Characterizing Fine-Scale Landscape Controls on Patterns of Arctic Plant Phenology Using High-Resolution Remote Sensing


Daryl Yang1,2* (, Andrew McMahon1, Wouter Hantson3, Jeremiah Anderson1, Kenneth Davidson1,2, Kim Ely1, Alistair Rogers1, Shawn Serbin1,2, Colleen Iversen4


1Environmental and Climate Sciences Department, Brookhaven National Laboratory, Upton, NY; 2Department of Ecology and Evolution, Stony Brook University, Stony Brook, NY; 3School of Forest Resources, University of Maine–Orono, ME; 4Oak Ridge National Laboratory, Oak Ridge, TN



The timing of seasonal plant leaf growth, expansion, and senescence—known as leaf phenology—is highly sensitive to environmental conditions and is a strong control of annual fluxes of carbon, water, and energy. In the high-latitude Arctic, the air is warming two times faster than the rest of the planet, driving changes in both the onset and duration of plant phenological events (e.g., earlier leaf-on and delayed leaf-off). However, differences in observed phenological timing across warming experiments, long-term ecological research, and satellite records due to differences in scales, approaches, and collection periods have strained the ability to understand the primary drivers of plant phenological response to climate and to correctly represent them in process models. Researchers hypothesize that a major reason for the mismatch between observations is the neglect of the significant landscape-scale spatial variability in phenology driven by fine-scale landscape characteristics (e.g., vegetation composition, snow seasonality, topography, permafrost, and soil moisture). Improved understanding of these fine- scale interconnections between plant phenology and landscape characteristics is important but remains limited due to challenges associated with deploying in situ observational equipment or the use of coarse resolution (spatially and temporally) time-series satellite observations.

To address this challenge, researchers deployed 26 custom phenocam systems (PiCAM) that were designed for long-term unattended operations at three low-Arctic tundra sites on the Seward Peninsula, Alaska. Combining data from these PiCAMs and high-resolution (3 m) PlanetScope CubeSats, researchers investigated phenological variations across 12 Arctic plant functional types (PFTs) and their associations with landscape characteristics. The team found that both spring and fall phenology differed strongly across PFTs (by up to 20 days in leaf-on and 40 days in leaf-fall). In particular, deciduous tall shrub species (alder and willow) displayed a later spring green-up (~7 days behind the mean of other PFTs) but completed leaf expansion much faster than other PFTs (within only ~10 days). In contrast, dry tussock graminoids had an earlier start of spring green-up but maintained slow progressive growth during the season. Researchers found that the variation in spring phenology across space and time was strongly coupled with the timing of snowmelt, as well as topography and geomorphological features that affected vegetation and soil moisture distribution. The findings highlight a critical need to characterize Arctic plant phenology at the landscape scale to gain an improved understanding of the fine-scale controls on phenology and species distribution to better represent these processes in ecosystem process models.