scholarly journals Understanding the Dynamics of Ancillary Pelagic Species in the Adriatic Sea

2021 ◽  
Vol 8 ◽  
Author(s):  
Silvia Angelini ◽  
Enrico N. Armelloni ◽  
Ilaria Costantini ◽  
Andrea De Felice ◽  
Igor Isajlović ◽  
...  
Keyword(s):  
Adriatic Sea ◽  
Production Model ◽  
Horse Mackerel ◽  
Surplus Production ◽  
Robust Model ◽  
Production Models ◽  
The Status ◽  
History Of ◽  
Age Structured ◽  
Fish And Shellfish

The status of fishery resources in the Mediterranean Sea is critical: most of the fish and shellfish stocks are in overexploitation and only half of them are routinely assessed. This manuscript presents the use of Surplus Production Models (SPMs) as a valid option to increase the number of assessed stocks, with specific attention to the Adriatic basin. Particularly, the stock of European sprat (Sprattus sprattus), Mediterranean horse mackerel (Trachurus mediterraneus), and Atlantic horse mackerel (Trachurus trachurus) living in the Adriatic Sea have been evaluated comparing three SPMs: Catch Maximum Sustainable Yields (CMSY), Stochastic surplus Production model in Continuous Time (SPiCT), and Abundance Maximum Sustainable Yields (AMSY). The different approaches present some variations; however, they generally agree on describing all the stocks close to the reference values for both biomass and fishing mortality in the most recent year. For the European sprat, AMSY results are the most robust model for this species’ survey data allow depicting a clearer picture of the history of this stock. Indeed, for the horse mackerel species, CMSY or SPiCT results are the preferred models, since for these species landings are not negligible. Notwithstanding, age-structured assessments remain the most powerful approach for evaluating the status of resources, but SPMs have proved to be a powerful tool in a data-limited context.

scholarly journals Application of age-structured production models to assess oyster Striostrea margaritacea populations managed by rotational harvesting in KwaZulu-Natal, South Africa

2008 ◽  
Vol 66 (2) ◽  
pp. 408-419 ◽  
Author(s):  
Paul A. de Bruyn ◽  
Coleen L. Moloney ◽  
Michael H. Schleyer
Keyword(s):  
South Africa ◽  
Ad Hoc ◽  
North Coast ◽  
Management Zones ◽  
Production Models ◽  
Kwazulu Natal ◽  
Management Plans ◽  
The Status ◽  
History Of ◽  
Age Structured

Abstract de Bruyn, P. A., Moloney, C. L., and Schleyer, M. H. 2009. Application of age-structured production models to assess oyster Striostrea margaritacea populations managed by rotational harvesting in KwaZulu-Natal, South Africa. – ICES Journal of Masrine Science, 66: 408–419. Oysters have been harvested in KwaZulu-Natal for more than a century, by both commercial and recreational users. However, management of the resource has been based on ad hoc measures rather than quantitative, defensible management plans. Early in the history of the fishery, a rotational harvesting strategy was employed, but it has changed over time. At present, there are 10 management zones, each fished 2 years out of five, and recreational harvesting is allowed in the year preceding commercial harvesting. To assess the status of the oyster resource as well as the historical levels of exploitation, age-structured production models were applied to the oyster populations in the five North Coast management zones. The model fits to the observed data were good. Oyster abundance differed among zones, with the lowest abundance in the two most northern zones. As these zones had only recently been established, however, the paucity of data renders their assessments uncertain. The southernmost zone had the greatest oyster abundance. The benefits of rotational harvesting were demonstrated by the model outputs, which showed rapid population recovery during fallow years, suggesting sustainability of the resource. It is recommended that rotational harvesting continues to be used to manage oysters in KwaZulu-Natal.

scholarly journals The status of Japanese fisheries relative to fisheries around the world

2017 ◽  
Vol 74 (5) ◽  
pp. 1277-1287 ◽  
Author(s):  
Momoko Ichinokawa ◽  
Hiroshi Okamura ◽  
Hiroyuki Kurota
Keyword(s):  
Maximum Sustainable Yield ◽  
Production Model ◽  
Structured Population Model ◽  
Total Allowable Catch ◽  
Quick Recovery ◽  
Stock Status ◽  
Surplus Production Model ◽  
The Status ◽  
Stock Recruitment ◽  
Age Structured

