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

Global Change Biology

Volumn 20, Issue 4, 2014, Pages 1251-1263

  Allen, Jenica M ^a   Terres, Maria A ^b   Katsuki, Toshio ^c   Iwamoto, Kojiro ^c   Kobori, Hiromi ^d   Higuchi, Hiroyoshi ^e   Primack, Richard B ^f   Wilson, Adam M ^g   Gelfand, Alan ^b   Silander, John A ^a  

^a UNIVERSITY OF CONNECTICUT   (United States)

^b Duke University   (United States)

^c FORESTRY AND FOREST PRODUCTS RESEARCH INSTITUTE   (Japan)

^d TOKYO CITY UNIVERSITY   (Japan)

^e KEIO UNIVERSITY   (Japan)

^f USA   (United States)

^g YALE UNIVERSITY   (United States)

Author keywords

Bayesian; Prunus yedoensis; Prunus jamasakura; Prunus lannesiana; Prunus spachiana; Survival model; Time to event model; Vernalization; Weather

Indexed keywords

BAYESIAN ANALYSIS; CLIMATE CHANGE; CLIMATE EFFECT; FLOWERING; NUMERICAL MODEL; PHENOLOGY; PROBABILITY; REGRESSION ANALYSIS; SURVIVAL; TIME SERIES ANALYSIS; TREE; VERNALIZATION;

HACHIOJI; HONSHU; JAPAN; KANTO; TOKYO [KANTO];

AVES; HEXAPODA; PRUNUS; PRUNUS JAMASAKURA; PRUNUS SERRULATA VAR. LANNESIANA; PRUNUS SUBHIRTELLA;

BAYES THEOREM; BIOLOGICAL MODEL; CLIMATE CHANGE; FLOWER; JAPAN; LONGITUDINAL STUDY; PROBABILITY; PRUNUS;

BAYES THEOREM; CLIMATE CHANGE; FLOWERS; JAPAN; LONGITUDINAL STUDIES; MODELS, BIOLOGICAL; PROBABILITY; PRUNUS;

EID: 84896717281     PISSN: 13541013     EISSN: 13652486     Source Type: Journal    
DOI: 10.1111/gcb.12364     Document Type: Article

References (62)

