1. Modeling winter annuals as a function of climate using the satellite-based Enhanced Vegetation Index
Chris Pruden
Mentor: Grant Casady PhD
Arizona Space Grant Consortium Statewide Symposium
April 17, 2010

2. Contents Purpose of research
Introduction to winter annual characteristics and why they are important
Site description of study area in the San Simon watershed
Methods and remote sensing techniques
Results and discussion

3. Statement of Purpose
Determine how climate drives inter-annual variability and abundance of winter annual plants in the San Simon watershed
Relate precipitation and temperature data to predict the abundance of winter annual plants in the San Simon watershed

4. Winter Annual Characteristics
Ephemeral plants that occur widely in the Desert Southwest whose peak growing season is late winter and spring
“Bet Hedging” variety of plants
Tied to variation in precipitation and temperature of the region
Monitoring helps measure environmental change and predict fire regimes
Vital part of the ecosystem
Verbally expand bet hedging to explain the rest
Grasses and forbs
Fire danger
Erosion control
Sensitive species like desert tortoise

5. Winter Annuals

6. Site Description: San Simon Watershed
Watershed area: about 5,828 km2 (2,250 mi2)
Mix of Chihuahuan Desert and Grassland
Courtesy of OALS

7. Methods
Determine the optimal combination to precipitation and temperature data to account for inter-annual variability in winter annual abundance
Used 250m MODIS Enhanced Vegetation Index (EVI) satellite data
Used multiple linear regression on averaged climate and EVI data to select a model

8. Original and Smoothed VI time series
Used peak evi data as an estimate of winter annual abundance. Don’t mention peak evi again
2000
2001
2002
2003
2004
2005
2006
2007
2008
Casady: unpublished

9. PRISM data
Uses point data from climate stations to model a surface of climatic parameters such as precipitation or temperature over a large geographic area
This data has a spatial resolution of 4km.
This data was resampled to match the finer resolution MODIS data (250 meters)

10. Integrating climate data to create model:
Reworked matlab plot for ppt and evi
Scale the y axis for precip (PRISM site)
Units of winter annual abundance are relative but have been related in previous work by casady to kg per hectare production

11. Integrating climate data to create model:
Mention r2
Model is linear combo of precip and temp

12. Results and Discussion
Model demonstrates that a specific combination of precipitation and temperature accounts for inter-annual variability measured in winter annual plants by satellite based sensors
Precipitation throughout the late fall and winter is an important factor in winter annual abundance
Rising minimum temperatures in the early spring is vital to winter annual growth

13. Results and Discussion
Future mapping of model residuals can help to identify other environmental factors that may affect winter annual abundance
Add reworked residuals map with a better color scheme and a legend

14. Results and Discussion
Reformat the legend
Compare modeled abundance with estimate
Colors predict

15. Thank You Acknowledgements: Grant Casady Aaryn Olsson Stuart Marsh
Barron Orr
Jahan Kariyeva
acknowlegements