Genetic variation among populations of the endangered giant kangaroo rat, Dipodomys ingens, in the Southern San Joaquin Valley.
The giant kangaroo rat (Dipodomys ingens) is listed both federally and in the state of California as an endangered species and has been since the 1980s, making its conservation of the utmost importance. The giant kangaroo rat now inhabits only a small portion of its historic range (Good et al., 1997; Loew el al, 2005). This species is endemic to the San Joaquin Valley and several small valleys to the southwest. The giant kangaroo rat was once widespread, but populations have decreased since the early 1900s, in part due to secondary exposure to rodenticides when ranchers attempted to eliminate the California ground squirrel (Spermophilus beecheyi) on grazing land (Williams, 1992; Whisson, 1999). Populations have further decreased due to agricultural development since the 1960s (Williams and Kilburn, 1991). Giant kangaroo rats occur on shrublands of saltbush (Alriplex sp.) and California ephedra (Ephedra californica; Shaw, 1934; Williams and Kilburn, 1991; Williams, 1992) on sandy loam soils that do not tend to flood. The habitat is usually dominated by a herbaceous layer of exotic grasses (Williams and Kilburn, 1991; Schiffman, 1994).
Good et al. (1997) and Loew el al. (2005) performed genetic analyses of giant kangaroo rats in the northern portion of the species range and in the southern end but west of the Temblor Mountains (Fig. 1). Mitochondrial DNA suggested that population sizes have fluctuated over time and/or that populations have not been isolated from one another for a substantial period of time (Good el al., 1997). Their southern-most populations were not genetically subdivided, but there was subdivision between the northern and southern-most populations and among some of the northern populations (Good el al., 1997). There was more genetic distance between some northern haplotypes than between any northern and southern haplotypes despite greater geographic distance north to south. Also, one northern population contained old allelic lineages and shared ancestral polymorphisms with several other populations (Good et al., 1997). Further, there was evidence that there had been a recent increase in population size in the remaining populations in the north and suggested one valley could have played an important role in the expansions. This increase in population size is consistent with what Williams el al. (1995) found when estimating population size of giant kangaroo rats in the north. It was found that the area occupied by colonies in the northern populations during the early 1990's was 6.6 times greater than what was calculated in the 1980s (Williams el al., 1995).
[FIGURE 1 OMITTED]
Using microsatellites, Loew el al (2005) also found significant genetic subdivision for the northern and southern range but there was still considerable gene flow among the southern populations (Fig. 1). The northern populations in Fresno and San Benito counties exhibited nonrandom mating and genetic drift within subpopulations. Loew ei al (2005) concluded effective dispersal and genetic distances between populations is better predicted by ecological conditions and topography of the environment than by linear geographic distance between populations.
Because of the endangered status of the giant kangaroo rat, the fragmentation of its range can be detrimental to its long-term survival (US Fish and Wildlife Service, 1998; Germano el al, 2001). Within this context it is important to understand the genetic structure of fragmented populations and determine the most at-risk populations in order for targeted conservation action to be taken if the population structure indicates species decline. We used the analysis of microsatellite loci to determine the genetic structure of six populations of giant kangaroo rats in the southern San Joaquin Valley. This approach has become a popular choice among ecologists over the last decade (DeSalle and Amato, 2004; Selkoe and Toonen, 2006) because it allows for a precise and statistically powerful way to estimate gene flow and genetic relatedness within and between individuals and populations (Selkoe and Toonen, 2006).
Although the studies by Good el al. (1997) and Loew el al. (2005) were fairly comprehensive in the populations they studied, they did not analyze populations of giant kangaroo rats in the southern San Joaquin Valley, which historically and currently has supported large numbers of giant kangaroo rats. Because the area we studied is a major portion of the range of the species (U.S. Fish and Wildlife Service 1998) that has not been previously evaluated, we conducted a genetic study among populations of the giant kangaroo rat from six sites in the southern San Joaquin Valley and compared our results to the other two metapopulations that had been studied (Good et al., 1997; Loew et al., 2005). We measured the genetic diversity, including the number of alleles per locus, observed heterozygosity, and expected heterozygosity under Hardy-Weinberg assumptions. We predicted that there would be some differentiation among populations in the southern San Joaquin Valley because the populations are fragmented and separated by both linear distance and features of the landscape, but that there would be less difference among populations within the southern San Joaquin as compared to populations across the Temblor Mountains to the west and to populations farther north due to greater geographical distance between these populations and the southern ones.
