Shifting Seasons: Phenological evidence from observations, reconstructions, measurements and models (co-sponsored by PAGES & ILEAPS)
Convener: T. Rutishauser  | Co-Convener: Menzel 
Oral Programme
 / Tue, 21 Apr, 08:30–12:00  / Room 14
Poster Programme
 / Attendance Tue, 21 Apr, 17:30–19:00  / Halls X/Y

The IPCC AR4 report from 2007 presented unequivocal evidence of regional to global-scale change in seasonality, as evidenced by plant and animal phenological records. Observations from all continents and several oceans now show that many physical and biological natural systems are being affected by regional climate change, particularly increases in temperature. To allow a consistent global analysis, AR4 focused only on significant trends from traditional phenological observations during the 20-year period between 1970 and 1990. However, there has been much additional research in recent years that lends new insights into spatial and temporal patterns of interrelationships between climate change and organisms, with attendant impacts on carbon dynamics, species interactions, biogeochemistry, etc. This new research has focused on novel investigations of data, and the development and application of new methods and techniques for investigation of phenology. However, robust identification of long-term centennial phenological trends and of systematic decadal fluctuations in biotic and abiotic variables requires compilation and analysis of much longer time series from historical evidence. Integration of historical and contemporary data, on global scales, will be required to reliably understand the processes underlying phenological dynamics. This session would also serve as an opportunity to discuss and strategize on the development of a global network of detailed regional and seasonal observations of phenology.

Therefore, we invite contributions with cross-disciplinary perspectives that present seasonality changes based on recent plant and animal phenological observations, historical documentary sources, or seasonality measurements using climate data, remote sensing, flux measurements or modelling studies. We seek contributions across spatial and temporal scales that compare and integrate seasonality changes across methods and that advance our understanding of seasonality response to long-term climate change and single extreme events.