The wide geographic range of Anastrepha ludens (Loew) (Diptera: Tephritidae) in Mexico and its ability to use various taxonomically unrelated host plant species suggests that this species has considerable evolutionary potential and represents a high risk pest. The genetic diversity and structure of A. ludens populations from 7 Mexican states (Chiapas, Yucatán, Morelos, Veracruz, San Luis Potosí, Tamaulipas and Durango) were investigated. Flies were collected as larvae from infested citrus fruits in each state, and sent as pupae to the Genetic Sexing Laboratory at the “Moscafrut ” facility in Metapa, Chiapas, where adults emerged and were used in isoenzymatic analysis. Genetic diversity was estimated based on expected and observed heterozygosity, mean number of alleles and polymorphism obtained from allelic and genotypic frequencies of 6 enzyme loci revealed in cellulose acetate. Expected heterozygosity (He) ranged from 0.199 to 0.330, and percentage of polymorphic loci (P) was between 50 and 67%. We found a high level of inbreeding (Fis = 0.393, Fit = 0.456) and moderate genetic differentiation among populations (Fst = 0.105). A negative correlation was found between elevation and He. We conclude that A. ludens populations are genetically diverse with moderate levels of differentiation. Genetic structure could not be attributed to the geographic distance among populations. Differentiation could be the result of natural selection associated with the colonization process. Genetic drift and pest management practices may have contributed to this differentiation to a lesser extent.
The Mexican fruit fly, Anastrepha ludens (Loew) (Diptera: Tephritidae), is widely distributed in Mexico, and it has also been recorded in the southern United States, Belize and Central America (Hernández-Ortíz 1992). Twenty two plant species have been reported as A. ludens hosts (Norrbom & Kim 1988). The species is native to México and Sargentia greggii Wats and Casimiroa edulis Llave & Lex of the Rutaceae family have been proposed as its native hosts (Plummer et al. 1941). Among commercial crops, Citrus spp. L. and Mangifera indica L. (Sapindales: Anacardiaceae) are the most economically important ones (Norrbom & Kim 1988; Hernández-Ortíz 1992).
The wide range of environmental conditions in which this species is found and its ability to use different taxonomically unrelated plant species as hosts, suggests that this species has considerable evolutionary potential and represents a high risk pest. A species' evolutionary potential is closely related to its population genetic variation (Futuyma 1986; Gould 1991). Greater genetic diversity increases the possibility to respond to natural and human induced environmental changes (Kim 1993).
Genetic diversity and structure of insect populations is determined by natural selection, by the differential movement of individuals between populations, the type of reproduction, random events (demographic and environmental) and the effective population size (Hedrick 2000; Zúñiga et al. 2006; Demirici et al. 2011). The level of genetic diversity and how it is distributed within and among populations depends on the intensity of each factor and how they interact (Slatkin 1994; Hedrick 2000). Population genetic studies with tephritid species have shown a wide range of genetic diversity (He). In Ceratitis capitata (Wied.), heterozygosity values based on isoenyzmes have been determined between He = 0.005 and He = 0.186 (Huettel et al. 1980; Gasperi et al. 1987; Vilardi et al. 1990). This variation has been attributed mainly to the geographic origin of the populations sampled.
Knowledge on genetic variability and its distribution among populations of tephritid species has been useful for pest management strategies; for example, to determine pest origin and to recognize migration routes (Reyes & Ochando 1998; Davies et al. 1999; Gilchrist et al. 2006). In the case of A. ludens, there is limited information on the genetic diversity of its populations. Pecina-Quintero et al. (2009) found moderate genetic diversity (index = 0.30) in a population in northeast Mexico using the AFLP technique.. Our goals in this study were to describe the genetic diversity of A. ludens populations from 7 states in México, and to estimate by means of enzymatic markers if these populations are genetically structured.
Materials and Methods
The samples of A. ludens were collected as larvae from infested citrus fruits (Citrus aurantium L., C. sinensis Osbeck, and C. paradisi Makfad.) in Chiapas, Durango, Morelos, San Luis Potosí, Tamaulipas, Veracruz and Yucatán from Sep 2008 to Jan 2009. Figure 1 shows collection sites and Table 1 shows the different climate types, mean annual temperatures, main natural vegetation at each site, altitudes and decimal coordinates, and the hosts collected at each location. Collections were made in small orchards of 500 to 10,000 m2. Flies collected at one farm or orchard in 3 states were considered as a population. In the case of Veracruz, Chiapas, Morelos and Durango, we grouped the flies collected in different sites in order to have a representative sample of each state and to avoid sampling biases with respect to the other 3 States.
