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Genetics and Molecular Biology

Print version ISSN 1415-4757

Genet. Mol. Biol. vol.35 no.1 São Paulo  2012  Epub Dec 15, 2011

http://dx.doi.org/10.1590/S1415-47572011005000062 

Genetic structure and conservation of Mountain Lions in the South-Brazilian Atlantic Rain Forest

 

 

Camila S. CastilhoI, II; Luiz G. Marins-SáII; Rodrigo C. BenedetIII; Thales R.O. FreitasI

IDepartamento de Genética, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
IIInstituto Serrano de Conservação da Natureza, Urubici, SC, Brazil

IIIProjeto Puma, Lages, SC, Brazil

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ABSTRACT

The Brazilian Atlantic Rain Forest, one of the most endangered ecosystems worldwide, is also among the most important hotspots as regards biodiversity. Through intensive logging, the initial area has been reduced to around 12% of its original size. In this study we investigated the genetic variability and structure of the mountain lion, Puma concolor. Using 18 microsatellite loci we analyzed evidence of allele dropout, null alleles and stuttering, calculated the number of allele/locus, PIC, observed and expected heterozygosity, linkage disequilibrium, Hardy-Weinberg equilibrium, FIS, effective population size and genetic structure (MICROCHECKER, CERVUS, GENEPOP, FSTAT, ARLEQUIN, ONESAMP, LDNe, PCAGEN, GENECLASS software),we also determine whether there was evidence of a bottleneck (HYBRIDLAB, BOTTLENECK software) that might influence the future viability of the population in south Brazil. 106 alleles were identified, with the number of alleles/locus ranging from 2 to 11. Mean observed heterozygosity, mean number of alleles and polymorphism information content were 0.609, 5.89, and 0.6255, respectively. This population presented evidence of a recent bottleneck and loss of genetic variation. Persistent regional poaching constitutes an increasing in the extinction risk.

Key words: Araucaria Forest, Atlantic Rain Forest, conservation, genetic diversity, microsatellite.


 

 

Introduction

The Brazilian Atlantic Rain Forest, one of the four most important biodiversity hotspots worldwide (Myers et al., 2000), is also one of the most endangered ecosystems, through having undergone intense human exploitation and deforestation (Ribeiro et al., 2009). The Araucaria Forest, one of the Atlantic Rain Forest physiognomies in south Brazil, has been heavily logged since the early 1900's. The whole biome is now legally protected (Federal Law 285/99, February, 2006) Even so, illegal exploitation still persists, and only 11.26% of the original area of the Atlantic Rain Forest itself, and 12.6% of the Araucaria Forest (Ribeiro et al., 2009), still remain. Of this small remnant, only 0.39% of the latter lies within some kind of legally protected area (Ribeiro et al., 2009).

Although almost 90% of the original habitat has disappeared in less than a hundred years, little is known on the effects of this fragmentation on animal populations. There are no population estimates prior to deforestation, and even today there are still none for most Brazilian mammals. The mountain lion (Puma concolor) is a top predator, whose very presence influences the ecosystem, and prey populations, hence the importance of its conservation (Henke and Bryant, 1999; Miller et al., 2001; Terborgh et al., 2001).

The mountain lion, the second largest Neotropical felid, occupies the largest geographical area in the Americas, this extending from Canada to southern Argentina. The subspecies that occurs in southern Brazil is Puma concolor capricornensis (Culver et al., 2000). It is listed as of least concern (IUCN, 2008), and as vulnerable in the Brazilian National Red List (MMA and Fundação Biodiversitas, 2008). Little is known about local populations. Although having suffered severe habitat loss, there is no information regarding population sizes, and only scarce recent data on regional species (Mazzolli et al., 2002; Mazzolli, 2010; Castilho et al., 2011; and Marins-Sá, 2005, MSc Dissertation, Curso de Pós-Graduação em Ecologia UFRGS, Porto Alegre).

