The goals of this research were to examine the effects of climate, land-use, and plot-level characteristics on interannual change of vegetation characteristics. Using mixed-effects regression models, we examined the influences of climatic limiting factors and plot-level characteristics on annual fraction of Absorbed Photosynthetically Active Radiation (fAPAR) estimates from MODIS 250 m resolution data across agricultural and restored prairie plots in Iowa. Prairie plots had significantly higher annual fAPAR and less year-to-year variability than highly intensive agriculture. Comparisons between fixed and random effects models show that differential climate responses between land-use types explain approximately 85 percent of between pixel differences. Year-to-year climate differences and pixel scale land-use factors explained approximately 48 percent of agriculture within-plot trends and interannual variability and 54 percent of prairie year-to-year variance. Agriculture responses were predominantly influenced by precipitation and prairies were primarily influenced by incident radiation and age since restoration.