DOI: 10.5061/dryad.ghx3ffbsf
title: Spatial distribution data of stomata at the areole level for eight Magnoliaceae species

description: The dataset includes two .csv files of the spatial distribution data of
 stomata at the areole level for eight Magnoliaceae species: “EightSpecies”
 and “OneSpecies” .csv files.  The “EightSpecies” .csv file saves
 the planar coordinates of the stomatal centres of eight Magnoliaceae
 species. For each species, there are 41 to 60 leaves; for each leaf, three
 lamina sections (1.2 mm × 0.9 mm) equidistantly spaced from the leaf left
 margin to the midrib along the leaf maximum width axis were selected.
 There are in total 1189 sections. The “OneSpecies” .csv file saves the
 planar coordinates of stomatal centres of 12 Michelia cavaleriei var.
 platypetala leaves. There are six layers from leaf apex to leaf petiole
 (represented by the numbers 1 to 6) and three positions from the left leaf
 margin to the midrib on each layer (represented by the numbers 1 to 3. In
 total, stomatal sections from 18 locations were sampled in 12 leaves (i.e.
 12 replicates for different positions). There are in total 216 sections.
description: Eight Magnoliaceae species
 (four <em>Magnolia</em> species and four
 <em>Michelia</em> species) growing at the Nanjing Forestry
 University campus in September 2020 were examined in this study, with 100
 leaves for each species. With the exception of <em>Michelia
 maudiae</em> (for which only one tree was sampled), leaves were
 sampled from the middle canopies of three to five trees. For
 each leaf, three lamina sections (1.2 mm × 0.9 mm) equidistantly spaced
 from the leaf left margin to the midrib along the leaf maximum width axis
 were selected (Cited From Shi et al. [2022]).
 For <em>Michelia
 cavaleriei</em> var.
 <em>platypetala</em>, we additionally sampled
 72 leaves from four mature trees of
 <em>Michelia cavaleriei</em> var.
 <em>platypetala</em>, growing in Nanjing Forestry University
 campus, Nanjing, China (32°4'53.14''N,
 118°48'27.68'') in early September 2020. The trees ranged
 in diameter at breast height (DBH) from 9.5 to 12.5 cm and in height from
 5.5 to 6 m. All leaves were sampled from the middle canopy of trees
 without distinguishing current-year leaves from older leaves (the leaf
 life span of <em>M. cavaleriei</em> var.
 <em>platypetala</em> is 2-3 yr.). From the sampled leaves, 12
 leaves were randomly selected, and 18 rectangular sections (1.2 mm × 0.9
 mm) were collected from each of these leaves as illustrated in Figure 1.
 The sections were positioned equidistant from the leaf apex to the petiole
 (six layers). Because of
 the bilateral symmetry of the elliptical leaf shape of this tree species,
 we only needed to take sections of stomata from the left side of each
 leaf. From each layer,
 three sections were positioned equidistantly between the left leaf margin
 and the midrib (see Figure 1 for details). Among the six layers, layer 3
 was the closest to the leaf minor (width) axis, i.e., the maximum leaf
 dimension perpendicular to the leaf major (length) axis (straight line
 through the leaf apex and base). From the remaining 60 leaves, three
 sections (1.2 mm × 0.9 mm) were sampled from the left leaf marginal to the
 midrib on the leaf width axis; their sampling positions are similar to
 those on layer 3 as shown in Figure 1. The sections were taken between
 major veins to avoid leaf locations lacking stomata (Cited From Shi et al.
 [2021]).  The segregation method (Jiao et
 al., 2021) was used to obtain stomatal images saved as TIF files with a
 Leica DM 2500 light microscope (Leica Microsystems Shanghai, Shanghai,
 China), and the LAS X Life Science Microscope software (version
 3.4.2.18368, Leica Microsystems CMS GmBH, Wetzlar, Germany) installed on a
 desktop computer (Dell OptiPlex 3020, Xiamen, China). Details of the
 protocols are reported by Jiao et al. (2021) and Li et al. (2022). The
 maintained sample size of leaves with integrated sections of stomata for
 each species ranged between 40 to 60, and three positions of sections on
 each leaf could be clearly counted. We used R (version 3.6.1; R Core Team,
 2019) and the specific package ‘tiff’ (version 0.1-11; Urbanek and
 Johnson, 2022) to read the TIF files of stomatal section images and
 extract the planar coordinates of stomatal centres within the observation
 window of [0, 1200 μm] × [0, 900 μm]. There were 1189 observation windows
 (i.e., 1189 sections with the same size of 1.2 mm × 0.9 mm). For each
 section, there were 106 to 472 stomata, with an average (± SE) of 254 (±
 72) stomata per section. We used the ‘locator’ function in R (version
 3.6.1; R Core Team, 2019) to locate and designate all stomatal centres to
 obtain their planar coordinates in each section. In total, &gt;
 300,000 manual “clicks” were performed on the 1189 sections (Cited From
 Shi et al. [2022]).  
 <strong>References</strong>:
 <strong>Jiao Y,
 Gao Z, Wang
 </strong><strong>R.
 2021</strong>. Application of the segregation method to
 observing leaf stomatal structures of the <em>Michelia</em>
 plants. <em>Anhui Forestry Science and Technology</em>
 <strong>47(1)</strong>: 27–29.
 <strong>Li Y, Xiong D,
 Wang R, Jiao Y, Liu M, Yu K, Guo X, Shi P. 2022</strong>.
 Spatial distribution
 characteristics of stomata of six Magnoliaceae species. <em>Journal
 of West China Forestry Science</em>
 <strong>51(2)</strong>: 57–64.
 <strong>R Core Team.
 2019</strong>.
 <em>R: a language and environment for statistical
 computing</em>. Vienna: R Foundation for statistical computing.
 http://www.R-project.org (1 January 2020, date last accessed). <strong>Shi P, Jiao Y, Diggle PJ, Turner R, Wang R, Niinemets Ü. 2021</strong>. Spatial distribution characteristics of stomata at the areole level in <em>Michelia cavaleriei</em> var. <em>platypetala</em> (Magnoliaceae). <em>Annals of Botany</em> <strong>128</strong>: 875−885. <strong>Shi P, Wang L, Niinemets Ü, Jiao Y, Niklas K. 2022</strong>. Estimation of stomatal density of leaves with hierarchical reticulate venation. <em>Botany Letters</em> Under review. <strong>Urbanek S, Johnson K. 2022</strong>. <em>tiff: read and write TIFF images</em>. https://CRAN.R-project.org/package=tiff.