Analysis of Length Frequency Samples with Relative Abundance Data for the Gulf of Maine Northern Shrimp (Pandalus borealis) by the MULTIFAN Method

1991 ◽  
Vol 48 (4) ◽  
pp. 591-598 ◽  
Author(s):  
David A. Fournier ◽  
John R. Sibert ◽  
Mark Terceiro
Keyword(s):  
Relative Abundance ◽  
Gulf Of Maine ◽  
Parameter Estimates ◽  
Detailed Knowledge ◽  
Frequency Data ◽  
Length Frequency ◽  
Pandalus Borealis ◽  
Abundance Data ◽  
Northern Shrimp ◽  
Length Frequency Data

We present an extension of the MULTIFAN method for simultaneously analyzing several length frequency data sets from length frequency data collected by research trawl surveys. The assumption that the research trawl samples the animals in a regular fashion allows the proportions at age in the samples to be parameterized in terms of relative year class strengths and the age-dependent selectivity of the sampling procedure. When available, relative abundance data can be incorporated into the analysis and permit the estimation of mortality. The method is applied to Gulf of Maine northern shrimp (Pandalus borealis) data. The parameter estimates obtained agree substantially with those previously obtained using a more detailed knowledge of the species' biology.

MULTIFAN a Likelihood-Based Method for Estimating Growth Parameters and Age Composition from Multiple Length Frequency Data Sets Illustrated using Data for Southern Bluefin Tuna (Thunnus maccoyii)

1990 ◽  
Vol 47 (2) ◽  
pp. 301-317 ◽  
Author(s):  
D. A. Fournier ◽  
John R. Sibert ◽  
Jacek Majkowski ◽  
John Hampton
Keyword(s):  
Growth Parameters ◽  
Bluefin Tuna ◽  
Parameter Estimates ◽  
Data Sets ◽  
Frequency Data ◽  
Length Frequency ◽  
Objective Criterion ◽  
Southern Bluefin Tuna ◽  
Robust Likelihood ◽  
Length Frequency Data

We present a method for simultaneously analyzing multiple length frequency data sets. The method utilizes a robust likelihood-based estimation procedure that provides an objective criterion for hypothesis testing. The method is applied to length frequency data from southern bluefin tuna (Thunnus maccoyii) for which independent estimates of growth parameters based on tag return data are available. The estimates of the growth parameters from the new method were found to be in substantial agreement with the values previously obtained for these parameters. The strength of the likelihood approach is demonstrated by discriminating between alternative structural hypotheses for describing the data. The ability to simultaneously analyze multiple samples permits the method to exploit the extra information not available when analyzing samples one by one. The computer program maintains a database of fits to the data which enable the user to organize the results of the analysis. Graphical displays permit the user to view any of the fits, and an interactive graphics routine aids the user to find good initial parameter estimates.

scholarly journals A study of the life history of Brazilian sardine, Sardinella brasiliensis: IV. Distribution and abundance of sardine larvae

1977 ◽  
Vol 26 (2) ◽  
pp. 219-247 ◽  
Author(s):  
Yasunobu Matsuura
Keyword(s):  
Relative Abundance ◽  
Larval Abundance ◽  
Frequency Data ◽  
Length Frequency ◽  
Depth Zone ◽  
Average Temperature ◽  
History Of ◽  
The Mean ◽  
Egg Abundance ◽  
Length Frequency Data

Data on distribution and abundance of larvae of the Brazilian sardine, Sardinella brasiliensis, are presented based on samples collected in waters off southern Brazil during 1969 to 1971. The distribution pattern and relative abundance of sardine larvae during three spawning seasons are discussed. Relative abundance, using regional census estimates, was calculated each year. In general, larval abundance in each subarea coincided with that of eggs, although the area of distribution of larvae was larger than the spawning area. Estimates of larval abundance showed that the 1970-71 spawning season was the poorest, both in larval and egg abundance, despite the enlarged size of the area surveyed. The average temperature at stations where sardine larvae occurred was 23.4º C, ranging from 14.6 to 27.4º C, and the average salinity was 35.6º /oo, ranging from 35.0 to 36.7º /oo. Distribution of the larvae in different depth zones was analysed. Larvae usually were most abundant in the 51-100 m depth zone. No tendency for a unidirectional transport of larvae was observed; apparently they move from the spawning ground in all possible directions, spreading over the continental shelf. An estimate of survival rate of larvae, based on length frequency data pooled from the three years, was calculated. Undersampling of larvae during daytime was observed. The mean night-day catch ratio, based on larvae from all length classes sampled, was 3.93.

