Conserv Genet (2014) 15:441–452 DOI 10.1007/s10592-013-0552-1

RESEARCH ARTICLE

Where did they come from? Genetic diversity and forensic investigation of the threatened palm species

Alison Gonc¸alves Nazareno • Maurı´cio Sedrez dos Reis

Received: 19 August 2013 / Accepted: 18 November 2013 / Published online: 22 November 2013 Springer Science+Business Media Dordrecht 2013

Abstract Few studies have assessed the genetic diversity Our results provide information that can be used to help that exists in individuals that were illegally-traded. In this support B. eriospatha conservation. paper, we evaluate the genetic consequences of illegal trade of the palm species Butia eriospatha. Although it is Keywords Á Assignment test Á protected by Brazilian environmental law, information Conservation genetics Á Illegal trade about the genetic consequences of illegal trading which can be used to support conservation planning is still needed. The two main questions approached were: (a) do illegally- Introduction traded individuals have higher levels of genetic diversity than those found in wild populations; and (b) where did the Hundreds of millions of and animals species around illegally-traded individuals come from? To answer these the world have been hunted and caught for food, leather, questions, we used nine microsatellite loci to quantify the and medicine (Kate and Laird 1999; Arroyo-Quiroz et al. genetic diversity in eight wild populations (n = 390) and 2007; Larsen and Olsen 2007) and the majority are sold to one group of individuals (n = 50) planted in an urban area private collectors (Alves and Filho 2007; Rosa et al. 2011; of Southern . For the forensic investigation, an Natusch and Lyons 2012). While some of this trade is legal assignment exclusion-test was performed. Remarkably, the and does not harm wild populations, an alarmingly large illegally-traded B. eriospatha individuals had more genetic proportion is illegal (Redford 1992; Destro et al. 2012), variation than all of the studied wild B. eriospatha popu- putting many wild and animal species on the verge of lations, suggesting that there is no single target population extinction (Redford 1992; Wilkie et al. 2011). used by poachers. Accordingly, the multilocus assignment Some examples of illegal and unsustainable wildlife test indicated that the urban B. eriospatha individuals came trade are well documented, such as poaching of elephants from a variety of different populations, with 46 % coming for ivory (Wasser et al. 2004, 2010), bears for their skin, from populations not surveyed in this study. In light of claws and canines (Shepherd and Nijman 2008), rhinos for these results, we discuss the very real problem of illegal their horn (Graham-Rowe 2011), and felines for their skin trading of B. eriospatha that must be quickly addressed. and bones (Kenney et al. 1995; Check 2006). A long-term study in India showed that at least four leopards (Panthera pardus) have been poached every week for the past decade (Mutterback 2012). Another problematic example comes Electronic supplementary material The online version of this from Brazil where due to illegal trafficking, the bird spix’s article (doi:10.1007/s10592-013-0552-1) contains supplementary material, which is available to authorized users. macaw (Cyanopsitta spixii, ararinha-azul) is now extinct in the wild, with only 79 individuals left in the world (e.g. A. G. Nazareno (&) Á M. S. dos Reis Qatar, Spain, Germany and Brazil) all being raised in Nu´cleo de Pesquisas em Florestas Tropicais, captivity (Foldenauer et al. 2007). But the exploitation of Federal University of , CP 476, Floriano´polis, Santa Catarina 88040-900, Brazil species is not a new phenomenon. During the colonial e-mail: [email protected] period, the Brazilian tree ‘Pau Brasil’ (Caesalpinia 123 442 Conserv Genet (2014) 15:441–452 echinata) was harvested and sent to Portugal in such large them as decorative plants are aware of their vulnerability. quantities that the species almost became extinct (Bueno Furthermore, the habitat in which this vulnerable palm 2006). Likewise, at the beginning of the 20th century in occurs (highlands or campos de altitude) is not adequately Southern Brazil, the population of the Brazilian , protected by conservation policies (Overbeck et al. 2007). angustifolia, was almost completely decimated Even more concerning is the fact that the Atlantic Forest (Carvalho 2006). (with scattered, discontinuous grassland areas, especially on Around the word, the illegal trade of species and their the plateaus in the southern region) has been reduced to about products is a lucrative business, providing high returns with 7 % of its original area (Morellato and Haddad 2000). relatively little risk (Destro et al. 2012). In Brazil, nearly 40 Despite the significant fragmentation of the biome, million animal specimens are captured from the wild annu- researchers estimate that there are at least 20,000 plant ally, representing a total retail value of approximately species occurring in the biome (Myers et al. 2000), many of US$2.5 billion a year (RENCTAS 2011). However, this which are also at severe risk of extinction. amount is an underestimate; it does not consider the illegal Although B. eriospatha is protected by Brazilian law trade of plants as data on plant poaching is rare. The orna- (Instruc¸a˜o Normativa 06, MMA 2008), information about mental plants of some botanical families (e.g. Orchidaceae, the genetic consequences of illegal harvesting is still needed Cactaceae, Bromeliaceae and Cyatheaceae) and timber tree in order to effectively support conservation programs. From species (e.g. Swietenia macrophylla) are the most traded this point of view, the goals of this study were to: (i) quantify plants in Brazil. According to the database of CITES (Con- and compare the genetic diversity of wild B. eriospatha vention on International Trade in Endangered Species of populations with a group of individuals that have been ille- Wild Fauna and Flora that enforces regulations on Interna- gally traded and are now planted in urban areas, around tional Trade of species) during the period from 2006 to 2010, luxurious homes, malls and public gardens in Southern International trade in S. macrophylla alone reached an esti- Brazil; (ii) estimate the genetic differentiation between mated value of US$168 million (CITES 2010). studied wild populations; and (iii) determine the originating Even though some species are protected by environ- population of the planted urban B. eriospatha individuals. To mental laws and by International agreements, we need to address these questions we used nine polymorphic micro- address trafficking of species from a multi-stakeholder satellite loci and assessed the likely originating population of approach in order to inform, facilitate and support con- the illegally traded B. eriospatha individuals using Bayesian servation plans and to reduce this serious threat facing assignment tests. In previous studies, nuclear microsatellites biological diversity. Furthermore, identifying and protect- and allozymic variation in wild populations of B. eriospatha ing species that are jeopardized by illegal trade, such as the revealed significant genetic differentiation among popula- vulnerable palm species Butia eriospatha (IUCN 2012), tions (Reis et al. 2012; Nazareno and Reis 2013). This can act as an insurance policy to preserve not only the regional feature of genetic variation, which is fundamental in future of the species, but also the futures of the species’ determining the origins of individuals by assignment tests ecological communities. (Manel et al. 2002; Guinand et al. 2004), and their irregular In Brazil, individuals of B. eriospatha have a high orna- distribution throughout Atlantic Forest highlands allowed us mental value, approximately US$3,000, an amount which is to test two linked hypotheses: (1) the illegally traded B. one hundred times more than the price that poachers pay to eriospatha individuals come from multiple source popula- landowners. In Europe and North America, where this spe- tions since the current distribution of native plants is so cies is also sold, its price varies depending on the stem size. fragmented; and (2) due to their origins from multiple dif- Interestingly, in a forum from one US website (http://forums. ferentiated populations, the illegally traded B. eriospatha gardenweb.com) we found the following dialogue: ‘‘We individuals have more genetic diversity than those in distinct were attracted to the B. eriospatha because they’re a real wild B. eriospatha populations. Our results provide impor- feather palm and we want them to be at the front of our tant information for decision-makers to help support con- building—along with bananas, hibiscus, etc.—to set the servation strategies of this threatened palm species as well as tropical tone. But at this point, the nearest I’ve found any combat B. eriospatha trafficking in Brazil and abroad. sizable trees is Holland……… or Brazil’’.A respondent then goes on to name an alternative source to purchase this species in California. All B. eriospatha individuals sold abroad and Materials and methods in Brazil are illegally poached, as they could not be the result of several generations of sub-cultivation. Thereby, their Study species desirability and market value, as noted through the above exchange, underscore the susceptibility of this species to The slow-growing palm B. eriospatha (Fig. 1)isa illegal trade. However, not all those who seek to purchase monoecious species locally known as butia´-da-serra.This 123 Conserv Genet (2014) 15:441–452 443

