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Ian R. Stevenson
Researcher at University of Stirling
Publications - 17
Citations - 1997
Ian R. Stevenson is an academic researcher from University of Stirling. The author has contributed to research in topics: Soay sheep & Population. The author has an hindex of 14, co-authored 17 publications receiving 1900 citations. Previous affiliations of Ian R. Stevenson include University of Cambridge.
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Dominant rams lose out by sperm depletion
TL;DR: A waning success in siring counters a ram's high score in competition for ewes.
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Competition and mutualism among the gut helminths of a mammalian host
TL;DR: Evidence of consistent interspecific interactions in a natural mammalian system is presented through the analysis of parasite intensity data collected from a free-ranging rabbit population, sampled monthly for a period of 23 yr, suggesting that parasite interactions could have profound implications for the dynamics of parasite communities.
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Overt and covert competition in a promiscuous mammal: the importance of weaponry and testes size to male reproductive success.
TL;DR: The Soay sheep mating system is characterized by male contests for mating opportunities and high female promiscuity and it is found that greater horn length, body size and good condition each independently influence a male' ability to monopolize receptive females.
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Climate change and constraints on breeding
Ian R. Stevenson,David M. Bryant +1 more
TL;DR: An energy trade-off between reproduction and maintenance that occurs during cold weather in great tits (Parus major L.), pointing to a thermal constraint on the timing of egg laying.
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Population fluctuations, reproductive costs and life-history tactics in female soay sheep
Tim H. Clutton-Brock,Ian R. Stevenson,Paul Marrow,Andrew D. C. MacColl,Alasdair I. Houston,JM McNamara +5 more
TL;DR: Using long-term records of individual reproduction and survival in the Soay sheep of St Kilda, it is shown that the costs and benefits of breeding to animals of different weight categories vary with population density and stochastic dynamic programming is used to predict the optimal fecundity of animals belonging to each category at high and low population density.