Extending the range of applicability of the semi-empirical ecosystem flux model PRELES for varying forest types and climate

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Tian , X , Minunno , F , Cao , T , Peltoniemi , M , Kalliokoski , T & Mäkelä , A 2020 , ' Extending the range of applicability of the semi-empirical ecosystem flux model PRELES for varying forest types and climate ' , Global Change Biology , vol. 26 , no. 5 , pp. 2923-2943 . https://doi.org/10.1111/gcb.14992

Title: Extending the range of applicability of the semi-empirical ecosystem flux model PRELES for varying forest types and climate
Author: Tian, Xianglin; Minunno, Francesco; Cao, Tianjian; Peltoniemi, Mikko; Kalliokoski, Tuomo; Mäkelä, Annikki
Other contributor: University of Helsinki, Department of Forest Sciences
University of Helsinki, Ecosystem processes (INAR Forest Sciences)
University of Helsinki, Northwest A&F University
University of Helsinki, Natural Resources Institute Finland
University of Helsinki, INAR Physics
University of Helsinki, Department of Forest Sciences






Date: 2020-05
Language: eng
Number of pages: 21
Belongs to series: Global Change Biology
ISSN: 1354-1013
DOI: https://doi.org/10.1111/gcb.14992
URI: http://hdl.handle.net/10138/324501
Abstract: Abstract Applications of ecosystem flux models on large geographical scales are often limited by model complexity and data availability. Here, we calibrated and evaluated a semi-empirical ecosystem flux model, PRELES, for various forest types and climate conditions, based on eddy covariance data from 55 sites. A Bayesian approach was adopted for model calibration and uncertainty quantification. We applied the site-specific calibrations and multisite calibrations to nine plant functional types (PFTs) to obtain the site-specific and PFT specific parameter vectors for PRELES. A systematically designed cross-validation was implemented to evaluate calibration strategies and the risks in extrapolation. The combination of plant physiological traits and climate patterns generated significant variation in vegetation responses and model parameters across but not within PFTs, implying that applying the model without PFT-specific parameters is risky. But within PFT, the multisite calibrations performed as accurately as the site-specific calibrations in predicting gross primary production (GPP) and evapotranspiration (ET). Moreover, the variations among sites within one PFT could be effectively simulated by simply adjusting the parameter of potential light-use efficiency (LUE), implying significant convergence of simulated vegetation processes within PFT. The hierarchical modelling of PRELES provides a compromise between satellite-driven LUE and physiologically oriented approaches for extrapolating the geographical variation of ecosystem productivity. Although measurement errors of eddy covariance and remotely sensed data propagated a substantial proportion of uncertainty or potential biases, the results illustrated that PRELES could reliably capture daily variations of GPP and ET for contrasting forest types on large geographical scales if PFT-specific parameterizations were applied.
Subject: BAYESIAN CALIBRATION
BOREAL-FOREST
CARBON BALANCE MODEL
GAS-EXCHANGE
GROSS PRIMARY PRODUCTION
LIGHT USE EFFICIENCY
NET PRIMARY PRODUCTION
OF-THE-ART
PRIMARY PRODUCTIVITY
RADIATION-USE EFFICIENCY
evapotranspiration
geographical variations
gross primary production
inverse modelling
light-use efficiency
multisite calibration
plant functional type
1181 Ecology, evolutionary biology
1172 Environmental sciences
4112 Forestry
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