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Population genetic structure of Phaedranassa cinerea Ravenna (Amaryllidaceae) and conservation implications

BMC Plant Biology volume 25, Article number: 106 (2025) Cite this article

Abstract

Background

Andean orography has shaped the endemism of plant species in montane forests, creating a mosaic of habitats in small and isolated areas. Understanding these endemic species' genetic diversity patterns is crucial for their conservation. Phaedranassa cinerea (Amaryllidaceae), a species restricted to the western Andes of Ecuador, is listed as “vulnerable” according to the IUCN criteria. This study seeks to determine whether there is genetic structure among and within Phaedranassa cinerea populations, estimate the timing of their genetic divergence, and recommend conservation strategies based on these genetic structure findings.

Results

Using 13 microsatellites and a Bayesian approach, we analyzed the genetic differentiation of P. cinerea and possible diversification scenarios. Our results indicate that the genetic diversity of P. cinerea is lower than congeneric species. The Bayesian analysis identified two genetic groups, with no evidence of isolation by distance. Populations in the northwest of the Ecuadorean Andes have less allele richness compared to those in the southwest. Additionally, the species exhibits excess homozygosity and evidence of bottlenecks. Our Bayesian analysis suggests that the differentiation among populations was not older than 5,000 years and was as recent as 600 years ago for some of the populations. Based on the geographic distribution of the known populations, the species should be listed as endangered instead of vulnerable to extinction.

Conclusions

Phaedranassa cinerea shows lower genetic diversity than related species, with the most variation within populations. We identified two to four genetic groups, suggesting recent divergence along the ridges of the western Andes. The findings suggest that conservation efforts should focus on securing genetic exchange between populations to preserve the genetic diversity of P. cinerea.

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Background

The Andes are the most biodiverse mountain range on Earth, with a significant number of endemic species [1, 2]. This extraordinary diversity was a consequence of the Andean orogeny, which resulted in a variety of physical, climatic, and unique habitat conditions along elevational gradients [3, 4]. Furthermore, altitudinal gradients can affect endemic plant population dynamics and, in turn, genetic structure [5]. Since montane ecosystems are small and isolated, endemic plants in this region face relatively high extinction rates and low migration rates [6, 7]. To conserve and sustainably manage these ecosystems, it is fundamental to understand the patterns of genetic diversity of the unique species of the Andean system [7].

Population genetics using neutral markers provides useful information on diversity at different hierarchical levels for designing conservation strategies [8,9,10,11,12,13,14,15,16,17]. These studies estimated population substructure, genetic variation, effective population size, and interpopulation connectivity, which are important information for conservation management [18,19,20]. Furthermore, genetic diversity research in endemic and endangered species has improved conservation unit definitions, enhancing proactive approaches to safeguarding endemic plants [21, 22].

In this study, we focused on understanding the intraspecific genetic structure of Phaedranassa cinerea Ravenna (Amaryllidaceae), and we evaluated possible diversification scenarios related to the Andean orogeny. Phaedranassa is a mostly Andean genus with ten species, eight of which are found in Ecuador and seven of which are endemic to the country. In Ecuador, the common name is "ashpa cebolla", which in the Quichua language means "fake onion" because of the similarity of an onion bulb [23]. The genus is monophyletic within the tribe Eucharideae, and Phaedranassa includes species with stalked leaves and pseudoumbelate inflorescence with six to 20 red, pink, yellow, or orange tubular flowers per inflorescence [24].

Phaedranassa cinerea is listed as a “vulnerable” species according to the IUCN Red List [25], and its conservation is important because it is a potential biomedical source of alkaloids used for the treatment of Alzheimer's disease. Recent studies have shown that this species has a high percentage of galantamine, an alkaloid that acts as an acetylcholinesterase inhibitor, which increases when people have this medical condition [26, 27]. The study of population structure and the conservation of rare species such as P. cinerea is therefore essential to maintain a solid gene pool with evolutionary potential.

