Genetic structure in Brazilian breeding colonies of the Roseate Spoonbill (Platalea ajaja, Aves: Threskiornithidae)

INTRODUCTION

Accurate knowledge of local population structure can provide important insights into species biology, including social structure and the dispersal behavior of individuals (Dobson et al., 1998). Most of our knowledge of how genetic variability is partitioned among avian populations comes from studies on species from temperate latitudes. Genetic structure and dispersal studies of Neotropical birds, however, are scarce (Brown et al., 2004).

The Roseate Spoonbill (Platalea ajaja, Linnaeus 1758; Aves: Ciconiiformes) is a widely distributed Neotropical aquatic bird that breeds colonially from the southeastern United States (U.S.) to central Argentina. U.S. Spoonbill populations underwent a profound bottleneck from 1890 to 1920 (Powell and Bjork, 1990), and the species was listed as one of special concern (Florida Fish and Wildlife Conservation Commission, 1997). Brazilian breeding colonies of these birds are located in several wetlands at different latitudes, including the Pantanal region (Yamashita and Valle, 1990) and the lagoon areas along the coast of the State of Rio Grande do Sul (Encarnação and Diniz, 1992). Breeding period and composition are different in the colonies of these regions: Pantanal ones are established between July and October together with other species of Ciconiiformes (e.g., Wood Stork, Great Egret, and Snowy Egret) (Yamashita and Valle, 1990), whereas in Rio Grande do Sul, they occur during the period of September-February with White-necked Herons, Night Herons, Great Egrets, and Cattle Egrets (Silva and Bello Fallavena, 1995). To our knowledge, Brazilian reproductive and wintering areas have not been affected by population bottlenecks due to environmental stress or to anthropogenic disturbances. del Hoyo et al. (1992) classified Pantanal populations as declining, but they did not show data to support this information. On the other hand, Harris et al. (2005) point out that the Pantanal, one of the most continuous wetland areas in South America (approximately 1,000,000 km²; Neiff, 2001), is still well preserved.

Only one genetic study has been conducted on natural populations of the Roseate Spoonbill by Santos (2005), who performed an analysis of the mitochondrial DNA (mtDNA) control region and found no significant levels of genetic differentiation between individuals from the Brazilian Pantanal and Rio Grande do Sul regions.

In the present study, we estimated and characterized the distribution of genetic variability among Roseate Spoonbill populations from five Brazilian breeding colonies, using five polymorphic microsatellite loci. Our aim was to investigate genetic connectivity among breeding colonies to provide data that may be of key importance in supporting decision making regarding the management and conservation of these populations.

MATERIAL AND METHODS

Sample collection

A total of 69 samples were collected by either drawing blood or plucking growing feathers. The samples were from nestlings in four Pantanal wetland colonies in the States of Mato Grosso and Mato Grosso do Sul: Fazenda Ipiranga (N: 11; 16°25’S; 56°36’W), Porto da Fazenda (N: 8; 16°27’S; 56°07’W), Baia de Gaíva (N: 20; 16°39’S; 57°10’W), and Fazenda Retirinho (N: 18; 19°50’S; 56°02’W), and in one colony in the State of Rio Grande do Sul: Banhado do Taim (N: 12; 32°29’S; 52°32’W ) (Figure 1, Table 1).

Genomic DNA isolation

Blood samples were centrifuged, and cell and plasma fractions were frozen separately in liquid nitrogen. Growing feathers were also frozen in liquid nitrogen. DNA was extracted following the phenol-chloroform method (Sambrook et al., 1989). A tube containing no bird tissue was included in each group of DNA extractions as a contamination control.

