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. 2021 May 18;118(20):e2022302118.
doi: 10.1073/pnas.2022302118.

Phylogenomic and ecological analyses reveal the spatiotemporal evolution of global pines

Affiliations

Phylogenomic and ecological analyses reveal the spatiotemporal evolution of global pines

Wei-Tao Jin et al. Proc Natl Acad Sci U S A. .

Abstract

How coniferous forests evolved in the Northern Hemisphere remains largely unknown. Unlike most groups of organisms that generally follow a latitudinal diversity gradient, most conifer species in the Northern Hemisphere are distributed in mountainous areas at middle latitudes. It is of great interest to know whether the midlatitude region has been an evolutionary cradle or museum for conifers and how evolutionary and ecological factors have driven their spatiotemporal evolution. Here, we investigated the macroevolution of Pinus, the largest conifer genus and characteristic of northern temperate coniferous forests, based on nearly complete species sampling. Using 1,662 genes from transcriptome sequences, we reconstructed a robust species phylogeny and reestimated divergence times of global pines. We found that ∼90% of extant pine species originated in the Miocene in sharp contrast to the ancient origin of Pinus, indicating a Neogene rediversification. Surprisingly, species at middle latitudes are much older than those at other latitudes. This finding, coupled with net diversification rate analysis, indicates that the midlatitude region has provided an evolutionary museum for global pines. Analyses of 31 environmental variables, together with a comparison of evolutionary rates of niche and phenotypic traits with a net diversification rate, found that topography played a primary role in pine diversification, and the aridity index was decisive for the niche rate shift. Moreover, fire has forced diversification and adaptive evolution of Pinus Our study highlights the importance of integrating phylogenomic and ecological approaches to address evolution of biological groups at the global scale.

Keywords: Pinus; evolutionary museum; fire adaptation; phylogenomics; spatiotemporal evolution.

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Conflict of interest statement

The authors declare no competing interest.

Figures

Fig. 1.
Fig. 1.
Phylogeny of Pinus. (A) ML tree inferred from the concatenated CDS alignment of 1,662 OGs. The numbers attached to the branches show the UFBoot supports (* for 100%). The 13 subsections of Pinus are listed with some abbreviations, that is, Co. (Contortae), At. (Attenuatae), Sa. (Sabinianae), K. (Krempfianae), Ge. (Gerardianae), Ba. (Balfourianae), and N. (Nelsoniae). Each species is shown in color corresponding to its geographic distribution shown in A. The letters in brackets following species names correspond to the pine images on the right (BY).
Fig. 2.
Fig. 2.
Historical biogeography of Pinus. (A) Ancestral range estimation using BioGeoBEARS with the DIVALIKE+J model. Divergence times were estimated using MCMCTree based on the concatenated CDS dataset (SI Appendix, Fig. S5). Horizontal bars at nodes indicate 95% credible intervals of the divergence time estimates. Pie charts at the nodes indicate relative probabilities of all possible geographic ranges. (B) Net diversification rate (green) and evolutionary rates of niche (red) and phenotypic traits (blue) estimated by BAMM, with color density shading to denote confidence on evolutionary rates through time. The unit of net diversification is species/Ma, and niche and phenotypic rates are unitless. Red numbers along branches represent major ecological niche shifts, and blue numbers along branches represent major phenotype shifts. The gray curve in the background shows the fluctuation of global temperature using the dataset from (94). Co., Contortae; At., Attenuatae; Sa., Sabinianae; K., Krempfianae; Ge., Gerardianae; Ba., Balfourianae; N., Nelsoniae; Pal., Paleocene; Eoc., Eocene; Oli., Oligocene; Mio., Miocene; P., Pliocene; Q., Quaternary; and MCAC represents Mexico, Central America, and Caribbean.
Fig. 3.
Fig. 3.
The global patterns of species diversity (A) and mean divergence times (B) of pines plotted in grid cells of 100 km × 100 km.
Fig. 4.
Fig. 4.
Determinants of pine species diversity. (AI) Relationships between predictor variables and species richness based on the global multipredictor model across grid cells of 100 km × 100 km. (JR) The relative importance of four types of variables (climate, topography, soil, and landcover) in explaining species richness based on global, two subgenera, and six regional analyses. The bar plots were implemented in the “ggplot2” package (97) using R (v.3.6.2) (84). The positive and negative correlations are indicated as + and −, respectively. MCAC represents Mexico, Central America, and Caribbean. Abbreviations and explanations of predictor variables refer to SI Appendix, Table S10.

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