scholarly journals Testing different methods of incorporating climate data into the assessment of US West Coast sablefish

2009 ◽  
Vol 66 (7) ◽  
pp. 1605-1613 ◽  
Author(s):  
Michael J. Schirripa ◽  
C. Phillip Goodyear ◽  
Richard M. Methot
Keyword(s):  
West Coast ◽  
Environmental Variability ◽  
Stock Assessment ◽  
Environmental Variable ◽  
Environmental Data ◽  
Observation Error ◽  
Climate Data ◽  
Simulation Techniques ◽  
Stock Recruitment ◽  
Us West

Abstract Schirripa, M. J., Goodyear, C. P., and Methot, R. M. 2009. Testing different methods of incorporating climate data into the assessment of US West Coast sablefish. – ICES Journal of Marine Science, 66: 1605–1613. The objective of this investigation was to evaluate different methods of including environmental variability directly into stock assessments and to demonstrate how this inclusion affects the estimation of recruitment parameters, stock status, and the conservation benchmarks used to manage a stock. Variations on two methods of incorporating environmental effects were tested. The first method (“model” method) utilizes a structural change in the stock–recruitment function to adjust the annual expected number of recruits by a value, either positive or negative, equal to that year's anomaly in the environmental variable. The second method (“data” method) allows for observation error in the environmental data and uses the time-series as an index to tune the vector of estimates of annual recruitment deviations. Simulation techniques were utilized to produce datasets of known quantities that were subsequently analysed with a widely used stock assessment platform. Under the circumstances simulated in this study, neither method could be said to have performed significantly better than the other in all situations. Because the two approaches handle years of missing data differently, the best approach is dictated by the available data, rather than a more appropriate method.

Detecting environmental regimes in fish stock-recruitment relationships by fuzzy logic

2001 ◽  
Vol 58 (11) ◽  
pp. 2139-2148 ◽  
Author(s):  
D G Chen
Keyword(s):  
Fuzzy Logic ◽  
Environmental Variable ◽  
Clupea Harengus ◽  
Fish Stock ◽  
Environmental Regimes ◽  
Fuzzy Logic Approach ◽  
Stock Recruitment ◽  
Logic Approach ◽  
Traditional Approaches ◽  
The Impact

A fuzzy logic approach is developed to model and test the impact of environmental regimes on fish stock–recruitment relationships. Traditional methods use environmental variables to classify stock–recruitment data into different membership percentiles followed by fitting the stock–recruitment models for each subset. In contrast, the fuzzy logic approach uses a continuous membership function to provide a rational basis for the classification. Thus, parameter estimation is based on a more logically consistent foundation without resorting to subjective partitions. This new approach is applied to herring stock from the west coast of Vancouver Island (Clupea harengus pallasi) using sea surface temperature as the environmental variable and to Pacific halibut stock (Hippoglossus stenolepis) using the Pacific Decadal Oscillation as the environmental variable. From these applications, the herring stock–recruitment relationships were found to vary significantly during different regimes, whereas this was not the case for halibut. However, in both instances, the fuzzy logic approach demonstrated that density-dependent effects differed between regimes. The fuzzy logic model consistently outperformed traditional approaches as measured by several diagnostic criteria. Because fuzzy logic models address uncertainty better than traditional approaches, they have the potential to improve our ability to understand factors influencing stock–recruitment relationships and thereby manage fisheries more effectively.

scholarly journals Quirky patterns in time-series of estimates of recruitment could be artefacts

2014 ◽  
Vol 72 (1) ◽  
pp. 111-116 ◽  
Author(s):  
M. Dickey-Collas ◽  
N. T. Hintzen ◽  
R. D. M. Nash ◽  
P-J. Schön ◽  
M. R. Payne
Keyword(s):  
Time Series ◽  
Stock Assessment ◽  
Meta Analysis ◽  
Reference Points ◽  
Fish Stocks ◽  
Stock Recruitment ◽  
Modelling Assumptions ◽  
Meta Analyses ◽  
Recruitment Model ◽  
Recruitment Time

Abstract The accessibility of databases of global or regional stock assessment outputs is leading to an increase in meta-analysis of the dynamics of fish stocks. In most of these analyses, each of the time-series is generally assumed to be directly comparable. However, the approach to stock assessment employed, and the associated modelling assumptions, can have an important influence on the characteristics of each time-series. We explore this idea by investigating recruitment time-series with three different recruitment parameterizations: a stock–recruitment model, a random-walk time-series model, and non-parametric “free” estimation of recruitment. We show that the recruitment time-series is sensitive to model assumptions and this can impact reference points in management, the perception of variability in recruitment and thus undermine meta-analyses. The assumption of the direct comparability of recruitment time-series in databases is therefore not consistent across or within species and stocks. Caution is therefore required as perhaps the characteristics of the time-series of stock dynamics may be determined by the model used to generate them, rather than underlying ecological phenomena. This is especially true when information about cohort abundance is noisy or lacking.

