short title: spatial distribution of chlorophyll ... · 42 profile similarity, clade, and leaf...

1

Short title: 1

Spatial distribution of chlorophyll 2

Corresponding Author: 3

Craig Brodersen 4

Article title: 5

The spatial distribution of chlorophyll in leaves 6

7

Authors: 8

Aleca M. Borsuk and Craig R. Brodersen 9

School of Forestry & Environmental Studies, Yale University, New Haven, CT, 06511, USA 10

One-sentence summary: 11

Relative chlorophyll concentration as a function of leaf depth is a remarkably conserved trait 12

across a wide diversity of plant taxa and can be described by a simple mathematical model. 13

Author contributions: 14

C.B. conceived the original research plans and complemented the experiments, data 15

interpretation, and writing; A.B. performed most of the experiments, analyzed the data, and 16

wrote the manuscript with the contribution of C.B.; C.B. agrees to serve as the author 17

responsible for contact. 18

Funding information: 19

This material is based upon work supported by the National Science Foundation Graduate 20

Research Fellowship Program under Grant No. DGE1752134. Any opinions, findings, and 21

conclusions or recommendations expressed in this material are those of the author(s) and do 22

not necessarily reflect the views of the National Science Foundation. 23

ABSTRACT 24

Measuring and modeling the spatial distribution of chlorophyll within the leaf is critical for 25

understanding the relationship between leaf structure and carbon assimilation, for defining the 26

Plant Physiology Preview. Published on April 3, 2019, as DOI:10.1104/pp.19.00094

Copyright 2019 by the American Society of Plant Biologists

www.plantphysiol.orgon June 20, 2020 - Published by Downloaded from Copyright © 2019 American Society of Plant Biologists. All rights reserved.

http://www.plantphysiol.org

2

relative investments in leaf tissues from the perspective of leaf economics theory, and for the 27

emerging application of in silico carbon assimilation models. Yet, spatially-resolved leaf 28

chlorophyll distribution data are limited. Here, we used epi-illumination fluorescence microscopy 29

to estimate relative chlorophyll concentration as a function of mesophyll depth for 57 plant taxa. 30

Despite interspecific variation due to differences in leaf thickness, mesophyll palisade fraction, 31

and presence of large intercellular airspaces, the spatial distribution of chlorophyll in laminar 32

leaves was remarkably well conserved across diverse lineages (ferns, cycads, conifers, ginkgo, 33

basal angiosperms, magnoliids, monocots, and eudicots) and growth habits (tree, shrub, 34

herbaceous, annual, perennial, evergreen, and deciduous). In the typical leaf, chlorophyll 35

content increased gradually as a function of depth, peaking deep within the mesophyll. This 36

chlorophyll distribution pattern is likely coupled to adaxial and abaxial intra-leaf light gradients, 37

including the relative enrichment of green light in the lower leaf. Chlorophyll distribution for the 38

typical leaf from our dataset was well represented by a simple mathematical model (R2 = 0.94). 39

We present chlorophyll distribution data and model equations for many ecologically and 40

commercially relevant species and plant functional types (defined according to chlorophyll 41

profile similarity, clade, and leaf thickness). These findings represent an advancement toward 42

more accurate photosynthesis modeling and increase our understanding of first principles in 43

intra-leaf physiology. 44

INTRODUCTION 45

The biochemistry of photosynthesis and biophysical processes that constrain it are intrinsically 46

linked within the landscape of the inner leaf. Because leaf tissue is heterogeneous in structure 47

as well as photosynthetic capacity (Smith et al., 1997; Adams and Terashima, 2018; Earles et 48

al., 2018a), it follows that chlorophyll may also be spatially heterogeneous. Yet, while bulk 49

chlorophyll content of leaves can be readily measured (Porra et al., 1989; Palta, 1990), fewer 50

studies have systematically dissected the leaf to determine how chlorophyll content is 51



3partitioned across the photosynthetic domain, or mesophyll (Vogelmann and Evans, 2002; 52



4

Johnson et al., 2005; Evans and Vogelmann, 2006; Brodersen and Vogelmann, 2010; Slattery 53

et al., 2016). The paucity of spatially resolved chlorophyll distribution data available at present is 54

likely due to the historically labor- and time-intensive processes of obtaining such data, requiring 55

extraction of chlorophyll from thin paradermal sections (Bornman et al., 1991; Cui et al., 1991; 56

Nishio et al., 1993) or counting chloroplasts with a light microscope (e.g. Aalto and Juurola, 57

2002). However, epi-illumination chlorophyll fluorescence offers a simple and rapid method of 58

measuring relative chlorophyll distribution within cell layers of a leaf (Vogelmann and Evans, 59

2002). In this method, a fresh leaf is cut transversely, placed under a microscope (Fig. 1A), and 60

irradiated with an excitation wavelength orthogonal to the cut surface. Autofluorescence emitted 61

from chlorophyll is captured with a charge-coupled device (CCD) camera with a bandpass filter 62

to collect only light generated from fluorescence. Pixel intensity in the grayscale images derived 63

from this method is proportional to relative chlorophyll content according to a 1:1 relationship, as 64

reported in detail by Vogelmann and Evans (2002). Relative chlorophyll content can then be 65

measured directly from images using image analysis software (Fig. 1B) to obtain chlorophyll 66

distribution (Fig. 1C). To the best of our knowledge, the epi-illumination fluorescence technique 67

has only been used to measure leaf chlorophyll distribution for seven species—spinach 68

(Spinacia oleracea) (Vogelmann and Evans, 2002), Rhododendron catawbiense, Abies fraseri, 69

and Picea rubens (Johnson et al., 2005), Eucalyptus pauciflora (Evans and Vogelmann, 2006) 70

and snapdragon (Antirrhinum majus) and sunflower (Helianthus annuus) (Brodersen and 71

Vogelmann, 2010). Using light sheet microscopy, a modified form of this method, Slattery et al. 72

(2016) were able to make similar measurements in a soybean (Glycine max) cultivar and 73

mutant. These studies reported that chlorophyll content in laminar leaves is non-uniform, with 74

the lowest concentration in the palisade mesophyll near the adaxial surface and higher 75

concentrations in the medial and abaxial domains. Johnson et al. (2005) introduced the model 76

equation 77



5

y = y0 + ax + bx2 (1) 78

to express chlorophyll distribution (y) as a function of leaf depth (x) in vertical profiles of R. 79

catawbiense and A. fraseri (both laminar or relatively flattened) leaves. Yet, because of the lack 80

of chlorophyll distribution data in the literature and the wide variability in leaf form, it is unclear 81

whether this characterization represents the rule or the exception. 82

In theory, as a light-harvesting molecule, chlorophyll should be well coordinated spatially with 83

intra-leaf light availability. Yet, Nishio et al. (1993) showed that carbon fixation gradients in S. 84

oleracea leaves do not follow leaf internal light gradients, which decrease exponentially through 85

the leaf. Instead, carbon fixation was higher in the middle of the leaf, with spongy mesophyll 86

contributing significantly (40%) to total carbon reduction. This is largely counter-intuitive 87

assuming that carbon fixation should be highest at the upper leaf surface where there is the 88

most light available. Yet, observed increases in chlorophyll within the middle of leaves has 89

been observed in multiple species (using paradermal sectioning; Cui et al. 1991; Bornman et al. 90

1991), with the suggestion that this would balance the decline in the amount of available light 91

from the adaxial and/or abaxial surfaces. Here, we note that light gradients, and therefore 92

chlorophyll distribution, could be altered by palisade mesophyll, which may propagate light 93

deeper into the leaf (Johnson et al., 2005; Smith et al., 1997). Studies have also demonstrated 94

the importance of different rates of light extinction through the leaf between strongly absorbed 95

(e.g. blue, red) and weakly absorbed (e.g. green) wavelengths. Cui et al. (1991) found that while 96

strongly absorbed wavelengths such as blue and red are 90% attenuated in the upper 20% of 97

leaves, medial and deep leaf tissues remain relatively enriched in green light. Interestingly, Sun 98

et al. (1998) reported that green light drove more CO2 fixation than red or blue light in deep leaf 99

tissues of S. oleracea. Evans and Vogelmann (2003) also reported that photosynthetic capacity 100

matched the profile of green but not white light absorption in S. oleracea leaves. Taken 101

together, studies such as these have contributed to the growing understanding of the role of 102



6

green light in driving photosynthesis deep within leaf tissues (Terashima et al., 2009; Smith et 103

al., 2017). These reports are also consistent with the concept of the intra-leaf environment as an 104

analog to a canopy, with vertical gradients in light quantity and quality. Terashima et al. (2009) 105

noted, for example, that chloroplasts acclimate to the local light environment, resulting in a 106

gradient of sun and shade characteristics. Terashima et al. (2009) also reported that 107

chloroplasts in the lowermost part of S. oleracea leaves exhibit 20-40% of the maximal 108

photosynthetic capacity of the chloroplasts closest to the adaxial surface. These data were used 109

by Tholen et al. (2012) to model the fraction of chlorophyll in palisade vs. spongy mesophyll and 110

the photosynthetic rate that could be sustained by green light. Assuming that S. oleracea 111

chloroplasts in the lowermost part of the leaf exhibit 20% of the maximal photosynthetic capacity 112

of those in the uppermost part, photosynthetic capacity was maximized by a roughly equal 113

(~50%) distribution of chlorophyll between palisade and spongy mesophyll tissues. 114

Based on these precedents, in a laminar leaf receiving irradiation primarily from the adaxial 115

surface, we anticipate that relative chlorophyll content would increase towards the abaxial 116

domain as a response to the decline in available light and/or the relative enrichment of weakly 117

absorbed green light and would be well characterized by the model equation y = y0 + ax + bx2 118

proposed by Johnson et al. (2005). Yet, carbon assimilation requires more than light, namely 119

CO2 and water. Interestingly, leaf veins represent a nexus of distribution of these resources. 120

Specifically, leaf vein-to-vein and vein-to-evaporative surface spacing is highly conserved 121

(Noblin et al., 2008; Zwieniecki and Boyce, 2014), especially in derived taxa. Thus, we also 122

anticipated that chlorophyll content might peak at a depth coincident with leaf veins. 123

