| Literature DB >> 30151163 |
Pedro H S Brancalion1, Giancarlo C X Oliveira2, Maria I Zucchi3, Mariana Novello3,4, Juliano van Melis1, Silvio S Zocchi5, Robin L Chazdon6,7, Ricardo R Rodrigues8.
Abstract
One of the most intriguing questions in plant ecology is which evolutionary strategy allows widely distributed species to increase their ecological range and grow in changing environmental conditions. Phenotypic plasticity and local adaptations are major processes governing species range margins, but little is known about their relative contribution for tree species distribution in tropical forest regions. We investigated the relative role of phenotypic plasticity and local adaptation in the ecological distribution of the widespread palm Euterpe edulis in the Brazilian Atlantic Forest. Genetic sampling and experiments were performed in old-growth remnants of two forest types with higher (Seasonal Semideciduous Forests vs. Submontane Rainforest) and lower biogeographic association and environmental similarities (Submontane Rainforest vs. Restinga Forest). We first assessed the molecular genetic differentiation among populations, focusing on the group of loci potentially under selection in each forest, using single-nucleotide polymorphism (SNPs) outliers. Further, we looked for potential adaptive divergence among populations in a common garden experiment and in reciprocal transplants for two plant development phases: seedling establishment and sapling growth. Analysis with outlier loci indicated that all individuals from the Semideciduous Forest formed a single group, while another group was formed by overlapping individuals from Submontane Rainforest and Restinga Forest. Molecular differentiation was corroborated by reciprocal transplants, which yielded strong evidence of local adaptations for seedling establishment in the biogeographically divergent Rainforest and Semideciduous Forest, but not for Restinga Forest and Submontane Rainforest. Phenotypic plasticity for palm seedling establishment favors range expansion to biogeographically related or recently colonized forest types, while persistence in the newly colonized ecosystem may be favored by local adaptations if climatic conditions diverge over time, reducing gene flow between populations. SNPs obtained by next-generation sequencing can help exploring adaptive genetic variation in tropical trees, which impose several challenges to the use of reciprocal transplants.Entities:
Keywords: Atlantic Forest; Euterpe edulis; SNP genotyping; common garden; ecological ranges; ecotypes; evolutionary ecology; next‐generation sequencing; reciprocal transplants
Year: 2018 PMID: 30151163 PMCID: PMC6106193 DOI: 10.1002/ece3.4248
Source DB: PubMed Journal: Ecol Evol ISSN: 2045-7758 Impact factor: 2.912
Genomic diversity parameters using 501 neutral SNPs of three Euterpe edulis populations from different forest types of the Brazilian Atlantic Forest
| Forest types |
|
|
|
| Ar |
|
|---|---|---|---|---|---|---|
| Semideciduous Forest | 19 | 897 | 0.149 (0.153–0.194) | 0.129 (0.135–0.162) | 1.58 | −0.1653 |
| Rainforest | 20 | 743 | 0.176 (0.137–0.184) | 0.134 (0.113–0.142) | 1.36 | −0.2537 |
|
| 16 | 706 | 0.160 (0.129–0.175) | 0.116 (0.101–0.131) | 1.34 | −0.3021 |
Number of individuals (N), mean number of alleles (A), observed heterozygosity (H o), expected heterozygosity (H E), allelic richness (Ar), and inbreeding coefficient (F IS). The values in parentheses correspond to the upper and lower limits of the confidence interval. * indicates significantly higher values.