In addition to the severe habitat loss, the species is still illegally hunted because of livestock depredation (Mazzolli et al., 2002; Marins-Sá, 2005, MSc Dissertation, Curso de Pós-Graduação em Ecologia UFRGS, Porto Alegre), which, in south Brazil, has been reported since the 1990's (Mazzolli et al., 2002). Depletion very much decreased when ranchers implemented management actions, such as corralling small animals (sheep and goats) at night (Mazzolli et al., 2002).

Previous studies described the genetic variability, and structural and ecological characteristics of mountain lions in North America (Sinclair et al., 2001; Ernest et al., 2003; Anderson et al., 2004; McRae et al., 2005,) and South America (Culver et al., 2000; Moreno et al., 2006; Miotto et al., 2007; Ruiz-Garcia et al., 2009). However, specific information regarding genetic variability status related to recent specific processes, especially in such an important ecosystem as the Brazilian, is still lacking.

Knowledge of possible recent bottlenecks is extremely important for present-day management strategies. Identification of their very existence, the subsequent loss in genetic diversity, and the prevailing genetic structure, is important for evaluating the extinction risk of a population (Montgomery et al., 2000; Reed and Frankham, 2003; Frankham et al., 2005; O'Grady et al., 2008).

Thus, the aim of this study was to determine whether there was a bottleneck that could possibly affect future population viability, besides assessing genetic structure, inbreeding and causes of mortality in regional mountain lions. The results would contribute to the conservation and management of both this endangered species and the ecosystem itself.

 

Material and Methods

Sample collection and laboratory procedures

We collected 63 samples of the mountain lion (Puma concolor Linnaeus, 1771) population in southern Brazil, 37 (58.7%) from the field and 26 from museum skins and skulls (41.3%). The samples came from the south Brazilian states of Rio Grande do Sul, Santa Catarina, and Paraná, from 1983 through 2007. Location, year and cause of death/capture were recorded. All the sample locations were recorded (coordinates registered in museum samples, and death/capture location in field samples using GPS) and mapped using TrackMaker (Figure 1). Genomic DNA was extracted using the CTAB protocol (Doyle and Doyle, 1987) for tissue samples, and phenol-chloroform (Sambrook et al., 1989) for blood samples.

 

 

18 loci, four originally designated in Felis catus (Menotti-Raymond et al., 1999) and 14 in Puma concolor (Kurushima et al., 2006; Rodzen et al., 2007), were amplified for subsequent analysis of genetic variability of the wild mountain lion population in south Brazil. Each microsatellite locus was individually amplified in PCR reactions, according to Castilho et al., (2011). Allele sizes were defined by separating the amplification products on 6% polyacrylamide gels together with a 25 bp marker ladder. Intron DBY-7 (Luo et al., 2007) was used for sex determination under the same PCR conditions as those for microsatellites. Samples were genotyped at least twice for validated allele scores.

Data analysis

Genetic polymorphism was estimated as the number of alleles per locus (A), observed heterozygosity (Ho), expected heterozygosity (HE), polymorphic information content (PIC), and allelic frequencies, using the CERVUS 3.0.3 program (Marshall et al., 1998). GENEPOP 3.3 (Raymond and Rousset, 1995) was used for testing linkage disequilibrium (LD) and ARLEQUIN 3.1 for checking genotypic distribution conformance to Hardy-Weinberg equilibrium (HWE).

Significance levels (α = 0.05) were corrected with the Bonferroni approach for multiple simultaneous comparisons (Rice, 1989), in order to infer LD and departures from HWE. The probability of the presence of null alleles, allele dropout, and scoring errors due to stutter was tested using MicroChecker 2.2.3 (Van Oosterhout et al., 2004). Allelic richness (AR) and inbreeding coefficient (FIS) were calculated with the FSTAT 2.9.3.2 program (Goudet, 2001).

