Population structure of Athene cunicularia (Strigiformes: Strigidae) in anthropized areas in the state of São Paulo, BrazilAbstract
Anthropogenic processes commonly interfere in the way communities of local species establish themselves in the environment, especially the urbanization process. Some species, such as the burrowing owl Athene cunicularia (Strigiformes: Strigidae), have characteristics that allow them to occupy urban areas successfully. However, this capacity of occupation does not mean that urbanization cannot negatively affect them. Given that genetic variability is extremely important for maintaining adaptive capacity to environmental changes, investigating the level of structuring and genetic diversity within populations has proven to be an excellent tool for understanding the adaptive responses of species. Thus, the genetic structure and diversity of three populations of burrowing owls in anthropized São Paulo, Brazil, were investigated using seven species-specific microsatellite markers. It is important to emphasize that there have been no studies on A. cunicularia in Brazil from a genetic point of view. The results of the genotypic analysis of genetic diversity, together with information about the distribution of this diversity, indicate that the populations of A. cunicularia analyzed have considerable genetic differentiation and that this is positively related to the geographic distance of individuals. This genetic differentiation is due to the presence of rare and exclusive alleles in populations, a result of the isolation process by distance caused by the reduction in gene flow, which seems to occur due to the selection of habitats and the nesting behavior of the species. The excess of homozygotes observed in these populations that led to deviation from Hardy–Weinberg equilibrium is characteristic of the Wahlund effect, and analyses identified an ancestry composed of six genetic units in the evolutionary history of A. cunicularia, which is still present across the three sampled localities.
Keywords
Anthropized areas and urbanization; burrowing owl; genetic diversity; microsatellite DNA; population genetics.
Resumo
Os processos antrópicos comumente interferem no modo como as comunidades de espécies locais se estabelecem no ambiente, em especial o processo de urbanização. Espécies como a coruja-buraqueira, Athene cunicularia (Strigiformes: Strigidae), têm êxito em ocupar áreas urbanas, entretanto, esta capacidade de ocupação não significa que elas não possam ser negativamente afetadas pela mesma. Sabendo que a variabilidade genética é de extrema importância para que as populações mantenham sua capacidade de adaptação frente às mudanças ambientais, investigar o nível de estruturação e diversidade genética contida nas populações tem demonstrado ser uma excelente ferramenta de estudo na compreensão das respostas adaptativas das espécies. Assim, foi investigada a estrutura e diversidade genética presente em três populações de corujas-buraqueiras em áreas antropizadas no interior Paulista, utilizando sete marcadores microssatélites espécie-específicos. Ressalta-se que até o momento não há registros de estudos com A. cunicularia no Brasil do ponto de vista genético, sendo este então pioneiro. Os resultados da análise genotípica de diversidade genética, juntamente com as informações sobre a distribuição desta diversidade, indicam que as populações de A. cunicularia analisadas possuem considerável diferenciação genética e que esta se relaciona positivamente com a distância geográfica dos indivíduos. Esta diferenciação genética se deve pela presença de alelos raros e exclusivos nas populações, resultado do processo de isolamento por distância ocasionado pela redução de fluxo gênico que, ao que tudo indica, ocorre devido à seleção de habitat e comportamento de nidificação da espécie. O excesso de homozigotos observado nestas populações, que levou ao desvio do equilíbrio de Hardy–Weinberg é característico do efeito Wahlund, e as análises identificaram uma ancestralidade composta por seis unidades genéticas na história evolutiva de A. cunicularia, a qual ainda está presente nas três localidades amostradas.
Palavras-chave
Áreas antropizadas e urbanização; coruja-buraqueira; diversidade genética; DNA microssatélite; genética de populações.