The aim of the present study was to describe the spatial distribution of chlorophyll as a function 124

of leaf depth in bulk mesophyll domains of laminar leaves across broad levels of phylogenetic 125

diversity. These observations were intended to expand the number of species for which 126

empirical chlorophyll distribution data are available, articulate any common scheme(s) in 127



7

chlorophyll distribution within bulk mesophyll domains, and initiate an understanding of 128

associations between chlorophyll distribution, light environment, leaf anatomy, and the 129

optimization of photosynthesis relative to the multiple competing biophysical demands placed on 130

a leaf. 131

Towards this, we used epi-illumination fluorescence microscopy to measure chlorophyll 132

distributions within vertical (transverse) leaf profiles of 57 species from eight major terrestrial 133

plant clades (ferns, cycads, conifers, ginkgo, basal angiosperms, magnoliids, monocots, and 134

eudicots), representing a diversity of growth habit, habitat, and leaf form (e.g. tree, shrub, 135

herbaceous, annual, perennial, evergreen, and deciduous plant species; Table S1). Seven 136

congeneric pairs (Acer, Arenga, Begonia, Dioon, Encephalartos, Quercus, and Zamia) were 137

included in this dataset to explore variability within a genus in basal and derived groups. 138

Hierarchical cluster analysis and mean model approaches were used to articulate patterns in 139

chlorophyll distribution. We also characterized leaf thickness, vein depth, and palisade fraction 140

of mesophyll to examine possible relationships between patterns in chlorophyll content and 141

major anatomical traits (Table S1). In a subset of species, we measured monochromatic light 142

absorption profiles following the methods of Brodersen and Vogelmann (2010) to characterize 143

the relationship between intra-leaf light environment and chlorophyll distribution. 144

The results of this work could be used for research focused on the relative investments in leaf 145

tissues from the perspective of leaf economics theory (Shipley et al., 2006; Reich, 2014) or the 146

relationship between leaf structure and carbon assimilation (Terashima et al., 2011; Earles et 147

al., 2018a). This information is also relevant to the emerging application of in silico carbon 148

assimilation models for testing first principles in plant physiology and towards engineering 149

increased performance and resiliency in agricultural crops (Tholen et al., 2012; Ort et al., 2015). 150

While such models may incorporate fine-scale phenomena such as intra-leaf CO2 diffusion 151

(Pieruschka et al., 2006; Morison et al., 2007; Terashima et al., 2011; Tholen et al., 2014; Ho et 152



8

al., 2016; Earles et al., 2018b), hydraulics (Noblin et al., 2008; Zwieniecki and Boyce, 2014), 153

and light propagation (Smith et al., 1997; Sun et al., 1998; Vogelmann and Gorton, 2014; Ichiro 154

et al., 2016; Smith et al., 2017), similarly resolved chlorophyll distribution data are not yet widely 155

available or well understood. This is evident from the multiple approaches used for 156

parameterizing chlorophyll distribution in leaf carbon assimilation models, including as a 157

homogeneous biochemical domain (Oguchi et al., 2011; Tholen and Zhu, 2011; Earles et al., 158

2017). 159

160



9

RESULTS 161

Chlorophyll profiles of individual species 162

To visually assess the chlorophyll distribution, or chlorophyll profiles, of individual species, mean 163

chlorophyll content was plotted as a function of mesophyll depth (n = 3 profiles were collected 164

for each leaf and n = 2-6 leaves were collected for each species; Fig. S1). The profile expressed 165

by Quercus alba is representative of many of the species in this study, where chlorophyll 166

content was relatively uniform or increased slightly towards the abaxial surface (Fig. 2A-C). In 167

some species, such as the fern Platycerium bifurcatum (Fig. 2D-F), chlorophyll content was 168

clearly partitioned into two domains, concentrating chlorophyll in either palisade and/or spongy 169

mesophyll just below the epidermis (Fig. 2E). Yet, for most species, it was unclear whether 170

mesophyll tissue type was coordinated with changes in relative chlorophyll content (e.g. Dioon 171

merolae, Amorphophallus titanum, Arenga engleri; Fig. S1) or whether chlorophyll content was 172

relatively uniform across the leaf, i.e. did not change despite differentiation of mesophyll (e.g. Q. 173

alba, Fig. 2A-C; Acer saccharum, Drimys winteri, Robinia pseudoacacia, Fig. S1). The presence 174

of large intercellular airspaces depressed local chlorophyll content in some leaves, such as with 175

the aquatic plant Eichhornia crassipes (Fig. 2G-I), and the spatial heterogeneity of these 176

intercellular airspaces led to increased variability compared to areas of the leaf with lower 177

porosity (Fig. 2H). Where congeneric pairs were measured, the chlorophyll profiles were 178

remarkably similar, particularly in the cases of Acer and Quercus from the derived eudicot clade 179

(Fig. S1). 180

Major patterns in chlorophyll distribution 181

A hierarchical cluster analysis was used to identify common patterns in the chlorophyll profiles 182

without imposing a priori classification. This indicated the presence of six clusters, or groups of 183

species with similar chlorophyll profiles (a-f; Fig. 3A). To aid in comparing the major patterns, 184



10

the mean chlorophyll profiles of each group was analyzed according to the model equation (Eq. 185

1) using quadratic regression (Fig. 3B). Numerical coefficients for the regression curves are 186

found in Table 1. As discussed in detail in the Materials and Methods section, the first and last 187

relative depth values (relative depth = 0, 100), or where mesophyll was bordered by epidermal 188



11

layers, are not part of the photosynthetic domain and are excluded from all regressions. Group 189

(a) contained a single species, the bromeliad Billbergia minarum. This species had an atypical 190

leaf form in our dataset due to a multiple-layer hypodermis (which was not included in 191

measurements but may have influenced chlorophyll distribution indirectly). B. minarum had 192



12

markedly lower chlorophyll content in the adaxial chlorenchyma (n = 1, R2 = 0.98, F(2,16) = 193

426.5, p < 0.000). Group (b) was dominated by gymnosperms (predominantly cycads; mean = 194

0.482 mm, s.e. = 0.051). Species in group (b) exhibited a gradual increase in chlorophyll from 195

the adaxial side and maxima shifted heavily to the abaxial domain (n = 11, R2 = 0.96, F(2,16) = 196

172, p < 0.000). Group (c) was the largest group. This group was phylogenetically diverse, 197

containing fern, cycad, magnoliid, monocot, and eudicot taxa, and was typified by a uniform 198

distribution (n = 22, R2 = 0.86, F(2,16) = 48.9, p < 0.000). Group (d) was also phylogenetically 199

diverse, with a typical profile similar to groups (b) and (c), but with a gradual tapering of 200

chlorophyll content at both adaxial and abaxial edges (n = 15, R2 = 0.98, F(2,16) = 363.9, p < 201

0.000). The outlier Eichhornia crassipes comprised group (e). This was separated from the 202

other groups because of a local depression in the center of the mesophyll reflective of large 203

intercellular airspaces. The model equation was not applied to this profile because of its 204

divergence from the typical parabolic shape. Group (f) was unique in that it contained profiles 205

with chlorophyll maxima in the adaxial domain (n = 7, R2 = 0.93, F(2,16) = 100.7, p < 0.000), 206

also from diverse lineages (i.e. fern, eudicot, monocot, magnoliid). 207

One-way ANOVA were conducted to determine if groups of species with similar chlorophyll 208

profiles (groups derived from the cluster analysis) differed in anatomical traits anticipated to 209

influence chlorophyll distribution (i.e. leaf thickness, palisade fraction of mesophyll, and vein 210

depth). Groups (a) and (e) with only one species were excluded from the analyses. Boxplots 211

illustrating the differences in traits by group are shown in Fig. 4. There was a statistically 212

significant difference in leaf thickness between groups (R2 = 0.25, F(3,54) = 5.65, p = 0.002) as 213

determined by one-way ANOVA. A Tukey post hoc test revealed that leaves from the 214

taxonomically diverse groups (c) (mean leaf thickness = 0.2449 ± 0.1386 mm, p = 0.002) and 215

(d) (mean leaf thickness = 0.2788 ± 0.1002 mm, p = 0.020) were significantly thinner compared 216

to leaves from group (b), which was dominated by gymnosperms (mean leaf thickness = 0.4835 217



13

± 0.1780 mm). One-way ANOVA analysis indicated a statistically significant difference in the 218

palisade fraction of mesophyll between groups (R2 = 0.23, F(3,47) = 4.38, p = 0.009); a Tukey 219



14

post hoc test showed that this difference was only significant (p = 0.004) between groups (b) 220

(mean palisade fraction of mesophyll = 27.56% ± 12.07) and (c) (mean palisade fraction of 221

mesophyll = 46.81% ± 17.68). There were no statistically significant differences in vein depth 222

between groups. 223

A general model for chlorophyll distribution in laminar leaves 224

Quadratic regression was applied to the mean chlorophyll profile of the 57 species in our study, 225

resulting in the following general model of relative chlorophyll distribution for the mean or typical 226

leaf: 227

y = 67.52 + 0.4149x - 0.0029x2 (2) 228

(R2 = 0.94, F(2,16) = 127.3, p < 0.001; Fig. 5). Thus, for the typical leaf from our dataset, 229

chlorophyll increased gradually as a function of leaf depth, with minor depressions in chlorophyll 230

content at the outermost edges of the mesophyll. The highest chlorophyll concentration 231

occurred at 83% (s.e. = 1.0) relative mesophyll depth, which is highly shifted towards the 232

abaxial surface, and deeper than the mean vein position (~60% relative mesophyll depth) and 233

mean transition point between the palisade and spongy tissue layers (~38% relative mesophyll 234

depth). This extends the work of Johnson et al. (2005) who first introduced a model equation 235

(Eq. 1) to describe chlorophyll distribution in leaves of two species, R. catawbiense and A. 236

fraseri. 237

Chlorophyll distribution models by clade 238

Quadratic regression was applied to the mean chlorophyll profile of categorical sets of plants 239

based on clade (fern, cycad, conifer, ginkgo, basal angiosperm, magnoliid, monocot, eudicot; 240

