Climatic drivers of leaf traits and genetic divergence in the tree Annona crassiflora: a broad spatial survey in the Brazilian savannas
The Cerrado is the largest South American savanna and encompasses substantial species diversity and environmental variation. Nevertheless, little is known regarding the influence of the environment on population divergence of Cerrado species. Here, we searched for climatic drivers of genetic (nuclea...
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Published in | Global change biology Vol. 22; no. 11; pp. 3789 - 3803 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
England
Blackwell Publishing Ltd
01.11.2016
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Subjects | |
Online Access | Get full text |
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Summary: | The Cerrado is the largest South American savanna and encompasses substantial species diversity and environmental variation. Nevertheless, little is known regarding the influence of the environment on population divergence of Cerrado species. Here, we searched for climatic drivers of genetic (nuclear microsatellites) and leaf trait divergence in Annona crassiflora, a widespread tree in the Cerrado. The sampling encompassed all phytogeographic provinces of the continuous area of the Cerrado and included 397 individuals belonging to 21 populations. Populations showed substantial genetic and leaf trait divergence across the species' range. Our data revealed three spatially defined genetic groups (eastern, western and southern) and two morphologically distinct groups (eastern and western only). The east‐west split in both the morphological and genetic data closely mirrors previously described phylogeographic patterns of Cerrado species. Generalized linear mixed effects models and multiple regression analyses revealed several climatic factors associated with both genetic and leaf trait divergence among populations of A. crassiflora. Isolation by environment (IBE) was mainly due to temperature seasonality and precipitation of the warmest quarter. Populations that experienced lower precipitation summers and hotter winters had heavier leaves and lower specific leaf area. The southwestern area of the Cerrado had the highest genetic diversity of A. crassiflora, suggesting that this region may have been climatically stable. Overall, we demonstrate that a combination of current climate and past climatic changes have shaped the population divergence and spatial structure of A. crassiflora. However, the genetic structure of A. crassiflora reflects the biogeographic history of the species more strongly than leaf traits, which are more related to current climate. |
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Bibliography: | Fundação de Amparo à Pesquisa do Estado de Minas Gerais - No. APQ-00671-11 Coordenacão de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) ArticleID:GCB13312 Spanish Ministry for Economy and Competitiveness - No. CGL2012-40129-C02-02 Spanish Ministry for Science and Innovation - No. RYC2009-04537 Table S1. List of vouchers of Annona crassiflora deposited in the Herbarium of the Departamento de Botânica da Universidade Federal de Minas Gerais (BHCB), Brazil. Table S2. Characteristics of the microsatellite markers tested in Annona crassiflora. Table S3. Proportion of variance explained by the first three principal components (PC) of the climatic Bioclim variables (downloaded at 5 arc-min resolution) in each set of environmental variables (ENV1, ENV2, ENV3) used in the GLMM modelling. Loading values of −0.1 < X < 0.1 are not shown. ENV1 = 19 Woldclim variables (BIO1-19), ENV2 = BIO8, BIO10, BIO16, BO18 (summer), ENV3 = BIO9, BIO11, BIO17, BIO19 (winter). Table S4. Null allele frequency by locus estimated with Brookfield 1 method in Annona crassiflora populations. Table S5. Results of the amova for genetic data and anova for morphological data (metamer) for each of the three genetic groups of Annona crassiflora defined by the Bayesian structure analysis. Table S6. Principal component analysis for 14 metamer traits in Annona crassiflora. Loading values of −0.1 < X < 0.1 are not shown. Table S7. Generalized linear mixed effect modelling selection results for morphological traits in Annona crassiflora including all populations together, and genetic groups defined by Bayesian structure analysis, separately. Models include as predictor variables geographic (GEO) and environmental distance (ENV1, ENV2 and ENV3) among populations, and differences in population assignment with phytogeographic provinces (PHY; only used in the analysis of all populations together). Table S8. Pearson pairwise correlation coefficients between geographic and climatic variables across the sampled areas. Coefficients > 0.5 are highlighted in bold. Lon, longitude; Lat, latitude; Alt, altitude, and B, Bioclimatic variable. Fig. S1. Population structure analysis of Annona crassiflora using tess. (A) Results postprocessed with the Evanno approach; ΔK values for each K. (B) Deviance information criterion (DIC) plotted against K. Fig. S2. Mean values and standard errors of the first principal component (PC1) from the PCA of morphological metamer data in relation to longitude of populations of Annona crassiflora. Results of a Pearson's correlation test of the mean values of PC1 against longitude are reported in the graphic. Graphical symbols: (▲) single population-FOR; (●) east group and (○) west group. Fig. S3. Mean values of the first principal component from the PCA of (summer, ENV2) climate data, in relation to latitude (A) and longitude (B) for each Annona crassiflora population. Results of Pearson's correlation tests of mean ENV2 values against latitude and longitude are reported in the graphic. Graphical symbols: (●) southern group, (Δ) eastern group and (○) western group. istex:4E55535F4020DDCF15B8523B017D63A66802B319 ark:/67375/WNG-N7SCM1KP-G Conselho Nacional de Desenvolvimento Científico e Tecnológico - No. 475331/2012-5 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 1354-1013 1365-2486 1365-2486 |
DOI: | 10.1111/gcb.13312 |