Can plant traits be used to classify functionality in remote sensing data

Background/Question/Methods

Detecting and monitoring changes in physiological functioning and changes in species composition provides key information needed to address a wide range of environmental concerns, from ecological restoration and biodiversity conservation to land use changes and climate change.  The use of Plant Functional Types (PFTs), based on growth form (herb, shrub, tree) and whether leaves are deciduous or evergreen, were introduced in ecosystem and climate models to increase the accuracy of predicted functionality, particularly with regard to carbon, water and nitrogen fluxes and storage.  Mapping PFTs has received widespread use in environmental remote sensing applications. Using plant traits to characterize ecophysiological functions is an alternative approach developed in the botanical and ecological literature.  This approach focuses on leaf traits associated with functionality, independent of the growth form, allowing multiple types of functionality within a traditional PFT.  Using field-based spectroscopy, biochemical, and ecological methods, we address the extent to which PFTs are associated with characteristic biophysical and biochemical properties or whether biophysical and biochemical groupings better describe trait assemblages.  We used and airborne hyperspectral imagery of plant communities in California, that represent different PFTs, to identify whether leaf and canopy traits can be detected and mapped across complex terrain and mixed communities. 

Results/Conclusions

We show differences in leaf biochemical traits related to chlorophyll and carotenoid pigments, water content, total carbon and nitrogen concentrations, dry biomass, and leaf mass area within traditional plant PFTs that are detectable from leaf spectroscopy and airborne imaging spectroscopy.  At the leaf and canopy scale we show association of trait clusters that have been related to differences in stress tolerance in the ecological literature. These results show promise for eventual high spatial resolution mapping of canopy physiological functioning.