Fig. 6A-H). While mesophyll depth was not a significant predictor of chlorophyll distribution for 241

the clade-wise group of ferns (n = 3, R2 = 0.17, F(2,16) = 1.687, p = 0.216), it was a significant 242

predictor and explained a high degree of variance in chlorophyll distribution for the sampled 243



15

groups of cycads (n = 9, R2 = 0.84, F(2,16) = 42.57, p < 0.001), conifers (n = 2, R2 = 0.96, 244

F(2,16) = 211.7, p < 0.001), ginkgo (Ginkgo biloba) (n = 1 species [mean of n = 6 leaves and n 245

= 3 profiles per leaf], R2 = 0.85, F(2,16) = 46.51, p < 0.001), basal angiosperm (n = 1 species 246

[mean of n = 6 leaves and n = 3 profiles per leaf], R2 = 0.96, F(2,16) = 170.2, p < 0.001), 247

magnoliids (n = 6, R2 = 0.92, F(2,16) = 95.72, p < 0.001), monocots (n = 9, R2 = 0.69, F(2,16) 248

=17.47, p < 0.001), and eudicots (n = 26, R2 = 0.94, F(2,16) = 122, p < 0.001). Numerical 249

coefficients for the regression curves are shown in Table 1. 250



16

Chlorophyll distribution models by leaf thickness 251

Quadratic regression was applied to the mean chlorophyll profile of categorical sets of plants 252

based on leaf thickness (Fig. 6I,J). Mesophyll depth was a significant predictor of chlorophyll 253

distribution for species with both categorically thin leaves (<0.5 mm; n = 47, R2 = 0.92, F(2,16) = 254



17

88.46, p < 0.001) and species with categorically thick leaves (≥0.5mm; n = 10, R2 = 0.91, 255

F(2,16) = 85.83, p < 0.001). Numerical coefficients for the regression curves are shown in Table 256

1. 257

General model predictions vs. clade/leaf thickness model predictions 258

Chlorophyll content predictions made by the clade and leaf thickness model equations, which 259

are significant for all but the fern model, correlated strongly with chlorophyll content predictions 260

made by the general model, or Equation 2. The general and subgroup model predictions were 261

most highly correlated for the cycad, magnoliid, monocot, eudicot, thin leaf, and thick leaf 262

subgroups (r = 0.99, p < 0.001), but also strongly correlated for the conifer group (r = 0.97, p < 263

0.001), ginkgo (r = 0.67, p = 0.0018), and basal angiosperm (r = 0.87, p < 0.001). 264

Mesophyll tissue type and vein depth as predictors of chlorophyll content maxima 265

Given that the typical parabolic chlorophyll profile has a distinguishable peak or global 266

maximum, it was anticipated that this peak in chlorophyll content would be associated with 267

anatomical features of the leaf, i.e. at a predictable location relative to the transition from light-268

guiding palisade to light-diffusing spongy mesophyll or at a depth coincident with leaf veins. 269

Indeed, by observation, some chlorophyll profiles did peak at a similar depth as the veins (e.g. 270

G. biloba; Fig. S1). Yet, when linear regression was used to statistically assess the strength of 271

these anatomy–chlorophyll relationships; the spatial associations between anatomical traits and 272

peak chlorophyll content were very weak, and neither mesophyll tissue type transitions (r = - 273

0.05, n = 49, p = 0.710; Fig. 7A) nor vein depth (r = 0.08, n = 54, p = 0.956; Fig. 7B) were 274

significant predictors of peak chlorophyll according to Pearson’s test. 275

Intra-leaf light absorption and chlorophyll distribution 276

Light absorption profiles and chlorophyll profiles of species from different clades (n = 5 species, 277

Arenga pinnata, Ulmus sp., Dryopteris sp., Coffea sp., and Bowenia spectabilis) were used to 278



18

examine the relationship between the intra-leaf light environment and chlorophyll distribution. 279

Monochromatic (blue, red, and green) light extinction profiles decayed exponentially through the 280

leaf as seen in previous studies (e.g. Vogelmann and Evans, 2002; Johnson et al., 2005; 281

Brodersen and Vogelmann, 2010). As anticipated from previous work by Vogelmann and Han 282

(2000), red and blue light were absorbed strongly near the source of irradiation while deeper 283

portions of the mesophyll remained enriched in green light (Fig. 8). In an analysis of light 284

absorption profiles generated from light entering opposite sides of the leaf, we found that the 285

overlap of these profiles for red, green, and blue light occurred within a relatively narrow region 286

of the mesophyll, approximately between the mean vein position and the position of the 287

transition between the palisade and spongy mesophyll. Chlorophyll content reached a maximum 288

around this narrow band of tissue (Fig. 8). 289

290



19

DISCUSSION 291

Leaf thickness, palisade fraction of mesophyll, and intercellular airspaces may influence 292

chlorophyll distribution 293

Although many of the leaves sampled showed chlorophyll distributions that were parabolic, with 294

abaxially-shifted maxima, variations on and deviations from this trend were observed, indicating 295

which anatomical traits may alter or influence chlorophyll allocation. Unsurprisingly, we found 296

pronounced localized depressions in chlorophyll content in areas of leaves with high porosity, or 297

large intercellular airspaces, such as in the medial tissue of the aquatic plant E. crassipes (Fig. 298

2G-I). Considering the results of the cluster analysis (Fig. 3B), chlorophyll content in group (b) 299

increased sharply across the photosynthetic domain, with a clear minimum in the upper leaf and 300



20

maximum in the lower leaf. This group was dominated by gymnosperms and had statistically 301

thicker leaves than plants in groups (c) and (d), and less palisade tissue than those in group (c). 302

In contrast, group (c) had members with the thinnest leaves, was dominated by more derived 303

taxa, and had the most uniform or flat chlorophyll distribution across the photosynthetic domain. 304

Taken together, this suggests that a thicker leaf with less developed palisade tissue (e.g. cycad) 305

allocates less chlorophyll near the adaxial leaf surface, while a thinner leaf with more developed 306

palisade tissue (e.g. eudicot) allocates chlorophyll more uniformly throughout the chlorenchyma. 307

Assuming that chlorophyll content increases to balance decreases in available light (Cui et al. 308

1991 and Bornman et al. 1991), then the observed chlorophyll distributions would occur 309

because thinner leaves, particularly with highly developed light-guiding palisade tissue, would 310

experience more of a homogenous internal light environment compared to a thick leaf, which 311

would rapidly attenuate light with increasing depth (Takahashi et al., 1994; Koizumi et al., 1998; 312

Vogelmann and Han, 2000; Johnson et al., 2005; Brodersen and Vogelmann, 2010). Intra-leaf 313

gradients in CO2 may also influence the allocation of chlorophyll in bulk mesophyll domains. 314

Assuming most laminar leaves have a higher relative abundance of CO2 near stomata on the 315

underside of the leaf, thick leaves might have a more pronounced CO2 diffusion gradient and 316

therefore less CO2 available for photosynthesis in the upper mesophyll. We also note that the 317

localized depressions in chlorophyll content at both adaxial and abaxial mesophyll edges 318

observed in most leaves could be due to limited mesophyll conductance in these areas (Earles 319

et al. 2018b). That is, if a large proportion of the mesophyll cell wall has contact with an 320

epidermal cell, then the diffusion of CO2 would be limited and chloroplasts within this region 321

would underperform. While beyond the scope of the present work, future studies are anticipated 322

to show the degree to which variations in mesophyll porosity and/or connectivity influence CO2 323

availability, chlorophyll distribution, and chloroplast performance. 324



21

Common patterns in chlorophyll distribution indicate that a general chlorophyll profile 325

scheme is conserved across phylogenetic boundaries 326

When hierarchical cluster analysis was used to identify common patterns in the chlorophyll 327

profiles without imposing a priori classification (Fig. 3), most species (n = 48/57) were sorted 328

into groups (b), (c), and (d), for which the mean chlorophyll profile converged to a similar 329

pattern; i.e. chlorophyll content increased gradually as a function of mesophyll depth. Thus, this 330

general pattern of chlorophyll distribution is exhibited by plants as phylogenetically diverse as 331

ferns, cycads, conifers, G. biloba, Illicium parviflorum (basal angiosperm), magnoliids, 332

monocots, and eudicots, representing a diversity of growth habits, habitats, and leaf 333

morphologies (e.g. tree, shrub, herbaceous, annual, perennial, evergreen, deciduous, etc.). 334

Considering all species sampled in the study (n = 57), for the typical species, chlorophyll 335

content increased gradually as a function of mesophyll depth from the adaxial surface, peaking 336

deep within the leaf (~83% relative mesophyll depth). This is quantitatively described by a 337

simple quadratic equation, or general model (Eq. 2, R2 = 0.94, F(2,16) = 127.3, p < 0.001; Fig. 338

5). 339

Chlorophyll content maxima are well positioned to take advantage of relative enrichment 340

of green light in medial and abaxial leaf tissues and abaxially incident irradiation 341

Our comparison of intra-leaf light absorption profiles and chlorophyll profiles (Fig. 8) also 342

suggests that peak chlorophyll content may respond not only to irradiation incident on the upper 343

leaf, but also to opposing light gradients from both upper and lower leaf surfaces. We found that 344

the red, green, and blue light absorption profiles overlapped within a relatively narrow region of 345

mesophyll that also coincided with the positioning of the palisade to spongy transition, the 346

location of the veins, and maximum chlorophyll content. This region is also relatively enriched in 347

green light compared with blue and red wavelengths, which is consistent with the growing 348

understanding of the role of green light in driving photosynthesis within deep leaf tissue 349



22

(Terashima et al., 2009; Johkan et al., 2012; Earles et al., 2017; Smith et al., 2017). While 350

further studies are needed, this could point to the optimization of peak chlorophyll content where 351

absorption of strong light from the adaxial surface and weaker light from the abaxial surface is 352

maximized. 353

Vein depth and mesophyll tissue type are not predictive of chlorophyll content maxima 354

We expected to find some coordination between the peak chlorophyll content within the leaf and 355

other anatomical trait patterns that are believed to be important for optimizing photosynthesis. 356

