Measuring and modelling ecosystem productivity: a PhenoCam-based approach.

Abstract:

Phenology controls feedbacks to the climate system through abiotic and biotic forces such as albedo or fluxes of water, energy and CO₂. Understanding and modelling these vegetation-climate feedbacks is key to accurately predicting a future climate. For the past 6 years the PhenoCam network, a network of near-surface remote sensing cameras, has consistently monitored vegetation phenology in a wide range of ecoregions, climate zones, and plant functional types. Here we explore the tight coupling between canopy greenness and rates of photosynthesis using two studies.

A first study highlights how PhenoCam data can be used to quantify the effect of a late spring frost event on ecosystem productivity, introducing a 7-14% loss in annual gross productivity across 8753 km² in the northeastern United States. This case study emphasizes the use of the PhenoCam data in estimating productivity loss / the opportunity cost of ecosystem disturbance in areas not covered by ecosystem flux measurement equipment.

In a more recent, second, study we developed a PhenoCam data-informed pulse-response model of grassland growth to explore potential responses of grasslands to future climate change across North America. Our findings projected widespread and consistent increase in grassland productivity (for the current range of grassland ecosystems of North American) over the coming century, despite a general increase in aridity projected across most of our study area. Once more PhenoCam data allowed us to inform our modelling efforts with data of a high temporal and spatial resolution.

In conclusion, both studies illustrate direct applications of the ever growing PhenoCam network (http://phenocam.sr.unh.edu/webcam/) in scaling the effects of ecosystem disturbances, predicting future ecosystem productivity and underscore the complementary nature of PhenoCam data with ecosystem exchange measurements.