Article (Scientific journals)
A functional growth model with intraspecific competition applied to a sea urchin, Paracentrotus lividus
Grosjean, Philippe; Spirlet, Christine; Jangoux, Michel
2003In Canadian Journal of Fisheries and Aquatic Sciences, 60, p. 237-246
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Keywords :
[en] intraspecific competition; [en] fuzzy logic; [en] growth model; [en] quantile regression; [en] sea urchin
Abstract :
[en] A new growth model is fitted on data from reared sea urchins, Paracentrotus lividus. Quantile regressions are used instead of least-square regressions, because they are insensitive to the dimension of the measurement and accommodate more than just symmetrical distributions. Quantile regressions allow comparison of fittings on various parts of the size distributions, including large competitors versus small, inhibited animals, in the presence of a size- based intraspecific competition. The model has functionally interpretable parameters and allows quantifying of the intensity of growth inhibition. An extension of this model, called 'envelope model', fits the whole data set at once, including size distributions. Its parameters are constrained using information about underlying biological processes involved, namely asymptotic growth with inhibition in early ages as the result of intraspecific competition, the intensity of which depends on the relative size of the individual in the cohort. The new model appears most adequate to describe growth of P. lividus and probably many other sea urchins species as well as other animals or plants.
Disciplines :
Agriculture & agronomy
Phytobiology (plant sciences, forestry, mycology...)
Mathematics
Author, co-author :
Grosjean, Philippe  
Spirlet, Christine
Jangoux, Michel ;  Université de Mons > Faculté des Sciences > Biologie des Organismes Marins et Biomimétisme
Language :
English
Title :
A functional growth model with intraspecific competition applied to a sea urchin, Paracentrotus lividus
Publication date :
01 January 2003
Journal title :
Canadian Journal of Fisheries and Aquatic Sciences
ISSN :
0706-652X
Publisher :
NRC Research Press, Canada
Volume :
60
Pages :
237-246
Peer reviewed :
Peer Reviewed verified by ORBi
Research unit :
S807 - Ecologie numérique
Research institute :
R150 - Institut de Recherche sur les Systèmes Complexes
R100 - Institut des Biosciences
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