PARENT SESSION
Oral Session # 85: GIS and Remote Sensing II; Ecological Modeling III.
Presiding: Y Lin
Thursday, August 7. 1:30 PM to 5:00 PM, SITCC Meeting Room 203.

Relationships between vegetation greenness and ecosystem CO₂ flux in southern California chaparral: A test of the functional convergence hypothesis.

Sims, Daniel^*,1, Oechel, Walter², Luo, Hongyang², Gamon, John¹, ¹ California State University, Los Angeles, CA² San Diego State University, San Diego, CA

ABSTRACT- Correlations between vegetation greenness and CO₂ flux have been found across a wide range of ecosystems. This observation led to the functional convergence hypothesis stating that capacity for CO₂ fixation should be curtailed whenever a limitation in the availability of any resource prevents the efficient exploitation of additional capacity. Remote sensing data used to support the functional convergence hypothesis have all been gathered over long time periods (one year or more) and across diverse ecosystems. In this study, we tested the functional convergence hypothesis within one ecosystem (southern California chaparral) and collected spectral reflectance data at monthly intervals. Ecosystem CO₂ flux was measured continuously with the eddy covariance technique. In order to better match the temporal and spatial scales of the spectral reflectance measurements to those of the eddy flux, we installed an automated tram system within the eddy flux tower footprint. This system measured hyperspectral reflectance over a 100 m transect throughout the diurnal cycle. Since we observed large effects of diurnal and seasonal variation in solar elevation angle on NDVI, we defined the inherent vegetation greenness as NDVI at a solar elevation angle of 40 degrees. Large seasonal and inter-annual variation in ecosystem carbon flux rates, resulting from annual summer droughts and the severe drought of 2002, provided a strong test of the relationships between CO₂ flux and vegetation greenness. CO₂ flux was strongly correlated with NDVI at a constant solar elevation angle (i.e. vegetation greenness) but was only weakly correlated with NDVI measured at noon. In contrast to previous studies, this correlation between CO₂ flux and vegetation greenness did not imply a constant light use efficiency (LUE) of the vegetation. In fact LUE varied widely, approaching values associated with crop plants during favorable environmental conditions and dropping to zero during the severe drought. Our results suggest that it may be possible to predict CO₂ flux directly from vegetation greenness without any assumptions about LUE.

Key words: NDVI, eddy covariance, remote sensing, CO2 flux