We present the first quantitative review of the stock status relative to the stock biomass (B) and the exploitation rate (U) that achieved the maximum sustainable yield (MSY) (BMSY and UMSY, respectively) for 37 Japanese stocks contributing 61% of the total marine capture production in Japan. BMSY and UMSY were estimated by assuming three types of stock-recruitment (S-R) relationships and an age-structured population model or by applying a surplus production model. The estimated stock status shows that approximately half of the stocks were overfishing (U/UMSY > 1), and approximately half of the stocks were overfished (B/BMSY < 0.5) during 2011–2013. Over the past 15 years, U decreased and B slightly increased on average. The rate of decrease in the U of the stocks managed by the total allowable catch (TAC) was significantly greater than that of the other stocks, providing evidence of the effectiveness of TAC management in Japan. The above statuses and trends were insensitive to the assumption of the S-R relationship. The characteristics of Japanese stocks composed mainly of resources with relatively high natural mortality, i.e. productivity, suggest that Japanese fisheries have great potential of exhibiting a quick recovery and increasing their yield by adjusting the fishing intensity to an appropriate level.

scholarly journals Fisheries Reference Point and Stock Status of Croaker Fishery (Sciaenidae) Exploited from the Bay of Bengal, Bangladesh

2022 ◽  
Vol 10 (1) ◽  
pp. 63
Author(s):  
Partho Protim Barman ◽  
Md. Mostafa Shamsuzzaman ◽  
Petra Schneider ◽  
Mohammad Mojibul Hoque Mozumder ◽  
Qun Liu
Keyword(s):  
Bay Of Bengal ◽  
Maximum Sustainable Yield ◽  
Reference Points ◽  
Production Model ◽  
Fishing Pressure ◽  
Surplus Production ◽  
Stock Status ◽  
Management Measures ◽  
Production Models ◽  
The Monte Carlo Method

This research evaluated fisheries reference points and stock status to assess the sustainability of the croaker fishery (Sciaenidae) from the Bay of Bengal (BoB), Bangladesh. Sixteen years (2001–2016) of catch-effort data were analyzed using two surplus production models (Schaefer and Fox), the Monte Carlo method (CMSY) and the Bayesian state-space Schaefer surplus production model (BSM) method. This research applies a Stock–Production Model Incorporating Covariates (ASPIC) software package to run the Schaefer and Fox model. The maximum sustainable yield (MSY) produced by all models ranged from 33,900 to 35,900 metric tons (mt), which is very close to last year’s catch (33,768 mt in 2016). The estimated B > BMSY and F < FMSY indicated the safe biomass and fishing status. The calculated F/FMSY was 0.89, 0.87, and 0.81, and B/BMSY was 1.05, 1.07, and 1.14 for Fox, Schaefer, and BSM, respectively, indicating the fully exploited status of croaker stock in the BoB, Bangladesh. The representation of the Kobe phase plot suggested that the exploitation of croaker stock started from the yellow (unsustainable) quadrant in 2001 and gradually moved to the green (sustainable) quadrant in 2016 because of the reduction in fishing efforts and safe fishing pressure after 2012. Thus, this research suggests that the current fishing pressure needs to be maintained so that the yearly catch does not exceed the MSY limit of croaker. Additionally, specific management measures should implement to guarantee croaker and other fisheries from the BoB.

scholarly journals Penentuan Status Pemanfaatan dan Pengelolaan Ikan Tongkol (Auxis rochei) yang Tertangkap di Perairan Bolaang-Mongondow Selatan dan Bolaang-Mongondow Timur Sulawesi Utara

d'CARTESIAN ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 1
Author(s):  
Ladi Beatriex Deeng ◽  
Hanny A H Komalig ◽  
John S Kekenusa
Keyword(s):  
Maximum Sustainable Yield ◽  
Production Model ◽  
Model Data ◽  
Biological Resource ◽  
Surplus Production ◽  
North Sulawesi ◽  
Surplus Production Model ◽  
The Status ◽  
Level Of Effort

