An ecosystem-based hypothesis for climatic effects on surplus production in California sardine (Sardinops sagax) and environmentally dependent surplus production models

2005 ◽  
Vol 62 (8) ◽  
pp. 1782-1796 ◽  
Author(s):  
Larry D Jacobson ◽  
Steven J Bograd ◽  
Richard H Parrish ◽  
Roy Mendelssohn ◽  
Franklin B Schwing
Keyword(s):  
Environmental Data ◽  
Production Model ◽  
Climatic Effects ◽  
High Productivity ◽  
Surplus Production ◽  
Habitat Area ◽  
California Sardine ◽  
Maximum Sustained Yield ◽  
Sustained Yield ◽  
Sardinops Sagax

We used environmentally dependent surplus production (EDSP) models to test hypotheses linking changes in habitat area, carrying capacity and surplus production in California sardine (Sardinops sagax). Habitat area (with mean sea surface temperatures of 14–16 °C) was centered off Oregon, Washington, and British Columbia during July–December and off southern and central California during January–June. Habitat area increased during El Niño and decreased during La Niña events. EDSP models fit better than a conventional Fox surplus production model without environmental data. Our estimated fishing mortality rate at maximum sustained yield FMSY = 0.099·year–1 was consistent with other estimates. Maximum sustained yield (MSY) and stock biomass for MSY (BMSY) depend on habitat area and environmental conditions. Negative surplus production occurred when biomass was high and habitat area declined abruptly. Managers might monitor habitat area to anticipate changes in the California sardine stock and changes in the California Current ecosystem. Periods of high productivity appear easier to identify than periods of negative productivity. Models that incorporate environmental effects on both recruitment and survival and mortality of adult fish appear useful in studying climatic effects on fishery surplus production.

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 Population changes in rattail species on the Chatham Rise

2021 ◽  
Author(s):  
◽  
Kathleen Large
Keyword(s):  
Maximum Likelihood ◽  
Stock Assessment ◽  
Production Model ◽  
Likelihood Method ◽  
Model Parameters ◽  
Important Species ◽  
Surplus Production ◽  
Surplus Production Model ◽  
Abundance Indices ◽  
The Impact

<p>The aim of this project was to conduct a stock assessment to determine the population dynamic characteristics of rattail species taken as bycatch in the hoki, hake and ling fishery on the Chatham Rise. No quantitative assessment of the current size of rattail populations , and how these may have changed over time, has been carried out before. There is interest in the need to quantify the impact of commercial fishing on the rattail populations, as rattails (Macrouridae family) are considered to be an ecologically important species complex in the deep ocean, and there may be the potential for the development of a commercial fishery based on their value as processed fishmeal. The minimum data required for a stock assessment are an abundance index and a catch history. Abundance indices are available for over 20 species of rattail produced from scientific surveys conducted annually on the Chatham Rise since 1992. Catch histories for individual rattail species in the same area are not available. A method was developed to reconstruct commercial catches of rattails from commercial effort data and survey catch and effort data. A surplus production model was fitted to the reconstructed catch data and survey abundance indices, using maximum likelihood and Bayesian methods to estimate model parameters and uncertainty. A surplus production model has two components: an observation model for abundance indices and a process model for population dynamics. Maximum likelihood estimation was applied to a model that specified errors for the observations only, and this produced estimates that had wide confidence intervals. A Bayesian approach was then taken to fit a statespace version of the model that incorporates errors associated with the observation and process models. While the Bayesian method produced more plausible parameter estimates (in comparison to the maximum likelihood method) and parameter uncertainty was reduced, our analysis indicated the posterior estimates were highly sensitive to the specification of different priors. There may be several reasons for these results, including: the small number of observations, lack of contrast in the data and mis-specification of the model. Meaningful estimates of the absolute size of rattail populations are not possible with these results, where estimates can vary by orders of magnitude depending on prior specification. This implies that more work needs to be done to develop more effective methods that can be used to help inform decisions regarding the management of these fish populations. Improving data collection, investigating informative priors and extending/respecifying the model are considered worthwhile avenues of future work to improve stock assessments of rattails.</p>

scholarly journals DEPLESI SUMBER DAYA IKAN TUNA DAN CAKALANG DI INDONESIA

2019 ◽  
Vol 13 (2) ◽  
pp. 167
Author(s):  
Maulana Firdaus ◽  
Akhmad Fauzi ◽  
A Faroby Falatehan
Keyword(s):  
Resource Depletion ◽  
Production Model ◽  
Economic Potential ◽  
Average Volume ◽  
Negative Numbers ◽  
Average Value ◽  
Surplus Production ◽  
Fish Resources ◽  
Surplus Production Model ◽  
The World

