Flora Incognita Update

Our new release brings you a modern and simplified user experience, and a whole bunch of new features to help you further enjoy your plant findings:

Identify Plants:

  • The new user interface is more modern and clear.
  • It’s now easier to capture and identify a plant in nature.
  • You can disable the autofocus with a new camera feature to make it much easier to take sharp photos of small objects.

Collect plant findings:

  • You can add pictures to an observation after the observation.
  • You can use your own keywords to sort and filter your plant findings more easily.
  • You can now view and filter your plant findings on a map.
  • You can more easily browse the general species list by using numerous filters.

Availability:

  • Even without a personal profile, you can transfer your data to a new device.
  • You can save Flora Incognita pictures in your gallery.

Fact sheets:

  • We have added extensive information on invasive species in Central Europe.

Promote cultivation of wild fruit

In the Wild Fruit Project of the Austrian Federal Forest Research Center (BfW), measures are being taken to secure and maintain the biodiversity of rare, native wild fruit trees in Austria – an opportunity for silviculture and biodiversity in times of climate change. The Flora Incognita project provides important distribution information on endangered wild fruit trees for this project.

For more information, please visit the following website:  https://www.bfw.gv.at/anbau-wildobst-foerderung/

Photo: BPWW/N.Novak

Digital beekeeping to learn and play

With the “beeactive” app from the Würzburg Bee Research Association, children and young people can playfully learn more about bees and the biodiversity of various wild plants in their environment. The aim is to bring nature conservation and species protection into focus and to broaden their awareness of this. Flora Incognita provides the automatic identification of plant species as an important game content of “beeactive”.

The core principle of the app “beeactive” is the playful accompaniment of the virtual beekeeper Melli Fera and thus the establishment and care of digital bee colonies. Users can place individual beehives on an interactive map and search the real surroundings of the bee colony for flowering plants within a certain radius. The plants found are then automatically identified directly by the app. In this way, the virtual bee colony is supplied with pollen and nectar and the users can expand their knowledge of the species at the same time. The higher the number of plant species found, the better the digital bee colony develops and new hives may be added. In this way, users can also be motivated to sow their own bee-friendly flowering meadows. In addition, they support the creation of local and regional flowering maps with the numerous plant photos. The game is supplemented by a wide range of information on the ecology of honey bees and wild bees, as well as on the basics of ecological relationships. An integrated quiz allows direct application of the new knowledge and consolidates what has been learned.

For more information, please visit the following website: https://beeactive.app/.

 

The app “beeactive” was developed by Porf. Tautz and Florian Schimpf and financed with funds from the Bayerische Sparkassenstiftung. It is available free of charge in the Google Play Store and the Apple App Store.

Automated plant identification with the Flora Helvetica app

We are pleased to announce a successful collaboration with Haupt Verlag. Since version 2.3, the Flora Helvetica app includes a function for the automatic image-based identification of plants, which is provided as part of the Flora Incognita project. Thus, for the first time, it is possible with a single app to identify plants automatically as well as manually with the integrated identification key.

For more information about the Flora Helvetica app, please visit the following page:

https://www.flora-helvetica.ch/app

How smartphones can help detect ecological change

Leipzig/Jena/Ilmenau. Mobile apps like Flora Incognita that allow automated identification of wild plants cannot only identify plant species, but also uncover large scale ecological patterns. These patterns are surprisingly similar to the ones derived from long-term inventory data of the German flora, even though they have been acquired over much shorter time periods and are influenced by user behaviour. This opens up new perspectives for rapid detection of biodiversity changes. These are the key results of a study led by a team of researchers from Central Germany, which has recently been published in Ecography.

With the help of Artificial Intelligence, plant species today can be classified with high accuracy. Smartphone applications leverage this technology to enable users to easily identify plant species in the field, giving laypersons access to biodiversity at their fingertips. Against the backdrop of climate change, habitat loss and land-use change, these applications may serve another use: by gathering information on the locations of identified plant species, valuable datasets are created, potentially providing researchers with information on changing environmental conditions.

