Dynamics of genetic diversity and population structure of Eucalyptus urophylla in Indonesia Islands using SNP Data

doi:10.21203/rs.3.rs-5304039/v1

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Dynamics of genetic diversity and population structure of Eucalyptus urophylla in Indonesia Islands using SNP Data

https://doi.org/10.21203/rs.3.rs-5304039/v1

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Eucalyptus urophylla is one of the most economically important species in the world due to its wood quality and tolerance to water stress. Understanding the genetic composition at the population level of this species is essential for the sustainable and efficient management and utilization of its genetic resources. This study describes the genetic diversity and population structure of E. urophylla from progenies collected on four islands in Indonesia (Wetar, Timor, Lembata, and Adonara) and conserved ex situ in Brazil. A total of 692 open-pollinated adult individuals from 17 populations were genotyped using 5,374 SNP markers. Analyses of diversity (observed heterozygosity, \(\:{H}_{o}\), and expected heterozygosity, \(\:{H}_{e}\)), population hierarchical levels (\(\:{F}_{ST},\:{F}_{IT},\:\text{a}\text{n}\text{d}\:{F}_{IS}\)), effective population size (\(\:{N}_{e}\)), ancestry, PCA, and dendrogram Neighbor-Joining were conducted. The populations showed greater genetic differentiation at the island level (\(\:{F}_{ST}\) ≤0.055). The estimates of genetic diversity were moderate, with \(\:{H}_{o}\) ranging from 0.39 to 0.47, being higher than \(\:{H}_{e}\), which ranged from 0.30 to 0.36. The sublevels \(\:{F}_{IS}\) and \(\:\:{F}_{IT}\) showed negative estimates, indicating a high proportion of heterozygous individuals in the populations and a negative intraclass correlation, showing that alleles were more related among populations than within them. The populations exhibited low genetic differentiation among themselves (\(\:{F}_{ST}\)=0.05). The analyses showed a clear and significant separation of two genetic clusters. The observed genetic diversity and structure ensure that ex situ conservation can be effectively carried out, preserving and exploring the genetic variability found in natural populations.

Conservation genetics

Forest genetic resources

Genetic differentiation

Genetic investigation

Wright's F-statistics

Eucalyptus is the most widely planted forest genus in the world, covering an area of over 25 million hectares (FAO 2021; Martins et al. 2022). We focus on the description of the genetic diversity of the species Eucalyptus urophylla S.T. Blake, S.T. Blake, widely cultivated in many tropical regions. This species has its center of origin on several islands in Indonesia, such as Wetar, Pantar, Alor, Adonara, Lembata/Lomblem, Flores, and Timor (Pryor et al. 1995).

These islands are located in the Wallacea region, a global biodiversity hotspot (Payn et al. 2007). The island substructure has likely contributed to the formation of several E. urophylla populations, leading to extensive genetic variability and high polymorphism (Luz 1997). This genetic diversity has been shaped by periodic climatic changes during the Pleistocene (Voris 2000; Payn et al. 2007), as well as by factors such as reproductive biology, gene flow (pollen and seed), natural hybridization, introgression events, and geological factors (Dvorak et al. 2008, Luz 1997).

Geographic location and spatial distribution are key drivers of genetic diversity, influencing adaptation and resilience to evolutionary pressures (Frankham et al. 2010). For E. urophylla, which occurs at altitudes from 0 to 3,000 m, SNP markers offer a molecular-level assessment of the causes and patterns of genetic variability across populations (Savolainen and Pyhäjärvi 2007). E. urophylla's economic importance in forestry has led to studies on its genetic diversity using molecular (isoenzymatic and microsatellite markers) (House and Bell 1994; Payn et al. 2007, 2008; Barros et al. 2022) and phenotypic data (Dvorak et al. 2008; Hodge and Dvorak 2015). These studies have separated the population on Wetar from the others (Pantar, Alor, Adonara, Lembata/Lomblem, Flores, and Timor) based on seasonality (Dvorak et al. 2007) and morphological differences (Doran et al. 1995; Pryor et al. 1995).

There have been concerns about the conservation of the genetic heritage of E. urophylla (Luz 1997). These concerns have intensified over the years due to the effects of climate change and the restricted access to populations in their center of origin, resulting from both political restrictions and agricultural expansion that has led to forest loss (Pepe et al. 2004).

For E. urophylla, the management of base populations through conservation programs is aligned with the objectives of the genetic improvement program (Dvorak et al. 2008). Since genetic gain is directly related to the level of genetic diversity, it is essential to characterize the genetic variability both within and among the populations available for improvement (Barros et al. 2022).