The objective of this study was to analyze the genetic structure of Phaedranassa cinerea using microsatellites and to propose conservation actions. Specifically, we aimed to address the following questions: (1) Is there genetic structure among and within populations of P. cinerea? (2) When did the genetic divergence of P. cinerea populations likely occur? (3) What conservation strategies could be recommended based on the genetic structure findings for Phaedranassa cinerea?

As a threatened species, we hypothesize that P. cinerea would show low genetic diversity and genetic structure caused by geographic distances that impede gene flow. We also expect to find recent genetic differentiation among populations. Finally, we hope that the results of this study can be used as a guide for the conservation of rare species.

Methods

Study species

Phaedranassa cinerea is a perennial bulbous herb with long (up to 17 × 1 cm) stalked, glaucous leaves; it has seven to 17 tubular flowers that are 3.2 to 5.5 cm long, coral pink in color, and six connate tepals with a green band at the tip, separated by a narrow yellow band [28] (Fig. 1). Although there are no pollination or breeding studies on this species, based on the colors and shape of the flower, we might expect hummingbird pollination. Butterflies and bees have been observed visiting other Phaedranassa species (data not published, N. Oleas pers. obs.). It flowers from July to September [23, 28]. This species is one of the most widely distributed species of the family in Ecuador; it is found in dry and rocky areas of the Western Andes (Fig. 1) in the provinces of Pichincha, Cotopaxi, and Chimborazo between 850 and 1800 m in elevation [25]. However, populations of the species are scattered throughout its geographic distribution (Fig. 2).

Fig. 1
figure 1

a. Habitat of Phaedranassa cinerea in the western Andes of Ecuador, b. leaves and bulb of P. cinerea, c. Inflorescence of P. cinerea

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Fig. 2
figure 2

Population structure and divergence times of P. cinerea Top: Distribution map of Phaedranassa cinerea and mean divergence time estimated from the most likely scenario estimated in DIYABC. Bottom: STRUCTURE analysis for P. cinerea at K = 2 and K = 4. Populations are separated by vertical lines, and each vertical bar indicates which genetic group each individual belongs

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Sampling and data collection

Leaf samples were collected from 180 individuals of Phaedranassa cinerea. Within populations, individuals are clumped and because Phaedranassa species reproduce asexually by bulbs, we sampled plants at least one meter apart to avoid collecting multiple ramets from the same genet. A total of 30 ± 1 individuals per population were sampled. Only six populations were identified previously for P. cinerea, so our sampling captures the species’ distribution across its range [23] (Fig. 2). This species is found in two ecosystems: evergreen forests at the foothills of the Western Cordillera of the Andes and lower montane evergreen forest of the Western Cordillera of the Andes. The former is located between 300 and 1400 m of elevation, with dominant families such as Arecaceae, Lauraceae, and Rubiaceae [29]. The second is located between 1400 and 2000 m of elevation and is characterized by climbers, woody plants, and epiphytic species such as ferns and aroids [29,30,31]. One presentative voucher specimen for each population was selected from vouchers reviewed by NHO and AWM that are deposited in a publicly available herbarium. The full name of the herbarium with the deposit number is listed in Table 1. Formal identification of the plant material used in this study was carried out by Nora H. Oleas using the species key available at [28].

Table 1 Basic descriptive population genetic statistics of Phaedranassa cinerea
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DNA extraction, quantification, and genotyping

The samples were fast-dried in silica gel in the field for subsequent DNA extraction. Approximately one gram of leaves per individual was collected from plants separated by at least one meter to avoid sampling individuals from the same plant since Phaedranassa species exhibit clonal vegetative reproduction [23].

DNA extraction and quantification followed protocols described by Oleas et al. [32] and Livingstone et al. [33]. Individuals were genotyped for 13 previously developed microsatellite loci for P. schizantha (ps2, ps13, ps16, ps27, and ps28) and P. tunguraguae (pt14, pt21, pt32, pt39, pt43, pt48, pt49, and pt61) [32, 34]. Polymerase chain reaction (PCR) was performed according to protocols described by Oleas et al. [32, 34]. The sizes of the DNA fragments were genotyped by capillary electrophoresis in AB3730 using GeneScan 500 Rox [32]. Allele calling was performed manually in GeneMapper 4.0 [23]. Data availability: Microsatellite genotypes that support the findings of this study are available in Supplementary Material 1.