DNA methods

Each sample was genotyped at five microsatellite loci using primers developed for Mycteria americana by Tomasulo-Seccomandi et al. (2003) and for Platalea ajaja by Sawyer and Benjamin (2006) (Table 2). To account for genotyping errors, 5% of the samples, randomly chosen, were amplified and genotyped three times. Extractions and amplifications were performed in separate rooms. Amplification reactions were prepared in a UV-sterilized cabinet, pipetting was performed using filtered tips, and one control PCR blank was included for each set of amplifications. PCR reactions were performed in a 25-µL final volume with 1 mM Tris-HCL, pH 8.4, 50 mM KCl, 50 µg bovine serum albumin, 2.5 mM MgCl₂, 0.25 mM dNTPs, 0.5 U of Taq DNA polymerase, and 50 ng template DNA in a GeneAmp^® PCR System 2400 thermal cycler (Applied Biosystems). Briefly, the PCR reaction profile was: 96°C for 5 min, 10 cycles for 45 s at 96°C, corresponding annealing temperatures for 45 s and 1 min at 72°C; 10 cycles for 30 s at 96°C, corresponding annealing temperatures -0.5°C per cycle (touchdown) for 30 s and 1 min at 72°C; 10 cycles for 30 s at 96°, 50° or 53°C (depending on primer) for 30 s and 1 min at 72°C. All reactions had a final extension for 10 min at 72°C. PCR products were sized in a MegaBACE™1000 automatic sequencer using the Gensize Rox 500 ladder as the internal standard (Amersham Biosciences). Results were analyzed using the GeneticProfiler^® software (Amersham Biosciences).

Data analysis

Microsatellite genotyping error rates (allelic dropout and false alleles) were calculated using GIMLET, v1.3.4 (Valière, 2002). A set of standard population genetic analyses was conducted to quantify genetic diversity within and among Roseate Spoonbill colonies. Gene frequencies were calculated using GENEPOP version 3.2 (Raymond and Rousset, 1995) and used to estimate other genetic variability parameters. Allelic richness (El Mousadik and Petit, 1996) was calculated using FSTAT, version 2.9.3.2 (Goudet, 2001). Gametic phase disequilibria and departures from Hardy-Weinberg equilibrium at each locus were determined with exact tests using a Markov chain algorithm (Guo and Thompson, 1992) in GENEPOP version 3.2 (Raymond and Rousset, 1995). Sequential Bonferroni corrections were used to adjust the P values obtained for possible type I errors (Rice, 1989). Levels of genotypic heterozygosity for each breeding colony at each microsatellite locus were assessed by calculating observed (Ho) and expected (HE) heterozygosity (also using GENEPOP, version 3.2). Heterozygosities were compared to the values obtained by Sawyer (2002) using the G test for contingency analysis (Zar, 1996) performed in BIOSTAT 3.0 (Ayres et al., 2003). Wright’s (1951) F_ST values were calculated for each locus independently, as well as for all loci. Pairwise comparisons between breeding colonies of the Roseate Spoonbill for estimators of F_ST were calculated using a variance-weighted determination of allele frequency in ARLEQUIN, version 2.0 (Schneider et al., 2000). Analysis of molecular variance (AMOVA, Excoffier et al., 1992) was also performed in ARLEQUIN using all colonies to estimate the total percentage of variance attributable to differences between colonies and differences among individuals within colonies.

RESULTS

Genetic diversity

Five of the six microsatellite loci tested were polymorphic in all breeding colonies. Locus WS09 was monomorphic in all colonies and it was excluded from further analysis. Individual multi-locus genotyping was reliable in separate amplifications for the repeated samples (across loci: allele dropout: 0.097; false alleles: 0.144). Gametic phase disequilibria between all pairwise microsatellite loci comparisons did not prove significant after performing a sequential Bonferroni correction (Rice, 1989). Genetic independence among loci was thus assumed for all subsequent analyses.

Average allelic richness ranged from 2.69 to 3.04 (Table 3). A total number of 34 alleles were detected across all loci, with allele numbers per locus ranging from 3 (WS03) to 10 (Aajµ1) (Table 2). A minimum of 17 alleles were detected in the Fazenda Ipiranga and Porto da Fazenda colonies and a maximum of 26 alleles at Baia de Gaíva. Seven alleles were unique to a single-breeding colony (Baia de Gaíva, four alleles; Fazenda Retirinho, three alleles). Ho across all loci was 0.575. Average Ho for each colony ranged from 0.499 (Fazenda Ipiranga) to 0.712 (Porto da Fazenda) (Table 2). Mean Ho per locus was: 0.768 (Aajµ1), 0.622 (Aajµ2), 0.637 (Aajµ3), 0.491 (Aajµ5), and 0.360 (WS03). No population showed significant departure from Hardy-Weinberg equilibrium, and estimates of F_IS (Table 3) for each population did not differ significantly from zero (P > 0.05), showing that genotypic frequencies are in accordance with that expected for a random-mating population (Hartl and Clark, 1997).

