MicroCT data to 'Maximum CO2 diffusion inside leaves is limited by the scaling of cell size and genome size'

This dataset is presented in the following publication. Please cite this publication if you use the dataset.

Théroux-Rancourt Guillaume, Roddy Adam B., Earles J. Mason, Gilbert Matthew E., Zwieniecki Maciej A., Boyce C. Kevin, Tholen Danny, McElrone Andrew J., Simonin Kevin A. and Brodersen Craig R. 2021. Maximum CO₂ diffusion inside leaves is limited by the scaling of cell size and genome size. Proceedings of the Royal Society B. 288: 20203145. doi:10.1098/rspb.2020.3145

We collected leaf samples from botanical gardens, greenhouses, and field sites,  which were then transported to one of three synchrotron-based microCT beamlines for imaging. To- and three-dimensional data were then extracted from the microCT images to characterize the structural anatomy of the different study species. Those data were then analyzed and correlated with genome size data available from the Kew Plant DNA C-values database (https://cvalues.science.kew.org) or newly collected by us.

From the botanical garden collections we selected representative species from across the vascular plant phylogeny, aiming to capture as much variation in anatomical/physiological/ecological traits as possible while also sampling species that represented important divergences in the phylogeny.  Within clades, we also sampled species that spanned ecological breadth (e.g. xerophytic ferns). We focused solely on C3 terrestrial vascular plants, meaning that we did not sample C4 or CAM species, which have different photosynthetic biochemistry and associated anatomy.

In most cases, single microCT scans were used per species. This constraint was primarily due to the extremely limited amount of time available at the microCT facility, as well as the labor intensive process of producing the final volume renderings and data analysis.

MicroCT scans were collected by GTR, JME, ABR, CRB, AJM, CKB, MJZ, and DT at one of the three microCT beamlines from fresh leaf material. Leaves were cut at the base of the petiole or short stem segment, the cut end was wrapped in wet paper towels, and the entire shoot immediately put in a plastic bag before being transported to the synchrotron and scanned within 36 h of excision.  Samples were prepared before each scan (less than 30 min) by excising a small sample that was then enclosed between two pieces of Kapton (polyimide) tape to prevent desiccation while allowing high X-ray transmittance.

All microCT data were collected at the Lawrence Berkeley National Laboratory (LBNL) tomography beamline 8.3.2, the Swiss Light Source (SLS) TOMCAT Tomography beamline of the Paul Scherrer Institute, or the Advanced Photon Source  tomography beamline 2-BM-A,B of Argonne National Laboratory (ANL).  MicroCT datasets were reconstructed from the raw projection images obtained using TomoPy, an open-source Python-based framework for reconstructing tomographic data (LBNL), or using the in-house reconstruction platform of the beamline (SLS, ANL). LBNL and SLS data can be reconstruction using TomoPy, and this software is available at the following link: http://microct.lbl.gov/software

Image stacks were segmented using the open-source software ImageJ either manually or using an automated machine learning algorithm (Théroux-Rancourt et al., 2020: doi:10.1002/aps3.11380).  Traits were extracted from the segmented image stacks using ImageJ, the BoneJ plugin of ImageJ, or with an open-source Python-program available at: https://github.com/plant-microct-tools/leaf-traits-microct. Because of the multiple synchrotron and multiple sessions involved in acquiring this dataset, and because the analysis process lasted several years and was carried out by several persons, the size of each image stack and the details in each stack vary. What is present in each stack is the airspace and the whole mesophyll (i.e. the leaf without the epidermis), and in the majority of the cases, the vasculature is also segmented.