Predicting the successful flowering time strategies of future climates using life history theory and molecular genetics

Project: Research

Research areas and keywords


  • Narrowleaf hawksbeard, hoary rockrose, barley, flowering time


Shifts in plant's flowering seasons towards earlier dates belong to the most well documented biological effects of climate change, but the demographic consequences are variable and little studied. Are these responses adaptive or will they cause declines? Are plastic responses sufficient for species to keep pace with a warmer climate or is natural selection necessary?

The molecular machinery regulating flowering seems to have evolved only once and it is established that flowering time is controlled mainly by temperature- and daylength cues at the molecular level. Life history theory can been used to predict the fitness consequences of flowering times and how they influence trade-offs between reproduction, growth and survival. Recently, we showed how such trade-offs critically affect the direction and magnitude of optimal phenological shifts.

The aim for this project is to predict how plants will adapt their flowering times to climatic changes and which genes are most important in this process.

Layman's description

We associate flowers with spring and summer and they adorn our gardens and parks. What one might not often think of is that the flower itself is crucial for the plant's reproduction. It is also important for plants exactly when during the year they choose to flower. A plant that blooms too early in the year risks being hit by weather conditions such as frost and if a plant blooms late, the seeds may not be able to mature before it becomes too cold. For many plants, it is also important to bloom when there are bees and other insects that can pollinate the flowers. For the plants, therefore, the flowering is vital and it is important to optimize the flowering in time and space in order to succeed in forming as many seeds as possible. In this project we combine theoretical models and molecular genetic methods to predict how plants adapt their flowering times to climate change and which genes are most important in this process.
Effective start/end date2018/01/012019/12/31

Collaborative partners