First automatic size measurements for the separation of dwarf birch and tree birch pollen in MIS 6 to MIS 1 records from Northern Germany

Research output: Journal contributionsJournal articlesResearchpeer-review

Authors

  • Martin Theuerkauf
  • Elias Nehring
  • Alexander Gillert
  • Philipp Morten Bodien
  • Michael Hein
  • Brigitte Urban

During past glacial periods, the land cover of Northern Eurasia and North America repeatedly shifted between open steppe tundra and boreal/temperate forest. Tracking these changes and estimating the coverage of open versus forested vegetation in past glacial and interglacial landscapes is notoriously difficult because the characteristic dwarf birches of the tundra and the tree birches of the boreal and temperate forests produce similar pollen grains that are difficult to distinguish in the pollen record. One objective approach to separating dwarf birch pollen from tree birch pollen is to use grain size statistics. However, the required grain size measurements are time-consuming and, therefore, rarely produced. Here, we present an approach to automatic size measurement based on image recognition with convolutional neural networks and machine learning. It includes three main steps. First, the TOFSI algorithm is applied to detect and classify pollen, including birch pollen, in lake sediment samples. Second, a Resnet-18 neural network is applied to select the birch pollen suitable for measurement. Third, semantic segmentation is applied to detect the outline and the area and mean width of each detected birch pollen grain. Test applications with two pollen records from Northern Germany, one covering the Lateglacial-Early Holocene transition and the other covering the Mid to Late Pleistocene transition, show that the new technical approach is well suited to measure the area and mean width of birch pollen rapidly (>1000 per hour) and with high accuracy. Our new network-based tool facilitates more regular size measurements of birch pollen. Expanded analysis of modern birch pollen will help to better understand size variations in birch pollen between birch species and in response to environmental factors as well as differential sample preparation. Analysis of fossil samples will allow better quantification of dwarf birch versus tree birch in past environments.

Original languageEnglish
Article numbere11510
JournalEcology and Evolution
Volume14
Issue number6
Number of pages17
ISSN2045-7758
DOIs
Publication statusPublished - 01.06.2024

Bibliographical note

Publisher Copyright:
© 2024 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

    Research areas

  • automatic pollen recognition, convolutional neural networks, dwarf birch, Holocene, machine learning, middle and upper Pleistocene, TOFSI, tree birch
  • Biology

DOI

Recently viewed

Publications

  1. Creative Work, Self-Organizing, and Autonomist Potentiality
  2. Fat or lean
  3. Construal level theory
  4. Effects of different video- or text-based reflection stimuli on pre-service teachers’ emotions, immersion, cognitive load and knowledge-based reasoning
  5. Multilevel Water Governance and Problems of Scale
  6. The interaction of precipitation and deformation in a binary Mg-Ca alloy at elevated temperatures
  7. Emotions and multimedia learning
  8. Disciplines and Doubts
  9. Das Alltagsmedium Blatt
  10. Evaluationbedarf des § 650c BGB
  11. Experimental and numerical analysis of material flow in porthole die extrusion
  12. Handbook of Philosophy of Management
  13. Monitoring of methotrexate chlorination in water
  14. Beyond the Network
  15. What explains the performance of participatory governance?
  16. Illegal Migration in Postfordism
  17. Guest editorial
  18. Conceptualizing sustainable consumption
  19. Acknowledging temporal diversity in sustainability transformations at the nexus of interconnected systems
  20. Transcending the Locality of Grassroots Initiatives
  21. The role of knowledge and information in innovation
  22. Internet-Based Cognitive Behavioral Therapy for Insomnia
  23. Applying the principles of green engineering to cradle-to-cradle design
  24. Geschlechtsneutralität
  25. Resisting foundations
  26. How to measure the substantive representation of traditionally excluded groups in comparative research
  27. “From Within Fur and Feathers”
  28. Welcome home! Introducing SocSES
  29. New incremental methods for springback compensation by stress superposition
  30. Lagrangian perspectives on turbulent superstructures in Rayleigh-Bénard convection
  31. Logistical futures the chinese dream, debordering labor, and migration
  32. Patterns of organizational (sub)culture and their influence on organizational effectiveness
  33. Indigenous and local knowledge in biocultural approaches to sustainability:
  34. Two high-mountain burnet moth species (Lepidoptera, Zygaenidae) react differently to the global change drivers climate and land-use
  35. Textkommentierungen
  36. Pathways for Transformation
  37. The Basic Values of Russian and European Schoolteachers
  38. Don't ignore the floor
  39. The Folding of the American Working Class in Mad Men