Unlocking tropical forest complexity: How tree assemblages in secondary forests boost biodiversity conservation

Fuente: arXiv
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Main Authors: Oliveira, Maïri Souza, Lenormand, Maxime, Luque, Sandra, Zamora, Nelson A., Alleaume, Samuel, Porras, Adriana C. Aguilar, Castillo, Marvin U., Chacón-Madrigal, Eduardo, Delgado, Diego, Sánchez, Luis Gustavo Hernández, Bieng, Marie-Ange Ngo, Quesada, Ruperto M., Solano, Gilberth S., Zúñiga, Pedro M.
Format: Preprint
Published: 2025
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author Oliveira, Maïri Souza
Lenormand, Maxime
Luque, Sandra
Zamora, Nelson A.
Alleaume, Samuel
Porras, Adriana C. Aguilar
Castillo, Marvin U.
Chacón-Madrigal, Eduardo
Delgado, Diego
Sánchez, Luis Gustavo Hernández
Bieng, Marie-Ange Ngo
Quesada, Ruperto M.
Solano, Gilberth S.
Zúñiga, Pedro M.
author_facet Oliveira, Maïri Souza
Lenormand, Maxime
Luque, Sandra
Zamora, Nelson A.
Alleaume, Samuel
Porras, Adriana C. Aguilar
Castillo, Marvin U.
Chacón-Madrigal, Eduardo
Delgado, Diego
Sánchez, Luis Gustavo Hernández
Bieng, Marie-Ange Ngo
Quesada, Ruperto M.
Solano, Gilberth S.
Zúñiga, Pedro M.
contents 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 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.
format Preprint
id arxiv_https___arxiv_org_abs_2503_02523
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Unlocking tropical forest complexity: How tree assemblages in secondary forests boost biodiversity conservation
Oliveira, Maïri Souza
Lenormand, Maxime
Luque, Sandra
Zamora, Nelson A.
Alleaume, Samuel
Porras, Adriana C. Aguilar
Castillo, Marvin U.
Chacón-Madrigal, Eduardo
Delgado, Diego
Sánchez, Luis Gustavo Hernández
Bieng, Marie-Ange Ngo
Quesada, Ruperto M.
Solano, Gilberth S.
Zúñiga, Pedro M.
Populations and Evolution
Quantitative Methods
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 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.
title Unlocking tropical forest complexity: How tree assemblages in secondary forests boost biodiversity conservation
topic Populations and Evolution
Quantitative Methods
url https://arxiv.org/abs/2503.02523