Detecting Synchrony of Recruitment using Short, Autocorrelated Time Series

1989 ◽  
Vol 46 (10) ◽  
pp. 1831-1838 ◽  
Author(s):  
Keith R. Thompson ◽  
Fred H. Page
Keyword(s):  
Time Series ◽  
Egg Production ◽  
Gadus Morhua ◽  
Statistical Tests ◽  
Simulated Data ◽  
Melanogrammus Aeglefinus ◽  
Data Sets ◽  
Similar Data ◽  
Environmental Forcing ◽  
Fish Stocks

Synchrony of recruitment to distinct fish stocks is difficult to detect because the available time series are generally short and autocorrelated. The recent introduction of more sophisticated statistical techniques has not been particularly helpful; several contradictory interpretations of similar data sets are discussed in the paper. To help resolve the continuing controversy surrounding the question of synchrony, we review three statistical tests of independence and determine their power using simulated data. The tests are then applied to recruitment data for six cod (Gadus morhua) and three haddock (Melanogrammus aeglefinus) stocks of the northwest Atlantic. Prior to analysis each series was first-differenced to reduce autocorrelation and hence increase statistical reliability in the results. The cod stocks are shown to fluctuate independently of the haddock stocks. There is, however, evidence of synchrony for stocks of the same species; the more widely separated cod stocks have a lower mean correlation [Formula: see text] than the haddock [Formula: see text] but both correlations are significant at the 1% level. The within-species synchrony is not due to fluctuations in our index of egg production and it appears that environmental forcing is probably important.

Benthic Habitats and the Effects of Fishing

2005 ◽  
Keyword(s):  
Gadus Morhua ◽  
Atlantic Cod ◽  
Fish Habitat ◽  
Weather Conditions ◽  
Data Sets ◽  
Fish Stocks ◽  
Habitat Features ◽  
The Irish Sea ◽  
Belfast Lough ◽  
Existing Data

<strong><em>Abstract. </em><strong>Fishers have often complained that standard United Kingdom groundfish survey data do not adequately reflect the grounds targeted by commercial fishers, and hence, scientists tend to make overcautious estimates of fish abundance. Such criticisms are of particular importance if we are to make a creditable attempt to classify potential essential fish habitat (EFH) using existing data from groundfish surveys. Nevertheless, these data sets provide a powerful tool to examine temporal abundance of fish on a large spatial scale. Here, we report a questionnaire-type survey of fishers (2001–2002) that invited them to plot the location of grounds of key importance in the Irish Sea and to comment on key habitat features that might constitute EFH for Atlantic cod <em>Gadus morhua</em>, haddock <em>Melanogrammus aeglefinus</em>, and European whiting <em>Merlangius merlangus</em>. Plotted grounds were cross-checked using records of vessel sightings by fishery protection aircraft (1985–1999). A comparison of the areas of seabed highlighted by fishers and the observations made on groundfish surveys were broadly compatible for all three species of gadoids examined. Both methods indicated important grounds for cod and European whiting off northern Wales, the Ribble estuary, Solway Firth, north of Dublin, and Belfast Lough. The majority of vessel sightings by aircraft did not match the areas plotted by fishers. However, fishing restrictions, adverse weather conditions, and seasonal variation of fish stocks may have forced fishers to operate outside their favored areas on the (few) occasions that they had been recorded by aircraft. Fishers provided biological observations that were consistent among several independent sources (e.g., the occurrence of haddock over brittle star [ophiuroid] beds). We conclude that fishers’ knowledge is a useful supplement to existing data sets that can better focus more detailed EFH studies.

scholarly journals IMPROVED ESTIMATION OF COVARIANCE MATRIX IN HOTELLING’S T2 FOR MICROARRAY DATA

2016 ◽  
Vol 8 (2) ◽  
pp. 26 ◽  
Author(s):  
Suryaefiza Karjanto ◽  
Norazan Mohamed Ramli ◽  
Nor Azura Md Ghaninor Azura Md Ghani
Keyword(s):  
Covariance Matrix ◽  
Microarray Data ◽  
Simulated Data ◽  
Principal Component ◽  
Data Sets ◽  
Similar Data ◽  
Shrinkage Methods ◽  
Differential Gene ◽  
The Relationship ◽  
Simulated Data Sets

