scholarly journals Influence of fleet renewal and trawl development on landings per unit effort of the Danish northern shrimp (Pandalus borealis) fishery

2010 ◽  
Vol 68 (1) ◽  
pp. 26-31 ◽  
Author(s):  
Ole Ritzau Eigaard ◽  
Sten Munch-Petersen
Keyword(s):  
Time Series ◽  
Pandalus Borealis ◽  
Northern Shrimp ◽  
Unit Effort ◽  
Generalized Linear Modelling ◽  
Stock Assessments ◽  
Order Books ◽  
The Relationship ◽  
Logbook Data ◽  
Engine Power

Abstract Eigaard, O. R., and Munch-Petersen, S. 2011. Influence of fleet renewal and trawl development on landings per unit effort of the Danish northern shrimp (Pandalus borealis) fishery. – ICES Journal of Marine Science, 68: 26–31. Recent stock assessments of the Pandalus stock in the Skagerrak (ICES Division IIIa) and the Norwegian Deep (Division IVa east) have relied largely on a time-series of landings per unit effort (lpue) calculated from Danish logbook data. Because of fleet renewal and trawl-size changes, the relationship between nominal effort data as recorded in logbooks (days fishing) and effective effort is likely to have changed, so to standardize the nominal lpue time-series, trawl-size development has been taken into account using generalized linear modelling. As logbooks do not provide trawl-size information, this standardization was made possible by retrieving technical trawl and vessel data from industry order books. These data demonstrated an approximately linear relationship between vessel engine power and Pandalus trawl size, so validated the use of vessel horsepower from the logbooks as a proxy for an unknown trawl size. Standardized lpue time-series for the past 20 years indicated a lesser increase in stock size than nominal lpue, the modelling results demonstrating that vessel lpue increased by 9.5% with each 100 hp of engine power.

Influence of decreased biomass on the ogive of sex change of northern shrimp (Pandalus borealis)

2017 ◽  
Vol 75 (3) ◽  
pp. 1054-1062 ◽  
Author(s):  
Ingibjörg G Jónsdóttir ◽  
Gudrún G Thórarinsdóttir ◽  
Jónas P Jonasson
Keyword(s):  
Time Series ◽  
Change Process ◽  
Sex Change ◽  
Test Case ◽  
Pandalus Borealis ◽  
The Third ◽  
Northern Shrimp ◽  
Stock Biomass ◽  
Low Levels ◽  
Lower Size

Abstract Northern shrimp (Pandalus borealis) are protandrous hermaphrodites that reproduce first as males, go through a transition phase and transform to females, and then spawn as such for the rest of their lives. No clear consensus exists as to which factors influence the activation of the sex change process, but one possible factor is population density. Here, we investigate whether changes in stock size can influence the ogive of sex change, and use a 26-year time series (i.e. 1990–2015) of survey data on shrimp biomass from three different stocks in Iceland as a test case. Two of the stocks experienced periods of high biomass during the 1990 s, with a pronounced and prolonged depletion observed after 2000. In contrast, stock biomass of the third stock decreased only slightly during the time series. We found that the ogives of sex change of the two stocks where the biomass decreased to very low levels have changed significantly, and that shrimp now change sex at a lower size compared to earlier. Furthermore, Lmax has decreased significantly.

scholarly journals Modeling of Lake Malombe Annual Fish Landings and Catch per Unit Effort (CPUE)

Forecasting ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 39-55
Author(s):  
Rodgers Makwinja ◽  
Seyoum Mengistou ◽  
Emmanuel Kaunda ◽  
Tena Alemiew ◽  
Titus Bandulo Phiri ◽  
...  
Keyword(s):  
Time Series ◽  
Information Criterion ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Efficiency Coefficient ◽  
Arima Models ◽  
Catch Per Unit Effort ◽  
Annual Fish ◽  
Unit Effort ◽  
The Mean

Forecasting, using time series data, has become the most relevant and effective tool for fisheries stock assessment. Autoregressive integrated moving average (ARIMA) modeling has been commonly used to predict the general trend for fish landings with increased reliability and precision. In this paper, ARIMA models were applied to predict Lake Malombe annual fish landings and catch per unit effort (CPUE). The annual fish landings and CPUE trends were first observed and both were non-stationary. The first-order differencing was applied to transform the non-stationary data into stationary. Autocorrelation functions (AC), partial autocorrelation function (PAC), Akaike information criterion (AIC), Bayesian information criterion (BIC), square root of the mean square error (RMSE), the mean absolute error (MAE), percentage standard error of prediction (SEP), average relative variance (ARV), Gaussian maximum likelihood estimation (GMLE) algorithm, efficiency coefficient (E2), coefficient of determination (R2), and persistent index (PI) were estimated, which led to the identification and construction of ARIMA models, suitable in explaining the time series and forecasting. According to the measures of forecasting accuracy, the best forecasting models for fish landings and CPUE were ARIMA (0,1,1) and ARIMA (0,1,0). These models had the lowest values AIC, BIC, RMSE, MAE, SEP, ARV. The models further displayed the highest values of GMLE, PI, R2, and E2. The “auto. arima ()” command in R version 3.6.3 further displayed ARIMA (0,1,1) and ARIMA (0,1,0) as the best. The selected models satisfactorily forecasted the fish landings of 2725.243 metric tons and CPUE of 0.097 kg/h by 2024.

scholarly journals Does a Manager Respond to a Going-Concern Audit Opinion with an Asymmetry in Gain and Loss?