In the first analysis, including all colonies, global F_ST value was not significant (0.002, P > 0.05). In order to determine if this pattern would also be observed among more geographically distant colonies, two groups were defined: one joining only the Pantanal colonies (Baia de Gaíva, Fazenda Ipiranga, Fazenda Retirinho, and Porto da Fazenda) and the other including the sample of the Rio Grande Sul colony (Banhado do Taim). Non-significant levels of genetic differentiation were found in this test. Pairwise estimates of F_ST did not differ significantly from zero for any of the breeding colony comparisons, with values ranging from -0.020 (Fazenda Ipiranga vs Porto da Fazenda) to 0.015 (Baia de Gaíva vs Rio Grande do Sul) (P > 0.05). In agreement with the above results, the AMOVA analysis showed that most of the genetic variation present in the colonies can be explained by differences among individuals within breeding colonies (99%). In summary, Brazilian Roseate Spoobill populations did not show a significant population genetic structure.

DISCUSSION

From a total of six microsatellite loci studied, only the non-specific WS09 was monomorphic in the sample examined. This result is expected because locus WS09 was isolated from Mycteria americana, another species from the Ciconiiformes order, while the other five loci are species-specific (Sawyer and Benjamin, 2006). Overall observed heterozygosity was greater than that reported for other Ciconiiformes species. For example, Pantanal Wood Stork colonies showed lower heterozygosity levels (0.389, Van Den Bussche et al., 1999; 0.303, Tomasulo-Seccomandi, 2004) and Pantanal Jabiru Stork populations showed a value of 0.410 (Lopes et al., 2005). According to the G test, levels of genetic variability detected in Brazilian Roseate Spoonbill populations did not differ significantly from that determined by Sawyer (2002), in a U.S. wild-caught sample of 15 individuals, using data generated by the same set of microsatellite loci (Table 3). To explain these similar levels of genetic diversity in the U.S. and Brazilian populations, we can suppose, firstly, that these levels are inherent to the species, and that the northern population was not seriously affected by its documented reduction in size in the early 1900s. Another possible hypothesis for the observed similarity could be that the Brazilian population may have undergone undocumented population declines, as reported for the Pantanal region by del Hoyo et al. (1992). Studies including samples from other areas along the distribution range in the American continent, where there is no evidence of demographic decline, can help in clarifying if the U.S. population was not genetically affected or if both populations suffered a decline and loss of genetic variability.

Analyses based on multi-locus microsatellite genotyping indicate that genetic homogeneity characterizes Brazilian Roseate Spoonbill colonies. Observed F_ST values between Pantanal and Rio Grande do Sul populations were low and none differed significantly from zero. We found no evidence to support the possibility that coastal colonies (Banhado do Taim, RS) are genetically different from inland (Pantanal) colonies. Low levels of genetic structuring have been previously detected, using mtDNA and microsatellite data, in Pantanal populations of other Ciconiiformes species such as Jabiru and Wood Storks (Del Lama et al., 2002; Rocha et al., 2004; Lopes, 2006). The lack of evidence for strong genetic structure reported in the present study can be interpreted as follows: 1) colonies are of recent origin and have not had sufficient time to differentiate genetically, or 2) levels of gene flow have been maintained high between breeding colonies of this species. However, when interpreting our results we have to bear in mind that the performance of the commonly used estimators of genetic structure depends on the applicability of the underlying analytical models and on a number of other factors that are difficult to sort out clearly (Balloux and Lugon-Moulin, 2002). On the other hand, the results presented here, from an analysis using a highly variable nuclear molecular markers, are in accordance with the results previously reported using mtDNA (Santos, 2005), indicating that the population sampled merits recognition as a single-conservation unit (Allendorf and Luikart, 2007).