The preservation of the gene pool, whether from introduced genetic material of different origins or from recombined populations adapted to the local environment, is essential for the development of healthy forests and for maintaining competitiveness in the constantly changing global market (Dvorak et al. 2008).

The only study investigating the genetic diversity of E. urophylla introduced in Brazil more than 25 years ago was conducted by Barros et al. (2022), using microsatellite markers. However, the number of individuals representing the native populations from the studied islands was limited to 25, which may underestimate the actual diversity present on the islands of Adonara, Lomblen, Alor, and Pantar.

Aiming to fill existing gaps, contribute to the advancement of population genetics research for the Eucalyptus genus, and improve the genetic breeding of E. urophylla, our study is the first to characterize the genetic diversity and population structure of E. urophylla populations using SNP markers, which are generally more numerous and distributed throughout the genome, providing a more detailed view of genetic variability.

We used material from progenies collected from mother trees originating from four islands in Indonesia (Timor, Wetar, Lembata, and Adonara) to determine the level of genetic differentiation among and within the islands, identify phylogenetic relationships, and answer the following questions: (1) What is the degree of differentiation and genetic variability between the populations located on the westernmost islands (Timor and Wetar) and the easternmost islands (Lembata and Adonara)? (2) Do the populations of Wetar exhibit lower genetic variability due to geographic isolation compared to the other populations? (3) Is there evidence of hybridization and introgression in these populations? (4) Do the populations represent the natural genetic diversity found, ensuring their proper ex situ conservation? (5) What are the implications of population genetic structure for the conservation management of E. urophylla?

Plant Material

The studied populations consist of four E. urophylla seedling seed orchards (SSOs) located in the municipality of Selvíria, Mato Grosso do Sul, Brazil (20°24'55.74"S e 51°47'22.13"O). The region has a tropical climate with a dry season in winter (classified as Aw according to Köppen), at an altitude of 393 meters (m), with an average annual temperature of 24.8°C and an average precipitation of 1,309 mm (Fig. 1). The SSOs were established in 2006 from open-pollinated seeds collected in areas of natural occurrence of the species in Indonesia, specifically from 17 populations distributed across the islands of Wetar, Adonara, Lembata (also called Lomblen), and Timor (Fig. 1 and Table 1).

Table 1

Geographical coordinates, average precipitation, and conservation status of 17 populations of *Eucalyptus urophylla* located on the islands of Adonara, Wetar, Lembata, and Timor
Island	Populations	Lat (S)	Lon (E)	Alt			Prec	Conservation Status	N
Island	Populations	Lat (S)	Lon (E)	max	min	mean	Prec	Conservation Status	N
Adonara	Dua Muda	08°20'	123°15'	733	733	733	1348	V	52
	Gonehama	08°20'	123°16'	687	687	687	1452	V	38
	Kawella	08°21'	123°04'	600	600	600	1398	CE	60
	Lamahela	08°22'	123°15'	856	856	856	1452	V	54
	Lamalota Barat	08°21'	123°15'	866	866	866	1376	V	17
	Watololong	08°19'	123°15'	630	800	715	1292	V	31
Wetar	Alasannaru	07° 51′	126°24′	580	612	596	1172	LR	44
	Elun Kripas	07°51'	126°17'	715	750	733	1136	LR	44
	Ketur*	07°52'	126°27'	432	498	465	1116	LR	52
	Nakana Ulam	07°52'	126°21'	680	750	715	1232	LR	44
	Nesunhuhun	07°52'	126°15'	600	642	621	1136	LR	38
	Puaanan*	07°51'	126°27'	453	516	485	1116	LR	56
	Remamea*	07°52'	126°26'	409	542	476	1116	LR	72
	Talianan*	07°53'	126°28'	483	559	521	1018	LR	39
Lembata	Bunga Muda^B	08°16'	123°32'	600	700	650	1440	V	16
Lembata	Ille Kerbau^B	08°29'	123°29'	730	750	740	1421	V	23
Timor	Bonmuti^B	09°31'	124°16'	1370	1370	1370	1692	LR	12
LR - low risk, V - vulnerable, CE - critically endangered, according to the standards of the International Union for Conservation of Nature and Natural Resources (IUCN) (Farjon and Page, 1999; Hodge and Dvorak, 2015); Occurs together with Eucalyptus alba*; ^B seed bulk from multiple progenies.