Introduction
Recurrently, natural populations are affected by environmental changes promoted by human activities, such as the urbanization process (Frankham et al. 2009). Urban development constitutes a severe and long-lasting form of landscape alteration (Evans et al. 2011), whose effects on biodiversity have been growing in recent decades (Marzluff 2001). Since preexisting vegetation is removed, alterations can occur, such as changes in biogeochemical cycles, the soil, the direction of rivers, modifications in the microclimate, and artificial structures in the environment (Alberti et al. 2003, Grimm et al. 2008). Thus, urbanization causes significant ecological change and is strongly associated with the loss and fragmentation of natural habitats (Evans et al. 2011). Nevertheless, some birds have found ways to cope with the challenges presented by urbanized habitats and have colonized them; these are what we call urban adapters. As an example of a great urban adapter, we have burrowing owls. These owls are typically associated with open grasslands but are frequently found on poles and roofs due to urban colonization (Sick & Barruel 1997). Additionally, because of the urban nature of the field, burrowing owls exhibit the behavioral innovation of digging their own burrows, a new adaptive characteristic (Martínez et al. 2017). However, despite the behavioral plasticity of these owls (Martin 1973a), this species has a hierarchical nature of habitat selection that makes them susceptible to habitat fragmentation effects (Baladrón et al. 2016). These consequences could isolate populations, decrease genetic diversity and increase genetic distance and endogamy rates (Frankham et al. 2009). It is essential to consider that human actions promote rapid environmental changes, which tend to subject organisms to different pressures from those existing in a natural environment (Mueller et al. 2013). Additionally, this evolutionary scenario involves changes occurring on a much shorter time scale than those organisms had in their evolutionary past (Julian et al. 2003). Genetic variation directly influences the evolutionary responses of a population to selection pressure conditions (Lankau et al. 2011).
The species Athene cunicularia has an extensive area of occurrence extending from southern Canada to the USA through the Tierra del Fuego, Argentina (König & Weick 2008). Even with a wide continental occurrence, most of the population genetic studies have been carried out only in temperate climates (e.g., Desmond and Savidge 1999, Korfanta et al. 2005, Macías-Duarte et al. 2019). In South America, few genetic investigations have been carried out (e.g., Mueller et al. 2018). There are no genetic analyses of A. cunicularia in Brazil, while research related to diet, habitat, and hunting behavior is more common in this country (e.g., Desmond & Savidge 1999, Motta Junior & Alho 2000, Specht et al. 2013, Santos 2019). Therefore, research aimed at obtaining a better understanding of Brazilian populations of burrowing owls from a genetic perspective is still lacking. In this paper, our goal was to conduct the first genetic analysis of Athene cunicularia in Brazil. We then conducted a population analysis of burrowing owls in urban areas, characterized their variability, investigated the population structure, and described the kinship relationships among individuals. For this purpose, we used species-specific microsatellite molecular markers. Microsatellite DNA markers are well known and commonly used for genetic population structure studies (Ellis & Burke 2007). Variation in the number of repeated nucleotide elements gives microsatellites a high degree of polymorphism, which makes them one of the most polymorphic types of markers in the genome (Ellegren 2004).
Materials and Methods
1. Study site
We conducted our study in anthropized areas in São Paulo, Brazil, where the land cover corresponds to urban centers such as buildings, curbs and city outskirts such as highways. We sampled the owls at São Paulo State University Campus, Jaboticabal (JAB: 21°15’17” S, 48°19’20” W); Ribeirão Preto city (RIB: 21° 12’ 42” S, 47° 48’ 24” W); and São José do Rio Preto city (SJR: 20° 49’ 13” S, 49° 22’ 47” W). To define the sampling areas, we selected three sites separated by straight-line distances of 35 km (JAB-RIB), 74 km (JAB-SJR), and 100 km (RIB-SJR). These distances are well above the dispersal capacity previously reported for burrowing owls (Riding & Belthoff 2018). These cities are surrounded by sugarcane and other plantations, livestock, and forest reserves; thus, it is possible to find burrowing owls within and between these cities (Figure 1).
Satellite images of the sampled locations (red markers). (a) Our study was in São Paulo, Brazil. The colorful area on the map marks the cerrado biome; the green areas are the native areas, and the yellow areas are the anthropized areas. (b) JAB sampling site, Jaboticabal, SP. (c) RIB sampling site, Ribeirão Preto, SP. (d) SJR sampling site, São José do Rio Preto, SP. Source: Google Earth-Mapas (2021) and MapBiomas (2021).
