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

10.7287/peerj.preprints.2604 ◽

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.

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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

Asian Fisheries Science ◽

10.33997/j.afs.2021.34.2.005 ◽

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.

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Detecting and correcting underreported catches in fish stock assessment: trial of a new method

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f10-051 ◽

2010 ◽

Vol 67 (8) ◽

pp. 1247-1261 ◽

Cited By ~ 14

Author(s):

Nicolas Bousquet ◽

Noel Cadigan ◽

Thierry Duchesne ◽

Louis-Paul Rivest

Keyword(s):

Gadus Morhua ◽

Stock Assessment ◽

Population Analysis ◽

Assessment Model ◽

Fish Stock ◽

Stock Biomass ◽

Stock Assessments ◽

Spawning Stock ◽

Age Structured ◽

Fish Stock Assessment

Landings from fisheries are often underreported, that is, the true landings are greater than those reported. Despite this bias, reported landings are widely used in fish stock assessments, and this might lead to overoptimistic exploitation strategies. We construct a statistical stock assessment model that accounts for underreported landings using the theory of censoring with sequential population analysis (SPA). The new model is developed and implemented specifically for the cod stock ( Gadus morhua ) from the southern Gulf of St. Lawrence (Canada). This stock is known to have unreported overfishing during 1985–1992. We show in simulations that for this stock, the new censored model can correctly detect the problematic landings. These corrections are nearly insensitive to subjective boundaries placed on real catches and robust to modifications imposed in the simulation of landings. However, when surveys are too noisy, the new SPA for censored catches can result in increased uncertainty in parameters used for management such as spawning stock biomass and age-structured stock size.

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

ICES Journal of Marine Science ◽

10.1093/icesjms/fsw046 ◽

2016 ◽

Vol 73 (7) ◽

pp. 1788-1797 ◽

Cited By ~ 20

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.

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Use and abuse of fishery models

Canadian Journal of Fisheries and Aquatic Sciences ◽

10.1139/f00-150 ◽

2001 ◽

Vol 58 (1) ◽

pp. 10-17 ◽

Cited By ~ 63

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.

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

Data ◽

10.3390/data4020078 ◽

2019 ◽

Vol 4 (2) ◽

pp. 78 ◽

Cited By ~ 1

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%.

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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 ◽

10.1017/s0031182014001103 ◽

2014 ◽

Vol 142 (1) ◽

pp. 90-108 ◽

Cited By ~ 17

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.

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