The seeds were obtained through a cooperative project, with seed lots formed from collection expeditions conducted between 1996 and 2003 by Camcore (Cooperative Program in Forest Genetics and Tree Breeding) (Pepe et al. 2004). Established as provenance and progeny test (PPTs), the experimental design used was a randomized complete block design with eight blocks, each containing linear plots of six plants and three or four (depending on the experiment) operational clones as controls. The number of progenies and bulks per test ranged from 37 to 58 (Table S1). The area occupied by the four orchards was 8.60 hectares. To advance the genetic improvement program of the population, the PPTs underwent a 90% thinning at six years of age, transforming them into seedling seed orchards (SSOs), where only the origins and individuals with the best performance were retained. These included straight trunks, high values for mean annual increment (MAI, m³ ha^− 1 year^− 1), and absence of susceptibility to pests and diseases.

At 18 years of age, 692 remaining individuals from the four orchards were genotyped to investigate the genetic diversity of this wild material.

DNA Extraction, Genotyping, and SNP Quality Control

Leaf tissue was individually collected from the 692 individuals for DNA extraction, performed using the CTAB (Cetyltrimethylammonium Bromide) method according to Doyle and Doyle (1987). The integrity of the DNA was confirmed by electrophoresis on a 1% agarose gel, while quantification was performed using a Nanodrop spectrophotometer (Thermo Fisher, Waltham, MA, USA). Genotyping was conducted by sequencing a panel containing approximately 5000 SNPs from the genome, a subset of the high-density Illumina chip, the EUChip60K SNPchip Infinium developed for Eucalyptus species (Silva-Junior et al. 2015).

After genotyping, a total of 5,374 SNP markers were available for analysis. The molecular sequences in the form of biallelic nucleotide bases were numerically recoded as 0, 1, and 2. The homozygous individual with two copies of the minor allele was coded as 2, the heterozygote as 1, and the homozygote with no copies of the minor allele as 0. Prior to analysis, SNP markers underwent quality control, with the following criteria: Read Depth > 40, removal of monomorphic markers and those not in Hardy-Weinberg Equilibrium (HWE), call rate, callrate < 95% for SNPs and MAF ≥ 2% (Minor Allele Frequency). Both the recoding and quality control were performed using the ASRgenomics package (Gezan et al. 2022).

After data filtering, linkage disequilibrium (LD) between each SNP pair was verified using the TASSEL software (Bradbury et al. 2007). SNPs in linkage disequilibrium and with \(\:{r}^{²}\) values > 0.3, were removed to ensure the use of only independent markers and to avoid redundancy and distortions in the analyses. After filtering and quality control, the final dataset consisted of the same 692 individuals and 2,169 SNPs. The rate of missing data per individual remained below 3.70% for all samples.

Diversity Parameters, Genetic Structure, and Effective Population Size

The observed (\(\:{H}_{o}\)) and expected (\(\:{H}_{e}\)) heterozygosities were estimated for each SNP, as well as the population hierarchical levels, which were estimated using Wright's F-statistics (Wright 1931; Weir and Cockerham 1984). The analyses were performed using the adegenet v. 2.1.10 package (Jombart and Ahmed 2011) and hierfstat v 0.5.7 (Goudet and Jombart 2022).

Pairwise \(\:{F}_{ST}\) values were estimated to assess allelic differences between the islands, as well as between populations within the islands of Wetar, Adonara, and Lembata, which had eight, six, and two populations represented in the sampling, respectively. Pairwise \(\:{F}_{ST}\) values, as well as global \(\:{F}_{ST}\), were calculated using the Weir and Cockerham (1984) method. From the global \(\:{F}_{ST}\) and \(\:{F}_{IS}\) values, the relation between the three levels of differentiation was used to obtain the total heterozygosity (\(\:{F}_{IT}\)), given by the formula: \(\:{1-F}_{IT}=\left(1-{F}_{IS}\right)(1-{F}_{ST})\).

The genetic structure of the populations was also analyzed by estimating the ancestry proportion of each individual using the sparse non-negative matrix factorization (sNMF) algorithm implemented in the LEA package (Frichot et al. 2014; Frichot and François 2015). The algorithm allows for the estimation of ancestry coefficients from large genotypic matrices and determines the number of ancestral populations (\(\:K\)), assuming that the data result from the admixture of \(\:K\) ancestral populations. The sNMF algorithms are flexible and robust to deviations from population genetic model assumptions and are suitable for addressing inbreeding and outbreeding in ancestral populations, as well as complex patterns of population structure and relatedness, as expected in the present context.

Values of \(\:K\) ranging from 1 to 10 were considered, and 100 independent runs were performed for each \(\:K\) value. The value of \(\:K\) that best explained the data was determined based on cross-entropy errors and cross-validation (Frichot et al. 2014), with the one having the lowest cross-entropy value being selected. The ancestry coefficients for each individual were visualized in bar plots, ordered by island, and within each island, by population (Frichot et al. 2014; Frichot and François 2015). The number of ancestral populations per island was visualized in pie charts using the mapmixture package (Jenkins 2024) in R.

