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High genetic load in an old isolated butterfly population

Mattila, Anniina L. K., Duplouy, Anne, Kirjokangas, Malla, Lehtonen, Rainer, Rastas, Pasi, Hanski, Ilkka
Proceedings of the National Academy of Sciences of the United States of America 2012 v.109 no.37 pp. E2496
adults, at-risk population, butterflies, cages, eggs, extinction, flight, genetic markers, genetic variation, heterosis, inbreeding, inbreeding depression, islands, landscapes, longevity, males, metabolism, models, mutation, reproductive performance, resting metabolic rate, viability, Baltic Sea, Estonia, Finland
We investigated inbreeding depression and genetic load in a small (N ₑ ∼ 100) population of the Glanville fritillary butterfly (Melitaea cinxia), which has been completely isolated on a small island [Pikku Tytärsaari (PT)] in the Baltic Sea for at least 75 y. As a reference, we studied conspecific populations from the well-studied metapopulation in the Åland Islands (ÅL), 400 km away. A large population in Saaremaa, Estonia, was used as a reference for estimating genetic diversity and N ₑ. We investigated 58 traits related to behavior, development, morphology, reproductive performance, and metabolism. The PT population exhibited high genetic load (L = 1 − W PT/W ÅL) in a range of fitness-related traits including adult weight (L = 0.12), flight metabolic rate (L = 0.53), egg viability (L = 0.37), and lifetime production of eggs in an outdoor population cage (L = 0.70). These results imply extensive fixation of deleterious recessive mutations, supported by greatly reduced diversity in microsatellite markers and immediate recovery (heterosis) of egg viability and flight metabolic rate in crosses with other populations. There was no significant inbreeding depression in most traits due to one generation of full-sib mating. Resting metabolic rate was significantly elevated in PT males, which may be related to their short lifespan (L = 0.25). The demographic history and the effective size of the PT population place it in the part of the parameter space in which models predict mutation accumulation. This population exemplifies the increasingly common situation in fragmented landscapes, in which small and completely isolated populations are vulnerable to extinction due to high genetic load.