Using remotely sensed foliar traits to capture spatial variation in tropical forest productivity across edaphic gradients with a dynamic global vegetation model

Our understanding of biogeochemical cycles in tropical forests remains limited despite the important role these ecosystems play in the Earth's carbon cycle. Spatial heterogeneity in tropical forest productivity and resulting rates of carbon uptake and storage stem from variation in ecosystem structure and function reflecting differences in climate, edaphic conditions, evolutionary history, and natural and anthropogenic disturbance histories. Remote sensing provides a powerful tool for measuring heterogeneity in ecosystem structure and function at large spatial scales. To examine whether plant traits related to photosynthetic capacity (specifically, SLA, foliar N, and foliar P) can be used to improve predictions of tropical biomass dynamics and carbon fluxes, we parameterized a terrestrial biosphere model (ED2) using foliar traits derived from high-fidelity imaging spectroscopy (HiFIS) data from a Visible-Shortwave Imaging Spectrometer (VSWIR) collected by the Global Airborne Observatory (formerly Carnegie Airborne Observatory) across an edaphic gradient in Borneo. ED2 incorporates vertical and horizontal heterogeneity in fine-scale ecosystem dynamics at the scales of individual plants and predicts the resulting emergent properties of ecosystem composition, structure and functioning at local-to-regional scales. We find significant site-level differences in relationships between SLA and foliar nutrient concentrations, suggesting that remotely sensed foliar traits can be used to capture variation in photosynthetic capacity at large, edaphically varying spatial scales. We further show that plant functional types parameterized with site constrained trait values yielded more accurate predictions of canopy demography, forest productivity and above-ground biomass dynamics. Our study offers insight into the underlying biogeochemical processes that influence how spatial heterogeneity in nutrient availability governs observed patterns of variation in ecosystem productivity.