Diversity and relatedness enhance survival in colour polymorphic grasshoppers.
Evolutionary theory predicts that different resource utilization and behaviour by alternative phenotypes may reduce competition and enhance productivity and individual performance in polymorphic, as compared with monomorphic, groups of individuals. However, firm evidence that members of more heterogeneous groups benefit from enhanced survival has been scarce or lacking. Furthermore, benefits associated with phenotypic diversity may be counterbalanced by costs mediated by reduced relatedness, since closely related individuals typically are more similar. Pygmy grasshoppers (Tetrix subulata) are characterized by extensive polymorphism in colour pattern, morphology, behaviour and physiology. We studied experimental groups founded by different numbers of mothers and found that survival was higher in low than in high density, that survival peaked at intermediate colour morph diversity in high density, and that survival was independent of diversity in low density where competition was less intense. We further demonstrate that survival was enhanced by relatedness, as expected if antagonistic and competitive interactions are discriminately directed towards non-siblings. We therefore also performed behavioural observations and staged encounters which confirmed that individuals recognized and responded differently to siblings than to non-siblings. We conclude that negative effects associated with competition are less manifest in diverse groups, that there is conflicting selection for and against genetic diversity occurring simultaneously, and that diversity and relatedness may facilitate the productivity and ecological success of groups of interacting individuals.
School of Natural Sciences, Linnaeus University, Kalmar, Sweden.
Sofia
S
Caesar
Magnus
M
Karlsson
Anders
A
Forsman
D000818:Animals; D006110:Grasshoppers / Q000235:genetics*; D010641:Phenotype; D010802:Phylogeny; D010858:Pigmentation / Q000235:genetics*; D011110:Polymorphism, Genetic; D011157:Population Dynamics; D016019:Survival Analysis