Title: Genetic Diversity and Population Genetic Structure in Three Threatened Ocotea Species

1Title: Genetic diversity and population genetic structure in three threatened Ocotea species 2(Lauraceae) from Brazil's Atlantic Rainforest and implications for their conservation.

3Authors: Martins EM*12, Lamont RW3, Martinelli G1, Lira-Medeiros CF1, Quinet A1 and Shapcott A3.

4Addresses: 1Diretoria de Pesquisa, Instituto de Pesquisas Jardim Botânico do Rio de Janeiro, Rio de 5Janeiro (RJ), Brasil. 62 Escola Nacional de Botânica Tropical - ENBT, Rio de Janeiro (RJ), Brasil. 73 GeneCology Research Centre, University of the Sunshine Coast, Maroochydore, Queensland, Australia. 8 9Send proofs to: 10Author for correspondence: *Eline M. Martins 11Mailing address: Diretoria de Pesquisas, Instituto de Pesquisas Jardim Botânico do Rio de Janeiro, Rua 12Pacheco Leão 915, 22460-030, Jardim Botânico, Rio de Janeiro, RJ, Brasil. Telephone number: + 55 132132042128; Fax number: +55 2138756206; e-mail: [email protected]

15Keywords: Vulnerable species, conservation genetics, Ocotea catharinensis, Ocotea odorifera, Ocotea 16porosa, microsatellite markers, in-situ conservation, priority populations.

19Running title: Genetic diversity of three Ocotea species

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2 1Abstract

2The Atlantic Rainforest in Brazil is currently comprised of small fragments due to the history of 3conversion and degradation in the last five centuries. The rainforest trees, Ocotea catharinensis, O. 4odorifera and O. porosa have been heavily harvested because of the high economic value of their timber 5and essential oils. Their respective habitats have undergone substantial reduction in area due to continuing 6anthropogenic pressures. As a consequence, these species have suffered large declines in population size 7and are now considered to be potentially vulnerable to extinction. This study investigated the patterns and 8levels of genetic diversity and inbreeding of these species using eight microsatellite markers in order to 9define priority populations for conservation management actions focusing on population enhancement 10and ex-situ germplasm collections. High genetic diversity was found for each of the species with 11moderate genetic differentiation among populations. Most populations displayed significant inbreeding 12and isolation by distance. The results provide important information to choose priority populations for 13both in situ and ex situ conservation measures.

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2 1Introduction

2 The Atlantic Rainforest in Brazil, one of the world’s major hotspots of biodiversity (Myers et al. 32000), has suffered a large loss of primary habitat due to continuous anthropogenic pressures, with only 411% of the original area now remaining (Ribeiro et al. 2009). It is mainly comprised of small fragments 5(<100 ha), many of which exhibit significant reductions in habitat quality and it is still subjected to 6processes of degradation (Ribeiro et al. 2009). Consequently, many species have experienced 7considerable declines in population size due to habitat loss and fragmentation of larger populations. This 8process has been further exacerbated by the selective logging in the remaining fragments (Lowe et al. 92005). Tree species such as Ocotea catharinensis Mez, O. odorifera (Vellozo) Rohwer and O. porosa 10(Nees & Mart.) (Lauraceae) have been heavily harvested because of the high economic value of their 11timber and/or essential oils. They have undergone particularly large reductions in population size, to the 12point that they are currently classified as vulnerable to extinction by the IUCN Red List (Varty 1998; 13Varty and Guadagnin 1998a; Varty and Guadagnin 1998b), The Official List of Brazilian Threatened 14Plant Species (MMA 2008) and O. catharinensis as vulnerable, O. odorifera and O. porosa as 15endangered by the Red Book of Brazilian Flora (Martinelli and Moraes 2013). 16 Information regarding the population genetic structure of a species is an essential component for 17species recovery programs, because genetic-related factors may facilitate the species extinction 18(Frankham and Ralls 1998; Oostermeijer et al. 2003; Leimu et al. 2006). For instance, population changes 19associated with habitat degradation and lack of species connectivity can cause an overall erosion of 20genetic diversity leading to increased genetic divergence among populations due to random genetic drift, 21elevated inbreeding and reduced levels of gene flow (Young et al. 1996). Genetic drift has the potential to 22override natural selection as the main evolutionary process within a species. The inbreeding increases as 23population sizes decrease, and subsequent deleterious effects on reproductive fitness and the persistence 24of isolated populations becomes challenging (Frankham 2003). As populations become more isolated, co- 25evolved mutualisms with pollinators and seed-dispersing animals are disrupted altering historical 26arrangements of genetic subdivision found in continuous populations of tropical tree taxa (Hamilton 271999; Dick 2001). 28 Appropriate genetic management of fragmented populations therefore requires the identification 29of populations that need to be prioritized for conservation (Petit et al. 1998; Frankham 2003). The 30development and implementation of conservation strategies must take into account the species current 31genetic diversity and population structure to recognize priority areas for both in situ and ex situ 32conservation, monitoring and protection (Shapcott et al. 2007; Stefenon et al. 2007). 33 This study investigates the structure and levels of genetic diversity and inbreeding of Ocotea 34catharinensis, O. odorifera and O. porosa with the aim of indicating priority populations for conservation 35management actions focusing on population enhancement and ex-situ germplasm collections. The specific 36objectives were to quantify the genetic diversity within and among populations across the geographic 37range of each species representing different types of vegetation and land tenure and to test if there is a 38correlation between genetic and geographic distances among populations. 39

