Relationships between photochemical reflectance index and light-use efficiency in deciduous and evergreen broadleaf forests
Introduction
Forests are subjected to climate events with different intensities. Severe droughts can cause significant effects such as leaf discoloration, leaf browning, and early leaf loss (Bréda et al., 2006, Carnicer et al., 2011). These effects may lead to a decrease of forest productivity and a higher vulnerability to fire and to the proliferation of devastating opportunistic pathogens in the following years (La Porta et al., 2008). Under moderate water, temperature, or light stress, these effects are not as significant; however, the physiological state of the trees, the water use and carbon exchanges may be significantly affected. Under such environmental conditions, the available energy exceeds the capacity of the utilization of light in photosynthesis and the excess of energy is dissipated as fluorescence and heat according to many mechanisms, which are grouped under the generic term of non-photochemical quenching (NPQ) (as opposed to the photochemical processes involved in photosynthesis). The most important mechanism involved in NPQ processes is associated with changes in the composition of carotenoid pools known as the xanthophyll cycle (Demmig-Adams and Adams, 1996, Jahns and Holzwarth, 2012, Ort, 2001, Yamamoto, 2006). Changes in the concentration of xanthophylls are accompanied by changes in reflectance at approximately 531 nm (Gamon et al., 1992, Gamon et al., 1997). Gamon et al., 1992, Gamon et al., 1997 developed the photochemical reflectance index (PRI) using the narrow-band reflectance at 531 nm and a reference band at 570 nm – assumed to be insensitive to variations in the concentrations of xanthophylls – and suggested using this index as a remotely sensed proxy to track changes in the xanthophyll cycle pigment content at the leaf scale and to predict the light-use efficiency (LUE) for many herbaceous and woody species (Gamon and Surfus, 1999, Sims and Gamon, 2002).
Remote sensing is a powerful tool that provides important information concerning the structure and functioning of forest ecosystems due to its unique potential in terms of spatial and temporal resolutions. The potential use of this tool was mainly evaluated to monitor temporal changes of the forest canopy structure when these changes are accompanied by significant variations in the amount of green leaf biomass or in the chlorophyll content. However, there are still limited studies that focus on the evaluation of remote sensing to monitor the ecophysiological responses at the canopy scale. It may be noted that LUE-based models of gross primary production (GPP) (Hilker et al., 2008) such as the MODIS GPP model (Turner et al., 2006), Glo-PEM (Prince & Goward, 1995) and CASA (Potter et al., 1993) applied at regional and global scales using remote-sensing data do not explicitly account for the large variations in LUE at short time scales. In the MODIS-based GPP approach, a constant biome-specific maximum LUE is used and short-term temporal variations of this parameter are implicitly considered using modulation factors that depend only on the VPD (vapor pressure deficit) and air temperature. This type of modulation may be insufficient to account for the effects of the soil water deficit on GPP because meteorological and edaphic factors are decoupled at short time scales (Hwang et al., 2008, Pan et al., 2006, Turner et al., 2005). The explicit consideration of these effects in the model may be necessary, as suggested by Gebremichael and Barros (2006) and Mu et al. (2007).
The pioneering works of Gamon et al. (Filella et al., 1996, Gamon et al., 1992, Gamon et al., 1997, Peñuelas et al., 1995) demonstrated that it is possible to track short-term changes in LUE at the leaf and canopy scales by clearly demonstrating the sensitivity of PRI to the photosynthetic activity due to variations in environmental conditions. At the canopy scale, especially above complex structures such as forests, recent studies have reported contrasting results, highlighting the combined effects of exogenous factors, especially solar and viewing angles, and the structural and biochemical attributes of the canopy. Using MODIS bands, Drolet et al., 2005, Drolet et al., 2008 observed good relationships between PRI and LUE in the back-scattering direction (relative azimuth angle − difference between the sensor and sun azimuth angles < 60°) and under a relative zenith angle (difference between the sensor and sun zenith angles) less than 10° and explained these results based on the lower proportion of shaded leaves compared with the forward-scattering direction. Hall et al. (2008) and Hilker et al. (2009) showed the strong dependency of PRI on within-canopy light conditions and established two distinct relationships between PRI and LUE for sunlit and shaded foliage surfaces, respectively. These authors explained these differences based on the changes in the xanthophyll cycle that lead to the decrease in LUE for the sunlit foliage surface exposed to strong light above a saturating point. Hall et al. (2008) noted that the PRI–LUE relationship is better for a sunlit foliage surface, confirming the findings of Gamon et al. (1997). The effects of illumination and viewing angle on the relationship between MODIS-based PRI and LUE were also highlighted by Goerner, Reichstein, and Rambal (2009). The strongest relationships were obtained for viewing angles close to the nadir and in the range of 30–40° from the zenith. In addition to these factors, Goerner et al. (2009) noted the direct and indirect effects of atmospheric conditions that severely degrade the quality of the PRI signal and introduce bias in the relationships between PRI and LUE by restricting the LUE variability to a narrow range because only cloud-free MODIS images can be used.
