Given the known heterogeneity in ecological processes within plant communities in California, we questioned whether the concept of conventional plant functional types (cPFTs) was adequate to characterize the functionality of the dominant species in these communities. We examined seasonal (spring, summer, fall) airborne AVIRIS and MASTER imagery collected during three years of progressive drought in California, and airborne LiDAR acquired once, for ecosystems that represent a wide range of plant functional types, from annual agriculture and herbaceous perennial wetlands, to forests and shrublands, including broadleaf deciduous and evergreen species and conifer species. These data were used to determine the extent to which changes in canopy chemistry could be detected, quantified, and related to leaf and canopy traits that are indicators of physiological functioning (water content, Leaf Mass Area, total C, N, and pigments (chlorophyll a, b, and carotenoids). At the canopy scale we measured leaf area index, and for forests — species, height, canopy area, DBH, deciduous or evergreen, broadleaf or needleleaf, and gap size. Strong correlations between leaf and canopy traits were predictable and quantifiable from spectroscopy data. Key structural properties of canopy height, biomass and complexity, a measure of spatial and vertical heterogeneity, were predicted by AVIRIS and validated against LiDAR data. Our data supports the hypothesis that optical sensors provide more detailed information about the distribution and variability in leaf and canopy traits related to plant functionality than cPFTs.
|Number of pages||1|
|Publication status||Published - Dec 2015|
|Event||AGU fall meeting 2015 - San Francisco, United States|
Duration: 14 Dec 2015 → 18 Dec 2015
|Conference||AGU fall meeting 2015|
|Period||14/12/15 → 18/12/15|