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Examining the link between vegetation leaf area and land–atmosphere exchange of water, energy, and carbon fluxes using FLUXNET data

Published on
September 4, 2020

An article of Anne Hoek van Dijke, Kaniska Mallick, Martin Schlerf, Miriam Machwitz, Martin Herold and Adriaan Teuling: Examining the link between vegetation leaf area and land–atmosphere exchange of water, energy, and carbon fluxes using FLUXNET data, has been published in Biogeosciences, 17, 4443–4457.

doi:10.5194/bg-17-4443-2020

Abstract
Vegetation regulates the exchange of water, energy, and carbon fluxes between the land and the atmosphere. This regulation of surface fluxes differs with vegetation type and climate, but the effect of vegetation on surface fluxes is not well understood. A better knowledge of how and when vegetation influences surface fluxes could improve climate models and the extrapolation of ground-based water, energy, and carbon fluxes. We aim to study the link between vegetation and surface fluxes by combining the yearly average MODIS leaf area index (LAI) with flux tower measurements of water (latent heat), energy (sensible heat), and carbon (gross primary productivity and net ecosystem exchange). We show that the correlation of the LAI with water and energy fluxes depends on the vegetation type and aridity. Under water-limited conditions, the link between the LAI and the water and energy fluxes is strong, which is in line with a strong stomatal or vegetation control found in earlier studies. In energy-limited forest we found no link between the LAI and water and energy fluxes. In contrast to water and energy fluxes, we found a strong spatial correlation between the LAI and gross primary productivity that was independent of vegetation type and aridity. This study provides insight into the link between vegetation and surface fluxes. It indicates that for modelling or extrapolating surface fluxes, the LAI can be useful in savanna and grassland, but it is only of limited use in deciduous broadleaf forest and evergreen needleleaf forest to model variability in water and energy fluxes.