In order to detect any genetic evidence of a population decline, the BOTTLENECK program (Cornuet and Luikart, 1996) was used with the infinite allele (I.A.M.), stepwise mutation (S.M.M.), and two-phase (T.P.M.) models, with 70% t and 95% S.M.M., 20% variance, and 1,000 iterations, as recommended by Piry et al. (1999). The Wilcoxon sign-rank test was applied to determine significance (p < 0.05). In order to assess whether the small sample size (n = 37) was masking the results, HYBRIDLAB 1.0 (Nielsen et al., 2006) was used to simulate a population with 500 individuals, with n = 37 as a base population, and BOTTLENECK run with the same parameters described above.

The existence of population structure was inferred by principal component analysis (PCA) with PCAGEN software. GENECLASS 2 (Piry et al., 2004) was carried out to infer the assignment or exclusion of individuals, assuming that all those sampled belonged to the same population. The ONESAMP1.1 (Tallmon et al., 2008) and LDNe 1.31 (Waples, 2006) programs were used with genotypic data for estimating the effective population size (Ne).

The probability of loss in a generation of alleles with frequencies from 0.01 to 0.10 was calculated, using Pr (A) = (1 - p)2N, where p is allele frequency (Frankham et al., 2005), and considering N as a mean between that calculated by LDNe and ONESAMP. The loss of genetic variation in one generation was also calculated, using the equation He = 1 - 1/(2Ne)t , where He is the level of heterozygosity, Ne the effective population size, and t the number of generations (Lowe et al., 2004).

 

Results

DNA extraction was successful for 37 individuals, viz., 28 field samples (25 obtained from poachers, 1 road kill and 2 captured animals) and 9 from museums. DNA extraction was a failure in the case of field samples containing excess fat. Sixteen males and 21 females were successfully sexed using intron DBY-7 from the Y chromosome.

106 alleles were identified for the 18 microsatellite loci in the 37 samples (Table 1). The number of alleles/locus ranged from 2 (PcoB115) to 11 (PcoB203w), with a mean of 5.89. Mean observed heterozygosity (Ho) was 0.609 (ranging from 0.027 to 0.806), and mean expected heterozygosity (HE) 0.6818 (ranging from 0.027 to 0.850) (Table 1). Polymorphism information content (PIC) for 16 of the 18 loci was higher than 0.5, with only Fca453 and Pco115 lower (0.463 and 0.026 respectively). The mean PIC for all the loci was 0.6255 (Table 1).

Tests showed no loci to be in linkage disequilibrium, although deviation from HWE (p > 0.05 after Bonferroni correction) occurred in three loci, Fca391, Fca424 and PcoB210w (Table 1). FIS, calculated to test whether inbreeding was responsible for deviations from HWE, ranged from -0.30 to 0.42 (mean FIS = 0.10), in the case of global FIS and seven samples, significantly (Table 1). The FIS value for sample Fca453 indicated heterozygote excess, and for the remainder, heterozygote deficit. CERVUS failed to find mother/ father - offspring pairs. For more details on parentage relations in this population see Castilho et al. (2011). MicroChecker results gave no evidence of allele dropout or scoring erros due to stuttering, although loci Fca391 and Fca424 presented a general excess of homozygotes for most allele-size classes, thereby implying the possible presence of null alleles.

Allelic frequencies varied from 0.013 to 0.986, with 17% at 0.01, and 34% and 46.2% lower than 0.05 and 0.10, respectively. One, at 0.98, was almost fixed in this population (locus Pco115). Seven alleles (6.6% of the total), apparent in samples dating from 1983 to 1995, were absent in the more recent.

Analysis with PCAGEN software (p > 0.05, data not shown) failed to detect a population genetic structure. The results from GENECLASS corroborated this, by indicating that all the individuals came from the same population source (p > 0.05).

Although evidence of a recent bottleneck in this population was found, when applying the Wilcoxon sign-rank test using the infinite allele model (I.A.M.) and two-phase model (T.P.M.), with 70% stepwise mutation model (S.M.M.), this was not so with either 95% S.M.M. (p > 0.05) or the stepwise mutation model (S.M.M.) for n = 37 (Table 2). However, when using n = 500 simulated genotypes, a recent bottleneck for I.A.M. and T.P.M. with 70% and 95% S.M.M. was noted (Table 2).

