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Climate change would lead to a sharp acceleration of Central African forests dynamics by the end of the century

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  • Additional Information
    • Contributors:
      AgroParisTech; Forêts et Sociétés (UPR Forêts et Sociétés); Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad); Département Environnements et Sociétés (Cirad-ES); Bureau d'Économie Théorique et Appliquée (BETA); Institut National de la Recherche Agronomique (INRA)-Université de Strasbourg (UNISTRA)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS); Unité de recherche TERRA Gembloux; Gembloux Agro-Bio Tech Gembloux; Université de Liège-Université de Liège; Georgetown University Washington (GU); Institut National Polytechnique Félix Houphouët-Boigny Yamoussoukro (INP-HB); Ministry of Environment, Sustainable Devlopment, Waters, Forestry, Hunting and Fishery (MEDDEFCP); Frédéric MORTIER and Mahlet TADESSE were partially supported by a Georgetown Environment Initiative award. Sylvie GOURLET-FLEURY was partially supported by the DYNAFFOR project (supported by the French Fund for the Global Environment (FFEM), grant number no. CZZ1636.01D) which also supported the publication.; ANR-11-LABX-0002,ARBRE,Recherches Avancées sur l'Arbre et les Ecosytèmes Forestiers(2011)
    • Publication Information:
      HAL CCSD
      IOP Publishing
    • Publication Date:
      2019
    • Collection:
      Université de Lorraine: HAL
    • Abstract:
      Impacts of climate change on the future dynamics of Central African forests are still largely unknown, despite the acuteness of the expected climate changes and the extent of these forests. The high diversity of species and the potentially equivalent diversity of responses to climate modifications are major difficulties encountered when using predictive models to evaluate these impacts. In this study, we applied a mixture of inhomogeneous matrix models to a long-term experimental site located in M'Baiki forests, in the Central African Republic. This model allows the clustering of tree species into processes-based groups while simultaneously selecting explanatory climate and stand variables at the group-level. Using downscaled outputs of 10. general circulation models (GCM), we projected the future forest dynamics up to the end of the century, under constant climate and Representative Concentration Pathways. 4.5 and. 8.5. Through comparative analyses across GCM versions, we identified tree species meta-groups, which are more adapted than ecological guilds to describe the diversity of tree species dynamics and their responses to climate change. Projections under constant climate were consistent with a forest ageing phenomenon, with a slowdown in tree growth and a reduction of the relative abundance of short-lived pioneers. Projections under climate change showed a general increase in growth, mortality and recruitment. This acceleration in forest dynamics led to a strong natural thinning effect, with different magnitudes across species. These differences caused a compositional shift in favour of long-lived pioneers, at the detriment of shade-bearers. Consistent with other field studies and projections, our results show the importance of elucidating the diversity of tree species responses when considering the general sensitivity of Central African forests dynamics to climate change.
    • Relation:
      PRODINRA: 476566; WOS: 000462623300001
    • Accession Number:
      10.1088/1748-9326/aafb81
    • Online Access:
      https://hal.science/hal-02175592
      https://hal.science/hal-02175592v1/document
      https://hal.science/hal-02175592v1/file/Claeys_2019_Environ._Res._Lett._14_044002_1.pdf
      https://doi.org/10.1088/1748-9326/aafb81
    • Rights:
      http://creativecommons.org/licenses/by/ ; info:eu-repo/semantics/OpenAccess
    • Accession Number:
      edsbas.B2C51E76