Within‐canopy variation in the rate of development of photosynthetic capacity is proportional to integrated quantum flux density in temperate deciduous trees

Abstract

The present study was undertaken to test for the hypothesis that the rate of development in the capacity for photosynthetic electron transport per unit area ( J max;A ), and maximum carboxylase activity of Rubisco ( V cmax;A ) is proportional to average integrated daily quantum flux density ( Q int ) in a mixed deciduous forest dominated by the shade-intolerant species Populus tremula L., and the shade-tolerant species Tilia cordata Mill. We distinguished between the age-dependent changes in net assimilation rates due to modifications in leaf dry mass per unit area ( M A ), foliar nitrogen content per unit dry mass ( N M ), and fractional partitioning of foliar nitrogen in the proteins of photosynthetic electron transport ( F B ), Rubisco ( F R ) and in light-harvesting chlorophyll-protein complexes. In both species, increases in J max;A and V cmax;A during leaf development were primarily determined by nitrogen allocation to growing leaves, increases in leaf nitrogen partitioning in photosynthetic machinery, and increases in M A . Canopy differences in the rate of development of leaf photosynthetic capacity were mainly controlled by the rate of change in M A . There was only small within-canopy variation in the initial rate of biomass accumulation per unit Q int (slope of M A versus leaf age relationship per unit Q int ), suggesting that canopy differences in the rate of development of J max;A and V cmax;A are directly proportional to Q int . Nevertheless, M A , nitrogen, J max;A and V cmax;A of mature leaves were not proportional to Q int because of a finite M A in leaves immediately after budburst (light-independent component of M A ). M A , leaf chlorophyll contents and chlorophyll : N ratio of mature leaves were best correlated with the integrated average quantum flux density during leaf development, suggesting that foliar photosynthetic apparatus, once developed, is not affected by day-to-day fluctuations in Q int . However, for the upper canopy leaves of P. tremula and for the entire canopy of T. cordata , there was a continuous decline in N contents per unit dry mass in mature non-senescent leaves on the order of 15-20% for a change of leaf age from 40 to 120 d, possibly manifesting nitrogen reallocation to bud formation. The decline in N contents led to similar decreases in leaf photosynthetic capacity and foliar chlorophyll contents. These data demonstrate that light-dependent variation in the rate of developmental changes in M A determines canopy differences in photosynthetic capacity, whereas foliar photosynthetic apparatus is essentially constant in fully developed leaves.

Global leaf trait estimates biased due to plasticity in the shade

“…Q int was averaged for the 50 days after the start of leaf development, or for the actual number of days since the start of leaf development for leaves younger than 50 days or for leaves with an average life span of less than 50 days. This approach is motivated by reports that foliage trait acclimation to integrated light stabilizes about 30-60 days after leaf formation in both woody and herbaceous canopies 21,22 .…”

“…Leaf trait acclimation to integrated light has been reported to stabilize about 30-60 days after leaf formation in both woody and herbaceous canopies 21,22 , but age-dependent modifications are possible for some plant growth forms 23 and such modifications can further alter the correlative relationships within the leaf economics spectrum 24 . In particular, in evergreen woody species, M a and N a plasticity has been reported to decrease with increasing leaf age, with limited changes in A a plasticity 23 .…”

Estimations of isoprenoid emission capacity from enclosure studies: measurements, data processing, quality and standardized measurement protocols

“…This is needed as mono-and sesquiterpenes can be non-specifically stored within the leaves and leaf surface after synthesis (Niinemets et al, 2010c;Niinemets and Reichstein, 2002). This means that even if the system and plant responses can be deconvoluted, sufficient time is needed for plant emission rates to reach a steady-state for accurate estimation of the emission rate.…”

“…The simulation was performed with a ray tracing model for circular flat leaves having a spherical leaf angle distribution and random dispersion (Cescatti and Niinemets, 2004 for details). The gradients of light are expected to be even stronger for aggregated foliage dispersions as is common in most conifers (Cescatti and Zorer, 2003;Niinemets et al, 2006).…”

“…through secondary organic aerosol formation (Cahill et al, 2006;Chen and Hopke, 2009;Hallquist et al, 2009;Helmig et al, 2006;Kleindienst et al, 2007;Spracklen et al, 2008;Zhang et al, 2007) and cloud formation (Huff Hartz et al, 2005;Spracklen et al, 2008). The vegetation source-strength for volatile isoprenoids is typically estimated using models based on species-or vegetation-specific emission capacity for different volatile isoprenoid classes under standardized environmental conditions (E S , the emission factor) and environmental correction functions initially developed for light and temperature (so-called Guenther et al algorithms, Guenther et al, 1991, and more recently for CO 2 concentration (Niinemets et al, 2010c;Wilkinson et al, 2009). …”