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2 1Methods 2Study Species 3 Ocotea catharinensis occurs naturally in the South and Southeast of Brazil, being more abundant 4in montane Atlantic rainforest between 300 - 700 m a.s.l. and less frequent in Araucaria forest (Carvalho 51994; Reitz et al. 1988). The tree reaches more than 25 m in height and up to 1.5 m DBH (diameter at 6breast height). Its hermaphroditic flowers are pollinated by small insects (Carvalho 1994; Silva et al. 71998; Brotto et al. 2009) and seed dispersal has been reported to be facilitated by monkeys (Alouatta 8fusca, Silva et al. 2009; Brachyteles arachnoids, Moraes and Paoli 1999) and the bird, Pipele jacutinga 9(Galetti et al. 1997). Both B. arachnoides and P. jacutinga are considered to be endangered by the IUCN 10Red List (Mendes et al. 2008; BirdLife International 2012). Its seed germination is known to require high 11soil moisture with seedlings preferring moderate shade thereafter (Silva and Aguiar 1998; Moraes and 12Paoli 1999). The quality timber is highly sought after for building, naval construction, luxury furniture 13and its essential oil (95% linalol) is used by the perfume industry (Nakaoka Sakita and Yatagai 1992). 14Consequently, these species have been heavily harvested in the past with more than 176 000 tons of wood 15exported from Brazil between 1944 and 1951 (INP 1949-1960). 16 Ocotea odorifera is found throughout the south of the Bahia State, the Southern region and 17Southeastern region of Brazil in Atlantic Rainforest habitat although it also occurs in Araucaria forest, in 18semi-deciduous and deciduous forests (Carvalho 2005). Its trees grow up to 15 m tall with a DBH up to 191.2 m (Carvalho 1994). Small hermaphroditic flowers are followed by ellipsoid fruit with ~ 2.3 cm in 20length (Quinet 2008). Seedlings establish best in shade and initial growth rates are extremely slow (Reitz 21et al. 1978). The species does not reach reproductive maturity until 25 - 40 years of age (Oltramari et al. 222002). Seeds are likely to be dispersed by monkeys and birds (Carvalho 2005). The tree is prized for its 23essential oil with high teor in Safrol, which was used for cosmetics and folk medicine (Gemballa 1955). 24This species trade was centred in the Paraná and Santa Catarina States from where almost the entire 25production was exported (Raoul and Iachan 1948). By the 1940s the species had undergone a rapid 26population decline and conservation measures were already suggested (Machado and Souza 1948). The 27timber also has excellent structural properties and was used for building and naval construction (Pedroso 28and Mattos 1987). 29 In contrast, Ocotea porosa occurs naturally mainly in Araucaria forest in the Southern and 30Southeastern regions of Brazil, but some populations can also be found in montane rainforest (> 850m 31a.s.l.). Trees can grow up to 30 m with a DBH of 3.2 m (Carvalho 1994). The small hermaphroditic 32flowers are self-compatible; however spontaneous self-pollination is very rare (5%) due to protogyny 33(Danieli-Silva and Varassin 2012). Pollination is made by thrips (Thysanoptera; Frankliniella gardenia) 34which are responsible for either cross-pollination among different plants or geitonogamous pollination 35between flowers on the same plant (Danieli-Silva and Varassin 2012). Seeds are likely to be dispersed by 36mammals and birds (Carvalho 2003). The high quality timber was chiefly used for the manufacture of 37luxury furniture. Approximately ~280 000 m3 of wood was exported to South Africa and the USA 38between 1947 – 1967 (INP 1949-1960). Then the intense harvesting of 150 years started to become 39evident as serious decline in population size (Reitz et al. 1978). 40

