Energy, water and carbon exchanges in managed forest ecosystems: description, sensitivity analysis and evaluation of the INRAE GO+ model, version 3.0

Moreaux Virginie, Martel Simon, Bosc Alexandre, Picart Delphine, Achat David, Moisy Christophe, Aussenac Raphaël, Chipeaux Christophe, Bonnefond Jean-Marc, Figuères Soisick, Trichet Pierre, Vezy Rémi, Badeau Vincent, Longdoz Bernard, Granier André, Roupsard Olivier, Nicolas Manuel, Pilegaard Kim, Matteucci Giorgio, Jolivet Claudy, Black Andrew T., Picard Olivier, Loustau Denis. 2020. Energy, water and carbon exchanges in managed forest ecosystems: description, sensitivity analysis and evaluation of the INRAE GO+ model, version 3.0. GeoScientific Model Development, 13 (12) : 5973-6009.

https://doi.org/10.5194/gmd-13-5973-2020

Article de revue ; Article de recherche ; Article de revue à facteur d'impact

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Url - jeu de données - Entrepôt autre : https://doi.org/10.15454/5K9HCS / Url - jeu de données - Entrepôt autre : https://github.com/DenisLOUSTAU/GOplus_model_INRAE

Quartile : Q1, Sujet : GEOSCIENCES, MULTIDISCIPLINARY

Résumé : The mechanistic model GO+ describes the functioning and growth of managed forests based upon biophysical and biogeochemical processes. The biophysical and biogeochemical processes included are modelled using standard formulations of radiative transfer, convective heat exchange, evapotranspiration, photosynthesis, respiration, plant phenology, growth and mortality, biomass nutrient content, and soil carbon dynamics. The forest ecosystem is modelled as three layers, namely the tree overstorey, understorey and soil. The vegetation layers include stems, branches and foliage and are partitioned dynamically between sunlit and shaded fractions. The soil carbon submodel is an adaption of the Roth-C model to simulate the impact of forest operations. The model runs at an hourly time step. It represents a forest stand covering typically 1 ha and can be straightforwardly upscaled across gridded data at regional, country or continental levels. GO+ accounts for both the immediate and long-term impacts of forest operations on energy, water and carbon exchanges within the soil–vegetation–atmosphere continuum. It includes exhaustive and versatile descriptions of management operations (soil preparation, regeneration, vegetation control, selective thinning, clear-cutting, coppicing, etc.), thus permitting the effects of a wide variety of forest management strategies to be estimated: from close to nature to intensive. This paper examines the sensitivity of the model to its main parameters and estimates how errors in parameter values are propagated into the predicted values of its main output variables.The sensitivity analysis demonstrates an interaction between the sensitivity of variables, with the climate and soil hydraulic properties being dominant under dry conditions but the leaf biochemical properties being most influential with wet soil. The sensitivity profile of the model changes from short to long timescales due to the cumulative effects of the fluxes of carbon, energy and water on the stand growth and canopy structure. Apart from a few specific cases, the model simulations are close to the values of the observations of atmospheric exchanges, tree growth, and soil carbon and water stock changes monitored over Douglas fir, European beech and pine forests of different ages. We also illustrate the capacity of the GO+ model to simulate the provision of key ecosystem services, such as the long-term storage of carbon in biomass and soil under various management and climate scenarios.

Mots-clés Agrovoc : écosystème forestier, aménagement forestier, modélisation, accroissement forestier, développement forestier, biogéochimie, séquestration du carbone

Classification Agris : K01 - Foresterie - Considérations générales
U10 - Informatique, mathématiques et statistiques

Champ stratégique Cirad : CTS 5 (2019-) - Territoires

Agences de financement européennes : European Commission

Programme de financement européen : H2020

Projets sur financement : (EU) Readiness of ICOS for Necessities of integrated Global Observations

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