Fruits infested with third instar larvae were collected. These fruits were taken to the local laboratory of the national fruit fly program (SENASICA- SAGARPA) in each State, and where larval development was completed. The larvae ready to pupate were placed in containers with vermiculite. The insects were shipped as pupae from the different locations to the Genetic Sexing Laboratory of the “Moscafrut” facility in Metapa, Chiapas, Mexico. Here, the pupae were maintained at 26 °C and 70% RH until adult emergence. Anastrepha ludens is by far the most common tephritid species found in citrus in Mexico. When adults emerged, their taxonomic identity was confirmed following Hernández-Ortíz (1992).
When adults were 15 days-old, a random sample of 40 individuals (20 males and 20 females) from each location was taken. Adult flies were individually placed in vials, frozen at -70 °C temperature and maintained at these conditions until electrophoresis. Six enzymatic loci were used as biochemical genetic markers, i.e., 6-Phosphogluconate Dehydrogenase (6PGDH, EC18.104.22.168), Glutamate-oxoloacetate transaminase (also known as Aspartate Amino Tranferase; GOT, EC 22.214.171.124), Glucose-6-Phosphate Isomerase (GPI, EC 126.96.36.199), Isocitrate Dehydrogenase (IDH, EC 188.8.131.52), Malate Dehydrogenase (MDH, EC 184.108.40.206), and Malic Enzyme (ME, EC 220.127.116.11); using CAMMP to pH 7.0 as electrophoresis buffer (see Herbet & Beaton 1993 for details). Each individual adult was macerated in 250 mL of a solution of CAAMP- pH 7.0 and centrifuged at 13,000 rpm during 3 min. The supernatant was used immediately for enzyme separation by electrophoresis in cellulose acetate.
Electrophoretic separation was carried out at room temperature, at 55 V and 30 mA during 150 min. We visualized the loci using the staining procedure indicated by Herbet & Beaton (1993). The number of individuals for each enzyme-genotype was recorded (Richardson et al. 1986; Herbet & Beaton 1993). We used only reproducible, clearly legible and interpretable electro-morphs. The percent of polymorphisms, and genotypic and allelic frequencies were estimated for each population. Expected (He) and observed (Ho) heterozygosity of each population were used as a measure of genetic diversity. We used all loci scored in this analysis. The average of all populations represented the diversity of A. ludens in Mexico. Chi-square tests for goodness fit were carried out to test if each of the loci was in Hardy-Weinberg equilibrium. Genetic diversity was compared within and among populations by Analysis of Molecular Variance (AMOVA) (Excoffier et al. 1992) using GeneAlEx software (Peakall & Smouse 2006). The relationship between genetic diversity (He) with altitude was analyzed by linear regression with arcsine(x)1/2 transformed data for He and log10 transformed data for altitude. To have additional statistical criteria on the significance of the relationship, the 95% confidence interval was calculated for the regression slope (Quinn & Keough 2002) using the packages mod.lm and boot.ci of software Statistical Data Analysis R version 2.13.2(R Development Core Team 2012).
Wright's F-statistics (Wright 1951), Fis, Fit and Fst, were calculated to estimate the level of inbreeding by ancestry in each population and the whole total population, and to estimate the level of differentiation among populations, respectively. F-statistics were calculated by AMOVA, and its framework allows for statistical testing by random permutation (Peakall & Smouse 2006; GenAlEx 6.4-Appendix 1-Methods and Statistics). Fis is the inbreeding coefficient within individuals in a given population and can be interpreted as a measure of the reduction in heterozygosity due to nonrandom mating within each population. Fit is the inbreeding coefficient within individuals in relation to the population (and accounts for both nonrandom mating and genetic differentiation among populations), and Fst provides a measure of genetic differentiation among populations (Peakall & Smouse 2006). All genetics parameters and AMOVA were obtained by using GenAlex software (Peakall & Smouse 2006)
Characteristics of the collection sites of Anastrepha ludens in 7 Mexican states. mat, mean annual temperature; nsv, natural surrounding vegetation; m asl, meters above sea level; decimal coordinates of municipality: lw, longitude west; ln, latitude north.
To analyze whether there was genetic differentiation between pairs of populations and isolation by distance pattern, a linear regression analysis was done between the Fst/(1-Fst) ratio and the geographic distances (km) calculated for all pairs of subpopulations. Pairwise Fst were calculated via AMOVA in GenAlex software (Peakall & Smouse 2006); the geographic distances were previously transformed to log10 (Slatkin 1994; Rousset 1997). The regression analysis was done with the software Statistical Data Analysis R and was used to calculate the 95% confidence interval of the regression slope.
We estimated by Nei's genetic distance among populations (Nei 1972), after an UPGMA (unweighted pair-group method with arithmetic mean) analysis, and the reliability of groups was evaluated by bootstrap analysis. UPGMA was carried out by the TFPGA genetic analysis program (Miller 1997). We include an analysis of population structures with a Bayesian approach implemented in the Software Structure 2.3.4 (Pritchard et al. 2000). Cluster analysis was based on the assignment of individuals to K clusters or populations inferred by a probabilistic estimation of the proportion of the genome that belongs to each K population. To obtain the value of K Structure we used a Bayesian approach and Markov Chain Monte Carlo (Pritchard 2000). We ran the program with the admixture option with a burn-in period of 10,000 iterations and a subsequent period of 10,000 independent runs of 1–7 populations were performed. The most likely K was recognized by the Evanno et al. (2005) method, and after the genome mapping of each of the individuals corresponding to the inferred cluster they were plotted to each population.