Fig. 1 Individuals of Butia eriospatha (Martius ex Drude) Beccari in wild population (A) is surrounded by roadways (arrow) making a clustered wild population (A) and in a public garden in the city of access to these areas easier for illegal harvesting Floriano´polis (B), both in Santa Catarina State, Southern Brazil. The long-lived palm species is endemic to the Atlantic Forest sampled. The number of B. eriospatha individuals sampled and grows in highlands (or campos de altitude, a subtype of per population was 29 for population D, 41 for population the Atlantic Forest Domain). Their populations, which are C, and 50 for A, B, E, F and H. Except for populations C restricted to this specific habitat, generally consist of and D, in which samples from all individuals were col- mature individuals aged 100 years or older. Populations lected, the B. eriospatha individuals were sampled at 50 m often occur in dense and extensive clustered distributions intervals to avoid sampling from relatives. In addition, a (i.e. population-islands), known as butiazais (Fig. 1a). group of 50 B. eriospatha individuals (all are reproductive Some populations are on roadside verges and many of them and with height above 5 m) were sampled from a non- are located on private properties. To our knowledge, there native, urban area (X in Fig. 2). These plants were har- is no B. eriospatha population protected in nature reserves. vested illegally and planted in malls, and public and private Mating system analyses reveal that B. eriospatha gardens (Fig. 1b) in the city of Floriano´polis, Santa Cata- (2n = 32; Correa et al. 2009) is predominantly an out- rina, Southern Brazil. The B. eriospatha population nearest crossing species, although it is self-compatible and repro- to the city of Floriano´polis is 200 km away. Considering duction can occur by geitonogamy (Nazareno and Reis the species is slow-growing and it takes 60–100 years for a 2012). Illegal trafficking of B. eriospatha, along with other B. eriospatha individual to reach five meters in height threats facing the species (e.g., cattle grazing; Nazareno (information obtained from interviews with landowners), it and Reis 2013), have contributed significantly to the spe- is likely that the plants in the urban area come from natural cies becoming at risk of local extinction due to a contin- populations and have not been grown from seeds. All of the uing decrease in the number of reproductive individuals. natural populations included in the study have been impacted by anthropogenic activities such as cattle farm- Sampling and study area ing, deforestation and the introduction of exotic species (e.g. Pinus sp.) that are cultivated in large homogeneous As the assignment test applied herein does not require stands (Nazareno and Reis 2013). extensive sampling over the species’ native range (see explanation below), we sampled eight of 14 wild popula- Data analysis tions of B. eriospatha located in Santa Catarina State, Western Plateau, Southern Brazil (A–H in Fig. 2). The microsatellite data analyses followed two approaches. Although there are other B. eriospatha populations in Santa Our primary interest was in verifying the level of genetic Catarina State, we focused our sampling in populations diversity in wild populations as compared to a group of located within close proximity to highways (see Fig. 1a) illegally-traded B. eriospatha individuals. Secondly, in because we believe that these populations are more sus- order to identify the originating population of the illegally ceptible to illegal harvesting. We do not provide the exact traded B. eriospatha individuals, we checked the genetic locations of natural populations in this study in order to homogeneity of each wild population using a Bayesian reduce the risk of poaching. A total of 360 reproductive B. model. For forensic investigations, we conducted one eriospatha individuals, above five meters in height, were exclusion-simulation method of assignment, based on 123 444 Conserv Genet (2014) 15:441–452

Fig. 2 Highlands (dark gray areas) in the Atlantic Forest (IBGE 2004) where Butia eriospatha (Martius ex Drude) Beccari can occur in Southern Brazil (States of Parana´, Santa Catarina and ). The black circles indicate the eight natural populations (A–H) and one urban area (X) from which genetic samples were obtained in Santa Catarina State, Southern Brazil

multilocus genotype data, in order to determine the likely with silver nitrate. Allele sizes were estimated by compari- origin of the illegally traded B. eriospatha individuals. son with a 10 base pair DNA ladder standard (Invitrogen, Carlsbad, CA, USA). Genotyping and genetic analyses Deviation from the Hardy-Weinberg equilibrium and linkage disequilibrium were tested for each B. eriospatha Genomic DNA extraction from leaves was conducted using population. The significant levels for linkage equilibrium the NucleoSpin kit (MACHEREY–NAGEL GmbH & Co. were modified for multiple comparisons by Bonferroni KG), according to the manufacturer’s instructions. Ampli- correction (Rice 1989). Allele frequencies and the fol- fication protocols for nine microsatellite loci are described in lowing parameters were then calculated: allelic richness

Nazareno et al. (2011). Amplification products were dena- (AR), number of private (AP) and rare alleles (R; defined as tured and separated with 10 % polyacrylamide gels stained those with a frequency of less than 5 %), observed 123 Conserv Genet (2014) 15:441–452 445

heterozygosity (HO), and expected heterozygosity (HE, Nei iterations and 500,000 data iterations. In order to estimate the 1978). Rarefaction approach was used to standardize A to appropriate number of populations, we estimate DK as an ad the smallest sample size in each comparison. All of these hoc quantity related to the second order rate of change of the analyses were run using the program FSTAT 2.9.3.2 log probability of data with respect to the number of clusters, (Goudet 2002). In order to compare the average values of as proposed by Evanno et al. (2005).

