Biodiversity is a key component driving ecosystem stability and productivity under global change. With the recent recognition of the importance of trait-based biodiversity assessments, a way to map, monitor and predict changes in plant functional diversity and functioning is urgently needed. In previous research, we demonstrated how one can measure plant functional diversity by remote sensing in a spatially explicit and continuous way. Now, we show how we can estimate productivity based on remote sensing and ED2 modeling for different sites and in a future step, we can assess the relationship between the two as normally done with ground-based data of productivity and trait diversity.
We developed a method to map canopy structure and composition as well as corresponding functional diversity at very high spatial resolution using airborne laser scanning and imaging spectroscopy data. We applied this method to a temperate mixed forest in Switzerland (Laegern, CH) to characterize and initialize five forest sites, spanning an elevation gradient with changing canopy structure and composition as well as soil type and depth, in the ecosystem demography model ED2. The modeling framework allows interchanging structure, composition and soils of the sites, helping to answer the question what is driving productivity across sites within an ecosystem.
Results/Conclusions
A comparison with ground based measurements showed accurate forest structure and composition derived from remote sensing data and the ability to predict monthly carbon (GPP, NEP, R) and water fluxes (ET) with the ED2 model at a flux tower, which is located on one of the sites. Applying this modeling approach to all five sites for the years 2006 to 2015 will offer the opportunity to simulate different combinations of structure, composition and soils to disentangle their effects on ecosystem functioning over time. Furthermore, functional diversity mapped from remotely sensed plant functional traits showed a diversity gradient among the sites from higher diversity at lower elevation with flatter, deeper soils to lower diversity at higher elevation with steep, rocky and shallow soils. This could be an indication of environmental filtering and potentially higher vulnerability to change and overall lower productivity. Exploring this gradient using the modeling framework will allow us to test the hypothesis that functionally more diverse forest communities are more productive over time, and to disentangle whether morphological or physiological diversity or the environment is driving the diversity-productivity relationship at sites within an ecosystem.