SAMPLING LOCATIONS AND POPULATIONS
We collected tissue samples from six populations of giant kangaroo rats in the southern part of the range in the San Joaquin Valley (Fig. 2). All sites were in Kern County and included populations at North Lokern (n = 20; 35[degrees]25'43"N, 119[degrees]37'06"W), Lokern (n = 20; 35[degrees]20'19"N, 119[degrees]36'09"W), Midway (n = 10; 35[degrees]11'12"N, 119[degrees]29'05"W), Derby Acres (n = 20; 35[degrees]15'22"N, 119[degrees]33'60"W), Buttonwillow (n = 20; 35[degrees]21'29"N, 119[degrees]28'20"W), and Northwest Belridge (n = 11; 35[degrees]27'25"N, 119[degrees]45'03"W). We collected tissue samples fall 2011 and spring 2012. We used 30-50 Sherman live traps baited with bird seed to catch kangaroo rats. We set approximately three traps in late afternoon around each active precinct (burrow system used by single giant kangaroo rat) to ensure catching the most individuals per night. We checked traps starting at dawn the next morning. Once an individual was caught at a precinct, we would move traps to new precincts if additional trapping was needed. Trapping lasted until we caught 10 males and 10 females at a site (1-3 nights usually), although we stopped after 5 nights if we did not catch new kangaroo rats. We collected individual samples of small ear clips for DNA extraction from males and females from each site. We immediately placed ear clips in 90% ethanol and took samples back to the lab for freezing until we could complete DNA extractions.
[FIGURE 2 OMITTED]
DNA EXTRACTION. PCR AMPLIFICATION AND DNA SEQUENCING
We extracted genomic DNA from 2-4 [mm.sup.2] ear clippings cut into small pieces using the DNeasy Tissue Kit (Qiagen, Valencia, California). The microsatellite primers used in this study were characterized in banner-tailed kangaroo rats (Dipodomys spectabilis) and giant kangaroo rats by Davis et al. (2000). We performed all (PCR) amplifications in 50 [micro]l volume that contained 2 [micro]l of genomic DNA (50 ng) and 200 [micro]M dNTP, 0.2 [micro]M of each primer, 1.5 mM Mg[Cl.sub.2], 2.5 units of HotStarTaq DNA polymerase, and lx PCR buffer (10mM Tris buffer, pH 8.8, 0.1% Triton X-100, 50mM KC1 and 0.16 mg/mL BSA. The temperature profile for the microsatellite PCR amplification consisted of an initial heat activation step of 95 C for 15 min followed by three cycles of 94 C 0.5-1 min, 50-68 C for 0.5-1 min, and 72 C for 1 min. The number of cycles we used was 25-35. A final extension step of 72 C for 10 min was also added. We electrophoresed PCR products on a 1.0% agarose gel to detect successful amplification. We submitted PCR products to the DNA Sequencing Core Facility of the University of Florida to be run on an automated ABI 3730 DNA Analyzer with Genescan 500-LIZ as an internal size standard.
We imported and read the ABI fragment analysis files to predict allele sizes to infer individual genotypes using GeneMarker v1.97 (Softgenetics, U.S.A.). We used these genotypes to measure genetic diversity, including the number of alleles per locus (N\), observed heterozygosity ([H.sub.O]) and expected heterozygosity ([H.sub.E]) under Hardy-Weinberg assumptions (Nei 1978), using the program GENALEX v6.5 (Peakall and Smouse, 2006; 2012). The degree of genetic differentiation among the predefined geographical populations was determined with pairwise [F.sub.ST] and AMOVA using GENALEX (Peakall and Smouse, 2006; 2012) and GENEPOP v4.0 (Rousset, 2008) with Bonferroni correction applied. We also analyzed the variation within the genetic distance using principal coordinate analysis as implemented in GENALEX (Peakall and Smouse, 2006; 2012). Lastly, we used Mantel tests in GENALEX and spatial autocorrelation analysis to explore the relationship between ecological and/or genetic variables and geographic location.
Initially, we evaluated all of the microsatellite loci except for Dil2F characterized by Davis el al. (2000) for amplification success from 101 giant kangaroo rats from six populations. Of these, Ds46 was not successful and Dsl9 was only successful for 17 individuals. We conducted analyses both with and without the inclusion of Dsl9 to ensure this locus was not having a significant impact on the results and the results were congruent. As a preliminary evaluation of population structure, we calculated pairwise FST values in GENALEX using 10,000 random permutations of the data. This initial analysis revealed that the DS3, DS19, and DS28 loci for the Lokern population were not in Hardy-Weinberg equilibrium (HWE). With locus DS19 removed due to missing data, pairwise population comparisons were then made for each of the remaining loci using Genepop 4.0 (Rousset, 2008) with Bonferroni correction applied. After correction, only DS28 (Lokern) was found to not be in HWE (P < 0.01). All subsequent analyses included the Dsl9 locus. Thus, the comparison of genetic diversity between populations was based on seven loci (Dsl, Ds3, Dsl9, Ds28, Ds30, Di5, Dil2E). The size range of alleles at these loci are presented in Table 1, and are all greater than those found by Loew el al. (2005), with a few overlapping alleles lengths at each locus.
