Relationships between photosystem II efficiency and photochemical reflectance index under different levels of illumination: comparison among species grown at high- and low elevations through different seasons

Abstract

Previously, we found a significant association between photosystem II efficiency (I broken vertical bar PSII) and photochemical reflectance index (PRI) measured at predawn among different species at different elevations and throughout several seasons. However, this relationship has not been evaluated under varied levels of illumination. Here, we used the Taiwan species Pinus taiwanensis (a conifer distributed at 750-3,000 m a.s.l.), Stranvaesia niitakayamensis (an evergreen tree, 1,700-3,100 m) and two Miscanthus spp. (perennial C-4 Gramineae, coastline-3,200 m) to elucidate the I broken vertical bar PSII-PRI relationship. We studied six levels of photosynthetic photon flux density (PPFD) (0, 200, 400, 800, 1,200 and 2,000 mu mol m(-2) s(-1)) over several growth seasons at high (2,600 m a.s.l.) and low (800 m a.s.l.) elevation sites. In comparing the same species or genus, I broken vertical bar PSII and PRI were closely correlated in darkness or under the same level of PPFD, with data obtained from different seasons and elevations pooled for regression analysis. Because both the intercept and slope of the I broken vertical bar PSII-PRI equation showed a negative curvilinear correlation with PPFD, we could fit an empirical regression model, I broken vertical bar PSII = c + d center dot ln(PPFD) + e center dot[ln(PPFD)](2) + f center dot PRI + g center dot PRI center dot ln(PPFD) + h center dot PRI center dot[ln(PPFD)](2), for multiple regression analysis. Using this model, we found a close correlation between the estimated and measured I broken vertical bar PSII (r (2) = 0.842-0.937, P < 0.001) for all four species examined and for mango (Mangifera indica) measured under both artificial illumination and sunlight (data from Weng et al. 2010). This empirical regression model could simulate both seasonal and diurnal variations of leaf-scale photosynthetic efficiency at high and low elevations

Interspecific differences in photosynthetic efficiency and spectral reflectance in two Umbilicaria species from Svalbard during controlled desiccation

“…Similar response was found by Stylinski et al (2000) who reported that an increase in photosynthetic electron rate brought an increase in PRI in Quercus pubescenc leaves exposed to natural and elevated CO 2 concentrations. Positive relation between Φ PSII and PRI was also found in grasses (Weng et al 2012) as well as two srubs Baccharis halimifolia and Myrica cerifera exposed to salt stress (Zinnert et al 2012).…”

Relation of Photochemical Reflectance Indices Based on Different Wavelengths to the Parameters of Light Reactions in Photosystems I and II in Pea Plants

“…It is important that intensities of the reflected light can be used for the calculation of reflectance indices, because analysis based on these indices has low errors in comparison with the analysis of absolute values of the reflected light [10]. It is known that reflectance indices permit to estimate different characteristics of plants, including the growth of biomass [21], the photosynthetic efficiency and photosynthetic stress responses [16][17][18][19][20]23,33,58,70,71], the changes in biochemical compositions [29][30][31][32][33][34][35][36], the transpiration [72,73], the isoprene emission [20,24,25], etc.…”

“…There are numerous investigations that analyze the relations of the modifications of reflectance with the responses of physiological processes (including photosynthesis and its regulation [16][17][18][19][20], growth [21], water exchange [14,22,23], isoprene emission [20,24,25], electrical activity [26][27][28], etc. ), the changes in biochemical content (including concentrations of chlorophylls [29][30][31], carotenoids [32][33][34], nitrogen compositions [35,36], etc.…”

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

“…PRI values during growth were lower for sunlit than shaded leaves [83,112] and were higher for dark-green than either light-or yellow-green leaves [83,87]. PSII efficiency could not be efficiently tracked by PRI in varying light intensities, seasons and leaf colors due to the influence of chlorophyll, low temperature at night or low illumination on reflectance, which inhibit the epoxidation of the xanthophyllic cycle and retain more xanthophyllic pigments [87,113]. Likewise, the tracking of seasonal levels of Chlorophyll a/b (Chl a/b) using PRI was affected by high non-photochemical dissipation from the senescence of the vegetation and drought stress in desert species during growth [114].…”

“…The accuracy of the simulated PRI from ACRM (A Markov chain Analytical two-layer Canopy Reflectance Model) was affected by canopy structural change and thus led to inaccurate estimates of RUE and GPP [83]. Empirical regression models were effectively used to assess PRI and ecophysiological variation [87,109,113,124]. Devising a valid model is therefore important for accurately estimating PRI and providing a continuous assessment of GPP.…”