Are the Populations of Oenocarpus Bataua (Arecaceae) Separated by Geography Or United by Dispersion?

Are the populations of Oenocarpus bataua (Arecaceae) separated by geography or united by dispersion?

MELISSA MARTÍNEZ, ANA M. ALDANA, LUIS FRANCISCO HENAO DÍAZ, PABLO R. STEVEN- SON Laboratorio de Ecología de Bosques Tropicales y Primatología (LEBTYP), Departamento de Cien- cias Biológicas, Universidad de los Andes. Bogotá, Colombia.

Abstract Biogeographic studies have shown that Andean uplift has acted as an accelerator of plant diversity, for lowland species it may be possible that Andean uplift has acted as a barrier to gene flow, separating populations on both sides of the mountain, perhaps promoting allopatric speciation. For widespread plant species, it would not be expected that the Andes have acted as a barrier because seed dispersal could promote gene flow between opposite sides of the mountains. Such would be the case of the sehe palm (Oenocarpus bataua Mart.). We studied the genetic structure of five populations of O. bataua in the eastern and western sides of the eastern cordillera, to determine if there is gene flow between these populations, using information from 6 microsatellite markers designed for this species. We found a moderate genetic differentiation for O. bataua populations on the eastern side of the eastern cordillera and a high differentiation for the geographically isolated populations.

Keywords: population structure, genetic differentiation, eastern Cordillera, gene flow, seed dispersal, Fst, Rst

Introduction promoting allopatric speciation. This has been documented for lowland bird spe- Biogeographic studies have shown that cies, such as the Three-striped Warbler Andean uplift has acted as an accelerator (Gutiérrez-Pinto et al. 2012). of plant diversity, creating new environ- However, the different features of the ments for plant lineages that have diver- barrier may cause variable degrees of sified rapidly at high altitudes (Antonelli genetic isolation. For instance, the lack of et al. 2009; Madriñán, Cortés, and gene flow between some widespread Ne- Richardson 2013; Hughes and Eastwood otropical bird species occurring in east- 2006). For some lowland species it may ern Cordillera and central-western Cor- be possible that Andean uplift has acted dillera of Colombia in contrast with the as a barrier to gene flow, separating pop- feasible high levels of gene flow between ulations on both sides of the mountain, populations of the central Cordillera and help us understand the quality of seed the eastern Cordillera, may account to the dispersal of this bird species. close proximity of the latters and by the fact that these mountain ranges are con- In this project we studied the genetic nected at their southern ends (Cadena, structure of five populations of O. bataua Klicka, and Ricklefs 2007). in the eastern and western sides of the eastern cordillera, to determine if there is For some widespread plant species, it gene flow between these populations. We would not be expected that the Andes also aimed to investigate the population have acted as a barrier if seed dispersal of origin of dispersed seeds to a high could promote gene flow between oppo- elevation site in the western side of the site sides of the mountains. Such may be Eastern Cordillera (PNN Cueva de los the case of the sehe palm (Oenocarpus Guácharos). bataua Mart.), which has been used by humans for more than 10.000 years We expected a moderate genetic varia- (Morcote-Ríos and Bernal 2001) and that tion among the populations that have is also a main component of the diet of maintained gene flow between them but many animal species (Stevenson and Link some populations, at regional scales, 2010; Holland et al. 2009). Studies at should be differentiated mostly by pri- smaller geographic scales with O. bataua vate alleles. Also it is probable that some have shown that seed dispersal by long- degree of genetic isolation by distance wattled umbrella bird is very effective could be present at local and regional reducing genetic structure at fine scales scales. Specifically at the regional scale within a 143ha forest patch (Karubian et we expect that the isolation by distance al. 2010). Interestingly, Federman et al., will show a longitudinal gradient of ge- (2013) found, for Mauritia flexuosa, an- netic differentiation. other widespread Neotropical palm, that gene flow has been interrupted due to Methods habitat fragmentation which has limited Study sites and material collection animal mediated seed dispersal and pollination. This suggests that, at wider Using information from the O. bataua scales, areas affected by deforestation populations in vegetation plots we sam- and de-faunation may hold higher genetic pled leaf tissue from tagged individuals structure. inside the plots at five study sites. Two in the eastern side of the eastern cordillera We have found that O. bataua is the most (Figure 1) Finca Santa Rosa and Finca Las common plant species shared between Unamas in San Martín (Meta) and our studies sites in lowland rainforests in Reserva Natural Tomo Grande in Santa Northeast South America. We also have Rosalía (Vichada). And three on the west- found seeds of this species being dis- ern side of the eastern cordillera: PNR persed by Oilbirds (Steatornis caripensis) Serranía de las Quinchas (Santander), to the high lands in the western side of PNN Cueva de los Guácharos (Huila) and the eastern cordillera. It is yet unknown, Chocó. In each site we collected plant ma- which are the populations of origin for terial from between 6 and 21 individual these seeds. Learning about this could palms. To determine the population of origin for null alleles and allele dropout (Taberlet et seeds dispersed to the PNN Cueva de los al. 1991; Gagneux, Boesch, and Woodruff Guácharos (Huila) we collected 10 seeds 1997). Nevertheless, it was used the MI- that were deposited in the floor of the CRO-CHEKER software (Van Oosterhout et caves where the Oilbirds (Steatornis al. 2004) to check the microsatellite data caripensis) nest. for null alleles and scoring errors. Allele size was performed automatically and DNA extraction and amplification later confirmed manually using the GENE MAPPER 4.1 (Applied Biosystems) soft- DNA from plant material was isolated ware. from 20 mg of dry collections using the Quiagen Plant DNA extraction Kit follow- Data analysis ing the manufactures protocol. DNA from seeds was obtained from the maternally We calculated number of alleles per locus inherited husk tissue. To corroborate the (NA), the expected (He) (Nei 1973), and success of DNA extraction process we observed heterocigocity (Ho). The fixa- used the nanodrop by examining the tion index (Fst), Rst (an Fst analogue as- DNA’s concentration and purity. suming a stepwise mutation model) and the inbreeding coefficient (Fis) deter- mined the genetic structure among the populations and their degree of inbreeding respectively. Also the Hardy- Weinberg and linkage equilibrium was estimated to account for possible deviations from the expected frequencies. The- se analyses were conducted using GENE POP software (Raymond and Rousset 1995).

