Cargando…
Monitoring of cherry flowering phenology with Google Trends
Google Trends (GT) is an online tool designed for searching for changes over time. We assessed its use for evaluating changes in the timing of cherry flowering phenology, which is of intense interest to Japanese people. We examined the relationship between time-series of relative search volume (RSV:...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9302780/ https://www.ncbi.nlm.nih.gov/pubmed/35862347 http://dx.doi.org/10.1371/journal.pone.0271648 |
_version_ | 1784751708224618496 |
---|---|
author | Shin, Nagai Kotani, Ayumi Tei, Shunsuke Tsutsumida, Narumasa |
author_facet | Shin, Nagai Kotani, Ayumi Tei, Shunsuke Tsutsumida, Narumasa |
author_sort | Shin, Nagai |
collection | PubMed |
description | Google Trends (GT) is an online tool designed for searching for changes over time. We assessed its use for evaluating changes in the timing of cherry flowering phenology, which is of intense interest to Japanese people. We examined the relationship between time-series of relative search volume (RSV: relative change in search requests over time obtained from the GT access engine) and cherry flowering information published on websites (as ground truth) in relation to three famous ancient cherry trees. The time-series of RSV showed an annual bell-shaped seasonal variability, and the dates of the maximum RSV tended to correspond to the dates of full bloom. Our results suggest that GT allows monitoring of multiple famous cherry flowering sites where we cannot obtain long-term flowering data to evaluate the spatiotemporal variability of cherry flowering phenology. |
format | Online Article Text |
id | pubmed-9302780 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-93027802022-07-22 Monitoring of cherry flowering phenology with Google Trends Shin, Nagai Kotani, Ayumi Tei, Shunsuke Tsutsumida, Narumasa PLoS One Research Article Google Trends (GT) is an online tool designed for searching for changes over time. We assessed its use for evaluating changes in the timing of cherry flowering phenology, which is of intense interest to Japanese people. We examined the relationship between time-series of relative search volume (RSV: relative change in search requests over time obtained from the GT access engine) and cherry flowering information published on websites (as ground truth) in relation to three famous ancient cherry trees. The time-series of RSV showed an annual bell-shaped seasonal variability, and the dates of the maximum RSV tended to correspond to the dates of full bloom. Our results suggest that GT allows monitoring of multiple famous cherry flowering sites where we cannot obtain long-term flowering data to evaluate the spatiotemporal variability of cherry flowering phenology. Public Library of Science 2022-07-21 /pmc/articles/PMC9302780/ /pubmed/35862347 http://dx.doi.org/10.1371/journal.pone.0271648 Text en © 2022 Shin et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Shin, Nagai Kotani, Ayumi Tei, Shunsuke Tsutsumida, Narumasa Monitoring of cherry flowering phenology with Google Trends |
title | Monitoring of cherry flowering phenology with Google Trends |
title_full | Monitoring of cherry flowering phenology with Google Trends |
title_fullStr | Monitoring of cherry flowering phenology with Google Trends |
title_full_unstemmed | Monitoring of cherry flowering phenology with Google Trends |
title_short | Monitoring of cherry flowering phenology with Google Trends |
title_sort | monitoring of cherry flowering phenology with google trends |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9302780/ https://www.ncbi.nlm.nih.gov/pubmed/35862347 http://dx.doi.org/10.1371/journal.pone.0271648 |
work_keys_str_mv | AT shinnagai monitoringofcherryfloweringphenologywithgoogletrends AT kotaniayumi monitoringofcherryfloweringphenologywithgoogletrends AT teishunsuke monitoringofcherryfloweringphenologywithgoogletrends AT tsutsumidanarumasa monitoringofcherryfloweringphenologywithgoogletrends |