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2 1 Field methods and sampling design 2 Populations of each Ocotea study species were selected from herbarium (JBRJ/JABOT; CRIA 3database) and floristic inventory data (IFFSC 2012). The sites were selected across the geographic range 4of each species in order to accurately reflect their distribution, and purposely included different vegetation 5types in both unprotected and protected areas. Adult trees were sampled at random from a total of 22 6populations throughout southern and southeastern regions of Brazil representing a sample of the known 7populations of each species (Fig. 1). It comprised of six populations of O. catharinensis, nine of O. 8odorifera and seven of O. porosa. The collected individuals were identified by a Lauraceae family 9specialist. Leaf samples of 30 plants were collected from each population. However populations with less 10than 30 individuals had all adult plants sampled. Individuals with a diameter at breast height (DBH) 11greater than 5cm were considered to be adults except for two montane O. porosa populations (Op5 and 12Op7) that had mature trees significantly smaller as a result of the habitat conditions. Samples were stored 13in silica gel prior to DNA extraction. 14 The species’ samples were collected spanning six Brazilian Federation States (Fig. 1; Table 1) in 15six protected and 11 unprotected areas. Herbarium databases indicated populations of O. catharinensis in 16Rio de Janeiro State, O. odorifera populations in Espírito Santo State, and O. porosa in Southern Region, 17but they could not be located despite an intensive field search effort. 18 19Laboratory methods 20 Approximately 0.05g of leaf from each sample was grinded using an automated Mixer Mill 21(Retsch MM200; Haan, Germany). Total genomic DNA was extracted from samples using CTAB 22procedure (Doyle and Doyle 1987) modified by Ferreira and Grattapaglia (1998) that uses two extraction 23stages with CTAB 2% and CTAB 10%. However, this method was not successful for O. catharinensis, 24which DNA was extracted using DNeasy Plant Mini-kits (Qiagen; Hilden, Germany) following the 25manufacturer’s instructions. The DNA quantifications were performed by electrophoreses in ethidium 26bromide-stained 1% agarose gels using genomic lambda DNA as standard. 27 Microsatellite analysis were conducted using eight markers developed and optimized for O. 28odorifera (Ood05, Ood07, Ood09, Ood14, Ood15, Ood16, Ood17 and Ood20; Martins et al. “in press”; 29Online Resource 1). All markers were subsequently cross-amplified in O. catharinensis and O. porosa 30samples (Martins et al. “in press”). The locus Ood16 was monomorphic in O. porosa, so it was excluded 31from the analysis of this species. All PCR reactions were performed in a total volume of 12.5 µL 32including approximately 20 ng of template DNA, 1 U MyTaq DNA Polymerase (Bioline), 1x MyTaq

33Reaction Buffer (Bioline; 1mM dNTPs, 1mM MgCl2, stabilizers and enhancers) and 0.2 µM of each 34primer, with the following cycling conditions: 94°C for 5 min, 35 cycles of 94°C for 1 min, specific 35annealing temperature for 1 min, 72°C for 1 min and a final extension step at 72°C for 10 min. The 36amplification products were verified for their expected sizes by electrophoresis using EtBr-stained 2% 37agarose gels (0.6X TBE) with 100 bp ladder (Axygen Biosciences) as size standard. The forward primer 38of each marker was directly end-labelled with a fluorescent dye (PET, NED, VIC or FAM) to enable 39multiplexed reactions for genotyping.

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2 1 The genotyping of the microsatellite fragments was conducted on AB 3500 Genetic Analyzer 2(Life Technologies Inc., Grand Island, NY, USA). The fragment size was determined based on the size 3standard GS-600 LIZ (Life Technologies Inc.) using GeneMarker software 1.91 (Softgenetics, State 4College PA, USA) and manually checked for consistency and accuracy. 5 6Data analysis 7 Allelic frequencies were used to calculate species and population measures of genetic diversity

8including the mean number of alleles per locus (A), the mean number of effective alleles per locus (Ae),

9observed (Ho) and expected heterozygosities (He), the allelic fixation index (F) and the number of private

10alleles (Apr) using GenAlEx 6.5 (Peakall and Smouse 2006). Tests for departures from Hardy–Weinberg 11equilibrium were also performed for each locus within each population by estimating Fvalues with 960 12randomizations while linkage disequilibrium was tested between pairs of loci using FSTAT 2.9.3.2 13(Goudet 2002).

14 The partitioning of genetic diversity among populations (FST), within populations (FIS) and across

15the whole species (FIT) was analyzed with Wright's F statistics (Wright 1965). In addition to test if there 16were significant differences in genetic partitioning among populations within species, PhiPT was 17calculated and an AMOVA with 999 permutations was undertaken in GenAlEx 6.5 (Peakall and Smouse 182006). Genetic relationships among individuals of the same species were visualized using Principal 19Coordinate Analyses (PCoA; Orloci 1978) with 9999 bootstrap permutations to assess the distinctiveness 20of genetic groupings between populations which was further analyzed by assignment test with 9999 21permutations and 9999 bootstraps in GenAlEx 6.5 (Peakall and Smouse 2006). The correlation between 22genetic and geographic distance matrices among populations was analyzed using a Mantel test with

23genetic distance expressed as: FST (1- FST) as described by Rousset (1997) utilizing IBDWS 3.23 24(Bohonak 2002) software. The correlations and probabilities were tested using 30000 bootstrap 25randomizations. 26 Model-based clustering was performed using the multilocus genotype data of all samples for 27each species in STRUCTURE 2.3.4 software (Pritchard et al. 2000). The default admixture model settings 28of the program were used. To determine the most likely number of groups (K) in the data, a series of 29analyses were performed with K=1 to K=7, using a burn-in of 100000 and 800000 Markov Chain Monte 30Carlo (MCMC) repetitions with ten iterations per K for O. catharinensis, K=1 to K=10 and 900000 31MCMC for O. odorifera and K=1 to K=8 and 1000000 MCMC repetitions for O. porosa. These results 32were examined using the dK method (Evanno et al. 2005) to identify the true number of clusters in the 33data as calculated by STRUCTURE Harvester (Earl and VonHoldt 2012). 34 Priority populations for in situ and ex situ conservation were identified based on genetic diversity 35within populations, level of inbreeding, number of private alleles and genetic differentiation among 36populations for each species. Moreover they were considered by the representativeness of the species 37allelic composition with the selection aiming to include the greatest allelic diversity. This was calculated 38using the formula (number of alleles in the selected populations - number of loci/number of total alleles of 39the species - number of loci) proposed by Petit et al. 1998. The highest priority populations thus scored 40where then ranked in order of conservation value and priority based on their genetic diversity (A, Ae and

