Our understanding of carbon, energy, and water cycles in tropical forests remains limited despite the important role these ecosystems play in the Earth’s carbon cycle. Spatial heterogeneity in tropical forests reflects variation in ecosystem structure and function governed by climate, edaphic conditions, evolutionary history, and natural and anthropogenic disturbance histories and remote sensing provides a powerful tool for measuring heterogeneity in ecosystem structure and function at large spatial scales. To examine the mechanisms that underpin patterns of spatial heterogeneity and tropical forest productivity, we integrated measurements of forest structure and function, derived from LiDAR data and high-fidelity imaging spectroscopy (HiFIS) data from a Visible-Shortwave Imaging Spectrometer (VSWIR) collected by the Carnegie Airborne Observatory (CAO), with the mechanistic ecosystem demography model (ED2). ED2 tracks fine-scale ecosystem dynamics at individual plant and patch scales, with the ability to aggregate processes at larger scale. We explore the contribution of spatial heterogeneity in forest structure and functional composition to modeled vegetation demographics and productivity across lowland tropical forests in Southeast Asia.
Results/Conclusions
We found that structural and functional differences between sites spanning an edaphic gradient in Southeast Asia contribute to observed sub-regional variation in productivity. We also found that plant functional types parameterized with regionally constrained trait values yielded more accurate modeled demographics and productivity. Our study provides the first application of ED2 in Southeast Asian tropical forests, offering insight into the underlying biological processes that influence how regional and sub-regional spatial heterogeneity govern observed patterns of variation in ecosystem productivity.