AR, HO and HE between wild populations and the group of To identify a possible source population for the illegally illegally traded B. eriospatha individuals, the 95 % confi- traded individuals of B. eriospatha, individual assignment dence interval of the standard error of these parameters tests were performed using a Bayesian multilocus-approach were calculated using a jackknife procedure across all loci. (Rannala and Mountain 1997), implemented in the Gene-

The inbreeding index (FIS) was also estimated and its Class 2.0 (Piry et al. 2004). Prior to assignment tests, we significance (determined by 10,000 permutations across all verified the applicability of the Bayesian method using loci) tested using the SPAGeDi program (Hardy and Ve- Rannala and Mountain (1997) for our dataset in GeneClass kemans 2002). 2.0. For this procedure, all individuals of the reference The genetic differentiation was estimated using an population (the eight sampled populations) were self-clas- unbiased estimator (with respect to sample size) of FST sified within the sampled populations using self-assignment (Weir and Cockerham 1984) with FSTAT 2.9.3 (Goudet (leave-one-out procedure; Efron 1983). For this approach, 2002). Null allele frequencies were assessed for all popu- the program excludes one sample from one population and lations using the Microchecker software V 2.2.0 (van Oo- runs assignment tests against the rest of the data, calcu- sterhout et al. 2004). If significant homozygosity was lating a mean value of the scores of each individual in the detected at a given locus, it was dropped and a modified population to which it belongs. average FIS over loci was calculated. Significance was In the Bayesian model-based assignment test imple- calculated from jackknife over loci. Likewise, estimates of mented in GeneClass 2.0, the assumption that the true pop- genetic differentiation between populations were calcu- ulation of origin has been sampled is not required. The lated using the ENA method (10,000 permutations) exclusion simulation method was calculated based on the implemented in FreeNA (Chapuis and Estoup 2007), which resampling algorithm described in Paetkau et al. (2004). In corrects for the presence of null alleles. Furthermore, FST the GeneClass 2.0 program, the allele frequencies from a values calculated with FSTAT 2.9.3 and FreeNA were used sampled population are used to compute the likelihood of a to investigate isolation by distance pattern. The relation- genotype occurring in the population; it compares the like- ship between the matrix of the logarithm of geographical lihood of the specific genotype to a distribution of the like- distances and the matrix of pairwise genetic distance [FST/ lihoods of simulated genotypes for each investigated (1 - FST), Rousset 1997] was analysed via a Mantel’s test population. In our analysis, the genotypes were generated by (Mantel 1967) with 30,000 randomizations using the pro- MCMC simulations of 10,000 individuals for each of the gram IBDWS 3.23 (Jensen et al. 2005). sampled B. eriospatha populations. In order to exclude an individual from all but the true population of origin, one strict Identification of genetic units and forensic analysis criterion was chosen (p value of 0.001; i.e. if a specific genotype is observed less than once in 1,000 randomly In order to test whether B. eriospatha populations were simulated genotypes, the population will be excluded as the genetically differentiated without a priori classification of origin). Using GeneClass2.0, we also performed an exclu- individuals, a Bayesian model was executed in a Markov sion test based on allele frequencies to calculate likelihoods Chain Monte Carlo (MCMC), as implemented in the struc- (Paetkau et al. 1995) to determine the most likely candidate ture program, version 2.3.4 (Hubisz et al. 2009). In this population from the non-excluded populations. No addi- model, the number of populations, K, is treated as a param- tional analysis to correct null alleles was performed, since eter processed by the MCMC scheme without any approxi- Carlsson (2008) has show that microsatellite loci affected by mation providing a better estimation of K. Based on the null alleles do not alter the overall outcome of this test. spatial configuration and distribution of the sampled B. eriospatha populations and high allozyme variation between

B. eriospatha populations (FST = 0.36, Reis et al. 2012), we Results performed our analysis under the assumption that the allele frequencies in different populations are not correlated with Genetic diversity one another and that alleles carried at a particular locus by a particular individual originated in some known population A total of 440 individuals from the wild populations and (no admixture model). The K was set from 2 to 8 with each the urban area were surveyed (Table 1), in which 57 alleles K estimate replicated 15 times with 100,000 burn-in were identified across nine microsatellite loci. As expected, 123 446 Conserv Genet (2014) 15:441–452

Table 1 Population genetics estimates for eight Butia eriospatha (Martius ex Drude) Beccari populations sampled in Santa Catarina State, Southern Brazil. Estimates for a group of 50 B. eriospatha individuals sampled in an urban area, in Floriano´polis, Santa Catarina, are also presented

1 Samples NnKAP/R AR (CI95 %) HE (CI95 %) HO (CI95 %) FIS FIS

A 490 50 26 0/3 2.89 (± 0.15) 0.49 (± 0.03) 0.43 (± 0.02) 0.13* 0.08* B 610 50 30 0/5 3.33 (± 0.16) 0.47 (± 0.02) 0.42 (± 0.01) 0.12* 0.08* C 41 41 23 0/1 2.56 (± 0.22) 0.40 (± 0.02) 0.22 (± 0.01) 0.46* 0.12* D 29 29 28 0/4 3.11 (± 0.17) 0.49 (± 0.02) 0.47 (± 0.02) 0.04 0.00 E 120 50 29 1/2 3.22 (± 0.15) 0.52 (± 0.01) 0.35 (± 0.01) 0.32* 0.13* F 150 50 26 0/4 2.88 (± 0.08) 0.49 (± 0.01) 0.29 (± 0.03) 0.41* 0.12* G 40 40 25 0/2 2.67 (± 0.10) 0.47 (± 0.02) 0.29 (± 0.02) 0.38* 0.13* H 100 50 33 2/10 3.67 (± 0.18) 0.50 (± 0.03) 0.43 (± 0.01) 0.15* -0.06 X 200 50 44 9/12 5.11 (± 0.22) 0.62 (± 0.03) 0.40 (± 0.02) nc nc

The genetic parameters AR and HE are significantly different between wild populations (A–H) and the group of illegally traded individuals (X) according to the 95 % confidence interval

