relative (to the intrinsic growth rate of the population) fishing mortality resulting from catches. This allows, among other things, to compare the catch with the maximum sustainability yield. Some fish stocks are well described and monitored, but for many data-limited stocks, catch time series are remaining the only source of data. Recently, an algorithm (CMSY) has been proposed, allowing an estimation of stock assessment variables from catch and resilience. In this paper, we provide stock reference points for all global fisheries reported by Food and Agriculture Organization (FAO) major fishing area for almost 5000 fish stocks. These data come from the CMSY algorithm for 42% of the stock (75% of the global reported fish catch) and are estimated by aggregated values for the remaining 58%.

scholarly journals Length-Based Stock Assessment of Smith's Barb, Puntioplites proctozystron (Bleeker, 1865) (Cyprinidae) and Asian Redtail Catfish, Hemibagrus nemurus, (Valenciennes, 1840), (Bagridae) in a Multipurpose Reservoir in Thailand

2021 ◽  
Vol 34 (2) ◽  
Author(s):  
KAJITPAN CHARERNNATE ◽  
PAVAROT NORANARTTRAGOON ◽  
TUANTONG JUTAGATE ◽  
Keyword(s):  
Growth Parameters ◽  
Stock Assessment ◽  
Relative Yield ◽  
Mesh Size ◽  
Fish Stock ◽  
Fish Stocks ◽  
The Status ◽  
Curvature Parameter ◽  
Spawning Potential Ratio ◽  
Fish Stock Assessment

Catches from inland fisheries in Thailand are about 200,000 tonnes annually and plays an important role in food security and subsidiary income. However, fish stocks are seldom assessed because of the lack of catch and effort data. In this study, two fish stock assessment models, viz., relative yield per recruit and length-based spawning potential ratio, were used to evaluate the status of two species as well as to highlight their applications to datalimited situation in Thailand. The study was conducted at Kangkrajan Reservoir, Thailand, for two targeted species, viz., Smith's barb, Puntioplites proctozystron (Bleeker, 1865) and Asian redtail catfish, Hemibagrus nemurus (Valenciennes, 1840) using length frequency data. The data were collected throughout 2019. Both species showed isometric growth. Von Bertalanffy growth parameters were estimated. Asymptotic length, curvature parameter and theoretical age at length zero were 36.2 cm TL, 0.39 yr-1 and -0.28 yr for P. proctozystron, respectively, and 63.2 cm TL, 0.37 yr-1 and -0.32 yr for H. nemurus. The exploitation rates reveal that both species are slightly overfished. Sizes at 50 % maturity and 50 % selectivities were 17.8 and 23.5 cm TL for P. proctozystron, respectively, and 15.6 and 20.8 cm TL for H. nemurus. Considering both parameters, the size at first capture to sustain the fisheries of P. proctozystron and H. nemurus should be >18 cm and >30 cm, respectively, which can be achieved by mesh-size regulations.

scholarly journals Systmod II: Approaching a real dynamic computer model for fish stock assessment and development of fishery strategies

2016 ◽  
Author(s):  
Kristin Hamre ◽  
Steinar Moen ◽  
Johannes Hamre
Keyword(s):  
Stock Assessment ◽  
Growth Function ◽  
Field Studies ◽  
Fish Growth ◽  
Fish Stock ◽  
Initial State ◽  
Fish Stocks ◽  
Spawning Stock ◽  
Fish Stock Assessment ◽  
In The Beginning

Simulating development of fish stocks may be as complex as calculation of the development of the atmosphere, which is treated in meteorology as an initial value problem in physics. This approach was first proposed by Abbe and Bjerknes in the beginning of the 20 th century and today huge systems of differential equations are used to predict the weather. A similar approach to fisheries biology and ecology requires a real dynamic population model, which calculates the development of fish stocks from an initial state with equations that are independent of time. Here we present Systmod II, which uses a length-based growth function with a parameter for environmental variation and length-based data structure. The model uses monthly time steps to integrate population growth by moving fish to higher length groups as they grow. Since fish growth and maturity correlate more with length than with age, this gives comprehensive and clear results. The model was validated for Norwegian Spring-Spawning herring, using observed data from ICES working groups, and correlations (R2) between simulated and observed stock (total stock, spawning stock and catchable stock, numbers and biomass) were above 0.93. At present, the model makes reliable predictions on the short term (3 year for herring). For long term forecasts, better predictions of recruitment are needed . Since length is the main variable of the growth function, the state of the fish stock, including variability in length per yearclass, can be measured in situ, using hydro-acoustic trawl surveys. Data for modelling of many of the relations are still lacking, but can be filled in from future field studies.

