1. Case study III The continental scale: home ranges Species differ in home range Home ranges may be continuous or scattered. Scattered distributions might not allow for any gene flow. Such regional subpopulation quickly evolve into new species

2. Many species have seasonal migrations. Then summer and winter home ranges differ.

3. The UTM grid of Poland used for species distribution atlases Philaeus chrysops Regression analysis with environmental factors allows for the assessment of habitat preferences. No gene flow Relict species Introduced species Habitat specialists

4. S Alps C Balkans E France Languedoc W France Marche Venetian Romagna Tuscany Calabria P. liolepis P. lsiculus P. melidellensis MiocenePliocenePleistoceneH Case study III The continental scale: home ranges How did Podarcis muralis colonise Europe aft the glacial period? How will the species spread in the face of climate change? Podarcis muralis olocene Substitutions

5. Species distribution modelling (MaxEnt) under five different climatic scenarios

6. The map of 144 alleles from 10 loci spread across 20 sites from southern and western Europe Sites sorted according to allele richness Sites sorted according to distance from Athens The mean number of elleles per locus decreases with distance from Greece Colonisation gradient Founder effects Ordered genetic loss Relict populations Vicariant (scattered) genetic loss Popu- lations

7. Site Alleles12345678910 11111111111 21111111100 31111110000 41111100000 51111000000 61110000000 71000000000 81000000000 A perfectly nested pattern of allele loss Site Alleles12345678910 11111111111 21101111100 31111110000 40111100000 51111000000 61110000100 71000000010 81000000000 Unexpected absences Unexpected presences Rows and columns are sorted according to species richness Site Alleles12345678910 11110100000 21111000000 30111110000 40011110000 50001111100 60000111110 70000001111 80000000111 A matrix sorted to maximise the number of occurrences along the diagonale reveals the degree of allele turnover in the population Site Alleles12345678910 11010100101 21101000010 30100110000 40011110010 50010101100 60100110100 71001001101 80100000111 A random matrix A nested pattern of allele loss with unexpected absences and presences

8. ItalyW-BalkansE FranceS Luxemburg C Luxemburg N-GermanyN Luxemburg S- Belgiu m W France Distan ce from Athens 9.039.8717.2017.5418.1818.6818.6918.9118.9219.0619.1019.1119.1219.2119.2520.3520.5021.9522.2922.53 NAlleles10356556395496432513046444858493369424361 Allel es Locus323317161912131511102941522822242325 19120 0.08 3 0.05 6 0.50.1840.1250.3640.3670.6110.25 0.10.50.3390.1670.4170.0280.0380.0630.0830 18127 0.41 7 00.1750.2110.0630.4090.750.5110.60.83310.7330.91700.8850.7510.333 18132 0.16 7 0.22 2 0.650.6840.5630.8180.65110.60.450.8330.1430.8330.958100.12500.722 18118 0.04 2 0.16 7 0.1250.1580.0630.2270.3670.3890.1110.10.2500.4820.200.6670.0770.3130.3330.111 17153 0.04 2 0.11 1 0.1250.1840.1880.2730.100.0560.05 0.0560.08900.16700.6920.0630.1670.333 Eastern limeage with ordered loss of alleles along the colonisation gradient Western limeage with ordered loss of alleles along the colonisation gradient The ordered (nested) loss of alleles along putative cpolonisation gradients Intermediate situation

9. Balkans and Italy Western France Eastern and western clades do not completely overlap in allele distribution. Apparently we have two postglacial colonisation trajectories: from Spain and from the Balkans. Seriation : sorting the matrix according to reciprocal averaging. Occurrences are maximised along the matrix diagonal. S Alps C Balkans E France W France Marche Venetian Romagna Tuscany PleistoceneH olocene 1.2 my Languedoc 0.4 my Calabria Eastern Clade Italian Clade Western Clade