Data analysis

Control and data quality

Null alleles can occur because of changes in the flanking regions of microsatellites that fail to amplify a given locus [35]. We minimize this issue in the laboratory by repeating the PCR up to three times for samples that failed to amplify. Additionally, we analyzed our data in Micro-Checker 2.2.3 to determine the presence of null alleles within each locus [36]. We found two loci with the possible presence of null alleles: Locus14 and Locus43 (Supplementary Material 2). To determine whether the presence of null alleles affected our results, we compared the Fst values with and without the loci showing putative null alleles in GenAlEx 6.5.03 [37], and the results were practically the same (Fst = 0.16 and Fst = 0.17). Thus, we used all loci in our analysis.

Genetic diversity statistics

The number of alleles (N), number of effective alleles (Ne), number of private alleles (PA), observed (Ho) and expected (He) heterozygosity, fixation index (F) and number of multilocus matches were estimated with GenAlEx 6.5.03. [37]. Linkage disequilibrium (LD) and global tests to evaluate Hardy‒Weinberg deviation with heterozygous deficit were performed with GENEPOP 4.7; the parameters for the Markov chain were 10,000 batches of 10,000 interactions per batch and 10,000 rounds of recall [38, 39].

Analysis of population structure

STRUCTURE 2.3.4 was used to evaluate population structure. This program identifies different populations and assigns individuals to each of the populations [40]. We used an admixture model with 2,000,000 repetitions and a burn-in period of 500,000, with 20 runs for each K (number of populations) and K from 1 to 7. We identified the most likely K in Structure Harvester [41] using the method of Evanno et al. [42]. In addition, we used CLUMPAK [43], which summarizes the runs for each K. Genetic diversity (Fst and Dest) was estimated with GenAlEx 6.5.03 [37]. Additionally, GenAlEx 6.5.03 was used for the analysis of molecular variance (AMOVA) with 999 permutations to determine the variance among populations.

Demographic scenarios

To evaluate demographic scenarios for P. cinerea, we used approximate Bayesian calculations with DIYABC 1.0 [44]. In this program, various diversification models were compared, and the one that best fits our data was selected as the most likely [45]. The parameters were as follows: a uniform demographic distribution for the effective population size between ten and 10,000, and it was assumed that the loci followed a generalized model of stepwise mutation (GSM) with an average mutation rate per generation per locus of 5 × 10−4 (min: 10−5, max: 10−2). To explore this parameter space, one million pseudo-observed datasets (PODs) were simulated. The parameter values for the main runs were then refined based on the 95% confidence intervals of the simulation results. The most likely scenario was selected with logistic regression and principal component analysis (PCA) was used to check the fit between simulated values and observed values. Because time divergence in DIYABC is obtained as number of generations, for simplicity we transform the results into years based on the presumed generation time of P. cinerea of three years; this value is based on studies of the reproductive biology of the amaryllis genus Nerine [46].

The analysis aimed to identify which group, as obtained by STRUCTURE, was the more likely to diverge first in time and which others followed afterward. We compare six scenarios. Number one did not consider any previous information, and populations diverged randomly. Number two corresponded to the results of STRUCTURE k = 2, where populations C and B form one group at time a (ta) and then merge with the rest of the populations (tb). The third scenario was the opposite: C and B diverge later at tb. In the fourth to sixth scenarios, different options with the groups from k = 4 were included: Scenario 4 populations C and B diverge more recently (ta), followed by population A (tb), then D and E together (tc) and finally F (td). In Scenario 5, F diverges first with E and D (ta), then Populations C and D, and then A. Scenario 6 merging population ABC (ta), then E and D (tb), and finally F (tc) (Fig. 3).

