Estimation of true dates of various flowering stages at a centennial scale by applying a Bayesian statistical state space model

Nagai Shin, Hakuryu Fujiwara, Shinjiro Sugiyama, Hiroshi Morimoto and Taku M Saitoh

PLOS ONE, 2025, vol. 20, issue 2, 1-15

Abstract: Evaluation of long-term detailed cherry flowering phenology is required for a deep understanding of the sensitivity of spring phenology to climate change and its effect on cultural ecosystem services. Neodani Usuzumi-zakura (Cerasus itosakura) is a famous cherry tree in Gifu, Japan. On the basis of detailed decadal flowering phenology information published on the World Wide Web, we estimated the probability distributions of the year-to-year variability of the true dates of first flowering (FFL), first full bloom (FFB), last full bloom (LFB), and last flowering (LFL) from 1924 to 2024 by applying a Bayesian statistical state space model explained by air temperature data. We verified the estimated values against flowering phenology records of the tree from the literature and a private collection. The true dates of FFL and FFB could be explained by means of daily minimum air temperature from 1 December to 28/29 February and that of daily mean air temperature from 1 to 31 March, and those of LFB and LFL by means of daily mean air temperature from 1 to 10 April. Results were similar when we used air temperature data recorded at weather stations both 1 km and 29 km from the tree. These results indicated that our proposed Bayesian statistical state space model can estimate cherry flowering phenology that takes into account centennial-scale air temperature data recorded at a nearby weather station with a coarse temporal resolution.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0317708

DOI: 10.1371/journal.pone.0317708

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