Need for speed? It is not necessary to be always the fastest–a case study of two thermophilous ant species
Data files
Dec 03, 2025 version files 816.87 KB
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README.md
2.94 KB
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Ślipiński_et_al_-_Supplementary_material_Tab_S2.xlsx
786.23 KB
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Ślipiński_et_al_-_Supplementary_material_Tab_S3.xlsx
27.70 KB
Abstract
When the decisions about the movement are made and the animal should adjust the trajectory and movement speed to maximise the efficiency in reaching its goal. The most important environmental factor, which influence the movement in case of ectothermic ants, is temperature. In the current experiment, we compared how species with different thermal adaptations responded to foraging in the thermally challenging conditions. To be more specific, how the external temperature influences the inbound time and path (straightness) of ants' movement when they return to the nest with prey. Generally, workers’ inbound time was linked with the mean speed of foraging ants in case of both species–faster workers return earlier to the nest. The straightness of workers’ movements–the path they took to the nest–was not linked with sand temperature, nor with the speed of workers in case of C. velox. On the contrary, in case of A. senilis, the straightness of workers’ movements was linked with mean speed of ants. The faster workers choose the most straight path to the nest entrance. The difference in behavioural response of both species may derive from the physiological differences between species. C. velox, as a more physiologically temperature resistant and generally faster seem to have a broader bandwidth of behaviours concerning the choice inbound trajectory with no need to narrow it when the temperature rises e.g. increase the movement straightness. Each of the species tries to take the advantage based on their stronger properties, C. velox on its higher speed and A. senilis on higher straightness and also possibility to recruit nestmates.
Dataset DOI: 10.5061/dryad.z612jm6q8
Description of the data and file structure
In this study, we compare the response of two behaviourally subordinate (species that are at the bottom of the dominance/aggression hierarchy) and thermophilous (species thriving at high soil temperatures) ant species to the thermally challenging conditions. To be more specific, how the external temperature influences the speed and path of ant movement in Cataglyphis velox and Aphaenogaster senilis, when they return to the nest with prey.
Files and variables
File: Ślipiński_et_al_-_Supplementary_material__1.docx
Description: Supplementary figures and literature
File: Ślipiński_et_al_-_Supplementary_material_Tab_S2.xlsx
Description: Raw data from ants' movement
Sheets: There are two sheets in the file, one with the data from Cataglyphis velox and the second from Aphaenogaster senilis
Variables
- Col - colony
- Ant ID - the ant ID
- Position ID - reflects the ant position measurement. From 1, where was the first ant position measurement was up to the moment of ant capture
- X position - position of ant on the x/y axis
- Y position - position of ant on the x/y axis
- Distance (cm) - the distance from the bait
- Speed (cm/s) - ant speed
File: Ślipiński_et_al_-_Supplementary_material_Tab_S3.xlsx
Description: Averaged and calculated data based on the data from Tab_S2
Variables
- Date - the date of measurement
- Colony - colony
- Eppendorf ID - Id of the Eppendorf tube with the particular ant
- Temperature Bait (Celsius degrees) - the surface temperature measured close to the bait position
- Ant ID - Id of the measured ant
- Mean speed (cm/s) - mean speed of the ant
- Distance (cm) - the distance covered by the ant
- Inboud time (s) - the time measured from the moment of collecting the prey to the moment of capture
- Capture from the bait (cm) - reflects the distance in cm of the individual from the bait in the moment when the ant was captured.
- Capture from the entrance (cm) - same as above, but from the nest entrance.
- Straightenss - the straightness index value
- Head Width (mm) - head width measurement of the ant
- Head length (mm) - head length measurement of the ant
Code/software
In all models, the nested random factor was the studied colony ID and repetition (video recording). The models were fit with the Gaussian distribution, and diagnostics of model residuals were done with the use of the DHARMa package (Hartig, 2022). The linear models were performed using the lme4 and lmer packages (Bates et al., 2015; Kuznetsova et al., 2017). All dependent variables were log-transformed. All statistical analyses were performed in R (RStudio Team 2024). The significance threshold was set to 0.05.