How are these extensions different to ‘classic’ LMC? (what makes them interesting?)
Extensions of LMC • less well tested empirically • and less good a fit of data to theory • most commonly explained by a)information processing or b)fertility insurance • 1 example of each…
1st female 2nd female time Sequential oviposition: Superparasitism Scenario: 2 females lay eggs on the same host sequentially
Predictions: ESS sex ratio for 2nd female is influenced by clutch size of 1st female If 2nd<1st, should lay less female biased sex ratio Why? Smaller proportion of offspring = weaker LMC - less competition between sons - less benefit to increasing number of daughters
Stu’s worked example 1st female: 2 males + 18 females = sex ratio of 0.1 2nd female lays only 1 egg… 2 options: daughter: gains average female reprod value son: gains 6 times reprod value of a female Because of female biased sex ratio, son has 18/(2=1) =6 mates… 2nd female should ‘parasitise’ female biased SR of 1st The larger the brood of the 2nd female, the greater LMC…
Superparasitism in Nasonia - Graph from Werren 1980: ESS sex ratio for 2nd female No. offspring 2nd female/ no. offspring 1st female
2 points to highlight: On one hand, a good fit of data to theory… On the other, % variance explained here ~ 30% vs. 90% variance of data explained by LMC theory (last wk) Why? main probable reason = imperfect information processing
Further extensions: asymmetrical LMC • Sequential oviposition may lead to asynchronous offspring emergence • May affect male mating success &/or level of LMC faced • e.g. Patch of multiple hosts - Nasonia, Shuker et al. • - 1st clutch emerge & mate; females disperse, males stay • 1st clutch males experience different level of LMC to 2nd • predicts different optimal sex ratios… • Less female biased SR if other hosts on patch parasitised • But less biased than theory: constraints + info processing
Fertility insurance LMC assumes the minimum predicted number of male offspring will be able to fertilise all female offspring… Not always the case. Malaria meets conditions for LMC - population subdivided Expect variation in sex allocation with level of inbreeding But much unexplained variation in sex ratio, e.g. -through course of infection -with level of host anaemia -life history differences?
Fertility Insurance: Malaria Sexual stage gametocytes taken up by vector in blood meal Male & female gametes produced Must leave blood cells & enter hostile environ to mate Fertility insurance favoured for 2 reasons: low number of functional male gametes produced ~ sperm limitation Unsuccessful gamete production; poor motility; low survival the number of gametes that interact is low High mortality; low number in blood; limited search area
Theory predicts that: • small number of interacting gametes (~small clutch size) =less female-biased sex ratio favoured: need to ensure female gametes are mated… • these two factors can interact to favour even less female-biased sex ratio • Data so far: • - sex ratios in humans & lizards suggest low number of functional gametes • bird malaria: less female biased SR than expected • much variation in sex ratio taken at different stages of an infection
LMC Summary Predicts mean sex ratios well, even with complex individual sex ratios 2 most general reasons for data not matching theory: 1.limits on information processing & 2.constraints in small clutches ~ fertility insurance Future directions - quantitative tests of existing theory - mechanistic Q’s for well-understood models e.g. assessing environ & sex ratio adjustment - new theory for biology of less-understood systems?