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Effects of Corridors on Genetics of a Butterfly in a Landscape Experiment
Carrie N. Wells, Ray S. Williams, Gary L. Walker, and Nick M. Haddad

Southeastern Naturalist, Volume 8, Number 4 (2009): 709–722

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2009 SOUTHEASTERN NATURALIST 8(4):709–722 Effects of Corridors on Genetics of a Butterfl y in a Landscape Experiment Carrie N. Wells1,2, Ray S. Williams1,*, Gary L. Walker1, and Nick M. Haddad3 Abstract - To investigate the possible role of landscape connectivity on the genetic structure of isolated populations, we examined the effects of habitat corridors on the population genetics of a vagile butterfl y species, Junonia coenia, within a largescale, experimental system. Using allozyme electrophoresis, a total of nine loci were identified and scored, six of which exhibited polymorphism. Our data demonstrated consistently higher levels of expected (He) and observed (Ho) heterozygosity in butterfl ies sampled from patches connected by corridors compared to unconnected patches. A t-test comparing He and Ho in connected versus unconnected patches found a marginally significant difference in one locus, the glycolytic enzyme phosphoglucose isomerase (PGI). Connected patches exhibited overall lower FST values compared to unconnected patches, indicating potentially increased levels of gene fl ow due to corridors. Our results support previous investigations on dispersal and population size for J. coenia, and show that higher dispersal through corridors promotes genetic variability at a locus (PGI) implicated in dispersal and fitness in butterfl ies. Introduction The fragmentation and outright loss of natural habitats are currently thought to be the most serious threats to global biodiversity (Fischer and Lindenmayer 2007, Saunders et al. 1991, Solé et al. 2004, Wilcove et al. 1998). Fragmentation of large contiguous areas into smaller habitat islands often results in the geographic isolation of populations, in turn limiting movement of individuals between populations (Bierregaard et al. 1992, Harris 1984). A popular management strategy to counter this type of fragmentation often involves attempts to connect habitat remnants with a corridor of similar habitat (Mann and Plummer 1995, Merriam and Saunders 1993, Noss 1992). Habitat corridors have been shown to facilitate dispersal of diverse taxa (Berggren et al. 2002, Haas 1995, Haddad 1999a, Haddad et al. 2003, Machtans et al. 1996, Sutcliffe and Thomas 1996, Tewksbury et al. 2002, Zhang and Usher 1991), reduce local extinction rates (Fahrig and Merriam 1985, Noss 1991), and increase levels of gene flow (Aars and Ims 1999, Hale et al. 2001, Mech and Hallett 2001). While the use of habitat corridors presents a potential benefit for species in isolated habitats, many uncertainties about their importance for use as a conservation strategy 1Department of Biology, PO Box 32027, 572 Rivers Street, Appalachian State University, Boone, NC 28608. 2Current address - Department of Biological Sciences, 132 Long Hall, Clemson University, Clemson, SC 29634-0315. 3 Department of Zoology, 2104 North Gardner, Box 7617, North Carolina State University, Raleigh, NC 27695. *Corresponding author - 710 Southeastern Naturalist Vol. 8, No. 4 remain. Of particular concern is, even if corridors increase dispersal rates, does more movement have impacts on populations, including population genetic structure? Population genetics provides a powerful approach to investigate population dynamics in a landscape context (Manel et al. 2003). Smaller, isolated habitats could be expected to contain fewer individuals than larger, more contiguous areas (see Vandewoestijne and Baguette 2004), affecting genetic diversity within species (Schmitt and Seitz 2002). Therefore, studies that examine the effects of connectivity on maintaining genetic variation are timely. Since new alleles appear in a gene pool through both the process of mutation and immigration of individuals from separated populations (Mettler et al. 1988, Wallace 1981), both mechanisms contributing to genetic variation within populations need to be considered. In the short-term, gene fl ow via immigration tends to increase genetic diversity within a given local population by offsetting the loss of alleles due to inbreeding and drift (Hoole et al. 1999, Peterson and Denno 1998, Slatkin 1985). Habitat degradation limits gene fl ow by reducing the movement of individuals and their alleles between fragmented, isolated populations (Hänfl ing et al. 2004; Nei 1973, 1987; Slatkin 1985). In addition to fewer alleles being introduced, the isolation of unconnected populations would likely reduce both heterozygosity and the total number of alleles in the population through the process of random genetic drift and inbreeding (Slatkin 1985, Van Rossum et al. 2004, Wright 1978). Recent work suggest distinct correlations between fitness and genetic diversity (Reed and Frankham 2003), with particular attention paid to molecular polymorphism in the glygolytic enzyme phosphoglucose isomerase (PGI), as this locus has been shown to affect fitness in