Principal component analysis (PCA) and dendrograms were used to visualize genetic groups, based on the \(\:G\) matrix estimated using the ASRgenomics package (Gezan et al. 2024), following the method of Yang et al. (2010). PCA was performed using the factoextra package version 1.0.7 (Kassambara and Mundt 2020), representing the distances between individuals in a Cartesian plot with PC1 and PC2 axes.

The dendrogram was constructed to analyze genetic relationships using the Neighbor-Joining method (Saitou and Nei 1987), based on pairwise \(\:{F}_{ST}\) distances between the islands using the poppr package version 2.9.4 (Kamvar et al. 2015) and ape package version 5.7-1 (Paradis and Schliep, 2019), with 10,000 bootstrap interactions and a confidence level of 70%. All analyses were performed in R software (R Core Team 2023).

The effective population size (\(\:{N}_{e}\)) per island was estimated using the Estimator v2.1 software (Do et al., 2014).

Genetic Diversity Parameters and Effective Population Size

The observed (\(\:{H}_{o}\)) and expected (\(\:{H}_{e}\)) heterozygosities ranged from 0.39 to 0.47, and from 0.30 to 0.36, respectively, with the lowest values observed on Wetar Island (Table 2).

Table 2

Genetic diversity parameters, inbreeding coefficient (\(\:{F}_{IS}\)), number of private alleles (P), and effective population size (\(\:{N}_{e})\) of *Eucalyptus urophylla* populations collected from the islands of Adonara, Wetar, Lembata, and Timor in Indonesia
Island	\(\:n\)	S	\(\:{H}_{o}\)	\(\:{H}_{e}\)	\(\:{F}_{IS}\)	\(\:P\)	\(\:{N}_{e}\)
Adonara	252	0.84(± 0.03)	0.46(± 0.02)	0.36(± 0.02)	-0.24(± 0.11)	12	37.4(± 0.2)
Wetar	392	0.89(± 0.02)	0.39(± 0,05)	0.30(0 ± .04)	-0.20(± 0.11)	13	213.2(± 1.3)
Lembata	39	0.91(± 0.04)	0.46(± 0.02)	0.35(± 0.01)	-0.24(± 0.12)	-	54.6 (± 0.8)
Timor	12	0.83(± 0.04)	0.47(± 0.03)	0.36(± 0.02)	-0.22(± 0.13)	-	3.1(± 1.0)
\(\:n\) = number of individuals; S: Survival at 6 years of age; \(\:{H}_{o}\): Observed heterozygosity; \(\:{H}_{e}\):Expected heterozygosity; F_IS= Inbreeding coefficient. P: Number of private alleles; N_e=Effective population size.

The inbreeding coefficient (\(\:{F}_{IS}\)) ranged from − 0.24 to -0.20, and the effective population size varied from 3.1 (Timor) to 213.2 (Wetar) for the four analyzed islands (Table 2). Private SNPs per population sample were also observed for the islands of Adonara and Wetar (Table 3).

Table 3

Private SNPs found on the islands of Wetar and Adonara
Island	N	Private SNPs
Adonara	12	EuBR01s30341166, EuBR01s36713156, EuBR02s24834756, EuBR02s44144952, EuBR02s44358442, EuBR02s44918466, EuBR02s62213350, EuBR03s40398524, EuBR06s46168115, EuBR08s14022725, EuBR10s1370596, EuBR10s38460129
Wetar	13	EuBR02s7448428, EuBR02s24611822, EuBR02s33355276, EuBR04s58364, EuBR04s17635885, EuBR06s10044285, EuBR07s44276320, EuBR07s45517733, EuBR07s51502277, EuBR08s1138949, EuBR08s24989346, EuBR10s27443527, EuBR11s36737426
N: Total number of SNPs

Population Genetic Structure

The global genetic differentiation (\(\:{F}_{ST}\)) among the 17 populations of E. urophylla was 0.052. To understand the hierarchical levels of the populations, the analyses will be presented at two levels: (i) macro, where each island is considered a population, and (ii) micro, where populations (origins) within each island are considered.

At the island level (Fig. 2A), the greatest differences in allele frequencies were observed for Wetar Island. The pairwise \(\:{F}_{ST}\) values between islands (Fig. 2A) and within islands (among populations) (Figs. 2B and 2C) ranged from 0.01 (Adonara vs. Lembata) to 0.05 (Wetar vs. Lembata and Wetar vs. Adonara), and from 0.005 (Wetar: Puaanan vs. Remamea) to 0.037 (Adonara: Kawela vs. Gonehama), respectively.