We recorded 6 loci of which 2 (GPI and MDH) were monomorphic in all populations. We recorded 2 alleles each for 6PGDH and GOT, and 3 alleles each for IDH and ME (Table 2). The test to estimate bias in the Hardy Weinberg Equilibrium of genotype frequencies revealed that none of the loci was under equilibrium in Morelos (Table 3). Only one locus was under equilibrium in each of Chiapas (IDH), Veracruz (ME) and Durango (IDH). Two loci were in equilibrium in each of Yucatán (GOT and ME) and San Luis Potosi (6PGDH and ME), and 3 in Tamaulipas (6PGDH, GOT and ME) (Table 3). The average number of alleles per population was 2, only the samples from San Luis Potosí and Durango had less than 2 (Table 4). The percentage of polymorphism, based on monomorphic and polymorphic loci, was the same in 6 of the populations (66.7%), but in Durango it was 50% (Table 4). The expected heterozygosity (He) ranged from 0.199 to 0.330. The lowest He value was recorded from the Durango population and the greatest from San Luis Potosí. The observed heterozygosity (Ho) was always lower than He. He ranged from 0.111 to 0.302 (Table 4). Linear regression analysis showed a negative correlation between genetic diversity (He) and altitude, genetic diversity decreased as altitude increased (F = 6.35; df = 1,5; P = 0.055; Fig. 2).
Allelic frequency of six enzymatic loci at 7 Mexican populations of Anastrepha ludens. N, sample size; N, allele (fast = 1, slow = 2 or 3); Dgo, durango; Chis, chiapas; Mor, morelos; Yuc, yucatán; Tam, tamaulipas; Ver, veracruz; and slp, San Luis Potosí.
Population Genetic Structure
The AMOVA revealed at least 10 % genetic differentiation among populations; 35% among individuals from each population and 54 % among individuals of total sample (Table 5). Fis and Fit values were 0.393 and 0.456, respectively; and they were positively significant in 9,999 permutations for the polymorphic loci (P < 0.0001). Genetic differentiation (Fst) value was 0.105, indicating a moderate genetic differentiation among populations. Pairwise Fst statistics were significantly different from zero, ranging from 0.02 to 0.253 (Table 6). Linear regression analysis did not detect a significant relationship between genetic differentiation and geographic distance (Fig. 3).
χ2 (Chi-square) statistics to test the hardy-weinberg equilibrium for enzymatic loci in Mexican populations of Anastrepha ludens.
Cluster analysis (UPGMA) showed low genetic distances between groups of populations, ranging from 0.017 to 0.043. This analysis revealed two groups (Fig. 4): one formed by the populations from Yucatán, Tamaulipas and Chiapas (genetic distance = 0.017), with the population from Durango attached to this group (genetic distance = 0.042). The other group was formed by the populations from Veracruz, San Luis Potosí and Morelos (genetic distance 0.043). The Bootstrap values were below 45% for all clusters; this indicates a low reliability of node or sluster formation (Fig. 4).
Genetic diversity of Anastrepha ludens populations in México. N, sample size; P, percentage of polymorphism; Ho, observed heterozygosity; He, expected heterozygosity. Dgo, Durango; Chis, Chiapas; Mor, Morelos; Yuc, Yucatán; Tam, Tamaulipas; Ver, Veracruz; And Slp, San Luis Potosí.
The Bayesian approach indicated the probability of 2 populations (cluster inferred) that could be represented by Tamaulipas and Durango. The other populations showed an admixture genome composition (Fig. 5).
Results from the analysis of molecular variance (amova ) on 268 individuals from 7 populations of Anastrepha ludens in Mexico. ss, sum of squares; P, test the hypothesis that the observed values were smaller or equal to random values based on 9,999 permutations.
Our study based on 4 polymorphic loci, suggests that populations of A. ludens had high levels of genetic diversity (He ≥ 0.200) and moderate genetic differentiation (Fst = 0.105) (Hartl & Clark 1997). The He recorded values were greater than those reported for Anastrepha fraterculus Wiedemann (1830) from Brazil (mean He = 0.03; Morgante & Malavasi 1985) but lower than those found by Alberti et al. (2002) for that same species in Argentina (He, 0.353 – 0.492). The Mexican populations of A. ludens showed a genetic diversity within the range reported for Ceratitis capitata based on enzymes (from 0.022 to 0.48; Milani et al. 1989). Bonnizzoni et al. (2001) and Meixner et al. (2002) reported lower genetic diversity for C. capitata in California, but this is a case of an recently adventive species and this lower diversity can be explained as the bottleneck of the colonization process (Carey 2010).
