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

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

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

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

Winter Annuals

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

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

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 Don’t mention peak evi again 2000 2001 2002 2003 2004 2005 2006 2007 2008 Casady: unpublished

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)

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

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

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

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

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

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