Chapter 5: extensions of LMC
What a monster…
Local Mate Competition - quick recap
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Foundress Number
Sex Ratio (proportion male)
More Mums = More Sons
How are these extensions different to ‘classic’ LMC?
(what makes them interesting?)
Classic LMC What’s the difference?
Partial LMC All mating at natal patch
Dispersal = some mating beyond patch
Variable clutch size
Equal number of offspring /female
Different f = different clutch size
Limited dispersal
Foundress females unrelated
Females may be related
Haystacks Interactions within one generation
Groups extends over multiple generations
Fertility insurance
Min no. sons = can mate all girls
May need more males to mate all
females
Classic LMC What’s the difference?
Partial LMC All mating at natal patch
Dispersal = some mating beyond patch
Variable clutch size
Equal number of offspring /female
Different f = different clutch size
Limited dispersal
Foundress females unrelated
Females may be related
Haystacks Interactions within one generation
Groups extends over multiple generations
Fertility insurance
Min no. sons = can mate all girls
May need more males to mate all
females
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…
Sequential oviposition: Superparasitism
Scenario:
2 females lay eggs on the same host sequentially
time
1st female 2nd female
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:
a) daughter: gains average female reprod value
b) 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…
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Superparasitism in Nasonia - Graph from Werren 1980:
No. offspring 2nd female/ no. offspring 1st female
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S s
ex r
atio
for
2nd
fem
ale
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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:
1. low number of functional male gametes produced ~ sperm limitation
Unsuccessful gamete production; poor motility; low survival
2. 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
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?
LMC Summary