Fig. 3
figure 3

Divergence scenarios tested with an ABC approach in 6 populations of Phaedranassa cinerea. Most likely scenarios in a darker square. Bottom row: Logistic regression of the most likely scenarios. Principal component analysis (PCA) of scenario four

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Bottleneck

The effective population size and deviation of mutation-drift balance were estimated with the program BOTTLENECK 1.2.02 [47, 48]. Analysis was performed with 100,000 repetitions, and the data were subjected to three tests: the Wilcoxon test, the statistical sign test, and the mode change test [47]. Two very similar models were chosen for the tests that are the most appropriate for microsatellite data: the infinite allele model (IAM) and the stepwise mutation model (SMM) [47]. We also reported M-ratio of allelic richness to allelic size range test [49] calculated in DIYABC 1.0 [44]. M-ratio test estimates the relation between the number of alleles and the range in allele size, assuming that number of alleles decreases more quickly than allele size during a bottleneck [49].

Isolation by distance

The geographic distance matrix in km and the Fst genetic distance matrix were correlated, and their significance was tested using the Mantel test in GenAlEx 6.5.03 [37].

IUCN assessment

The last evaluation of the conservation status of P. cinerea was done in 2011 [25]. We evaluate the conservation status of P. cinerea using GeoCAT [50] with a buffer area de 2 × 2 km, which is the recommended value by IUCN [51].

Results

Genetic diversity

A total of 180 alleles were recorded at 13 polymorphic microsatellite (SSR) loci in the six populations. No multiple locus matches were identified in our data; thus, we did not find evidence of clonality. The average number of alleles (Na) was 7.21, with an average ranging from 5.23 to 8.69 (Table 1). The average number of effective alleles (Ne) was 3.33, varying among populations from 2.48 to 4.44 (Table 1). The observed heterozygosity (Ho) was between 0.31 and 0.43, and the expected heterozygosity (He) was between 0.50 and 0.69 (Table 1). In general, the expected heterozygosity (He) was significantly greater than the observed heterozygosity (Ho) (Table 1). The most diverse populations were A, D, and F, while populations B, C, and E showed less observed heterozygosity than the expected heterozygosity (Table 1). Linkage disequilibrium (LD) was found in less diverse populations, such as B and C, with six and five cases, respectively (Table 1). Population E did not show linkage disequilibrium (LD) (Table 1). The fixation index (Fi) was highest in population A (0.48) and lowest in population B (0.28) (Table 1). The number of private alleles (PAs) varied from one to two in each population (Table 1).

Values of Fst indicated low to medium differentiation between populations, while Dest indicated greater differentiation (Table 2). The greatest genetic difference was found among populations F and B, and the smallest difference was between populations E and D (Table 2). The AMOVA results indicated that 15% of the diversity was among populations and 85% within populations (Table 3).

Table 2 Values of Fst below the diagonal and Dest above the diagonal for the six populations of Phaedranassa cinerea
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Table 3 Results of the analysis of molecular variance of Phaedranassa cinerea
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Population genetic structure

Using the delta K method of Evanno et al. [42] in Structure Harvester, the best K that was obtained was K = 2, followed by another peak at K = 4 (Fig. 2, Supplementary material 3). When K = 2, two groups were formed, one by populations B and C and the other by populations A, D, E, and F (Fig. 2). However, when K = 4, four population groups were identified, one composed of B and C, the second composed of D and E, and the last two composed of populations A and F (Fig. 2). Populations A, B, and C are located in the northern part of the species range, while populations D, E, and F are in the southern part. Our results show an indication of recent gene flow among populations because some individuals belong to different genetic groups (Fig. 2).

Demographic history

Evidence of recent bottlenecks was found under the sign test in the stepwise mutation model in all populations (SMM) (Supplementary Material 4). According to the scenarios evaluated in the DIYABC program, scenario four best fits our data, followed by scenario six (Fig. 3). In Scenario 4, we divided the populations into the four groups proposed by k = 4 obtained in STRUCTURE. The ancestral population would be C and sometime later the F population, which is estimated to have diverged approximately 1350 years ago. The most recent population is population B, which diverged approximately 178 years ago, followed by population A approximately 709 years ago, and populations D and E approximately 999 years ago. (Table 4, Fig. 3). The time of divergence among the populations was recent (Table 4). The Mantel test showed no correlation between geographic and genetic distance, as indicated by the values of R = 0.27 and P = 0.16 (Fig. 4).