For example, the density and spacing of veins within the leaf has been shown to have a 357

remarkable scaling relationship across evolutionarily diverse species (Noblin et al. 2008), 358

presumably to most efficiently deliver water to the sites of photosynthesis and evaporation from 359

the mesophyll surface exposed to the intercellular airspace (Boyce et al. 2009). However, no 360

statistical evidence for the coordinated positioning of maximum chlorophyll content with vein 361

position was found (Fig. 7). Vein depth was also not statistically different between groups of 362

species with distinctive chlorophyll profiles as identified through cluster analysis, suggesting that 363

vein location is not a driver of major patterns in chlorophyll distribution, at least in the 1D vertical 364

profiles of bulk mesophyll measured in this study. Future studies are anticipated to show if there 365

are additional patterns in chlorophyll distribution in 2- and 3-dimensions in the leaf, including 366

around the vascular tissue in transverse and paradermal planes. 367

The general model (Eq. 2) predicts bulk mesophyll chlorophyll distribution in a broad 368

range of plant lineages and for leaves with different thicknesses 369

While we report that several variations in leaf form do affect chlorophyll distribution, we also 370

suggest that the general model (Eq. 2) is appropriate for describing chlorophyll distribution in 371

most cases; this is because chlorophyll distribution predictions based strictly on categorical 372

groupings of leaves (i.e. by clade and leaf thickness; Fig. 6) were highly correlated with those 373



23

given by the general model (r = 0.99, p < 0.001 for cycad, magnoliid, monocot, eudicot, thin leaf, 374

and thick leaf groups). 375

CONCLUSIONS 376

While further studies are warranted to determine the mechanistic underpinnings of the 377

chlorophyll profile schemes characterized in this study, the main trend shared by the majority of 378

species—as well as the deviations from this trend in thick leaves—suggests that fundamental 379

physical constraints, such as intra-leaf gradients in light, are central to chlorophyll distribution in 380

laminar leaves. It is worth noting that the leaves in this study were all relatively thin (< 1 mm) 381

and most exhibited C3 photosynthesis. Variation in chlorophyll distribution could occur outside 382

these phenotypic parameters; for example, the C4 grass Zea mays (Fig. S1) shows a 383

depression in chlorophyll content near the midpoint of the depth profile, potentially due to the 384

highly modified Kranz anatomy of the bundle sheath that occupies a significant portion of the 385

leaf cross-sectional area. For our datasets where mesophyll depth failed to predict chlorophyll 386

distribution (e.g. clade-wise for ferns), this could in future studies be re-tested by increasing the 387

sample size or taxonomic representatives. Expanding the epi-illumination chlorophyll 388

fluorescence dataset, particularly within a genus or species, and in 2- and 3-dimensions, is an 389

opportunity for further research. For example, the observed similarity between chlorophyll 390

profiles of congeneric pairs points to the possibility of nuanced modification of chlorophyll 391

distribution according to shared traits. The response of these traits and of the spatial allocation 392

of chlorophyll within the leaf to different environmental conditions awaits testing. 393

In summary, this study provides empirical chlorophyll distribution data and model equations for 394

many ecologically and commercially relevant species, quantitatively defines a common 395

chlorophyll distribution scheme across phylogenetic and functional group boundaries, and 396

initiates an understanding of the mechanisms underlying chlorophyll distribution in bulk 397

mesophyll domains. Taken together, these findings advance our understanding of first-principles 398



24

in intra-leaf physiology and move us towards more accurate in silico photosynthesis modeling 399

and a clearer relationship between chlorophyll distribution, the light environment within a leaf, 400

and photosynthetic performance. 401

MATERIALS AND METHODS 402

Plant material 403

Mature, fully expanded leaves were collected from various environments (Marsh Botanical 404

Garden, New Haven, CT; Yale Marsh Greenhouse, New Haven, CT; Montgomery Botanical 405

Center, Coral Gables, FL; University of Vermont Campus, Burlington, VT; University of Vermont 406

Greenhouse, Burlington, VT; private garden, Monterey, CA; naturalized habitat, New Haven, 407

CT; Table S1). Spinacia oleracea and Arabidopsis thaliana wildtype (wt) were grown in 408

commercial and controlled growth chamber environments, respectively. In outdoor 409

environments, leaves were collected from sun-exposed, south-facing sides of the plant canopy. 410

Highly contrasting leaf phenotypes (i.e. sun or shade) were avoided where distinctive. All 411

species had laminar or flattened leaf forms. Excised leaves were adapted to darkness for a 412

minimum of 20 min before being prepared for chlorophyll fluorescence measurements. This 413

period of dark adaptation was implemented as a control for possible chloroplast movement 414

within cells as a response to the external light environment (Trojan and Gabrys, 1996). 415

Anatomical measurements 416

Leaf thickness, upper epidermis thickness (including hypodermis where present), lower 417

epidermis thickness, mesophyll thickness, percentage of mesophyll cross-sectional area 418

occupied by palisade mesophyll, and vein depth (measured from the adaxial edge of leaf 419

mesophyll to the center of the vein) were measured from images of leaf cross-sections. All 420

measurements were replicated twice per leaf on 2-6 leaves for each species. In three cases 421

(Begonia erythrophylla, Dryopteris sp., Zamia fairchildiana), veins were excluded from or not 422



25

discernable in the chlorophyll fluorescence images. Mean and standard error were calculated 423

for all measurements. Species were categorized as having thick or thin leaves subjectively 424

based on the non-uniform distribution of sampled leaf thickness frequencies by 0.05 mm bins 425

(thin < 0.50 mm, thick ≥ 0.50 mm). 426

Measurement of relative chlorophyll distribution within leaves 427

Relative chlorophyll distribution within leaves was measured using epi-illumination fluorescence 428

microscopy similar to the method of Vogelmann and Evans (2002). Transverse hand sections 429

cut several cells thick were mounted on lightly wetted filter paper on top of a glass slide, such 430

that the sample did not dry out during imaging and while preventing the infiltration of intercellular 431

airspaces with mounting liquid (water). The sample was then placed on the stage of a 432

microscope (Olympus BX43, Olympus America Inc., Center Valley, PA, USA) and irradiated 433

with epi-illumination at 490 nm generated from a broad-spectrum LED light source (Lumen 300-434

LED, Prior Scientific Instruments Ltd, UK) after passing through a filter. Light emitted via 435

chlorophyll fluorescence passed through a barrier filter (680 nm, half band width = 16 nm, S10–436

680F; Corion Filters, Franklin, MA, USA) and was imaged with a digital Peltier-cooled CCD 437

camera (PIXIS 1024B, Princeton Instruments, Trenton, NJ, USA) using shutter times of 70-150 438

ms. Individual profiles were measured from the images by drawing lines from the adaxial edge 439

of the mesophyll to the abaxial edge of the mesophyll with a line width of 50-100 pixels over 440

which the mean intensity was given; in general 100-pixel width (equivalent to ~60 µm at 20x 441

magnification or ~120 µm at 10x magnification) was used; however, thinner widths were used 442

as necessary when non-photosynthetic features such as veins were spaced less than 100 pixels 443

apart. Measurements excluded epidermal cells, veins, and other conspicuous non-444

photosynthetic structures such as hypodermis. Chlorophyll and depth data for each profile were 445

normalized by dividing all values by the global absolute chlorophyll or depth maxima, 446

respectively. The mean of three profiles was measured for each leaf sample and the mean of 2-447



26

6 leaf samples was measured per species. Estimates of absolute fluorescence intensity among 448

different samples were not possible. This was due to variability in exposure needed to image 449

differently sized samples at appropriate focal lengths, and additionally the temporal variation in 450

signal due to Kautsky decay, i.e. the decline in fluorescence intensity as a function of exposure 451

time under continuous irradiation. As discussed in Vogelmann and Han (2008), Kautsky decay 452

changes the relative intensity of the fluorescence signal but does not alter the relative 453

distribution of fluorescence imaged from the sample. The entire epi-illumination process for a 454

single sample was completed within approximately 30 seconds. Differential detection of 455

chlorophyll a and b by the epi-illumination method was considered as a source of bias in the 456

shape of the measured chlorophyll profiles, yet is assumed to be minimal due to precedent by 457

Vogelmann and Evans (2002). These authors found a strong linear relationship for in vivo 458

paradermal chlorophyll concentration as a function of fluorescence detected by the epi-459

illumination method. Additionally, excitation and emission bands used here were well within 460

peaks for detection of both chlorophyll a and b. Finally, our protocol for normalizing the 461

fluorescence signal for each sample removes potential bias in chlorophyll a/b ratios across 462

species. 463

Cluster analysis of species chlorophyll profiles 464

Hierarchical cluster analysis was used to group species chlorophyll profiles according to similar 465

distribution schemes. Euclidean distances between chlorophyll intensity data points were 466

calculated at 21 loci (0%, 5%, 10%, …, 100% relative mesophyll depth) and clusters were 467

agglomerated using complete linkage. Analysis was performed using the R statistical program 468

(R Core Team, 2018). Visual assessment of clustering patterns indicated the presence of six 469

major groups. The small sub-cluster containing B. bowerae and A. majus could have been 470

treated as a seventh group; however, to avoid over-splitting, and consistent with observed 471

patterns in the species chlorophyll profiles, this was grouped with its neighboring major cluster. 472



27

To aid in comparison of major patterns in chlorophyll distribution between groups, a mean 473

model was generated from the individual chlorophyll profiles of species in each group. A 474

regression of the form y = y0 + ax + bx2 was applied to each group mean model and tested for 475

significance and fit (Johnson et al., 2005). Domains where the upper and lower epidermal cell 476

walls met the chlorenchyma cell walls (0%-5% and 95%-100% relative depth, respectively) were 477

excluded from the regression. These domains represent a non-photosynthetic transition point 478

between tissue types, which is retained in the data as a marker of the transition point in tissue 479

morphology. 480

General model of chlorophyll distribution 481

A mean model approach was used to develop a general equation for chlorophyll distribution in 482

laminar leaves. The mean model, or mean species chlorophyll profile, was calculated by 483

averaging relative chlorophyll intensity values at common relative depth values for all fifty-seven 484

species in the study. Mean standard error was calculated to evaluate the variation in chlorophyll 485

intensity among species as a function of mesophyll depth. A regression curve of the form y = y0 486