With a genetic structure analysis we searched for the most plausible number of genetic clusters (K) in the meta- population. Estimated clusters were in- spected in K values ranging from 1 to 7 (the Number of populations plus two) and ran with 1000000 MCMC and a 10%

Figure 1: map showing the location of 5 localities of burn-in. The mentioned analysis was where samples of O. bataua were collected. conducted in the Bayesian software STRUCTURE (Pritchard, Stephens, and The samples genotyping consisted in 6 Donnelly 2000). The second-order rate microsatellite markers designed to O. ba- of change (Delta K) was calculated among taua (Montufar et al. 2006). The genetic the resulting values of K (Evanno, reactions were conducted at least three Regnaut, and Goudet 2005). times to assure the procedure precision Also we performed a discriminant analy- in order to minimize the occurrence of sis of principal components using the R 3.2.1 software. This test summarizes the pairs. The first pair of loci was not inde- data variation by searching for a reduced pendent for Tomo Grande and Quinchas set of linear combinations of the varia- populations. And for the second pair the bles. The cross validation method was same was found for San Martín popula- used to identify the optimal number of tion. principal components (PCs) and found to be 19. Additionally, the GDA software The Hardy Weinberg equilibrium test per (Lewis and Zaykin 2001) was used to locus was performed for all the popula- identify private alleles. tions and it was found that 4 of the 6 loci were not in HWE. Only the ob07 and Results ob18 loci were in HWE in all the five populations. Deviations from HWE were The genetic characterization of our popu- apparent in at most two populations per lations of O. bataua showed a new locus. Those populations varied between expanded size range (¡Error! No se the loci analyzed. The heterozygous defi- encuentra el origen de la referencia.) ciency test revealed that most of the loci of the allele size reported by Montufar et that were not in HWE presented less het- al. (2006) for O.bataua populations in erozygotes individuals than expected. French Guyana and Perú. For the ob06, ob07 and ob16 loci, this range was more consistent with that reported by Karubi- an et al. (2010) for O.bataua populations of northwestern Ecuador, since as for those samples, alleles with less base pairs (bp) were found in our populations (Fig- ure 2). Nevertheless, the alleles size range showed a great variation between populations (Figure 3).