Table 4 ABC results of scenario 4, the most likely divergence of Phaedranassa cinerea populations
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Fig. 4
figure 4

Mantel test between the genetic distance (FstP) and the geographic distance (km) between the populations of Phaedranassa cinerea

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IUCN assessment

The extent of occurrence based on the known populations of the species is calculated as 3982 km2 and the area of occupancy is 52 km2. Based on both estimates, this species qualifies as endangered under IUCN criteria B1ab (iii). B refers to the geographic range, and to qualify as endangered the extent of occurrence of the species should be less than 5000 km2 and the area of occupancy less 500 km2, with fragmented populations (a) and a decline in the extension and or quality of habitat (biii).

Discussion

Diversity within and among populations of Phaedranassa cinerea

Our results show that the populations of P. cinerea are not under HWE and exhibit an excess of homozygotes and inbreeding. Our findings are expected since populations of P. cinerea tend to be small and geographically isolated from each other, which likely limits gene flow and increases genetic drift, which would lead to high inbreeding. Additionally, P. cinerea has a mixed mating system with some degree of self-fertilization, further promoting inbreeding within populations. As an herbaceous plant with limited dispersal mechanisms, P. cinerea experiences restricted movement of its seeds and pollen, which supports the genetic results suggesting greater differentiation among populations than might occur in species with higher dispersal capacity. The low differentiation and high inbreeding we observed are therefore consistent with what we know about the species' life history, reproductive traits, and geographic distribution.

All populations showed high fixation index (Fi) values, a lower effective number of alleles (Ne) relative to the total alleles (Na), and a consistent heterozygote deficit (observed heterozygosity, Ho, is lower than expected heterozygosity, He). These indicators suggest reduced genetic diversity, a common outcome following bottleneck events. The populations D, E, F, and A exhibited greater numbers of alleles, effective alleles, and expected and observed heterozygosity (Table 1, Fig. 2). Populations B and C were characterized by low levels of genetic diversity (Table 1).

The results of our study indicate that the populations of Phaedranassa cinerea have lower levels of genetic diversity in terms of heterozygosity (He = 0.38) compared to congeneric species such as P. tunguraguae (He = 0.74) and P. schizantha (He = 0.64) [52, 53]. Similarly, its genetic diversity is similar to that of other Andean species from other families that are widely distributed, such as mortiño (Vaccinium floribundum Kunth, Ericaceae) [54] and quinine (Cinchona officinalis Linnaeus, Rubiaceae) [55].

The Dest values were greater than the Fst values between populations because Fst minimizes genetic differentiation when making comparisons between populations [56]. For high mutation rates as microsatellite as well as fragmented populations, Dest will detect genetic differentiation while Fst will not [56]. Because of this, we consider that the level of genetic differentiation among populations of P. cinerea is high. Analysis of molecular variance (AMOVA) revealed that 85% of the genetic variation occurred within populations, while only 15% occurred among populations (Table 3). These values can be explained by the fact that plants from different populations are outcrossed; the highest genetic variability is distributed among individuals within a population, and a smaller percentage is distributed among populations [57].

Phaedranassa cinerea shows an excess of homozygotes, possibly as a consequence of small population size with consequent inbreeding, genetic drift, restricted gene flow, and loss of heterozygotes [58]. The effects of genetic drift are greater in small populations, causing allele frequencies to change, genetic variation to be lost, and, in the absence of genetic variation, alleles to become fixed [59]. This is shown in the fixation index (F), which is close to 1 (Table 1).

Phaedranassa cinerea shows little to moderate differentiation among populations (Fst = 0.04–0.16), which is greater if we consider Dest (Table 2) [60, 61]. The Fst values found in P. cinerea are comparable to the values found for perennial, cross-pollinated, and long-lived species [57, 62]. However, some studies have shown that ecological factors can influence the measurement of genetic differentiation or Fst [63, 64]. Using a phylogenetic multiple regression model, a recent study of data from 337 species of seed plants revealed the ecological factors that contribute to genetic differentiation [65], as in P. cinerea. One of these factors is geographical location; species in the tropics and subtropics have greater population differentiation because of seasonal asynchrony. Additionally, mixed mating, i.e., both outcrossing and self-fertilization to a certain extent, contributes to greater homozygosity and a reduction in the effective population size. Furthermore, there is a greater distance between the subpopulations of herbs and shrubs, which restricts gene flow [65].

