K. A. Novick

The paper identifies 56% of global eddy covariance towers as paired, finds they sample richer soils and different climates than the global network, and highlights data gaps in certain regions and ecosystems.

This paper introduces a hierarchical Bayesian calibration method for dynamic vegetation models, showing it improves prediction accuracy by accounting for site-to-site parameter variability.