N estimate of population size, n sample size, K number of alleles, AP number of private alleles, R number of rare alleles (here defined as alleles with a frequency of less than 5 %), AR allelic richness by rarefaction based on the minimum sample size of 29 individuals, HE and HO expected 1 and observed heterozygosity respectively, FIS inbreeding index, FIS inbreeding index excluding the loci segregating for null alleles, CI95 % 95 % standard error calculated by the jackknife method * Significant at p \ 0.05. nc, not calculated

the allelic richness (AR) and expected heterozygosity (HE) was positive and significantly different from zero for all but in the illegally traded B. eriospatha individuals differed one population (Table 1), the excess homozygosity observed significantly from the values calculated in wild populations can be due to the combined effects of null alleles (Table S1) according to the 95 % confidence interval calculated by the and inbreeding. When loci with significant null alleles were jackknife method (Table 1; Fig. S1). However, the omitted from the analysis, the FIS values remained positive observed heterozygosity did not significantly differ and significantly different from zero for six of the seven between the illegally traded B. eriospatha individuals and populations (Table 1). This result indicates that these six those in wild populations (Table 1). Of the 13 private populations likely lose allelic richness through inbreeding. alleles observed, 9 or 70 % were found in the urban area. The overall estimate of genetic differentiation (Weir and We observed a greater number of rare alleles in this group Cockerham 1984) was significant among B. eriospatha of individuals (Table 1). Our results also indicated that B. populations (FST = 0.23, p \ 0.05). This value was similar eriospatha plants that occur in the urban area of Flori- to the overall estimate of FST obtained after the correction ano´polis have an expected heterozygosity value slightly for null alleles (FST = 0.17, p \ 0.05). However, the higher than the B. eriospatha individuals in wild popula- geographic distance among B. eriospatha populations did tions. The average observed heterozygosity (HO) within not explain the pattern of genetic differentiation observed wild populations was 0.36, ranging from 0.22 to 0.47 (i.e., lack of isolation by distance, Z = 15.73, r = 0.05, (Table 1). These values are considerably lower than the p = 0.63; Fig. 3A), indicating that there is an imbalance expected heterozygosity assuming the Hardy-Weinberg between drift and migration. equilibrium, which averaged 0.48. Our results also indicated that null alleles inflated the For the eight wild B. eriospatha populations, the test for estimates of genetic distance (Fig. 3). However, even after

Hardy-Weinberg equilibrium found that of 144 locus- the correction for null alleles in the FST pairwise estimates, population combinations, 46, 34 and 20, or 32.0, 23.6 and no isolation by distance was observed for B. eriospatha 13.9 %, showed significant deviation at p \ 0.05, 0.01 and populations (Z = 10.79, r = 0.09, p = 0.70; Fig. 3B). The

0.001, respectively. The test for the genotypic disequilib- matrix of geographic distance and the pairwise FST values rium in all wild population samples found that 79 of 288 quantifying genetic differentiation among B. eriospatha locus combinations or 27.4 % showed significant deviation populations are presented in Table 2. at the p \ 0.05; however, none of the locus pairs were found to be in significant genotypic disequilibrium after the Bayesian cluster analysis Bonferroni correction (p \ 0.001).

The average FIS values were 0.25 (ranging from 0.04 to Bayesian clustering without prior information about the 0.46) for all studied wild B. eriospatha populations. As the FIS geographical origins of populations showed that the highest

123 Conserv Genet (2014) 15:441–452 447

Fig. 3 Scatter plots of pairwise .0 genetic distance [FST/(1- FST)] A B

versus geographical distance .8 1 (Km) for eight Butia eriospatha 60 . (Martius ex Drude) populations .6 0.8 1.0 0 sampled in Santa Catarina, 0 Southern Brazil. The geographic distance among populations did not explain the pattern of Genetic distance genetic differentiation 0.2 0.4 quantified by the presence .0 0.2 0.4 0.0 (A) and absence of null alleles 0 (B) 0 50 100 150 0 50 100 150 Geographic distance (Km) Geographic distance (Km)

Table 2 Matrix of the geographic distances (km; above diagonal) and the genetic differentiation (FST; below diagonal) between eight B. eriospatha populations from Santa Catarina State, Southern Brazil, based on nine microsatellite loci Populations A B C D E F G H

A – 3.2 26.7 100.7 127.5 123.8 21.5 128.9 B 0.039 – 25.1 97.8 126.1 122.5 20.8 129.1 C 0.355* 0.364* – 101.7 144.1 140.8 44.2 152.7 D 0.240* 0.223* 0.381* – 80.8 80.5 87.8 126.7 E 0.123* 0.196* 0.325* 0.208* – 4.4 106.2 58.3 F 0.159* 0.202* 0.367* 0.227* 0.168* – 102.5 55.3 G 0.167* 0.181* 0.435* 0.181* 0.159* 0.206* – 108.6 H 0.099* 0.035 0.358* 0.218* 0.150* 0.206* 0.157* – B 0.027* – C 0.205* 0.196* – D 0.220* 0.211* 0.284* – E 0.107* 0.184* 0.200* 0.189* – F 0.133* 0.171* 0.191* 0.197* 0.144* – G 0.152* 0.170* 0.254* 0.178* 0.150* 0.171* – H 0.091* 0.040 0.206* 0.188* 0.137* 0.172* 0.137* –

In bold are the pairwise FST values using the ENA correction method as proposed by Chapuis and Estoup (2007) Asterisks denote values that are significant at the 0.05 level likelihood value (DK) occurred at K = 6 (Fig. S2), where and without prior information about geographical origins the number of clusters (K) was similar to the number of of populations, considering both the allele frequencies in wild populations sampled in this study (n = 8). Although different populations are correlated with one another and we expected a K equal to six due to the spatial clustering of the admixture model (data not show), also indicated that populations (e.g., clustering of populations A and B, and E highest likelihood value (DK) occurred at K = 6. and F), the K value was not the result of population clus- ters. The difference between the number of clusters and the Assignment tests number of sampled populations was due to the grouping of three populations (A, B, and H) into only one unit. While it Considering all nine loci and the eight B. eriospatha pop- makes biological sense for populations A and B to be ulations as reference data, the self-assignment tests indi- grouped as they are located in close proximity to each other cated that 36 % of all individuals were correctly assigned. (less than 4.0 km), this result is noteworthy because the H For eight populations, the expectation of correctly assign- population is separated from populations A and B by a ing individuals by chance is 12.5 %. However, the mean distance of 129 km. However, this result strengthens our value of the scores from the individual self-assignment previous observations of lack of isolation by distance tests was higher when we used the results of the Bayesian among B. eriospatha populations. Bayesian clustering with cluster analysis (i.e., six populations). Fifty-three percent