Population structure and demographic patterns

Reproductive characteristics, ecological factors, interference from human activity, and other events could lead to the formation of a species' population structure [66, 67]. Isolation by distance analysis correlates the genetic distance matrix and the geographic distance matrix, with a regression slope close to zero, showing that there is no correlation between these two variables (Fig. 4). These same results were also observed in other species of this genus [52, 53]. The isolation-by-distance model does not consider geographical features such as mountains, coasts, or hills that prevent gene flow between populations, nor does it consider ecological and climatic variables [68]. However, the estimates of recent divergence among the populations (Table 4) are likely a mitigating factor on isolation by distance. These results are expected taking into consideration the complex divergence scenario obtained with DIYABC (see below).

In Phaedranassa cinerea, the population structure could be influenced by the discontinuity of the geographic distribution and the mechanism of colonization and dispersal. Geographical distance may include geographic barriers or habitat fragmentation that obstruct pollination and seed dispersal methods [57]. Seed dispersal possibly occurs by wind, as suggested by small, winged seeds [52]. Studies carried out in Neotropical communities have shown that vertebrate pollination can covary with other biotic and abiotic factors to affect the rate of diversification [69,70,71]. When hummingbirds pollinate, the complexity of the habitat may allow greater geographic isolation, as in the case of Campanulaceae [58, 72].

The population structure of Phaedranassa cinerea is related to geographic location, and it appears that divergence times follow an intricate path. The population structure shows two main groups formed by the populations located in the northwestern Ecuadorian Andes (B and C) and the other formed by the rest of the populations. However, within those groups, K = 4 separates the population range into four genetic groups. Two of them are in the Northern Andes, one formed by populations B and C and the second only by population A. The two remaining groups occur in the southeast, one formed by D and E and the other by F (Fig. 2). The pattern of the Bayesian analysis is consistent with the results of the analysis in the DIYABC program (Fig. 3). Considering the results of both programs, colonization events could explain the genetic differences among populations. For example, three colonization events can be inferred: the first and oldest of populations that could be the source C northwest of the Andes and F southwest of the Andes, then populations D and E located southwest of the Andes, and the most recent A and B to the northwest of the Andes (Fig. 2).

Our data suggest that the demographic history of Phaedranassa cinerea is recent; it has been colonizing new areas, and its populations have been reduced by recent bottlenecks. These results agreed with the sign test under the stepwise mutation model (SMM) showing that all the populations of P. cinerea showed recent bottlenecks. For the Infinite Allele Model (IAM), only population D showed evidence of a bottleneck. Furthermore, when populations experience recent bottlenecks and are small, linkage disequilibrium increases [73]. The populations located in the northwestern Ecuadorian Andes exhibited low genetic diversity with high values of linkage disequilibrium (Table 1 and Fig. 2). On the other hand, the populations that had the highest number of alleles per locus had high numbers of effective alleles (Ne) and were located to the southwest of the Ecuadorian Andes (Table 1 and Fig. 2).

Genetic differentiation within Phaedranassa cinerea and the Andes dynamics

The extraordinary biodiversity of the Andes has been attributed to the spatial variability and altitudinal gradients created during the mountain-building processes, generating sharp environmental gradients across geographic space and geographic isolation of populations by topographic features [74, 75]. The uplift of the Andes is the result of the plates’ subduction, which began in the Cretaceous but progressed unevenly across the range [74]. In the Northern Andes, around 3 Ma, the mountains reached current elevations [76]. Furthermore, climatic factors have also shaped the diversity in the Andes, for example, the climatic fluctuations during the Pleistocene (2.58 Ma-11,700 years approx.) [77, 78]. Glacial and interglacial cycles of the Pleistocene promoted the retraction and fragmentation of tropical forests, isolating populations and generating allopatric speciation [79, 80]. For this reason, the Pleistocene has shaped intraspecific genetic diversity [81]. Our ABC results suggest that the differentiation among populations was not older than 5,000 years and was as recent as 600 years ago. Therefore, we have no evidence that patterns of genetic variation in the populations of P. cinerea could be explained by climate change in the Pleistocene or the uplift of the Andes. Both events most probably played a role in the speciation process of the genus, which originated around 5 Ma [24].