butterfl ies. Polymorphism at the PGI locus has specifically been shown to enhance the fl ight performance and fitness of Colias butterfl ies (Watt 2003), as well as to act to increase metabolic rate, fecundity, and population growth in the Melitaea cinxia L. (Glanville Fritillary) (Haag et al. 2005, Hanski and Saccheri 2006). With the potential for habitat isolation to alter genetic structure at some loci and perhaps not others, a consideration of the role habitat connectivity plays in affecting the population genetics of previously isolated populations is important. Allozyme electrophoresis has been a useful tool for investigating the genetic structure of numerous insect populations, including nymphalid butterfl ies (Britten and Brussard 1992, Britten et al. 1994, Brittnacher et al. 1978, Porter and Mattoon 1989). Allozymes are considered to be a valuable but conservative measure of genetic variation and are interpretable in terms of Mendelian inheritance for specific loci (Avise 1975, 1994). Numerous investigators have successfully used both DNA and allozyme analyses to examine the effects of habitat fragmentation on the genetic structure of various insects, including beetles (Britten and Rust 1996, Knutsen et al. 2000, Six et al. 1999), crickets (Berggren et al. 2002), and butterfl ies (Baguette et al. 2003, Johannesen et al. 1997, Keyghobadi et al. 1999, Kronforst and Fleming 2001, Meglécz et al. 2004, Vandewoestijne et al. 1999, Williams et al. 2003). 2009 C.N. Wells, R.S. Williams, G.L. Walker, and N.M. Haddad 711 The main objective of this study was to examine if habitat corridors facilitated gene fl ow in an open-habitat specialist butterfl y, Junonia coenia Hübner (Common Buckeye), within a large-scale experimental system at Savannah River Site (SRS), SC. This system was established within native Pinus taeda L. (Loblolly Pine) forest and contained replicate connected and unconnected habitat patches. Several previous studies with J. coenia at SRS (Haddad 1999a, 1999b, 2000; Haddad and Tewskbury 2005) showed that the establishment of corridors increased movement of butterfl ies, resulting in higher population densities in habitat patches that were experimentally connected by corridors (Haddad and Baum 1999, Tewksbury et al. 2002). Because the facilitation of movement between patches via corridors was previously established, we asked if the genetic structure of butterfl ies within isolated and connected patches would be differentially affected via connectivity. We expected that increased levels of gene fl ow in habitat patches connected to each other by a corridor would cause J. coenia populations in connected habitat patches to have higher genetic diversity than those in unconnected patches. We also collected butterfl ies from outside the experiment to establish a background or “source” level of variation. These butterfl ies also provided insight into the development of genetic structure within the experiment since the original colonization by the butterfl y after experimental creation. The main questions addressed were: (1) do Common Buckeye butterfl ies sampled from patches connected by a corridor have a different genetic structure than butterfl ies sampled from isolated unconnected patches and, (2) does the model-corridor system at SRS refl ect the natural genetic structure of J. coenia? Materials and Methods Study site We examined the genetic structure of J. coenia in an experimental-model system established in the winter of 1999–2000 within the 1240-km2 Savannah River Site. Eight 50-ha experimental blocks were created to examine the effects of corridors on plant and animal dispersal. Each block contained five open habitat patches within a dense matrix of pine forest. Patches are being restored to Pinus palustris P. Mill. (Longleaf Pine) savannah through restoration of Longleaf Pine and other herbaceous species, and through regular controlled fire. In each block, a central 1-ha patch was surrounded by four other patches, each 150 m away (Fig. 1). This central patch was connected to only one of the peripheral patches (also 1 ha) by a 25- X 150-m corridor. The three remaining patches were unconnected and equal to the size of the connected patch plus the corridor (i.e., 1.375 ha; Fig. 1). For a complete description of the site and establishment of plots, see Tewksbury et al. (2002). This model system was ideal for our questions because a previous study found movement of butterfl ies from the central patch to peripheral patches was greater with a corridor present (Tewksbury et al. 2002). 