Beware of the impact of land use legacy on genetic connectivity: A case study of the long-lived perennial Primula veris

This dataset contains genetic and landscape data of 32 Primula veris populations in Muhu island in Estonia. The study populations are on two 2x2 km study landscapes. Genetic samples were collected in 2014. Landscape data was extracted from maps dated 2015. Data is divided into node- and link-based data. Node-based data contains genetic diversity data of the P. veris populations. Link-based data contains genetic differentiation between population pairs and landscape data in buffers surrounding a straight line between population pairs.

Methods
To generate the genetic information, the leaves of Primula veris were collected from study populations and DNA was extracted from the leaves. Extracted DNA was prepared for library using ddRAD (Peterson, Weber, Kay, Fisher, & Hoekstra, 2012) method and sequenced.

Genetic data was filtered geoinformatically (see Träger et al. 2021) and population-based genetic diversity indices (unbiased expected and observed heterozygosity, uHe and Ho, respectively) were calculated using GENALEX version 6.503 (Peakall & Smouse, 2005, 2012)  and mean nucleotide diversity (π) was calculated using vcftools v0.1.12b (Danecek et al., 2011) within a window of 125 bp over all loci for each population. Inbreeding coefficients (FIS) and genetic differentiation (FST) were calculated using the package `genepop´ (Rousset, 2008) in R version 3.4.2 (R Core Team, 2017).

Pairwise mean assignment probability (MAP) was calculated with the package AssignPop (Chen et al., 2018). For calculating MAP, we used assignment tests. 
We performed assignment tests for which we filtered out loci with low variance (threshold at 0.95) and used Monte-Carlo cross-validation. All loci (100%) were used as training data.

The classification method for prediction was linear discriminant analysis. The resulting pairwise probabilities (membership accuracies across all individuals) 
were directional (e.g. 1 to 2, 2 to 1). We added these pairs together and divided them by two, resulting in one value per population pair (MAP; following van Strien et al., 2014).

Study populations were sampled at the scale of 2 2x2 km study landscapes (Koguva, Lepiku) and a 250 m buffer around the 2x2 km landscapes was added, resulting in two 2.5x2.5 km squares. We calculated the proportional amount of landscape elements surrounding the straight line between population pairs in a buffer with a width of 100 m. 
We only calculated this within one landscape. We transformed the landscape data from vector data to 10x10 m raster data for resistance surface analysis.

References:

Chen, K.-Y., Marschall, E. A., Sovic, M. G., Fries, A. C., Gibbs, H. L., & Ludsin, S. A. (2018). assignPOP: An r package for population assignment using genetic, non-genetic, 
or integrated data in a machine-learning framework. Methods in Ecology and Evolution, 9(2), 439–446. https://doi.org/10.1111/2041-210X.12897
Danecek, P., Auton, A., Abecasis, G., Albers, C. A., Banks, E., DePristo, M. A., Handsaker, R. E., Lunter, G., Marth, G. T., Sherry, S. T., McVean, G., & Durbin, R. (2011). 
The variant call format and VCFtools. Bioinformatics, 27(15), 2156–2158. https://doi.org/10.1093/bioinformatics/btr330
Peakall, R., & Smouse, P. E. (2005). genalex 6: Genetic analysis in Excel. Population genetic software for teaching and research. 
Molecular Ecology Notes, 6(1), 288–295. https://doi.org/10.1111/j.1471-8286.2005.01155.x
Peakall, R., & Smouse, P. E. (2012). GenAlEx 6.5: Genetic analysis in Excel. Population genetic software for teaching and research—an update. 
Bioinformatics, 28(19), 2537–2539. https://doi.org/10.1093/bioinformatics/bts460
Rousset, F. (2008). genepop’007: A complete re-implementation of the genepop software for Windows and Linux. 
Molecular Ecology Resources, 8(1), 103–106. https://doi.org/10.1111/j.1471-8286.2007.01931.x
R Core Team. (2017). R: A language and environment for statistical computing. R
Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
Reinula, I., Träger, S., Järvine, H-T., Kuningas, V-M., Kaldra, M., Aavik, T. (2024). 
Beware of the impact of land use legacy on genetic connectivity: A case study of the long-lived perennial Primula veris. Biological Conservation, xx. 
Träger, S., Rellstab, C., Reinula, I., Zemp, N., Helm, A., Holderegger, R., Aavik, T. (2021).
Genetic diversity at putatively adaptive but not neutral loci in Primula veris responds to recent habitat change in semi-natural grasslands bioRxiv 2021.05.12.442254; doi: https://doi.org/10.1101/2021.05.12.442254
van Strien, M. J., Keller, D., Holderegger, R., Ghazoul, J., Kienast, F., & Bolliger, J. (2014). Landscape genetics as a tool for conservation planning: 
Predicting the effects of landscape change on gene flow. Ecological Applications, 24(2), 327–339. https://doi.org/10.1890/13-0442.1