Using the radiative-transfer SCOPE Model to Predict the Vulnerability of Tropical Forests to Changing Climate
Kelvin Tuazon Acebron, Quantitative Ecology Lab, Smithsonian Environmental Research Center, acebronk@si.edu (Presenter)
Sean M. McMahon, Quantitative Ecology Lab, Smithsonian Environmental Research Center, mcmahons@si.edu
Maquelle Neves Garcia, Forest Ecosystems and Society, Oregon State University, maquelle.garcia@oregonstate.edu
Charles D. Southwick, Department of Biology, West Virginia University, cds00028@mix.wvu.edu
Emmelia J. Braun, Department of Biology, West Virginia University, eb0067@mix.wvu.edu
Matteo Detto, Smithsonian Tropical Research Institute, dettom@si.edu
Vicente Vasquez, Smithsonian Tropical Research Institute, vicenteavv7@gmail.com
Egor Prikaziuk, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, e.prikaziuk@utwente.nl
Christiaan van der Tol, Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, c.vandertol@utwente.nl
Loren Albert, Oregon State University, loren.albert@mail.wvu.edu
Tropical forests, as the largest terrestrial carbon sink and a hub for biodiversity, are crucial in predicting the course of climate change. However, the response of these forests to changing climate varies across space and time, affecting demographic species composition and vulnerability. Species-specific strategies and environmental heterogeneity contribute to these differences, making it challenging to model the relationship between species, strategies, climate, and carbon cycling across diverse tropical forests.
We used the Soil-Canopy Observation, Photochemistry, and Energy (SCOPE) model to investigate the temporal dynamics of photosynthesis, transpiration, and energy fluxes of plant functional types based on data of selected tree species on Barro Colorado Island (BCI) in Panama. For model inputs, we collected leaf traits such as leaf pigments (total chlorophylls (Chla+b), carotenoids and anthocyanin), maximum carboxylation efficiency (Vcmax), leaf mass per area (LMA) and dry matter content. Furthermore, we used five years of meteorological data from BCI to extend the temporal scope of our simulations. Our simulations revealed seasonal variation in water and light-use efficiencies, emphasizing the importance of studying resource strategies of tree species to predict tropical forests’ response to climate change.
The SCOPE model output is a promising tool for interpreting global patterns of optical signals in pantropical forests, inferring changes in ecosystem functions, and predicting the impact of climate change on these forests at a global scale. Our study provides insights into establishing causal models and identifying leaf-to-landscape predictors for the vulnerability of tropical forests under temperature and vapor pressure deficit stress. As a next step, we aim to use species-specific model configuration and link the results of simulation with the ForestGEO inventory plot to estimate carbon fluxes at larger scales. This will enable us to better understand the complex interplay between species composition and demography as a response to drought stress.
Poster: Poster_Acebron_3-42_145_35.pdf
Associated Project(s):
Poster Location ID: 3-42
Presentation Type: Poster
Session: Poster Session 3
Session Date: Thu (May 11) 3:00-5:00 PM
CCE Program: TE