Leaf optical properties reflect variation in photosynthetic metabolism and its sensitivity to temperature

Abstract

Researchers from a number of disciplines have long sought the ability to estimate the functional attributes of plant canopies, such as photosynthetic capacity, using remotely sensed data. To date, however, this goal has not been fully realized. In this study, fresh-leaf reflectance spectroscopy (λ=450–2500 nm) and a partial least-squares regression (PLSR) analysis were used to estimate key determinants of photosynthetic capacity—namely the maximum rates of RuBP carboxylation (Vcmax) and regeneration (Jmax)—measured with standard gas exchange techniques on leaves of trembling aspen and eastern cottonwood trees. The trees were grown across an array of glasshouse temperature regimes. The PLSR models yielded accurate and precise estimates of Vcmax and Jmax within and across species and glasshouse temperatures. These predictions were developed using unique contributions from different spectral regions. Most of the wavelengths selected were correlated with known absorption features related to leaf water content, nitrogen concentration, internal structure, and/or photosynthetic enzymes. In a field application of our PLSR models, spectral reflectance data effectively captured the short-term temperature sensitivities of Vcmax and Jmax in aspen foliage. These findings highlight a promising strategy for developing remote sensing methods to characterize dynamic, environmentally sensitive aspects of canopy photosynthetic metabolism at broad scales.

Reviews and Syntheses: optical sampling of the flux tower footprint

“…Critical biochemical aspects of photosynthetic regulation (e.g., Rubisco activation) occur over similarly short timescales, and this biochemical capacity, illustrated as carboxylation capacity (V cmax ) and electron transport capacity (J max ) in Fig. 1, can be assessed with optical methods (Serbin et al, 2012). In parallel to these photochemical and biochemical regulatory processes, leaf structure, ultrastructure, and pigmentation are adjusted over minutes (in the case of chloroplast or rapid leaf movement) to days or weeks (in the case of pigment pool sizes and leaf area index) (Björkman and Demmig-Adams, 1994).…”

“…Over the past 2 decades, the functional significance of gradual changes in carotenoid pigment pools has received far less attention than the shortterm regulation of the xanthophyll cycle, despite the clear importance of pigment pool sizes as indicators of vegetation stress responses (Sims and Gamon, 2002). Neither the slow nor the rapid pigment responses have yet been fully addressed in mechanistic models of photosynthesis, which tend to focus more on biochemical processes (e.g., V cmax , Serbin et al, 2012). Thus, there is potential to develop more integrated photosynthesis models that link the full range of pigment responses and concurrent optical signals (including Figure 5.…”

“…Depending upon the specific sampling goal, some methods use relatively few, discrete bands to assess particular features, while others may utilize the full spectral range, yielding a seemingly infinite number of sampling possibilities. Similarly, analytical approaches can range from specific targeted approaches using a few optimal formulations (e.g., Gamon, 2002, 2003) to more openended statistical methods to discover which bands or formulations can yield the best result for a given purpose or context (e.g., Serbin et al, 2012). Proper attention to waveband definition (both spectral position and bandwidth) is essential, particularly for detecting specific physiological features (e.g., pigments, water content, or chlorophyll fluorescence).…”

“…However, the literature largely remains a series of site-based observations, and we are still a long way from a comprehensive understanding of how best to integrate optical and flux measurements across biomes. Similarly, most analyses have been limited to one or a few vegetation indices, rather than exploring the full power of the electromagnetic spectrum, but improvements in instrumentation and data processing methods are now beginning to change that (Ustin et al, 2004;Serbin et al, 2012;Campbell et al, 2013). Comparative, experimental approaches are needed both within and across sites.…”

“…In addition to the optical sampling methods, other methods not fully discussed here, including thermal, lidar, microwave, and acoustic remote sensing, can add to our understanding of functional processes within the footprint. To obtain a deeper mechanistic understanding, the LUE approach can be compared to other, more biochemically based models of photosynthetic carbon flux (e.g., Sellers et al, 1992bSellers et al, , 1996Serbin et al, 2012). Presumably, integration of several different and complementary optical methods (e.g., reflectance with fluorescence and canopy absorbance, including indices and fullspectral approaches) would provide a more complete assessment of ecosystem function than any single method alone (Fig.…”