LADI BEATRIEX DEENG. Determination of Utilization and Management Status of Bonito (Auxis Rochei) Caught in South Bolaang-Mongondow and East Bolaang-Mongondow Waters of North Sulawesi. Supervised by Mr. JOHN S. KEKENUSA as main supervisor, and Mr. HANNY A. H. KOMALIG as co-supervisor.Bonito (Auxis rochei), needs to be managed properly because even though it is a renewable biological resource, it can experience overfishing, depletion or extinction. One way to approach the management of fish resources is by modeling. The analysis was carried out aiming to determine the status of utilization and management of bonito and maximum sustainable yield (MSY) using the Surplus Production Model. Data on catching and efforts to catch bonito is collected from the Marine and Fisheries Service of South Bolaang-Mongondow Regency and East Bolaang-Mongondow of North Sulawesi. The surplus production model that can be used to determine the catch of bonito is the Schaefer model. The maximum sustainable catch of bonito is 869.556 tons per year, obtained at the level of catching effort of 933 trips. For 2017 the level of utilization is 64.95 % so that production can still be increased, with a level of effort of 73.74 % indicating the level of effort that is not optimal and can still be increased. Keywords : Bonito, Surplus Production Model, South Bolaang-Mongondow and   East Bolaang-Mongondow Regency

scholarly journals Comment on “Impacts of historical warming on marine fisheries production”

Science ◽  
2019 ◽  
Vol 365 (6454) ◽  
pp. eaax5721 ◽  
Author(s):  
Cody Szuwalski
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Maximum Sustainable Yield ◽  
Structured Data ◽  
Sea Surface ◽  
Sustainable Yield ◽  
Surplus Production ◽  
Production Models ◽  
Fitting Production ◽  
Age Structured

Free et al. (Reports, 1 March 2019, p. 979) linked sea surface temperature (SST) to surplus production and estimated a 4% decline in maximum sustainable yield (MSY) since 1930. Changes in MSY are expected when fitting production models to age-structured data, so attributing observed changes to SST is problematic. Analyses of recruitment (a metric of productivity in the same database) showed increases in global productivity.

Island in the Stream: Oceanography and Fisheries of the Charleston Bump

2001 ◽  
Keyword(s):  
Mortality Rate ◽  
Yellowfin Tuna ◽  
Production Model ◽  
Fishing Mortality ◽  
Target Species ◽  
Surplus Production ◽  
Blue Marlin ◽  
Production Curve ◽  
Age Structured ◽  
Charleston Bump

<em>Abstract.</em>—Atlantic blue marlin are primarily harvested as bycatch in fisheries targeting tunas and swordfish. These target species are managed for maximum sustainable yield (MSY) based largely on guidance from surplus production models that lack age structure. Simulation models were constructed around the life history characteristics of Atlantic blue marlin and yellowfin tuna, one of the target species. Each simulated population was exposed to fishing mortality and the resulting time streams of catches and abundances were used as surplus production model inputs using the computer program ASPIC. The slopes of the stock-recruitment curves of the simulated populations were adjusted until the ASPIC estimates of the intrinsic growth rates for the simulations were equivalent to the estimates derived for these populations in the last ICCAT stock assessments. The equilibrium curves of production on fishing mortality for the age-structured populations were then compared to the logistic production model fitted by ASPIC. For blue marlin, the underlying production curve shifted to the left, and F<SUB> MSY </SUB>was lower than the value estimated by ASPIC. For yellowfin tuna, the underlying production curve shifted to the right and F<SUB> MSY </SUB>occurred at a higher fishing mortality rate than that estimated by ASPIC. These results suggest that the Atlantic blue marlin stock is more vulnerable to fishing mortality than indicated by the production model fitted in the last assessment. Also, the fishing mortality rate that produces MSY for yellowfin is near the extinction level for blue marlin. This characteristic is likely shared by other highly productive stocks that support the fisheries in which blue marlin are killed as bycatch. These results indicate that fishing target species at MSY may result in continued serious depletions of Atlantic blue marlin unless the catchability can be reduced relative to the catchability of the target species.

Comparative performance of data-poor CMSY and data-moderate SPiCT stock assessment methods when applied to data-rich, real-world stocks

2020 ◽  
Author(s):  
Paul Bouch ◽  
Cóilín Minto ◽  
Dave G Reid
Keyword(s):  
Stock Assessment ◽  
Assessment Methods ◽  
Production Model ◽  
Fishing Mortality ◽  
Comparative Performance ◽  
Fish Stocks ◽  
Surplus Production ◽  
Stock Biomass ◽  
Surplus Production Model ◽  
The Status