Pairwise Fst (genetic differentiation) statistic for Mexican populations of Anastrepha ludens below of diagonal and nm (gene flow) values over the diagonal.
A possible explanation for the high genetic diversity in A. ludens is its origin in Mexico. Ancestral populations tend to maintain high levels of genetic diversity and low genetic differentiation (Gilchrist et al. 2006, 2012). Also, its demographic characteristics, such as large size populations and high fecundity rates (Leyva et al. 1991; Liedo et al. 1992; Carey et al. 2005), could contribute to overcome the loss of genetic diversity associated with genetic drift and natural selection.
Inbreeding coefficients (Fis and Fit) were positive, indicating a deficiency of heterozygotes, probably caused by nonrandom mating both within populations and among populations. High levels of average inbreeding were also found in A. ludens at a smaller geographic scale in Chiapas (f = 0.682, R.M.L. unpublished data). Assortative mating is the most parsimonious explanation of high inbreeding coefficients; however, some studies have documented an absence of assortative mating among populations of A. ludens (Orozco et al. 2007; Aluja et al. 2009). Nonrandom inverse frequency-dependent mating could also explain high inbreeding coefficients. The lek mating behavior of this species, where one dominant male could account for a large fraction of the total number of matings (Burk 1981; Robacker & Hart 1985; Sivinski & Burk 1989), could explain our findings. Another possible cause of inbreeding could be that adults coming from the same fruit are likely to mate, as have been suggested for A. fraterculus (Alberti et al. 1999). The possibility of sex-linked loci and a sub-structuring of female and male populations may lead to an expected excess of homozygotes and deficiency of heterozygotes compared with Hardy- Weinberg proportions (Hedrick & Parker 1997). We did not detect significant differences in the allelic frequencies of any loci between sexes, and a possible substructure cannot be revealed with the present data due to the small number of localities sampled in each State. The null alleles also could account for the excess of homozygotes.
We found moderate genetic differentiation (Fst = 0.105) among populations and from moderate to high genetic differentiation in pairwise comparisons, which were done as suggested by Hartl & Clark (1997, page 118) for qualitative interpretation of Fst values. A similar pattern was observed in populations of A. ludens from northeast Mexico (Pecina-Quintero et al. 2009). The effect of gene flow on the population genetic structure depends on the species' movement capacity and its ability to overcome geographic and ecological barriers. Isolation due to distance is one of the most common and simple mechanisms to decrease gene flow. As distance between population increases, gene flow decreases to produce genetic differentiation (Slatkin 1994; Rousset 1997). Our results are not in agreement with this isolation-by-distance model, but we recognize that the samples from distant locations without intermediately located populations do not allow us to accurately estimate gene flow (Nm). However, their structure could be explained by their geographical origin. The populations from Veracruz, Morelos and San Luis Potosí showed little differentiation among them (Fst values ranged from 0.050 to 0.088) and they conform to a group in the UPGMA analysis. The Bayesian approach showed that they have a similar genome content as in the 2 inferred clusters, which is in partial agreement with the proposed ancestral origin of this species from the Morelos region in central Mexico (Plummer et al. 1941). The gene pool of the ancestral Morelos populations would be expected to have much in common with those of the derived populations. This is supported by the fact that the Yucatan, Chiapas and Tamaulipas populations constituted a group slightly differentiated from the ancestral Morelos population and the population from Durango was further differentiated. The Bayesian approach also indicated Durango to be a single population. A genetic study of populations of northeast Mexico based on amplified fragment length polymorphism (AFLP markers) showed genetic differentiation between a population from San Luis Potosí and those from Tamaulipas and Nuevo Léon (Pecina-Quintero et al. 2009). Thus, we hypothesize a historical dispersion process from the Morelos region to Tamaulipas, where A. ludens could enlarge its population using its abundant host S. greggi (Plummer et al. 1941; Hernández-Ortíz 1992; Baker et al. 1944), afterwards it moved to other parts of the country facilitated by human activities, such as the establishment of Citrus crops, which in some cases covered large areas (Garcia-Dessommes 2009; SIAP 2009).
Our results do not rule out the possibility that populations distributed over a smaller geographic scale might have a genetic structure consistent with the isolation-by-distance model or relating to use of different host species, considering that the typical range of movement of this species is around 240 m (Thomas & Loera-Gallardo 1998; Hernández et al. 2007).