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2 1He) and level of genetic uniqueness (presence of private alleles). Populations with lower levels of 2inbreeding (F) were also given higher ranking. Where a species was found in more than one vegetation 3type, the highest diversity representatives from each vegetation type were selected for conservation 4priority. In addition the size of habitat patches was weighted in favor of the largest patches and current 5level of protection was also taken into account such that unprotected populations were given higher 6ranking. 7 8Results 9Genetic Diversity 10 All loci displayed independent inheritance and no significant linkage disequilibrium was 11detected. Microsatellite signatures were highly polymorphic for each species (Table 1). Ocotea 12catharinensis had the higher number of alleles with 155 alleles found across the eight loci examined

13(AS=19.4), compared with 143 alleles in O. odorifera (AS=17.9), and 137 alleles in O. porosa (AS=17.1).

14For O. catharinensis, the population with the highest number of effective alleles (Ae = 7.6) was in Tinguá 15Biological Reserve/RJ (Oc1), which was also the largest (34 947ha) and most well-conserved remnant 16assessed for this species (Table 1). In contrast, the O. odorifera’s population with the highest number of

17effective alleles (Colombo/PR Oo4; Ae = 7.52) was located within a small fragment (< 3ha) situated in a 18degraded unprotected area (Table 1). All Ocotea porosa populations had similar number of effective 19alleles although they were generally lower than the other two species values (Table 1). Interestingly, O. 20porosa populations Op5 and Op2 located in the largest protected area and the smallest unprotected 21remnants, respectively (Op5-Guaratuba/PR, 4670ha and Op2-Bela Vista do Toldo/SC, <3ha) contained

22equal number of effective alleles (Ae = 4.75, Table 1), and there was no significant correlation between 23allelic diversity and patch size (p>0.05) for any of the three species studied. 24 Private alleles were found in all populations of O. catharinensis and O. porosa and most of O. 25odorifera with the exception of two populations located on unprotected land (Oo3 and Oo7; Table 1). For 26O. catharinensis, the population Oc1 located in a large fragment of protected forest contained the highest

27number of private alleles (Apr=20) and the population Oc2 in a small privately-owned fragment had the

28lowest number of unique alleles (Apr=2; Table 1). The population Op5 of O. porosa located in a protected

29montane rainforest fragment had the greatest number of private alleles within this species (Apr=8). Ocotea

30odorifera had fewer private alleles (mean Apr= 2.89) than the other two Ocotea species. The population in 31Colombo/PR, Oo4, located within a very small remnant (< 3ha) exhibited the greatest number of private

32alleles (Apr=8; Table 1).

33 All species had high expected heterozygosity (He=0.73; He=0.78 and He=0.64, for O. 34catharinensis, O. odorifera and O. porosa, respectively) with similar values among populations (Table 1).

35The mean expected heterozygosity (He) was higher than the mean observed heterozygosity (Ho) for all 36species (Table 1). The allelic fixation index was significant greater than zero in most populations of each 37species indicating a small heterozygote deficit across loci probably due to inbreeding (p<0.5; Table 1). 38 Ocotea catharinensis had the highest mean value of allelic fixation (F= 0.21) but this varied 39considerably among populations ranging from 0.06 to 0.30 (Table 1). Four of its six populations studied 40were significantly inbred. Mean values for O. odorifera and O. porosa populations were F=0.16 and

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2 1F=0.13 respectively, suggesting overall lower inbreeding levels than O. catharinensis. Only three of 2seven populations of O. porosa were significantly inbred, the highest allelic fixation index was found in 3the protected population, Op7 (F=0.36; P<0.05) indicating it was the most inbred population. One 4population in a protected area (Op6) had negative values of F (-0.01; not significant). Generally negative 5values of F indicate heterozygote excess, however this was not observed by Ho vs. He on Op6 6population. So this value of F, which was very close to zero, could be due to fewer samples and/or 7missing data for several individuals in this particular population. Eight of the nine populations of O. 8odorifera were inbred with the highest level occurring in the population Oo7 (F=0.30; P<0.05) and the 9lowest level in population Oo8 (F=0.02), which is near to random mating (Table 1). The inbreeding was 10not correlated with patch size (p>0.05) for any of the three species studied. 11 12Population Structure and Isolation by Distance 13 A moderate genetic differentiation was found among populations of each species; O.