2. Sample collection
Between 2019, 2020, and 2021, we sampled 49 different adult burrowing owls: 20 from JAB, 15 from RIB, and 14 from SJR. The sex of the individuals was not identified. Of these, 41 owls were captured during the chicken-rearing season (late November to early January); five samples were provided by Dr. Karin Werther from the Department of Veterinary Pathology and Veterinary Hospital “Governador Laudo Natel”, FCAV-UNESP, Brazil; and three samples were collected from individuals who died on highways. As can be seen from the capture dates, this work was carried out during the lockdown in the Covid-19 pandemic. The sample size selected per population allows accurate estimation of population diversity and specific genetic differentiation due to the characteristics of the molecular markers used (Hale et al. 2012).
The burrowing owls were captured in their nests using a tomahawk trap and playback song, adapting the method described by Martin (1971). The tomahawk was fitting due to the ground-nesting behavior of the burrowing owl, high activity in the morning and strong burrow defense early in the reproductive cycle. The playback song was a value addition that made the capture process faster, optimizing the sampling effort. We used a song (Rocha 2014) available on the Wikiaves website for Athene cunicularia. By comparing the spectrogram of this song with the spectrograms available in Martin (1973b), it is possible to categorize it as a coo coo, a primary song usually played by males whose function is to form pairs of precopulatory and territorial defenses. This kind of song was great for luring the owls to the trap and working for males and females. Thus, the entire capture process took an average of two hours per owl, and the total sampling effort was approximately 82 hours over the 15 days per area.
The owls captured were marked with a superficial feather cut in the nape that could be seen at a distance, and even though it was temporary, it remained long enough that no recapture occurred during work. Through manual restraint, we collected pectoral plumes. Their smaller caliber makes them easy to obtain, reducing the birds’ restraint time and stress levels. Each sample was stored in absolute alcohol at the Animal Tissue Collection of the Evolutionary Biology Laboratory (CTA-LaBE), FCAV-UNESP, Brazil. All capture and collection procedures complied with SISBIO license no. 68449 and were approved by the Animal Use Ethics Committee (CEUA) of FCAV-UNESP, Brazil. Data from this sample are publicly accessible and deposited in the Brazilian Biodiversity Information System (SiBBr) (https://doi.org/10.71819/smkeus).
3. DNA extraction and SSR amplification
We extracted DNA from feathers using a DNeasy Blood and Tissue® Kit (Qiagen) and a NucleoSpin® Tissue Kit (Macherey-Nagel). PCR was performed on an MJ Research PTC-100 Thermal Cycler (GMI, Inc.) in 15 µl containing 7.5 µl of GoTaq® Master Mix (Promega), 0.6 µl of the primers forward and reverse at 2 mM, 4.3 µl of deionized water and 2.0 µl of DNA at 100 ng.
The seven microsatellite loci were amplified using species-specific SSR primers for A. cunicularia: ATCU04, ATCU06, ATCU08, ATCU23, ATCU43, ATCU45 (Macías-Duarte et al. 2010), and BUOW11 (Korfanta et al. 2002) following the methods described by the developers, with some adaptations in temperature. Touchdown PCR was used to amplify all loci within the annealing temperature range, for which the initial temperature was increased by 2°C every 30 s until the final temperature was reached. Therefore, the PCR touchdown profiles for the primers ATCU04, ATCU06, ATCU08, ATCU23, ATCU43, and ATCU45 included an initial denaturation step of 5 min at 95°C; 34 cycles of 30 s at 95°C, 30 s at 52–62°C, 30 s at 72°C, and 10 min at 72°C; and an indefinite hold at 4°C. The PCR touchdown profile for the primer BUOW11 included an initial denaturation step of 9 min at 96°C, followed by 34 cycles of 45 s at 95°C, 30 s at 54–60°C, 45 s at 72°C, the elongation step of 10 min at 72°C, and an indefinite hold at 4°C.
The PCR products were mixed with 0.1 μl of loading dye containing bromophenol blue and xylene cyanol (Thermo Fisher) and resolved in a 3% MetaPhor (Lonza) high-resolution agarose matrix. The results were visualized by UV transillumination after staining the gel with 0.5 μg/ml ethidium bromide. The alleles were detected and measured relative to a 50–1000 bp region from the Low Range DNA Ladder (Cellco Biotec).
