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Forest degradation and biomass loss along the Chocó region of Colombia / Victoria Meyer in Carbon Balance and Management, vol 14 (March 2019)
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Titre : Forest degradation and biomass loss along the Chocó region of Colombia Type de document : Article/Communication Auteurs : Victoria Meyer, Auteur ; Sassan Saatchi, Auteur ; António Ferraz , Auteur ; Liang Xu, Auteur ; Duque Alvaro, Auteur ; Mariano Garcia, Auteur ; Mariano Chave, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage automatique
[Termes IGN] biomasse aérienne
[Termes IGN] canopée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] Colombie
[Termes IGN] densité du bois
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] dynamique de la végétation
[Termes IGN] dynamique spatiale
[Termes IGN] forêt tropicale
[Termes IGN] hauteur de la végétation
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] semis de pointsRésumé : (auteur) Background: Wet tropical forests of Chocó, along the Pacific Coast of Colombia, are known for their high plant diversity and endemic species. With increasing pressure of degradation and deforestation, these forests have been prioritized for conservation and carbon offset through Reducing Emissions from Deforestation and forest Degradation (REDD+) mechanisms. We provide the first regional assessment of forest structure and aboveground biomass using measurements from a combination of ground tree inventories and airborne Light Detection and Ranging (Lidar). More than 80,000 ha of lidar samples were collected based on a stratified random sampling to provide a regionally unbiased quantification of forest structure of Chocó across gradients of vegetation structure, disturbance and elevation. We developed a model to convert measurements of vertical structure of forests into aboveground biomass (AGB) for terra firme, wetlands, and mangrove forests. We used the Random Forest machine learning model and a formal uncertainty analysis to map forest height and AGB at 1-ha spatial resolution for the entire pacific coastal region using spaceborne data, extending from the coast to higher elevation of Andean forests.
Results: Upland Chocó forests have a mean canopy height of 21.8 m and AGB of 233.0 Mg/ha, while wetland forests are characterized by a lower height and AGB (13.5 m and 117.5 Mg/a). Mangroves have a lower mean height than upland forests (16.5 m), but have a similar AGB as upland forests (229.9 Mg/ha) due to their high wood density. Within the terra firme forest class, intact forests have the highest AGB (244.3 ± 34.8 Mg/ha) followed by degraded and secondary forests with 212.57 ± 62.40 Mg/ha of biomass. Forest degradation varies in biomass loss from small-scale selective logging and firewood harvesting to large-scale tree removals for gold mining, settlements, and illegal logging. Our findings suggest that the forest degradation has already caused the loss of more than 115 million tons of dry biomass, or 58 million tons of carbon.
Conclusions: Our assessment of carbon stocks and forest degradation can be used as a reference for reporting on the state of the Chocó forests to REDD+ projects and to encourage restoration efforts through conservation and climate mitigation policies.Numéro de notice : A2019-625 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1186/s13021-019-0117-9 Date de publication en ligne : 23/03/2019 En ligne : https://doi.org/10.1186/s13021-019-0117-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95368
in Carbon Balance and Management > vol 14 (March 2019)[article]