712 Southeastern Naturalist Vol. 8, No. 4 Butterfl y Collection The Common Buckeye is a multi-voltine, open-habitat butterfl y that occurs throughout the southeastern United States (Opler 1998). Because the Common Buckeye in the southern US produces more than one generation per year, we estimate that at the time of our collection (summer 2002), from 6–7 generations could have developed within experimental patches since plot colonization in 2000. A total of 111 butterfl ies were collected from experimental patches during May and June of 2002. We choose this period to collect because populations likely peak in May and June in the deep south (N.M. Haddad, pers. observ.; Pyle 1981). In total, 53 butterfl ies were collected from patches connected by a corridor, while 58 butterfl ies were collected from unconnected peripheral patches (for the number of individuals collected in each patch refer to Table 1). No butterfl ies were sampled within the boundaries of an actual corridor. After collection, we determined that two blocks yielded too few butterfl ies (n = 7) and thus were excluded from analysis. Therefore, our Figure 1. Patch arrangement in a single experimental block at the Savannah River Site. 2009 C.N. Wells, R.S. Williams, G.L. Walker, and N.M. Haddad 713 genetic analysis was based on comparisons between and among six blocks, using a total of 104 butterfl ies. While sample size was a potentially limiting factor in our experiment, based on the numbers of alleles identified and the amount of genetic variation found across sites (see below), we feel there was a sufficient number of specimens collected to adequately address our primary questions. In order to assess genetic variation in long established populations of J. coenia at SRS, we sampled two populations (n = 18, n = 20) from outside of the experiment. These large, panmictic butterfl y populations were sampled from wide, open power-line right-of-ways. Since butterfl ies from surrounding habitats founded patches within the experimental blocks, the genetic structure of “source” butterfl ies provides insight into mechanisms responsible for observed genetic variation within the experiment. In all cases, butterfl ies were captured with a handheld net and stored on ice in the field for no longer than 2 h. Individuals were then frozen and transported to Appalachian State University (ASU), Boone, NC for analysis. Genetic analysis Individuals were dissected to determine gender. The thorax was then partitioned into two equal-sized parts, with one half stored at -80 °C, and the remaining half ground in 2.5 ml of simple grinding buffer solution described by Werth (1985). Homogenized tissue was partitioned into two equal aliquots and stored at -80 °C until used in electrophoresis. Nine allozyme loci were resolved on 13% starch gels (Sigma Chemical Company) using three gel/electrode buffer systems following Werth (1985) and Selander et al. (1971). Four loci, Aspartate aminotransferase (AAT) (EC, Malate dehydrogenase (MDH) (EC, Malic enzyme (ME) (EC, and Aldolase (ALD) (EC, were found to be consistently scorable on a Tris-borate-EDTA pH 9.1 gel/electrode buffer system with gel run for 6 hours at 50 mA. Phosphoglucomutase (PGM) (EC, Phosphoglucoisomerase (PGI) (EC, and Isocitrate dehydrogenase (IDH) (EC were consistently scorable on a discontinuous Triscitrate pH 6.3/6.7 gel/electrode buffer system with gel run for 5 hours at 100 mA. Triosephosphate isomerase (TPI) (EC and Glycerol-3- Phosphate dehydrogenase (G3PDH or α-GPDH) (EC were scorable on a discontinuous Tris-citrate pH 8.2/8.7 gel/electrode buffer system with gel run for 5 hours at 100 mA. Stains were prepared according to Cardy et al. (1983), Soltis et al. (1983), and Werth (1985). The fastest-tracking allele was always scored as number one, with all subsequent alleles ordered sequentially. Zymograms were drawn immediately following staining to record all observed banding patterns. Stained gel slices were digitally photographed using a Nikon Coolpix 3500 digital camera. Standard measures of genetic diversity, including observed heterozygosities (Ho; Levene 1949), expected heterozygosities (He; Nei 1978) and Wright’s F-statistics (Wright 1951) were calculated using Popgene-32 (Yeh et al. 1997) and F-stat (Goudet 2001). Observed heterozygosity and He across all loci were calculated using a correction for small sample size (Nei 1978). Differences 714 Southeastern Naturalist Vol. 8, No. 4 between Ho and He in connected versus unconnected patches were tested for significance at each locus using a paired t-test (Proc GLM, SAS Institute, 2001). Butterfl ies were pooled in either connected or unconnected patches in an experimental block and the data analyzed using the block as a replicate (n = 6). All values were arcsine transformed to normalize the data. Expected and observed heterozygosities were tested for deviation from Hardy-Weinberg expectations using a chi-square goodness-of-fit analysis. Wright’s F-statistics, specifically FST, was used to examine relative amounts of reductions in heterozygosity at a given level of the population structure relative to another more inclusive level of population structure (see Wright 1965, 1978). Results where 0.10 > P > 0.05 are reported as marginally significant. Results Of the 111 butterfl ies sampled within the model system, eighteen females (16.2%) and 93 males (83.8%) were collected (male:female ratio of 5.2:1). The source populations contained a total of 38 butterfl ies, with 8 females (21.1%) and 30 males (78.9%) (male:female ratio of 3.8:1). We believe that the skewed sex ratio is caused by lower detection probabilities of females (males are pseudo-territorial and highly visible; N.M. Haddad, pers. observ.). Allele frequencies and numbers of butterfl ies