Modelling Eucalyptus biomass production at regional scale in Brazil

Among forest vegetation grown in Brazil, Eucalyptus is the most widely planted tropical hardwood genus covering approximately 5.7 million ha for an average yield of 49 m3 ha-1 yr-1. Wide differences of biomass production were observed among neighboring stands representing challenges to forestry companies to spatially estimate biomass yield in large plantation zones. The first objective of the present research was to modify the carbon allocation scheme in the process-based model Generic Decomposition And Yield Model (G'DAY), to better capture the spatial variability in growth rates of Eucalyptus as influenced by environmental constraints such as water stress. The model was parametrized and tested using experimental and long term commercial datasets in the state of Sao Paulo Brazil. Measured data included several variables of carbon and water fluxes and carbon stock. The calibrated model produced accurate prediction of the carbon key variables such as leaf area index, stem biomass, and gross primary production and water related variables such as plant available water and evapotranspiration. Simulating the spatial variability among commercial Eucalyptus stands at landscape scale showed reasonable prediction of plant height with r2 of 0.89 but lower level of accuracy for stem biomass. This could partially be attributed to spatial soil data differences used at regional scales which came from the Global Soil Dataset for Earth Systems Modeling dataset, at a resolution of 1 km. Testing the soil data with the use of soil type map crossed with soil profile measurements is expected to improve the soil information for higher accuracy of stem simulation at landscape to regional scale.

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Main Authors: Attia, Ahmed, Cuandra, Santiago, Nouvellon, Yann, Guillemot, Joannès, Camargo Campoe, Otávio, Cabral, Osvaldo Machado Rodrigues, Laclau, Jean-Paul, Galdos, Marcelo, Lamparelli, Rubens Augusto Camargo, Le Maire, Guerric
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Online Access:http://agritrop.cirad.fr/589490/
http://agritrop.cirad.fr/589490/1/ID589490.pdf
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spelling dig-cirad-fr-5894902021-02-09T07:32:53Z http://agritrop.cirad.fr/589490/ http://agritrop.cirad.fr/589490/ Modelling Eucalyptus biomass production at regional scale in Brazil. Attia Ahmed, Cuandra Santiago, Nouvellon Yann, Guillemot Joannès, Camargo Campoe Otávio, Cabral Osvaldo Machado Rodrigues, Laclau Jean-Paul, Galdos Marcelo, Lamparelli Rubens Augusto Camargo, Le Maire Guerric. 2018. In : Eucalyptus 2018: Managing Eucalyptus plantation under global changes. Abstracts book. CIRAD, IUFRO, MUSE. Montpellier : CIRAD, Résumé, p. 43. ISBN 978-2-87614-743-0 Eucalyptus 2018, Montpellier, France, 17 Septembre 2018/21 Septembre 2018. Researchers Modelling Eucalyptus biomass production at regional scale in Brazil Attia, Ahmed Cuandra, Santiago Nouvellon, Yann Guillemot, Joannès Camargo Campoe, Otávio Cabral, Osvaldo Machado Rodrigues Laclau, Jean-Paul Galdos, Marcelo Lamparelli, Rubens Augusto Camargo Le Maire, Guerric eng 2018 CIRAD Eucalyptus 2018: Managing Eucalyptus plantation under global changes. Abstracts book Among forest vegetation grown in Brazil, Eucalyptus is the most widely planted tropical hardwood genus covering approximately 5.7 million ha for an average yield of 49 m3 ha-1 yr-1. Wide differences of biomass production were observed among neighboring stands representing challenges to forestry companies to spatially estimate biomass yield in large plantation zones. The first objective of the present research was to modify the carbon allocation scheme in the process-based model Generic Decomposition And Yield Model (G'DAY), to better capture the spatial variability in growth rates of Eucalyptus as influenced by environmental constraints such as water stress. The model was parametrized and tested using experimental and long term commercial datasets in the state of Sao Paulo Brazil. Measured data included several variables of carbon and water fluxes and carbon stock. The calibrated model produced accurate prediction of the carbon key variables