14catharinensis populations had the greatest divergence (FST=0.148) and O. odorifera populations were the

15most similar (FST=0.086; Table 2). The majority of genetic diversity within each species was found within 16populations (80%, 88% and 84%, respectively for O. catharinensis, O. odorifera and O. porosa; Table 2). 17These values may indicate effective gene flow among populations before habitat fragmentation. 18 19Ocotea catharinensis 20 Most of the genetic divergence of O. catharinensis was due to the variation between the samples 21from Novo Hamburgo (Oc6) and the other populations (Oc6 mean D = 1.943; species mean D = 1.223; 22Online Resource 2; Fig. 2). The population Oc5 was also genetically distant from the other populations 23(Oc5 mean D = 1.323) but more similar to Oc1 population (Oc5 vs. Oc1 D=0.767; Fig. 2). From all 24populations analyzed, Oc2 and Oc3 were the most similar genetically (D = 0.283; Online Resource 2). 25 The population Oc6 located in Rio Grande do Sul (Fig. 1) is the most southern population and 26was the most genetically divergent population. It is genetically distinct even from the closely located 27populations, Oc2, Oc3 and Oc4 (~368 km distant; Online Resource 3). This genetic differentiation was 28particularly evident at locus Oo17, where the allelic frequencies found in Oc6 were very distinct from the 29other five populations’ frequencies (Online Resource 4). At first, there was no significant correlation 30between genetic and geographic distances among O. catharinensis populations (r = 0.5269, p = 0.08). 31Given the genetic distinctiveness of population Oc6 and the possibility of it masking other genetic- 32geographic relationships, a second Mantel test was run excluding Oc6 population. As predicted, it showed 33a significant correlation between genetic and geographic distances (r = 0.7645, p = 0.0351; Online 34Resource 5). 35 The STRUCTURE analysis suggested the existence of five groups (∆K=5) with an overlap 36between populations Oc2, Oc3 and Oc4 (Fig. 3a), consistent with PCoA results. The populations Oc5 and 37Oc6 displayed the most distinctive genotypes. The population Oc5 had high genetic diversity (Table 1) 38and different allelic frequencies as shown at locus Oo17 (Online Resource 4).

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2 1 Those results were consistent with the assignment test, which classified most of O. catharinensis 2individuals to their population of origin (93%), suggesting these populations were distinct genetically but 3still there was some allelic overlapping specially between populations Oc1, Oc2, Oc3 and Oc4 (Table 3). 4 5Ocotea odorifera 6 Genetic differentiation among populations of O. odorifera was the lowest of the three Ocotea

7species analyzed (FST = 0.086) with mean genetic distance (D) among populations of 0.687 (Online 8Resource 2). The most genetically distinct was Oo9 which segregated from the other populations (Oo9 9mean D =1.536; Online Resource 2; Fig. 4). The population Oo1 was also slightly different from the other 10populations (Oo1 mean D = 0.701). Both of these populations (Oo1 and Oo9) are also the most distant 11geographically from the other populations (Fig. 1) and the genetic distance among populations was 12strongly correlated with the geographic distance for O. odorifera (r = 0.6672, p = 0.0000; Online 13Resource 5). 14 The STRUCTURE analysis defined four different origins (∆K=4; Fig. 3b) with high overlap 15among populations Oo1 to Oo8 consistent with PCoA analysis (Fig. 4). The genetic distinctiveness of the 16population Oo9 can be observed in differences in the allelic frequencies at locus Oo14 (Online Resource 176). The assignment test classified most of the individuals to within their population of origin (73%) and 18again indicated the genetic distinctiveness of the population Oo9 (Table 3). This result also shows a much 19greater overlap of individuals among most of the populations of O. odorifera. 20 21Ocotea porosa 22 Ocotea porosa had most of its genetic variation partitioned between the two more southern 23populations (Op6 and Op7, Fig. 1) and the other populations (between-groups mean D = 0.689; species 24mean D = 0.521; Online Resource 2). Op6 is a small population (n=8) in a very small fragment (Table 1) 25and is genetically depleted. The populations Op1 and Op5 were slightly distinct from populations Op2, 26Op3 and Op4 and there was a significant correlation between genetic and geographic distances among 27populations (r = 0.5902, p = 0.0313; Online Resource 5). 28 A strong overlap between populations Op2, Op3 and Op4 was detected based on the 29STRUCTURE analysis (Fig. 3c) that determined four different origins and on allelic frequencies as 30observed at locus Oo15 (Online Resource 7). These results are congruent with the PCoA analysis of the 31distribution of diversity in O. porosa (Fig. 5). The populations Op6 and Op7 though closely located (58 32km; Online Resource 3), were slightly distinct (Fig. 3c). The populations Op1 and Op5 showed some 33overlap with the other populations. Assignment tests classified 91% of the individuals to within their 34population of origin and indicated the genetic distinctiveness of population Op7 with no individual from 35other populations (Table 3). The population Op6 was not considered in the assignment test because of its 36small number of individuals.