But is this information reliable – as reliable as the information provided by data collected over long time periods? A team of researchers from the German Centre for Integrative Biodiversity Research (iDiv), the Remote Sensing Centre for Earth System Research (RSC4Earth) of Leipzig University (UL) and Helmholtz Centre for Environmental Research (UFZ), the Max Planck Institute for Biogeochemistry (MPI-BGC) and Technical University Ilmenau wanted to find an answer to this question. The researchers analysed data collected with the mobile app Flora Incognita between 2018 and 2019 in Germany and compared it to the FlorKart database of the German Federal Agency for Nature Conservation (BfN). This database contains long-term inventory data collected by over 5,000 floristic experts over a period of more than 70 years.

Mobile app uncovers macroecological patterns in Germany

The researchers report that the Flora Incognita data, collected over only two years, allowed them to uncover macroecological patterns in Germany similar to those derived from long-term inventory data of German flora. The data was therefore also a reflection of the effects of several environmental drivers on the distribution of different plant species.

However, directly comparing the two datasets revealed major differences between the Flora Incognita data and the long-term inventory data in regions with a low human population density. “Of course, how much data is collected in a region strongly depends on the number of smartphone users in that region,” said last author Dr. Jana Wäldchen from MPI-BGC, one of the developers of the mobile app. Deviations in the data were therefore more pronounces in rural areas, except for well-known tourist destinations such as the Zugspitze, Germany’s highest mountain, or Amrum, an island on the North Sea coast.

User behaviour also influences which plant species are recorded by the mobile app. “The plant observations carried out with the app reflect what users see and what they are interested in,” said Jana Wäldchen. Common and conspicuous species were recorded more often than rare and inconspicuous species. Nonetheless, the large quantity of plant observations still allows a reconstruction of familiar biogeographical patterns. For their study, the researchers had access to more than 900,000 data entries created within the first two years after the app had been launched.

Automated species recognition bears great potential

The study shows the potential of this kind of data collection for biodiversity and environmental research, which could soon be integrated in strategies for long-term inventories. “We are convinced that automated species recognition bears much greater potential than previously thought and that it can contribute to a rapid detection of biodiversity changes,” said first author Miguel Mahecha, professor at UL and iDiv Member. In the future, a growing number of users of apps like ‘Flora Incognita’ could help detect and analyse ecosystem changes worldwide in real time.

The Flora Incognita mobile app was developed jointly by the research groups of Dr. Jana Wäldchen at MPI-BGC and the group of Professor Patrick Mäder at TU Ilmenau. It is the first plant identification app in Germany using deep neural networks (deep learning) in this context. Fed by thousands of plant images, that have been identified by experts, it can already identify over 4,800 plant species.

“When we developed Flora Incognita, we realized there was a huge potential and growing interest in improved technologies for the detection of biodiversity data. As computer scientists we are happy to see how our technologies make an important contribution to biodiversity research,“ said co-author Patrick Mäder, professor at TU Ilmenau.

Original publication
Miguel D. Mahecha, Michael Rzanny, Guido Kraemer, Patrick Mäder, Marco Seeland, Jana Wäldchen (2021). Crowd-sourced plant occurrence data provide a reliable description of macroecological gradients. Ecography, DOI: 10.1111/ecog.0549

(Text: Kati Kietzmann, iDiv)

Kosmos „Was blüht den da“ in our Flora Incognita App

„Was blüht denn da?“ –  always mobile!

All buyers of the current edition of the two books “Was blüht denn da? Das Original” and “Was blüht denn da? Der Fotoband” have the possibility to have the contents of their “Was blüht denn da?” with them on their smartphone.

After entering a code in our identification app “Flora Incognita”, the corresponding texts and images will be displayed for all plants included in “Was blüht denn da?”.

For further questions please contact directly KOSMOS.