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Updated: Jan 26, 2026

Evaluation of the Spatial Distribution of γH2AX following Ionizing Radiation
Published on: August 7, 2010
The Spatial Distribution of Chlorophyll in Leaves
Aleca M Borsuk1, Craig R Brodersen2
1School of Forestry & Environmental Studies, Yale University, New Haven, Connecticut 06511.
Abstract:
Measuring and modeling the spatial distribution of chlorophyll within the leaf is critical for understanding the relationship between leaf structure and carbon assimilation, for defining the relative investments in leaf tissues from the perspective of leaf economics theory, and for the emerging application of in silico carbon assimilation models. Yet, spatially resolved leaf chlorophyll distribution data are limited. Here, we used epi-illumination fluorescence microscopy to estimate relative chlorophyll concentration as a function of mesophyll depth for 57 plant taxa. Despite interspecific variation due to differences in leaf thickness, mesophyll palisade fraction, and presence of large intercellular airspaces, the spatial distribution of chlorophyll in laminar leaves was remarkably well conserved across diverse lineages (ferns, cycads, conifers, ginkgo, basal angiosperms, magnoliids, monocots, and eudicots) and growth habits (tree, shrub, herbaceous, annual, perennial, evergreen, and deciduous). In the typical leaf, chlorophyll content increased gradually as a function of depth, peaking deep within the mesophyll. This chlorophyll distribution pattern is likely coupled to adaxial and abaxial intraleaf light gradients, including the relative enrichment of green light in the lower leaf. Chlorophyll distribution for the typical leaf from our dataset was well represented by a simple mathematical model (R2 = 0.94). We present chlorophyll distribution data and model equations for many ecologically and commercially relevant species and plant functional types (defined according to chlorophyll profile similarity, clade, and leaf thickness). These findings represent an advancement toward more accurate photosynthesis modeling and increase our understanding of first principles in intraleaf physiology.
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