37 38Conservation Issues 39 A total of 17 populations were indicated as priority for both in situ and ex situ conservation 40regarding to conserving the genetic diversity of the studied species (Table 4). Populations showing the 1 9

2 1presence of unique alleles, high genetic diversity, low inbreeding and representative of the different types 2of vegetation were prioritized. The five O. catharinensis populations selected represent 84% of all allelic 3diversity sampled in this study. The seven O. odorifera populations have 78,48% of the 4representativeness of allelic composition and for O. porosa the five priority populations for conservation 5encompass together 79% of the allelic diversity. 6 7Discussion 8Population Genetic Structure of Ocotea species 9 Reductions in population size and connectivity are known to eventually result in the random loss 10of rare alleles, while some alleles may become fixed within each fragment by genetic drift. Subsequent 11inbreeding may accelerate the loss of heterozygosity (Fuchs and Hamrick 2011). Levels of genetic 12diversity found in the present study for each of the three species were considerably higher than that found 13in previous studies using allozyme markers at local scale (Ocotea catharinensis – Tarazi et al. 2010; O. 14odorifera - Kageyama et al. 2003; Ocotea porosa - Bittencourt 2004; Daros - 2006). This is not surprising 15since microsatellites are more polymorphic than allozymes (Zhu et al. 2000; Guichoux et al. 2011; Zalapa 16et al. 2012), and also the present study encompassed a broader geographical scale than the previous ones. 17It has been well documented that species with wide geographic distribution frequently possess high 18genetic variation (Hamrick et al.1979). 19 Ocotea odorifera has a widespread occurrence from south of Bahia to southern Brazil (~2000 20km; Fig. 1) and occurs within different vegetation types and across ill-defined altitudinal gradients. This 21species showed the highest genetic diversity and lower differentiation among populations in this study, as 22expected by its broader occurrence. Although O. catharinensis has a similar geographic range, it has quite 23restricted habitat preferences and it is found mainly in patches of montane rainforest, resulting in the 24highest genetic differentiation among populations. In contrast, Ocotea porosa is geographically more 25limited (~900 km) and occurs mostly in Araucaria forest in the southern Brazil. Nevertheless, within its 26extension of occurrence, suitable habitat is relatively continuous. So this species displayed slightly lower 27levels of genetic diversity than the levels found for O. catharinensis and O. odorifera in the current study, 28but still higher than previous studies results for this species. 29 The structure of genetic diversity in each of the three species was distributed mostly within 30populations (more than 80%) as expected for outcrossed, long-lived tree species (Hamrick and Loveless 311989; Hamrick and Murawski 1991). There was considerable genetic differentiation among O. porosa’s 32studied populations (PhiPT = 0.164). The populations Op6 (São Francisco de Paulo-RS) and Op7 33(Cambará do Sul-RS) possessed similar genotypes but were genetically divergent from the other five 34populations suggesting a geographic isolation. For instance, population Op7 (Cambará do Sul/RS) occurs 35within small patches of cloud forest set amongst an extensive grassland matrix at high altitude (Pillar and 36Quadros 1997). 37 The heavily exploited species, O. odorifera, exhibited the highest level of within-population 38genetic diversity and the lowest but still moderate level of genetic differentiation among populations of 39the three species (PhiPT = 0.119). This is consistent with the findings using allozyme (Kageyama et al. 402003) which detected a similar pattern of high genetic diversity and genetic structure in two near

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2 1populations of this species in São Paulo State (θP= 0.028). This is likely due to O. odorifera’s previous 2occurrence, prior to logging activities, throughout relatively continuous habitat across a broad geographic 3range, as well as the fact that long generation times tend to restrict the loss of genetic diversity (Hamrick 4et al 1979). However, the population Oo9 (Lavras-MG) was genetically eroded compared with all other 5populations. This population was inbred, genetically dissimilar from other populations and had high 6allelic fixation index. These results are consistent with loss of genetic diversity due to fragmentation, and 7it was aggravated due to its patch size of less than three hectares and isolation in a landscape impacted by 8intense clearing and over-exploitation, with most of the remaining fragments in this region also occupying 9tracts of less than 10ha (Oliveira-Filho et al. 1994; Teixeira and Barros 1992). 10 Ocotea catharinensis had the highest genetic differentiation between populations (PhiPT = 110.205) so we suggest that even before logging populations were already differentiated. This can be due to 12the restricted natural distribution of suitable habitat in patches resulting in limited opportunities for gene 13flow. A previous study analyzing four populations of O. catharinensis in Santa Catarina State (greater

