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Optimized Application of Biome‐BGC for Modeling the Daily GPP of Natural Vegetation Over Peninsular Spain
Author(s) -
SanchezRuiz Sergio,
Chiesi Marta,
Fibbi Luca,
Carrara Arnaud,
Maselli Fabio,
Gilabert María Amparo
Publication year - 2018
Publication title -
journal of geophysical research: biogeosciences
Language(s) - English
Resource type - Journals
eISSN - 2169-8961
pISSN - 2169-8953
DOI - 10.1002/2017jg004360
Subject(s) - biome , primary production , vegetation (pathology) , environmental science , eddy covariance , scale (ratio) , root (linguistics) , ecosystem , mediterranean climate , atmospheric sciences , soil science , ecology , geography , geology , cartography , biology , linguistics , philosophy , pathology , medicine
A methodology for improving the application of Biome‐BGC in peninsular Spain was developed focusing on the optimization of the rooting depth ( z root ), which is not available for the study area on a spatially distributed basis. The optimal z root was identified by comparing daily gross primary production (GPP) simulations with varying z root to GPP estimations from a production efficiency model previously optimized for and validated in the study area. The methodology was first tested in four eddy covariance (EC) sites representative of Mediterranean ecosystems and next applied at a regional scale to the whole study area. As a result, daily GPP simulated maps for the 2005–2012 period and an optimal z root map were obtained. Optimal z root in the four EC sites was shallower than the default one (100 cm) and led to better simulation results. Realistic, spatially distributed GPP estimates were obtained at regional scale. Withal, some discrepancies appeared both at local and regional scale emphasizing the difficulty to adequately simulate the site's water budget and the need for proper setting of inputs, including z root for the correct functioning of Biome‐BGC. The performed optimization opens the door for using Biome‐BGC to simulate other main vegetation processes, such as net carbon fluxes, in the study area.