ABSTRAKTuna dan cakalang memiliki potensi ekonomi yang besar di Indonesia. Beberapa penelitian menunjukkan bahwa kedua komoditas ini telah menunjukkan gejala over fishing di dunia, termasuk Indonesia. Penelitian ini bertujuan untuk mengestimasi seberapa besar deplesi ikan tuna dan cakalang di Indonesia. Deplesi sumber daya dihitung melalui perkiraan stok dan tingkat hasil lestari dengan menggunakan model produksi surplus dan estimasi parameter menggunakan metoda Clarke Yoshimoto Pooley (CYP). Nilai deplesi diperoleh dari perkalian volume deplesi dengan unit rent. Hasil penelitian menunjukkan bahwa volume rata-rata deplesi sumber daya ikan tuna dan cakalang pada periode 1992-2015 adalah (-) 2.828 ton per tahun. Rata-rata nilai deplesi sumber daya ikan tuna dan cakalang menunjukkan angka negatif, yaitu (-) Rp131,89 miliar per tahun. Nilai negatif ini menunjukkan bahwa selama periode 1992-2015, stok sumber daya ikan tuna dan cakalang mengalami penurunan sebesar 2.828 ton per tahun dengan nilai potensi kerugian atau kehilangan akibat penurunan stok yang mencapai Rp131,89 miliar per tahun.Title: Tuna And Skipjack Resources Depletion In IndonesiaABSTRACTTuna and Skipjack has a great economic potential in Indonesia. Several studies have shown that these commodities have symptomed of over-fishing in the world, including Indonesia. This study aims to estimate the extent of tuna and skipjack depletion in Indonesia. Resource depletion is calculated through stock estimates and sustainable yield levels using surplus production model and parameter estimation of Clark Yoshimoto Pooley (CYP) method. Depletion value is obtained from multiplication of depletion volume with unit rent. Results of the study showed that the average volume of depletion of tuna and skipjack resources in the period 1992-2015 was (-) 2,828 tons per year. The average value of tuna and skipjack resource depletion showed negative numbers, ie (-) IDR 131.89 billion per year. This negative value indicates that during the period 1992-2015, the stock of tuna and skipjack fish resources decreased by 2.828 tons per year with the potential value of loss or loss due to a decrease in stock which reached IDR131,89 billion per year. 

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

Temporal and spatial considerations in data-model comparisons involving transient paleoclimatic simulations

2021 ◽  
Author(s):  
Patrick Bartlein ◽  
Sandy Harrison
Keyword(s):  
Time Series ◽  
Best Practices ◽  
Data Model ◽  
Environmental Data ◽  
Climatic Effects ◽  
Data Archiving ◽  
Model Comparisons ◽  
Climate Reconstructions ◽  
Temporal And Spatial ◽  
Further Development

&lt;p&gt;The increasing availability of time-evolving or transient palaeoclimatic simulations makes it imperative to develop &amp;#8220;best-practices&amp;#8221; for comparing simulations with palaeoclimatic observations including both climate reconstructions and environmental data.&amp;#160; There are two sets of considerations, temporal and spatial, that should guide those comparisons.&amp;#160; The chronology of simulations can in some ways be viewed as exact, as determined by the insolation forcing, but data archiving and reporting conventions, such as reporting summaries that use the modern calendar (that leads to the long-recognized palaeo-calendar effect) can, if ignored, lead to &amp;#8220;built-in&amp;#8221; temporal offsets of thousands of years in such features as temperature or precipitation maxima or minima.&amp;#160; Likewise, there are age uncertainties in time series of palaeoclimatic data that are often ignored, despite the fact that these are large during &amp;#8220;climatically interesting times&amp;#8221; such as the Younger Dryas chronozone.&amp;#160; Similarly, although model resolution is increasing, there is still a mismatch in topography (and its climatic effects) between a model and the &amp;#8220;real world&amp;#8221; sensed by the palaeoclimatic data sources.&amp;#160;&lt;/p&gt;&lt;p&gt;There are existing approaches for dealing with some of these issues, such as calendar-adjustment programs, Monte-Carlo approaches for describing age uncertainties in palaeoclimate time series, or clustering approaches for objectively defining appropriate regions for the calculation of area averages, but there is certainly room for further development.&amp;#160; This abstract is intended to serve as platform for discussion of some of best practices for data-model comparisons in transient mode.&lt;/p&gt;

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