collected in each experimental unit for the polymorphic loci are presented in Table 1. Of the nine enzyme systems used for analysis, six displayed polymorphism at a 95% confidence level. The loci ALD, α-GPDH, and ME were all fixed for a single allele and were therefore considered monomorphic. While only two blocks (in connected patches) had butterfl ies polymorphic for MDH, this locus was included in the analysis (Table 1). There was considerable variation in the numbers of J. coenia collected in the different blocks. We found that four loci from connected patches and two loci from the unconnected patches were not in Hardy-Weinberg equilibrium (Table 2). When comparing observed and expected heterozygosity across treatments using a student t-test, only one locus, PGI, differed between connected and unconnected patches (marginally significant; Table 2). Without considering other factors such as wing wear and changes due to fl ight season, this result possibly demonstrates an effect on some loci but not others and suggests, based on other studies with PGI, that a locus implicated in dispersal ability of butterfl ies is affected by connectivity between habitats. There was considerable variation in Ho and He within blocks in both connected and unconnected patches (Table 3). Overall, Ho, He, and percent polymorphic loci were higher in connected than unconnected patches for five of the six blocks sampled. One word of caution regarding sample size: in some plots, the disproportionate number of butterfl ies collected in connected versus unconnected patches could have biased our results with respect to calculated Ho and He (see Tables 1 and 3). However, the consistent observation of higher heterozygosites in connected versus unconnected patches 2009 C.N. Wells, R.S. Williams, G.L. Walker, and N.M. Haddad 715 Table 1. Allele frequencies for connected (C) and unconnected (U) patches in six polymorphic loci in sequentially numbered experimental blocks. n = number of Common Buckeye butterfl ies collected in patches. See Materials and Methods for a description of the loci. Blocks Locus Allele 1-C 1-U 2-C 2-U 3-C 3-U 4-C 4-U 5-C 5-U 6-C 6-U n 10 3 6 3 5 6 21 13 4 21 5 7 AAT 1 0.083 0.047 0.154 0.024 0.100 2 1.000 1.000 0.917 1.000 1.000 1.000 0.929 0.808 1.000 0.976 0.900 1.000 3 0.024 0.039 TPI 1 0.024 0.192 0.125 0.024 0.143 2 1.000 1.000 1.000 1.000 1.000 0.976 0.769 0.875 0.976 0.900 0.857 3 0.039 0.100 PGI 1 0.100 0.083 0.120 0.077 2 0.450 0.500 0.417 0.500 0.500 0.250 0.452 0.462 0.625 0.452 0.100 0.357 3 0.500 0.500 0.500 1.000 0.300 0.583 0.405 0.423 0.375 0.548 0.900 0.929 4 0.050 0.083 0.100 0.083 0.024 0.039 0.071 PGM 1 0.050 0.167 0.024 2 0.250 0.167 0.250 0.024 0.115 0.125 0.143 0.100 3 0.700 0.677 0.583 0.833 0.800 0.667 0.050 0.577 0.625 0.738 0.900 0.928 4 0.250 0.167 0.083 0.800 0.667 0.214 0.269 0.250 0.119 0.071 5 0.083 0.039 IDH 1 0.050 0.083 0.083 0.039 0.024 2 0.850 0.833 0.833 0.500 0.800 0.917 0.833 0.962 0.875 0.905 0.900 0.857 3 0.100 0.167 0.083 0.500 0.200 0.167 0.125 0.048 0.100 0.143 MDH 1 0.200 0.125 2 1.000 1.000 1.000 1.000 0.800 1.000 1.000 1.000 0.875 1.000 1.000 1.000 716 Southeastern Naturalist Vol. 8, No. 4 with near equal numbers of butterfl ies collected supports our stated result. Averaging blocks, observed heterozygosity was 20% higher in the connected (Ho = 0.1928) than unconnected (Ho = 0.1547) patches. Similarly, expected heterozygosity increased by 23% in connected patches, while Wrights FST was 37% lower in connected than unconnected patches when blocks were averaged (Table 3). Finally, source-population butterfl ies were substantially and consistently higher in Ho, He, and percent polymorphic loci compared to butterfl ies collected within the experiment. Average values of Wrights FST for the source populations were more comparable to butterfl ies collected in connected than unconnected patches (Table 3). Table 3. Mean ± standard deviation (SE) of observed (Ho) and expected (He) heterozygosity within each block for connected (C) and unconnected (U) patches and source (S) populations. Also presented are mean ± SE for all blocks (1–6) and source populations (S1–S2) combined for Ho, He, percent polymorphic loic (% Ploci) and Wrights F statistic (FST). See Materials and Methods for a description of the analyses. Block Ho (mean ± SE) He (mean ± SE) % Ploci FST 1 C 0.2393 ± 0.2827 0.2163 ± 0.2660 55.6 0.0299 U 0.1746 ± 0.3228 0.1914 ± 0.2555 55.6 0.0913 2 C 0.1333 ± 0.1414 0.1330 ± 0.1518 55.6 0.0816 U 0.1270 ± 0.1667 0.1202 ± 0.1652 44.4 0.0973 3 C 0.2500 ± 0.3062 0.1840 ± 0.2064 55.6 0.0462 U 0.1270 ± 0.1813 0.1319 ± 0.1942 55.6 0.0943 4 C 0.1778 ± 0.2906 0.1778 ± 0.2325 44.4 0.1354 U 0.1481 ± 0.2561 0.1358 ± 0.2329 33.3 0.1681 5 C 0.1778 ± 0.3073 0.1394 ± 0.2209 33.3 0.0908 U 0.2222 ± 0.3727 0.1420 ± 0.2224 33.3 0.1001 6 C 0.2037 ± 0.3203 0.1775 ± 0.2474 44.4 0.0510 U 0.1481 ± 0.3379 0.0864 ± 0.1803 22.2 0.0783 1–6 C 0.1928 ± 0.0177 0.1690 ± 0.0126 47.4 ± 3.72 0.0643 ± 0.0156 U 0.1547 ± 0.0147 0.1310 ± 0.0139 38.7 ± 5.51 0.1017 ± 0.0130 S1 0.3210 ± 0.3411 0.2454 ± 0.2544 55.6 0.0185 S2 0.3278 ± 0.3392 0.2517 ± 0.2452 55.6 0.0185 S1–S2 0.3244 ± 0.0034 0.2485 ± 0.0032 55.6 ± 0.0 0.0185 ± 0.0 Table 2. Statistical results from Hardy-Weinberg Equilibrium analysis (χ2 and P value) for connected and unconnected patches and Ho and He analysis using a t-test (t and P value) for each locus. See Materials and Methods for a description of the analyses and loci. * = P < 0.05, ** = P < 0.1. Connected Unconnected Ho He Locus χ2 P χ2 P t P t P AAT 9.310 0.030* 10.31 0.020* 0.58 0.595 0.22 0.595 TPI 0.030 0.990 1.800 0.610 0.83 0.443 0.94 0.390 PGI 13.33 0.040* 21.42 0.002* 2.11 0.059** 1.15 0.275 PGM 7.050 0.720 8.080 0.620 0.51 0.621 0.37 0.718 IDH 14.27 0.003* 0.850 0.990 0.95 0.364 0.56 0.583 MDH 34.33 0.001* 2009 C.N. Wells, R.S. Williams, G.L. Walker, and N.M. Haddad 717 Discussion We found that J. coenia had higher levels of genetic variation in connected patches as measured by percent polymorphic loci, observed and expected heterozygosity, and lower FST values, strongly suggesting that increased dispersal between populations infl uences the genetic structure of populations. Furthermore, differences in genetic variation at the PGI locus occur due to connectivity, demonstrating that variation at loci implicated for importance in fitness and dispersal in butterfl ies is likely due to increased connectivity provided by corridors. Our study supports a previous multi-year study conducted at the SRS that found a greater number of marked butterfl ies released in a central patch are recaptured in patches connected by a corridor (Tewksbury et al. 2002). In combination with those results, our evidence suggests that movement between isolated populations is important for maintaining genetic diversity of J. coenia. By a number of metrics, our data suggest that habitat connectivity promotes greater genetic variability, as J. coenia had overall higher level of heterozygosity and polymorphic loci when corridors were present. The fixation index (i.e., FST) indicates moderate levels of genetic differentiation (see Wright 1978 for description) in populations collected within habitat patches, regardless of connectivity. Butterfl ies collected in connected patches did, however, have an overall lower FST than those in unconnected patches (Table 3), indicating less genetic divergence, likely because of increased gene fl ow. We base this conclusion in part on the fact that our results correspond with data on J. coenia movement within the same experimental corridor system that has shown increased movement of this butterfl y in patches connected by corridors (Tewksbury et al. 2002). Although other investigators have examined the effects of habitat fragmentation on the genetic structure of insect populations (Baguette et al. 2003, Johannesen et al. 1997, Kronforst and Fleming 2001, Meglécz et al. 2004, Williams et al. 2003), few have attempted to link a genetic analysis to movement results, providing a mechanistic explanation as to why genetic changes occur (Castellón and Sieving 2006, Keyghobadi et al. 1999). Our results also support the notion that habitat connectivity promotes polymorphism at a particular locus. Populations of J. coenia exhibited higher overall genetic variation at the PGI locus in connected habitats, refl ected in the marginally significantly higher Ho in connected versus unconnected patches (Table 2). This result is extremely interesting in light of recent studies linking the PGI locus to dispersal capability in butterfl ies (Hanski and Saccheri 2006). Relevant to our investigation, patch area and spatial connectivity of habitat have been demonstrated as being important in maintaining polymorphism of PGI (Hanski et al. 2004). Our results support the conclusion that spatial configuration of habitat can contribute to the maintenance of molecular polymorphisms, even in vagile taxa like butterfl ies. This is especially relevant in the experimental system used in this study, which accounted for the size of the corridor, and from previous work that determined the shape of the habitat patches 718 Southeastern Naturalist Vol. 8, No. 4 had no effect on the ability to capture butterfl ies (Tewksbury et al. 2002). Thus, in this system, there is no evidence the corridors acted as drift fences with respect to butterfl y movement. Although somewhat speculative, we conclude that variation at the PGI locus provides evidence that gene fl ow is the primary mechanism shaping the genetic structure of J. coenia in connected habitat patches. To better understand possible mechanisms contributing to the genetic differentiation observed in our experiment, we asked how well the model system refl ected source-population genetic differentiation. This is relevant to consider since the population genetic structure within experimental patches was ultimately dependent on butterfl ies colonizing from nearby source populations. We found that source populations had much higher genetic variation than butterfl ies in the experiment (Table 3). The substantially lower FST in these populations indicate higher levels of gene fl ow, resulting in genetic panmixia. Lower values of heterozygosity and FST values observed in our experiment are likely the result of a combination of founder effects and reduced gene fl ow (see