DOI: 10.5061/dryad.z8w9ghxmw
title: Supporting data for: Honeybees adapt to a range of comb cell size by merging, tilting and layering their construction

description: Honeybees are renowned for their skills in building intricate and adaptive
 hives that display notable variation in cell size. However, the extent of
 their adaptability in constructing honeycombs with varied cell sizes has
 not been investigated thoroughly. We use 3D-printing and X-ray Microscopy
 to quantify honeybees' capacity in adjusting the comb to different
 initial conditions. Using the average area of natural worker cells as a
 reference, our findings suggest three distinct construction modes when
 faced with foundations of varying cell sizes. For smaller cell size, bees
 occasionally merge cells to compensate for the reduced space. However, for
 larger cell sizes, the hive uses adaptive strategies like tilting for
 cells up to twice the reference size, and layering for cells that are
 three times larger than the reference cell. Our findings shed light on
 honeybees’ adaptive comb construction strategies with potential to find
 applications in additive manufacturing, bio-inspired materials, and
 entomology.
description: <strong>Experimental data
 Collection</strong>  
 All of our experiments are performed using colonies of European
 honeybees Apis melifera L. at the Peleg lab apiary in Boulder, Colorado,
 USA.   Fused deposition
 modeling (FDM) technology was used for 3D-printing of experimental frames
 using Polylactic Acid (PLA) material, and the designs are made in
 SolidWorks 2019 CAD design software. Each frame consists of a pair of
 3D-printed plates that are placed opposite to each other. For our control
 set with S=1, each hexagonal element on the 3D-printed plates has a
 side-length of 2.7 mm. All the other configurations are designed relative
 to the area of our control set.  
 All photographs of honeycomb are captured using a Nikon DSLR
 camera and controlled lighting and a black background.
   XRM data collection was performed at
 MIMIC facility, at CU Boulder (RRID:SCR_019307). 
   All tomography scans are performed
 using Micro CT ZEISS Xradia 520 Versa (Carl Zeiss X-ray Microscopy Inc,
 Pleasanton, CA, USA).  
 Image processing and segmentation on the X-ray data is
 conducted using Python and Dragonfly (Object Research Systems, Montreal,
 QC, Canada).  
 <strong>Dataset Contents</strong>
   The raw data obtained from X-ray
 microscopy of our control dataset, S=1, in the form of a stack of tiff
 images.  2D images of honeycomb that captured using
 a Nikon DSLR camera and controlled lighting, and a black
 background. Stacks of thresholded tiff images for
 reproducing the 3D volumes, obtained from X-ray Microscopy.
 CSV files that show the angle of tilt (in degrees) for each
 cell on the X-rayed sample. CSV files that contain
 the xy coordinates of cell centers, and their area.
 Movies showing the 3D-reconstruction of the sample, made using
 the thresholded X-ray data in Dragonfly software.
   <strong>X-ray data
 Processing</strong>  
 X-ray tomography scanning of our experimental samples generate
 stacks of cross-sectional tomography images which form a 3D model of the
 samples when digitally stitched together. Each tomography image comprises
 of the following elements-- air, honeycomb, and the plastic base, each
 captured with a different pixel intensity which is a function of the
 radiodensity of the element. We develop an image processing pipeline that
 converts the stack of tomography images to filter out unwanted parts of
 the raw X-ray image data and segment particular regions of interest.  We
 mainly used computer vision techniques, with OpenCV [1] library in Python
 3.0, to conduct all our image analyses. For creating clear 3D
 visualizations, we use a combination of convolution with a specially
 designed kernel and morphological operations to segment the plastic cell
 edges. We use the second derivative of the image histogram to find the
 optimum threshold value for the effective segmentation of air from data
 (i.e., honeycomb and plastic). Next, we identify pixels that mark the
 boundary of the plastic base and air using convolution with a specially
 designed kernel that detects changes in pixel intensities.Using this we
 create a kernel which is convolved over the image as a sliding window and
 at each row, the result of convolution is maximized precisely when the
 kernel is at the boundary of the plastic base. As a result, this process
 generates a mask that marks the boundary pixels. With this mask as a seed,
 we use morphological operations to generate an enhanced mask that covers
 the plastic base entirely.  
 <strong>Tilt angle calculation</strong>
   For the comb built on the 3D-printed
 frames with size S=1, 1.25, 1.5, 1.75, and 2 we compare and quantify the
 cell tilt values relative to the plastic base. We achieve this by creating
 two parallel planes intersecting the honeycomb at the base and the upper
 layer. Then, in each plane we identify the intersecting hexagonal
 cross-sections (components) corresponding to the hexagonal cavities of
 individual cells. Subsequently, we identify the centroids of each of these
 hexagonal components and their centroids by running Connected Component
 Analysis on each plane in the Dragonfly software [2]. Once these contours
 are established, the angle of tilt for each honeycomb cell is computed
 through simple geometric analysis using the displacement value of the cell
 centroids.  