4. Genetic diversity
We assessed our dataset for null alleles using Micro-Checker v.2.2.3 (Van Oosterhout et al. 2004) to avoid an overestimation of population differentiation caused by the presence of false homozygotes (Chapuis & Estoup 2007). For each locus-by-population combination, genetic diversity was quantified by the total number of alleles per locus (N), frequency of the most common allele (freq), number of unique alleles observed, observed heterozygosity (Ho), and expected heterozygosity (He) (Nei 1978). Deviation from Hardy–Weinberg equilibrium (HWE) and linkage disequilibrium between all pairs of loci were calculated using Arlequin v.3.5.2.2 (Excoffier & Lischer 2010), and a family-wise error rate of 0.05 was obtained by applying a Bonferroni correction (Weir 1990). Additionally, in Arlequin, we computed the modified Garza-Williamson index (Garza & Williamson 2001) to detect population bottlenecks using microsatellite data. This statistic calculates the mean ratio of the number of alleles at a given locus to the range in allele size. The results can vary from 0 to 1, where the critical values M < 0.68 indicate a bottleneck and M > 0.80 indicates a stationary population.
To estimate the overall genetic variation resulting from differentiation among the three A. cunicularia populations, we computed unbiased global and pairwise FST values using FreeNA software (Chapuis & Estoup 2007). This software considers the potential bias reflecting the presence of null alleles using the excluding null alleles (ENA) correction method. We set 10,000 replicates to bootstrap a 95% confidence interval for the global and pairwise FST. The genetic distance analysis (δµ)2 was estimated in Arlequin v.3.5.2.2 using the stepwise mutation model (SMM), which is specific for microsatellite data (Goldstein et al. 1995) and presented as a comparison matrix between the three locations where the individuals were sampled. The correlation between geographic distance and genetic distance was measured using the R package vegan (Oksanen et al. 2020) with pairwise genetic distance data for all individuals and their geographic locations obtained from GPS.
5. Genetic structure
We investigated whether there was a genetic population subdivision and the best group for the genotypes. For this purpose, we used the Bayesian clustering STRUCTURE v.2.3.4 to infer the number K of clusters without using prior information on source populations. In this way, the algorithm minimizes the Hardy‒Weinberg deviation and linkage disequilibrium (Pritchard et al. 2000).
Thus, the Markov Monte Carlo (MCMC) chain was run for 1 million generations, with an initial burn-in of 10% of discarded steps and 10 iterations of each K. The mixture model adopted was admixture, considering that the individuals may have mixed ancestry and may inherit a fraction of their genome from ancestors of these populations. The final posterior probability of K was calculated using the runs with the highest likelihood for each K. In the end, the value of K was selected using delta K (Evanno et al. 2005) through Structure Harvester (Earl & Vonholdt 2012).
We tested the possible groups generated by distribution analysis and determined the level of genetic sharing between the groups sampled through analysis of molecular variance (AMOVA) in Arlequin v.3.5.2.2. This population genetic structure was estimated with Wright’s fixation index (FST) but with the alternative statistic RST (Slatkin 1995); this statistic is useful for microsatellite data because, unlike FST, it assumes a stepwise mutation model. Sequential Bonferroni correction was applied to correct type I errors when appropriate (Rice 1989).
6. Kinship analysis
Kinship analysis of owls was performed using the maximum-likelihood method to predict parent-offspring relationships. For this purpose, Cervus 3.0.7 software (Kalinowski et al. 2010) initially calculates the allele frequencies, and then, a simulation of kinship relationships is performed; from these two generated datasets, the software estimates the final kinship relationships. In addition, we used the parent pair (Sex Unknown) option, which is the most appropriate method when there is no information about any of the parents or the sex of the sampled individuals.
