Data from: Bat pollination in the Yungas
Data files
Apr 11, 2024 version files 3.17 KB
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README.md
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visits.csv
Abstract
Bat-plant pollination interactions at the range margin in the southwestern Neotropics have been largely unexplored. Here, we report for the first time on bat pollination, visitation rate, and efficiency for Melidiscus giganteus, Helicteres lhotzkyana, and Pitcairnia oranensis, representing the first direct evidence of bat pollination in the Southern Andean Yungas.
README: Bat pollination in the Yungas
https://doi.org/10.5061/dryad.9s4mw6mqc
Description of the data and file structure
The data table is embedded with the script
Column names have the following meanings:
For data.frame "visits":
- Plant: plant species name
- patch: observation unit
- T: observation time in each patch in hours
- F: number of flowers in each patch
- type: type of flower visitor
- Vf: visitation frequency
- success: successful visitation frequency
Operations added as columns to "visits"
- F.T: vector of the product F*T
- Vr: visitation rate obtains as Vr/F.T
Code/Software
An R script is attached
Methods
We conducted a plant-centered interaction survey focusing on three plant species at four foothill sites in northwestern Argentina. To record visits, we employed both video cameras and direct observation during nighttime, when flowers opened, accumulating a total observation time of 41.6 hours for 36 flowers across the three species. The visitation rate (Vr) was calculated as Vr=VfxF-1xT-1, where Vf represents visitation frequency, F is the number of observed flowers, and T is the observation time in hours. Additionally, we calculated pollination efficiency (PE) as PE = VsxF-1xT-1, where Vs represents the visitation frequency with visitors making contact with anthers and stigma. To assess differences in Vr and PE among plant species, we utilized generalized linear models with Poisson data distribution. We used Vf and Vs as a response variable and the natural log of the product of F and T as an offset to obtain Vr and PE, respectively. Our models sought to explore whether Vr and PE variations could be explained by plant species and pollinator groups, distinguishing between bats and other nocturnal pollinators. Significance tests involved comparing each model with a null model where the prediction variable was set to one. Subsequently, we conducted analyses of variance and Chi2 tests to compare the residual sum of squares across models. All statistical analyses were performed using R (R Core Team 2022).