Divergence calculations have been consistent for congeneric species [52, 53]. The divergence time in Phaedranassa schizantha is relatively recent (< 10,000 years), and its spatial and demographic patterns have been shaped by urban development [53]. For P. tunguraguae, the time of differentiation among populations is less than 6,000 years, and for those populations, the divergence time is estimated to be 3,000 years, which is related to the eruption of the Tungurahua volcano [52]. Likewise, similar patterns were found for P. cinerea with a recent colonization time of approximately 5,000 years, which could suggest that the populations diverged in the complex orogeny of the western Andes, diverging from higher elevation populations to lower, following mountain ridges, resulting in the isolated populations we found today. Unfortunately, there is a lack of detailed topographic data from the region where P. cinerea is located that could help us better understand the divergence paths found in this study. Finally, we need to consider that our results show evidence based on one type of molecular marker and testing the scenarios proposed. To fully understand the divergence patterns, we suggest that studies use SNPs.

Conservation implications

For the last two decades, Phaedranassa cinerea has been classified as “vulnerable” under the IUCN criteria B1ab(iii) [25], that is, with populations in a geographic area of less than 20,000 km2 potentially affected by severely fragmented habitat. However, recent studies using species distribution models (SDMs) for the genus carried out with verified data show that P. cinerea occurs in a distribution area of less than 5,000 km2 and that it belongs to the “Endangered” category [82]. These data suggest that recategorization of the species is needed, taking into account verified data. Prioritizing its conservation is necessary, as the species may be more at risk of loss of genetic diversity [83]. For this reason, it is necessary to implement conservation strategies that guarantee the maintenance of the genetic diversity of P. cinerea.

The results of the population genetics of Phaedranassa cinerea showed that the genetic diversity was not as low as expected; however, it did not have a genetic diversity distributed homogeneously among the populations (Table 1). The STRUCTURE results also showed that P. cinerea genetic diversity at the geographic scale is represented by two genetic groups, populations from the northwestern Ecuadorian Andes (B and C) and populations from the southwestern Ecuadorian Andes (A, D, E). and F) (Fig. 2). With these results, at least one of the populations of each genetic group must be protected. It is important that conservation action is accompanied by studies of future climate projections to guarantee the effective conservation of the genetic diversity of P. cinerea in the future.

The two most common conservation units are evolutionarily significant units (ESUs) and management units (MUs) [84]. ESUs are populations or groups of populations that are prioritized for conservation because they seek to protect against genetic variation and evolutionary processes [84]. Considering the genetic diversity and demographic history of Phaedranassa cinerea, we suggest two ESUs. The first will be the northwestern populations, which present less genetic diversity and are the most recent group; therefore, these populations should be the group with the highest priority for conservation. The second corresponds to the populations of the southwestern distribution that show greater genetic diversity.

Because of the reduced number of known populations of Phaedranassa cinerea, public awareness is necessary for the in situ protection of this species. Unfortunately, landslides are part of both the western Andean historical lithology and land use activities [85]. We recommend in situ conservation strategies close to native populations, such as in home gardens, with the goal of expanding their distribution and attracting pollinators while imparting conservation of a natural resource. This and other Phaedranassa species are attractive plants that are already used for ornamental purposes in other countries but not in Ecuador and have enormous horticultural potential.

Conclusions

In the present study, we investigated the genetic diversity and structure of Phaedranassa cinerea using 13 previously developed microsatellites for the genus. Compared with conspecific species, P. cinerea has lower levels of genetic diversity. Genetic variation existed mainly within populations, and STRUCTURE analysis revealed that two and four genetic groups from the six analyzed populations best fit our data. We found that the divergence of P. cinerea is recent and follows several routes along the ridges of the complex landscape of the western cordillera. We suggest conservation significant units (ESUs) for northwestern populations with less diversity and for southwestern populations with greater diversity. In addition, in situ conservation strategies in home gardens of populations close to the habitat of P. cinerea should be encouraged. Finally, the conservation status based on IUCN criteria should be updated to endangered.