With ONESAMP1.1 (Tallmon et al., 2008), it was estimated that the effective population size (Ne) was 23.5 (confidence limits 95% = 20.74-31.5), and with LDNe, 16.5. Ne as a mean between 23.5 and 16.5 was considered for further calculations.

The high percentage of alleles with allelic frequency of 0.01 (17%), or lower than 0.05 (32.1%) and 0.10 (46.2%), presume the risk of loss in future generations. The probability of future loss of alleles with frequencies from 0.01 to 0.10, considering N = 20.0 (mean between calculations by LDNe and ONESAMP) were 0.67 for alleles with a frequency of 0.01 (17%), and 0.44, 0.30, 0.20, 0.13, and 0.02 for alleles with allelic frequencies of 0.02 (3.8%), 0.03 (7.5%), 0.04 (5.7%), 0.05 (1.9%), and 0.10 (2.82%), respectively (Figure 2). It is possible that 6.6% of all the alleles have already been lost, as they appeared only in samples dating from 1983 through 1995, and not in more recent ones. Using the equation He = 1-1/(2Ne)t, it was calculated that, in one generation, an effective population size of 20 individuals loses 0.025% of the variation present in the initial population.

 

 

The cause of death was recorded in the case of field samples (71.4% and 81.25% of all the females and males, respectively). The main cause was farmer retaliatory hunting, due to livestock depredation (74% of all deaths, and 92.8% and 53.8% of female and male deaths respectively). Human action was instrumental for 92.86% of all deaths/captures (100% and 84.6% of females and males, respectively). Road kills were responsible for 7.2% and 7.7% of female and male deaths, respectively. Only males were captured (23.2%), or killed by disease (15.4%).

 

Discussion

The absence of genetic structure in the study area corroborates data obtained by Castilho et al. (2011) for this population, in that the surroundings are still permeable for mountain lions, possibly arising from the long distances that this species is capable of traveling (Sweanor et al., 2000; Logan and Sweanor, 2001), even though through discontinuous habitats (Logan and Sweanor, 2001; Castilho et al., 2011). Ruiz-Garcia et al. (2009) found genetic similarity among individuals from the Bolivian Andes, and samples from Colombia, Peru, Ecuador, Venezuela, and the west Brazilian Amazon.

Severe habitat loss is one of the major causes of genetic loss and extinction risk in animals in general, and carnivore populations in particular (Nowell and Jackson, 1996). Bottlenecks caused by habitat loss have been recorded for several species (Hoelzel, 1999; Kuo and Janzen, 2004; Culver et al., 2008), these always indicating the need for attention to the population that has undergone a reduction in size, because of the increased extinction risk of both the population or species (Montgomery et al., 2000; Reed and Frankham, 2003; Frankham et al., 2005; O'Grady et al., 2008).

Evidently there has been a recent bottleneck in the south Brazilian mountain lion population. The excess of heterozygosity observed when a population has suffered a recent bottleneck can be detected during 0.25 to 2.5 x 2 Ne generations (41 to 412 years for P. concolor), after which allelic frequencies again regain equilibrium. The bottleneck that was detected in the present study possibly started when intense deforestation occurred in the Araucaria Forest in south Brazil. From the early 1900's, this has brought about the loss of almost 90% of the original vegetation cover. Concomitantly, in addition to the extensive loss of habitat, many loggers hunted mountain lions and their prey species for food or protection. Although illegal, the hunting of mountain lions and prey species still persists (Mazzolli et al., 2002). A severe decrease in population through human intervention can induce genetic loss (Allendorf et al., 2008). Thus, poaching can be held directly responsible for bottlenecks, and the consequential loss of genetic diversity, in several animal species (Bonnell and Selander 1974; Larson et al., 2002; Culver et al., 2008; Bishop et al., 2009). Furthermore, bottlenecks induce the loss of low-frequency alleles, and, consequentially, of genetic diversity through inbreeding and genetic drift (Allendorf and Luikart, 2007), thereby increasing the susceptibility to inbreeding depression effects, such as reproductive and cardiac problems, and epidemic diseases (O'Brien and Evermann, 1988; Roelke et al., 1993).