14distance between populations: 202 km) had similar genetic differentiation (FST = 0.1175; Tarazi et al. 152010) corroborating our results. Moraes and Paoli 1999 found that seed dispersal by the monkey 16Brachyteles arachnoides may reach over 1Km and each animal disperses ~50 seeds per day. In contrast, 17Jacutinga birds (Pipele jacutinga) stay up to ten days in the same tree, and then almost all seeds are 18dispersed under the mother plant (Galetti et al. 1997). Such variation in dispersal mechanisms may 19explain the patterns of differentiation among populations of O. catharinensis. This species had a high 20number of private alleles, probably due to patchy population distribution. Interestingly, population Oc1 21(Tinguá-RJ) exhibited high numbers of effective and private alleles far above mean values for the species. 22This population is highly diverse, but possibly isolated in terms of gene flow. Although the population 23Oc5 (Santa Teresa-ES) was more similar to Oc1, it still have a divergent genotype and should be 24considered a priority population for conservation purposes. The population Oc6 (Novo Hamburgo-RS) 25had low genetic diversity and highly divergent genotypes, probably due to its geographic isolation. It is 26located in a depression behind a range of mountains, quite disjunct from other rainforest fragments (E. 27Martins, personal communication). 28 Previous research into O. porosa has found pollen dispersal to be quite restricted (Danieli-Silva 29and Varassin 2012). All three species in this study displayed moderate to high levels of inbreeding in 30some of their populations which may be due to restricted pollinator dispersal. However, the levels of 31inbreeding for O. porosa in this study were lower than found by Bittencourt (2004) which may possibly 32be due to the higher levels of polymorphism detected by microsatellites. Breeding system and life form 33are strongly correlated to the genetic structure and diversity in natural plant populations (Hamrick and 34Godt 1996). Assuming that O. catharinensis and O. odorifera have similar pollination system of O. 35porosa (thrips), the highly inbred populations may be a consequence of the limited flight capabilities of 36these insect pollinators (Danieli-Silva and Varassin 2012). This may also explain why so many private 37alleles were found for the three Ocotea species studied here and previously by Bittencourt (2004). 38 Plant longevity may ensure the representation of many generations in the current population and 39consequently different genotypes can be maintained more effectively (Aparicio et al. 2012). Therefore, 40genetic drift would be expected to have the least impact on long-lived species (Hamrick et al.1979; Hartl

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2 1and Clark 1989; Lowe et al. 2005). The high overall genetic diversity and moderate genetic structure (FST) 2found in these three species of Ocotea may be explained by their long generation times counteracting 3recent habitat loss and population reductions. Due to intense exploration and habitat fragmentation, we 4would expect higher levels of genetic differentiation among populations for these three species. However 5our results indicate that there has been considerable gene flow among populations historically, when the 6biome was more continuous prior to habitat fragmentation and selective logging, except for O. 7catharinensis studied populations that we believe they were already differentiated before logging. 8Aparicio et al. (2012) analyzed the correlation between the effect of habitat fragmentation and plant 9species’s life span on the genetic diversity and population genetic structure within the same landscape 10context. They found that diversity measures clearly and consistently increased from the most short-lived 11species to the longest. 12 The individuals sampled for this study may belong to the second generation after the period of 13intensive harvesting. But some individuals could be remnants from before this time and they may be 14acting as reservoirs of diversity, particularly as overlapping generations are also known to have the 15potential to mitigate the loss of genetic diversity via within-population gene flow, leading post-logging 16analyses to underestimate the genetic impacts of such intensive exploitation (Lowe et al. 2005). An 17analysis of seedlings’ genetic diversity may detect the result of these deleterious effects on the species, as 18found for O. porosa in Paraná State an excess of homozygotes in the seedlings in relation to adults in the 19same population (Daros, 2006). However the seedlings’ analysis might be hampered in the studied 20populations because extremely few seedlings were observed in three populations (Oo1, Oo2 and Oc1), 21and none in all other populations for the three species (E. Martins, personal communication). 22 23Identification of priority populations for conservation 24 The findings from this study show that even small forest fragments (eg. Oo4-Colombo/PR; Oo7- 25Marcelino Ramos/RS; Table 1) possess high levels of genetic diversity and that both unprotected and 26protected areas have different allelic frequencies and distinct genotypes (eg. Oc6-Novo Hamburgo/RS; 27Oc1-Tinguá/RJ). Thus, regardless of these attributes, each population may have an important function on 28the maintenance of overall species genetic diversity. The selected populations are described in Table 4 29and ranked according to highest value for conservation based on genetic diversity and uniqueness. 30 Ocotea catharinensis populations were quite differentiated genetically, so all populations, apart 31from Oc2 (Ituporanga/SC), have high conservation value with regard to preserving the current level of 32genetic diversity within this species making it hard to identify single populations of higher value (Table 334). The population Oc2 were excluded because it displayed a marked genetic similarity with Oc3 34(Taió/SC), however the latter had higher number of private alleles and is located in a larger fragment, 35therefore it would better represent the genetic diversity of this area. Oc3 has already been indicated by 36government agencies as priority area for conservation (MMA 2007), although the site is as yet un- 37protected area our results will hopefully reinforce the importance of this site as a fragment requiring 38immediate conservation. 39 Ocotea odorifera populations were less differentiated; however some populations were quite 40genetically distinct, such as Oo1-Tinguá/RJ and Oo9-Lavras/MG suggesting their importance for both in

