scholarly journals An application of the Bayesian approach to stock assessment model uncertainty

2001 ◽  
Vol 58 (3) ◽  
pp. 648-656 ◽  
Author(s):  
T Hammond
Keyword(s):  
Bayesian Approach ◽  
Model Uncertainty ◽  
Stock Assessment ◽  
Assessment Model ◽  
The Bayesian Approach

scholarly journals Can Cattle Basis Forecasts Be Improved? A Bayesian Model Averaging Approach

2019 ◽  
Vol 51 (02) ◽  
pp. 249-266
Author(s):  
Nicholas D. Payne ◽  
Berna Karali ◽  
Jeffrey H. Dorfman
Keyword(s):  
Bayesian Approach ◽  
Model Uncertainty ◽  
Bayesian Model Averaging ◽  
Model Performance ◽  
Model Averaging ◽  
Forecasting Model ◽  
Forecast Errors ◽  
Forecast Horizon ◽  
Combining Forecasts ◽  
The Bayesian Approach

AbstractBasis forecasting is important for producers and consumers of agricultural commodities in their risk management decisions. However, the best performing forecasting model found in previous studies varies substantially. Given this inconsistency, we take a Bayesian approach, which addresses model uncertainty by combining forecasts from different models. Results show model performance differs by location and forecast horizon, but the forecast from the Bayesian approach often performs favorably. In some cases, however, the simple moving averages have lower forecast errors. Besides the nearby basis, we also examine basis in a specific month and find that regression-based models outperform others in longer horizons.

scholarly journals Comparing Bayesian and traditional end-member mixing approaches for hydrograph separation in a glacierized basin

2020 ◽  
Vol 24 (6) ◽  
pp. 3289-3309
Author(s):  
Zhihua He ◽  
Katy Unger-Shayesteh ◽  
Sergiy Vorogushyn ◽  
Stephan M. Weise ◽  
Doris Duethmann ◽  
...  
Keyword(s):  
Bayesian Approach ◽  
Model Uncertainty ◽  
Cold Season ◽  
Spatiotemporal Variability ◽  
Water Sampling ◽  
Hydrograph Separation ◽  
Total Runoff ◽  
Central Asian ◽  
Insight Into ◽  
The Bayesian Approach

Abstract. Tracer data have been successfully used for hydrograph separation in glacierized basins. However, in these basins uncertainties of the hydrograph separation are large and are caused by the spatiotemporal variability in the tracer signatures of water sources, the uncertainty of water sampling, and the mixing model uncertainty. In this study, we used electrical conductivity (EC) measurements and two isotope signatures (δ18O and δ2H) to label the runoff components, including groundwater, snow and glacier meltwater, and rainfall, in a Central Asian glacierized basin. The contributions of runoff components (CRCs) to the total runoff and the corresponding uncertainty were quantified by two mixing approaches, namely a traditional end-member mixing approach (abbreviated as EMMA) and a Bayesian end-member mixing approach. The performance of the two mixing approaches was compared in three seasons that are distinguished as the cold season, snowmelt season, and glacier melt season. The results show the following points. (1) The Bayesian approach generally estimated smaller uncertainty ranges for the CRC when compared to the EMMA. (2) The Bayesian approach tended to be less sensitive to the sampling uncertainties of meltwater than the EMMA. (3) Ignoring the model uncertainty caused by the isotope fractionation likely led to an overestimated rainfall contribution and an underestimated meltwater share in the melt seasons. Our study provides the first comparison of the two end-member mixing approaches for hydrograph separation in glacierized basins and gives insight into the application of tracer-based mixing approaches in similar basins.

scholarly journals Comparing Bayesian and traditional end-member mixing approaches for hydrograph separation in a glacierized basin

2019 ◽  
Author(s):  
Zhihua He ◽  
Katy Unger-Shayesteh ◽  
Sergiy Vorogushyn ◽  
Stephan M. Weise ◽  
Doris Duethmann ◽  
...  
Keyword(s):  
Bayesian Approach ◽  
Model Uncertainty ◽  
Temporal Variability ◽  
Isotope Fractionation ◽  
Cold Season ◽  
Water Sampling ◽  
Hydrograph Separation ◽  
Total Runoff ◽  
Spatio Temporal ◽  
The Bayesian Approach