Analyzing the populations within each island, the greatest allelic differences (\(\:{F}_{ST}\)>0.015) were observed among the populations of Gonehama (Go), Dua Muda (DM), and Kawela (Ka) from Adonara (\(\:{F}_{ST}\) ranging from 0.016 to 0.037), as well as between the two populations of Lembata (Bunga Muda vs. Iller Kerbau, \(\:{F}_{ST}\) =0.017), compared to the other populations (Figs. 2B and 2C; Table S2). The global inbreeding coefficient (\(\:{F}_{IT}\)) was lower at the island level ( \(\:{F}_{IT}\) = -0.22) and not for populations within islands (\(\:{F}_{IT-Wetar}\)=-0.27; \(\:{F}_{IT-Adonara}\) = -0.30; \(\:{F}_{IT-Lembata}\) = -0.29). Given the negative \(\:{F}_{IS}\) values, we found that the observed number of heterozygotes was higher than expected, both at the island level (ranging from \(\:{F}_{IS-Wetar}\) -0.20 a \(\:{F}_{IS-Adonara}\) -0.25) (Fig. 2A and Table 2) and among populations within the islands, with values ranging from -0.21 (Puaanan, Alasannaru, Nakana Ulan, and Remamea, Wetar Island) to -0.27 (Watololong, Kawela, and Gonehama, Adonara Island) (Figs. 2B and 2C).

The most likely optimal number of ancestral populations for the 17 populations, determined based on cross-validation error rates, was \(\:K\)=3 (Fig. 3A), which is lower than the number of islands evaluated.

At the island level, Wetar showed greater genetic differentiation compared to the western islands (Lembata and Adonara), as evidenced by the \(\:{F}_{ST}\) values (Fig. 2A) give confidence intervals, being genetically closer to Timor, with a more homogeneous genetic composition predominantly represented by Cluster III (Fig. 3B). Lembata and Adonara have similar proportions of the three ancestral populations, with a low \(\:{F}_{ST}\) value of 0.01, indicating low genetic differentiation.

Within each island, the eight populations of Wetar showed homogeneous genetic compositions, consistent with the pairwise \(\:{F}_{ST}\) values (Figura 2D). In Lembata and Adonara, except for Kawela, which demonstrated greater homogeneity in terms of ancestry and closer relatedness among individuals (Figs. 3D and C, respectively), heterogeneity in individual ancestry coefficients was observed. This pattern was also seen in the Bonmuti population on Timor (Figs. 3D and C), corresponding to the highest values of genetic diversity (\(\:{H}_{o\:}\)and \(\:{H}_{e\:}\)) found on these islands, as well as the elevated heterozygosity values in the populations (\(\:{F}_{IS\:}\)) (Fig. 2).

The \(\:K\)=3 structure was also confirmed by the PCA analysis, revealing three distinct genetic groups among the 17 wild populations of E. urophylla (Fig. 4).

The PCA analysis is consistent with the \(\:{F}_{ST\:}\) estimates and ancestry analysis, highlighting the distinction of individuals into three groups: two formed by the easternmost islands of Indonesia (Wetar and Timor) and one formed by the western islands (Adonara and Lembata) (Figs. 4B and 4C). The individuals from Kawela were more isolated from the other sampled populations on Adonara Island (Fig. 4B), which was also observed in the admixture plot (Figs. 3C and 3D). On Wetar Island, a small number of individuals from the Remamea and Puaanan populations were also isolated (Figs. 4A and 4B).

The phylogenetic relationships observed among the islands confirm the \(\:K\)=3 structure (Fig. 5A). Adonara is genetically more distant from Lembata and Wetar, which, due to their proximity, are more genetically related (Fig. 5A). Figure 5B shows the distribution of bark types among individuals by island, with Adonara presenting the greatest phenotypic diversity in bark, while Lembata and Wetar exhibit a predominance of similar bark types ("Brown_fibrous" and "Red_fibrous") (Fig. 5B). This phenotypic variation observed in bark type may indicate possible hybridization between E. urophylla and E. alba.

The wide natural distribution of E. urophylla (from 0 to 3,000 m in altitude) and considering altitude as one of the main sources of climatic and ecotypic variation for the species (Silva et al. 2023) justify the high values of genetic diversity observed (\(\:{H}_{o}\) and \(\:{H}_{e}\)). Although the observed genetic diversity indices were higher than the average values reported for the species, they are consistent with the results of Yang et al. (2020), who reported \(\:{H}_{o}\) values ranging from 0.30 to 0.38 and \(\:{H}_{e}\) values from 0.27 to 0.35, using SNPs.