However, comparing with the populations of Montufar et al. (2006), we found a high variability in the high total number of alleles per locus (NA) (¡Error! No se encuentra el origen de la referencia.). Nevertheless, the number of identified alleles per locus per population exhibited a great variation.

The linkage disequilibrium test was performed for each pair of loci in each popu- Figure 2. Allele´s size range per locus for Colombia, Perú lation and across all the populations. For (Montufar 2006) and Ecuador (Karubian 2010) popula- the overall test, all loci were in linkage tions. Additionally, there is shown a violin plot of the allele frequency for the populations of Colombia equilibrium, except the ob07- ob16 (p=0.015) and ob06-ob18 (p=0.023) loci Being the Quichas- Guácharos pair (both east of the Cordillera Orien- tal) the most differentiated population. The genetic structure analysis revealed five clusters K as the underlying Figure 3. Frequency of alleles per locus per population. genetic populations. As can be seen, the Although, for the San Martin and Chocó priori defined populations exhibit a char- acteristic color, which corresponds to the populations, the MICRO-CHECKER software revealed no evidence of null alleles for assigned cluster (Figure 4). the six loci analyzed. Instead, several loci San Martin and Guácharos were grouped showed evidence of null alleles for Tomo within the yellow cluster. While Tomo Grande (ob03 and ob08), Quinchas Grande, Chocó and Quinchas were (ob06) and Guácharos (ob08). grouped within the pink, blue and red clusters, respectively. There is a green The difference between the Fst and Rst cluster which can be traced to almost all accounts for its distinct mutation models. the populations with the exception of Although, both the Fst and Rst exhibit a Chocó and that predominates in Tomo significant differentiation between almost Grande. all the population pairs (Table S2). How- ever, the Rst drawback is its high associ- Table S2. Pairwise population differentiation from microsatellites for 5 sampling locations of O. bataua using Rst (above ated variance, but still a better estimate diagonal) and Fst (below the diagonal). Significant p-values are of population differentiation than Fst highlighted. The grayscale color represents the degree of popu- when there is an elevated ratio of muta- lation differentiation. From light to dark gray moderate differentiation (0.05 ˂ Fst/Rst ≤ 0.15), high differentiation (0.15 ˂ tion over migration (Balloux, and Lugon- Fst/Rst ≤ 0.25) and very high differentiation (0.25 ˂ Fst/Rst ≤ 1). Moulin 2002). As it is expected in popula- San Tomo Guácha- tions with a reduced gene flow, being the Martín Grande Chocó Quinchas ros effect of polymorphism much greater San Martín - 0.11804 0.39714 0.21510 0.03930 Tomo (due to the high mutation rate of the mi- Grande 0.07336 - 0.14651 0. 0717 0.03875 crosatellites). Chocó 0.21252 0.13203 - 0.44004 0.21530 Quinchas 0.17813 0.14022 0.21631 - 0.27541 According to what was stayed by Wright Guácharos 0.08910 0.12984 0.20642 0.25791 -

(1978), the population pairs of San Mar- tín-Chocó, San Martín-Quinchas, Chocó- Guácharos, Chocó-Quinchas and Quin- chas-Guácharos exhibit a high or very high differentiation.

Figure 4. Bar plots showing Bayesian assignment probabilities from the software STRUCTURE 2.3.4 (Pritchard, Stephens, and Donnelly 2000) for five clusters. Each vertical bar corresponds to one individual. The proportion of each bar that is yellow, pink, blue, red and green represents an individual’s assignment probability to clusters one, two, and three, four and five respectively. Sampling localities of San Martín, Tomo Grande, Chocó, Guácharos and Quinchas, separated by a black line, correspond to the 1, 2, 3, 4, 5 numbers, respectively.

On the other hand, the populations of Chocó and Quinchas were the most spaced and clear cut populations. In ac- cordance with the Fst and Rst values. Ad- ditionally, there was found that Tomo Grande has several private alleles at different loci. Being the population with the highest number of private alleles, fol- lowed by Guácharos (Figure 5).

Figure 5. Scatter plot of the discriminant analysis of principal components (DAPC). The individuals are represented by dots and the groups as inertia ellipses.