Baughman et al. 1990, Nice and Shapiro 2001) compared to butterfl ies in the open environment outside the experimental units, which have likely passed through many generations. With no prior knowledge of genetic structure in founding butterfl ies, it is somewhat speculative to conclude that the genetic variation we found was due mostly to gene fl ow and not genetic drift (possibly due to a small population size in patches compared to the surrounding area). Nevertheless, provided that colonizing butterfl ies in connected and unconnected patches had similar levels of genetic variation after patches were created, the lower FST and higher heterozygosity in the connected patches two years later provide evidence that since the time of establishment, populations of J. coenia have differentiated more when a corridor connected patches. In conclusion, our investigation demonstrates the value of addressing genetic questions when the role of habitat connectivity on species in fragmented landscapes is being examined. We demonstrated greater levels of genetic differentiation in butterfl y populations connected by corridors and, importantly, provided evidence that variation in a key locus implicated in the fitness and dispersal of butterfl ies is affected by connectivity. Data from source populations suggest effects of both gene fl ow and possibly genetic drift acting in this system, pointing to a need to examine both population and genetic data in conservation studies. Though we studied a common species, our study suggests a need for similar experimental approaches in cases where species become rare or imperiled due to habitat fragmentation. Acknowledgments We sincerely thank Ellen Damschen for her help at SRS. We would like to thank all field assistants, especially Jeff White, for help with the butterfl y collections and Aaron Kennedy and Matt Estep (Appalachian State University), who provided valuable assistance in the allozyme analysis. We thank the anonymous reviewers for their helpful comments that improved this manuscript. The Cratis D. Williams Graduate School, the Biology Graduate Student Association, and the Graduate Student Association Senate supported this research at Appalachian State University. The 2009 C.N. Wells, R.S. Williams, G.L. Walker, and N.M. Haddad 719 creation of the experimental sites at SRS was funded by a collaborative grant from the National Science Foundation and by an interagency agreement with the Department of Energy Operations Office through the US Forest Service/Savannah River (DE-IA09-00SR22188). Literature Cited Aars, J., and R.A. Ims. 1999. The effect of habitat corridors on rates of transfer and interbreeding between vole demes. Ecology 80:1648–1655. Avise, J.C. 1975. Systematic value of electrophoretic data. Systematic Zoology 23:465–481. Avise, J.C. 1994. Molecular Markers, Natural History, and Evolution. Chapman and Hall, New York, NY. Baguette, M., G. Mennechez, S. Petit, and N. Schtickzelle. 2003. Effect of habitat fragmentation on dispersal in the butterfl y Proclossiana eunomia. Comptes Rendus Biologies 326:200–209. Baughman, J.F., P.F. Brussard, P.R. Ehrlich, and D.D. Murphy. 1990. History, selection, drift, and gene fl ow: Complex differentiation in checkerspot butterfl ies. Canadian Journal of Zoology 68:1967–1975. Berggren, A., B. Birath, and O. Kindvall. 2002. Effect of corridor and habitat edges on dispersal behavior, movement rates, and movement angles in Roesel’s Bush Cricket (Metrioptera roeseli). Conservation Biology 16:1562–1569. Bierregaard, R.O., T.E. Lovejoy, V. Kapos, A. Augusto dos Santos, and R.W. Hutchings. 1992. The biological dynamics of tropical rainforest fragments: A prospective comparison of fragments and continuous forest. Bioscience 42:859–866. Britten H.B., and P.F. Brussard. 1992. Genetic divergence and the Pleistocene history of alpine butterfl ies (Nymphalidae) and the endangered Nymphalidae in western North America. Zoology 70:539–548. Britten, H.B., and R.W. Rust. 1996. Populaiton structure of a sand dune-obligate beetle, Eusattus muricatus, and its implications for dune management. Conservation Biology 10:647–652. Britten H.B., P.F. Brussard, D.D. Murphy, and G.T. Austin. 1994. Colony isolation and isozyme variability of the Western Seep Fritillary, Speyeria nokomis apacheana (Nymphalidae), in the Western Great Basin. Great Basin Naturalist 54:97–105. Brittnacher, J.G., S.R. Sims, and F.J. Ayala. 1978. Genetic differentiation between species of the genus Speyeria (Lepidoptera: Nymphalidae). Evolution 32:199–210. Cardy, B.J., C.W. Stuber, J.F. Wendel, and M.M. Goodman. 1983. Techniques for starch gel electrophoresis of enzymes from maize (Zea mays L.). Institute of Statistics Monograph Series No.1317R, North Carolina State University, Raleigh, NC. Castellón, T.D., and K.E. Sieving. 2006. An experimental test of matrix permeability and corridor use by an endemic understory bird. Conservation Biology 20:135–145. Fahrig, L., and G. Merriam. 1985. Habitat patch connectivity and population survival. Ecology 66:1762–1768. Fischer, J., and D.B. Lindenmayer. 