Simulating the onset of spring vegetation growth across the Northern Hemisphere.

Changes in the spring onset of vegetation growth in response to climate change can profoundly impact climate-biosphere interactions. Thus, robust simulation of spring onset is essential to accurately predict ecosystem responses and feedback to ongoing climate change. To date, the ability of vegetation phenology models to reproduce spatiotemporal patterns of spring onset at larger scales has not been thoroughly investigated. In this study, we took advantage of phenology observations via remote sensing to calibrate and evaluated six models, including both one-phase (considering only forcing temperatures) and two-phase (involving forcing, chilling, and photoperiod) models across the Northern Hemisphere between 1982 and 2012. Overall, we found that the model that integrated the photoperiod effect performed best at capturing spatiotemporal patterns of spring phenology in boreal and temperate forests. By contrast, all of the models performed poorly in simulating the onset of growth in grasslands. These results suggest that the photoperiod plays a role in controlling the onset of growth in most Northern Hemisphere forests, whereas other environmental factors (e.g., precipitation) should be considered when simulating the onset of growth in grasslands. We also found that the one-phase model performed as well as the two-phase models in boreal forests, which implies that the chilling requirement is probably fulfilled across most of the boreal zone. Conversely, two-phase models performed better in temperate forests than the one-phase model, suggesting that photoperiod and chilling play important roles in these temperate forests. Our results highlight the significance of including chilling and photoperiod effects in models of the spring onset of forest growth at large scales, and indicate that the consideration of additional drivers may be required for grasslands.