Snowmelt velocity predicts vegetation green-wave velocity in mountainous ecological systems of North America

• Published in: International Journal of Applied Earth Observation and Geoinformation
• Main Authors: Donal O’Leary, III, David Inouye, Ralph Dubayah, Chengquan Huang, George Hurtt
• Format: Article in Journal/Newspaper
• Language: English
• Published: Elsevier 2020
• Subjects: Remote sensing; Resource availability; Green wave; Snowmelt timing; Migration; Phenology; Physical geography; GB3-5030; Environmental sciences; GE1-350; Tundra
• Online Access: https://doi.org/10.1016/j.jag.2020.102110; https://doaj.org/article/18856d4bc89c47159645c7f26f021374

The timing of spring initiates an important period for resource availability for large trophic webs within ecosystems, including forage for grazing animals, flowers for pollinators, and the higher trophic levels that depend on these resources. Spring timing is highly variable across space, being influenced strongly by the departure of snow cover (i.e. snowmelt timing, in locations with a seasonal snowpack), climate, weather, elevation, and latitude. When spring timing occurs along a gradient (e.g. spring arriving later in higher elevations of mountainous terrain), the organisms that rely on spring resources often migrate to maintain an optimal position for spring resources – a phenomenon known as ‘surfing the green wave.’ While this behavior has been observed by tracking animals, there have been no studies to quantify the green wave as a movement across space and time. Furthermore, considering that snowmelt timing has moderate power to explain green-up timing for a given location, we ask the question: does snowmelt velocity predict green wave velocity? Here, we introduce the first continental maps of snowmelt and green wave velocity for North America from 2001 to 2016 as derived from the MODIS MCD12Q2 phenology dataset. We show that both snowmelt and green wave velocities are influenced strongly by topography, including slope and aspect. Furthermore, we quantify the relationships between snowmelt and green wave velocities according to three variables: direction, speed, and distance traveled. We conclude that mountainous ecoregions, such as the western North American cordillera, have the highest correspondence between snowmelt and green wave velocities, compared to flatter regions such as the Great Plains and tundra. This work will be of interest to wildlife ecologists, biologists, and land managers who seek to conserve migratory animals and the ecosystems that support them.