This diversity can be explained by several factors, including artificial selection in the orchards, which reduced the orchard populations by 90%, altering their genetic composition in a targeted manner (Frankham et al. 2010), the structure, the larger number of individuals sampled per island (Table 1), and the ecological diversity of the collection sites, including islands with volcanic activities. Although the high heterozygosity observed on Adonara Island may be attributed by artificial selection (90% thinning), the low \(\:{N}_{e}\) value (37.4) could indicate reduced genetic diversity in regenerating individuals, particularly in areas near Mount Boleng (Hodge and Dvorak 2015). Of the six populations evaluated, five (Dua Muda, Gonehama, Lamahela, Watololong, and Lamalota) are located only 2.5 km from the volcano, which has a recent history of eruptions (Hodge and Dvorak 2015). Populations in areas of recent volcanic activity may possibly be facing greater selective pressure and limited regeneration, which contributes to the reduced \(\:{N}_{e}\:\)value observed.

A direct comparison of SNP data with microsatellites is difficult because of the different mutation rates. Studies that used microsatellites, such as Tripiana et al. (2007), Payn et al. (2008), Lu et al. (2018), Pupin et al. (2019), and Barros et al. (2022), reported higher heterozygosity values, indicating that E. urophylla consistently exhibits high genetic diversity. Additionally, Payn et al. (2007) reported high haplotypic diversity (\(\:h\)), ranging from 0 (Flores and Lembata) to 0.88 (Wetar), which further supports the high genetic variability of the populations. Despite the low genetic differentiation both between islands (0 < \(\:{F}_{ST}\) ≤ 0.05 and among populations within islands (0 < \(\:{F}_{ST}\) ≤ 0.04) (Wright, 1978) (Fig. 2A, B and C), the values obtained were higher than those found in previous studies (0.03 <\(\:{F}_{ST}\)≤0.044) (Payn et al. 2008; Tripiana et al. 2007; Lu et al. 2018). According to Wright (1978), an \(\:{F}_{ST}\) value < 0.05, even if small, can still indicate the presence of significant evolutionary processes, such as natural selection, genetic drift, or migration, that influence the genetic structure of these populations.

Among the factors that may have contributed to the reduced genetic divergence observed between islands are gene flow via pollen facilitated by the east-west wind speed and direction (Payn et al. 2007; Dvorak et al. 2008; Payn et al. 2008), and cyclonic events occurring once every 50 years that may promote long-distance gene flow (Dvorak et al. 2008).

Additionally, the low differentiation can be explained by ancestry (\(\:K\)=3) (Figs. 3 and 4C), considering the geological hypotheses and colonization routes from east to west across these islands (Timor → Wetar → Adonara → Lembata) (Payn et al. 2007). Geological and paleontological evidence indicates the existence of the supercontinent Gondwana (Rogers 1996), which included the natural occurrence area of E. urophylla. During the Pleistocene, the islands of Flores, Adonara, and Lembata were still connected. Approximately 11,700 years ago, they got separated due to sea level increase following deglaciation (Dvorak et al. 2008; Voris 2000).

Another factor that may explain the low genetic differentiation is the reproductive biology of the species and the geographical distance between populations (Figs. 2D and 2E). Although it allows up to 10% self-fertilization, E. urophylla is predominantly allogamous, which favors cross-pollination (Pryor 1975; House and Bell 1994). Regarding gene flow, if via pollen, it is mainly transported by bees (Eldridge et al. 1993) with a range of over 8 km (Dick et al. 2003). Via seeds, dispersal by wind and mammals contributes to long-distance gene flow (Tripiana et al. 2007). The high gene flow between populations on each island prevents genetic differentiation due to the high rate of allele migration from one population to another (House and Bell 1994).

The higher observed heterozygosity in Timor confirms its importance as the first island colonized (Kitada et al. 2021; Payn et al. 2007), since populations closer to the ancestral population likely had more opportunities for evolutionary events such as mutations than more recent populations (Liu et al. 2006). Another factor contributing to the higher diversity observed on this island was the conservation status of the areas at the time of collection, which, as in Wetar, were more preserved areas with more wild populations and a lower risk of genetic vulnerability, with most of the vegetation within the boundaries of the Mount Mutis Forest Park (Pepe et al. 2004). Additionally, it is important to note that Timor had a limited number of individuals (N = 11 and \(\:{N}_{e}\)=3.1), whose seeds were not obtained from progenies (families) but rather from a seed bulk.

According to the conservation status (Pepe et al. 2004), the high haplotypic diversity (\(\:h\)=0.8), and the fact that it was one of the first islands colonized by the species (Payn et al. 2007), the populations from Wetar Island were expected to have high genetic diversity and a large effective population size ( \(\:{N}_{e}\)= 213). However, the low\(\:{\:H}_{o}\) and \(\:{H}_{e}\) values observed on this island, compared to the others, can be explained by gene flow between populations due to their short geographical distances (1.86–24.19 km) (Fig. 1).