scholarly journals Accounting for correlated observations in an age-based state-space stock assessment model

2016 ◽  
Vol 73 (7) ◽  
pp. 1788-1797 ◽  
Author(s):  
Casper W. Berg ◽  
Anders Nielsen
Keyword(s):  
State Space ◽  
Stock Assessment ◽  
Age Groups ◽  
Assessment Model ◽  
Fish Stock ◽  
Confidence Bounds ◽  
Independence Assumption ◽  
Fish Stocks ◽  
Fish Stock Assessment ◽  
Improved Model

Abstract Fish stock assessment models often rely on size- or age-specific observations that are assumed to be statistically independent of each other. In reality, these observations are not raw observations, but rather they are estimates from a catch-standardization model or similar summary statistics based on observations from many fishing hauls and subsamples of the size and age composition of the data. Although aggregation mitigates the strong intra-haul correlation between sizes/ages that is usually found in haul-by-haul data, violations of the independence assumption can have a large impact on the results and specifically on reported confidence bounds. A state-space assessment model that allows for correlations between age groups within years in the observation model for catches and surveys is presented and applied to data on several North Sea fish stocks using various correlation structures. In all cases the independence assumption is rejected. Less fluctuating estimates of the fishing mortality is obtained due to a reduced process error. The improved model does not suffer from correlated residuals unlike the independent model, and the variance of forecasts is decreased.

Use and abuse of fishery models

2001 ◽  
Vol 58 (1) ◽  
pp. 10-17 ◽  
Author(s):  
Jon T Schnute ◽  
Laura J Richards
Keyword(s):  
World Literature ◽  
Fishery Management ◽  
Stock Assessment ◽  
Management Practice ◽  
Fish Stock ◽  
Fish Stocks ◽  
Creative Thought ◽  
Modeling Process ◽  
Stock Biomass ◽  
Fish Stock Assessment

Recent failures of important fish stocks give mathematical models a poor reputation as tools for fishery management. This paper examines the role of models in fish stock assessment and identifies reasons why they can fail. Starting with laws of arithmetic, models attempt to relate observed data to unknown quantities, such as the stock biomass and abundance. Typically, the number of unknowns greatly exceeds the number of observations, and models must impose hypothetical constraints to give useful estimates. We use the word "fishmetic" (rhymes with arithmetic) to represent uncertainty in the conversion of arithmetic to practical fishery models. Arbitrary assumptions cannot be avoided, even though different choices can greatly influence the outcome of the analysis. We compare the modeling process in fisheries with that in other sciences. World literature also offers useful analogies. Potential reasons for failure suggest possible improvements to the application of fishery models. We recommend that modelers remain skeptical, expand their knowledge base, apply common sense, and implement robust strategies for fishery management. Particularly creative thought must be applied to the problem of translating scientific knowledge into management practice. Comparisons between fish stocks and financial stocks illustrate some possibilities.

STRUKTUR UKURAN DAN TINGKAT PEMANFAATAN IKAN LENCAM (Lethrinus lentjan Lacepede, 1802) PERAIRAN ARAFURA DI PROBOLINGGO

2020 ◽  
Vol 13 (1) ◽  
pp. 128-138
Author(s):  
Andina Ramadhani Putri Pane ◽  
Nurulludin Nurulludin ◽  
Heri Widiyastuti ◽  
Ali Suman
Keyword(s):  
Size Structure ◽  
Stock Assessment ◽  
Demersal Fish ◽  
Fish Population ◽  
Fish Stock ◽  
Control Value ◽  
Scientific Analysis ◽  
Fish Exploitation ◽  
Fish Stock Assessment

