Evaluating the convergence between eddy-covariance and biometric methods for assessing carbon budgets of forests

The eddy-covariance (EC) micro-meteorological technique and the ecology-based biometric methods (BM) are the primary methodologies to quantify CO₂ exchange between terrestrial ecosystems and the atmosphere (net ecosystem production, NEP) and its two components, ecosystem respiration and gross primar...

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Detalles Bibliográficos
Autores: Campioli, Matteo|||0000-0002-3427-2368, Malhi, Yadvinder|||0000-0002-3503-4783, Vicca, Sara|||0000-0001-9812-5837, Luyssaert, Sebastiaan|||0000-0003-1121-1869, Papale, D., Peñuelas, Josep|||0000-0002-7215-0150, Reichstein, M., Migliavacca, Mirco|||0000-0003-3546-8407, Arain, M. Altaf|||0000-0002-1433-5173, Janssens, Ivan|||0000-0002-5705-1787
Tipo de recurso: artículo
Fecha de publicación:2016
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:168359
Acceso en línea:https://ddd.uab.cat/record/168359
https://dx.doi.org/urn:doi:10.1038/ncomms13717
Access Level:acceso abierto
Palabra clave:Carbon cycle
Ecosystem ecology
Descripción
Sumario:The eddy-covariance (EC) micro-meteorological technique and the ecology-based biometric methods (BM) are the primary methodologies to quantify CO₂ exchange between terrestrial ecosystems and the atmosphere (net ecosystem production, NEP) and its two components, ecosystem respiration and gross primary production. Here we show that EC and BM provide different estimates of NEP, but comparable ecosystem respiration and gross primary production for forest ecosystems globally. Discrepancies between methods are not related to environmental or stand variables, but are consistently more pronounced for boreal forests where carbon fluxes are smaller. BM estimates are prone to underestimation of net primary production and overestimation of leaf respiration. EC biases are not apparent across sites, suggesting the effectiveness of standard post-processing procedures. Our results increase confidence in EC, show in which conditions EC and BM estimates can be integrated, and which methodological aspects can improve the convergence between EC and BM.