Subsystem grid attack could darken US west coast

2009 ◽  
Vol 203 (2725) ◽  
pp. 22
Author(s):  
Paul Marks
Keyword(s):  
West Coast ◽  
Us West

scholarly journals Towards a long-term global aerosol optical depth record: applying a consistent aerosol retrieval algorithm to MODIS and VIIRS-observed reflectance

2015 ◽  
Vol 8 (10) ◽  
pp. 4083-4110 ◽  
Author(s):  
R. C. Levy ◽  
L. A. Munchak ◽  
S. Mattoo ◽  
F. Patadia ◽  
L. A. Remer ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Infrared Imaging ◽  
Quantitative Information ◽  
Environmental Data ◽  
Retrieval Algorithm ◽  
Climate Data ◽  
Data Record ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. To answer fundamental questions about aerosols in our changing climate, we must quantify both the current state of aerosols and how they are changing. Although NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) sensors have provided quantitative information about global aerosol optical depth (AOD) for more than a decade, this period is still too short to create an aerosol climate data record (CDR). The Visible Infrared Imaging Radiometer Suite (VIIRS) was launched on the Suomi-NPP satellite in late 2011, with additional copies planned for future satellites. Can the MODIS aerosol data record be continued with VIIRS to create a consistent CDR? When compared to ground-based AERONET data, the VIIRS Environmental Data Record (V_EDR) has similar validation statistics as the MODIS Collection 6 (M_C6) product. However, the V_EDR and M_C6 are offset in regards to global AOD magnitudes, and tend to provide different maps of 0.55 μm AOD and 0.55/0.86 μm-based Ångström Exponent (AE). One reason is that the retrieval algorithms are different. Using the Intermediate File Format (IFF) for both MODIS and VIIRS data, we have tested whether we can apply a single MODIS-like (ML) dark-target algorithm on both sensors that leads to product convergence. Except for catering the radiative transfer and aerosol lookup tables to each sensor's specific wavelength bands, the ML algorithm is the same for both. We run the ML algorithm on both sensors between March 2012 and May 2014, and compare monthly mean AOD time series with each other and with M_C6 and V_EDR products. Focusing on the March–April–May (MAM) 2013 period, we compared additional statistics that include global and gridded 1° × 1° AOD and AE, histograms, sampling frequencies, and collocations with ground-based AERONET. Over land, use of the ML algorithm clearly reduces the differences between the MODIS and VIIRS-based AOD. However, although global offsets are near zero, some regional biases remain, especially in cloud fields and over brighter surface targets. Over ocean, use of the ML algorithm actually increases the offset between VIIRS and MODIS-based AOD (to ~ 0.025), while reducing the differences between AE. We characterize algorithm retrievability through statistics of retrieval fraction. In spite of differences between retrieved AOD magnitudes, the ML algorithm will lead to similar decisions about "whether to retrieve" on each sensor. Finally, we discuss how issues of calibration, as well as instrument spatial resolution may be contributing to the statistics and the ability to create a consistent MODIS → VIIRS aerosol CDR.

scholarly journals Analysis of the effectiveness of face-coverings on the death ratio of COVID-19 using machine learning

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ali Lafzi ◽  
Miad Boodaghi ◽  
Siavash Zamani ◽  
Niyousha Mohammadshafie ◽  
Veeraraghava Raju Hasti
Keyword(s):  
Machine Learning ◽  
West Coast ◽  
Economic Condition ◽  
Preventive Measure ◽  
Accuracy Score ◽  
Machine Learning Classification ◽  
Monthly Average ◽  
The Us ◽  
Recent Outbreak ◽  
Us West