1. Alburquerque N, García-Montiel F, Carrillo A, Burgos L (2008) Chilling and heat requirements of sweet cherry cultivars and the relationship between altitude and the probability of satisfying the chill requirements. Environmental and Experimental Botany, 64, 162-170.
2. Anderson JV, Chao WS, Horvath DP (2001) A current review on the regulation of dormancy in vegetative buds. Weed Science, 49, 581-589.
3. Arora R, Rowland LJ, Tanino K (2003) Induction and release of bud dormancy in woody perennials: a science comes of age. HortScience, 38, 911-921.
4. Basler D, Körner C (2012) Photoperiod sensitivity of bud burst in 14 temperate forest tree species. Agricultural and Forest Meteorology, 165, 73-81.
5. Burkle LA, Marlin JC, Knight TM (2013) Plant-pollinator interactions over 120 years: loss of species, co-occurrence, and function. Science, 339, 1611-5.
6. Caffarra A, Donnelly A, Chuine I, Jones MB (2011) Modelling the timing of Betula pubescens budburst. I. Temperature and photoperiod: a conceptual model. Climate Research, 46, 147-157.
7. Cannell MGR, Smith RI (1984) Spring frost damage on young Picea sitchensis 2. Predicted dates of budburst and probability of frost damage. Forestry, 57, 177-197.
8. Cannell MGR, Smith RI (1986) Climatic warming, spring budburst and frost damage on trees. Journal of Applied Ecology, 23, 177-191.
9. Cesaraccio C, Spano D, Snyder RL, Duce P (2004) Chilling and forcing model to predict bud-burst of crop and forest species. Agricultural and Forest Meteorology, 126, 1-13.
10. Chuine I (2000) A unified model of budburst in trees. Journal of Theoretical Biology, 207, 337-347.
11. Chuine I, Morin X, Buggman H (2010) Warming, Photoperiods, and tree Phenology. Science, 329, 277-278.
12. Chung U, Jung J-E, Seo H-C, Yun JI (2009) Using urban effect corrected temperature data and a tree phenology model to project geographical shift of cherry flowering date in South Korea. Climatic Change, 93, 447-463.
13. Chung U, Mack L, Yun JI, Kim SH (2011) Predicting the timing of cherry blossoms in Washington, DC and Mid-Atlantic states in response to climate change. PLoS ONE, 6, e27439.
14. Clark JS (2004) Why environmental scientists are becoming Bayesians. Ecology Letters, 8, 2-14.
15. Cook BI, Wolkovich EM, Parmesan C (2012) Divergent responses to spring and winter warming drive community level flowering trends. Proceedings of the National Academy of Sciences of the United States of America, 109, 9000-9005.
16. Cox DR (1972) Regression models and life tables. Journal of Royal Statistical Society Series B (Methodological), 34, 187-220.
17. Cox DR, Oakes D (1984) Analysis of Survival Data. CRC Press, New York.
18. Dasguptaa AS, Self G, Dadgupta S (2007) Non-identifiable parametric probability models and reparametrization. Journal of Statistical Planning and Inference, 137, 3380-3393.
19. Dirlewanger E, Quero-García J, Le Dantec L et al. (2012) Comparison of the genetic determinism of two key phenological traits, flowering and maturity dates, in three Prunus species: peach, apricot, and sweet cherry. Heredity, 109, 280-292.
20. Ellison AM (2004) Bayesian inference in ecology. Ecology Letters, 7, 509-520.
21. Gelman A, Carlin JB, Stern HS, Rubin DB (2004) Bayesian Data Analysis. Chapman & Hall/CRC, Boca Raton.
22. Gienapp P, Hemerik L, Visser ME (2005) A new statistical tool to predict phenology under climate change scenarios. Global Change Biology, 11, 600-606.
23. Gonzalez-Megias A, Menendez R (2012) Climate change effects on above- and below-ground interactions in a dryland ecosystem. Philosophical Transactions of the Royal Society B, 367, 3115-3124.
24. Hanninen H (1990) Modelling bud dormancy release in trees from cool and temperate regions. Acta Forestalia Fennica, 213, 1-47.
25. Heide OM (2008) Interaction of photoperiod and temperature in the control of growth and dormancy of Prunus species. Scientia Horticulturae, 115, 309-314.
26. Iizumi T, Semenov MA, Nishimori M, Ishigooka Y, Kuwagata T (2012) ELPIS-JP: a dataset of local-scale daily climate change scenarios for Japan. Philosophical Transactions of the Royal Society - A, 370, 1121-1139.
27. Jimenez S, Reighard GL, Bielenberg DG (2010) Gene expression of DAM5 and DAM6 is suppressed by chilling temperatures and inversely correlated with bud break rate. Plant Molecular Biology, 73, 157-167.
28. de Jong R, de Bruin S (2012) Linear trends in seasonal vegetation time series and the modifiable temporal unit problem. Biogeosciences, 9, 71-77.
29. Kramer K (1994) Selecting a model to predict the onset of growth of Fagus sylvatica. Journal of Applied Ecology, 31, 172-181.
30. Linkosalo T, Häkkinen R, Hänninen H (2006) Models of the spring phenology of boreal and temperate trees: is there something missing? Tree Physiology, 26, 1165-1172.
31. Luedeling E, Zhang M, McGranahan G, Leslie C (2009a) Validation of winter chill models using historic records of walnut phenology. Agricultural and Forest Meteorology, 149, 1854-1864.
32. Luedeling E, Zhang M, Luedeling V, Girvetz EH (2009b) Sensitivity of winter chill models for fruit and nut trees to climatic changes expected in California's Central Valley. Agriculture, Ecosystems and Environment, 133, 23-31.