2007. Landscape modification and habitat fragmentation: A synthesis. Global Ecology and Biogeography 16:265–280. Goudet, J. 2001. F-STAT user’s Manual: A Program to Estimate and Test Gene Diversities and Fixation Indices (version 2.9.3). Available online at http://www.unil. ch/izea/softwares/fstat.html. Accessed September 2003. 720 Southeastern Naturalist Vol. 8, No. 4 Haag C.R., M. Saastamoinen, J.H. Marden, and I. Hanski. 2005. A candidate locus for variation in dispersal rate in a butterfl y metapopulation. Proceedings of the Royal Society B 272:2449–2456. Haas, C.A. 1995. Dispersal and use of corridors by birds in wooded patches on an agricultural landscape. Conservation Biology 9:845–854. Haddad, N.M. 1999a. Corridor and distance effects on interpatch movements: A landscape experiment with butterfl ies. Ecological Applications 9:612–622. Haddad, N.M. 1999b. Corridor use as predicted from behaviors at habitat boundaries. American Naturalist 153:215–227. Haddad, N.M. 2000. Corridor length and patch colonization by a butterfl y, Junonia coenia. Conservation Biology 14:738–745. Haddad, N.M., and K.A. Baum. 1999. An experimental test of corridor effects on butterfl y densities. Ecological Applications 9:623–633. Haddad, N.M., and J.J. Tewksbury. 2005. Low-quality habitat corridors as movement conduits for two butterfl y species. Ecological Applications 15:250–257. Haddad, N.M., D.R. Bowne, A. Cunningham, B. Danielson, D. Levey, S. Sargent, and T. Spira. 2003. Corridor use by diverse taxa. Ecology 84:609–615. Hale, M.L., P.W. Lurz, M.D. Shirley, S. Rushton, R.M. Fuller, and K. Wolff. 2001. Impact of landscape management on the genetic structure of red squirrel populations. Science 293:2246–2248. Hänfl ing, B., W. Durka, and R. Brandl. 2004. Impact of habitat fragmentation on genetic population structure of roach, Rutilus rutilus, in a riparian ecosystem. Conservation Genetics 5:247–257. Hanski, I., and I. Saccheri. 2006. Molecular-level variation affects population growth in a butterfl y metapopulation. PLoS Biology 4: e129. Hanski, I., C. Erälahti, M. Kankare, O. Ovaskainen, and H. Sirén. 2004. Variation in migration rate among individuals maintained by landscape structure. Ecology Letters 7:958–966. Harris, L.D. 1984. The Fragmented Forest: Island Biogeographic Theory and Preservation of Biotic Diversity. University of Chicago Press, Chicago, IL. Hoole, J.C., D.A. Joyce, and A.S. Pullin. 1999. Estimates of gene fl ow between populations of the Swallowtail Butterfl y, Papilio machaon, in Broadland, UK and implications for conservation. Biological Conservation 89:293–299. Johannesen, J., U. Schwing, W. Seufert, A. Seitz, and M. Veith. 1997. Analysis of gene fl ow and habitat-patch network for Chazara briseis (Lepidoptera: Satyridae) in an agricultural landscape. Biochemical Systematics and Ecology 25:419–427. Keyghobadi, N., J. Roland, and C. Strobeck. 1999. Infl uence of landscape on the population genetic structure of the alpine butterfl y Parnassius smintheus (Papilionidae). Molecular Ecology 8:1481–1495. Knutsen, H., B.A. Rukke, P.E. Jorde, and A.I. Rolf. 2000. Genetic differentiation among populations of the beetle Bolitophagus retculatus (Coleoptera: Tenebrionidae) in a fragmented and continuous landscape. Heredity 84:667–676. Kronfrost, M.R., and T.H. Fleming. 2001. Lack of genetic differentiation among widely spaced subpopulations of a butterfl y with home-range behavior. Heredity 86:243–250. Levene, H. 1949. On a matching problem arising in genetics. Annals of Mathematics and Statistics 20:91–94. Machtans, C.S., M. Villard, and S.J. Hannon. 1996. Use of riparian buffer strips as movement corridors by forest birds. Conservation Biology 10:1366–1379. Manel, S., M.K. Schwartz, G. Luikart, and P. Taberlet. 2003. Landscape genetics: Combining landscape ecology and population genetics. Trends in Ecology and Evolution 18:189–197. 2009 C.N. Wells, R.S. Williams, G.L. Walker, and N.M. Haddad 721 Mann, C.C., and M.L. Plummer. 1995. Are wildlife corridors the right path? Science 270:1428–1430. Mech, S.G., and J.G. Hallett. 2001. Evaluating the effectiveness of corridors: A genetic approach. Conservation Biology 15:467–474. Meglécz, E., G. Nève, K. Pecsenye, and Z. Varga. 2004. Genetic variations in space and time in Parnassius mnemosyne (L.) (Lepidoptera) populations in northeast Hungary: Implications for conservation. Biological Conservation 89:251–259. Merriam, G., and D.A. Saunders. 1993. Corridors in restoration of fragmented landscapes. Pp. 71–87, In D.A. Saunders, R.J. Hobbs, and P.R. Ehrlich (Eds.). Nature Conservation III: Reconstruction of Fragmented Ecosystems. Surrey Beatty and Sons, Chipping Norton, New South Wales, Australia. Mettler, L.E., T.G. Gregg, and H.E. Schaffer. 1988. Population Genetics and Evolution, 2nd Edition. Patience Hall, Englewood Cliffs, NJ. Nei, M. 1973. Analysis of gene diversity in subdivided populations. Proceedings of the National Academy of Science 70:3321–3323. Nei, M. 1978. Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics 89:583–890. Nei, M. 1987. Molecular Evolutionary Genetics. Columbia University Press, New York, NY. Nice, C.C., and A.M. Shapiro. 