TY - JOUR
T1 - Unlocking Tropical Forest Complexity
T2 - How Tree Assemblages in Secondary Forests Boost Biodiversity Conservation
AU - Souza Oliveira, Maïri
AU - Lenormand, Maxime
AU - Luque, Sandra
AU - Zamora, Nelson A.
AU - Alleaume, Samuel
AU - Aguilar Porras, Adriana C.
AU - Castillo, Marvin U.
AU - Chacón-Madrigal, Eduardo
AU - Delgado, Diego
AU - Hernández Sánchez, Luis Gustavo
AU - Ngo Bieng, Marie Ange
AU - Quesada-Monge, Ruperto
AU - Solano, Gilberth S.
AU - Zúñiga, Pedro M.
N1 - Publisher Copyright:
© 2025 The Author(s). Ecology and Evolution published by British Ecological Society and John Wiley & Sons Ltd.
PY - 2025/11
Y1 - 2025/11
N2 - Secondary forests now dominate tropical landscapes and play a crucial role in achieving COP15 conservation objectives. This study develops a replicable national approach to identifying and characterising forest ecosystems, with a focus on the role of secondary forests. We hypothesised that dominant tree species in the forest canopy serve as reliable indicators for delineating forest ecosystems and untangling biodiversity complexity. Using national inventories, we identified in situ clusters through hierarchical clustering based on dominant species abundance dissimilarity, determined using the Importance Variable Index. These clusters were characterised by analysing species assemblages and their interactions. We then applied object-oriented Random Forest modelling, segmenting the national forest cover using NDVI to identify the forest ecosystems derived from in situ clusters. Freely available spectral (Sentinel-2) and environmental data were used in the model to delineate and characterise key forest ecosystems. We finished with an assessment of the distribution of secondary and old-growth forests within ecosystems. In Costa Rica, 495 dominant tree species defined 10 in situ clusters, with 7 main clusters successfully modelled. The modelling (F1-score: 0.73, macro F1-score: 0.58) and species-based characterisation highlighted the main ecological trends of these ecosystems, which are distinguished by specific species dominance, topography, climate, and vegetation dynamics, aligning with local forest classifications. The analysis of secondary forest distribution provided an initial assessment of ecosystem vulnerability by evaluating their role in forest maintenance and dynamics. This approach also underscored the major challenge of in situ data acquisition.
AB - Secondary forests now dominate tropical landscapes and play a crucial role in achieving COP15 conservation objectives. This study develops a replicable national approach to identifying and characterising forest ecosystems, with a focus on the role of secondary forests. We hypothesised that dominant tree species in the forest canopy serve as reliable indicators for delineating forest ecosystems and untangling biodiversity complexity. Using national inventories, we identified in situ clusters through hierarchical clustering based on dominant species abundance dissimilarity, determined using the Importance Variable Index. These clusters were characterised by analysing species assemblages and their interactions. We then applied object-oriented Random Forest modelling, segmenting the national forest cover using NDVI to identify the forest ecosystems derived from in situ clusters. Freely available spectral (Sentinel-2) and environmental data were used in the model to delineate and characterise key forest ecosystems. We finished with an assessment of the distribution of secondary and old-growth forests within ecosystems. In Costa Rica, 495 dominant tree species defined 10 in situ clusters, with 7 main clusters successfully modelled. The modelling (F1-score: 0.73, macro F1-score: 0.58) and species-based characterisation highlighted the main ecological trends of these ecosystems, which are distinguished by specific species dominance, topography, climate, and vegetation dynamics, aligning with local forest classifications. The analysis of secondary forest distribution provided an initial assessment of ecosystem vulnerability by evaluating their role in forest maintenance and dynamics. This approach also underscored the major challenge of in situ data acquisition.
KW - forest ecosystem
KW - GBF 2030 targets
KW - hierarchical clustering
KW - network analysis
KW - random forest
KW - Sentinel-2
UR - https://www.scopus.com/pages/publications/105021332358
U2 - 10.1002/ece3.72428
DO - 10.1002/ece3.72428
M3 - Artículo
AN - SCOPUS:105021332358
SN - 2045-7758
VL - 15
JO - Ecology and Evolution
JF - Ecology and Evolution
IS - 11
M1 - e72428
ER -