123 448 Conserv Genet (2014) 15:441–452 of all individuals were assigned correctly when populations our sample was adequate to detect low-frequency alleles. A, B and H were merged into one single population. For To be sure, there is no specific sample size required for this scenario, the expectation of correct assignment by such analysis; however, it is crucial for the sample to be chance is 16.7 %. In the following analyses we consider representative of the wider population and thus it should be that the performance of individual assignment tests were based on the degree of polymorphism of the genetic better when populations A, B and H were grouped. markers used. The forensic analysis using the exclusion-simulation While we found moderate to low genetic diversity in significance test found that 24 of the B. eriospatha indi- wild B. eriospatha populations, similar to the genetic viduals (48 %) sampled in the urban area have an unknown diversity reported for other palm species (Dowe et al. 1997; origin (p \ 0.001). For just three individuals (6 %), we Shapcott 1998; Perera et al. 2000; Gonza´les-Pe´rez et al. excluded all but one population as the probable population 2004; Shapcott et al. 2009; Jian et al. 2010), the continual of origin. Two individuals were assigned to the set of decrease of B. eriospatha population sizes due to illegal populations A, B, and H. The other B. eriospatha indi- trade and other deterministic factors (e.g. deforestation, vidual was assigned to the D population. On the other hand, habitat degradation, cattle grazing) can jeopardize the 23 out of the 50 B. eriospatha individuals (46 %) may have genetic variation that remains. For instance, population come from several of the six populations identified a pos- C—one of the smallest of the populations surveyed teriori (K = 6). For instance, for one individual we herein—shows the lowest levels of genetic diversity (i.e., excluded only one of the six populations as not being its expected and observed heterozygosities), which were sig- probable population of origin. For these 23 individuals, the nificantly different among all sampled wild B. eriospatha highest score of likelihoods among the non-excluded populations (Table 1). In a recent study, Nazareno and Reis populations indicated populations C, E and G as the most (2013) compared genetic parameters between large and likely source population for 2, 10 and 11 individuals, small B. eriospatha populations for both adult plants and respectively. seedlings. The study showed a reduction in allelic richness in small populations. Some authors (e.g., Nei et al. 1975; Cornuet and Luikart 1996) point out that allelic richness is Discussion highly affected by population reduction due to the rapid elimination of rare alleles. In the studied wild B. eriospatha Defined as any act that intentionally contravenes the laws populations, the genetic consequences of human activities and regulations established to protect biological resources, may have led to a loss of alleles (e.g. there is just one allele poaching (or illegal trade, Muth and Bowe 1998) is con- on locus But18 in the G population; Table S2) and may sidered one of the most significant threats to biological contribute to the loss of other alleles in the near future (e.g. diversity (Redford 1992; Alacs et al. 2010; Wilkie et al. while allele 149 of locus But11 could be lost in the B 2011; Destro et al. 2012). One of the main issues assessed population, in C population this allele could be fixed; Table was whether B. eriospatha individuals that were illegally S2). Likewise, stochastic forces such as genetic drift can traded and planted outside their natural area have higher contribute to the loss and fixation of alleles, mainly if the levels of genetic diversity than the ones found in wild B. eriospatha populations shrink in size and become spa- populations. tially isolated (Nazareno and Reis 2013). The loss of Interestingly, the analysis of microsatellite allelic data genetic diversity due to the threats facing this palm species revealed that the group of B. eriospatha individuals that is also reflected in the levels of inbreeding (i.e. fixation were illegally traded had more genetic variation (i.e. allelic index) as observed in almost all of the studied wild B. richness, expected heterozygosity) than all the studied wild eriospatha populations. B. eriospatha populations, suggesting that there is no pre- Consistent with the results from the analysis of genetic ferred target source population. Private and rare alleles diversity, the multilocus assignment exclusion-test corrob- were also observed in greater numbers in the urban popu- orates the hypothesis that illegaly traded B. eriospatha lation than the wild populations. However, as small sample individuals had varying origins. Even though we believe that size in population genetics can impose significant analyti- our sample sizes were adequate, this result should be viewed cal limitations (Nazareno and Jump 2012), we must con- with caution because we examined a modest number of sider that the private alleles found in B. eriospatha individuals with nine microsatellite loci (HE = 0.49). For individuals (56 % of them being rare) from the urban area some species, Manel et al. (2002) reported a roughly con- may be so rare in the wild that they were not present in our sistent result of assignment test using eight microsatellite sample. Nevertheless, it is equally important to point out loci (HE = 0.60) with 30–50 individuals sampled per pop- that based on the set of microsatellite markers used here (a ulation. In a recent study, Jolivet and Degen (2012), using total of 46 alleles in the wild populations) we believe that just three microsatellite loci, could determine the origin of 123 Conserv Genet (2014) 15:441–452 449 sapelli timber (Entandrophragma cylindricum; meliaceae) increases with increasing genetic differentiation among in the Congo Basin. Thus, the set of microsatellites used in populations (Cornuet et al. 1999). For example, if a poacher our analysis may have contributed to the number of indi- claims to have obtained one B. eriospatha individual from viduals (n = 23) that had more than one population assigned the C population, but we believe that the individual came as the origin. Even though we were able to identify the origin from the D population, an assignment test between the two of the majority of the B. eriospatha individuals (n = 27 or populations can be easily undertaken (FST between C and D 54 %), we emphasize that our analysis could be improved if population = 0.284, Table 2). However, it can be difficult to more polymorphic loci are added. This is in line with the conduct such an analysis if this individual came from the A, results of the self-assignment tests, which provided moder- B or H population (FST = 0.03–0.09, Table 2) which were ately accurate assignments, probably due to the moderate grouped as one unit by the cluster analysis. While the polymorphism of the microsatellite loci used herein. structure analysis using the Bayesian algorithm allowed us to

