Differences between the dispersal distance analysis and the probability to leave a plot analysis might originate because the more complex (less simplified) dispersal distance analysis additionally covers the temporal aspect of the dispersal process and also from the different spatial scales that are covered by the two.
In the context of GMP dispersal, cluster analysis can be used to integrate measurement data from different meteorological networks with different coverage in a GIS environment for defining representative climatic regions.
Secondly, the program Dispersal Vicariance Analysis (DIVA; Ronquist 1996) was used.
Dispersal Vicariance Analysis is based on the dispersal vicariance approach (Ronquist 1997), which consists of the optimization of a three-dimensional cost matrix derived from a simple biogeographic model.
We ran Statistical Dispersal Vicariance Analysis (S-DIVA) using RASP v.2.1 [ 95, 96] to infer the biogeographic history of this section based on the phylogenetic trees constructed only from our concatenated chloroplast dataset.
To calculate the posterior probability of ancestral distribution at internal nodes, we used a Bayesian approach implemented in the updated version of Statistical Dispersal Vicariance Analysis (S-DIVA), RASP v.2.0b [ 67, 68], and our generic-level phylogeny.
We used the Statistical Dispersal Vicariance analysis (SDiVA; [ 61] for the ancestral area reconstruction and for detection of the possible dispersal events. The t-files from the Bayesian analyses were used as input trees for the statistical part of the analysis (support value for the reconstructed ancestral area for the particular nodes).
Accordingly, we tested the following models: Dispersal-Extinction Cladogenesis Model (DEC), Dispersal-Vicariance Analysis (DIVA), Bayesian inference of historical biogeography for discrete areas (BayArea) and the same models including the founder-event speciation parameter ('j'), DECj, DIVAj and BayAreaj.
DEC = Dispersal-Extinction Cladogenesis; DIVA = Dispersal-Vicariance Analysis; BAYAREALIKE = Bayesian inference of historical biogeography for discrete areas; j = founder-event speciation parameter The model with lowest AIC value is marked in bold font.
Two alternative reconstruction methods were used: (a) Statistical Dispersal-Vicariance Analysis (S-DIVA) implemented in the program RASP 1.1 [ 82], and (b) dispersal-extinction-cladogenesis analysis (DEC) implemented in the software package Lagrange v2.0.1 [ 83]; see Additional file 14 for details].