AbstractThe recent outbreak of the COVID-19 led to death of millions of people worldwide. To stave off the spread of the virus, the authorities in the US employed different strategies, including the mask mandate order issued by the states’ governors. In the current work, we defined a parameter called average death ratio as the monthly average of the number of daily deaths to the monthly average number of daily cases. We utilized survey data to quantify people’s abidance by the mask mandate order. Additionally, we implicitly addressed the extent to which people abide by the mask mandate order, which may depend on some parameters such as population, income, and education level. Using different machine learning classification algorithms, we investigated how the decrease or increase in death ratio for the counties in the US West Coast correlates with the input parameters. The results showed that for the majority of counties, the mask mandate order decreased the death ratio, reflecting the effectiveness of such a preventive measure on the West Coast. Additionally, the changes in the death ratio demonstrated a noticeable correlation with the socio-economic condition of each county. Moreover, the results showed a promising classification accuracy score as high as 90%.

scholarly journals The impact of alternative rebuilding strategies to rebuild overfished stocks

2016 ◽  
Vol 73 (9) ◽  
pp. 2190-2207 ◽  
Author(s):  
Chantel R. Wetzel ◽  
André E. Punt ◽  
Keyword(s):  
West Coast ◽  
Life Histories ◽  
Estimation Error ◽  
The United States ◽  
Fish Stocks ◽  
Strategy Evaluation ◽  
The Us ◽  
History Of ◽  
The Impact ◽  
Us West

Abstract Ending overfishing and rebuilding fish stocks to levels that provide for optimum sustainable yield is a concern for fisheries management worldwide. In the United States, fisheries managers are legally mandated to end overfishing and to implement rebuilding plans for fish stocks that fall below minimum stock size thresholds. Rebuilding plans should lead to recovery to target stock sizes within 10 years, except in situations where the life history of the stock or environmental conditions dictate otherwise. Federally managed groundfish species along the US West Coast have diverse life histories where some are able to rebuild quickly from overfished status, while others, specifically rockfish (Sebastes spp.), may require decades for rebuilding. A management strategy evaluation which assumed limited estimation error was conducted to evaluate the performance of alternative strategies for rebuilding overfished stocks for these alternative US West Coast life histories. Generally, the results highlight the trade-off between the reduction of catches during rebuilding vs. the length of rebuilding. The most precautionary rebuilding plans requiring the greatest harvest reduction resulted in higher average catches over the entire projection period compared with strategies that required a longer rebuilding period with less of a reduction in rebuilding catch. Attempting to maintain a 50% probability of rebuilding was the poorest performing rebuilding strategy for all life histories, resulting in a large number of changes to the rebuilding plan, increased frequency of failing to meet rebuilding targets, and higher variation in catch. The rebuilding plans that implemented a higher initial rebuilding probability (≥60%) for determining rebuilding fishing mortality and targets generally resulted in fewer changes to the rebuilding plans and rebuilt by the target rebuilding year, particularly for stocks with the longer rebuilding plans (e.g. rockfishes).

Estimating multifleet catchability coefficients and natural mortality from fishery catch and effort data: comparison of Bayesian state–space and observation error models

2011 ◽  
Vol 68 (7) ◽  
pp. 1171-1181 ◽  
Author(s):  
Shijie Zhou ◽  
André E. Punt ◽  
Roy Deng ◽  
Janet Bishop
Keyword(s):  
State Space ◽  
Stock Assessment ◽  
Observation Error ◽  
Natural Mortality ◽  
Posterior Median ◽  
Median Estimate ◽  
Penaeus Semisulcatus ◽  
Process Error ◽  
Two Parameters ◽  
Delay Difference

Catchability and natural mortality are key quantities in fisheries stock assessment. However, it is difficult to estimate these two parameters simultaneously using only fishery catch and effort data. A Bayesian state–space modified delay–difference model is outlined that can estimate time series of catchability by fleet as well as natural mortality. This model, and three variants thereof, is fitted to data for grooved tiger prawns ( Penaeus semisulcatus ) in Australia’s Northern Prawn Fishery during the period of the year when there is little recruitment. A model that allows for both observation and process error and estimates natural mortality is best, in terms of model selection criteria as well as fit diagnostics. The posterior median estimate for catchability for the primary target fleet ranges from 6.15 × 10−4 to 1.09 × 10−4 during 1980–2007, while the posterior median estimate for catchability for a fleet with P. semisulcatus as its byproduct is about 20% of that for the primary fleet. Fishing efficiency increased at approximately 2% annually during 1980–2007, while the weekly natural mortality is estimated to be 0.053 week–1.

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