Therefore, in order to obtain a highly accurate assignment identify this group, the low pairwise FST values also sup- test of single individuals, more than nine microsatellites are ported this result. Furthermore, the lack of correlation required. Furthermore, the forensic analysis for this palm between genetic differentiation and geographic distance species can be better clarified if cytoplasmic markers suggest that an island model (Wright 1931; Maruyama (chloroplast and mitochondrial) are used alongside nuclear 1970), rather than isolation by distance model, may best markers (e.g. Nazareno et al. 2011; Nazareno and Reis 2011) describe the population structure of this palm species. In fact, to develop specific DNA profiles. DNA markers such as the island model is in line with the species’ distribution those suggested above have been validated in other forensic pattern (e.g. B. eriospatha populations cover small areas with analyses producing reliable results in identifying the geo- individuals in a clustered distribution) and with their speci- graphic origin of a specimen (Avise et al. 1987; Campbell ficity by habitat (highlands). However, even though the et al. 2003; DeYoung et al. 2003; Genton et al. 2005; island model is biologically plausible for this palm species, Schwenke et al. 2006; Gomez-Diaz and Gonzalez-Solis the number of populations likely plays a role in shaping the 2007; Velo-Anton et al. 2007; Sanders et al. 2008; Degen population structure. As such, this issue can be better et al. 2013; Jolivet and Degen 2012). explored when samples from other populations become Although the DNA-based analysis used to determine the available. origin of unknown samples has been successfully applied for plant species (Deguilloux et al. 2004; Sarri et al. 2006; Conservation perspectives Honjo et al. 2008; Howard et al. 2009; Nuroniah 2009; Lowe et al. 2010; Jolivet and Degen 2012; Degen et al. From a conservation perspective, the genetic diversity that 2013), there are limited discussions of their applicability exists in both wild B. eriospatha populations and individuals for non-timber species (Howard et al. 2009; Sarri et al. that occur in non-native settings should be preserved. 2006) and such approaches have mainly been used to study Although criminal charges and fines may be appropriate to endangered species (Honjo et al. 2008). Nevertheless, control or decrease the illegal trade of this palm species, encouraging results from assignment tests were reported in effective conservation strategies may be more feasible if the analysis of the geographic origins of cultivars of the compensatory mitigation (e.g. seed collection for genetic endangered species Primula sieboldii (Honjo et al. 2008). restoration) is targeted at the purchasers of illegally-traded Whilst our study is not the first test case to apply molecular B. eriospatha plants. Furthermore, even though B. erio- markers to trace the geographic origin of a plant species, it spatha can adapt to varying local environments, its perpet- is novel in that we are attempting to identify a specific uation in introduced habitats, like the urban area of population rather than a geographic region. In light of our Floriano´polis, can be difficult since each individual is gen- results, the inter-population differentiation across all pop- erally isolated and surrounded by buildings, homes, or ulations (FST = 0.17) and the FST pairwise estimates pro- motorways. As this palm species is able to reproduce by vide a moderate basis for successful assignment of B. selfing (Nazareno and Reis 2012), genetic diversity can be eriospatha individuals that were illegally harvested. lost in only a few generations due to inbreeding. In addition, As stated by several authors (Cornuet et al. 1999; Manel as previously pointed out (Clegg et al. 2002; Estoup and et al. 2002; Guinand et al. 2004; Degen et al. 2010), the Clegg 2003; Kolbe et al. 2004; Frankham 2005), coloniza- assignment test method is more appropriate when popula- tion following introduction into an area can lead to genetic tions are significantly differentiated (FST [ 0.1–0.2), bottlenecks that would further reduce genetic variation. In although there was a case of highly successful Bayesian light of this, we emphasize that conservation strategies assignment tests for populations with low genetic differen- should be undertaken for this palm species, such as the tiated on a regional scale (Jolivet and Degen 2012). Gener- creation of germplasm banks. Otherwise, even though there ally, the accuracy of genotype assignment procedures is significant genetic variation in the urban B. eriospatha 123 450 Conserv Genet (2014) 15:441–452 populations, this variation will become static in a few years Chapuis MP, Estoup A (2007) Microsatellite null alleles and because these individuals will become non-reproductive. estimation of population differentiation. Mol Biol Evol 24: 621–631 Others conservation strategies are also feasible for this Check E (2006) The tiger’s retreat. Nature 441:927–930 species, such as the sale of adult B. eriospatha individuals CITES—Convention on International Trade in Endangered Species that are no longer reproductive may be permitted. (2010) CITES Trade: a snapshot. http://www.cites.org/common/ In this analysis we demonstrate that the use of the docs/CITES-trade-snapshot-eng.pdf Clegg SM, Degnan SM, Kikkawa J, Moritz C, Estoup A, Owens IPF molecular tools such those employed herein may be useful in (2002) Genetic consequences of sequential founder events by an future investigations. However, the use of numerous, rapidly island-colonizing bird. Proc Nat Acad Sci USA 99:8127–8132 evolving DNA markers (e.g., next-generation sequencing Cornuet JM, Luikart G (1996) Description and power analysis of two technology) and a database containing information about tests for inferring recent population bottlenecks from allele frequency data. Genetics 144:2001–2014 allele frequencies for numerous, diverse samples of wild B. Cornuet J-M, Piry S, Luikart G, Estoup A, Solignac M (1999) New eriospatha populations are necessary in order to assess those methods employing multilocus genotypes to select or exclude populations severely threatened by illegal harvesting and populations as origins of individuals. Genetics 153:1989–2000 trafficking. Since public awareness is limited, we aspire to Correa LB, Barbieri RL, Rossato M, Buttow MW, Heiden G (2009) Caracterizac¸a˜o cariolo´gica de palmeiras do genero Butia (Arec- develop a genetic database with additional geographic and aceae). Rev Bras Frutic 31:1111–1116 genetic sampling to provide wildlife enforcement officials Degen B, Holtken A, Rogge M (2010) Use of DNA-fingerprints to with a powerful conservation tool. control the orign of forest reproductive material. Silvae Genet 59:268–272 Acknowledgments This study is part of the Doctoral Thesis (Plant Degen B, Ward S, Lemes MR, Navarro C, Cavers S, Sebbenn AM Genetic Resources Program-Federal University of Santa Catarina, (2013) Verifying the geographic origin of mahogany (Swietenia UFSC) of the first author. We are grateful to the Nu´cleo de Pesquisas em macrophylla King) with DNA-fingerprints. Forensic Sci Int: Florestas Tropicais (Rainforest Research Department) at UFSC for Genet 7:55–62 assistance during field work. We would also like to thank the Physiology Deguilloux MF, Pemonge MH, Petit RJ (2004) DNA based control of of Development and Plant Genetics Laboratory at UFSC for providing oak wood geographic origin in the context of cooperage industry. the infrastructure required for microsatellite analysis. The authors thank Ann For Sci 61:97–104 Dr. Evelyn R. Nimmo for editing the English of the manuscript and Destro GFG, Pimentel TL, Sabaini RM, Borges RC, Barreto R (2012) Renata Duzzioni for helping with Fig. 2. The authors are grateful to Efforts to combat wild animals trafficking in Brazil. In: Akeem FAPESC (Santa Catarina State Research Council, Brazil) and National Lameed G (ed) Biodiversity enrichment in a diverse World. Counsel of Technological and Scientific Development (CNPq; to A.G.N. InTech, Brasilia, pp 421–436 and to M.S.R. 304724/210-6) for the financial support. DeYoung RW, Demarais S, Honeycutt RL, Gonzales RA, Gee KL, Anderson JD (2003) Evaluation of a DNA microsatellite panel useful for genetic exclusion studies in white-tailed deer. Wildlife Soc Bull 31:220–232 Dowe JL, Benzie J, Ballment E (1997) Ecology and genetics of Carpoxylon macrospermum H. Wendl. & Drude (), an References endangered palm from Vanuatu. Biol Conserv 79:205–219 Efron B (1983) Estimating the error rate of a prediction rule: Alacs EA, Georges A, FitzSimmons NN (2010) DNA detective: a improvement on cross-validation. J Am Stat Assoc 78:316–331 review of molecular approaches to wildlife forensics. Forensic Estoup A, Clegg SM (2003) Bayesian inferences on the recent island Sci Med Pathol 6:180–194 colonization history by the bird Zosterops lateralis lateralis. Mol Alves RRN, Filho GAP (2007) Commercialization and use of snakes Ecol 12:657–674 in North and Northeastern Brazil: implications for conservation Evanno G, Regnaut S, Goudet J (2005) Detecting the number of and management. Biodivers Conserv 16:969–985 clusters of individuals using the software Structure: a simulation Arroyo-Quiroz I, Pe´rez-Gil R, Leader-Williams (2007) Mexico in the study. Mol Ecol 14:2611–2620 international reptile skin trade: a case study. Biodivers Conserv Foldenauer U, Borjal RJ, Deb A, Arif A, Taha AS, Watson RW, 16:931–952 Steinmetz H, Bu¨rkle M, Hammer S (2007) Hematologic and Avise JC, Arnold J, Martin Ball R, Bermingham E, Lamb T, Neigel plasma biochemical values of Spix’s Macaws (Cyanopsitta JE et al (1987) Intraspecific phylogeography: the mitochondrial spixii). J Avian Med Surgery 21:275–282 DNA bridge between population genetics and systematics. Ann Frankham R (2005) Resolving the genetic paradox in invasive Rev Ecol Syst 18:489–522 species. Heredity 94:385 Bueno E (2006) Na´ufragos, traficantes e degredados: as primeiras Genton BJ, Shykoff A, Giraud T (2005) High genetic diversity in expedic¸o˜es ao Brasil. Editora Objetiva 313(5783):58–61 French invasive populations of common ragweed, Ambrosia Campbell D, Duchesne P, Bernatchez L (2003) AFLP utility for artemisiifolia, as a result of multiple sources of introduction. population assignment studies: analytical investigation and empir- Mol Ecol 14:4275–4285 ical comparison with microsatellites. Mol Ecol 12:1979–1991 Gomez-Diaz E, Gonzalez-Solis J (2007) Geographic assignment of Carlsson J (2008) Effects of microsatellite null alleles on assignment seabirds to their origin: combining morphologic, genetic, and testing. J Heredity 99:613–616 biogeochemical analyses. Ecol Appl 17:1484–1498 Carvalho MMX (2006) O desmatamento das florestas de arauca´ria e o Gonza´les-Pe´rez MA, Caujape´-Castells J, Sosa PA (2004) Allozyme Me´dio Vale do Iguac¸u: uma histo´ria de riqueza madeireira e variation and structure of the Canarian endemic palm tree colonizac¸o˜es. Dissertation, Universidade Federal de Santa Cat- Phoenix canariensis (Arecaceae): implications for conservation. arina, Brazil Heredity 93:307–315

