Modeling daily flowering probabilities: expected impact of climate change on Japanese cherry phenology.

Published

Journal Article

Understanding the drivers of phenological events is vital for forecasting species' responses to climate change. We developed flexible Bayesian survival regression models to assess a 29-year, individual-level time series of flowering phenology from four taxa of Japanese cherry trees (Prunus spachiana, Prunus × yedoensis, Prunus jamasakura, and Prunus lannesiana), from the Tama Forest Cherry Preservation Garden in Hachioji, Japan. Our modeling framework used time-varying (chill and heat units) and time-invariant (slope, aspect, and elevation) factors. We found limited differences among taxa in sensitivity to chill, but earlier flowering taxa, such as P. spachiana, were more sensitive to heat than later flowering taxa, such as P. lannesiana. Using an ensemble of three downscaled regional climate models under the A1B emissions scenario, we projected shifts in flowering timing by 2100. Projections suggest that each taxa will flower about 30 days earlier on average by 2100 with 2-6 days greater uncertainty around the species mean flowering date. Dramatic shifts in the flowering times of cherry trees may have implications for economically important cultural festivals in Japan and East Asia. The survival models used here provide a mechanistic modeling approach and are broadly applicable to any time-to-event phenological data, such as plant leafing, bird arrival time, and insect emergence. The ability to explicitly quantify uncertainty, examine phenological responses on a fine time scale, and incorporate conditions leading up to an event may provide future insight into phenologically driven changes in carbon balance and ecological mismatches of plants and pollinators in natural populations and horticultural crops.

Full Text

Duke Authors

Cited Authors

  • Allen, JM; Terres, MA; Katsuki, T; Iwamoto, K; Kobori, H; Higuchi, H; Primack, RB; Wilson, AM; Gelfand, A; Silander, JA

Published Date

  • April 2014

Published In

Volume / Issue

  • 20 / 4

Start / End Page

  • 1251 - 1263

PubMed ID

  • 23966290

Pubmed Central ID

  • 23966290

Electronic International Standard Serial Number (EISSN)

  • 1365-2486

International Standard Serial Number (ISSN)

  • 1354-1013

Digital Object Identifier (DOI)

  • 10.1111/gcb.12364

Language

  • eng