1. Detecting the Onset of Spring in the Midwest and Northeast United States: An Integrated Approach Jonathan M. Hanes Ph.D. Student Department of Geography University of Wisconsin-Milwaukee

2. Introduction Phenology –Plant & animal life cycle events triggered by environmental changes (i.e. temperature) Example: Onset of spring in deciduous vegetation Primary methods of assessing plant phenology –Native species observations –Simulated phenology based on cloned species –Satellite imagery

3. Native Species Phenology Advantages –Adapted to the local environment Genetic variability can be evaluated Represent a precise signal of a certain location Disadvantages –Lack of geographically distributed observations –Geographical variations in response Limit comparisons between different locations

4. Simulated Phenology Advantages –Large geographical coverage Require simple input data (i.e. temperature observations) –Standardized response to the environment Disadvantages –Model insufficiencies Based on small number of species Simulates a limited set of events

5. Satellite Imagery Advantages –Large geographical coverage –Integrated ecosystem-scale response Disadvantages –Temporal resolution –Cloud cover & sensor error –Short period of record –Limited measurements Start of season (SOS), end of season (EOS), growing season length

6. Integrated Approach to Phenology Combines native species phenology, simulated phenology, and satellite SOS measurements Collaborator: Prof. Mark D. Schwartz Study Areas (2000-2006) –UW-Milwaukee Field Station –Harvard Forest, MA –Park Falls, WI

7. Satellite Data Satellite-derived SOS measurements at all sites –Fisher’s Method (Fisher et al. 2006) MODIS –Delayed Moving Average (Reed et al. 1994) MODIS NDVI & EVI –Seasonal Midpoint (White et al. 1997,1999,2002) MODIS NDVI & EVI –Boston Method (Zhang et al. 2003) MODIS EVI

8. Surface Data Bud-burst dates of native species –27 native species at UWM Field Station –33 native species at Harvard Forest Spring Index (SI) first bloom dates at all sites –Schwartz & Marotz 1986, 1988

9. Research Questions How are SOS measures related to each other? Which SOS measure is most similar to SI first bloom? How does native species bud-burst relate to SI first bloom & SOS measures? How can all phenological measures be compared?

10. SOS Comparisons Correlations differ at the 3 sites –Correlations are strong –Fisher’s method is similar to other SOS measures at all sites –No other consistent similarities

11. SOS Comparison

14. SOS-SI First Bloom Comparison Variable correlations

15. SI First Bloom-Native Species Comparison High correlation between average bud-burst of 4 native species & SI first bloom –Sugar maple (Acer saccharum) –Hawthorne (Crataegus sp.) –White ash (Fraxinus americana) –Witch hazel (Hamamelis virginia) –r=.842 at UWM Field Station –r=.824 at Harvard Forest

16. SOS-Native Species Comparison Variable correlations with average bud-burst of 4 native species

17. Comparison of All Measures Use hierarchical clustering –Organizes native species into groups based on bud-burst –Examine which clusters represent the signal captured by satellite sensors –Compare average bud-burst of each cluster with SOS and SI first bloom

18. Clustering Approach

19. 4 Clusters of Native Species UWM Field Station Harvard Forest

20. 3 Clusters of Native Species UWM Field Station Harvard Forest

21. Comparison of all Measures “Phenological footprints” –Standardizes native species bud-burst and SOS to SI first bloom –Uses simulated phenology to connect SOS & native species –Useful for comparing different locations

25. Conclusions Correlation between SOS measures vary at each site –Possible combination of issues Different locations Potential errors from clouds, atmosphere, & sensors SOS is similar to native species & SI first bloom –Similarity varies by location –Fisher’s SOS method is consistently similar Uses a logistic growth model Unique method of measuring vegetation (GVF)

26. Conclusions Clustering of native species phenology –Reveals site-specific differences in phenological response –Correlated with SI first bloom and SOS Phenological footprint –Comparison of phenology at multiple sites –Can be used with different phenological measures