123 Conserv Genet (2014) 15:441–452 451

Goudet J (2002) FSTAT: a program to estimate and test gene Muth R, Bowe J (1998) Illegal harvest of renewable resources in North diversities and fixation indices. Version 2.9.3.2. http://www2. Amercia: towards a typology of the motivations for poaching. Soc unil.ch/popgen/softwares/fstat.htm. Accessed 15 Dec 2012 Nat Resour 11:9–24 Graham-Rowe D (2011) Endangered and in demand. Nature Mutterback M (2012) Leopard poaching is a bigger problem in India 480:101–103 than previously believed. http://news.mongabay.com/2012/1030- Guinand B, Scribner KT, Topchy A, Page KS, Punch W, Burnham- mutterback-leopard-poaching.html Curtis MK (2004) Sampling issues affecting accuracy of Myers N, Mittermeier RA, Mittermeier CG, Fonseca GAB, Kent J likelihood-based classification using genetical data. Environ (2000) Biodiversity hotspots for conservation priorities. Nature Biol Fish 69:245–259 403:853–858 Hardy OJ, Vekemans X (2002) SPAGeDi: a versatile computer Natusch DJD, Lyons JA (2012) Exploited for pets: the harvest and program to analyse spatial genetic structure at the individual or trade of amphibians and reptiles from Indonesian New Guinea. population levels. Mol Ecol Notes 2:618–620 Biodivers Conserv 21:2899–2911 Honjo M, Ueno S, Tsumura Y, Handa T, Washitani I, Ohsawa R Nazareno AG, Jump AS (2012) Species-genetic diversity correlations (2008) Tracing the origins of stocks of the endangered species in habitat fragmentation can be biased by small sample sizes. Primula sieboldii using nuclear microsatellites and chloroplast Mol Ecol 21:2847–2849 DNA. Conserv Genet 9:1139–1147 Nazareno AG, Reis MS (2011) The same bus different: monomorphic Howard C, Gilmore S, Robertson J, Peakall R (2009) A Cannabis microsatellite markers as a new tool for genetic analysis. Am J sativa STR genotype database for Australian seizures: forensic Bot 98:265–267 applications and limitations. J Forensic Sci 54:556–563 Nazareno AG, Reis MS (2012) Linking phenology to mating system: Hubisz MJ, Falush D, Stephens M, Pritchard JK (2009) Inferring exploring the reproductive biology of the threatened palm species weak population structure with the assistance of sample group Butia eriospatha. J Heredity 103:842–852 information. Mol Ecol Resources 9:1322–1332 Nazareno AG, Reis MS (2013) At risk of population decline? An IBGE—Instituto Brasileiro de Geografia e Estatı´stica (2004) Mapa ecological and genetic approach to the threatened palm species da vegetac¸a˜o do Brasil e mapa de biomas do Brasil. http:// Butia eriospatha (Arecaceae) of Southern Brazil. J Hered doi. www.ibge.gov.br doi:10.1093/jhered/est065 IUCN World Conservation Union (2012) Red List of Threatened Nazareno AG, Zucchi MI, Reis MS (2011) Microsatellite markers for Species. Version 2010.1. http://www.iucnredlist.org. Accessed Butia eriospatha (Arecaceae), a vulnerable palm species from 12 Dec 2012 the Atlantic Rainforest of Brazil. Am J Bot 98:198–200 Jensen JL, Bohonak AJ, Kelley ST (2005) Isolation by distance, web Nei M (1978) Estimation of average heterozygosity and genetic service. http://ibdws.sdsu.edu/. Accessed 12 Dec 2012 distance from a small number of individuals. Genetics 89:583–590 Jian S, Ban J, Ren H, Yan H (2010) Low genetic variation detected Nei M, Maruyama T, Chakraborty R (1975) The bottleneck effect and within the widespread mangrove species Nypa fruticans (Pal- genetic variability in populations. Evolution 29:1–10 mae) from Southeast Asia. Aquat Bot 92:23–27 Nuroniah HS (2009) Diagnostic markers for the identification of the Jolivet C, Degen B (2012) Use of DNA fingerprints to control the origin tree species Shorea leprosula Miq. and S. parvifolia dyer and the of sapelli timber (entandrophragma cylindricum) at the forest geographic origin of S. leprosula Miq. Dissertation, Goettingen concession level in Cameron. Forensic Sci Int Genet 6:487–493 University Kenney JS, Smith JLD, Starfield AM, McDougal CW (1995) The Overbeck GE, Muller SC, Fidelis A, Pfadenhauer J, Pillar VD, Blanco long-term effects of tiger poaching on population viability. CC, Boldrini II, Both R, Forneck ED (2007) Brazil’s neglected Conserv Biol 9:1127–1133 biome: the South Brazilian Campos. Pers Plant Ecol Evol Sys Kolbe JJ, Glor RE, Rodriguez-Schettino L, Chamizo-Lara A, Larson 9:101–116 A, Losos JB (2004) Genetic variation increases during biological Paetkau D, Calvert W, Stirling I, Strobeck C (1995) Microsattelite invasion by a Cuban lizard. Nature 431:177–181 analysis of population structure in Canadian polar bears. Mol Kt Kate, Laird SA (1999) The commercial use of biodiversity. Ecol 4:347–354 Earthscan Publications Ltd, London Paetkau D, Slade R, Burden M, Estoup A (2004) Genetic assignment Larsen HO, Olsen CS (2007) Unsustainable collection and unfair methods for the direct, real-time estimation of migration rate: a trade? Uncovering and assessing assumptions regarding central simulation-based exploration of accuracy and power. Mol Ecol Himalayan medicinal plant conservation. Biodivers Conserv 13:55–65 16:1679–1697 Perera L, Russel JR, Provan J, Powell W (2000) Use of microsatellite Lowe AJ, Wong KN, Tiong YS, Iyerh S, Chew FT (2010) A DNA DNA markers to investigate the level of genetic diversity and method to verify the integrity of timber supply chains; confirm- population genetic structure of coconut (Cocos nucifera L.). ing the legal sourcing of merbau timber from logging concession Genome 43:15–21 to sawmill. Silvae Genet 59:263–268 Piry S, Alapetite A, Cornuet JM, Paetkau D, Baudouin L, Estoup A MMA - Ministe´rio do Meio Ambiente (2008) In: Lista oficial de (2004) GENECLASS2: a software for genetic assignment and espe´cies da Flora brasileira ameac¸ada de extinc¸a˜o. Dia´rio Oficial first-generation migrant detection. J Hered 95:536–539 da Unia˜o de 24 de setembro de 2008, no 185. Sec¸a˜o 1, p. 75-83. Reis MS, Mantovani A, Silva JZ, Mariot A, Bittencourt R, Nazareno http://www.mma.gov.br/estruturas/ascom_boletins/_arquivos/83_ AG, Ferreira SK, Steiner F, Montagna T, Silva AALS, Fernandes 19092008034949.pdf. Accessed 8 Dec 2012 CD, Altrak G, Figueredo LG (2012) Distribuic¸a˜o da diversidade Manel S, Berthier P, Luikart G (2002) Detecting wildlife poaching: gene´tica e conservac¸a˜o de espe´cies arbo´reas em remanescentes identifying the origin of individuals with Bayesian assignment florestais de Santa Catarina. In: Vibrans AC, Sevegnani L, tests and multilocus genotypes. Conserv Biol 16:650–658 Gasper AL, Lingner DV (eds) Inventa´rio florı´stico florestal de Mantel N (1967) The detection of disease clustering and a generalized Santa Catarina. Edifurb, Blumenau regression approach. Cancer Res 27:209–220 Rannala B, Mountain J (1997) Detecting immigration by using Maruyama T (1970) Effective number of alleles in a subdivided multilocus genotypes. Proc Nat Acad Sci USA 94:9197–9201 population. Theoret Popul Biol 1:273–306 Redford KH (1992) The empty forest. Bioscience 42:412–422 Morellato LPC, Haddad CFB (2000) Introduction: the Brazilian Reitz R (1974) Palmeiras—Parte 1. Flora ilustrada catarinense, Atlantic forest. Biotropica 32:786–792 Herba´rio Barbosa Rodrigues

