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Payne, Mark R (2013): The North Sea autumn spawning Herring (Clupea harengus L.) Spawning Component Abundance Index (SCAI). PANGAEA, https://doi.org/10.1594/PANGAEA.823680, Supplement to: Payne, MR (2010): Mind the gaps: a state-space model for analysing the dynamics of North Sea herring spawning components. ICES Journal of Marine Science, 67(9), 1939-1947, https://doi.org/10.1093/icesjms/fsq036

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Abstract:
The North Sea autumn-spawning herring (Clupea harengus) stock consists of a set of different spawning components. The dynamics of the entire stock have been well characterized, but although time-series of larval abundance indices are available for the individual components, study of the dynamics at the component level has historically been hampered by missing observations and high sampling noise. A simple state-space statistical model is developed that is robust to these problems, gives a good fit to the data, and proves capable of both handling and predicting missing observations well. Furthermore, the sum of the fitted abundance indices across all components proves an excellent proxy for the biomass of the total stock, even though the model utilizes information at the individual-component level. The Orkney–Shetland component appears to have recovered faster from historic depletion events than the other components, whereas the Downs component has been the slowest. These differences give rise to changes in stock composition, which are shown to vary widely within a relatively short time. The modelling framework provides a valuable tool for studying and monitoring the dynamics of the individual components of the North Sea herring stock.
Related to:
Fässler, Sascha M M; Payne, Mark R; Brunel, T; Dickey-Collas, M (2011): Does larval mortality influence population dynamics? An analysis of North Sea herring (Clupea harengus) time series. Fisheries Oceanography, 20(6), 530-543, https://doi.org/10.1111/j.1365-2419.2011.00600.x
Payne, Mark R; Ross, S D; Worssam, B C; Munk, Peter; Mosegaard, Klaus; Nash, Richard DM (2013): Recruitment decline in North Sea herring is accompanied by reduced larval growth rates. Marine Ecology Progress Series, 489, 197-211, https://doi.org/10.3354/meps10392
Coverage:
Median Latitude: 55.500000 * Median Longitude: -0.750000 * South-bound Latitude: 50.250000 * West-bound Longitude: -2.000000 * North-bound Latitude: 59.500000 * East-bound Longitude: 0.500000
Date/Time Start: 1972-07-01T00:00:00 * Date/Time End: 2012-07-01T00:00:00
Event(s):
Banks * Latitude: 55.000000 * Longitude: -0.500000 * Location: Banks, east coast of Great Britain
Buchan * Latitude: 57.250000 * Longitude: -1.000000 * Location: Buchan, east coast of Great Britain
Downs * Latitude: 50.250000 * Longitude: 0.500000 * Location: Downs, east coast of Great Britain
Comment:
The North Sea Autumn Spawning (NSAS) herring (Clupea harengus L.) spawning component abundance index (SCAI) provides relative indices of the four main sub-components of the NSAS herring stock. This fish stock has been surveyed annually on the main spawning grounds (Orkney/Shetland, Buchan, Banks and Downs, along the east-coast of Great Britain) at spawning time by the International Herring Larval Surveys (IHLS) from 1972 until the present. However, gaps and systematic biases in these surveys are present and limit the usefulness of this data. The SCAI is the output of a state-space statistical model that accounts for these problems in a statistically appropriate manner. The SCAI provides a consistent index of the abundance of the spawning components (at spawning time) relative to each other and over time and is therefore valuable in the study of both the total population of this stock, and of the individual sub-components.
Parameter(s):
#NameShort NameUnitPrincipal InvestigatorMethodComment
1Event labelEvent
2DATE/TIMEDate/TimeGeocode
3Spawning component abundance indexSCAIPayne, Mark R
4Standard errorStd e±Payne, Mark RThe error in the fit is in the log-transformed SCAI. A 95% confidence interval (CI) is therefore calculated as CI=exp(log(SCAI)+/-1.96*SE).
Size:
328 data points

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