33. Martinussen T, Scheike TH (2006) Dynamic Regression Models for Survival Data. Springer, New York.
34. McKee G (2012) Cherries profile. Agricultural Marketing Center. Available at: http://www.agmrc.org/commodities__products/fruits/cherry-profile/ (accessed 19 April 2013).
35. Menzel A, Sparks T, Estrella N et al. (2006) European phenological response to climate change matches the warming pattern. Global Change Biology, 12, 1969-1976.
36. Miller-Rushing A, Katsuki T, Primack R, Ishii Y, Lee SD, Higuchi H (2007) Impact of global warming on a group of related species and their hybrids: cherry tree (Rosaceae) flowering at Mt. Takao, Japan. American Journal of Botany, 94, 1470-1478.
37. Miller-Rushing AJ, Inouye D, Primack RB (2008) How well do first flowering dates measure plant responses to climate change? The effects of population size and sampling frequency. Journal of Ecology, 96, 1289-1296.
38. Nagata H, Yurugi Y (1982) Phenological studies in woody plants (II) flowering in cherry trees. Bulletin of the Faculty of Agriculture Mie University, 64, 11-20.
39. National Cherry Blossom Festival (2013) Available at: http://www.nationalcherryblossomfestival.org/about/links/ (accessed 21 February 2013).
40. Nord EA, Lynch JP (2009) Plant phenology: a critical controller of soil nutrient resource acquisition. Journal of Experimental Botany, 60, 1927-1937.
41. Parmesan C, Yohe G (2003) A globally coherent fingerprint of climate change impacts across natural systems. Nature, 421, 37-42.
42. Pau S, Wolkovich EM, Cook BI et al. (2011) Predicting phenology by integrating ecology, evolution and climate science. Global Change Biology, 17, 3633-3643.
43. Plummer M, Best N, Cowles K, Vines K (2006) CODA: convergence diagnosis and output analysis for MCMC. R News, 6, 7-11.
44. van de Pol M, Cockburn A (2011) Identifying the critical climatic time window that affects trait expression. The American Naturalist, 177, 698-707.
45. Polgar CA, Primack RB (2011) Leaf-out phenology of temperate woody plants: from trees to ecosystems. New Phytologist, 191, 926-941.
46. Primack RB, Ibáñez I, Higuchi H, Lee SD, Miller-Rushing AJ, Wilson AM, Silander JA (2009) Spatial and interspecific variability in phenological responses to warming temperatures. Biological Conservation, 142, 2569-2577.
47. R Core Team (2011) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
48. Richardson EA, Seeley SD, Walker DR (1974) A model for estimating the completion of rest for 'Redhaven' and 'Elberta' peach trees. HortScience, 9, 331-332.
49. Richardson AD, Hollinger DY, Dail DB, Lee JT, Munger JW, O'Keefe J (2009) Influence of spring phenology on seasonal and annual carbon balance in two contrasting New England forests. Tree Physiology, 29, 321-331.
50. Root TL, MacMynowski DP, Mastrandrea MD, Schneider SH (2005) Human-modified temperatures induce species changes: joint attribution. Proceedings of the National Academy of Science of the United States of America, 102, 7465-7469.
51. Sakurai R, Jacobson SK, Kobori H, Primack R, Oka K, Komatsu N, Machida R (2011) Culture and climate change: Japanese cherry blossom festivals and stakeholders' knowledge and attitudes about global climate change. Biological Conservation, 144, 654-658.
52. Sarvas R (1974) Investigations on the annual cycle of trees. II. Autumn dormancy and winter dormancy. Communicationes Instituti Forestalis Fenniae, 84, 1-101.
53. Schaber J, Badeck F-W (2003) Physiology-based phenology models for forest tree species in Germany. International Journal of Biometeorology, 47, 193-201.
54. Sherman R, Mullen R, Haomin L, Zhendong F, Yi W (2008) Spatial patterns of plant diversity and communities in Alpine ecosystems of the Hengduan Mountains, northwest Yunnan, China. Journal of Plant Ecology, 1, 117-136.
55. Spiegelhalter DJ, Best NG, Carlin BP, van der Linde A (2002) Bayesian measures of model complexity and fit (with discussion). Journal of the Royal Statistical Society: Series B, 64, 583-640.
56. Suehrcke H, Bowden RS, Hollands KGT (2013) Relationship between sunshine duration and solar radiation. Solar Energy, 92, 160-171.
57. Terres MA, Gelfand AE, Allen JM, Silander JA (2013) Analyzing first flowering event data using survival models with space and time-varying covariates. Environmetrics, 24, 317-331.
58. Thompson R, Clark RM (2006) Spatio-temporal modelling and assessment of within-species phenological variability using thermal time methods. International Journal of Biometeorology, 50, 312-322.
59. Venables WN, Ripley BD (2002) Modern Applied Statistics with S. Springer, New York. 512 pp.
60. Visser ME, Schaper SV, Holleman LJM, Dawson A, Sharp P, Gienapp P, Caro SP (2011) Genetic variation in cue sensitivity involved in avian timing of reproduction. Functional Ecology, 25, 868-877.
61. Wilson AM, Latimer AM, Silander JA Jr, Gelfand AE, de Klerk H (2010) Hierarchical Bayesian model of wildfire in a Mediterranean biodiversity hotspot: Implications of weather variability and global circulation. Ecological Modelling, 22, 106-112.
62. Yua H, Luedeling E, Xu J (2010) Winter and spring warming result in delayed spring phenology on the Tibetan Plateau. Proceedings of the National Academy of Sciences, 107, 22151-22156.