<p class="lead">The relationship between genes in gene set analysis in microarray data is analyzed using Hotelling’s <em>T</em><sup>2</sup> but the test cannot be applied when the number of samples is larger than the number of variables which is uncommon in the microarray. Thus, in this study, we proposed shrinkage approaches to estimating the covariance matrix in Hotelling’s <em>T<sup>2</sup></em> particularly to cater high dimensionality problem in microarray data. Three shrinkage covariance methods were proposed in this study and are referred as Shrink A, Shrink B and Shrink C. The analysis of the three proposed shrinkage methods was compared with the Regularized Covariance Matrix Approach and Kong’s Principal Component Analysis. The performances of the proposed methods were assessed using several cases of simulated data sets. In many cases, the Shrink A method performed the best, followed by the Shrink C and RCMAT methods. In contrast, both the Shrink B and KPCA methods showed relatively poor results. The study contributes to an establishment of modified multivariate approach to differential gene expression analysis and expected to be applied in other areas with similar data characteristics.</p>

Pronounced long-term juvenation in the spawning stock of Arcto-Norwegian cod (Gadus morhua) and possible consequences for recruitment

2008 ◽  
Vol 65 (3) ◽  
pp. 523-534 ◽  
Author(s):  
Geir Ottersen
Keyword(s):  
Time Series ◽  
Gadus Morhua ◽  
Experimental Studies ◽  
Reproductive Capacity ◽  
Fish Stocks ◽  
Stock Biomass ◽  
Clear Link ◽  
Spawning Stock ◽  
The Mean

The oldest and largest individuals are disappearing from many fish stocks worldwide as a result of overexploitation. This has been suggested to impair recruitment through decreasing the reproductive capacity of the spawners and increasing the mortality rate of the offspring. By using a time series on spawners biomass by age class for Arcto-Norwegian cod (Gadus morhua) from 1913–2004, I have documented pronounced changes in the spawning stock, including a trend towards younger fish, a less diverse distribution across ages, and a declining proportion of repeat spawners. Despite the total spawning stock biomass (SSB) being at similar levels now as in 1933, the mean age in the SSB has declined from 10–12.5 years to 7–8 years during the study period, and the percentage of fish of age 10 or above in the SSB has decreased from ~97% to ~10%. Contrary to earlier theoretical and experimental studies, no clear link between age structure and recruitment was found here. Recruitment to the Arcto-Norwegian cod stock may thus be more robust towards spawner juvenation than expected, possibly because of strong recruitment compensation.

scholarly journals Detecting trend on ecological river status – how to deal with short incomplete bioindicator time series? Methodological and operational issues

2018 ◽  
Vol 379 ◽  
pp. 169-174
Author(s):  
Flavie Cernesson ◽  
Marie-George Tournoud ◽  
Nathalie Lalande
Keyword(s):  
Time Series ◽  
Statistical Tests ◽  
Methodological Issue ◽  
Temporal Trends ◽  
Graphical Analysis ◽  
Point Of View ◽  
Trend Detection ◽  
Data Sets ◽  
Monitoring Networks ◽  
Operational Issues

Abstract. Among the various parameters monitored in river monitoring networks, bioindicators provide very informative data. Analysing time variations in bioindicator data is tricky for water managers because the data sets are often short, irregular, and non-normally distributed. It is then a challenging methodological issue for scientists, as it is in Saône basin (30 000 km2, France) where, between 1998 and 2010, among 812 IBGN (French macroinvertebrate bioindicator) monitoring stations, only 71 time series have got more than 10 data values and were studied here. Combining various analytical tools (three parametric and non-parametric statistical tests plus a graphical analysis), 45 IBGN time series were classified as stationary and 26 as non-stationary (only one of which showing a degradation). Series from sampling stations located within the same hydroecoregion showed similar trends, while river size classes seemed to be non-significant to explain temporal trends. So, from a methodological point of view, combining statistical tests and graphical analysis is a relevant option when striving to improve trend detection. Moreover, it was possible to propose a way to summarise series in order to analyse links between ecological river quality indicators and land use stressors.