2021 ◽  
Vol 13 (8) ◽  
pp. 4425
Author(s):  
Taewoo Kim
Keyword(s):  
Time Series ◽  
Accounting Conservatism ◽  
Timely Manner ◽  
Audit Opinion ◽  
Going Concern ◽  
Asymmetric Timeliness ◽  
Gain And Loss ◽  
Audit Opinions ◽  
The Relationship

In this paper, I investigate the relationship between previous going-concern audit opinions and subsequent asymmetric timeliness in accounting. Using the time-series and price-based models and conservatism proxy, I find that firms with going-concern audit opinions subsequently report losses in a more timely manner than firms that did not receive going-concern audit opinions. Furthermore, I also find that firms exiting going-concern audit opinions are more likely to report losses rather than gains in a timely manner, compared to firms non-exiting from going-concern opinions. This study extends the prior research by exploring the association between going-concern opinions and accounting conservatism from the perspective of client firms—that is, how firms behave strategically and conservatively to bypass going-concern opinions, once the firms had received previous going-concern opinions.

scholarly journals Comparative Time Series Analysis of Perceptual Responses to Electroacoustic Music

2012 ◽  
Vol 29 (4) ◽  
pp. 359-375 ◽  
Author(s):  
Freya Bailes ◽  
Roger T. Dean
Keyword(s):  
Time Series ◽  
Sound Intensity ◽  
Electroacoustic Music ◽  
Affective Content ◽  
Musical Expertise ◽  
Perceived Change ◽  
Time Series Analyses ◽  
Time Perceptions ◽  
The Relationship ◽  
Acoustic Measure

this study investigates the relationship between acoustic patterns in contemporary electroacoustic compositions, and listeners' real-time perceptions of their structure and affective content. Thirty-two participants varying in musical expertise (nonmusicians, classical musicians, expert computer musicians) continuously rated the affect (arousal and valence) and structure (change in sound) they perceived in four compositions of approximately three minutes duration. Time series analyses tested the hypotheses that sound intensity influences listener perceptions of structure and arousal, and spectral flatness influences perceptions of structure and valence. Results suggest that intensity strongly influences perceived change in sound, and to a lesser extent listener perceptions of arousal. Spectral flatness measures were only weakly related to listener perceptions, and valence was not strongly shaped by either acoustic measure. Differences in response by composition and musical expertise suggest that, particularly with respect to the perception of valence, individual experience (familiarity and liking), and meaningful sound associations mediate perception.

scholarly journals Relationship between daily suicide counts and temperature in England and Wales

2007 ◽  
Vol 191 (2) ◽  
pp. 106-112 ◽  
Author(s):  
Lisa A. Page ◽  
Shakoor Hajat ◽  
R. Sari Kovats
Keyword(s):  
Time Series ◽  
Seasonal Fluctuation ◽  
Daily Temperature ◽  
Short Term ◽  
Time Series Regression ◽  
England And Wales ◽  
Increased Risk ◽  
Hot Weather ◽  
The Impact ◽  
The Relationship

BackgroundSeasonal fluctuation in suicide has been observed in many populations. High temperature may contribute to this, but the effect of short-term fluctuations in temperature on suicide rates has not been studied.AimsTo assess the relationship between daily temperature and daily suicide counts in England and Wales between 1 January 1993 and 31 December 2003 and to establish whether heatwaves are associated with increased mortality from suicide.MethodTime-series regression analysis was used to explore and quantify the relationship between daily suicide counts and daily temperature. The impact of two heatwaves on suicide was estimated.ResultsNo spring or summer peak in suicide was found. Above 18 °, each 1 ° increase in mean temperature was associated with a 3.8 and 5.0% rise in suicide and violent suicide respectively. Suicide increased by 46.9% during the 1995 heatwave, whereas no change was seen during the 2003 heat wave.ConclusionsThere is increased risk of suicide during hot weather.

TIME SERIES MODELLING OF EPIDEMICS: LEADING INDICATORS, CONTROL GROUPS AND POLICY ASSESSMENT

2021 ◽  
Vol 257 ◽  
pp. 83-100
Author(s):  
Andrew Harvey
Keyword(s):  
Time Series ◽  
Data Science ◽  
Leading Indicators ◽  
Control Groups ◽  
Balanced Growth ◽  
Time Series Modelling ◽  
Key Variables ◽  
The Uk ◽  
The Relationship

This article shows how new time series models can be used to track the progress of an epidemic, forecast key variables and evaluate the effects of policies. The univariate framework of Harvey and Kattuman (2020, Harvard Data Science Review, Special Issue 1—COVID-19, https://hdsr.mitpress.mit.edu/pub/ozgjx0yn) is extended to model the relationship between two or more series and the role of common trends is discussed. Data on daily deaths from COVID-19 in Italy and the UK provides an example of leading indicators when there is a balanced growth. When growth is not balanced, the model can be extended by including a non-stationary component in one of the series. The viability of this model is investigated by examining the relationship between new cases and deaths in the Florida second wave of summer 2020. The balanced growth framework is then used as the basis for policy evaluation by showing how some variables can serve as control groups for a target variable. This approach is used to investigate the consequences of Sweden’s soft lockdown coronavirus policy in the spring of 2020.

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