123 452 Conserv Genet (2014) 15:441–452

RENCTAS (2011) Rede Nacional de Combate ao Tra´fico de Animais Shapcott A, Dowe JL, Ford H (2009) Low genetic diversity and Silvestres. 18 Relato´rio Nacional sobre o Tra´fico de Fauna recovery implications of the vulnerable Bankouale´ Palm Livis- Silvestre. http://www.renctas.org.br/. Accessed 14 Dec 2012 tona carinensis (Arecaceae), from North-eastern Africa and Rice WR (1989) Analyzing tables of statistical tests. Evolution Southern Arabian Peninsula. Conserv Genet 10:317–327 43:223–225 Shepherd CR, Nijman V (2008) The trade in bear parts from Rosa IL, Oliveira TPR, Oso´rio FM, Moraes LE, Castro ALC, Barros Myanmar: an illustration of the ineffectiveness of enforcement GML, Alvez RRN (2011) Fisheries and trade of seahorses in of international wildlife trade regulations. Biodivers Conserv Brazil: historical perspective, current trends, and future direc- 17:35–42 tions. Biodivers Conserv 20:1951–1971 van Oosterhout C, Hutchinson WF, Wills DPM, Shipley P (2004) Rousset F (1997) Genetic differentiation and estimation of gene flow Micro-checker: software for identifying and correcting genotyp- from F-statistics under isolation by distance. Genetics 145: ing errors in microsatellite data. Mol Ecol Notes 4:535–538 1219–1228 Velo-Anton G, Godinho R, Ayres C, Ferrand N, Rivera AC (2007) Sanders JG, Cribbs JE, Fienberg HG, Hulburd GC, Katz LS, Palumbi Assignment tests applied to relocate individuals of unknown SR (2008) The tip of the tail: molecular identification of origin in a threatened species, the European pond turtle (Emys seahorses for sale in apothecary shops and curio stores in orbicularis). Amphibia-Reptilia 28:475–484 California. Conserv Genet 9:65–71 Wasser SK, Shedlock AM, Comstock K et al (2004) Assigning African Sarri V, Baldoni L, Porceddu A, Cultrera NGM, Contento A, Frediani elephant DNA to geographic region of origin: applications to the M et al (2006) Microsatellite markers are powerful tools for ivory trade. Proc Nat Acad Sci USA 101:14847–14852 discriminating among olive cultivars and assigning them to Wasser S, Poole J, Lee P, Lindsay K (2010) Elephants, ivory, and geographically defined populations. Genome 49:1606–1615 trade. Science 327:1331–1332 Schwenke PL, Rhydderch JG, Ford MJ, Marshall AR, Park LK (2006) Weir BS, Cockerham CC (1984) Estimating F-statistics for the Forensic identification of endangered Chinook Salmon (On- analysis of population structure. Evolution 38:1358–1370 corhynchus tshawytscha) using a multilocus SNP assay. Conserv Wilkie DS, Bennett EL, Peres CA, Cunningham AA (2011) The Genet 7:983–989 empty forest revisited. Ann NY Acad Sci 1223:120–128 Shapcott A (1998) The genetics of Ptychosperma bleeseri a rare palm Wright S (1931) Evolution in Mendelian populations. Genetics from the Northern Territory, Australia. Biol Conserv 85:203–209 16(97):159

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