Population pairwise FST values (lower triangle) and 95% confidence intervals (upper triangle) for 501 neutral SNP loci of three Euterpe edulis populations from different forest types of the Brazilian Atlantic Forest (Global F ST = 0.064)
| Forest types | Semideciduous Forest | Rainforest |
|
|---|---|---|---|
| Semideciduous Forest | – | 0.057–0.108 | 0.059–0.102 |
| Submontane Rainforest | 0.082 | – | −0.001 to 0.023 |
|
| 0.080 | 0.011 | ‐ |
Genetic differentiation within and among three Euterpe edulis populations from different forest types of the Brazilian Atlantic Forest according to analysis of molecular variance (AMOVA)
| Source of variation |
| Sum of squares | Coefficient of variation | Percentage of variation (%) | θ statistics |
|
|---|---|---|---|---|---|---|
| Among populations | 2 | 2197.3 | 47.6 | 17.27 | θ = 0.173 | <0.0001 |
| Within populations | 52 | 11875.1 | 228.3 | 82.72 |
Figure 1Genetic structuring using 501 neutral and 84 outlier SNPs of Euterpe edulis populations from different forest types of the Brazilian Atlantic Forest: scatter plot of clusters of individuals and density plots of individuals using neutral loci (a and b, respectively) and outlier loci (c and d, respectively)
Figure 2Venn diagram indicating the common outlier loci of Euterpe edulis among forest types of the Brazilian Atlantic Forest
Selection of models according to the Akaike information criterion (AIC) for investigating the effect of seed provenance and site of transplant on seedling and sapling adaptive traits assessed in reciprocal transplants with Euterpe edulis in different forest types of the Brazilian Atlantic Forest
| Forest types | Adaptive trait | ΔAIC | ||||
|---|---|---|---|---|---|---|
| Seed provenance | Site of transplant | Both | With interaction | Seed mass inclusion | ||
| Semideciduous Forest versus Rainforest | Seedling emergence | 100.53 | 28.26 | 19.30 |
| |
| Seedling mortality | 267.34 | 5.39 | 1.19 |
| ||
| Seedling density | 33.88 | 39.37 | 35.77 |
| ||
| Seedling aboveground dry mass | 28.15 | 38.13 | 3.81 |
| Yes | |
| 49.20 | 53.21 | 24.91 | 22.31 | No | ||
| Sapling survival |
| 1.00 | 1.91 | 0.21 | ||
| Sapling root–shoot dry mass ratio | 5.13 | 8.34 |
| 1.78 | Yes | |
| 5.79 | 8.45 | 0.45 | 2.18 | No | ||
| Sapling total dry mass | 7.71 |
| 1.59 | 3.57 | Yes | |
| 11.57 | 3.54 | 5.21 | 7.20 | No | ||
| Rainforest versus Restinga Forest | Seedling emergence |
| 3.17 | 1.27 | 3.06 | |
| Seedling mortality | 12.97 |
| 1.42 | 2.36 | ||
| Seedling density | 13.70 | 6.99 |
| 1.56 | ||
| Seedling aboveground dry mass | 79.24 | 85.34 |
| 1.67 | Yes | |
| 103.35 | 105.58 | 25.66 | 27.27 | No | ||
| Sapling survival |
| 1.00 | 1.91 | 0.21 | ||
| Sapling root–shoot dry mass ratio | 9.44 | 2.47 | 1.68 | 3.54 | Yes | |
| 8.02 | 0.87 |
| 1.84 | No | ||
| Sapling total dry mass | 3.79 | 11.54 | 1.38 | 1.28 | Yes | |
| 2.20 | 9.93 |
| 0.06 | No | ||
Bold letters indicate models with ΔAIC < 2, or when more than one model has ΔAIC < 2, bold letters indicate the model with the lowest ΔAIC, indicating the most parsimonious model. aInteraction: considers that the effect of one predictor on the response variable is different at different levels of the other predictor, that is, the influence of seed provenance is different if seeds are in a site or another. bSeed mass inclusion: inclusion (yes) or not (no) of seed mass in the model depending on the significant effect of this covariable in the response variable (adaptive trait).
Figure 3Paired comparisons of the influence of seed provenance (RnF: Rainforest; SdF: Semideciduous Forest) on adaptive traits in reciprocal transplants established with Euterpe edulis within these forest types in the Brazilian Atlantic Forest. Mann–Whitney test was used for counting data and t test for the log‐transformed data. *p < 0.05; **p < 0.01; ***p < 0.0001
Figure 4Paired comparisons of the influence of seed provenance (RnF: Rainforest; RtF: Restinga Forest) on adaptive traits in reciprocal transplants established with Euterpe edulis within these forest types in the Brazilian Atlantic Forest. Mann–Whitney test was used for counting data and t‐test for the log‐transformed data. *p < 0.05; **p < 0.01; ***p < 0.0001