Predicting plant traits from leaf-level hyperspectral data
Best practices, a computer package, and hands-on tutorials to guide the application of a powerful technique for prediction of plant traits from hyperspectral data.
Arctic tundra vegetation composition under future climate
Fall and wintertime root and soil biogeochemistry, which are not well represented in large-scale land models, strongly affect 21st century shrub expansion.
Topographical controls on hillslope-scale hydrology drive shrub distributions
Scientists on the NGEE Arctic project find that topography and landscape hydrology are key environmental controls on observed Arctic shrub expansion of the past three decades.
Table Top exercises highlight the importance of communication
Participants across the NGEE Arctic team participated in Table Top exercises for increasing awareness and encouraging improved safety responsiveness to potentially dangerous field work scenarios.
Assessing dynamic vegetation model parameter uncertainty
Model sensitivity and uncertainty varied spatially across the highly heterogeneous Arctic tundra plant communities, illustrating the complexity inherent in model uncertainty in the Arctic.
Combining a climate-flash rate relationship with projections of future climate change shows that lightning strikes will more than double in Arctic tundra by the end of the century.