Genetic information has been widely used in management decision making. However, using only this approach is sometimes inadequate, because levels of genetic divergence and gene flow do not always correlate with ecologically relevant habitat adaptations (Hendry and Taylor, 2004). Moreover, according to Allendorf and Luikart (2007), many kinds of information, including environmental characteristics, may be integrated for identifying units of conservation. Roseate Spoonbills live in quite different habitats in Brazil, one that is strictly a freshwater environment in the Pantanal region, and the habitat where marine and fresh water mix in Banhado do Taim. Populations from these different places can show ecological adaptations that have not yet been investigated. Thus, we propose, at this time, not to consider the Pantanal and southern Brazilian colonies as a unique management unit. This proposal will conserve the evolutionary processes responsible for the actual patterns of genetic diversity, and the preservation of populations from different environments. This fact, as proposed by Allendorf and Luikart (2007), will allow selection pressures to be diverse and let multi-locus genotype diversity to remain high. This strategy should be applied to species lacking genetic differentiation and high gene flow but located in distinct environments so as to consider the local adaptations important to species survival.

In order to confirm if populations from these regions deserve recognition as independent conservation units, future studies in Roseate Spoonbills should focus on other markers (adaptive ones) to better explore the relationship between adaptive and neutral variation. A study with a more representative sample of the species along its distribution range, would also help unravel how genetic diversity is partitioned in these wading birds.

ACKNOWLEDGMENTS

We are extremely grateful to the farm owners that provided access to the Pantanal breeding colonies, to Mr. S. Scherezino for sending samples from Rio Grande do Sul, and to Mateus Henrique Santos for help with DNA extractions from blood and growing feathers. Research supported by a Brazilian National Research Council (CNPq) scholarship to C.I. Miño (32188/2004-0) and FAPESP-Brazil (04/15205-8).

REFERENCES

Allendorf FW and Luikart G (2007). Units of conservation. In: Conservation and the genetics of populations. Blackwell Publishing, Oxford, 380-420.

Ayres M, Ayres M Jr, Lima Ayres D and Santos dos Santos A (2003). BIOSTAT 3.0. Aplicações estatísticas nas áreas das Ciências Biológicas e Médicas. Sociedade Civil Mamirauá/MCT-CNPq/Conservation International, Mamirauá.

Balloux F and Lugon-Moulin N (2002). The estimation of population differentiation with microsatellite markers. Mol. Ecol. 11: 155-165.

Brown LM, Ramey RR II, Tamburini B and Gavin TA (2004). Population structure and mitochondrial DNA variation in sedentary Neotropical birds isolated by forest fragmentation. Conserv. Genet. 5: 743-757.

del Hoyo J, Elliot A and Sargatal J (1992). Handbook of the birds of the world: ostrich to ducks. Lynx Edicions, Barcelona.

Del Lama SN, Lopes IF and Del Lama MA (2002). Genetic variability and level of differentiation among Brazilian pantanal wood stork populations. Biochem. Genet. 40: 87-99.

Dobson FS, Chesser RK, Hoogland JL, Sugg DW, et al. (1998). Breeding groups and gene dynamics in a socially structured population of prairie dogs. J. Mammal. 79: 671-680.

El Mousadik A and Petit RJ (1996). High level of genetic differentiation for allelic richness among populations of the argan tree [Argania spinosa (L.) Skeels] endemic to Morocco. Theor. Appl. Genet. 92: 832-839.

Encarnação CD and Diniz MG (1992). Relatório Técnico 07/92. GETEC/Fauna-IBAMA/MG, Belo Horizonte.

Excoffier L, Smouse PE and Quattro JM (1992). Analysis of molecular variance inferred from metric distances among DNA haplotypes: application to human mitochondrial DNA restriction data. Genetics 131: 479-491.

Florida Fish and Wildlife Conservation Commission (1997). Florida’s endangered species, threatened species and species of special concern. Official lists [http://myfwc.com/imperiledspecies/species.htm].

Goudet J (2001). FSTAT, a program to estimate and test gene diversities and fixation indices.Version 2.9.3.2. http://www2.unil.ch/popgen/softwares/fstat.htm. Accessed December 15, 2005.

Guo SW and Thompson EA (1992). Performing the exact test of Hardy-Weinberg proportion for multiple alleles. Biometrics 48: 361-372.

Harris MB, Tomas W, Mourão G, da Silva CJ, et al. (2005). Challenges to safeguard the Pantanal wetlands, Brazil: threats and conservation initiatives. Conserv. Biol. 19: 714-720.

Hartl DL and Clark AG (1997). Principles of population genetics. Sinauer Associates, Inc., Sunderland.

