Ignoring within-flower self-fertilization and inbreeding depression biases estimates of selection on floral traits

Within-flower self-pollination should be the major source of self-fertilization in mixed-mating species that present single or few flowers simultaneously. It is also an often unmeasured source of selfing in species with many flowers open simultaneously. In self-compatible species in which pistil and stamen numbers vary, the rate of within-flower selfing should depend on the number of pistils and stamens, the timing of flowering, and the morphology of subsidiary floral traits. The intensity and direction of selection on these traits should thus also depend on the level of inbreeding depression. Here, we measured the dependence of the within-flower selfing rate on floral sex allocation, phenology, petal length, and floral stalk height in a population of the perennial herb Pulsatilla alpina (Ranunculaceae) in which most individuals had single flowers. We estimated inbreeding depression in the population by comparing inbreeding coefficients between parents and seed progeny using microsatell..., The data set was collected from filed work at Solalex, in the pre-Alps of Vaud canton, Switzerland in 2022. , , # Ignoring within-flower self-fertilization and inbreeding depression biases estimates of selection on floral traits

This README file was generated on 2024-07-07 by Kai-Hsiu Chen

General information: 

Title: Ignoring within-flower self-fertilization and inbreeding depression biases estimates of selection on floral traits
Journal of Ecology, 2024
Authors: Kai-Hsiu Chen and John R. Pannell
Affiliations: Department of Ecology and Evolution, University of Lausanne, Switzerland
Correspondance: Kai-Hsiu Chen ([[e-mail]](mailto:[e-mail]))
Date of data collection: 2022.5-8
Location: Solalex, Vaud, Switzerland

Data and R Codes for analyses in the paper
Within-flower selfing rate
R file: Within-flower_selfing.R
Data used: Data_selfing.csv
Output: Figure 2, 3

Phenotypic selection
R file: Phenotypic_selection.R
Data used: Data_phenotypic_selection.csv
Output: Figure 4

List and Details of Datasets

**Data_selfing.csv**
1.Number of variables: 11

2.Number of cases/rows...