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Long‐term trends in global flowering phenology

Abstract

- Flowering phenology is an indicator of the impact of climate change on natural systems. Anthropogenic climate change has progressed over more than two centuries, but ecological studies are mostly short in comparison. Here we harness the large-scale digitization of herbaria specimens to investigate temporal trends in flowering phenology at a global scale.
- We trained a convolutional neural network model to classify images of angiosperm herbarium specimens as being in flower or not in flower. This model was used to infer flowering across 8 million specimens spanning a century and global scales. We investigated temporal trends in mean flowering date and flowering season duration within ecoregions.
- We found high diversity of temporal trends in flowering seasonality across ecoregions with a median absolute shift of 2.5 d per decade in flowering date and 1.4 d per decade in flowering season duration. Variability in temporal trends in phenology was higher at low latitudes than at high latitudes.
- Our study demonstrates the value of digitized herbarium specimens for understanding natural dynamics in a time of change. The higher variability in phenological trends at low latitudes likely reflects the effects of a combination of shifts in temperature and precipitation seasonality, together with lower photoperiodic constraints to flowering.

Category

Academic article

Language

English

Author(s)

  • David Roddan Williamson
  • Tommy Prestø
  • Kristine Bakke Westergaard
  • Beatrice Maria Trascau
  • Vibekke Vange
  • Kristian Hassel
  • Wouter Koch
  • James David Mervyn Speed

Affiliation

  • Norwegian University of Science and Technology
  • SINTEF Ocean / Climate and Environment
  • Norwegian Institute for Nature Research
  • Nord University
  • Unknown

Year

2025

Published in

New Phytologist

ISSN

0028-646X

Publisher

John Wiley & Sons

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