caa a22 4500 445366990 CHVBK 20180317142933.0 cr unu---uuuuu 170323e20111101xx s 000 0 eng 10.1007/s00484-011-0427-4 doi (NATIONALLICENCE)springer-10.1007/s00484-011-0427-4 Using Self-Organising Maps (SOMs) to assess synchronies: an application to historical eucalypt flowering records [Elektronische Daten] [Irene Hudson, Marie Keatley, Shalem Lee] Self-Organising Map (SOM) clustering methods applied to the monthly and seasonal averaged flowering intensity records of eight Eucalypt species are shown to successfully quantify, visualise and model synchronisation of multivariate time series. The SOM algorithm converts complex, nonlinear relationships between high-dimensional data into simple networks and a map based on the most likely patterns in the multiplicity of time series that it trains. Monthly- and seasonal-based SOMs identified three synchronous species groups (clusters): E. camaldulensis, E. melliodora, E. polyanthemos; E. goniocalyx, E. microcarpa, E. macrorhyncha; and E. leucoxylon, E. tricarpa. The main factor in synchronisation (clustering) appears to be the season in which flowering commences. SOMs also identified the asynchronous relationship among the eight species. Hence, the likelihood of the production, or not, of hybrids between sympatric species is also identified. The SOM pattern-based correlation values mirror earlier synchrony statistics gleaned from Moran correlations obtained from the raw flowering records. Synchronisation of flowering is shown to be a complex mechanism that incorporates all the flowering characteristics: flowering duration, timing of peak flowering, of start and finishing of flowering, as well as possibly specific climate drivers for flowering. SOMs can accommodate for all this complexity and we advocate their use by phenologists and ecologists as a powerful, accessible and interpretable tool for visualisation and clustering of multivariate time series and for synchrony studies. ISB, 2011 Synchrony nationallicence Phenology nationallicence Moran effect nationallicence Eucalypts nationallicence Data visualisation nationallicence SOMs nationallicence Hudson Irene School of Mathematical & Physical Sciences, University of Newcastle, Callaghan, Newcastle, NSW, Australia aut Keatley Marie Department of Forest and Ecosystem Science, University of Melbourne, Melbourne, Victoria, Australia aut Lee Shalem School of Paediatrics and Reproductive Health, University of Adelaide, Adelaide, South Australia aut International Journal of Biometeorology Springer-Verlag 55/6(2011-11-01), 879-904 0020-7128 55:6<879 2011 55 484 https://doi.org/10.1007/s00484-011-0427-4 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00484-011-0427-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Hudson Irene School of Mathematical & Physical Sciences, University of Newcastle, Callaghan, Newcastle, NSW, Australia aut NATIONALLICENCE 700 1- Keatley Marie Department of Forest and Ecosystem Science, University of Melbourne, Melbourne, Victoria, Australia aut NATIONALLICENCE 700 1- Lee Shalem School of Paediatrics and Reproductive Health, University of Adelaide, Adelaide, South Australia aut NATIONALLICENCE 773 0- International Journal of Biometeorology Springer-Verlag 55/6(2011-11-01), 879-904 0020-7128 55:6<879 2011 55 484 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer