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作 者:Julian C.EVANS Anna K.LINDHOLM Barbara KöNIG
出 处:《Current Zoology》2021年第1期59-69,共11页动物学报(英文版)
基 金:Financial support was provided by the Swiss National Science Foundation(31003A_176114 to B.K.,31003A-120444,and 310030M_138389 to A.K.L.);University of Zurich,Promotor foundation,and Claraz Schenkung.
摘 要:Associating with relatives in social groups can bring benefits such as reduced risk of aggression and increased likelihood of cooperation.Competition among relatives over limited resources,on the other hand,can induce individuals to alter their patterns of association.Population density might further affect the costs and benefits of associating with relatives by altering resource competition or by changing the structure of social groups;preventing easy association with relatives.Consequently,the overlap between genetic and social structure is expected to decrease with increasing population size,as well as during times of increased breeding activity.Here,we use multi-layer network techniques to quantify the similarity between long-term,high resolution genetic,and behavioral data from a large population of free-ranging house mice(Mus musculus domesticus),studied over 10years.We infer how the benefit of associating with genetically similar individuals might fluctuate in relation to breeding behavior and environmental conditions.We found a clear seasonal effect,with decreased overlap between social and genetic structure during summer months,characterized by high temperatures and high breeding activity.Though the effect of overall population size was relatively weak,we found a clear decrease in the overlap between genetic similarity and social associations within larger groups.As well as longer-term within-group changes,these results reveal population-wide short-term shifts in how individuals associate with relatives.Our study suggests that resource competition modifies the trade-off between the costs and benefits of interacting with relatives.
关 键 词:genetic relatedness long-term data multilayer networks SEASONAL social behavior
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