AbstrakPenangkapan ikan di perairan Arafura banyak dilakukan oleh nelayan dari Pulau Jawa diantaranya Jakarta, Probolinggo, Pati, dan Indramayu. Nelayan dari Probolinggo yang menangkap ikan di perairan Arafura (WPP 718) menggunakan alat tangkap jaring dan pancing rawai dengan tujuan utama adalah ikan demersal, yaitu kakap (Lutjanus spp.), kerapu (Epeniphelus spp.), lencam (Lethrinus lentjan.), dan lainnya. Pemanfaatan ikan demersal terutama ikan lencam (Lethrinus lentjan) yang terus-menerus akan memicu terjadinya perubahan stok populasi ikan di perairan, sehingga diperlukan analisa ilmiah sebagai dasar pengelolaan perikanan. Tujuan dari analisa ilmiah ini untuk menjadi nilai kontrol dalam pengawasan jumlah eksploitasi ikan dan bahan pengkajian stok ikan lencam (Lethrinus lentjan). Penelitian dilakukan Februari hingga Desember 2017 di TPI Mayangan Probolinggo. Struktur ukuran ikan 23–65 cmFL dengan dominan pada ukuran 50 cmFL dengan ukuran pertama kali tertangkap (Lc) 44,5 cmFL. Laju pertumbuhan (K) 0,32 per tahun dengan panjang asimtotik 74 cmFL. Tingkat kematian karena penangkapan (F) lebih tinggi daripada tingkat kematian alami (M) dan tingkat eksploitasi E = 0,57%, yang berarti telah terjadi overfishing. Pengurangan eksploitasi sebesar 14%, dan penetapan ukuran layak tangkap serta ukuran legal diperdagangkan dapat menjadi upaya dalam dalam menjaga populasi ikan lencam.Abstract Fishing in Arafura waters is mostly done by fishermen from Java, including Jakarta, Probolinggo, Pati, and Indramayu. Fishermen from Probolinggo who catch fish in Arafura waters (FMA 718) use fishing nets and longline fishing with the main purpose being demersal fish, namely snapper (Lutjanus spp.), Groupers (Epeniphelus spp.), Lencam (Lethrinus lentjan) and others. Exploitation of demersal fish, especially lencam fish (Lethrinus lentjan) which will continually trigger changes in fish population stock in waters, so the scientific analysis is needed as a basis for fisheries management. The purpose of this scientific analysis is to become a control value in monitoring the amount of fish exploitation for fish stock assessment  (Lethrinus lentjan). The study was conducted from February to December 2017 at TPI Mayangan Probolinggo. The size structure of fish 23–65 cmFL with a dominant size of 50 cmFL with the length at first capture (Lc) 44.5 cmFL. Growth rate (K) 0.32 per year with an asymptotic length of 74 cmFL. The fishing mortality (F) is higher than the natural mortality (M) and the exploitation level E = 0.57%, which means overfishing has occurred. The 14% reduction in exploitation and the determination of catch size and legal size of trade can be an effort in maintaining fish populations.

scholarly journals Systmod II: Approaching a real dynamic computer model for fish stock assessment and development of fishery strategies

2016 ◽  
Author(s):  
Kristin Hamre ◽  
Steinar Moen ◽  
Johannes Hamre
Keyword(s):  
Stock Assessment ◽  
Growth Function ◽  
Field Studies ◽  
Fish Growth ◽  
Fish Stock ◽  
Initial State ◽  
Fish Stocks ◽  
Spawning Stock ◽  
Fish Stock Assessment ◽  
In The Beginning

Simulating development of fish stocks may be as complex as calculation of the development of the atmosphere, which is treated in meteorology as an initial value problem in physics. This approach was first proposed by Abbe and Bjerknes in the beginning of the 20 th century and today huge systems of differential equations are used to predict the weather. A similar approach to fisheries biology and ecology requires a real dynamic population model, which calculates the development of fish stocks from an initial state with equations that are independent of time. Here we present Systmod II, which uses a length-based growth function with a parameter for environmental variation and length-based data structure. The model uses monthly time steps to integrate population growth by moving fish to higher length groups as they grow. Since fish growth and maturity correlate more with length than with age, this gives comprehensive and clear results. The model was validated for Norwegian Spring-Spawning herring, using observed data from ICES working groups, and correlations (R2) between simulated and observed stock (total stock, spawning stock and catchable stock, numbers and biomass) were above 0.93. At present, the model makes reliable predictions on the short term (3 year for herring). For long term forecasts, better predictions of recruitment are needed . Since length is the main variable of the growth function, the state of the fish stock, including variability in length per yearclass, can be measured in situ, using hydro-acoustic trawl surveys. Data for modelling of many of the relations are still lacking, but can be filled in from future field studies.