POLYMORPHISM AND ALLELE FREQUENCY DISTRIBUTIONS
Loci Dsl, Ds28, Ds30, and Dil2E were polymorphic for each subpopulation (for exceptions see below), whereas Ds3 was monomorphic at the Buttonwillow site and Di5 was monomorphic at the Northwest Belridge site (Table 1). The monomorphism at Di5 was not surprising because only two alleles were seen in D. ingens in Davis el al (2000) and this locus was monomorphic at one of the subpopulations sampled by Loew el al (2005). Dsl9 was monomorphic at the Northwest Belridge; although this is based on only one successful PCR amplification for this locus at this site (Table 1). The maximum number of alleles detected per polymorhphic locus was 14 at locus Ds30 (Table 1). This was fairly consistent with what Loew et al. (2005) found in their southern populations. The mean number of alleles per locus ([N.sub.A]) ranged from 3 to 5 (Table 2). This is slightly less than that found by Loew et al. (2005) in the south, but consistent with what was described in the northern populations.
HARDY-WEINBERG EQUILIBRIUM AND HETEROZYGOSITY
Observed heterozygosities ranged from 0.38 to 0.51, and expected heterozygosities ranged from 0.42 to 0.56 (Table 2). All populations showed random mating with no heterozygote deficiencies, but values were less than those found by Loew et al. (2005). Expected heterozygosity was also relatively low, ranging from 0.42 in Northwest Belridge to 0.56 in Buttonwillow (Table 2). An AMOVA based on 9999 permutations of the distance matrix for calculation of [[PHI].sub.ST], revealed significant heterogeneity among the six populations ([PHI] = 0.183, P < 0.001; Table 3). The AMOVA also indicated that there was greater variation within populations (82%) than among populations (18%; Table 3).
POPULATION DIFFERENTIATION AND GENETIC DISTANCES
[F.sub.1S] is values for individual loci were significantly positive for Ds3, Dsl9, and Ds28 (Table 4), which is consistent with the deviation from Hardy-Weinberg frequencies within populations. The multilocus [F.sub.1S] was significantly higher than zero at the 1% level, which indicates an extreme deficit in heterozygotes. The multilocus [F.sub.ST] values were significantly different from zero, and are consistent with the individual locus analyses that revealed significantly positive values for each locus at the 1% level (Table 4).
The relationship between the matrices of the genetic distances [(delta mu).sup.2] and linear distances between populations was not significant ([R.sub.xy] = 0.257; P = 0.220; Fig. 3). Pairwise [F.sub.ST], [[PHI].sub.ST] and Nei's genetic distance analyses showed significant differentiation between all populations except for Lokern and Northwest Belridge (Table 5). Most all of these were significant at the 1% level except for Lokern and Buttonwillow, which was significant at 5% (Table 5). The principle coordinates analysis, which gives a visual representation of groupings, showed the Midway population and the Derby Acres population to be distinctly different, whereas the other four populations grouped together (Fig. 4). The first principle coordinate accounted for 50.72% of the variation and PC2 accounted for 26.44%.
[FIGURE 3 OMITTED]
[FIGURE 4 OMITTED]
The populations spanned approximately 35 km from the northernmost to the southernmost sites with no obvious natural geographic barriers. On the other hand, some populations were highly fragmented due to agricultural development (i.e., North Lokern) and separated by the California aqueduct (i.e., Buttonwillow). Pairwise comparisons did reveal [F.sub.ST] values that were significantly different from zero (Table 5). Along with the high Us and [F.sub.ST] values, the overall multilocus F-statistic ([F.sub.IT]) was also significantly different from zero (Table 4).