+ ax + bx2 was applied to the mean model and tested for fit (Johnson et al., 2005). Domains 487

where the upper and lower epidermal cell walls met the chlorenchyma cell walls (0%-5% and 488

95%-100% relative depth, respectively) were excluded from the regression. These domains 489

represent a non-photosynthetic transition point between tissue types, which is retained in the 490

data as a marker of the transition point in tissue morphology. 491

Measurement of light absorption profiles in leaves 492

Chlorophyll fluorescence was also used to estimate the relative absorption of red, green, and 493

blue light through leaf samples using previously reported methods (Takahashi et al., 1994; 494

Koizumi et al., 1998; Vogelmann and Evans, 2002; Vogelmann and Han, 2008; Brodersen and 495

Vogelmann, 2010). Fresh leaf sections were cut to ~1 cm2 with a razor blade and mounted in a 496



28

3D-printed sample holder on the stage of a microscope (Olympus BX43, Olympus America Inc., 497

Center Valley, PA, USA) with the transverse edge normal to the objective. The abaxial or 498

adaxial side of the leaves were irradiated with monochromatic red (660 nm), green (532 nm), or 499

blue (488 nm) light generated by one of three lasers (red solid state laser: Model #BWN-660–500

10E, BandW Tek Inc., Newark, DE, USA; green solid state laser: Model # DY20B, Power 501

Technology Inc., Little Rock, AR, USA; blue solid state laser: Model LRS-473-TM-10-5, 502

LaserGlow Technologies, Toronto, ON, Canada). The laser light was attenuated with neutral 503

density filters such that the light incident on the leaf surface was of equal intensity (1200 µmol 504

m-2s-1) measured by a LI-190 (Li-Cor Inc., Lincoln, NE, USA) light meter mounted in the same 505

position as the leaf sample holder. As the leaf was illuminated with the monochromatic laser 506

light the transverse (orthogonal) surface of the leaf was observed for fluorescence emitted from 507

the leaf tissue with a Peltier-cooled CCD camera (PIXIS 1024B, Princeton Instruments, Trenton, 508

NJ, USA). The laser spot (1 mm radius) was directed onto the 1 cm2 leaf surface centered on 509

the cut surface being observed. Consequently, the observed fluorescence would only arise from 510

chloroplasts up to 1 mm from the cut transverse surface. Light profiles were measured from the 511

resulting digital images where light absorbance was proportional (1:1) to the imaged 512

fluorescence, or pixel intensity (Vogelmann and Evans, 2002). Measurements were taken from 513

the adaxial edge of the mesophyll to the abaxial edge of the mesophyll and excluded 514

conspicuous non-photosynthetic structures such as veins. The mean of three profiles was 515

measured for each leaf sample and the mean of 2-3 leaf samples was measured per species. 516

All images were processed using the FIJI (Schindelin et al., 2012) distribution of ImageJ 517

(Rueden et al., 2017) software. All statistical calculations and graphing were performed using R 518

(R Core Team, 2018), with the exception of ANOVA and Tukey analyses which were performed 519

using Minitab® Statistical Software (2017). 520

521



29

Supplemental Data 522

Supplemental Table S1. The 57 plant species studied and associated traits. 523

Supplemental Figure S1. Chlorophyll distribution as a function of mesophyll depth for 57 524

species. 525

526

Acknowledgements 527

We thank Dr. Jay Wason (University of Maine) and Dr. Adam Roddy (Yale University) for 528

discussions, Dr. Jonathan Reuning-Scherer (Yale University) for statistical consultation, and the 529

Marsh Botanical Garden (New Haven, CT) and Montgomery Botanical Center (Coral Gables, 530

FL) for plant materials. The authors declare that there is no conflict of interest. 531

Tables 532

Table 1. Numerical coefficients for the equation y = y0 + ax + bx2 for models based on cluster 533

analysis, clade, and leaf thickness. 534

Model y0 a b

Cluster a 10.50834 2.31279 -0.01941

Cluster b 50.45836 0.59300 -0.00321

Cluster c 76.51942 0.27804 -0.00191

Cluster d 58.27920 0.88874 -0.00699

Cluster e N/A N/A N/A

Cluster f 88.74845 -0.38816 0.00250

Fern N/A N/A N/A

Cycad 59.28052 0.53491 -0.00348

Conifer 45.26811 0.99436 -0.00787

Ginkgo 66.61461 0.70577 -0.00672



30

Basal Angiosperm 61.51000 1.24990 0.00160

Magnoliid 74.46951 0.30182 -0.00223

Monocot 65.78703 0.36470 -0.00249

Eudicot 71.05103 0.33471 -0.00236

Thin Leaf 69.24298 0.35299 -0.00229

Thick Leaf 64.36971 0.33783 -0.00245

535

Figure legends 536

Figure 1. Overview of the epi-illumination method. Briefly, leaf samples are dark-adapted for 537

~20 min before transverse sections (A) are cut and placed on damp filter paper for imaging. 538

Samples are irradiated (< 30 s), and fluorescence from chlorophyll is detected with a CCD 539

camera. Chlorophyll content is proportional to pixel intensity in the resulting grayscale images 540

(B; Vogelmann and Evans, 2002). The 1D chlorophyll distribution is measured in ImageJ using 541

a line profile (line width mean of ~100 pixels, or ~60 µm at 20x magnification) drawn through the 542

photosynthetic tissue. Non-photosynthetic features such as veins (V), bundle sheath extensions 543

(BSE), and upper epidermal (UE) and lower epidermal (LE) cells are excluded from the 544

measurements. The profile begins at the upper edge of the mesophyll (e.g. palisade mesophyll 545

if present; PM) and ends at the lower edge of the spongy mesophyll (SM). Previous studies 546

using this technique included the epidermal cell layer (shown in panel C; blue bars), potentially 547

making chlorophyll profiles look more bell-shaped than with the current method. Chlorophyll 548

profiles are normalized as a function of maximum intensity to allow for comparison (absolute 549

fluorescence intensity varies across samples because of slight differences in exposure 550

parameters and signal decay over time) and are represented as a function of relative depth (C; 551

0% = upper edge of mesophyll, 100% = lower edge of mesophyll). 552

Figure 2. Differences in chlorophyll distribution for three representative species: Quercus alba 553

(A-C), Platycerium bifurcatum (D-F), and Eichhornia crassipes (G-I). At left, a typical grayscale 554



31

fluorescence image is shown for each species (A, D, G), where the yellow transect indicates the 555

section of tissue in a single measurement; chlorenchyma domains such as palisade (PM) and 556

spongy mesophyll (SM) are included in the measurements, whereas non-photosynthetic 557

structures such as veins (V), upper epidermal (UE) and lower epidermal (LE) layers, and 558

hypodermal layers (HL) are excluded. Intercellular airspaces (IA) in E. crassipes are included in 559

the measurements and increase local variability in mean profiles. Heat maps (B, E, H) of the 560

same images help to highlight trends in chlorophyll distribution. Multiple (n > 6) line profiles are 561

measured (gray points; C, F, I) to describe the mean chlorophyll profile (black points; C, F, I) for 562

an individual species. Chlorophyll content (as a percentage of the absolute chlorophyll 563

maximum) is displayed as a function of relative depth (percentage depth from upper to lower 564

edge of mesophyll). 565

566

Figure 3. Clustered display of chlorophyll profile data for 57 species. Dendrogram showing the 567

relationship among species chlorophyll profiles (A). The presence of six major profile schemes 568

(groups a-f) is indicated. Mean chlorophyll profiles of the species in each cluster are shown in 569

(B). Chlorophyll content (as a percentage of the absolute chlorophyll maximum) is displayed as 570

a function of relative depth (percentage depth from upper to lower edge of mesophyll). Points 571

and error bars represent mean ± s.e. Standard error bars less than ~ 3.0 are below resolution. 572

Figure 4. Differences in traits among groups with distinct chlorophyll profiles. Box plots of leaf 573

thickness (A), palisade fraction of mesophyll (B), and relative vein depth (C) by group derived 574

from hierarchical cluster analysis. Excludes groups (a) and (e) with single species. Boxes 575

represent inter-quartile range and lines across boxes represent group median. Whiskers extend 576

from the upper and lower quartiles to the group maximum and minimum, respectively. Asterisks 577

represent sample outliers. 578



32

Figure 5. General model of chlorophyll distribution. Mean chlorophyll distribution of 57 species 579

as a function of mesophyll depth (A). Chlorophyll content (as a percentage of the absolute 580

chlorophyll maximum) is displayed as a function of relative depth (percentage depth from upper 581

to lower edge of mesophyll). Quadratic regression is shown by the solid black curve. Points and 582

error bars represent mean ± s.e. The dashed, vertical line indicates the relative depth of the 583

transition between palisade and spongy mesophyll cell layers (38.64% ± 1.60 s.e.). The solid, 584

vertical line indicates the mean vein depth relative to the adaxial edge of leaf mesophyll 585

(59.76% ± 1.27 s.e.). Schematic of the typical leaf cross-section parameterized with 586

approximate chlorophyll content according to the general model (B). 587

Figure 6. Chlorophyll distribution by clade and leaf thickness. Chlorophyll content (as a 588

percentage of the absolute chlorophyll maximum) is displayed as a function of relative depth 589

(percentage depth from upper to lower edge of mesophyll) for cladistic and leaf thickness 590

subgroups: fern, n =3 (A); cycad, n= 9 (B); conifer, n=2 (C); ginkgo, n =1 (D); basal angiosperm, 591

n=1 (E); magnoliid, n=6 (F); monocot, n=9 (G); eudicot, n=26 (H); thin leaf, n = 47 (I); thick leaf, 592

n = 10 (J). Regressions shown in the form y = y0 + ax + bx2 for the respective datasets. Points 593

and error bars represent mean ± s.e. 594

Figure 7. Spatial associations between anatomical traits and peak chlorophyll content. 595