 <strong>References</strong>
   [1] G. Bradski, Dr. Dobb’s Journal of
 Software Tools (2000). [2] Comet Technologies
 Canada Inc., Montreal, Canada, Dragonfly.
description: # Supporting data for: Adaptive cell size, merging, tilting, and layering
 in Honeybee comb construction
 [https://doi.org/10.5061/dryad.z8w9ghxmw](https://doi.org/10.5061/dryad.z8w9ghxmw) We are sharing the data used to explore the adaptability of the honeycomb structure built on the 3D-printed experimental frames with various cell size foundations.  ## Description of the data and file structure All of the files are categorized based on the value of the 3D-printed cell sizes *S*. The file names in each dataset follow the naming convention `s_`, where `` is the relative 3D-printed cell size of the sample, with a *'o'* used to represent a decimal point *'.'*. For example, for data regarding *S=1* or *S=1.5*, all file names would start with `s_1` or `s_1o5` respectively. Refer to the paper for more details about *S*. ### ***s_1_raw_xrm_data.zip*** A sample of the raw X-ray microscopy data for our control dataset (S = 1) is provided as a stack of TIFF images. Raw X-ray images for the other size categories are available upon request. ### *2D_images.zip* Contains folders named `s_` which include a set of three JPEG files. * Filenames in each folder: `s__--.jpeg`, where `--` refers to the month, day and year that the picture is taken. ### *processed_XRM_data.zip* Stacks of thresholded images for reproducing the 3D volumes, obtained from X-ray Microscopy. * File names: `s__histogram_thresholded.zip`. ### ***cell_size_data.zip*** Cell size data is organized in 7 folders `s_` containing CSV files for more than 1000 cells built on experimental frames. * Filenames in each folder: `s__cell_sizes_.csv`. All CSV files contain these fields: - *cx:* the x-coordinate of the cell center - *cy:* the y-coordinate of the cell center - *normalized cell size:* the area of the cell in millimeter squared divided by the mean cell area of the reference cell (~12.96) ### ***angle_data.zip*** Contains CSV files that show the angle of tilt (calculated in degrees) for each cell on all of the tilted samples. * Filenames: `s__cell_tilts.csv`. These values are measured, using Dragonfly software, for all the cells imaged with the X-ray. * The contents of the file named `natural_drone_cell_tilts.csv` are manually measured for 20 individual drone cells. ### *angle_raw_data.zip*  Contains Dragonfly files to compute the angle of tilt of honeycomb cells. We use the Dragonfly 3D image processing software to measure the displacement of the centroid of a honeycomb cell at its top, relative to the base of an experimental frame. More details about how this is done can be found in the SI of the paper. ### ***3D_reconstruction_movies.zip*** A movie showing the 3D-reconstructed volume for each sample, made using the thresholded X-ray data (provided in *processed_XRM_data.zip* files) using Dragonfly software. * Filenames: `s__movie.mp4`. * All 3D volumes are constructed using the X-ray data from the *5 cm × 5 cm* sections of the comb constructed on our experimental frames, segmented to show comb in dark yellow and plastic in blue. ### ***s_o75_covered_cell_data.zip*** Contains CSV files showing the number of all covered cells in each row of the three replicates of *S=0.75*. * Filenames: `covered_cells_o75_.csv`. All files contain these fields: * *Row number* * *covered:* number of covered cells in the row * *all:* total number of cell in the row ### ***Fig.2K.zip*** Contains files and datasets that can be used to regenerate the corresponding figure 2K in the main paper. ### ***Fig.3C.zip*** Contains files and datasets that can be used to regenerate the corresponding figure 3C in the main paper. ### ***Fig.3D.zip*** Contains files and datasets that can be used to regenerate the corresponding figure 3D in the main paper. ### ***Fig.4D.zip*** Contains files and datasets that can be used to regenerate the corresponding figure 4D in the main paper. ### ***Fig.S5.zip*** Contains files and datasets that can be used to regenerate the corresponding figure S5 in the SI section of the paper. ### ***Fig.SAB.zip*** Contains files and datasets that can be used to regenerate the corresponding figure SA(B) in the SI section of the paper. ### ***Fig.SAC.zip*** Contains files and datasets that can be used to regenerate the corresponding figure SA(C) in the SI section of the paper. ## Sharing/access information All of our experiments are performed using colonies of European honeybees *Apis melifera* L. at the *Peleg lab* apiary in Boulder, Colorado, USA.  Fused deposition modeling (FDM) technology was used for 3D-printing of experimental frames using Polylactic Acid (PLA) material, and the designs are made in *SolidWorks 2019* CAD design software. All photographs of honeycomb are captured using a Nikon DSLR camera and controlled lighting and a black background. XRM data collection was performed at MIMIC facility, at *CU Boulder* (RRID:SCR_019307).  All tomography scans are performed using Micro CT ZEISS Xradia 520 Versa (Carl Zeiss X-ray Microscopy Inc, Pleasanton, CA, USA). Image processing and segmentation on the X-ray data is conducted using Python and Dragonfly (Object Research Systems, Montreal, QC, Canada). ## Code/Software The code that is used for this study can be found on [Zenodo](https://zenodo.org/records/15610301) or Peleg Lab's[ GitHub](https://github.com/peleg-lab/honeycomb-adaptive-construction), along with detailed instructions of how to use this data to process and run it.  ## Change Log **Jun 10, 2025**: We made some changes to the repository based on the reviewers' request to include all the data used for reproducing the plots in our paper and SI. The changes are as follows: * Added the folder *s_o75_covered_cell_data.zip* * Updated the *cell_size_data.zip* files to reflect the values for the normalized cell sizes rather than raw values **July 17, 2025**: We made some more changes to the repository based on the reviewers' request to rename all the folders including data used for reproducing the plots in our paper and SI and add them to the main directory for easier access. The changes are as follows: * Removed *Data_for_figures.zip* which previously contained sub-folders with data for all figures and instead added *Fig.2K.zip, Fig.3C.zip, Fig.3D.zip, Fig.4D.zip, Fig.S5.zip, Fig.SA-B-C.zip* folders to the main directory for easier access. * Renamed and separated the contents of *Fig.SA-B-C* to *Fig.SAB* and *Fig.SAC* for more clarity. * Added *angle_raw_data.zip* containing raw Dragonfly files that is used to calculate *angle_data.zip*.