The LOD score provides the relationship validation, resulting from the natural logarithm of the general likelihood ratio. A relationship with a positive LOD indicates that the probability of the candidate individual being the true parent of the analyzed individual is more significant than not being. Conversely, a negative LOD suggests that the probability of a candidate being the appropriate parent is lower than that of not being. Finally, a LOD of zero indicates that the probability of the candidate being the proper parent is equal to that of not being (Kalinowski et al. 2010).
Results
1. Genetic diversity
The seven microsatellite loci analyzed for the 49 individuals in the three sampled localities showed 100% polymorphism, with the number of alleles per locus ranging between 5 and 10. Overall, 49 genotypes and 55 alleles were identified, 12 of which were rare alleles (frequency < 0.05). Loci ATCU06 and BUOW11 had the highest number of these alleles (3), while ATCU04 was the only locus without rare alleles. We identified rare and exclusive alleles in all three populations through the frequency of the loci by the populations sampled. In JAB and SJR, we identified rare and exclusive alleles at the ATCU28 and BUOW11 loci, respectively. The JAB population presented the highest number of exclusive alleles (3), and the SJR population presented the highest number of rare alleles (10) (Supplementary Table S1).
In the first analysis, considering the 49 individuals as a single population, all p values were significant after Bonferroni correction, and the Ho was lower than the He, with all seven loci presenting deviations in the Hardy‒Weinberg equilibrium (Table 1). However, when we analyzed HWE by population, only JAB had significant p values for all loci with Ho values lower than He after Bonferroni correction. The other populations did not show significant p values for 57% of the loci sampled (Table 2). The genetic distance analysis (δµ) specific for microsatellite markers indicated that the highest genetic divergence occurred between RIB and SJR (1.26948), while the lowest genetic divergence occurred between JAB and SJR (1.02065) (Table 3). In addition, the Garza–Williamson index for the three burrowing owl populations was greater than the critical value of 0.68 (RIB = 0.97, JAB and SJR = 1.00). Thus, there was no reduction in the effective population size.
Genetic variation per microsatellite loci of Athene cunicularia in São Paulo, Brazil, considering the 49 individuals sampled as a single population.
Genetic variation using microsatellites for each population assessed for Athene cunicularia in São Paulo, Brazil. In bold, non-significant values after Bonferroni correction.
There was no evidence that linkage or occurrence of the null allele at the studied loci reflected analysis errors. Therefore, although linkage disequilibrium loci were present in both analyses, removing individuals as a single population and the three populations separately did not change any observed pattern. Just as the estimation of null allele frequencies indicated the possibility of null alleles at six of the seven loci analyzed due to the high number of homozygotes observed, the comparison did not reveal significant changes after correction. Thus, this work presents results based on the analysis of all loci.
The Mantel test for pairwise individuals indicated a positive correlation between genetic and geographic distances (r = 0.1554). In addition to being a low-to-medium correlation, it is important to note that this does not necessarily mean that there is no relationship between them. Additionally, the significance value 5e-04 (or 0.0005) indicates that the correlation is unlikely to be random (Figure 2).
Correlation between genetic and geographic distances based on the Mantel test for pairwise comparisons among individuals based on seven microsatellite loci in three populations of Athene cunicularia from São Paulo, Brazil.
2. Genetic structure
An analysis of molecular variance showed no hierarchy, indicating substantial genetic structure for the three A. cunicularia populations in São Paulo (Table 4). The FST Fixation Index, which determines the degree of inbreeding of individuals concerning subpopulations, obtained a value of 0.52769 with a significant confidence interval after the Bonferroni correction. Furthermore, the AMOVA results using the RST distance indicated that 52.77% of the variance was among these populations, and the remaining 42% reflected the differentiation within them. According to the pairwise RST analysis, RIB and SJR were the only significant differences after Bonferroni correction, with RST = 0.20685 (Table 5).
Analysis of molecular variance (AMOVA) was performed using the RST distance among the three Athene cunicularia populations in São Paulo, Brazil (p < 0.001).
Matrix of population pairwise FST (below diagonal) using the sum of the size squared size difference (RST) and p value (above diagonal) estimates for seven microsatellite loci between the studied populations of Athene cunicularia. In bold, nonsignificant values after Bonferroni correction.
