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JOURNAL OF PLANKTON RESEARCH | VOLUME 17 | NUMBER 6 | PAGES 1189-1208 | 1995
© Oxford University Press

research-article

Spatial distribution functions and abundances inferred from sparse noisy plankton data: an application of constrained thin-plate splines

Simon N. Wood1 and Joseph W. Horwood2

NERC Centre for Population Biology, Imperial College at Silwood Park Ascot, Berkshire SL5 7PY UK 1Present address: Wildlife Population Assessment Research Group, Mathematical Institute, University of St Andrews North Haugh, St Andrews, Fife KY16 9SS, UK; snw{at}st-and.ac.uk 2 MAFF Directorate of Fisheries Research, Fisheries Laboratory Lowestoft, Suffolk NR33 OHT, UK

As plankton biologists ask more detailed questions of necessarily sparse and noisy spatial data, the need for well founded methods for statistical analysis of such data grows. This note examines the utility of constrained thin-plate smoothing splines as a tool for inferring underlying spatial distribution functions from sparse noisy data. Constrained thin-plate splines are described in a straightforward manner. An economical method of calculation is suggested, which sacrifices mathematical optimality for ease of computation. Using simulated data several methods for choosing the complexity of the inferred distribution function are compared and robustness to large amplitude noise is examined. Confidence intervals are calculated and tested. The method is applied to egg data from Dover sole (Solea solea) in the Bristol Channel.


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