Local extinctions of the giant kangaroo rat have been occurring as a result of their natural communities becoming highly fragmented due to agricultural development (Loew el al, 2005) as well as poisoning that occurred in the early 1900s when California ground squirrels were targeted (Williams, 1992; Whisson, 1999). The remnant populations are fragmented and limited to suboptimal habitat on the western edge of the Tulare and Carrizo Basins, and the Cuyama and Panoche valleys and the adjacent foothills (Grinnell, 1932; Williams, 1992; Goldingay el al., 1997). The principle coordinate analysis showed the Lokern, North Lokern, and Northwest Belridge sites to be grouped together, an expectation based on their close geographic distance. These sites also grouped with the Buttonwillow site, which was not expected due to the California aqueduct representing a possible recent geographic barrier to a relatively new population that was reinvading this fallow field. We also expected the Midway and Derby Acres sites to be grouped together based on their proximity to each other, but this was not recovered in the principle coordinate analysis. This finding suggests that other factors, other than linear geographic distance, are operating to affect the genetic structure of populations in the southern San Joaquin Valley.
The significant genetic subdivision among populations was consistent with the increasing habitat fragmentation but not correlated with linear geographic distance among the six subpopulations examined. The multilocus F-statistics indicated that the six populations of giant kangaroo rat are experiencing significant amounts of genetic drift and inbreeding. The genetic drift these populations are experiencing can result in random fixation and loss of alleles within populations and thus increase the amount of differentiation among populations (Loew et al, 2005). On the other hand, gene flow among populations can counteract the detrimental effects of drift and preserve genetic diversity within subpopulations (Harrison and Hastings, 1996). Many species are considered endangered because of declining populations due to a variety of causes that in many cases includes habitat loss (Wilcove et al., 1998), and it is expected that genetic diversity would be decreased in these endangered species compared to non-endangered species. Habitat loss generally results in significant geographic separation among surviving populations, especially those species with reduced vagility. However, pairwise FST values indicate that the Lokern and Northwest Belridge sites, which represent two of the most geographically isolated sites sampled in the study, are not completely isolated from each other, whereas geographically closer populations exhibited significant genetic subdivision.
Good el al (1997) concluded that the southern populations on the Carrizo Plain to the west of the Temblor Mountains effectively act as one large population but that they had experienced fluctuations in size that could affect the genetic structure. These fluctuations in size were consistent with what Loew et al. (2005) also found, that the populations on the Carrizo Plain deviated from Hardy-Weinberg expectations, which could be due to genetic drift. The populations that we sampled in the southern San Joaquin Valley are east of the Temblor Mountains and also deviated from what would be expected under Hardy-Weinberg expectations without hating any long-term natural barriers. We expect that the Temblor Mountains could serve as a natural barrier between the populations occurring on either side, but we could not test that hypothesis directly with our data. Heterozygote frequencies at the Midway, Buttonwillow, and the North Lokem sites suggested that though they did deviate from Hardy-Weinberg expectations, they were slightly higher than those of the other populations, which can be evidence of population growth (Loew et al, 2005). The number of giant kangaroo rats captured at the North Lokern site during trapping in the spring of 2012 was an all-time high (D. Germano and L. Saslaw, unpubl data). In addition numbers of giant kangaroo rats at the Buttonwillow site were high on this once farmed field, which suggests rapid reestablishment and population growth. This population size fluctuation could have had an effect on the genetic structure that we found in these populations at the time of sampling, which would be consistent with what Good et al. (1997) found with their southern populations.
Population fluctuations and turnover within metapopulations can accelerate genetic drift, decreasing genetic diversity within populations and increasing differentiation among fragmented populations (Harrison and Hastings, 1996; Toro and Caballero, 2005). Population differentiation can be slowed, halted, or even reversed as a result of even a few migrants per generation (Wang, 2004; Greenbaum et al, 2014). The number of migrants occurring per generation can be affected by geographic distance, topography, and ecological conditions (Good el al., 1997; Loew et al, 2005) with ecological conditions having a greater effect than geographic distance (Hokit et al, 2010).
Good et al (1997) and Loew et al (2005) inferred that the Ciervo Hills population in the north was founded by one or several recent migrants from the nearby Panoche Valley and is isolated from other populations by distance and geographic barriers. The topography within the range of the giant kangaroo rat is complex with the remaining populations separated by unsuitable habitat that can limit dispersal (Loew et al, 2005). The area is becoming even more fragmented due to agricultural and residential development limiting dispersal even more. It was shown that linear geographic distances are less likely to predict dispersal than ecological conditions (Good et al, 1997; Loew et al., 2005).
The genetic differentiation that we observed in the absence of substantial geographic distance was consistent with what Loew et al (2005) found within the northern populations. In this regard, genetic differentiation may still result due to substantial habitat fragmentation and/or relatively low vagility of the species. Because we found genetic differentiation among populations, we conclude that the populations in the southern San Joaquin Valley are highly structured.