scholarly journals Estimating growth parameters and growth variability from length frequency data using hierarchical mixture models

2019 ◽  
Vol 76 (7) ◽  
pp. 2150-2163
Author(s):  
Luke Batts ◽  
Cóilín Minto ◽  
Hans Gerritsen ◽  
Deirdre Brophy
Keyword(s):  
Mixture Models ◽  
Growth Parameters ◽  
Growth Parameter ◽  
Melanogrammus Aeglefinus ◽  
Parameter Estimates ◽  
Frequency Data ◽  
Length Frequency ◽  
Frequency Distributions ◽  
Growth Variability ◽  
Length Frequency Data

Abstract Analysis of length frequency distributions from surveys is one well-known method for obtaining growth parameter estimates where direct age estimates are not available. We present a likelihood-based procedure that uses mixture models and the expectation–maximization algorithm to estimate growth parameters from length frequency data (LFEM). A basic LFEM model estimates a single set of growth parameters that produce one set of component means and standard deviations that best fits length frequency distributions over all years and surveys. The hierarchical extension incorporates bivariate random effects into the model. A hierarchical framework enables inter-annual or inter-cohort variation in some of the growth parameters to be modelled, thereby accommodating some of the natural variation that occurs in fish growth. Testing on two fish species, haddock (Melanogrammus aeglefinus) and white-bellied anglerfish (Lophius piscatorius), we were able to obtain reasonable estimates of growth parameters, as well as successfully model growth variability. Estimated growth parameters showed some sensitivity to the starting values and occasionally failed to converge on biologically realistic values. This was dealt with through model selection and was partly addressed by the addition of the hierarchical extension.

scholarly journals POPULATION DYNAMICS OF THE MAIN PELAGIC SPECIES EXPLOITED IN THE JAVA SEA: BIOLOGICAL PARAMETERS ESTIMATES

2017 ◽  
Vol 12 (1) ◽  
pp. 37
Author(s):  
Bambang Sadhotomo
Keyword(s):  
Population Dynamics ◽  
Data Structure ◽  
Growth Parameters ◽  
Parameter Estimates ◽  
Biological Parameters ◽  
Frequency Data ◽  
Length Frequency ◽  
Pelagic Species ◽  
Java Sea ◽  
Length Frequency Data

several sets of length frequency data (1991 to 1995) of the six species were used to estimate the growth parameters and to discuss the results in relation to possible influence of data structure on the parameter estimates

scholarly journals POPULATION DYNAMICS OF MALAYAN LEAF FISH (Pristolepisgrooti Blkr.) IN RANAU LAKE, SOUTH SUMATRA

2018 ◽  
Vol 24 (2) ◽  
pp. 125
Author(s):  
Sevi Sawetri ◽  
Subagdja Subagdja ◽  
Dina Muthmainnah
Keyword(s):  
Mortality Rate ◽  
Growth Parameters ◽  
Total Mortality ◽  
Natural Mortality ◽  
Fishing Mortality ◽  
Frequency Data ◽  
Length Frequency ◽  
Lake Ecosystems ◽  
Exploitation Rate ◽  
Length Frequency Data

The Malayan leaf fish or locally named as kepor (Pristolepis grooti) is one of important biotic components in Ranau Lake ecosystems. This study aimed to estimate population dynamic and exploitation rate of kepor in Ranau Lake, South Sumatera. The population parameters are estimated based on length frequency data which were collected in March to October 2013. Growth parameters and fishing mortality rates were calculated using FiSAT software package. The results showed that kepor’s growth was negative allometric, which tended to gain length faster than weight. Kepor population was dominated (42%) by individual length of 10.0 to 11.0 cm. Predicted length infinity (L) was 17.28 cm with high value of growth rates (K) of 1.4 year-1. The natural mortality rate (M) is 2.57 year-1, the fishing mortality rate (F) is 5.36 year-1 and total mortality rate (Z) is 7.93 year-1. The exploitation rate of Malayan leaf fish in Ranau Lake (E = 0.68 year-1) has passed the optimum score.  