Abstract. Water tracer data have been successfully used for hydrograph separation in glacierized basins. However, uncertainties in the hydrograph separation are large in these basins, caused by the spatio-temporal variability in the tracer signatures of water sources, the uncertainty of water sampling and the mixing model uncertainty. In this study, we used electrical conductivity (EC) measurements and two isotope signatures (δ18O and δ2H) to label the runoff components, including groundwater, snow and glacier meltwater, and rainfall, in a Central Asia glacierized basin. The contributions of runoff components (CRC) to the total runoff, as well as the corresponding uncertainty, were quantified by two mixing approaches: a traditional end-member mixing approach (TEMMA) and a Bayesian end-member mixing approach. The performance of the two mixing approaches were compared in three seasons, distinguished as cold season, snowmelt season and glacier melt season. Results show that: 1) The Bayesian approach generally estimated smaller uncertainty ranges for the CRC compared to the TEMMA. 2) The Bayesian approach tended to be less sensitive to the sampling uncertainties of meltwater than the TEMMA. 3) Ignoring the model uncertainty caused by the isotope fractionation likely leaded to an overestimated rainfall contribution and an underestimated meltwater share in the melt seasons. Our study provides the first comparison of the two end-member mixing approaches for hydrograph separation in glacierized basins, and gives insights for the application of tracer-based mixing approaches for similar basins.

scholarly journals The Bayesian Approach and the Results of the ISAR-REACT 5 Trial

2021 ◽  
Vol 14 (2) ◽  
pp. 231-232
Author(s):  
Adnan Kastrati ◽  
Alexander Hapfelmeier
Keyword(s):  
Bayesian Approach ◽  
The Bayesian Approach

scholarly journals Stock assessment and projections incorporating discard estimates in some years: an application to the hake stock in ICES Divisions VIIIc and IXa

2010 ◽  
Vol 67 (6) ◽  
pp. 1185-1197 ◽  
Author(s):  
C. Fernández ◽  
S. Cerviño ◽  
N. Pérez ◽  
E. Jardim
Keyword(s):  
Time Series ◽  
Stock Assessment ◽  
Reference Points ◽  
Assessment Model ◽  
Marine Science ◽  
Fishing Mortality ◽  
Change Over Time ◽  
Age Structured ◽  
Available Information ◽  
Over Time

Abstract Fernández, C., Cerviño, S., Pérez, N., and Jardim, E. 2010. Stock assessment and projections incorporating discard estimates in some years: an application to the hake stock in ICES Divisions VIIIc and IXa. – ICES Journal of Marine Science, 67: 1185–1197. A Bayesian age-structured stock assessment model is developed to take into account available information on discards and to handle gaps in the time-series of discard estimates. The model incorporates mortality attributable to discarding, and appropriate assumptions about how this mortality may change over time are made. The result is a stock assessment that accounts for information on discards while, at the same time, producing a complete time-series of discard estimates. The method is applied to the hake stock in ICES Divisions VIIIc and IXa, for which the available data indicate that some 60% of the individuals caught are discarded. The stock is fished by Spain and Portugal, and for each country, there are discard estimates for recent years only. Moreover, the years for which Portuguese estimates are available are only a subset of those with Spanish estimates. Two runs of the model are performed; one assuming zero discards and another incorporating discards. When discards are incorporated, estimated recruitment and fishing mortality for young (discarded) ages increase, resulting in lower values of the biological reference points Fmax and F0.1 and, generally, more optimistic future stock trajectories under F-reduction scenarios.

scholarly journals Correcting density-dependent effects in abundance estimates from bottom-trawl surveys

2014 ◽  
Vol 71 (5) ◽  
pp. 1107-1116 ◽  
Author(s):  
Stan Kotwicki ◽  
James N. Ianelli ◽  
André E. Punt
Keyword(s):  
Stock Assessment ◽  
Dead Zone ◽  
Walleye Pollock ◽  
Assessment Model ◽  
Bottom Trawl ◽  
Trawl Survey ◽  
Negative Consequences ◽  
Catch Per Unit Effort ◽  
Density Dependent ◽  
Index Of Abundance

Abstract Indices of abundance are important for estimating population trends in stock assessment and ideally should be based on fishery-independent surveys to avoid problems associated with the hyperstability of the commercial catch per unit effort (cpue) data. However, recent studies indicate that the efficiency of the survey bottom trawl (BT) for some species can be density-dependent, which could affect the reliability of survey-derived indices of abundance. A function qe∼f(u), where qe is the BT efficiency and u the catch rate, was derived using experimentally derived acoustic dead-zone correction and BT efficiency parameters obtained from combining a subset of BT catch data with synchronously collected acoustic data from walleye pollock (Theragra chalcogramma) in the eastern Bering Sea (EBS). We found that qe decreased with increasing BT catches resulting in hyperstability of the index of abundance derived from BT survey. Density-dependent qe resulted in spatially and temporarily variable bias in survey cpue and biased population age structure derived from survey data. We used the relationship qe∼f(u) to correct the EBS trawl survey index of abundance for density-dependence. We also obtained a variance–covariance matrix for a new index that accounted for sampling variability and the uncertainty associated with the qe. We found that incorporating estimates of the new index of abundance changed outputs from the walleye pollock stock assessment model. Although changes were minor, we advocate incorporating estimates of density-dependent qe into the walleye pollock stock assessment as a precautionary measure that should be undertaken to avoid negative consequences of the density-dependent qe.

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