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<p>We present a unique dataset of historical tropical tree phenology observations at two sites from different bioclimatic regions across the Congo Basin. We cover both the Atlantic Mayombe forest and the tropical forest in the central Congo Basin. To our knowledge this is&#xa0;the complete extant historical (1937–1957) phenology data across the Congo basin. The data contains ~10 million observations of 876 species, across 6339 individuals, and phenology metrics including leaf, flowering, and fruiting phenology. The data were recovered through expert transcription and validated community science based crowdsourcing. These data may provide a reference baseline and key information on how tree species are responding to a changing climate.</p>

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Historical tree phenology data across contrasting sites in the Congo Basin

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月7日

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  • Koen Hufkens,
  • Elizabeth Kearsley,
  • Piet Stoffelen,
  • Steven B. Janssens,
  • Camille Couralet,
  • Margaret Kosmala,
  • Emmanuel Kasongo Yakusu,
  • Donatien Musepena,
  • Dieu-Merci Assumani,
  • Nestor K. Luambua,
  • Benjamin Toirambe,
  • Jean-Remy Makana,
  • Corneille Ewango,
  • Tom De Mil,
  • Marijn Bauters,
  • Wannes Hubau,
  • Elasi Ramanzani Kitima,
  • José Mbifo Ndiapo,
  • Adelard Lonema Chuda,
  • Andrew D. Richardson,
  • Lisa Wingate,
  • Bhély Angoboy Ilondea,
  • Hans Beeckman,
  • Jan Van den Bulcke,
  • Pascal Boeckx,
  • Hans Verbeeck

摘要

We present a unique dataset of historical tropical tree phenology observations at two sites from different bioclimatic regions across the Congo Basin. We cover both the Atlantic Mayombe forest and the tropical forest in the central Congo Basin. To our knowledge this is the complete extant historical (1937–1957) phenology data across the Congo basin. The data contains ~10 million observations of 876 species, across 6339 individuals, and phenology metrics including leaf, flowering, and fruiting phenology. The data were recovered through expert transcription and validated community science based crowdsourcing. These data may provide a reference baseline and key information on how tree species are responding to a changing climate.