Effects of condition on fecundity and total egg production of eastern Scotian Shelf haddock (Melanogrammus aeglefinus)

2003 ◽  
Vol 60 (3) ◽  
pp. 321-332 ◽  
Author(s):  
Julia L Blanchard ◽  
Kenneth T Frank ◽  
James E Simon
Keyword(s):  
Time Series ◽  
Egg Production ◽  
Significant Proportion ◽  
Melanogrammus Aeglefinus ◽  
Hepatosomatic Index ◽  
Dramatic Improvement ◽  
Scotian Shelf ◽  
Residual Variation ◽  
Condition Effect ◽  
Haddock Melanogrammus Aeglefinus

A fecundity study of the eastern Scotian Shelf haddock (Melanogrammus aeglefinus) stock during the 1997–1999 spawning seasons is reported. We developed a model that accounted for fecundity changes at the individual level and that could be used to estimate population egg production beyond the study period. Incorporating condition factors into the model (relative condition factor (Kn) and hepatosomatic index) accounted for a significant proportion of the residual variation. The model predicted that a change in Kn from 0.8 to 1.0 resulted in a twofold increase in fecundity at length. This variability was as great as that observed for fecundity–length relationships among stocks. Three time series (1979–2001) of total egg production (TEP) were constructed using different fecundity relationships: one with a condition effect, one based on length only, and one based on weight only. The magnitude of change in TEP resulting from the condition effect ranged from +30 to –20%. Condition effects during the first half of the time series resulted in an enhancement of TEP, whereas in the latter half, condition effects depressed TEP. This evaluation of TEP generated new insights into haddock stock dynamics but did not result in a dramatic improvement of the relationship between recruitment and stock reproductive potential.

Catchability and the spatial distribution of fishing vessels

2003 ◽  
Vol 60 (3) ◽  
pp. 259-268 ◽  
Author(s):  
Are Salthaug ◽  
Sondre Aanes
Keyword(s):  
Gadus Morhua ◽  
Fish Stock ◽  
Melanogrammus Aeglefinus ◽  
Catch Per Unit Effort ◽  
Spatial Concentration ◽  
Commercial Catch ◽  
Fish Stocks ◽  
Fishing Vessels ◽  
The Relationship ◽  
Stock Abundance

A central problem when using commercial catch per unit effort (CPUE) as an index of fish stock abundance is that fishing vessels search for concentrations of fish. For a given stock abundance, CPUE may become high if the vessels succeed in finding patches of fish and low if the vessels distribute their catching operations more randomly. In this work, the relationship between catchability and two measures of the degree of spatial concentration of a trawl fleet (the fleet's spatial extent and the fleet's degree of spatial patchiness) is investigated for four different fish stocks. The catchability of northeast Arctic cod (Gadus morhua) is strongly related to the fleet's degree of spatial concentration, but the relationship is weaker for northeast Arctic haddock (Melanogrammus aeglefinus), and no relationships appear for two saithe (Pollachius virens) stocks. Our findings suggest that adjusting CPUE with a measure of the fleet's average degree of concentration relates CPUE more strongly with abundance for migratory stocks.

scholarly journals Detection Threshold Estimates for InSAR Time Series: A Simulation of Tropospheric Delay Approach

Sensors ◽  
2021 ◽  
Vol 21 (4) ◽  
pp. 1124 ◽  
Author(s):  
Emre Havazli ◽  
Shimon Wdowinski
Keyword(s):  
Time Series ◽  
Detection Threshold ◽  
Simulated Data ◽  
Inverse Correlation ◽  
Tropospheric Delay ◽  
Data Sets ◽  
Sampled Data ◽  
Magma Body ◽  
Study Results ◽  
Temporal Coverage

We present a method for estimating the detection threshold of InSAR time-series products that relies on simulations of both vertical stratification and turbulence mixing components of tropospheric delay. Our simulations take into account case-specific parameters, such as topography and wet delay. We generate the time series of simulated data with given intervals (e.g., 12 and 35 days) for temporal coverages varying between 3 and 10 years. Each simulated acquisition presents the apparent noise due to tropospheric delay, which is constrained by case-specific parameters. As the calculation parameters are randomized, we carry out a large number of simulations and analyze the results statistically and we see that, as temporal coverage increases, the amount of propagated error decreases, presenting an inverse correlation. We validate our method by comparing our results with ERS and Envisat results over Socorro Magma Body, New Mexico. Our case study results indicate that Sentinel-1 can achieve ≈1 mm/yr detection level with regularly sampled data sets that have temporal coverage longer than 5 years.

scholarly journals Combining Dependent P-values with an Empirical Adaptation of Brown's Method

