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Why do organisms age? Why is interspecific variation in life expectancies so great? These are questions of fundamental importance for the general public and scientists alike. Evolutionary biology explains ageing as a consequence of the decreasing power of selection with age and of life history trade-offs where a beneficial change in one trait is often linked with costs for another trait. Central to ageing is the trade-off between fecundity and longevity: in virtually all multicellular organisms an increase in fecundity is associated with a decrease in longevity. A major exception is found in the social insects, in which the most fecund individuals (the queens in ants, wasps and bees, and the kings and queens in termites) live up to two orders of magnitude longer than their sterile workers.

The overarching goal of the SO-LONG project (FOR2281) is to understand why and how the fecundity/longevity trade-off is remoulded in social insects. By uncovering the basis to the apparent escape from life history trade-offs, we expect to understand fundamental biological rules governing fecundity, longevity, ageing, and health.

Our Research Unit brings together internationally recognized experts in ecology, evolutionary biology, behavioural biology, molecular biology, bioinformatics, and scientific computing. Scientists from Germany, the Netherlands, Switzerland and Brazil collaborate tightly to study the fecundity/longevity trade-off in relation to sociality across three clades of social insects (ants, bees, and termites), using solitary model organisms as a control. With a common set-up of canonical experiments across taxa that manipulate two crucial factors, food and fecundity, we aim to disentangle their effects in shaping this trade-off. Using next generation sequencing (NGS) data, we conduct gene expression analyses and measure transcriptome changes along with oxidative stress and endocrine effects. We supplement these data with measures of fitness (e.g., survival, egg laying rate, colony productivity, sexual offspring production). These are the basis for overarching cross-taxon analyses that allow both the identification of key molecular pathways underpinning life history trade-offs as well as the development of quantitative life history models by applying a mechanistic socioevo-devo approach. We thereby expect to achieve a deeper understanding of the fundamental biological rules governing central life history traits.


This research unit is funded by the German Science Foundation DFG.