Mesophyll depth corresponding to peak chlorophyll concentration as a function of the palisade 596

to spongy mesophyll transition (A) and vein depth (B). Depth of chlorophyll maxima measured 597

from species chlorophyll profiles as a percentage of mesophyll thickness. Vein depth measured 598

from the adaxial edge of leaf mesophyll as a percentage of mesophyll thickness. Linear fit 599

shown in black (statistically non-significant in both cases). 600

Figure 8. Light absorption profiles and chlorophyll distribution in leaves. Subset of taxa (n = 5 601

species, with n = 2-3 leaves measured per species): Arenga pinnata, Bowenia spectabilis, 602

Coffea sp., Ulmus sp., Dryopteris sp. Points and error bars represent species mean ± s.e. 603



33

Leaves were irradiated on their adaxial or abaxial surface with blue (squares), red (diamonds), 604

or green (circles) light. Relative chlorophyll content is displayed (open circles) as a function of 605

relative depth (percentage depth from upper to lower edge of mesophyll). The dashed, vertical 606

line represents the mean relative depth of the transition between palisade and spongy 607

mesophyll (n = 3 species, excludes Bowenia spectabilis and Drypoteris sp.; 47.73% ± 5.2 s.e.). 608

The solid, vertical line represents mean vein depth relative to the adaxial edge of leaf mesophyll 609

(n = 4 species, excludes Drypoteris sp.; 62.3% ± 8.9 s.e.). 610

611



Parsed CitationsAalto T, Juurola E (2002) A three-dimensional model of CO2 transport in airspaces and mesophyll cells of a silver birch leaf. Plant, CellEnviron 25: 1399–1409

Pubmed: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Adams III WW, Terashima I (2018) The leaf: a platform for performing photosynthesis. Vol. 44. SpringerPubmed: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Bornman JF, Vogelmann TC, Martin G (1991) Measurement of chlorophyll fluorescence within leaves using a fibreoptic microprobe.Plant, Cell Environ 14: 719–725


Brodersen CR, Vogelmann TC (2010) Do changes in light direction affect absorption profiles in leaves? Funct Plant Biol 37: 403–412

Cui M, Vogelmann TC, Smith WK (1991) Chlorophyll and light gradients in sun and shade leaves of Spinacia oleracea. Plant CellEnviron 14: 493–500


Earles JM, Buckley TN, Brodersen CR, Busch FA, Cano FJ, Choat B, Evans JR, Farquhar GD, Harwood R, Huynh M, et al (2018a)Embracing 3D Complexity in Leaf Carbon–Water Exchange. Trends Plant Sci. 24:15-24


Earles JM, Theroux-Rancourt G, Roddy AB, Gilbert ME, McElrone AJ, Brodersen CR (2018b) Beyond porosity: 3D leaf intercellularairspace traits that impact mesophyll conductance. Plant Physiol 178: 148-162


Earles JM, Théroux-Rancourt G, Gilbert ME, McElrone AJ, Brodersen CR (2017) Excess Diffuse Light Absorption in Upper MesophyllLimits CO2 Drawdown and Depresses Photosynthesis. Plant Physiol 174: 1082–1096


Evans JR, Vogelmann TC (2003) Profiles of 14C fixation through spinach leaves in relation to light absorption and photosyntheticcapacity. Plant, Cell Environ 26: 547–560


Evans JR, Vogelmann TC (2006) Photosynthesis within isobilateral Eucalyptus pauciflora leaves. New Phytol 171: 771–782Pubmed: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Ho QT, Berghuijs HNC, Watté R, Verboven P, Herremans E, Yin X, Retta MA, Aernouts B, Saeys W, Helfen L, et al (2016) Three-dimensional microscale modelling of CO2 transport and light propagation in tomato leaves enlightens photosynthesis. Plant CellEnviron 39: 50–61


Ichiro T, Hiroki O, Takashi F, Riichi O (2016) Light environment within a leaf. II. Progress in the past one-third century. J Plant Res 129:353–363


Johkan M, Shoji K, Goto F, Hahida S, Yoshihara T (2012) Effect of green light wavelength and intensity on photomorphogenesis andphotosynthesis in Lactuca sativa. Environ Exp Bot 75: 128–133


Johnson DM, Smith WK, Vogelmann TC, Brodersen CR (2005) Leaf architecture and direction of incident light influence mesophyllfluorescence profiles. Am J Bot 92: 1425–1431


Koizumi M, Takahashi K, Mineuchi K, Nakamura T, Kano H (1998) Light Gradients and the Transverse Distribution of ChlorophyllFluorescence in Mangrove and Camellia Leaves. Ann Bot 81: 527–533


Minitab® 18 Statistical Software (2017) State College, PA: Minitab, Inc. (www.minitab.com) www.plantphysiol.orgon June 20, 2020 - Published by Downloaded from Copyright © 2019 American Society of Plant Biologists. All rights reserved.

https://www.ncbi.nlm.nih.gov/pubmed?term=Aalto T%2C Juurola E %282002%29 A three%2Ddimensional model of CO2 transport in airspaces and mesophyll cells of a silver birch leaf%2E Plant%2C Cell Environ 25%3A 1399%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Aalto&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=A three-dimensional model of CO2 transport in airspaces and mesophyll cells of a silver birch leaf.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=A three-dimensional model of CO2 transport in airspaces and mesophyll cells of a silver birch leaf.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Aalto&as_ylo=2002&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Adams III WW%2C Terashima I %282018%29 The leaf%3A a platform for performing photosynthesis%2E Vol%2E 44%2E Springer&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Adams&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=The leaf: a platform for performing photosynthesis.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=The leaf: a platform for performing photosynthesis.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Adams&as_ylo=2018&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Bornman JF%2C Vogelmann TC%2C Martin G %281991%29 Measurement of chlorophyll fluorescence within leaves using a fibreoptic microprobe%2E Plant%2C Cell Environ 14%3A 719%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Bornman&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Measurement of chlorophyll fluorescence within leaves using a fibreoptic microprobe.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Measurement of chlorophyll fluorescence within leaves using a fibreoptic microprobe.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Bornman&as_ylo=1991&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Cui M%2C Vogelmann TC%2C Smith WK %281991%29 Chlorophyll and light gradients in sun and shade leaves of Spinacia oleracea%2E Plant Cell Environ 14%3A 493%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Cui&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Chlorophyll and light gradients in sun and shade leaves of Spinacia oleracea.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Chlorophyll and light gradients in sun and shade leaves of Spinacia oleracea.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Cui&as_ylo=1991&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Earles JM%2C Buckley TN%2C Brodersen CR%2C Busch FA%2C Cano FJ%2C Choat B%2C Evans JR%2C Farquhar GD%2C Harwood R%2C Huynh M%2C et al %282018a%29 Embracing 3D Complexity in Leaf Carbon%26%23x2013%3BWater Exchange%2E Trends Plant Sci&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Earles&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Embracing 3D Complexity in Leaf Carbon?Water Exchange&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Embracing 3D Complexity in Leaf Carbon?Water Exchange&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Earles&as_ylo=2018&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Earles JM%2C Theroux%2DRancourt G%2C Roddy AB%2C Gilbert ME%2C McElrone AJ%2C Brodersen CR %282018b%29 Beyond porosity%3A 3D leaf intercellular airspace traits that impact mesophyll conductance%2E Plant Physiol&dopt=abstract


https://scholar.google.com/scholar?as_q=Beyond porosity: 3D leaf intercellular airspace traits that impact mesophyll conductance&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Beyond porosity: 3D leaf intercellular airspace traits that impact mesophyll conductance&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Earles&as_ylo=2018&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Earles JM%2C Th�roux%2DRancourt G%2C Gilbert ME%2C McElrone AJ%2C Brodersen CR %282017%29 Excess Diffuse Light Absorption in Upper Mesophyll Limits CO2 Drawdown and Depresses Photosynthesis%2E Plant Physiol 174%3A 1082%26%23x&dopt=abstract


https://scholar.google.com/scholar?as_q=Excess Diffuse Light Absorption in Upper Mesophyll Limits CO2 Drawdown and Depresses Photosynthesis.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Excess Diffuse Light Absorption in Upper Mesophyll Limits CO2 Drawdown and Depresses Photosynthesis.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Earles&as_ylo=2017&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Evans JR%2C Vogelmann TC %282003%29 Profiles of 14C fixation through spinach leaves in relation to light absorption and photosynthetic capacity%2E Plant%2C Cell Environ 26%3A 547%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Evans&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Profiles of 14C fixation through spinach leaves in relation to light absorption and photosynthetic capacity.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Profiles of 14C fixation through spinach leaves in relation to light absorption and photosynthetic capacity.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Evans&as_ylo=2003&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Evans JR%2C Vogelmann TC %282006%29 Photosynthesis within isobilateral Eucalyptus pauciflora leaves%2E New Phytol 171%3A 771%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Evans&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Photosynthesis within isobilateral Eucalyptus pauciflora leaves.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Photosynthesis within isobilateral Eucalyptus pauciflora leaves.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Evans&as_ylo=2006&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Ho QT%2C Berghuijs HNC%2C Watt� R%2C Verboven P%2C Herremans E%2C Yin X%2C Retta MA%2C Aernouts B%2C Saeys W%2C Helfen L%2C et al %282016%29 Three%2Ddimensional microscale modelling of CO2 transport and light propagation in tomato leaves enlightens photosynthesis%2E Plant Cell Environ 39%3A 50%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Ho&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Three-dimensional microscale modelling of CO2 transport and light propagation in tomato leaves enlightens photosynthesis.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Three-dimensional microscale modelling of CO2 transport and light propagation in tomato leaves enlightens photosynthesis.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Ho&as_ylo=2016&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Ichiro T%2C Hiroki O%2C Takashi F%2C Riichi O %282016%29 Light environment within a leaf%2E II%2E Progress in the past one%2Dthird century%2E J Plant Res 129%3A 353%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Ichiro&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Light environment within a leaf.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Light environment within a leaf.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Ichiro&as_ylo=2016&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Johkan M%2C Shoji K%2C Goto F%2C Hahida S%2C Yoshihara T %282012%29 Effect of green light wavelength and intensity on photomorphogenesis and photosynthesis in Lactuca sativa%2E Environ Exp Bot 75%3A 128%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Johkan&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Effect of green light wavelength and intensity on photomorphogenesis and photosynthesis in Lactuca sativa.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Effect of green light wavelength and intensity on photomorphogenesis and photosynthesis in Lactuca sativa.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Johkan&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Johnson DM%2C Smith WK%2C Vogelmann TC%2C Brodersen CR %282005%29 Leaf architecture and direction of incident light influence mesophyll fluorescence profiles%2E Am J Bot 92%3A 1425%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Johnson&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Leaf architecture and direction of incident light influence mesophyll fluorescence profiles.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Leaf architecture and direction of incident light influence mesophyll fluorescence profiles.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Johnson&as_ylo=2005&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Koizumi M%2C Takahashi K%2C Mineuchi K%2C Nakamura T%2C Kano H %281998%29 Light Gradients and the Transverse Distribution of Chlorophyll Fluorescence in Mangrove and Camellia Leaves%2E Ann Bot 81%3A 527%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Koizumi&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Light Gradients and the Transverse Distribution of Chlorophyll Fluorescence in Mangrove and Camellia Leaves.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Light Gradients and the Transverse Distribution of Chlorophyll Fluorescence in Mangrove and Camellia Leaves.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Koizumi&as_ylo=1998&as_allsubj=all&hl=en&c2coff=1