Therefore, in our understanding, the determining factor for the differentiation of Wetar from the other islands is geographical isolation, as it rules out the possibility that it originated from a founder effect resulting from a remnant population after a volcanic activity (Figs. 1 and 2). Wetar may be undergoing unique selective pressures or have a genetic dynamic that differs from the other studied populations; thus, a more detailed analysis, such as studies of gene flow or natural selection, may help clarify these observations.

The proportion of individuals from the islands of Wetar and Timor sharing the same ancestral population suggests that the colonization of E. urophylla occurred from Timor (Fig. 3) (Payn et al. 2007). In this context, two findings provide evidence for this colonization: (1) the occurrence of E. urophylla in the Irian Jaya region of New Guinea, alongside E. pellita, followed by migrations to Timor (Moura 2004) and subsequently to Wetar; (2) Timor was the first island to be colonized, given its high diversity and proximity to other centers of origin for Eucalyptus species, such as Australia and Papua New Guinea (Payn et al. 2007). These findings are not mutually exclusive; they indicate a colonization order from Timor to Wetar. Geographical isolation and restricted interbreeding among individuals on the same island may have contributed to the genetic composition of Wetar becoming progressively more homogeneous over generations (Figs. 3, 4, and 5). As observed in studies of genetic diversity and population structure, the E. urophylla individuals sampled from the seven islands group into two to, at most, four genetic clusters, according to their genetic distances (House and Bell 1994; Payn et al. 2008; Lu et al. 2018; Barros et al. 2022).

Another factor that may have contributed to the high diversity observed in the species is the presence of individuals resulting from natural hybridization and introgression with E. alba (Pepe et al. 2004; Dvorak et al. 2008). Both species occur simultaneously at altitudes ranging from 0 to 800 m (Dvorak et al. 2008). According to Griffin et al. (1988), intermediate phenotypes between Eucalyptus species may result from an ancient clinal variation that connected these species or from evolutionary pressure.

Considering the distinct morphological descriptors of E. alba (white and smooth bark) and E. urophylla (brown and rough bark), and the fact that natural hybridization and introgression are more noticeable in the field than in natural areas (Dvorak et al. 2008), we cannot rule out the possibility that within the population defined as E. urophylla, there may be individuals resulting from hybridization and/or introgression.

The observation of \(\:K\)=2, with one group consisting only of individuals from Wetar, has been related in previous studies to morphological differences (Doran et al. 1995; Pryor et al. 1995) and the existence of distinct seasonality patterns. These seasonality patterns correspond to (i) one with higher annual rainfall and irregular distribution of rain throughout the year, with well-defined prolonged dry periods of 5 to 6 months, and (ii) low rainfall with uniform distribution of rain throughout the year (Dvorak et al. 2008). A division of E. urophylla into E. orophilla and E. wetarensis was previously proposed, but it has not yet been established based on molecular analyses (Pryor et al. 1995). The phylogenetic analysis (Fig. 5A) shows that the individuals from Wetar are genetically distant from the others, thus reopening the discussion about classifying them as E. urophylla var. wetarensis.

On Adonara Island, the isolation of the Kawela individuals from the other populations was observed (Fig. 3C). This greater genetic differentiation may be related to higher levels of relatedness within this population, favored by the small size of the sampled fragment. The Kawella population originates from an area spanning approximately 50 hectares and is predominantly composed of ancient forest remnants (Hodge and Dvorak 2015). As reported by Luz (1997), this fragment contains a small stand of E. urophylla (fewer than 500 trees), which may increase the population's vulnerability to inbreeding and genetic drift, reducing its resilience to environmental disturbances.

The populations exhibit genetic diversity suitable for conservation and exploration, including the development of hybrids, the establishment of new populations with recombined genetic material, and, in the future, clones. The results allow for the definition of specific strategies for the efficient conservation and management of genetic resources, aiming at the selection of productive genotypes for different macro and micro climatic regions. An example of this is the evaluation of populations occurring in areas of high volcanic activity, with the goal of selecting genotypes tolerant to water stress, considering their evolutionary adaptation to these extreme conditions. This is a promising alternative to address current climatic fluctuations, where water availability and temperature are highly limiting factors for productivity. In these populations, migration rates exceeding one migrant per generation have already been observed (Payn et al. 2008). According to Wright (1931), such values may be sufficient to prevent population differentiation due to genetic drift. Studies investigating the past of populations using modern approaches in population genetics, such as Coalescent Theory, are scarce in the forestry context and will be the next step in our investigation. Such studies have the potential to clarify the species' evolutionary history by examining past evolutionary events, such as mutations, gene flow, and selection, that may explain genetic differentiation (Nordborg 2007).

