Artificial intelligence applied to multiple remote sensing datasets accurately represents shrub distribution across hillslopes at the Kougarok field site.

Worldwide trait database addresses long-standing questions about trait-environment relationships and provides an unprecedented digital resource to inform Earth system models.

Field observations and model simulations confirm the presence of unfrozen permafrost in shrub-dominated landscapes.

Light-harvesting processes involved in photosynthesis by tundra plants are unexpectedly sensitive to growth at low temperatures.

A convolutional neural network (CNN) approach produced highly accurate vegetation classifications. Hyper-spectral datasets (e.g., AVIRIS) were most useful for our machine learning approaches. Accurate and high-resolution datasets generated using our approach are needed for Arctic models.