1 12

2 1situ and ex situ conservation strategies of O. odorifera. Populations Oo7 (Marcelino Ramos/RS) and Oo8 2(Três Cachoeiras/RS) were also quite genetically divergent from the other populations and defined as 3priority populations too. The first one was unique for representing a population in semi-deciduous forest 4despite being relatively genetically eroded, which urges its necessity of conservation actions. Population 5Oo4 is likewise an important population for conservation, although it is located within a small and 6degraded unprotected fragment (<3ha). The Oo4 plants had many private alleles and displayed high 7number of effective alleles. The populations Oo2 and Oo3 were genetically similar, but Oo2 have a 8considerable in situ conservation value, due to its higher number of private alleles and effective alleles 9than Oo3 and thus has been given higher conservation priority (Table 4). 10 Ocotea porosa showed distinct genotypes that are represented in the five populations selected for 11conservation (Table 4). Only populations Op2 and Op6 were not assigned as priority for conservation. 12Population Op2 genotypes were already represented by populations Op1 and Op4 while population Op6 13was genetically similar to Op7. This latter population was deemed more important for conservation as it 14not only had a higher number of private alleles, but represents a different vegetation ecotype (montane 15rainforest; Table 4). 16 Some of the selected priority populations are already protected by Brazilian government laws 17(eg. Oc1; Oc4; Oo1; Op7), however they need more effective conservation measures to be implemented. 18There are still illegal logging, livestock grazing and illegal hunting happening in many protected areas, 19due to lack of monitoring and supervision. For instance, in the Tinguá Biological Reserve (created in 201989) has still illegal hunting of some species. The bird Pipele jacutinga, which is seed disperser of many 21plant species as Ocotea species, is considered extinct there (Fernandez and Travassos 2006). In addition, 22the conservation of suitable habitat for seedling recruitment and growth needs to be guaranteed. In the 23populations studied, seedlings were not detected in most of populations and areas nearby, except at 24Apiúna/SC (Oo2; one individual of O. odorifera) and Tinguá/RJ (Oo1 and Oc1). Thus, simply preserving 25the remaining genetic diversity of the three Ocotea species within protected areas may not be enough to 26guarantee the persistence of future generations without adequately first investigating factors affecting the 27recruitment of seedlings. 28 29Conclusions 30 We have found that three Ocotea species have relatively high levels of genetic diversity with 31moderate genetic differentiation among populations. As a consequence, we suggest that some populations 32assessed in this study should be conserved in situ and its plants should be used for ex situ conservation, in 33order to preserve the species overall genetic diversity and the presence of unique alleles. This study 34showed that even populations on small parcels of unprotected land and in degraded areas have 35conservation value and should be preserved. Some populations could act as connectors between 36fragments, corridors and/or stepping stones, regarding its location, to promote effective gene flow among 37populations and minimize inbreeding effects inside populations. Government programs are now essential 38to ensure the implementation of the recommendations arising from the current and previous studies of 39these over-exploited Ocotea species, particularly with regard to threat abatement, restoration and 40conservation management strategies into the future.

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2 1 2Acknowledgments 3We would like to thank Centro Nacional de Conservação da Flora (CNCFlora) for financial support. 4Thanks also to the GeneCology Research Centre (University of the Sunshine Coast, Australia) and 5Instituto de Pesquisas Jardim Botânico do Rio de Janeiro (JBRJ, Rio de Janeiro, Brazil) for technical 6assistance and the use of their respective laboratory facilities. The first author is grateful for the sandwich 7scholarship provided by Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES).

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6Figure titles:

7Fig. 1: The location of the (a) Ocotea catharinensis, (b) O. odorifera and (c) O. porosa populations in 8South and Southeast regions of Brazil. (a) Oc1, Nova Iguaçu (RJ); Oc2, Ituporanga (SC); Oc3, Taió (SC); 9Oc4, Guaratuba (PR); Oc5, Santa Teresa (ES) and Oc6, Novo Hamburgo (RS). (b) Oo1, Nova Iguaçu 10(RJ); Oo2, Apiúna (SC); Oo3, Taió (SC), Oo4, Colombo (PR); Oo5, Guaratuba (PR); Oo6, Ponta Grossa 11(PR); Oo7, Marcelino Ramos (RS); Oo8, Três Cachoeiras (RS) and Oo9, Lavras (MG). (c) Op1, 12Itaiópolis (SC); Op2, Bela Vista do Toldo (SC); Op3, Mafra (SC), Op4, Ponta Grossa (PR); Op5, 13Guaratuba (PR) and Op6, São Francisco de Paula (RS); Op7, Cambará do Sul (RS).

14Fig.2: Genetic relationship between all Ocotea catharinensis individuals as shown by principal 15coordinate analysis (PCoA). Symbols indicate the population. Axis 1 accounts for 34.06% and axis 2 for 1619.84% of the variation in the data.

17Fig. 3: STRUCTURE analysis for (a) Ocotea catharinensis populations based on 8 microsatellite loci. 18The K used was from 1 to 7, with the highest ∆K=5. (b) O. odorifera populations based on eight 19microsatellite loci. The K used was from 1 to 9, with the highest ∆K=4. (c) O. porosa populations based 20on seven microsatellite loci. The K used was from 1 to 8, with the highest ∆K=4.

21Fig. 4: Genetic relationships between all Ocotea odorifera sampled individuals calculated by principal 22coordinates analysis (PCoA). Symbols indicate the populations. Axis 1 accounts for 45.32% and axis 2 23for 16.10% of the variation in the data.

24Fig.5: Genetic relationships between all Ocotea porosa sampled individuals as shown by Principal 25Coordinates analysis (PCoA). Symbols indicate the populations. Axis 1 accounts for 26.79% and axis 2 26for 19.35% of the variation in the data.

28 29

1 19