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Life histories of anadromous salmon males reveal a trade-off between primary and secondary sexual traits

Vladić Tomislav, Järvi Torbjörn, Petersson Erik

Oceanological and Hydrobiological Studies

2019

Vol. 48, No. 3

279--289

The life-history trade-off between investment in somatic growth and gonadal tissue is caused by individual energy limitations and results in individuals that adopt specific tactics to achieve reproduction. Allocation in primary and secondary sexual traits in Atlantic salmon males was studied by assessing life history traits (smolt size, sea age, growth rate) based on back-calculation of scales, ejaculate energy content (sperm ATP content, mass and density) and the size of secondary sexual traits. We found that males investing less in secondary sexual traits produce ejaculates with a higher energy content. Differences were found in the investment into primary and secondary sexual traits between fish that spent one year in the sea before returning to their spawning grounds (grilse) and multi-sea-winter adults, suggesting that different energy allocation patterns in reproductive effort reflect alternative developmental pathways. These findings are consistent with the pattern where multi-sea-winter male ejaculate investment relies principally on the resource acquisition in the ocean, whereas grilse ejaculate investment relies chiefly on the resource allocation of available surplus energy, thus representing alternative male reproductive tactics.

Why life histories are diverse

Kozlowski Jan

Polish Journal of Ecology

2006

Vol. 54, nr 4

585-605

Why do some animals weigh a fraction of a milligram and others many tons? Why do some animals mature after a few days and others need several years? Why do some animals grow and then reproduce without growing, while others continue growing after maturation? Why are growth curves so often well-approximated by von Bertalanffy's equation? Why do some animals produce myriads of tiny eggs and others produce only a few large offspring? Evolution of life histories is driven basically by the size-dependences of three parameters: the resource acquisition rate, metabolic rate and mortality risk. The combinations of size-dependences of this trio produce a plethora of locally optimal life histories, and even more sub-optimal strategies which must coexist with optimal ones in the real world. Additionally, selection forces differ depending on whether a population stays most of the time at equilibrium or in an expansion phase. Life history evolution cannot be understood without mathematical modelling, and optimization of life-time resource allocation is a powerful approach to that, though not the only one. Modelling outcomes from studies based on resource allocation optimization are presented here mainly as graphs.