The studies cited above highlight the difficulty in assessing the relationships between PRI and LUE at canopy scale. This is due to a multitude of factors that may influence the reflectance in PRI bands directly through the effects of biochemical and structural canopy characteristics, sun-view geometry and atmospheric conditions and indirectly through the xanthophyll cycle and thus canopy photosynthesis (light conditions, soil water content, VPD, temperature, etc.). In addition, it is still more complicated to achieve this task using satellite data because the spatial, temporal, and spectral data of the sensors available onboard spatial platforms are not optimal.
In this study, we evaluate the relationships between PRI and LUE from continuous in situ measurements of PRI and net CO2 exchange data acquired on a half-hourly basis in two deciduous and evergreen mature forests in France. Eight years of simultaneous measurements of PRI and carbon fluxes are analyzed in this study. To the best of our knowledge, this data set is the longest time-series data set of in situ PRI measurements. Specifically, the objectives of this study involve the following: (1) investigating the daily, seasonal, and interannual variations of PRI and LUE; (2) linking the PRI variations to major influencing meteorological and eco-physiological variables; and (3) developing an approach for the disentangling the effects of canopy structure and leaf biochemistry that affect the PRI vs. aPAR and PRI vs. LUE relationships on a seasonal scale.
Section snippets
Study site
This study was undertaken in two mature forests (FLUXNET site codes: FR-Fon and FR-Pue; www.fluxnet.ornl.gov) differing in their vegetation types and climates. The first one, located near Fontainebleau (48°28′35″N/2°46′48″E) — southeast of Paris, corresponds to a temperate forest representative of the main deciduous broad leaf forest type in Europe. The forest stand is managed as mature deciduous forest occupied by two main overstory species of pedunculate and sessile oaks (Quercus robur L. and
Temporal patterns of the NDVI, aPAR, GPP, LUE, and PRI in the two forests
Fig. 1 illustrates the seasonal and interannual variations of the NDVI, aPAR, GPP, LUE, and PRI in 2010 in the two forest stands.
In Fontainebleau forest from 2006 to 2011, the NDVI, aPAR, GPP, LUE, and PRI exhibit similar patterns to that presented in Fig. 1. The temporal pattern of the NDVI indicates the typical seasonal variations of green canopy foliage in deciduous forests. This seasonal dynamic is characterized by two main phases: the leafy season during mid-spring and summer and the
Discussion
At the seasonal scale (Fig. 1), the temporal patterns of PRI and NDVI are similar, indicating that the temporal changes of PRI are primarily controlled by the seasonal phenology that modifies both the leaf area and biochemical properties of the canopies. Fig. 1 also demonstrates that during periods of stable total canopy leaf area during summer, the short-term variations in PRI are greater than those in NDVI, suggesting that these two indices are relatively independent.
At the seasonal scale,
Conclusions
Our study highlights the strong dependency between PRI and two categories of factors. At the seasonal scale, the temporal dynamics of PRI is primarily controlled by the phenology and the temporal dynamics of the structural and biochemical characteristics of the canopy. Thus, from this point of view, PRI is similar to other spectral indices sensitive to canopy structure such as the NDVI and to some other spectral biochemical indices sensitive to leaf chlorophyll and carotenoid contents. At a
Acknowledgments
The authors thank GIP ECOFOR and SOERE F-ORE-T (Systèmes d'observation et d'expérimentation pour la recherche en environnement). We would like to express our profound gratitude to Jean Yves Pontailler, Laurent Vanbostal and all other persons involved in the data collection process. We are also very grateful for thorough and helpful comments from the reviewers of the manuscript.
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