Molecular markers show that North American mountain lions comprise a large panmictic population, with reduced genetic variation compared to the South Americans (Culver et al., 2000). Most likely, the present-day North Americans descended from a founder event involving a small number of individuals that had migrated out of South America approximately 10,000 years ago (Culver et al., 2000). Therefore, higher genetic diversity in southern Brazil could be expected, when compared with North American studies. However, on comparing genetic diversity found for P. concolor with that for North American samples (Kurushima et al., 2006; Rodzen et al., 2007) (Table 3), the observed mean number of alleles/locus and the expected heterozygosity estimated in the present study were found to be lower, when using the same species-specific primers (n = 243 individuals from California and Nevada, and n = 23-25 individuals from California) (Kurushima et al., 2006; Rodzen et al., 2007).

Furthermore, diversity in individuals from south Brazil was lower than that found for previously analyzed South American mountain-lion populations (Table 4). The present results cannot be directly compared to other studies in South America, since different sets of microsatellites were used by all. Even so, by using species-specific primers, higher heterozygosity could be expected. Diversity in the individuals from south Brazil was lower than that indicated for other previously analyzed South-Americans. The mean number of alleles/locus was lower in the former than the latter, except when compared with São Paulo and Bolivian samples. Mean heterozygosity was also lower, except when compared with Bolivian samples, although this may have been due to the small number of samples used (9 and 8 individuals respectively) (Miotto et al., 2007; Ruiz-Garcia et al., 2009). This appears to indicate a loss of genetic diversity in south Brazilian mountain lion populations.

According to evident inbreeding and the estimated global value, this population may be in the process of losing genetic variability. Both estimates of effective population size were lower than Ne = 50, the number necessary for diminishing the loss of genetic diversity by inbreeding (Soulé, 1980), and Ne = 500, the number necessary for preventing long-term loss of variability by genetic drift (Franklin, 1980; Frankel and Soulé, 1981). This observed loss of genetic diversity is probably a consequence of the recent bottleneck this population apparently underwent. On increasing, with inbreeding and low Ne, this loss can lead to reduced adaptive potential and increased inbreeding depression, with vulnerability to environmental, demographic and stochastic variation, and a consequential increase in the probability of extinction (Reed and Frankham, 2003; Spielman et al., 2004; Frankham et al., 2005). Inbreeding may also affect both individual and population performances (Keller and Waller, 2002).

Conserving Brazilian mountain lions

As carnivores exert considerable influence on ecosystems and the maintenance of their ecological processes (Henke and Bryant, 1999; Miller et al., 2001; Terborgh et al., 2001; Ray et al., 2005), environments where mountain lions have disappeared through human presence and intervention manifest decreased biodiversity (Ripple and Beschta, 2006). Carnivores in general are secretive and nocturnal, comprise small populations, and are frequently endangered. These characteristics, although making it difficult to study them, increase the need for further information, thereby making conservation genetics an essential tool for the purpose. Little is known on mountain lion genetic variability in south Brazil, this constituting a crucial item for both understanding the evolutionary potential of the population and for determining the best strategy for their conservation and management.

A recent bottleneck and loss of genetic diversity were identified in this population. As it is well-known that a decrease in population size and the consequential loss of genetic diversity increase the risk of extinction (Hoelzel, 1999; Dalén et al., 2006; Hájková et al., 2007; Culver et al., 2008), special attention should be dedicated to conservation action, in order to reduce the risk in this case.