Base populations are direct sources of allelic diversity (Dvorak et al. 2008) and, therefore, must be preserved to ensure the security and longevity of the breeding program. Our aim is not only to present the genetic diversity of the 17 populations but also to highlight the importance of genetic conservation and promote a culture of gene pool preservation, especially among industrial companies, which are the primary beneficiaries. Mitigating measures that combine conservation and breeding, such as dynamic conservation, a perspective of revitalizing the base population of genetic improvement programs (Tambarussi et al. 2021), should be considered and implemented, as obtaining base populations without efficient use or management of resources is not true conservation (Dvorak et al. 2008).

The introduction of new populations, especially from unrepresented islands (Alor and Pantar), could further increase local genetic representativeness and variability. However, the limitation on new introductions requires even more efficient management of this genetic collection, particularly given that the genetic improvement base of E. urophylla in the country today is almost entirely comprised of genotypes originating from only two of the seven islands, Timor and Flores.

The use of SNP markers confirms the low degree of genetic differentiation among E. urophylla populations, with greater variability between islands than within islands. This pattern likely reflects the adaptation to specific environmental conditions in each region, as well as genetic drift resulting from small population sizes. The populations demonstrate sufficient capture of genetic diversity, ensuring that ex situ conservation can be carried out effectively and sustainably for the species.

The populations of Wetar show lower genetic diversity, which may be attributed to their geographical isolation, limiting gene flow with other populations. Nonetheless, Wetar stands out as a genetically distinct population, and its homogeneous structure may be related to specific selective pressures, justifying the need for differentiated conservation strategies for this region.

There is evidence of natural hybridization and genetic introgression between E. urophylla and E. alba, which contributes to increased genetic diversity and potentially enhances the adaptability of the populations.

The analyses of genetic diversity and structure revealed the presence of three main ancestral populations (\(\:K\)=3), with Wetar being the most divergent and Timor being the closest genetically to the other islands, suggesting an east-to-west colonization route (Timor → Wetar → Adonara → Lembata). This genetic differentiation, along with phenotypic observations, reopens the discussion about the possible classification of E. urophylla var. wetarensis, highlighting the need for more detailed molecular studies to evaluate this hypothesis.

These results have significant implications for the conservation management of E. urophylla. The observed genetic variability supports conservation strategies that preserve the genetic integrity of populations, promoting both ex situ and in situ conservation.

The population genetic structure of E. urophylla and the history of the original populations have important implications for conservation management, indicating the need for conservation strategies that consider genetic variability and differentiation among populations.

Given the genetic potential found, it is suggested that new efforts in introduction and management be undertaken, with an emphasis on unrepresented islands such as Alor and Pantar, to further increase genetic representativeness and promote the sustainability of E. urophylla populations in the future.

Acknowledgements

This study is part of the first author's doctoral thesis. We would like to thank the entire staff of field technicians at Suzano S.A. who were involved in establishing and managing the several field trials and collecting and organizing the growth data used in this study. Evandro V. Tambarussi is supported by a CNPq research fellowship (grant no. 303789/2022-0).

Author Contributions

Dandara Yasmim Bonfim de Oliveira Silva was involved in all stages of the study, including study planning, population sampling, statistical data analysis, and manuscript preparation. João Ricardo Bachega Feijó Rosa contributed to the study design, methodology, data analysis, and manuscript writing. Izabel Christina Gava de Souza managed the fieldwork and collaborated in writing the manuscript. Maria Paula Barion Alves Nunes assisted in the preparation of the manuscript. Thiago Romanos Benatti managed the genotyping process and contributed to the study's design. Jose Wilacildo de Matos oversaw the fieldwork and participated in the manuscript preparation. Shinitiro Oda contributed to the manuscript development and the interpretation of analyses, while Peter Beerli contributed to the methodology and manuscript writing. Evandro Vagner Tambarussi led the study design, coordinated the project, supervised the first author, secured funding for the study, contributed to the methodology, participated in data analysis, and drafted and edited the manuscript for submission. All authors reviewed and approved the final manuscript.

Funding: Not applicable.

Data availability: The datasets generated and analyzed during the study are available from the corresponding author upon reasonable request.

Conflict of interest: The authors declare no conflict interest.

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Dynamics of genetic diversity and population structure of Eucalyptus urophylla in Indonesia Islands using SNP Data

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Abstract

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Introduction

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Plant Material

DNA Extraction, Genotyping, and SNP Quality Control

Diversity Parameters, Genetic Structure, and Effective Population Size

Results

Genetic Diversity Parameters and Effective Population Size

Population Genetic Structure

Discussion

Conclusions

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