scholarly journals Investigation and Development of Post-Season Modelling of Arrow Squid in the Snares and Auckland Islands

2021 ◽  
Author(s):  
◽  
Vidette Louise McGregor
Keyword(s):  
Automatic Differentiation ◽  
Integrated Model ◽  
Current Data ◽  
Management Approach ◽  
Frequency Data ◽  
Catch Per Unit Effort ◽  
Length Frequency ◽  
Model Builder ◽  
Set Up ◽  
Length Frequency Data

<p>Squid fisheries require a different management approach to most fish species which are much longer living. Most squid live for around one year, spawn and then die. The result of this is an entirely new stock each year with little or no relationship of stock sizes between the years. Hence, it is difficult to set appropriate catch limits prior to the season. Currently, there is nothing set up for modelling the New Zealand squid fishery in-season or post-season. In-season management would allow for adjustments of catch limits during a season. Post-season management would provide information on how much the stock was exploited during a season (described as the escapement). I have produced an integrated model using ADMB (Automatic Differentiation Model Builder) (Fournier et al., 2011) which models length frequency data, CPUE (Catch Per Unit Effort) indices and catch weights from a season. It calculates escapement which indicates how much the fishery is currently being exploited. In running the model against data from four area and year combinations, I found the escapement calculation to be stable. The results suggest this modelling approach could be used with the current data collected for post-season modelling of the fishery. I am less confident about in-season modelling with the current data collected. The integrated model fits quite poorly to the CPUE data, suggesting some discrepancy either between the data or the assumptions made of them. Sampling from a greater number of tows is recommended to improve the length frequency data and this may also improve the ability of the model to fit both to these and the CPUE.</p>

scholarly journals Investigation and Development of Post-Season Modelling of Arrow Squid in the Snares and Auckland Islands

2021 ◽  
Author(s):  
◽  
Vidette Louise McGregor
Keyword(s):  
Automatic Differentiation ◽  
Integrated Model ◽  
Current Data ◽  
Management Approach ◽  
Frequency Data ◽  
Catch Per Unit Effort ◽  
Length Frequency ◽  
Model Builder ◽  
Set Up ◽  
Length Frequency Data

<p>Squid fisheries require a different management approach to most fish species which are much longer living. Most squid live for around one year, spawn and then die. The result of this is an entirely new stock each year with little or no relationship of stock sizes between the years. Hence, it is difficult to set appropriate catch limits prior to the season. Currently, there is nothing set up for modelling the New Zealand squid fishery in-season or post-season. In-season management would allow for adjustments of catch limits during a season. Post-season management would provide information on how much the stock was exploited during a season (described as the escapement). I have produced an integrated model using ADMB (Automatic Differentiation Model Builder) (Fournier et al., 2011) which models length frequency data, CPUE (Catch Per Unit Effort) indices and catch weights from a season. It calculates escapement which indicates how much the fishery is currently being exploited. In running the model against data from four area and year combinations, I found the escapement calculation to be stable. The results suggest this modelling approach could be used with the current data collected for post-season modelling of the fishery. I am less confident about in-season modelling with the current data collected. The integrated model fits quite poorly to the CPUE data, suggesting some discrepancy either between the data or the assumptions made of them. Sampling from a greater number of tows is recommended to improve the length frequency data and this may also improve the ability of the model to fit both to these and the CPUE.</p>

scholarly journals KORELASI PARAMETER MORFOMETRIK, NISBAH KELAMIN DAN KOMPOSISI UKURAN IKAN PEDANG (Xiphias gladius L.) DI SAMUDERA HINDIA

2015 ◽  
Vol 6 (3) ◽  
pp. 155
Author(s):  
Bram Setyadji ◽  
Budi Nugraha
Keyword(s):  
Body Size ◽  
Standard Form ◽  
Fork Length ◽  
Secondary Data ◽  
Primary Data ◽  
Frequency Data ◽  
Length Frequency ◽  
Lower Jaw ◽  
Length Measurements ◽  
Length Frequency Data