The Evanno method indicated that K = 6 was the most likely configuration for determining the genetic variability of the burrowing owls according to their similarity (Figure 3). With K = 6, all the JAB, RIB and SJR populations represented a mixture of all the clusters (Figure 4).
Bayesian inference of the number of genetic clusters (K) among 49 burrowing owls based on seven microsatellite loci in three populations of Athene cunicularia from São Paulo, Brazil.
Bar plot of Bayesian clustering generated by STRUCTURE for K = 6, based on seven microsatellite loci from three Athene cunicularia populations in São Paulo, Brazil. Each vertical bar represents one individual, and each color indicates the estimated membership in a genetic cluster. Individuals are grouped according to sampling location: JAB, RIB, and SJR.
3. Kinship analyses
In Cervus, according to LOD computing, eight sampled owls exhibited kinship relationships, four of which had confidence values higher than 95%. Additionally, the likelihood of having a father and mother together indicated possible parents for AC18 and AC35, with trio confidence values higher than 80%. Most of the relationships were between JAB individuals, but three were between JAB and RIB.
Discussion
Our genetic diversity results for the three populations of Athene cunicularia from São Paulo, Brazil, revealed a high polymorphism frequency in the seven loci analyzed. This high polymorphism rate has been documented in studies using the same loci in burrowing owl populations from Sinaloa, Mexico, California and Florida, USA (Korfanta et al. 2002; Macías-Duarte et al. 2010). Among the seven loci analyzed, the ATCU08 locus was the most polymorphic, with ten alleles. This same locus also exhibited the most polymorphism in Mexican and Californian populations. When we compare this locus with the others analyzed here, high polymorphism is genetically expected due to the positive correlation between the number of nucleotides and repeats of sequence motifs. ATCU08 is a dinucleotide with 20 repetitions and is thus more susceptible to slip events and, therefore, more frequent mutations. In contrast, ATCU04 (5 alleles) is a hexanucleotide with 18 repeats (Ellegren 2004). Even with high polymorphism, these Brazilian populations had lower allelic richness than did the populations mentioned above, except for the locus ATCU04, whose allelic richness was the same as that described for the Mexican burrowing owls. In total, we identified 28 rare alleles, JAB (7), RIB (9), and SJR (12), and six unique alleles, JAB (3), RIB (2) and SJRP (1). The presence of rare alleles may be due to a more recent evolutionary origin for these alleles, so there has not been enough time for them to disperse through populations (Neigel & Avise 1993). The probability of alleles being lost by stochastic events increases if they have a frequency lower than 0.05 and are present in small populations (Neigel & Avise 1993).
The consequence of this loss is a reduction in genetic diversity. However, most rare alleles identified do not have a low frequency in populations that are not rare. When we added the presence of exclusive alleles in this scenario, we strongly indicated that this allele distribution resulted from reduced gene flow between populations. In this case, the restricted allelic dispersion makes them rare or even exclusive in their populations. Low gene flow enhances differentiation between populations, and for these Brazilian owls, our microsatellite data showed that high genetic distance was positively correlated with geographic distance.
Of the three populations studied, only JAB was not included in the EHW population, which exhibited a deficit of heterozygotes. The same was observed when we analyzed the EHWs considering the 49 owls sampled as a single population. Nevertheless, the fact that JAB has the largest number of sampled individuals (20) and the largest allelic representation per locus may justify that the results of this population are close to those when we analyze all individuals together. Even so, these data suggest that evolutionary factors such as inbreeding and genetic drift may act on these owls and favor an increase in homozygosity.
Inbreeding in these populations can be easily explained by the behavior of the burrowing owl, which may limit its dispersal, such as through semicolonial nesting and philopatry, and because these factors are intensified by the fact that it inhabits urban areas. In addition, we have a medium degree of urbanization in the places where we capture these owls, which are growing cities with about a century of existence and a significant presence of urban constructions but still with wide open areas. With these data, we can consider genetic drift by the founder effect, where each city was colonized independently by a limited number of founders from adjacent rural areas, a phenomenon already reported for burrowing owls in Argentina (Mueller et al. 2018). In the future, the continuous growth of built-up areas may cause these populations to gradually lose their nesting sites. This could lead to a loss of genetic variability and initiate a population bottleneck. However, this remains a projection, as our data indicate these populations are currently stationary according to the Garza-Williamson index.
