Biodiversity is believed to be closely related to ecosystem functions. However, the ability of existing biodiversity measures (e.g., species richness and phylogenetic diversity) to predict ecosystem functions remains elusive. Here, we present a new vector of diversity metrics, structural diversity, which directly incorporates niche space in measuring ecosystem structure, to predict ecosystem functions. Using LiDAR data across USA and forest inventory data across North America (Mexico, USA, and Canada), we show that structural diversity provides better predictive ability of key ecosystem functions than traditional biodiversity measures.
Results/Conclusions
We show that LiDAR-derived structural diversity is a better predictor of key ecosystem functions, such as productivity, energy, and nutrient dynamics than existing biodiversity measures. Our stem inventory based analysis also clearly demonstrated that structural diversity is a better predictor of productivity than traditional biodiversity measures. As LiDAR data and filed inventory data are becoming readily available, we advocate for the use of structural diversity for better predictions of ecosystem functions.