Max Planck Institute for Biogeochemistry

A light blue banner on which numerous circles are depicted in which various flowers can be seen. The three flowers that make up the home screen of the Flora Incognita app are placed in the centre of the banner.

Publications of Samuel Levis

All genres

Journal Article (1)

Journal Article

Sitch, S.; Smith, B.; Prentice, I. C.; Arneth, A.; Bondeau, A.; Cramer, W.; Kaplan, J. O.; Levis, S.; Lucht, W.; Sykes, M. T. et al.; Thonicke, K.; Venevsky, S.: Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Global Change Biology 9 (2), pp. 161 - 185 (2003)

MPG.PuRe

Contact

Dr. Jana Wäldchen

Group Leader +49 3677 69-4849 jwald@...

News

Close-up of three different cranesbill species growing right next to each other and looking very similar, labeled with scientific names: Geranium molle, Geranium dissectum, and Geranium pyrenaicum.

What exactly is a species?

August 23, 2024

From the Greek philosopher Aristotle to Charles Darwin to the present day, scientists have dealt with this fundamental question of biology. Contrary to public perception, however, it is still largely unresolved. Scientists have now presented a new approach for the identification and delimitation of species using artificial intelligence (AI).

In a grassy field, a hand holds a smartphone capturing an image of bright yellow flowers. The phone screen shows the flowers in focus, with green grass in the background.

How a plant app helps to identify the consequences of climate change

July 09, 2024

A research team led by the German Centre for Integrative Biodiversity Research (iDiv) and Leipzig University has developed an algorithm that analyses observational data from the Flora Incognita app. The novel can be used to derive ecological patterns that could provide valuable information about the effects of climate change on plants.

A detailed view of a grass stem releasing pollen, with numerous pollen particles visibly floating in the air, set against a softly blurred green background.

Precisely predicting allergenic pollen with AI

April 19, 2024

The new research project "PollenNet" aims to use artificial intelligence to accurately predict the spread of pollen. In order to improve allergy prevention, experts are bringing together the latest interdisciplinary findings from a wide range of fields.