Genetic differentiation by natural selection and genetic drift has been reported for other tephritid species, such as C. capitata and A. fraterculus (Morgante et al. 1985; Reyes & Ochando 1997, 1998; Alberti et al. 1999, 2002; Gilchrist et al. 2006). The variation in the presence and abundance of host species and the local climatic conditions may constitute a wide range of environments with selectively distinct effects on A. ludens populations, and thereby promote genetic differentiation. The negative relationship found between altitude and genetic diversity (He) could be the result of selection. The altitude factor itself is not selective, but it is associated with other factors that could exert selection (Wang et al. 2008; Demirici et al. 2011). For example, temperature is known to influence developmental time and reproductive rates of many insect species, including tephritid fruit flies (Leyva 1988; Fletcher 1989; Bale et al. 2002). Developmental time and reproductive rates are important fitness components; their variation will invariably affect the genetic structure of populations. Other selective factors could be associated with the type, availability and nutritional quality of hosts, and the presence of natural enemies (Malavasi & Morgante 1981; Carey 1984; Krainacker et al. 1987; Leyva et al. 1991; Aluja et al. 2003; Díaz-Fleischer & Aluja 2003; Silva et al. 2010). The relationships between genetic diversity, temperature, presence and abundance of host species and natural enemies remain unresolved.
Finally, genetic structure could be factored into pest management strategies. The Mexican Fruit Fly Campaign divides the national territory in 3 pest management regions, according to fruit fly presence and population densities: (1) fruit fly free zones, (2) low prevalence zones, and (3) pest control zones (Fig. 1). Durango has a surface area of 121,134.0 km2 of which 77.4% is fruit fly free and the rest (22.6%) is part of the low prevalence zone. San Luis Potosí comprises 62,450.0 km2 of which 52.3% is fruit fly free, and 29.4% is part of the low prevalence zone, and the rest (18.3%) belongs to the areas under phytosanitary control. Tamaulipas comprises 136,063.4 km2 of which 82.7% is part of the low prevalence zone, and the rest (17.3%) belongs to the areas under phytosanitary control. The other 4 states (Chiapas, Yucatán, Morelos and Veracruz) belong to the areas under phytosanitary control. These categories represent different management strategies and fruit movement is only allowed within areas of the same category (SENASICA 2009). Thus there is a possibility that the gene flow patterns could be mediated by human activities (Oliver 2006).
To obtain a better understanding of the genetic diversity and structure of A. ludens populations, it will be necessary to sample the species entire geographical range. Sampling on a smaller geographic scale (hundreds of meters) and the use of nuclear DNA markers such as ITS or SSR (microsatelites), and mitochondrial DNA could contribute to a better understanding of the pathway and intensity of genetic interchange among subpopulations.
We thank Paula Gomez, Juan Vilardi for their comments and advice in earlier versions of the manuscript. We also thank the “Campaña Nacional Contra Moscas de la Fruta”, SENASICA, SAGARPA for the collections of A. ludens in 6 states of Mexico, and the staff of the Genetic Sexing Laboratory at the “Moscafru Program” for collections in Chiapas and laboratory facilities. Financial support was provided by the Consejo Nacional de Ciencia y Tecnología (CONACyT) México, through grant: SEP-CONACYT 2003-CO-43824 (granted to PLF-LRM); SAGARPA-CONACYT 163431 and by scholarship to MCMN (CVU/Becario: 249165/213435). This is a partial fulfillment of Master of Science dissertation of MCMN.
- A. C. Alberti , G. Calcagno , B. O. Saidman , and J. C. Vilardi 1999. Analysis of the genetic structure of natural populatons of Anastrepha fraterculus (Diptera, Tephritidae). Ann. Entomol. Soc. America 92: 731–736. Google Scholar
- A. C. Alberti , M.S. Rodriguero , P. Gomez-Cendra , B. O. Saidman , and J. C. Vilardi 2002. Evidence indicating that Argentine populations of Anastrepha fraterculus (Diptera: Tephritidae) belong to a single biological species. Ann. Entomol. Soc. America 95: 505–512. Google Scholar
