Plant phenologies are generally observed for discrete plant individuals removed from their ecological contexts. This project has intensively recorded spring tree/shrub/grass phenologies in a mixed temperate forest located in northern Wisconsin. In summer 2005, 216 trees/shrubs from representative forest species were sampled in a 625m by 275m large area with a cyclic sampling scheme (this is a quarter of a now expanded study area). Trees were identified to species along with DBH measurements. Plant communities and microenvironments were also empirically identified during the initial and follow-up field campaigns. Spring phenologies were scored with stringent field protocols (for both deciduous and coniferous species) every other day during the springs of 2006 and 2007. Grass phenologies were also recorded with a digital camera during the year of 2007. Air temperature and humidity were measured with HOBO sensors continuously throughout the spring seasons. Other ancillary data used include LiDAR DEM/Tree Heights, as well as high resolution multispectral images (IKONOS and QuickBird).
Results/Conclusions
Over the study area, no consistent spatial autocorrelations were detected among trees of the same species, suggesting a generally individualistic manner of phenological behaviors intraspecifically. Among the few exceptions, Populus tremuloides (trembling aspen, late cohort) showed spatial continuity within a 75 m radius in 2007 data. In regard to environmental drivers of phenology, no coherent correlations have been found between phenology and spatial variations of growing degree hours (GDHs), topography (elevation and aspects) and soil types. In addition, no coherent correlations exist between phenology and DBH and LiDAR estimated tree heights for most species, except for aspen which showed that bigger trees have earlier budbursts. Averaged species phenology across the study area is highly sensitive to weather fluctuations (especially to GDHs averaged over the entire study area for the previous 2 days), showing a corporate response to the environment at the population scale. Using both high resolution satellite images and ground survey data, community and landscape level phenologies were also derived. This study tackles questions related to plant phenology within its intricate ecological context, and provides a detailed account of phenological behaviors across scales within a typical seasonal forest.