2001. Population genetic evidence of restricted gene fl ow between host races in the butterfl y genus Mitoura (Lepidoptera: Lycaenidae). Annals of the Entomological Society of America 94:257–267. Noss, R.F. 1991. Landscape connectivity: Different functions at different scales. Pp. 27–39, In W.E. Hudson (Ed.). Landscape Linkages and Biodiversity. Island Press, Washington, DC. Noss, R.F. 1992. Wildlife corridors. Pp. 76–113, In D. Smith and P. Hellmund (Eds.). Ecology of Greenways. University of Minnesota Press, Minneapolis, MN. Opler, P.A. 1998. A Field Guide to Eastern Butterflies. Houghton Mifflin, New York, NY. Peterson, M.A., and R.F. Denno. 1998. Life-history strategies and the genetic structure of phytophagous insect populations. Pp. 263–322, In M. Mopper and S.Y. Strauss (Eds.). Genetic Structure and Local Adaptation in Natural Insect Populations. Chapman and Hall, New York, NY. Porter, A.H., and S.O. Mattoon. 1989. A new subspecies of Coenonympha tullia (Müller) (Nymphalidae: Satyrinae) confined to the coastal dunes of northern California. Journal of the Lepidopterists’ Society 43:229–238. Pyle, R.M. 1981. National Audubon Society Field Guide to North American Butterfl ies. Alfred A. Knopf, New York, NY. Reed, D.H., and R. Frankham. 2003. Correlation between fitness and genetic diversity. Conservation Biology 17:230–237. Saunders, D.A., J.A. Hobbs, and C.R. Margules. 1991. Biological consequences of ecosystem fragmentation: A review. Conservation Biology 5:18–32. SAS Institute. 2001. PROC User’s Manual, version 8.12., Cary, NC. Schmitt, T., and A. Seitz. 2002. Infl uence of habitat fragmentation on the genetic structure of Polyommatus coridon (Lepidoptera: Lycaenidae): implications for conservation. Biological Conservation 107:291–297. Selander, R.K., M.H. Smith, S.Y. Yang, W.E. Johnson, and J.B Gentry. 1971. Biochemical polymorphism and systematics in the genus Peromyscus: Variation in the Oldfield Mouse (Peromyscus polionotus). University of Texas Publication 7103:49–90. 722 Southeastern Naturalist Vol. 8, No. 4 Six, D.L., T.D. Paine, and J.D. Hare. 1999. Allozyme diversity and gene fl ow in the bark beetle, Dendroctonous jeffreyi (Coleoptera: Scolytidae). Canadian Journal of Forest Restoration 29:315–323. Slatkin, M. 1985. Gene fl ow in natural populations. Annual Review of Ecology and Systematics 16:393–430. Solé, R.V., D. Alonso, and J. Saldana. 2004. Habitat fragmentation and biodiversity collapse in neutral communities. Ecological Complexity 1:65–75. Soltis, D.E., C.H. Haufl er, D.C. Darrow, and G.J. Gastony. 1983. Starch gel electrophoresis of ferns: A compilation of grinding buffers, gel and electrode buffers, and staining schedules. American Fern Journal 73:9–27. Sutcliffe, O.L., and C.D. Thomas. 1996. Open corridors appear to facilitate dispersal of Ringlet Butterfl ies (Aphantopus hyperantus) between woodland clearings. Conservation Biology 10:1359–1365. Tewksbury, J.J., D.J. Levey, N.M. Haddad, S. Sargent, J.L. Orrock, A. Weldon, B.J. Danielson, J. Brinkerhoff, E.I. Damschen, and P. Townsend. 2002. Corridors affect plants, animals, and their interactions in fragmented landscapes. Proceedings of National Academy of Science 99:12923–12926. Vandewoestijne, S., and M. Baguette. 2004. Genetic population structure of the vulnerable Bog Fritillary butterfl y Hereditas 141:199–206. Vandewoestijne, S., G. Nève, and M. Baguette. 1999. Spatial and temporal population genetic strucuture of the butterfl y Aglais urticae L. (Lepidoptera: Nymphalidae). Molecular Ecology 8:1539–1543. Van Rossum, F., S.C. De Sousa, and L. Triest. 2004. Genetic consequences of habitat fragmentation in an agricultural landscape on the common Primula veris, and comparison with its rare congener, P. vulgaris. Conservation Genetics 5:231–245. Wallace, B. 1981. Basic Population Genetics. Columbia University Press, New York, NY. Watt, W.B. 2003. Mechanistic studies of butterfl y adaptation. Pp. 319–352, In C.L. Boggs, W.B. Watt, and P.R. Ehrlich, (Eds.). Butterfl y Ecology and Evolution Take Flight. University of Chicago Press, Chicago, IL. Werth, C.R. 1985. Implementing an isozyme laboratory at a field station. Virginia Journal of Science 36:53–76. Wilcove, D.S., D. Rothstein, J. Dunbow, A. Phillips, and E. Losos. 1998. Quantifying threats to imperiled species in the United States. Bioscience 48:607–615. Williams, B.L., J.D. Brawn, and K.N. Page. 2003. Landscape-scale genetic effects of habitat fragmentation on a high gene-fl ow species: Speyeria idalia (Nymphalidae). Molecular Ecology 12:11–20. Wright, S. 1951. The genetical structure of populations. Annals of Eugenics 15:323–420. Wright, S. 1965. The interpretation of population genetic structure by F-statistics with special regard to systems of mating. Evolution 19:395–420. Wright, S. 1978. Variability Within and Among Natural Populations. Volume 4. The University of Chicago Press, Chicago, IL. Yeh, F.C., R.C. Yang, T.B. Boyle, Z.H.Ye, and J.X. Mao. 1997. Popgene-32: The user-friendly shareware for population genetic analysis. Molecular Biology and Biotechnology Centre, University of Alberta, Edmonton, Alberta, Canada. Zhang, Z., and M.B. Usher. 1991. Dispersal of Wood Mice and Bank Voles in an agricultural landscape. Acta Theriological 36:239–245.