- M. Aluja , D. Pérez-Staples , R. Macías-Ordoñez , J. Piñero , B. Mcpheron , and V. Hernández-Ortíz 2003 Nonhost status of Citrus sinesis cultivar valencia y C. paradisi cultivar Ruby Red to Mexican Anastrepha fraterculus (Diptera: Tephritidae). J. Econ. Entomol. 96: 1693–1703. Google Scholar
- M. Aluja , J. Rull , D. Pérez-Staples , F. Díaz-Fleische , and J. Sivinski 2009. Random mating among Anastrepha ludens (Diptera: Taphritidae) adults of geographically distant and ecologically distinct populations in Mexico. Bull. Entomol. Res. 99: 207–214. Google Scholar
- A. C. Baker , W. E. Stone , C. C. Plummer , and M. Mcphail 1944. A review of studies on the Mexican fruit fly and related Mexican species. US Dept. Agric. Misc. Publ. No. 531, 3 pp. Google Scholar
- J. S. Bale , G. J. Masters , I. D. Hodkinson , C. Awmack , T. M. Bezemer , V. K. Brown , J. Butterfield , A. Buse , J. C. Coulson , J. Farrar , J. E. G. Good , R. Harrington , S. Hartley , T. H. Jones , R. L. Lindroth , M. C. Press , I. Symrnioudis , A. D. Watt , and J. B. Whittaker 2002. Herbivore in global climate change research: direct effects of rising temperature on insect herbivores. Global Change Biol. 8: 1–16. Google Scholar
- M. Bonnizzoni , L. Zheng , C. R. Gulielmino , D. S. Haymer , G. Gasperi , L. M. Gomulki , and A. R. Malacrida 2001. Microsatellite analysis of medfly bioinfestations in California. Mol. Ecol. 10: 2515–2524. Google Scholar
- T. Burk 1981. Signaling and sex in acalyptrate flies. Florida Entomol. 64: 30–43. Google Scholar
- J. R. Carey 1984. Host-specific demographic studies of the Mediterranean fruit fly Ceratitis capitata. Ecol. Entomol. 9: 261–270. Google Scholar
- J. R. Carey 2010. The Mediterranean fruit fly (Ceratitis capitata) invasion on California deepens: Response to an alternative explanation for recurring. American Entomol. 56: 158–163. Google Scholar
- J. R. Carey , P. Liedo , H. G. Müler , J. L. Wang , D. Senturk , and L. Harshman 2005. Biodemography of a long-lived tephritid: Reproduction and longevity in a large cohort of female Mexican fruit flies, Anastrepha ludens. Exp. Geront. 40: 793–800. Google Scholar
- N. Davies , F. X. Villablanca , and G. K. Roderick 1999. Bioinvasions of the Medfly Ceratitis capitata: Source estimation using DNA sequences at multiple intron loci. Genetics 153: 351–360. Google Scholar
- G. J. García Dessommes 2009. El origen de la citricultura moderna en México. In: MA Rocha-Peña , JE Padrón-Chávez (eds). El cultivo de los cítricos en el estado de Nuevo León No. 1. Instituto Nacional de Investigaciones Forestales Agrícolas y Pecuarias. CIRNE. Campo Experimental General Terán. México, pp. 1–18. Google Scholar
- B. Demirici , Y. Lee , G. C. Lanzaro , and B. Alten 2011. Altitudinal genetic and morphometric variation among populations of Culex theileri Theobald (Diptera: Culicidae) from northeastern Turkey. J. Vect. Ecol. 37: 197–209. Google Scholar
- F. Díaz-Fleisher , and M. Aluja 2003. Influence of conspecific presence, experience and host quality on oviposition behavior and clutch size determination in Anastrepha ludens (Diptera: Tephritidae). J. Insect Behav. 16: 537–554. Google Scholar
- L. Excoffier , P. E. Smouse , and J. M. Quattro 1992. Analysis of molecular variance inferred from metric distances among DNA haplotypes: Application to human mitocondrial DNA restriction sites. Genetics 131: 479–491. Google Scholar
- B. S. Fletcher 1989. Temperature — Development rate relationships of the immature stages and adults of tephritid fruit flies, pp. 273–289 In A. S. Robinson and G. Hooper [eds.], Fruit Flies: Their Biology, Natural Enemies and Control. World Crop Pests Vol. 3B. Elsevier, Amsterdam, The Netherlands. Google Scholar
- R. Frankham 2012. How closely does genetic diversity in finite populations conform to predictions of neutral theory? Large deficits in regions of low recombination. Heredity 108: 167–168. Google Scholar
- D. J. Futuyma 1986. Evolutionary Biology. 2nd edn. Sinauer Associates, Inc. Publishers, Sunderland, Massachusetts, USA. 600 pp. Google Scholar
- G. Gasperi , A. R. Malacrida , and R. Milani 1987. Protein variability and population genetics of Ceratitis capitata , pp. 149–175 In A. P. Economopoulos [ed.], Fruit Flies: Proc. 2nd Intl. Symp. Elsevier Science Publishers, Amsterdam, The Netherlands. Google Scholar
- A. S. Gilchrist , B. Dominiak , P. S. Gillespie , and J. A. Sved 2006. Variation in population structure across the ecological range of the Queensland fruit fly, Bactrocera tryoni. Australian J. Zool. 54:87–95. Google Scholar