Morison JIL, Lawson T, Cornic G (2007) Lateral CO2 Diffusion inside Dicotyledonous Leaves Can Be Substantial: Quantification inDifferent Light Intensities. Plant Physiol 145: 680-690


Nishio JN, Sun J, Vogelmann C (1993) Carbon Fixation Gradients across Spinach Leaves Do Not Follow Internal Light Gradients. ThePlant Cell 5:953-961


Noblin X, Mahadevan L, Coomaraswamy IA, Weitz DA, Holbrook NM, Zwieniecki MA (2008) Optimal vein density in artificial and realleaves. Proc Natl Acad Sci 105: 9140–9144


Oguchi R, Douwstra P, Fujita T, Chow WS, Terashima I (2011) Intra-leaf gradients of photoinhibition induced by different color lights:implications for the dual mechanisms of photoinhibition and for the application of conventional chlorophyll fluorometers. New Phytol191: 146–159


Ort DR, Merchant SS, Alric J, Barkan A, Blankenship RE, Bock R, Croce R, Hanson MR, Hibberd JM, Long SP, et al (2015) Redesigningphotosynthesis to sustainably meet global food and bioenergy demand. Proc Natl Acad Sci 112: 8529–36


Palta JP (1990) Leaf chlorophyll content. Remote Sens Rev 5: 207–213Pubmed: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Pieruschka R, Schurr U, Jensen M, Wolff WF, Jahnke S (2006) Lateral diffusion of CO2 from shaded to illuminated leaf parts affectsphotosynthesis inside homobaric leaves. New Phytol 169: 779–788


Porra RJ, Thompson WA, Kriedemann PE (1989) Determination of accurate extinciton coefficients and simultaneous equations forassaying chlorophylls a and b extracted with four different solvents: verification of the concentration of chlorophyll standards byatomic absorption spectroscopy. Biochim Biophys Acta – Bioenerg 975: 384–394


R Core Team (2018) R: A language and environment for statistical computing. Vienna, Austria. URL https://www.r-project.org/Pubmed: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Reich PB (2014) The world-wide 'fast-slow' plant economics spectrum: a traits manifesto. J Ecol 102: 275–301Pubmed: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Sharkey TD, Weise SE, Standish AJ, Terashima I (2004) Chloroplast to Leaf. Springer, New York, NY, pp 171–206Pubmed: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Shipley B, Lechowicz MJ, Wright I, Reich PB (2006) Fundamental Trade-offs Generating the Worldwide Leaf Economics Spectrum.Ecology 87: 535–541


Slattery RA, Grennan AK, Sivaguru M, Sozzani R, Ort DR (2016) Light sheet microscopy reveals more gradual light attenuation in light-green versus dark-green soybean leaves. J Exp Bot 67: 4697–4709


Smith HL, McAusland L, Murchie EH (2017) Don't ignore the green light: exploring diverse roles in plant processes. J Exp Bot 68:2099–2110


Smith WK, Vogelmann TC, Delucia EH, Bell DT, Shepherd KA (1997) Leaf Form and Photosynthesis: Do leaf structure and orientationinteract to regulate internal light and carbon dioxide? Source Biosci 47: 785–793

Sun J, Nishio JN, Vogelmann TC (1998) Green Light Drives CO2 Fixation Deep within Leaves. Plant Cell Physiol 39: 1020–1026 www.plantphysiol.orgon June 20, 2020 - Published by Downloaded from Copyright © 2019 American Society of Plant Biologists. All rights reserved.

https://www.ncbi.nlm.nih.gov/pubmed?term=Minitab� 18 Statistical Software %282017%29 State College%2C PA%3A Minitab%2C Inc%2E %28www%2Eminitab%2Ecom&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Minitab®&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=State College, PA: Minitab, Inc.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=State College, PA: Minitab, Inc.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Minitab®&as_ylo=2017&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Morison JIL%2C Lawson T%2C Cornic G %282007%29 Lateral CO2 Diffusion inside Dicotyledonous Leaves Can Be Substantial%3A Quantification in Different Light Intensities%2E Plant Physiol&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Morison&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Lateral CO2 Diffusion inside Dicotyledonous Leaves Can Be Substantial: Quantification in Different Light Intensities&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Lateral CO2 Diffusion inside Dicotyledonous Leaves Can Be Substantial: Quantification in Different Light Intensities&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Morison&as_ylo=2007&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Nishio JN%2C Sun J%2C Vogelmann C %281993%29 Carbon Fixation Gradients across Spinach Leaves Do Not Follow Internal Light Gradients%2E The Plant Cell&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Nishio&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Carbon Fixation Gradients across Spinach Leaves Do Not Follow Internal Light Gradients&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Carbon Fixation Gradients across Spinach Leaves Do Not Follow Internal Light Gradients&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Nishio&as_ylo=1993&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Noblin X%2C Mahadevan L%2C Coomaraswamy IA%2C Weitz DA%2C Holbrook NM%2C Zwieniecki MA %282008%29 Optimal vein density in artificial and real leaves%2E Proc Natl Acad Sci 105%3A 9140%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Noblin&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Optimal vein density in artificial and real leaves.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Optimal vein density in artificial and real leaves.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Noblin&as_ylo=2008&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Oguchi R%2C Douwstra P%2C Fujita T%2C Chow WS%2C Terashima I %282011%29 Intra%2Dleaf gradients of photoinhibition induced by different color lights%3A implications for the dual mechanisms of photoinhibition and for the application of conventional chlorophyll fluorometers%2E New Phytol 191%3A 146%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Oguchi&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Intra-leaf gradients of photoinhibition induced by different color lights: implications for the dual mechanisms of photoinhibition and for the application of conventional chlorophyll fluorometers.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Intra-leaf gradients of photoinhibition induced by different color lights: implications for the dual mechanisms of photoinhibition and for the application of conventional chlorophyll fluorometers.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Oguchi&as_ylo=2011&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Ort DR%2C Merchant SS%2C Alric J%2C Barkan A%2C Blankenship RE%2C Bock R%2C Croce R%2C Hanson MR%2C Hibberd JM%2C Long SP%2C et al %282015%29 Redesigning photosynthesis to sustainably meet global food and bioenergy demand%2E Proc Natl Acad Sci 112%3A 8529%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Ort&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Redesigning photosynthesis to sustainably meet global food and bioenergy demand.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Redesigning photosynthesis to sustainably meet global food and bioenergy demand.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Ort&as_ylo=2015&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Palta JP %281990%29 Leaf chlorophyll content%2E Remote Sens Rev 5%3A 207%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Palta&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Leaf chlorophyll content.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Leaf chlorophyll content.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Palta&as_ylo=1990&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Pieruschka R%2C Schurr U%2C Jensen M%2C Wolff WF%2C Jahnke S %282006%29 Lateral diffusion of CO2 from shaded to illuminated leaf parts affects photosynthesis inside homobaric leaves%2E New Phytol 169%3A 779%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Pieruschka&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Lateral diffusion of CO2 from shaded to illuminated leaf parts affects photosynthesis inside homobaric leaves.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Lateral diffusion of CO2 from shaded to illuminated leaf parts affects photosynthesis inside homobaric leaves.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Pieruschka&as_ylo=2006&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Porra RJ%2C Thompson WA%2C Kriedemann PE %281989%29 Determination of accurate extinciton coefficients and simultaneous equations for assaying chlorophylls a and b extracted with four different solvents%3A verification of the concentration of chlorophyll standards by atomic absorption spectroscopy%2E Biochim Biophys Acta %26%23x2013%3B Bioenerg 975%3A 384%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Porra&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Determination of accurate extinciton coefficients and simultaneous equations for assaying chlorophylls a and b extracted with four different solvents: verification of the concentration of chlorophyll standards by atomic absorption spectroscopy.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Determination of accurate extinciton coefficients and simultaneous equations for assaying chlorophylls a and b extracted with four different solvents: verification of the concentration of chlorophyll standards by atomic absorption spectroscopy.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Porra&as_ylo=1989&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=R Core Team %282018%29 R%3A A language and environment for statistical computing%2E Vienna%2C Austria%2E URL https%3A%2F%2Fwww%2Er%2Dproject%2Eorg&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=R&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=R: A language and environment for statistical computing.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=R: A language and environment for statistical computing.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=R&as_ylo=2018&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Reich PB %282014%29 The world%2Dwide %27fast%2Dslow%27 plant economics spectrum%3A a traits manifesto%2E J Ecol 102%3A 275%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Reich&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=The world-wide 'fast-slow' plant economics spectrum: a traits manifesto.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=The world-wide 'fast-slow' plant economics spectrum: a traits manifesto.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Reich&as_ylo=2014&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Sharkey TD%2C Weise SE%2C Standish AJ%2C Terashima I %282004%29 Chloroplast to Leaf%2E Springer%2C New York%2C NY%2C pp 171%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Sharkey&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Chloroplast to Leaf.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Chloroplast to Leaf.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Sharkey&as_ylo=2004&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Shipley B%2C Lechowicz MJ%2C Wright I%2C Reich PB %282006%29 Fundamental Trade%2Doffs Generating the Worldwide Leaf Economics Spectrum%2E Ecology 87%3A 535%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Shipley&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Fundamental Trade-offs Generating the Worldwide Leaf Economics Spectrum.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Fundamental Trade-offs Generating the Worldwide Leaf Economics Spectrum.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Shipley&as_ylo=2006&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Slattery RA%2C Grennan AK%2C Sivaguru M%2C Sozzani R%2C Ort DR %282016%29 Light sheet microscopy reveals more gradual light attenuation in light%2Dgreen versus dark%2Dgreen soybean leaves%2E J Exp Bot 67%3A 4697%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Slattery&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Light sheet microscopy reveals more gradual light attenuation in light-green versus dark-green soybean leaves.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Light sheet microscopy reveals more gradual light attenuation in light-green versus dark-green soybean leaves.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Slattery&as_ylo=2016&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Smith HL%2C McAusland L%2C Murchie EH %282017%29 Don%27t ignore the green light%3A exploring diverse roles in plant processes%2E J Exp Bot 68%3A 2099%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Smith&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Don't ignore the green light: exploring diverse roles in plant processes.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Don't ignore the green light: exploring diverse roles in plant processes.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Smith&as_ylo=2017&as_allsubj=all&hl=en&c2coff=1



