Whether bud formation, leaf emergence, flower or fruit formation: The development of a plant is characterised by the seasons. However, climate change and, above all, higher temperatures have shifted the life cycle of plants in many places in recent years. Recording such phenotypic changes on a large scale is essential for researchers in order to draw conclusions about the effects of climate change on plants. With the plant identification app Flora Incognita, a tool has been providing researchers with observation data on a large scale for several years.

Ecological patterns derived from app data

A research team led by the German Centre for Integrative Biodiversity Research (iDiv) and the University of Leipzig has now developed an algorithm that analyses all of the app's data. This analysis can in turn be used to derive ecological patterns that paint a clear picture of the effects of climate change on the plant world.

‘When I record a plant with the app, this observation is given a location and time stamp,’ says co-author Jana Wäldchen from the Max Planck Institute for Biogeochemistry (MPI-BGC), who developed Flora Incognita together with scientists from Ilmenau University of Technology. ‘This means that millions of time-stamped plant observations from different regions have now accumulated.’

Comprehensible changes in the annual cycle

The algorithm draws on almost 10 million observations of almost 3,000 plant species that were made via the app between 2018 and 2021 in Germany. Although plants have different flowering and vegetation phases, the researchers were able to use the algorithm to determine ‘group behaviour’ and in turn derive ecological patterns and track their changes within an annual cycle. For example, ecosystems by the river would differ from those in the mountains, where phenological events start later, the researchers write in the journal ‘Methods in Ecology and Evolution’.

Algorithm takes user behaviour of the app into account

Accordingly, the algorithm also takes into account the fact that plant observation via the app by users is not systematic compared to traditional data collection, but is more frequent at weekends and in densely populated areas.  ‘Our method can automatically isolate these effects from the ecological patterns,’ explains first author Karin Mora, a scientist at Leipzig University and iDiv. ’Fewer observations do not mean that we cannot record the synchronisation. Of course, there are very few observations in the depths of winter, but there are also very few plants that can be observed.’

The researchers are convinced that the new algorithm will allow them to better analyse the effects of climate change on the plant world. The consequences of the seasonal shifts for the relationship between plants and insects, and therefore for food security, are still being investigated.

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