Hendry AP and Taylor EB (2004). How much of the variation in adaptive divergence can be explained by gene flow? An evaluation using lake-stream stickleback pairs. Evol. Int. J. Org. Evol. 58: 2319-2331.

Lopes IF (2006). Variabilidade genética em populações de Ciconídeos (Jabiru mycteria e Mycteria americana): fluxo gênico e filogeografia. PhD dissertation, Universidade Federal de São Carlos, São Carlos.

Lopes IF, Haig S and Del Lama SN (2005). Genetic status and structure of the Jabiru storks from the Brazilian Pantanal. Meeting presentation. Thirty-Second Annual Meeting of the Pacific Seabird Group and Twenty-Seventh Annual Meeting of the Waterbird Society. January 19-23. Thirty-Second Annual Meeting of the Pacific Seabird Group and Twenty-Seventh Annual Meeting of the Waterbird Society, Portland, 82.

Neiff J (2001). Diversity in some tropical wetland systems of South America. In: Biodiversity in wetlands: assessment, function and conservation (Gopal B, Junk W and Davis J, eds.). Backhuys Publishers, Leiden, 157-186.

Powell GVN and Bjork RD (1990). Relationships between hydrologic conditions and quality and quantity of foraging habitat for Roseate Spoonbill and other wading birds in the C 111 basin. South Florida Research Center and Everglades National Park Services, Homestead.

Raymond M and Rousset F (1995). GENEPOP Version 1.2: population genetics software for exact tests and ecumenicism. J. Hered. 86: 248-249.

Rice WR (1989). Analyzing tables of statistical tests. Evolution 43: 223-225.

Rocha CD, Del Lama SN and Regitano LCA (2004). Lack of genetic structuring among tropical Brazilian wood stork populations and low genetic differentiation from north American populations. Biotropica 36: 248-258.

Sambrook J, Fritsch EF and Maniatis T (1989). Molecular cloning: a laboratory manual. Cold Spring Harbor Laboratory Press, New York.

Santos MH (2005). Estudo de haplótipos de DNA mitochondrial de colhereiros (Aves, Ordem Ciconiiformes, Platalea ajaja). MSc dissertation, Universidade Federal de São Carlos, São Carlos.

Sawyer GM (2002). DNA profiling of captive Roseate-Spoonbill (Ajaia ajaja) populations as a mechanism of determining lineage in colonial nesting birds. PhD dissertation, University of North Texas, Texas.

Sawyer GM and Benjamin RC (2006). Isolation and characterization of microsatellite loci for parentage assessment in captive populations of roseate spoonbill (Ajaia ajaja). Mol. Ecol. Notes 6: 677-679.

Schneider S, Roessli D and Excoffier L (2000). ARLEQUIN Version 2000: a software for population genetics analysis. Genetics and Biometry Laboratory, University of Geneva, Switzerland.

Silva F and Bello Fallavena MA (1995). Movimentos de dispersão de Platalea ajaja (Aves: Threskiornithidae) detectados através de anilhamento. Rev. Ecol. Lat. 2: 19-21.

Tomasulo-Seccomandi AM (2004). Populações de Mycteria americana L. (Aves; Ciconiiformes) da América do Norte e do Pantanal brasileiro: estruturação genética, razão sexual e assimetria flutuante. PhD thesis, Universidade Federal de São Carlos, São Carlos.

Tomasulo-Seccomandi AM, Schable NA, Lawrence Bryan A Jr, Brisbin IL Jr, et al. (2003). Development of microsatellite DNA loci from the wood stork (Aves, Ciconiidae, Mycteria americana). Mol. Ecol. Notes 3: 563-566.

Valière N (2002). GIMLET: a computer program for analysis in genetic individual identification data. Mol. Ecol. Notes 2: 377-379.

Van Den Bussche RA, Harmon SA, Baker RJ, Lawrence Bryan A Jr, et al. (1999). Low levels of genetic variability in North American populations of the wood stork (Mycteria americana). Auk 116: 1083-1092.

Wright S (1951). The genetical structure of populations. Annu. Eugenics 15: 323-354.

Yamashita C and Valle MP (1990). Sobre ninhais de aves do Pantanal do município de Poconé, Mato Grosso. Rev. Vida Silvestre Neotrop. 2: 59-63.

Zar J (1996). Biostatistical analysis. Prentice Hall, London.