Spectral reflectance from a soybean canopy exposed to elevated CO2 and O3

Abstract

By affecting the physiology and structure of plant canopies, increasing atmospheric CO2 and O3 influence the capacity of agroecosystems to capture light and convert that light energy into biomass, ultimately affecting productivity and yield. The objective of this study was to determine if established remote sensing indices could detect the direct and interactive effects of elevated CO2 and elevated O3 on the leaf area, chlorophyll content, and photosynthetic capacity of a soybean canopy growing under field conditions. Large plots of soybean (Glycine max) were exposed to ambient air (∼380 μmol CO2 mol−1), elevated CO2 (∼550 μmol mol−1), elevated O3 (1.2× ambient), and combined elevated CO2 plus elevated O3 at the soybean free air gas concentration enrichment (SoyFACE) experiment. Canopy reflectance was measured weekly and the following indices were calculated from reflectance data: near infrared/red (NIR/red), normalized difference vegetation index (NDVI), canopy chlorophyll content index (chl. index), and photochemical reflectance index (PRI). Leaf area index (LAI) also was measured weekly. NIR/red and LAI were linearly correlated throughout the growing season; however, NDVI and LAI were correlated only up to LAI values of ∼3. Season-wide analysis demonstrated that elevated CO2 significantly increased NIR/red, PRI, and chl. index, indicating a stimulation of LAI and photosynthetic carbon assimilation, as well as delayed senescence; however, analysis of individual dates resolved fewer statistically significant effects of elevated CO2. Exposure to elevated O3 decreased LAI throughout the growing season. Although NIR/red showed the same trend, the effect of O3 on NIR/red was not statistically significant. Season-wide analysis showed significant effects of O3 on PRI; however, analysis of individual dates revealed that this effect was only statistically significant on two dates. Elevated O3 had minimal effects on the total canopy chlorophyll index. PRI appeared to be more sensitive to decreased photosynthetic capacity of the canopy as a whole compared with previously published single leaf gas exchange measurements at SoyFACE, possibly because PRI integrates the reflectance signal of older leaves with accumulated O3 damage and healthy young, upper canopy leaves, enabling detection of significant decreases in photosynthetic carbon assimilation which have not been detected in previous studies which measured gas exchange of upper canopy leaves. When the canopy was exposed to elevated CO2 and O3 simultaneously, the deleterious effects of elevated O3 were diminished. Reflectance data, while less sensitive than direct measurements of physiological/structural parameters, corroborate direct measurements of LAI and photosynthetic gas exchange made during the same season, as well as results from previous years at SoyFACE, demonstrating that these indices accurately represent structural and physiological effects of changing tropospheric chemistry on soybean growing in a field setting.

Affecting Factors and Recent Improvements of the Photochemical Reflectance Index (PRI) for Remotely Sensing Foliar, Canopy and Ecosystemic Radiation-Use Efficiencies

“…Differences in the correlations between PRI and RUE for different types of vegetation can be due to differences in the canopy structure and shadow fraction, however, when the canopy is detected from only one angle (as with MODIS) [4], highlighting the importance of the effect of the canopy structure on PRI. PRI was also sensitive to changes in the structure and physiology during the soybean growing season caused by elevated CO 2 and O 3 concentrations [127]. Canopy PRI values were higher during the growth phase than other phases [83,129] and did not efficiently track RUE variability during the ripening stage [129].…”

“…Structural changes of the canopy caused by sustained water stress [120,123,125,126] or a varying leaf area index (LAI) [127] over the season led to PRI variability and loss of the seasonal relationship between PRI and RUE. PRI calculated from pure crown reflectance for fruit trees under different irrigation regimes varied with xanthophyllic pigment contents and not with vegetation structure or chlorophyllic content [128].…”

Developmental Changes of the Photochemical Reflectance Index (PRI), Chlorophyll Fluorescence and Leaf Pigments Show the Adaptability of Trees to Local Environments

“…Furthermore, projected environmental changes in water, nutrient, temperature, CO 2 , ultraviolet radiation, ozone and pathogens will negatively influence growth and induce an onset of the senescence process, independent of the natural recourse of leaf senescence [27] [28] [29] [30]. Therefore, the analysis or diagnosis of the physiological status of plants is a complex process involving several components that differ with respect to time and kinetics.…”

Algorithm for Soybean Classification Using Medium Resolution Satellite Images

“…Additionally, all four conditions are modulated by NDVI values greater than 0.6 units in order to avoid background and/or cloud contamination that usually have high values of reflectance. Also, saturation effects of Normalized Difference Vegetation Index (NDVI) when Leaf Area Index (LAI) is greater than 3 can mask water stress [31].…”