Literature DB >> 3982053

Are patterns of growth adaptive?

R Sibly, P Calow, N Nichols.   

Abstract

Models which define fitness in terms of per capita rate of increase of phenotypes are used to analyse patterns of individual growth. It is shown that sigmoid growth curves are an optimal strategy (i.e. maximize fitness) if (Assumption 1a) mortality decreases with body size; (2a) mortality is a convex function of specific growth rate, viewed from above; (3) there is a constraint on growth rate, which is attained in the first phase of growth. If the constraint is not attained then size should increase at a progressively reducing rate. These predictions are biologically plausible. Catch-up growth, for retarded individuals, is generally not an optimal strategy though in special cases (e.g. seasonal breeding) it might be. Growth may be advantageous after first breeding if birth rate is a convex function of G (the fraction of production devoted to growth) viewed from above (Assumption 5a), or if mortality rate is a convex function of G, viewed from above (Assumption 6c). If assumptions 5a and 6c are both false, growth should cease at the age of first reproduction. These predictions could be used to evaluate the incidence of indeterminate versus determinate growth in the animal kingdom though the data currently available do not allow quantitative tests. In animals with invariant adult size a method is given which allows one to calculate whether an increase in body size is favoured given that fecundity and developmental time are thereby increased.

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Year:  1985        PMID: 3982053     DOI: 10.1016/s0022-5193(85)80022-9

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  11 in total

1.  Unexpected discontinuities in life-history evolution under size-dependent mortality.

Authors:  Barbara Taborsky; Ulf Dieckmann; Mikko Heino
Journal:  Proc Biol Sci       Date:  2003-04-07       Impact factor: 5.349

2.  Statistical analysis of structural compensatory growth: how can we reduce the rate of false detection?

Authors:  Alfredo G Nicieza; David Alvarez
Journal:  Oecologia       Date:  2008-10-31       Impact factor: 3.225

3.  An energetics model of an aquatic predator and its application to life-history optima.

Authors:  L R Linton; R W Davies
Journal:  Oecologia       Date:  1987-03       Impact factor: 3.225

4.  Phenotypic plasticity of life-history traits in clonal and sexual fish (Poeciliopsis) at high and low densities.

Authors:  Stephen C Weeks
Journal:  Oecologia       Date:  1993-03       Impact factor: 3.225

5.  Telomere dynamics in wild brown trout: effects of compensatory growth and early growth investment.

Authors:  Joacim Näslund; Angela Pauliny; Donald Blomqvist; Jörgen I Johnsson
Journal:  Oecologia       Date:  2015-02-20       Impact factor: 3.225

6.  Inbreeding reduces fitness of seed beetles under thermal stress.

Authors:  Edward Ivimey-Cook; Sophie Bricout; Victoria Candela; Alexei A Maklakov; Elena C Berg
Journal:  J Evol Biol       Date:  2021-07-20       Impact factor: 2.516

7.  Distinguishing between determinate and indeterminate growth in a long-lived mammal.

Authors:  Hannah S Mumby; Simon N Chapman; Jennie A H Crawley; Khyne U Mar; Win Htut; Aung Thura Soe; Htoo Htoo Aung; Virpi Lummaa
Journal:  BMC Evol Biol       Date:  2015-10-14       Impact factor: 3.260

8.  Age and growth of the round stingray Urotrygon rogersi, a particularly fast-growing and short-lived elasmobranch.

Authors:  Paola A Mejía-Falla; Enric Cortés; Andrés F Navia; Fernando A Zapata
Journal:  PLoS One       Date:  2014-04-28       Impact factor: 3.240

9.  Quantifying and understanding reproductive allocation schedules in plants.

Authors:  Elizabeth Hedi Wenk; Daniel S Falster
Journal:  Ecol Evol       Date:  2015-11-07       Impact factor: 2.912

10.  Twelve fundamental life histories evolving through allocation-dependent fecundity and survival.

Authors:  Jacob Johansson; Åke Brännström; Johan A J Metz; Ulf Dieckmann
Journal:  Ecol Evol       Date:  2018-02-19       Impact factor: 2.912

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