Model pengkajian stok melalui data frekuensi panjang lebih banyak digunakan karena data tersebut paling banyak tersedia dan mudah didapatkan dibandingkan data pengukuran jaringan keras (sisik, otolith, sirip dan tulang belakang) dan tagging. Khusus untuk ikan pedang, data panjang yang tersedia sebagian besar tidak standar dikarenakan ikan pedang yang tertangkap langsung diproses di laut yang mana bagian kepala, sirip, isi perut dibuang. Oleh karena itu dibutuhkan persamaan empiris untuk konversi dari ukuran non-standar ke standar sehingga bisa digunakan sebagai basis data pengkajian stok yang berbasis data tersebut. Data primer merupakan hasil observasi laut selama kurun waktuMaret 2011 sampai dengan Desember 2013, sedangkan data sekunder merupakan data observasi ilmiah Loka Penelitian Perikanan Tuna periode 2005-2013. Hasil penelitian menunjukkan terdapat korelasi yang signifikan antara beberapa parametermorfometrik ikan pedang yang diukur yakni panjang dari pangkal sirip dada ke ujung lekukan tengah sirip ekor (LJFL), panjang dari mata ke ujung lekukan tengah sirip ekor (EFL) dan panjang dari ujung rahang bawah ke ujung lekukan tengah sirip ekor (PFL) (R2 > 0,97; P < 0,01), akan tetapi tidak ada perbedaan yang nyata antara morfometri ikan pedang dan jenis kelamin (EFL-LJFL, P > 0,05 dan PFL-LJFL, P > 0,05). Hubungan antara nisbah kelamin dengan panjang ikan signifikan (Nisbah Kelamin = 0,0175 LJFL – 3,1001; n = 6, selang kelas 5 cm; P < 0,01) yang mana ikan pedang dengan ukuran lebih dari 260 cmadalah betina.Stock assessment models using length frequency data are more frequently used by Indonesian scientist due to its availability and easily obtained rather than skeletal parts or tagging data. As for swordfish most of the data vailable are not in standard form because most of swordfish landed are usually dressed at sea with various ways, so the length measurement are possible done afterward. There fore conversion among different length measurements is a necessity for assessment and management purposes. Primary data was collected from scientific observer program conducted between March 2011 and December 2013, while secondary data was obtained from 2005-2013. The results showed that the models are fit quite well for Lower Jaw Fork Length (LJFL), Eye Orbit Fork Length (EOFL) and Pectoral Fork Length (PFL) (R2> 0.97; P < 0.01) and there was no significant relationship between morphometric and sex (EFL-LJFL, P > 0.05 and PFL-LJFL, P > 0.05). Correlation between sex ratio and body size proved to be significant with nearly all of the swordfish >260 cm was female.

Using length-frequency data to elucidate the population dynamics of Argulus foliaceus (Crustacea: Branchiura)

Parasitology ◽  
2009 ◽  
Vol 136 (9) ◽  
pp. 1023-1032 ◽  
Author(s):  
N. G. H. TAYLOR ◽  
R. WOOTTEN ◽  
C. SOMMERVILLE
Keyword(s):  
Population Dynamics ◽  
Growth Rates ◽  
Egg Laying ◽  
Frequency Data ◽  
Length Frequency ◽  
Reliable Prediction ◽  
Egg Incubation ◽  
Novel Method ◽  
Argulus Foliaceus ◽  
Length Frequency Data

SUMMARYThis study uses a novel method for discriminating cohorts and investigating the population dynamics of the parasitic crustacean, Argulus foliaceus. Analysis of parasite length-frequency data was carried out in order to elucidate the timings and drivers behind the parasite's life cycle. Up to 6 cohorts of the parasite emerge through the course of 1 year in still-water trout fisheries in England. Recruitment ceases over the winter months; however, 3 cohorts of the parasite over-winter, 2 as eggs and 1 as a hatched stage. The technique, when used in conjunction with temperature data, also allowed for the reliable prediction of growth rates and provided estimates of egg incubation times and the length of hatching periods. These data showed that growth rates increased exponentially between the observed temperatures of 4 to 22°C. The method allowed for the time taken from hatching to egg laying under field conditions to be predicted and produced estimates that were validated against independent laboratory studies on the growth of the parasite.

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