Publications by authors named "M Kever"

Social insects are models for studies of phenotypic plasticity. Ant queens and workers vary in fecundity and lifespan, which are enhanced and extended in queens. Yet, the regulatory mechanisms underlying this variation are not well understood.

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Parasites with complex life cycles often manipulate the phenotype of their intermediate hosts to increase the probability of transmission to their definitive hosts. Infection with Anomotaenia brevis, a cestode that uses Temnothorax nylanderi ants as intermediate hosts, leads to a multiple-fold extension of host lifespan and to changes in behaviour, morphology and colouration. The mechanisms behind these changes are unknown, as is whether the increased longevity is achieved through parasite manipulation.

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Humans and other social mammals experience isolation from their group as stressful, triggering behavioural and physiological anomalies that reduce fitness. While social isolation has been intensely studied in social mammals, it is less clear how social insects, which evolved sociality independently, respond to isolation. Here we examined whether the typical mammalian responses to social isolation, e.

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Article Synopsis
  • Classic life history theory suggests that both longevity and fecundity are influenced by external mortality factors, but in social insects like ants, high fecundity (in queens) correlates with longer lifespan.
  • A study on Temnothorax longispinosus ants found that workers live longer in the absence of queens, possibly because those that lay eggs receive better care or experience physiological benefits.
  • Additionally, the research revealed that younger worker nurses tend to have longer lifespans compared to foragers, while inactive workers had lower survival rates, indicating complex relationships between age, reproductive status, and activity levels in determining mortality.
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We analyze the unrestricted black-box complexity of the Jump function classes for different jump sizes. For upper bounds, we present three algorithms for small, medium, and extreme jump sizes. We prove a matrix lower bound theorem which is capable of giving better lower bounds than the classic information theory approach.

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