2015 ◽  
Author(s):  
William Poole ◽  
David L. Gibbs ◽  
Ilya Shmulevich ◽  
Brady Bernard ◽  
Theo Knijnenburg
Keyword(s):  
Statistical Tests ◽  
Null Distribution ◽  
Simulated Data ◽  
Correlated Data ◽  
The Cancer Genome Atlas ◽  
Data Sets ◽  
P Values ◽  
Brown's Method ◽  
Fisher's Method ◽  
Fisher’S Method

Combining P-values from multiple statistical tests is a common exercise in bioinformatics. However, this procedure is non-trivial for dependent P-values. Here we discuss an empirical adaptation of Brown's Method (an extension of Fisher's Method) for combining dependent P-values which is appropriate for the correlated data sets found in high-throughput biological experiments. We show that Fisher's Method is biased when used on dependent sets of P-values with both simulated data and gene expression data from The Cancer Genome Atlas (TCGA). When applied on the same data sets, the Empirical Brown's Method provides a better null distribution and a more conservative result. The Empirical Brown's Method is available in Python, R, and MATLAB and can be obtained from https://github.com/IlyaLab/CombiningDependentPvaluesUsingEBM.

Effect of Changes in Recruitment Levels on Multispecies Long-term Predictions

1993 ◽  
Vol 50 (11) ◽  
pp. 2315-2322 ◽  
Author(s):  
Henrik Gislason
Keyword(s):  
Gadus Morhua ◽  
Atlantic Cod ◽  
Relative Increase ◽  
Clupea Harengus ◽  
Melanogrammus Aeglefinus ◽  
Fish Stocks ◽  
The North ◽  
Predation Mortality ◽  
Spawning Stock ◽  
Relative Change

A multispecies model (MSFOR) is used to predict the relative change in equilibrium yield and spawning stock biomass (SSB) of commercially important fish stocks in the North Sea resulting from a reduction in the fishing mortality generated by the roundfish fishery. Because predation mortality is a function of the abundance of prey and predators the results will depend on recruitment. Assuming recruitment to be independent of stock sizes the effect of changes in recruitment is studied by repeating the predictions at all possible combinations of ±50% changes in predator and prey recruitment levels. All of the predictions result in a relative increase in the SSB of Atlantic cod (Gadus morhua) and saithe (Pollachius virens) and in a relative decrease in the SSB of Atlantic herring (Clupea harengus) and Norway pout (Trisopterus esmarkii). In these cases the sign of the relative change is robust to recruitment changes. However, for haddock (Melanogrammus aeglefinus), sprat (Sprattus sprattus), and sandeel (Ammodytes marinus) the relative change in SSB is found to be either positive or negative depending on the level of recruitment. The predictions for haddock are highly sensitive to changes in the level of saithe recruitment.

Is spawner biomass a sensitive measure of the reproductive and recruitment potential of Northeast Arctic cod?

1998 ◽  
Vol 55 (7) ◽  
pp. 1766-1783 ◽  
Author(s):  
C Tara Marshall ◽  
Olav Sigurd Kjesbu ◽  
Nathalia A Yaragina ◽  
Per Solemdal ◽  
Øyvind Ulltang
Keyword(s):  
Egg Production ◽  
Gadus Morhua ◽  
Atlantic Cod ◽  
Population Analysis ◽  
Reproductive Potential ◽  
Fish Stocks ◽  
Virtual Population ◽  
Individual Scale ◽  
The Individual ◽  
The Relationship

The assumption that spawner biomass is directly proportional to total egg production by fish stocks underlies most spawner-recruit relationships. Despite its importance, this assumption is largely untested. Data describing the reproductive potential of Northeast Arctic (NEA) Atlantic cod (Gadus morhua) were used to test the proportionality assumption for a period showing strong variation in condition and abundance of spawners. At the individual scale, relative fecundity varied with length and condition. This decreases the likelihood that the proportionality assumption is valid. At the stock level, total egg production was estimated (1985-1996) using acoustic estimates of total abundance and demographic information from trawl sampling in combination with year-specific fecundity-length relationships. For NEA cod, spawner biomass estimated by virtual population analysis (VPA) was not proportional to total egg production. Compared with VPA-based estimates of spawner biomass, total egg production is an improved index of recruitment potential because (i) the magnitude of variation observed in total egg production was closer to that observed in recruitment and (ii) the relationship between recruitment at age 1 and total egg production approaches the origin. The results suggest that further progress in explaining recruitment variation will be achieved using more sensitive measures of the true reproductive potential of the stock.

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