such as leaf area index, stem biomass, and gross primary production and water related variables such as plant available water and evapotranspiration. Simulating the spatial variability among commercial Eucalyptus stands at landscape scale showed reasonable prediction of plant height with r2 of 0.89 but lower level of accuracy for stem biomass. This could partially be attributed to spatial soil data differences used at regional scales which came from the Global Soil Dataset for Earth Systems Modeling dataset, at a resolution of 1 km. Testing the soil data with the use of soil type map crossed with soil profile measurements is expected to improve the soil information for higher accuracy of stem simulation at landscape to regional scale. conference_item info:eu-repo/semantics/conferenceObject Conference info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/589490/1/ID589490.pdf text Cirad license info:eu-repo/semantics/openAccess https://agritrop.cirad.fr/mention_legale.html http://agritrop.cirad.fr/589039/
institution CIRAD FR
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language eng
description Among forest vegetation grown in Brazil, Eucalyptus is the most widely planted tropical hardwood genus covering approximately 5.7 million ha for an average yield of 49 m3 ha-1 yr-1. Wide differences of biomass production were observed among neighboring stands representing challenges to forestry companies to spatially estimate biomass yield in large plantation zones. The first objective of the present research was to modify the carbon allocation scheme in the process-based model Generic Decomposition And Yield Model (G'DAY), to better capture the spatial variability in growth rates of Eucalyptus as influenced by environmental constraints such as water stress. The model was parametrized and tested using experimental and long term commercial datasets in the state of Sao Paulo Brazil. Measured data included several variables of carbon and water fluxes and carbon stock. The calibrated model produced accurate prediction of the carbon key variables such as leaf area index, stem biomass, and gross primary production and water related variables such as plant available water and evapotranspiration. Simulating the spatial variability among commercial Eucalyptus stands at landscape scale showed reasonable prediction of plant height with r2 of 0.89 but lower level of accuracy for stem biomass. This could partially be attributed to spatial soil data differences used at regional scales which came from the Global Soil Dataset for Earth Systems Modeling dataset, at a resolution of 1 km. Testing the soil data with the use of soil type map crossed with soil profile measurements is expected to improve the soil information for higher accuracy of stem simulation at landscape to regional scale.
format conference_item
author Attia, Ahmed
Cuandra, Santiago
Nouvellon, Yann
Guillemot, Joannès
Camargo Campoe, Otávio
Cabral, Osvaldo Machado Rodrigues
Laclau, Jean-Paul
Galdos, Marcelo
Lamparelli, Rubens Augusto Camargo
Le Maire, Guerric
spellingShingle Attia, Ahmed
Cuandra, Santiago
Nouvellon, Yann
Guillemot, Joannès
Camargo Campoe, Otávio
Cabral, Osvaldo Machado Rodrigues
Laclau, Jean-Paul
Galdos, Marcelo
Lamparelli, Rubens Augusto Camargo
Le Maire, Guerric
Modelling Eucalyptus biomass production at regional scale in Brazil
author_facet Attia, Ahmed
Cuandra, Santiago
Nouvellon, Yann
Guillemot, Joannès
Camargo Campoe, Otávio
Cabral, Osvaldo Machado Rodrigues
Laclau, Jean-Paul
Galdos, Marcelo
Lamparelli, Rubens Augusto Camargo
Le Maire, Guerric
author_sort Attia, Ahmed
title Modelling Eucalyptus biomass production at regional scale in Brazil
title_short Modelling Eucalyptus biomass production at regional scale in Brazil
title_full Modelling Eucalyptus biomass production at regional scale in Brazil
title_fullStr Modelling Eucalyptus biomass production at regional scale in Brazil
title_full_unstemmed Modelling Eucalyptus biomass production at regional scale in Brazil
title_sort modelling eucalyptus biomass production at regional scale in brazil
publisher CIRAD
url http://agritrop.cirad.fr/589490/
http://agritrop.cirad.fr/589490/1/ID589490.pdf
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