Near-surface remote sensing of canopy architecture and land-atmosphere interactions in an oak savanna ecosystem
Canopy architecture plays fundamental roles in the land-atmosphere interactions, yet quantification of canopy architecture using optical sensors in an open canopy remains a challenge. Savannas are spatially heterogeneous, open ecosystems, thus efforts to quantify canopy structure with methods developed for homogeneous, closed canopies are prone to failure. I employed a multi-model and multi-instrument approach to quantify leaf area index in an oak savanna ecosystem of California. I found that the effective area index should be calculated by taking the logarithm of average gap fraction. Contrary to boreal and temperate forests, the savanna ecosystem was highly clumped at the ecosystem scale (clumping index=0.49). Thus quantification of clumping effects at the ecosystem scale, which has been overlooked in most leaf area index products, is crucial to obtain the correct leaf area index.
To investigate how evaporation in the annual grassland of the savanna ecosystem is modulated by biological/environmental factors, I investigated the 6 year evaporation data measured with a eddy covariance system. The annual evaporation ranged between 266 mm to 391 mm despite a two-fold range in precipitation. I found that the pronounced energy-limited and water-limited periods occurred within the same year. In the water-limited period, monthly integrated evaporation scaled negatively with solar radiation and was restrained by precipitation. In the energy-limited period, on the other hand, the majority of evaporation scaled positively with solar radiation and was confined by potential evaporation. Evaporation was most sensitive to the availability of soil moisture during the transition to the senescence period rather than the onset of the greenness period, causing annual evaporation to be strongly modulated by the length of growing season.
To bridge canopy structure, function and metabolism, I tested the use of light emitting diodes (LEDs) to monitor the vegetation reflectance in narrow spectral bands. LEDs are appealing because they are inexpensive, small and reliable light sources that used in reverse mode, can measure spectrally selective radiation. To test the efficacy of this approach, I measured the spectral reflectance with LEDs in red and near-infrared wavebands, which are used to calculate the normalized difference vegetation index over the grassland over 3.5 years. The LED-spectrometer captured daily to inter-annual variation of the spectral reflectance at the two bands with reliable and stable performance. The spectral reflectance in the two bands and NDVI proved to be useful to identify the leaf-on and leaf-off dates (mean bias errors of 5.3 and 4.2 days, respectively) and to estimate the canopy photosynthesis (r2=0.91). I suggest that this novel instrument can monitor other structural and functional (e.g. leaf area index, leaf nitrogen) variables by employing the LEDs that have other specific wavelengths bands. Considering that off-the-shelf LEDs cover a wide range of wavebands from the ultraviolet to near-infrared regions, I believe that the research community could explore a range of similar instruments across a range of bands for a variety of ecological applications.
The regular monitoring of evaporation from satellites has been limited because of discontinuous temporal coverage. Here, I found a strong linear relationship between mean hourly λE (i.e., 1000-1100hh; 1100-1200hh; 1200-1300hh; 1300-1400hh) and 8-day means of λE at 26 eddy covariance flux towers across seven plant functional types from boreal to tropical climatic zones. Hourly time steps of evaporation were selected to correspond with potential overpass times of the MODIS Terra and Aqua satellites. The mean slope of the linear relationship between mean hourly means of evaporation and 8-day, 24-h evaporation means showed no significant differences among sites and for each of the four mid-day hours. The results suggest a factor of 0.370 (95% CI: 0.354, 0.385) can be used to temporally upscale instantaneous evaporation measurements averaged over 8-day periods to an 8-day mean evaporation.