Combining the least cost path method with population genetic data and species distribution models to identify landscape connectivity during the late Quaternary in Himalayan hemlock

Abstract

Himalayan hemlock (Tsuga dumosa) experienced a recolonization event during the Quaternary period; however, the specific dispersal routes are remain unknown. Recently, the least cost path (LCP) calculation coupled with population genetic data and species distribution models has been applied to reveal the landscape connectivity. In this study, we utilized the categorical LCP method, combining species distribution of three periods (the last interglacial, the last glacial maximum, and the current period) and locality with shared chloroplast, mitochondrial, and nuclear haplotypes, to identify the possible dispersal routes of T. dumosa in the late Quaternary. Then, both a coalescent estimate of migration rates among regional groups and establishment of genetic divergence pattern were conducted. After those analyses, we found that the species generally migrated along the southern slope of Himalaya across time periods and genomic makers, and higher degree of dispersal was in the present and mtDNA haplotype. Furthermore, the direction of range shifts and strong level of gene flow also imply the existence of Himalayan dispersal path, and low area of genetic divergence pattern suggests that there are not any obvious barriers against the dispersal pathway. Above all, we inferred that a dispersal route along the Himalaya Mountains could exist, which is an important supplement for the evolutionary history of T. dumosa. Finally, we believed that this integrative genetic and geospatial method would bring new implications for the evolutionary process and conservation priority of species in the Tibetan Plateau.

Keywords: Gene flow; Quaternary; Tibetan Plateau; landscape genetics; least cost path method; phylogeography; species distribution models.

Figure 1

Localities of Tsuga dumosa and its surrounding environment.

Figure 2

Haplotype distribution based on three genetic markers. (A) Chloroplast (cp) DNA; (B) Mitochondrial (mt) DNA; (C) Nuclear (n) DNA.

Figure 3

Research framework for this study.

Figure 4

Distribution changes of Tsuga dumosa at three time intervals (A) from the last interglacial (LIG) to the last glacial maximum (LGM); (B) from the LGM to the current period; (C) from the LIG to the current period. Black, red, and blue colors represent range expansion, no change in range and range contraction, respectively. EHe represents eastern Hengduan Mountains, and W&CHe represents western and central Hengduan Mountains.

Figure 5

Potential dispersal routes of Tsuga dumosa. Data are originated from three periods (last interglacial (LIG), last glacial maximum (LGM), and present) and based on three genetic markers (chloroplast (cp) DNA, mitochondrial (mt) DNA, and nuclear (n) DNA). Arrows represent the direction of Indian monsoon.

Figure 6

Estimation of gene flow among four regional groups based on cpDNA/mtDNA haplotype sequence (A) chloroplast (cp) DNA; (B) mitochondrial (mt) DNA. Arrows represent the direction of gene flow; numbers around the arrow represent mutation‐scaled immigration rates (M) and numbers in the circle represent mutation‐scaled the effective population size (Θ).

Figure 7

Pattern of genetic divergence among populations (A) chloroplast (cp) DNA; (B) mitochondrial (mt) DNA. Areas with low genetic divergence value are as a reflection of strong gene flow among populations.