Abstract All fish stocks should be managed sustainably, yet for the majority of stocks, data are often limited and different stock assessment methods are required. Two popular and widely used methods are Catch-MSY (CMSY) and Surplus Production Model in Continuous Time (SPiCT). We apply these methods to 17 data-rich stocks and compare the status estimates to the accepted International Council for the Exploration of the Sea (ICES) age-based assessments. Comparison statistics and receiver operator analysis showed that both methods often differed considerably from the ICES assessment, with CMSY showing a tendency to overestimate relative fishing mortality and underestimate relative stock biomass, whilst SPiCT showed the opposite. CMSY assessments were poor when the default depletion prior ranges differed from the ICES assessments, particularly towards the end of the time series, where some stocks showed signs of recovery. SPiCT assessments showed better correlation with the ICES assessment but often failed to correctly estimate the scale of either F/FMSY of B/BMSY, with the indices lacking the contrast to be informative about catchability and either the intrinsic growth rate or carrying capacity. Results highlight the importance of understanding model tendencies relative to data-rich approaches and warrant caution when adopting these models.

Are Age-Structured Models Appropriate for Catch-Effort Data?

1985 ◽  
Vol 42 (6) ◽  
pp. 1066-1072 ◽  
Author(s):  
Donald Ludwig ◽  
Carl J. Walters
Keyword(s):  
Simulated Data ◽  
Fishing Effort ◽  
Production Model ◽  
Model Structure ◽  
Catch Per Unit Effort ◽  
Unit Effort ◽  
Production Models ◽  
Stock Assessments ◽  
Age Structured ◽  
Age Structured Model

Simulated data have been used to evaluate the performance of schemes for estimating optimum fishing effort using a simple stock-production model and R. B. Deriso's age-structured model Even when the data are generated using Deriso's model, the simpler production model generally gives as good or better estimates for the optimal effort. The only exception to this result is when data are provided with unrealistically large contrasts in effort and catch per unit effort over time. The implication of these findings is that simple production models should often be used in stock assessments based on catch/effort data, even when more realistic and structurally correct models are available to the analyst; the best choice depends on how much contrast has occurred in the historical effort and catch per unit effort data, rather than on prior knowledge about which model structure is biologically more realistic.

Adaptive Probing Strategies for Age-Structured Fish Stocks

1983 ◽  
Vol 40 (5) ◽  
pp. 559-569 ◽  
Author(s):  
D. Ludwig ◽  
R. Hilborn
Keyword(s):  
Management System ◽  
Optimal Size ◽  
Fishing Mortality ◽  
Fish Stocks ◽  
Surplus Production ◽  
Production Models ◽  
Productive Potential ◽  
Adaptive Probing ◽  
Age Structured ◽  
Stock Abundance

This paper examines methods of preventing a stock of fish from being held far below its optimal size. Such sustained overexploitation could arise because the model used to manage the stock poorly represented the stock dynamics, because there are significant errors in the estimates of stock abundance, or because there is insufficient contrast in catch and fishing mortality to generate reliable estimates of the productive potential of the stock. We develop a method to correct for biases due to errors in estimates of abundance and show that this correction does improve estimates of productivity, but not sufficiently to enable a manager to recognize the presence of overexploitation. We demonstrate that the management system must generate significant contrast in catch and effort, and once the contrast is generated the managers can easily find near optimal abundance of the stock. With reasonable levels of contrast even very simple surplus production models will perform well when managing complex age-structured fish stocks.

Equilibrium Yields and Yield Isopleths from a General Age-Structured Model of Harvested Populations

1985 ◽  
Vol 42 (11) ◽  
pp. 1766-1771 ◽  
Author(s):  
Timothy A. Lawson ◽  
Ray Hilborn
Keyword(s):  
Structured Model ◽  
Surplus Production ◽  
Pacific Halibut ◽  
Production Models ◽  
The Pacific ◽  
Hippoglossus Stenolepis ◽  
Equilibrium Yield ◽  
Stock Recruitment ◽  
Age Structured ◽  
Age Structured Model

The equilibrium properties of an age-structured model that includes any arbitrary age-specific weights, vulnerabilities, fecundities, and natural mortality rates, combined with stock–recruitment relationships, are derived. The numbers, biomass, and catch at each age can be calculated quite simply. These relationships can be used to construct yield-isopleth diagrams, or to plot equilibrium yield and biomass against harvest intensity. We used the results to compute yield isopleths for the Pacific halibut (Hippoglossus stenolepis) fishery. The analysis can also include a fishing season of any specified length. Relationships are given to translate the aggregate properties of the age-structured models into several alternative surplus production models.

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