- A. S. Gilchrist , E. C. Cameron , J. A. Sved , and A. W. Meats 2012. Genetic consequences of domestication and mass rearing of pest fruit fly Bactrocera tryoni (Diptera: Tephritidae). J. Econ. Entomol. 105: 1051–1056. Google Scholar
- F. Gould 1991. The evolutionary potential of crop pests. American Scientist 79(6): 496–507. Google Scholar
- D. L. Hartl , and A. G. Clark 1997. Principles of population genetics. 3rd edn. Sinauer Associates Inc. Canada, 118 pp. Google Scholar
- W. P. Hedrick 2000. Genetics of Populations. 2nd Edn. Jones and Bartlett Publishers. Sudbury, Massachusetts, USA. 47 pp. Google Scholar
- W. P. Hedrick and J. D. Parker 1997. Evolutionary genetics and genetic variation of haplodiploids and x-linked genes. Annu. Rev. Ecol. Syst. 28: 55–83 Google Scholar
- P. D. N. Herbet , and M. J. Beaton 1993. Methodologies for Allozyme Analysis Using Cellulose Acetate Electrophopresis. Helena Laboratorios, Texas, USA, pp. 3–26. Google Scholar
- E. Hernández , D. Orozco , S. Flores-Breceda , and J. Domínguez 2007. Dispersal and longevity of wild and mass-reared Anastrepha ludens and Anastrepha obliqua (Diptera: Tephritidae). Florida Entomol. 90: 123–135. Google Scholar
- V. Hernández-Ortíz 1992. El género Anastrepha en México (Diptera-Tephritidae) Taxonomía, distribución y sus plantas hospederos. Inst. Ecol. Soc. Mexicana Entomol. Xalapa, Veracruz, México, 101 pp. Google Scholar
- M. D. Huettel , P. A. Fuerst , T. Maruyama , and R. Chacraborty 1980. Genetics effects of multiple population bottlenecks in the Mediterranean fruit flies (Ceratitis capitata) Genetics 94: 43–47. Google Scholar
- K. C. Kim 1993. Insect pests and evolution, pp. 3–26 In K. C. Kim and B. A. MacPheron [eds.], Evolution of Insect Pests: Patterns of Variation, John Wiley & Sons, Inc. Google Scholar
- D. A. Krainacker , J. R. Carey , and R. I. Vargas 1987. Effect of larval hosts on life history traits of the Mediterranean fruit fly, Ceratitis capitata. Oecologia 73: 583–590. Google Scholar
- J. L. Leyva , H. W. Browing , and F. E. Gilstrap 1991. Development of Anastrepha ludens (Ditera: Tephritidae) in several host fruits. Environ. Entomol. 20: 1160–1165. Google Scholar
- J. L. Leyva 1988. Temperatura umbral y unidades calor requeridas por los estados inmadurados de Anastrepha ludens (Loew) (Diptera: Tephritidae). Fol. Entomol. Mexicana 74: 189–196. Google Scholar
- P. Liedo , J. R. Carey , H. Celedonio , and J. Guillen 1992. Size specific demography of three species of Anastrepha fruit flies. Entomol. Exp. Appl. 63: 135– 142. Google Scholar
- A. Malavasi , and J. S. Morgante 1981. Adult and larval population fluctuation of Anastrepha fraterculus and its relationship to host availability. Environ. Entomol. 10:275–278. Google Scholar
- M. D. Meixner , B. A. Mcpheron , J. G. Silva , G. E. Gasparich , and W. S. Sheppard 2002. The Mediterranean fruit fly in California: Evidence for multiple introductions and persistent populations based on microsatellite and mitochondrial DNA variability. Mol. Ecol. 11: 891–899. Google Scholar
- R. Milani , G. Gasperi , and A. Malacrida 1989. Biochemical genetics, pp. 33–56 In A. S. Robinson and G. Hooper [eds.], Fruit Flies their Biology, Natural Enemies and Control. World Crop Pests Vol. 3B. Elsevier, Amsterdam, The Netherlands. Google Scholar
- M. P. Miller 1997. TFPGA 1.3. Tools for population genetics analysis: A Windows program for the analysis of allozymes and molecular population genetic data. Northern Arizona University, Arizona. Google Scholar
- J. S. Morgante , and A. Malavasi 1985. Genetic variability in populations of the south American fruit fly Anastrepha fraterculus ( Tephritidae). Rev. Brasileira Genética 8: 241–247. Google Scholar
- R. W. Murphy , J. W. Sites , D. G. Buth Jr. , and C. H. Haufler 1996. Proteins: Isozyme electrophoresis, pp. 51–120 In D. M. Hillis , C. Moritz , and B. K. Mable [eds.], Molecular Systematics. Sinauer Associates Inc., Sunderland, Massachusetts. Google Scholar
- M. Nei 1972. Genetic distance between populations. American. Nat. 106: 283–292. Google Scholar
- A. L. Norrbom , and K. C. Kim 1988. A list of reported host plants of the species of Anastrepha Schiner (Diptera: Tephiritidae). U.S. Dept. Agric., APHIS, Plant Prot. and Quar. APHIS 81–52, 114 pp. Google Scholar