As well, the discriminant analysis of principal components DAPC (Figure 5) reflects the presence of an important degree of genetic variation amongst the studied populations.

However, in the case of San Martin and Guácharos, even though the ellipses en- close most of the individuals in each location, they overlap, therefore indicating a possible single group. This is consistent with both, the Bayesian assignment and the Fst value. Figure 6. Frequency of private alleles per locus (symbols) and per population (colors). Discussion isolation by distance pattern through the eastern side of the Cordillera. As Guácha- Linkage disequilibrium and HWE ros- Tomo Grande are more differentiat- The linkage disequilibrium test results ed than Guácharos- San Martín, it is sup- may be ignorable as the developers of the posed that the gene flow follows the six loci found no evidence of linkage dise- northernmost population, passing quilibrium. However, it can be attributed through San Martín to the seed popula- to the few sampling in some populations, tion located in the south. which will lead to a flawed estimate of On the other hand, despite the distance allele frequencies. and the possible barriers to gene flow, Chocó- Tomo Grande (Fst= 0.13203) and Deviations from HWE may result from Quinchas- Tomo Grande (Fst= 0.14022) the presence of null alelles (microsatel- did not reveal a high or very high differ- lites alleles that do not amplify during entiation. Instead, it revealed a moderate PCR). Since them were significant for the differentiation. heterozygous deficiency test, that is One can imagine a longitudinal gene flow was significantly less than . through Chocó, Quinchas and Tomo Hence, heterozygotes were underesti- Grande. However, Chocó- Quinchas dis- mated considering that if only one allele played and elevated Fst (0.21631) and Rst from a heterozygote is amplified then it (0.44004) value. will be erroneously genotyped as a ho- mozygote (Freeland, Kirk, and Petersen Such an odd result can be addressed by 2011). looking the allele size range of the populations of Perú and Ecuador analyzed by Population structure Montufar et al. (2006) and Karubian et al. (2010), respectively (Figure 2). And by As expected, the nearest populations evaluating the frequency of the alleles per (Tomo Grande- San Martín) with no evi- locus, per population of the present study dent barrier to gene flow had the lowest (Figure 3). degree of population structure. However, it still corresponds to a moderate differ- In this manner, the alleles size range of entiation as it is shown graphically in the Peru and Ecuador seems to be well DAPC (Figure 5), where the ellipses show differentiated. The first presents a higher no overlapping. Moreover, the Bayesian numer of bp than the second. Meanwhile, assignment displays a major presence of Colombia looks like a combination of the the pink cluster in the San Martin popula- two previous size ranges for the distinct tion rather than the yellow cluster in the loci analyzed. Therefore, we aimed to Tomo Grande population (Figure 4). disentangle the populations’ similarities Hence, indicating an asymmetric gene to either Perú or Ecuador. flow towards San Martín.

Those, in spite of the few loci analyzed, in In addition, Guácharos- San Martín (Fst= general the Chocó and Quinchas popula- 0.08910) and Guácharos-Tomo Grande tions tend to follow the Ecuador and Perú (Fst= 0.12984) population pairs also re- size range distributions, respectively. vealed a moderate differentiation. Thus, indicating a longitudinal gene flow with And the Tomo Grande size range some- The large genetic differentiation values times coincides only with one population observed in Quinchas-San Martín, San or with both (the Perú/Quinchas and Ec- Martín- Chocó and Chocó- Quinchas, from uador/Chocó size range). Being some- lower to higher values, supports those where between the two populations as studies showing the effect of the Andes can be seen in the DAPC (Figure 5). For Cordillera as a barrier to gene flow. instance, for ob16 locus, Tomo Grande Without leaving aside the large rivers and agrees exclusively the Quinchas and Perú the long distances restricting genetic ex- size range (Figure 3). change.

This pattern, may account for a possible Population of origin of the seeds gene flow between, Perú, Tomo Grande The Bayesian assignment reveals that San and Quinchas populations, following the Martín is the predominant population of Amazonia region up the plains from the origin of the seeds dispersed to the PNN foot of the Eastern Cordillera of Colombia Cueva de los Guácharos, since they were to the middle and lower Orinoco in Vene- assigned to the yellow cluster. This was zuela (Pintaud et al. 2008). Thus, follow- consistent with the DAPC, which reflects ing the Caribbean corridor (Haffer 1970) an equal pattern of genetic variation be- which has been used to explain the pres- tween the groups, as the ellipses overlap. ence of tropical taxa from both sides of In addition, the low Fst value (0.08910) the Andes and even Central America also shows a moderate differentiation. without crossing the Andes (Pintaud et al.