Takahashi K, Mineuchi K, Nakamura T, Koizumi M, Kano H (1994) A system for imaging transverse distribution of scattered light andchlorophyll fluorescence in intact rice leaves. Plant, Cell Environ 17: 105–110


Terashima I, Fujita T, Inoue T, Chow WS, Oguchi R (2009) Green Light Drives Leaf Photosynthesis More Efficiently than Red Light inStrong White Light: Revisiting the Enigmatic Question of Why Leaves are Green. Plant Cell Physiol 50: 684–697


Terashima I, Hanba YT, Tholen D, Niinemets U (2011) Leaf Functional Anatomy in Relation to Photosynthesis. Plant Physiol 155: 108–16Pubmed: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Tholen D, Boom C, Zhu X-G (2012) Opinion: Prospects for improving photosynthesis by altering leaf anatomy. Plant Sci 197: 92–101Pubmed: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Tholen D, Éthier G, Genty B (2014) Mesophyll conductance with a twist. Plant Cell Environ 37: 2456–2458Pubmed: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Tholen D, Zhu X-G (2011) The Mechanistic Basis of Internal Conductance: A Theoretical Analysis of Mesophyll Cell Photosynthesis andCO2 Diffusion. Plant Physiol 156: 90–105


Trojan A, Gabrys H (1996) Chloroplast Distribution in Arabidopsis thaliana (L.) Depends on Light Conditions during Growth. PlantPhysiol 11: 419–425


Vogelmann TC, Evans JR (2002) Profiles of light absorption and chlorophyll within spinach leaves from chlorophyll fluorescence. Plant,Cell Environ 25: 1313–1323


Vogelmann TC, Gorton HL (2014) Leaf: Light Capture in the Photosynthetic Organ. Springer, Dordrecht, pp 363–377Pubmed: Author and TitleGoogle Scholar: Author Only Title Only Author and Title

Vogelmann TC, Han T (2000) Measurement of gradients of absorbed light in spinach leaves from chlorophyll fluorescence profiles.Plant, Cell Environ 23: 1303–1311


Zwieniecki MA, Boyce CK (2014) Evolution of a unique anatomical precision in angiosperm leaf venation lifts constraints on vascularplant ecology. Proceedings Biol Sci 281: 20132829



https://www.ncbi.nlm.nih.gov/pubmed?term=Sun J%2C Nishio JN%2C Vogelmann TC %281998%29 Green Light Drives CO2 Fixation Deep within Leaves%2E Plant Cell Physiol 39%3A 1020%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Sun&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Green Light Drives CO2 Fixation Deep within Leaves.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Green Light Drives CO2 Fixation Deep within Leaves.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Sun&as_ylo=1998&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Takahashi K%2C Mineuchi K%2C Nakamura T%2C Koizumi M%2C Kano H %281994%29 A system for imaging transverse distribution of scattered light and chlorophyll fluorescence in intact rice leaves%2E Plant%2C Cell Environ 17%3A 105%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Takahashi&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=A system for imaging transverse distribution of scattered light and chlorophyll fluorescence in intact rice leaves.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=A system for imaging transverse distribution of scattered light and chlorophyll fluorescence in intact rice leaves.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Takahashi&as_ylo=1994&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Terashima I%2C Fujita T%2C Inoue T%2C Chow WS%2C Oguchi R %282009%29 Green Light Drives Leaf Photosynthesis More Efficiently than Red Light in Strong White Light%3A Revisiting the Enigmatic Question of Why Leaves are Green%2E Plant Cell Physiol 50%3A 684%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Terashima&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Green Light Drives Leaf Photosynthesis More Efficiently than Red Light in Strong White Light: Revisiting the Enigmatic Question of Why Leaves are Green.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Green Light Drives Leaf Photosynthesis More Efficiently than Red Light in Strong White Light: Revisiting the Enigmatic Question of Why Leaves are Green.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Terashima&as_ylo=2009&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Terashima I%2C Hanba YT%2C Tholen D%2C Niinemets U %282011%29 Leaf Functional Anatomy in Relation to Photosynthesis%2E Plant Physiol 155%3A 108%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Terashima&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Leaf Functional Anatomy in Relation to Photosynthesis.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Leaf Functional Anatomy in Relation to Photosynthesis.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Terashima&as_ylo=2011&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Tholen D%2C Boom C%2C Zhu X%2DG %282012%29 Opinion%3A Prospects for improving photosynthesis by altering leaf anatomy%2E Plant Sci 197%3A 92%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Tholen&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Opinion: Prospects for improving photosynthesis by altering leaf anatomy.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Opinion: Prospects for improving photosynthesis by altering leaf anatomy.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Tholen&as_ylo=2012&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Tholen D%2C �thier G%2C Genty B %282014%29 Mesophyll conductance with a twist%2E Plant Cell Environ 37%3A 2456%26%23x&dopt=abstract


https://scholar.google.com/scholar?as_q=Mesophyll conductance with a twist.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Mesophyll conductance with a twist.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Tholen&as_ylo=2014&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Tholen D%2C Zhu X%2DG %282011%29 The Mechanistic Basis of Internal Conductance%3A A Theoretical Analysis of Mesophyll Cell Photosynthesis and CO2 Diffusion%2E Plant Physiol 156%3A 90%26%23x&dopt=abstract


https://scholar.google.com/scholar?as_q=The Mechanistic Basis of Internal Conductance: A Theoretical Analysis of Mesophyll Cell Photosynthesis and CO2 Diffusion.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=The Mechanistic Basis of Internal Conductance: A Theoretical Analysis of Mesophyll Cell Photosynthesis and CO2 Diffusion.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Tholen&as_ylo=2011&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Trojan A%2C Gabrys H %281996%29 Chloroplast Distribution in Arabidopsis thaliana %28L%2E%29 Depends on Light Conditions during Growth%2E Plant Physiol 11%3A 419%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Trojan&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Chloroplast Distribution in Arabidopsis thaliana (L.) Depends on Light Conditions during Growth.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Chloroplast Distribution in Arabidopsis thaliana (L.) Depends on Light Conditions during Growth.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Trojan&as_ylo=1996&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Vogelmann TC%2C Evans JR %282002%29 Profiles of light absorption and chlorophyll within spinach leaves from chlorophyll fluorescence%2E Plant%2C Cell Environ 25%3A 1313%26%23x&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Vogelmann&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Profiles of light absorption and chlorophyll within spinach leaves from chlorophyll fluorescence.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Profiles of light absorption and chlorophyll within spinach leaves from chlorophyll fluorescence.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Vogelmann&as_ylo=2002&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Vogelmann TC%2C Gorton HL %282014%29 Leaf%3A Light Capture in the Photosynthetic Organ%2E Springer%2C Dordrecht%2C pp 363%26%23x&dopt=abstract


https://scholar.google.com/scholar?as_q=Leaf: Light Capture in the Photosynthetic Organ.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Leaf: Light Capture in the Photosynthetic Organ.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Vogelmann&as_ylo=2014&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Vogelmann TC%2C Han T %282000%29 Measurement of gradients of absorbed light in spinach leaves from chlorophyll fluorescence profiles%2E Plant%2C Cell Environ 23%3A 1303%26%23x&dopt=abstract


https://scholar.google.com/scholar?as_q=Measurement of gradients of absorbed light in spinach leaves from chlorophyll fluorescence profiles.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Measurement of gradients of absorbed light in spinach leaves from chlorophyll fluorescence profiles.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Vogelmann&as_ylo=2000&as_allsubj=all&hl=en&c2coff=1

https://www.ncbi.nlm.nih.gov/pubmed?term=Zwieniecki MA%2C Boyce CK %282014%29 Evolution of a unique anatomical precision in angiosperm leaf venation lifts constraints on vascular plant ecology%2E Proceedings Biol Sci&dopt=abstract

https://scholar.google.com/scholar?as_q=&num=10&as_occt=any&as_sauthors=Zwieniecki&hl=en&c2coff=1

https://scholar.google.com/scholar?as_q=Evolution of a unique anatomical precision in angiosperm leaf venation lifts constraints on vascular plant ecology.&num=10&btnG=Search+Scholar&as_epq=&as_oq=&as_eq=&as_occt=any&as_publication=&as_yhi=&as_allsubj=all&hl=en&lr=&c2coff=1

https://scholar.google.com/scholar?as_q=Evolution of a unique anatomical precision in angiosperm leaf venation lifts constraints on vascular plant ecology.&num=10&btnG=Search+Scholar&as_occt=any&as_sauthors=Zwieniecki&as_ylo=2014&as_allsubj=all&hl=en&c2coff=1


short title: spatial distribution of chlorophyll ... · 42 profile similarity, clade, and leaf...

Documents