Mapping 'green wave' velocity across North America - spatiotemporal patterns of spring vegetation phenology derived from MODIS MCD12Q2

For temperate vegetated system of North America, the transition from winter to spring brings a rapid increase in vegetation productivity. The timing of this important phonological stage, often called 'green-up,' is readily observed using remote sensing (e.g. as a rapid increase in NDVI), and has been mapped at various scales. The spatial and temporal patterns of green-up have important implications for higher trophic levels within the ecosystem, as vegetation production offers forage for migrating animals, and is closely associated with other important resources (shelter, nectar, etc.). It is known that some animals closely follow peak green-up during their migrations, i.e., they surf the 'green wave' of resource availability along their migratory route. Still, to our knowledge there have been no explicit maps defining the speed and direction of the 'green wave' at any scale. Here, we introduce continental maps of 'green wave' velocity for North America derived from MODIS MCD12Q2 for 2001-2016. Using animated visualizations, we demonstrate our method to define the speed and direction of the advancing 'green wave' across the landscape. We show that the 'green wave' behaves differently across ecological regions, slopes, and aspects, with implications for cascading ecosystem impacts. Furthermore, we discuss important physical and ecological considerations for parameterizing our 'green wave' model, and the uncertainties associated with our assumptions. Finally, we explore the spatial interactions between snowmelt timing and green-up timing as land cover change waves across the landscape. This work establishes a new perspective on seasonal land cover change, refining pixel-based phenology into a spatially relevant vector of change by leveraging the power of existing remotely sensed data products.