Our molecular variance analyses revealed more significant genetic variation among the three populations than within each of them, with a high fixation index (FST = 0.53), reinforcing the restriction of gene flow between populations. As previously mentioned, this approach increases the strength of the isolation by distance (as indicated by the Mantel test correlation coefficients). To understand the spatial scale at which this isolation occurs, we must consider that there is a vast presence of agroecosystems between the urban locations sampled, mainly for the planting of sugarcane, in which the reproductive success of burrowing owls tends to be less than 35% (Martínez et al. 2017).
A deficit of heterozygotes is also expected when the Wahlund effect occurs, in which subpopulations are structured. Additionally, through kinship analysis, we identified direct descending relationships between individuals of JAB and RIB (50 km distance); despite the structuring and genetic distance diagnosed for the populations and the inbreeding scenario, gene flow still occurred between the populations analyzed. Allelic sharing established by gene flow is possible when dispersal behavior is practiced by young individuals when they leave their nests in search of mates and new nesting sites. However, it is essential to emphasize that the geographic distance and the matrices that surround these areas can be obstacles to this, e.g., even with good sampling of the JAB and SJR populations (153 km distance), no kinship relationships were identified between the individuals present within them, suggesting that this event of dispersal and exchange of alleles between these owls occurred between small distances and that lower dispersal distances may be sufficient to generate genetic structure (Korfanta et al. 2005).
The presence of null alleles is a frequent concern with microsatellite markers, particularly when a heterozygote deficit is observed. However, our analyses allowed us to statistically state that the null alleles did not bias the results of this work. The frequency of null alleles up to 20% has little influence on genetic differentiation estimates (Chapuis & Estoup 2007), and the comparative calculation of FST and distance with and without null alleles did not reveal results with different resolutions.
All our data converge to an increase in isolation by distance between these populations of burrowing owls in São Paulo, Brazil, fitting the stepping-stone model (Slatkin 1987) of genetic structuring. In addition to this finding, the genetic structuring analysis revealed that individuals from the three sampled populations constitute six evolutionary genetic units. The small difference between the variance among and within populations reflects the genetic structuring observed via the FST index. This index shows that the greatest variation occurs between populations, yet ancestral similarity is still maintained. Despite these particularities, it is clear that geographic isolation occurred, followed by a decrease in gene flow. The population genetic evidence presented here provides a pioneering and relevant contribution to the genetic characterization of Athene cunicularia in Brazil. Consequently, this work opens new avenues for research into the population dynamics of this species and its relationship with anthropogenic processes.
Conclusion
Analysis of the population structure of Athene cunicularia in anthropized areas of inland São Paulo leads to the following conclusions: the presence of rare and exclusive alleles results in genetic differentiation between populations; this differentiation is directly correlated with geographical distance and may be attributed to restricted gene flow caused by land use, habitat selection, and the nesting behavior of burrowing owls. Furthermore, the deviation from Hardy–Weinberg equilibrium, indicated by an excess of homozygotes in these populations, is characteristic of the Wahlund effect, and analyses identified an ancestry composed of six genetic units in the evolutionary history of A. cunicularia, which is still present across the three sampled localities.
Supplementary Material
The following online material is available for this article:
Table S1 – Allele frequency based on seven microsatellite loci according to the locality of individuals of Athene cunicularia found in anthropized areas of the Cerrado in São Paulo State.
Acknowledgments
We thank Prof. Dr. Karin Wether for providing samples from the Department of Veterinary Pathology and Veterinary Hospital “Governador Laudo Natel”, FCAV-UNESP, Brazil; the Laboratory of Genetic of Bacteria (FCAV-UNESP) for providing equipment, and the members of the Laboratory of Evolutionary Biology (FCAV-UNESP) for collaboration in the analyses and discussions. CAPES for the scholarship granted to T.C.T.
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Ethics
The analysis was based on existing data in the literature.
Data Availability
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