- J. C. Oliver 2006. Population genetic effects of humanmediated plant range expansions on native phytophagous insects. Oikos 112: 456–463. Google Scholar
- D. Orozco , R. Hernández , S. Meza , and J. Domínguez 2007. Sexual competitiveness and compatibility between mass-reared sterile flies and wild populations of Anastrepha ludens (Diptera: Tephritidae) from different regions in Mexico. Florida Entomol. 90: 19–26. Google Scholar
- R. Peakall , and P. E. Smouse 2006. GENALEX 6: Genetic analysis in Excel. Population genetics software for teaching and research. Mol. Ecol. 6:288–295. Google Scholar
- V. Pecina-Quintero , J. I. López Arroyo , J. Loera- Gallardo , J. Rull , E. Rosales Robles , E. Cortez- Mondaca , S. Hernández-Delgado , N. Mayek Perez , and M. Aluja 2009. Genetic differences between Anastrepha ludens (Loew) populations stemming from a native and exotic host in NE México. Agro Tec Méxicana 35: 323–331. Google Scholar
- C. C. Plummer , M. Mcphail , and J. W. Monk 1941. The yellow chapote, a native host of the Mexican fruit fly. U.S. Dept. Agr. Tech. Bull. No. 775. 12 pp. Google Scholar
- J. K. Pritchard , M. Stephens , and P. Donnelly 2000. Inference of population structure using multilocus genotype data. Genetics 155: 945–959. Google Scholar
- G. P. Quinn , and M. J. Keogh 2002. Experimental design and data analysis for biologists. Cambridge University Press, Cambridge, UK. pp. 25 Google Scholar
- A. Reyes , and M. D. Ochando 1997. Fitness of mitochondrial DNA haplotypes in Ceratitis capitata In J. Piedade-Guerreiro [ed.], Fruit Flies of Economic Importance. Intl. Org. Biol. Integ. Control Noxious Animals Plants (IOBC). West Palearctic Reg. Bull. 20: 175–185. Google Scholar
- A. Reyes , and M. D. Ochando 1998. Genetic differentiation in Spanish populations of Ceratitis capitata as revealed by abundant soluble protein analysis. Genética 104: 59–66. Google Scholar
- B. J. Richardson , P. R. Baverstock , and N. Adams 1986. Allozyme Electrophoresis. A Hdbk Animal Syst. Pop. Studies. Academic Press, London, 229. Google Scholar
- D. C. Robacker , and W. G. Hart 1985. Courtship and territoriality of laboratory reared Mexican fruit flies, Anastrepha ludens (Diptera: Tephritidae), in cages containing host and non host trees. Ann. Entomol. Soc. America 78: 488–494. Google Scholar
- F. Rousset 1997. Genetic differentiation and estimation of gene flow from F-Statistics under isolation by distance. Genetics 145: 1219–1228. Google Scholar
- J. G. Silva , V. S. Dutra , M. S. Santos , N. M. O. Silva , D. B. Vidal , R. A. Nink , J. A. Guimaraes , and E. L. Araujo 2010. Diversity of Anastrepha spp. (Diptera: Tephritidae) and associated braconid parasitoids from native and exotic hosts in southeastern Bahia, Brazilian Environ. Entomol. 39: 1457–1465. Google Scholar
- J. Sivinski , and T. Burk 1989. Reproductive and mating behaviour, pp. 343–351 In A. S. Robinson and G. Hooper [eds.], Fruit Flies: Their Biology, Natural Enemies and Control. World Crop Pests Vol. 3B. Elsevier, Amsterdam, The Netherlands. Google Scholar
- M. Slatkin 1994. Gene flow and population structure, pp. 3–17 In L. A. Real [ed.], Ecological Genetics. Princeton University Press, Princeton, NJ. Google Scholar
- D. B. Thomas , and J. Loera-Gallardo 1998. Dispersal and longevity of mass-released, sterilized Mexican fruit Flies (Diptera: Tephritidae). Environ. Entomol. 27: 1045–1052. Google Scholar
- J. C. Vilardi , A. Civetta , B. O. Saidman and J. L. Cladera 1990. Caracterización de tres sistemas isoenzimáticos de adultos de una población de Ceratitis capitata Wied. (Diptera:Tephritidae). Evol. Biol. 4: 107–118. Google Scholar
- Ji-R. Wang , Y-M. Wei , X-Y. Long , Z-H. Yan , E. Nevo , B. R. Baum , and Y. L. Zheng 2008. Molecular evolution of dimeric á-amylase inhibitor genes in wild emmer wheat and its ecological association. BMC Evol. Biol. 8: 91, doi:10.1186/1471-2148-8-91. Google Scholar
- S. Wright 1951. The genetical structure of populations. Ann. Eugenics 15: 323–354. Google Scholar
- S. Wright 1952. The theoretical variance within and among subdivisions of a population that is in a steady state. Genetics 37: 312–321. Google Scholar
- G. Zúñiga , R. Cisneros , Y. Salinas-Morenao , J. L. Hes and J. E. Rinehart 2006. Genetic structure of Dendroctonus mexicanus (Coleoptera: Curculionidae: Scolytinae) in the Trans-Mexican volcanic belt. Ann. Entomol. Soc. America 99(5): 944–958. Google Scholar