Functional diversity from airborne imaging spectroscopy explains stability in GPP from flux towers

Imaging spectroscopy (IS) enables characterization of foliar functional traits across Earth’s biomes. Foliar functional traits are widely used to estimate functional diversity, which can be a proxy for many dimensions of biodiversity. Here we integrate data from three airborne imaging spectroscopy campaigns spanning the 

Imaging spectroscopy (IS) enables characterization of foliar functional traits across Earth’s biomes. Foliar functional traits are widely used to estimate functional diversity, which can be a proxy for many dimensions of biodiversity. Here we integrate data from three airborne imaging spectroscopy campaigns spanning the Arctic to subtropical biomes to test whether functional richness derived from imaging spectroscopy confers stability in seasonal variation in GPP derived from eddy covariance flux towers, controlling for phenology and weather. Data include NASA’s ABoVE campaign in the Arctic-Boreal zone, NEON covering the biomes of North America, and an intensive study in the northern temperate forests of Wisconsin, USA (CHEESEHEAD). We aligned the imaging spectroscopy data with GPP estimates from 90 flux towers, and estimated stability as a metric of GPP variation detrended for phenological effects. We find a significant relationship between functional richness and GPP stability, with towers in more functionally diverse landscapes exhibiting greater seasonal stability in GPP. Relationships between functional richness and GPP vary by biome type, and the strengths of the relationships depend on the functional traits used to compute functional richness. With a suite of over 25 traits including nitrogen, leaf mass per area, nonstructural carbohydrates, lignin, phenolics and others, this points to the importance of initial analyses to identify the key traits describing vegetation in a region. These analyses provide conditional support for a positive relationship between ecosystem stability and functional diversity. More broadly, our results point to the promise of global trait estimations from satellite imaging spectroscopy to provide new insights into the drivers of diversity-productivity relationships.