Our results contribute to a better understanding of Andean biodiversity. This shows that genetic diversity does not follow an isolation-by-distance model because of the landscape configuration, which needs to be considered in conservation plans.

Data availability

Data availability Microsatellite genotypes that support the findings of this study are available in Supplementary Material 1.

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Acknowledgements

We thank the ‘Christopher Davidson & Sharon Christoph Fellowship’ of the Missouri Botanical Garden to MBB for writing and submitting the article for publication. We thank Enmily Sánchez and Paola Peña for their assistance in the field. Fieldwork was conducted with the Ministerio del Ambiente del Ecuador Research permits.

Clinical trial number

Not applicable.

Funding

This work was supported by the National Science Foundation (NSF Grant DEB 0129179) to AWM and the Judith Evans Parker Travel Grant from Florida International University to NHO. Further support came from the Universidad Tecnológica Indoamérica (Diversidad morfológica, genética y química de plantas, 2021; Elucidando la diversidad vegetal desde un análisis multidisciplinario, 2022-2026) to NHO.

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Author notes

  1. María Belén Buenaño and Nora H. Oleas contributed equally to this work.

Authors and Affiliations

  1. Centro de Investigación del Territorio y Hábitat Sostenible (CITEHS), y Facultad de Ciencias de Medio Ambiente, Universidad Tecnológica Indoamérica, Machala y Sabanilla, Quito, Ecuador

    María Belén Buenaño

  2. Missouri Botanical Garden, St. Louis, 4344 Shaw Blvd., MO, 63110, USA

    Carmen Ulloa Ulloa

  3. Department of Biological Sciences, Institute of Environment, Kimberly Green Latin American and Caribbean Center, Cuban Research Institute, Florida International University, University Park, Miami, FL, 33199, USA

    Javier Francisco-Ortega

  4. Center for Tropical Plant Conservation, Fairchild Tropical Botanic Garden, Coral Gables, Miami, FL, 33156, USA

    Javier Francisco-Ortega

  5. Kelly Research Fellow, Montgomery Botanical Center, 11901 Old Cutler Road, Coral Gables, FL, 33156, USA

    Javier Francisco-Ortega

  6. School of Life Sciences, Arizona State University, P.O. Box 874501, Tempe, AZ, 85287-4501, USA

    Alan W. Meerow

  7. Montgomery Botanical Center, Coral Gables, FL, 33156, USA

    Alan W. Meerow

  8. Centro de Investigación de La Biodiversidad y Cambio Climático (BioCamb), y Facultad de Ciencias de Medio Ambiente, Universidad Tecnológica Indoamérica, Machala y Sabanilla, Quito, Ecuador

    Nora H. Oleas

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  1. María Belén Buenaño
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  4. Alan W. Meerow
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Contributions

MBB and NHO contributed equally. Conception NHO; design of the work NHO, AWM, MBB; data acquisition NHO, MBB; analysis NHO, AWM, MBB, interpretation of data NHO, AWM, MBB, JFO, CUU; funding AWM, NHO; prepare figure MBB; first draft MBB, NHO; manuscript writing and revision MBB, NHO, CUU, AWM, JFO. All authors reviewed the manuscript.

Corresponding author

Correspondence to Nora H. Oleas.

Ethics declarations

Ethics approval and consent to participate

We were granted collecting permits from the Ministerio del Ambiente in Ecuador for all the samples used in this research (Contrato Marco: MAE–DNB–CM–2015–0054, Permit No. 003–14-IC-FLO-DNB-MA).

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Not applicable.

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The authors declare no competing interests.

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Buenaño, M.B., Ulloa Ulloa, C., Francisco-Ortega, J. et al. Population genetic structure of Phaedranassa cinerea Ravenna (Amaryllidaceae) and conservation implications. BMC Plant Biol 25, 106 (2025). https://doi.org/10.1186/s12870-025-06073-0

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BMC Plant Biology

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