Integrating Anisakis spp. parasites data and host genetic structure in the frame of a holistic approach for stock identification of selected Mediterranean Sea fish species

Parasitology ◽  
2014 ◽  
Vol 142 (1) ◽  
pp. 90-108 ◽  
Author(s):  
S. MATTIUCCI ◽  
R. CIMMARUTA ◽  
P. CIPRIANI ◽  
P. ABAUNZA ◽  
B. BELLISARIO ◽  
...  
Keyword(s):  
Mediterranean Sea ◽  
Stock Assessment ◽  
Spatial Scales ◽  
Holistic Approach ◽  
Fish Population ◽  
Fish Host ◽  
Fish Stock ◽  
Stock Identification ◽  
Fish Stocks ◽  
Fish Stock Assessment

SUMMARYThe unique environment of the Mediterranean Sea makes fish stock assessment a major challenge. Stock identification of Mediterranean fisheries has been based mostly from data on biology, morphometrics, artificial tags, otolith shape and fish genetics, with less effort on the use of parasites as biomarkers. Here we use some case studies comparing Mediterranean vs Atlantic fish stocks in a multidisciplinary framework. The generalized Procrustes Rotation (PR) was used to assess the association between host genetics and larval Anisakis spp. datasets on demersal (hake) and pelagic (horse mackerel, swordfish) species. When discordant results emerged, they were due to the different features of the data. While fish population genetics can detect changes over an evolutionary timescale, providing indications on the cohesive action of gene flow, parasites are more suitable biomarkers when considering fish stocks over smaller temporal and spatial scales, hence giving information of fish movements over their lifespan. Future studies on the phylogeographic analysis of parasites suitable as biomarkers, and that of their fish host, performed on the same genes, will represent a further tool to be included in multidisciplinary studies on fish stock structure.

scholarly journals Fish Stock Assessment for Data-Poor Fisheries, with a Case Study of Tropical Hilsa Shad (Tenualosa ilisha) in the Water of Bangladesh

2021 ◽  
Vol 13 (7) ◽  
pp. 3604
Author(s):  
Mohammed Shahidul Alam ◽  
Qun Liu ◽  
Md. Rashed-Un- Nabi ◽  
Md. Abdullah Al-Mamun
Keyword(s):  
Stock Assessment ◽  
Mesh Size ◽  
Single Species ◽  
Assessment Method ◽  
Reference Points ◽  
Fish Stock ◽  
Total Fish ◽  
Future Potential ◽  
Fish Stock Assessment ◽  
Over Exploitation

The anadromous tropical Hilsa shad formed the largest single-species fishery in Bangladesh, making the highest contribution to the country’s total fish production (14%) and nearly 83% of the global Hilsa catch in 2018. However, increased fishing pressure made the fishery vulnerable, and hence, information on the stock condition and its response to the current degree of removal is essential to explore the future potential for sustainable exploitation. This study carried out a rigorous assessment based on three different methodological approaches (traditional length-frequency based stock assessment method for fishing mortality and exploitation, Froese’s length-based indicators for fishing sustainability, and a surplus production-based Monte Carlo method-CMSY, for fisheries reference points estimation) for the best possible estimates of the Hilsa stock status in the water of Bangladesh. The present findings revealed that the stock is likely to be overfished due to over-exploitation. Depending on the outputs, this study recommended a lower length limit for the catch (> 33 cm), distinguished a selectivity pattern (mesh size limit ≥ 8 cm), and proposed a yearly landing limit (within the range of 263,000–315,000 tons) for the sustainable management of the Hilsa fishery in Bangladesh.

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.

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