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Introduktionsseminarium: "Seeing the forest from the trees to refine forest carbon stocks in a biodiversity hotspot"

Naturvetenskap & IT

Introduktionsseminarium med Luisa Gómez-Correa, doktorand vid Institutionen för biologi och miljövetenskap

Seminarium
Datum
18 dec 2025
Tid
12:15 - 13:00
Plats
"Vinden", Natrium, Medicinaregatan 7B
Ytterligare information
Zoom-länk

Arrangör
Institutionen för biologi och miljövetenskap

Luisas doktorandprojekt fokuserar på trädstruktur och biomassa för att kunna göra säkrare uppskattningar av skogarnas betydelse som kolsänkor, se mer nedan. Hennes huvudhandledare är Daniel Zuleta  (BioEnv) med Alexandre Antonelli  (BioEnv och Royal Botanic Gardens, Kew, London, UK) som biträdande handledare, och examinator är Angela Wulff  (BioEnv).

Sammanfattning
Tropical forests are the largest terrestrial carbon stock on Earth and therefore play a critical role in regulating global carbon fluxes. However, estimates of forest carbon stocks remain uncertain due to limited knowledge of tree structural variability. Carbon estimates often rely on allometric tree models, which estimate biomass based on tree architecture (for example, trunk diameter and height) and the wood density of the species. Tree architecture, however, varies widely among individuals, species, forest types, and abiotic conditions, which makes it challenging for current allometric models to accurately represent this variability. I will investigate forest biomass stocks and individual tree architecture across elevational gradients and forest disturbances in Montane Atlantic forests, a highly diverse but underrepresented ecosystem in forest carbon studies. This will be achieved by combining traditional ground measurements in 1 ha permanent forest plots with detailed tree structural data obtained from terrestrial laser scanning. This research will evaluate how biotic and abiotic factors shape tree architecture and will compare forest carbon estimates generated from reference allometric models with those derived from laser based structural models.