Apart from human persecution induced by financial loss, poaching and human exploitation are the major causes of death in carnivores (Nowell and Jackson, 1996). Although hunting is illegal in Brazil, it still occurs in many areas, including in the southern part of the country. In the studied samples, human action was responsible for 92.86% of all the deaths/captures (100% and 84.6% of females and males, respectively), 74% the result of poaching. Although this high percentage may be owing to the sampling method employed, obviously it still indicates the importance of the impact in the area. Weaver et al. (1996) found that 75% of all mountain lion deaths in North America were caused by human persecution, and Morrison and Boyle (2009) that 50% were by direct human action. Poaching also caused a general decline in the mammal population of the Atlantic Rain Forest (Cullen et al., 2000; Paviolo et al., 2008, 2009). The population in south Brazil is, without doubt, still prone to poaching and persecution by way of farmer retaliatory hunting (Mazzolli et al., 2002; Marins-Sá, 2005, MSc Dissertation, Curso de Pós-Graduação em Ecologia UFRGS, Porto Alegre), and although the observed bottleneck was probably caused by intense deforestation and habitat loss, it is currently believed that illegal poaching poses the largest local threat. Since this population has undergone a recent and intense reduction in size (identified by the evident bottleneck), with the consequentially low effective population size and decrease in genetic diversity, poaching will probably further increase the risk of extinction.

Conservation efforts may focus on the population level, instead of the species (Garner et al., 2005), since extinction rates for populations are estimated to be three to eight times higher than for species (Hughes et al., 1997). For P. concolor, a species that has a geographically diversified environment and various subspecies (Culver et al., 2000), as well as manifold genetic diversity across its range, and a variable intensity of threats, the best conservation strategy could be to develop regional conservation plans according to the identified threats for each region. Therefore, it is believed that mountain lion conservation efforts in south Brazil should be directed towards mitigating human-versus-predator conflicts due to livestock depredation, since this appears to be a grave threat and the principal cause of mountain lion deaths in the area nowadays. Mazzolli et al. (2002), when studying the causes of mountain lion depredation in south Brazil, observed that ranches without management plans lost as much as 78% of the goats and 84% of the sheep, whereas losses were substantially reduced if the herds were corralled at night. The authors observed that mountain lions often killed several free-ranging sheep or goats in a single attack, but would take only a single animal from a corral, thereby indicating that ranchers that have introduced management plans for their livestock are prone to few or no losses to mountain lions, thus implying that less conflict is possible with rancher cooperation. Furthermore, education programs should be intensified, with a focus on local populations and farmers, and genetic monitoring programs, implemented for surveying the fluctuation of genetic variability, since there are indications of an imminent loss in coming generations.

 

Acknowledgments

The authors thank the LAMAQ/UFSC and Capão da Imbuia museums, M. Mazzolli, P.W.V. Castilho, M. Graipel, S. Althoff, A. Fillippini, M. M. Mendoça, I. Croda, W. Veronezi, C. Silveira, T. C. Margarido, R. Von Hohendorff, M.E. Saito, landowners, and partners of the project for help in sample collecting. We also thank the staffs of the São Joaquim National Park/ICMBio and the Instituto Serrano de Conservação da Natureza-ISCN for technical and logistical support. We are grateful to Martha T.B. Wallauer and Jordan P. Wallauer for technical assistance, as also to P. Estrela, G.L. Gonçalves, C.M. Lopes, G.P. Fernández, E. Eizirik, P.G. Crawshaw Junior, R. Hoelzel, and anonymous reviewers for suggestions on earlier versions of this manuscript. This research was financially supported by the Conselho Nacional de Pesquisa (CNPq) and the Fundação de Amparo à Pesquisa do Rio Grande do Sul (FAPERGS).

 

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Send correspondence to:
Camila S. Castilho.
Departamento de Genética, Universidade Federal do Rio Grande do Sul
Av. Bento Gonçalves 9500, Prédio 43323M, Caixa Postal 15053
91501-970 Porto Alegre, RS, Brazil.
E-mail: cscastilho@hotmail.com.

Received: April 4, 2011; Accepted: September 14, 2011.

 

 

Associate Editor: Fabrício Santos
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