NSFDEB-NERC: Gigante: Quantifying and upscaling the causes and drivers of death for giant tropical trees
Lead Research Organisation:
University of Birmingham
Department Name: Sch of Geography, Earth & Env Sciences
Abstract
The land carbon sink depends on the persistence of giant tropical trees. The largest 1% of trees store half the carbon in tropical forests and their deaths release this carbon back to the atmosphere, but we do not know what kills these trees because their deaths are rarely described. A novel sampling strategy is needed to effectively monitor the life and death of giant tropical trees. Gigante will integrate remote sensing and frequent field surveys to answer: (1) What kills giant trees and how do their mortality rates vary over space and time? (2) What are the risk factors underlying variation in giant tree mortality rates? and (3) How does giant tree mortality risk influence pantropical carbon stocks?
We will locate giant tree mortality events using multi-platform, high-frequency remote sensing of 7,500 ha across five tropical forest super sites. These data will facilitate targeted field surveys using detailed state-of-the art protocols to assign proximate agents of mortality to recently dead trees in an unprecedently large field study. We will integrate these data with information about climate, topography, canopy structure, and tree traits to validate mechanistic models of tree mortality risk. Finally, combining these risk models with forest plots and satellite LiDAR, we will evaluate how drivers of giant tree death predict spatial variation in forest dynamics, structure, and carbon storage. The validation of geospatial relationships will allow us estimate the contributions of giant tree mortality to pantropical forest carbon stocks.
We will locate giant tree mortality events using multi-platform, high-frequency remote sensing of 7,500 ha across five tropical forest super sites. These data will facilitate targeted field surveys using detailed state-of-the art protocols to assign proximate agents of mortality to recently dead trees in an unprecedently large field study. We will integrate these data with information about climate, topography, canopy structure, and tree traits to validate mechanistic models of tree mortality risk. Finally, combining these risk models with forest plots and satellite LiDAR, we will evaluate how drivers of giant tree death predict spatial variation in forest dynamics, structure, and carbon storage. The validation of geospatial relationships will allow us estimate the contributions of giant tree mortality to pantropical forest carbon stocks.
Publications
Araza A
(2023)
Past decade above-ground biomass change comparisons from four multi-temporal global maps
in International Journal of Applied Earth Observation and Geoinformation
Bennett A
(2023)
Sensitivity of South American tropical forests to an extreme climate anomaly
in Nature Climate Change
Flores BM
(2024)
Critical transitions in the Amazon forest system.
in Nature