Using high-resolution images to analyze the importance of crown size and competition for the growth of tropical trees

Ndamiyehe Ncutirakiza Jean-Baptiste, Gourlet-Fleury Sylvie, Lejeune Philippe, Bry Xavier, Trottier Catherine, Mortier Frédéric, Fayolle Adeline, Muhashy Habiyaremye François, Ndjele Mianda-Bungi Léopold, Ligot Gauthier. 2024. Using high-resolution images to analyze the importance of crown size and competition for the growth of tropical trees. Forest Ecology and Management, 552:121553, 21 p.

Résumé : The influence of canopy structure on tropical tree growth has been scantly studied because of the difficulties making field measurements in these dense multi-layered ecosystems. The recent advent of unmanned aerial vehicles (UAVs), has made it easier to collect canopy data, so offering a way to gain a better understanding of forest productivity and thereby improve forest management. In this study, we assessed tree growth prediction using UAV-derived crown measurements as an alternative for field data. Four experimental 9 ha plots were sampled in two forest sites, Yoko in the Democratic Republic of the Congo and Loundoungou in the Republic of Congo. Field inventories were made between 2015 and 2020. For each tree, we computed the diameter increment (DBHI) using censuses and diameter-based competition indices (diameter-based CIs) using the first census. High-resolution orthoimages and digital surface models were acquired with UAVs in 2016 and 2018 in the two sites. They gave estimates of crown characteristics (size, relative elevation, shape) and crown-based competition indices (crown-based CIs). Co-recorded UAV and field measurements were obtained for 1558 trees. The diameter increment of these trees was then modelled using supervised component generalized linear regression, and 20 % of trees were kept for cross-validation. Combined field and UAV data predicted tree DBHI twice better than either taken separately. Diameter at breast height (DBH) and crown area (CA) were found to be complementary predictors. Crown-based CIs significantly improved predictions of models already containing DBH and CA. Adding diameter-based CIs to models containing DBH, CA, and crown-based CIs only marginally improved growth predictions, showing that tree competition can be well-described with UAV data. The model calibrated at one site predicted the growth at the other site well, suggesting that a general model could be devised for multiple sites. Growth variance was better explained in the site (Yoko) where the crown density was higher and the crown smaller. Further data are now needed from multiple sites with ranging stand structures and compositions to build a general model.

Mots-clés Agrovoc : accroissement du diamètre, Houppier, croissance, aménagement forestier, drone, mesure (activité), altitude, forêt tropicale, structure du peuplement

Mots-clés géographiques Agrovoc : République démocratique du Congo, France, Congo

Mots-clés libres : Tropical forest, Canopy structure, Crown competition Drone, Tree growth modelling

Agences de financement hors UE : International Foundation for Science, Centre for International Forestry Research, Royal Belgian Institute of Natural Sciences, Ambassade de France au Congo

Projets sur financement : (EU) FOrmation, Recherche, Environnement dans la TShopo

Auteurs et affiliations

• Ndamiyehe Ncutirakiza Jean-Baptiste, CIRAD-ES-UPR Forêts et sociétés (FRA) - auteur correspondant
• Gourlet-Fleury Sylvie, CIRAD-ES-UPR Forêts et sociétés (FRA) ORCID: 0000-0002-1136-4307
• Lejeune Philippe, Université de Liège (BEL)
• Bry Xavier, UM2 (FRA)
• Trottier Catherine, UM2 (FRA)
• Mortier Frédéric, CIRAD-ES-UPR Forêts et sociétés (FRA)
• Fayolle Adeline, Université de Liège (BEL)
• Muhashy Habiyaremye François, University of Goma (COD)
• Ndjele Mianda-Bungi Léopold, UNIKIS (COD)
• Ligot Gauthier, Université de Liège (BEL)

Source : Cirad-Agritrop (https://agritrop.cirad.fr/607179/)

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