Data from: Pitcher geometry facilitates extrinsically powered ‘springboard trapping’ in carnivorous Nepenthes gracilis pitcher plants
Data files
Sep 02, 2022 version files 112.56 GB
Abstract
Carnivorous pitcher plants capture insects in cup-shaped leaves that function as motionless pitfall traps. Nepenthes gracilis, evolved a unique ‘springboard’ trapping mechanism that exploits the impact energy of falling raindrops to actuate a fast pivoting motion of the canopy-like pitcher lid. We superimposed multiple computerized micro-tomography images of the same pitcher to reveal distinct deformation patterns in lid-trapping N. gracilis and closely related pitfall-trapping N. rafflesiana. We found prominent differences between downward and upward lid displacement in N. gracilis only. Downward displacement was characterised by bending in two distinct deformation zones while upward displacement was accomplished by evenly distributed straightening of the entire upper rear section of the pitcher. This suggests an anisotropic impact response, which may help to maximize initial jerk forces for prey capture, as well as the subsequent damping of the oscillation. Our results point to a key role of pitcher geometry for effective ‘springboard’ trapping in N. gracilis.
Methods
Dataset 1
N. gracilis (n = 6) and N. rafflesiana (n = 5) pitchers were freshly harvested and CT-scanned immediately.
To this end, they were embedded up to a third of their height in an upright position in a container filled with sand, and the sand was moistened to solidify and keep the pitchers in place. The lid of the container had a custom-built mechanism that was attached to the lid of the pitcher and allowed to manipulate the lid position in between scans (neutral lid position, pushed down lid and pulled up lid). Each pitcher was scanned in a computerized tomography scanner (Nikon XT H 225 ST, Nikon Metrology Inc., Brighton, US). Scans were conducted with 3141 projections, 70 kV, 354 ms exposure time, without averaging over multiple scans and resulted in a voxel size of 30 µm (all N. gracilis and 1 N. rafflesiana pitcher) and 38 µm (all other N. rafflesiana pitchers). Scan time was limited to 20 minutes per scan to minimize dehydration of the tissue.
The three image stacks of the same pitcher with different lid positions were imported into 3D Slicer 4.11.20210226 (https://www.slicer.org/) and superimposed using a least square fit on the coordinates of five identical features in the lower part of the scan. The scans were segmented via thresholding (at grey value = 15000) and viewed as 3D overlays to identify locations of major deformation. 2D images were taken from the image stacks to visualize major deformations in the dorsal spine (longitudinal section), over the pitcher body and neck (horizontal cross-sections) and through the lid (vertical cross-sections). 2D images from the same slice with three different lid positions were overlaid in GIMP 2.10.30 (https://wwww.gimp.org/).
Further analysis was conducted along the major axis of deformation, the dorsal spine (visible in the longitudinal section). 100 equidistant points were placed along the spine and exported. From those the curvature and curvature difference between lid displacements were calculated with a custom Python script.
As this resolution of spacing led to a very high noise in the curvature data, a convergence study was conducted on one N. gracilis pitcher, and the 100 equidistant points were resampled to 10, 20, 30 and 50 points. The final analysis with all samples was conducted on a spacing of roughly 30 points, with 6 points being in the pitcher lid and between 7 and 21 points in the pitcher body, depending on the pitcher height, excluding the attachment point of the lid manipulation mechanism. A separate script was written to visualise the data from all pitchers and both species.
Dataset 2
A second experiment was conducted on 10 fresh N. gracilis pitchers to investigate the anisotropic loading response of the lid. A weight of 3.5 g was attached to the lid, and the pitcher was imaged with and without the weight, using a Canon D5 Mark3 DSLR camera and 90 mm macro lens. Then the pitcher was turned upside down and the experiment was repeated. Each two corresponding images were overlaid with GIMP 2.10.30 and the lid displacement measured with ImageJ (https://imagej.nih.gov/ij/).
Usage notes
Dataset 1 includes (1) 33 CT scans as *.tif stacks and their scanning information; (2) coordinate data that was extracted from the CT scans as *.csv-files; (3) a python-script to analyse the coordinates and calculate curvature and visualise the data; and (4) an additional python-script to summarize this data.
Dataset 2 includes 20 overlaid jpg-images to measure lid displacement and the *.xlsx-file that summarises the measurements and data analysis for this data.
Further instructions are in the README.txt