2008). Then, the green cluster, repre- In this way, the seed population´s origin sentative in Tomo Grande population, is not exclusively traced to San Martín. It may come from O. bataua populations can be seen an affinity to Tomo Grande identified by Stauffer (2007) in Venezue- and to a lesser extend to Chocó clusters, lan plains. And thus may account for the by the Bayesian assignment and the high number of private alleles of this DAPC. Therefore, the oilbirds which for- population (Figure 6). age a vast area up to 120 km from the cave nightly (Del Risco and Echeverri The link-up between Chocó and the north 2011), seem to be feeding preferentially western Ecuador is evident, since them on O. bataua populations in the eastern correspond to the Chocó biogeographic side at the south of the eastern cordillera. region (Gentry 1982; Forero and Gentry

1989). But the presence of a moderate After all, the Fst and Rst estimates (Table genetic differentiation with Tomo Grande S2) revealed a very great differentiation at the opposite site of the Andes Cordille- between Guácharos and Quinchas. Possi- ra seem a tricky question. Still, if there is ble as a response to the economically dy- a way of having gene flow between the namic and highly populated region locat- mountains it is unlikely to have high dif- ed among these areas. That is in conse- ferentiation between the Chocó biogeo- quence affected by deforestation and de- graphic region and San Martín population faunation. Conversely, the samples collect- (Fst= 0.21252 and Rst= 0.39714) (seeing ed in San Martin corresponds to a continu- that the distance is less than to Tomo ous forest, less disturbed with presence of Grande), as it actually occurs. wide range of wildlife species, mostly mammals disappeared in transformed areas helped in the collection of plant material: (Franco and Rojas 2014). Daniel García, Ana María Garrido, Jack Hernandéz, Nicolás Valdivieso, Mónica Conclusions Bastidas, Vanessa Rubio, Ana Malagón, Diana Acosta. And the people from the It was found a moderate genetic differen- DNA sequencing laboratory at Univer- tiation for O. bataua populations on the sidad de los Andes: Mauricio Buitrago, eastern side of the eastern cordillera (San Diana Rosso, Sonia Quintanilla. 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Table S1. Information on the 6 microsatellites loci designed to O. bataua (Montufar et al. 2006). The number of alleles (NA), the expected (HE) and observed (HO) heterozygosi- ties and fixation index (FIS) were calculated for each study site. A new size range and a total number of alleles is given. Oenocarpus bataua Total (40 samples) San Martín (21 samples) Tomo Grande (21 samples) Chocó (6 samples) Quinchas (8 samples) Guácharos (10 samples)

Locus Size (bp) NA NA HE HO FIS NA HE HO FIS NA HE HO FIS NA HE HO FIS NA HE HO FIS Ob03 115-135 11 6 0,797 0,952 -0,201 8 0,725 0,381 0,48 4 0,778 0,8 -0,032 4 0,78 0,5 0,371 4 0,758 0,8 -0,059 Ob06 179-207 13 7 0,642 0,684 -0,068 10 0,89 0,762 0,147 2 0,545 0,333 0,412 5 0,792 0,375 0,544 5 0,558 0,4 0,294 Ob07 164-188 12 8 0,784 0,944 -0,212 9 0,846 0,762 0,101 4 0,712 0,333 0,556 6 0,717 0,625 0,136 7 0,832 0,9 -0,087 Ob08 187-205 8 3 0,621 0,619 0,004 5 0,627 0,3 0,528 5 0,727 0,667 0,09 2 0,233 0,25 -0,077 5 0,742 0,3 0,609 Ob16 125-153 14 9 0,785 0,857 -0,094 11 0,897 0,857 0,045 3 0,711 0,6 0,172 4 0,717 0,625 0,136 5 0,626 0,5 0,21 Ob18 124-144 10 6 0,809 0,789 0,025 6 0,771 0,684 0,115 7 0,879 0,833 0,057 4 0,642 0,625 0,028 9 0,789 0,7 0,119