Demographic factors, such as the populations being isolated from each other, could be the cause for the significant [F.sub.IS] and [F.sub.ST] values of giant kangaroo rat populations. By definition, endangered species often exhibit relatively small population sizes that may be highly fragmented. As such reduced heterozygosity due to genetic drift and/or inbreeding is a significant concern. Moderate inbreeding was supported within our populations. There were no negative [F.sub.IS] values that were significant, which is consistent with a low degree of polygyny and suggests insignificant sex bias in natal dispersal (Metcalf el al, 2001).
Our study has demonstrated the importance of understanding the population structure in the context of habitat fragmentation for the conservation of this endangered species. Metcalf et al (2001) demonstrated using mitochondrial DNA that Dipodomys species can colonize previously occupied habitat through long distance dispersal or in a stepping stone fashion through shorter dispersal events. The Soda Lake population studied by Loew et al (2005) indicates that when translocations are implemented, genetically diverse founders and the resulting gene flow among neighboring populations can result in beneficial population growth and the maintenance of high genetic diversity.
In future genetic studies of this species, it would be beneficial to resample the populations in the other metapopulations to determine their relation to those in the southern San Joaquin Valley, which we could not do because we could not access the data of Loew et al. (2005). Also, future studies on natal and breeding dispersal would provide better insight on the differentiation within populations. Monitoring in these cases would be important because this would allow for more information to be gained for better implementing management plans that will allow long-term survival of the giant kangaroo rat.
Acknowledgments.--This research was funded by Student Research Scholars Program, San Joaquin Valley Chapter of The Wildlife Society, and the Graduate Student-Faculty Collaborative Initiative. We thank L. Saslaw, D. Noce, R. Kelty, and J. Parker for assistance with fieldwork and support. Also, thanks to K. White for the assistance with the GIS maps. Thanks to C. Kloock for reading an earlier version of this manuscript, and for several helpful discussions. Giant kangaroo rats were captured under permits (California SC-000955 and Federal Permit No. TE749872-2) held by the second author and the study protocol was approved by the Institutional Animal Care and Use Committee (11-01) of California State University, Bakersfield.
Davis, C., B. Keane, B. Swanson, S. Loew, P. M. Waser, C. Strobeck, and R. C. Fleischer. 2000. Characterization of microsatellite loci in bannertailed and giant kangaroo rats, Dipodomys spectabilis and Dipodomys ingens. Mol. Ecol., 9:629-644.
DeSalle, R. and G. Amato. 2004. The expansion of conservation genetics. Nat. Rev. Genet., 5:702--712.
Germano, D. J., G. B. Rathbun, and L. R. Saslaw. 2001. Managing exotic grasses and conserving declining species. Wildlife Soc. Bull., 29:551-559.
Goldingay, R. L., P. A. Kelly, and D. F. Williams. 1997. The kangaroo rats of California: endemism and conservation of keystone species. Pacific Consent. Biol., 3:47-60.
Good, S. V., D. F. Williams, K. Ralls, and R. C. Fleischer. 1997. Population structure of Dipodomys ingens (Heteromyidae): the role of special heterogeneity in maintaining genetic diversity. Evolution, 51:1296-1310.
Greenbaum G., A. R. Templeton, Y. Zarmi, and S. Bar-david. 2014. Allelic richness following population founding events--a stochastic modeling framework incorporating gene flow and genetic drift. PloS ONE, 9, el 15203.
Grinnell, J. 1932. Habitat relations of the giant kangaroo rat. J. Mammal., 13:305-320.
Harrison, S. and A. Hastings. 1996. Genetic and evolutionary consequences of metapopulation structure. Trends Ecol. Evol., 11:180-183.
Hokit, D. G., M. Ascunce, J. Ernst, L. C. Branch, and A. M. Clark. 2010. Ecological metrics predict connectivity better than geographic distance. Consent. Genet., 11:149-159.
IUCN. 2012. IUCN red list of threatened species. Version 2012.1. Available from http: // www.icunredlist.org. Accessed 20 May 2013.
Loew, S. S., D. F. Williams, K. Ralls, K. Pilgrim, and R. C. Fleischer. 2005. Population structure and genetic variation in the endangered giant kangaroo rat (Dipodomys ingens). Consent. Genet., 6:495-510.
Metcalf, A. E., L. Nunney, and B. C. Hyman. 2001. Geographic patterns of genetic differentiation within the restricted range of the endangered Stephens' kangaroo rat Dipodomys stephensi. Evolution, 55:1233-1244.
Nei, M. 1978. Estimation of average heterozygosity and genetic distance from a small number of individuals. Genetics, 89:583-590.
Peakall, R. and P. E. Smouse. 2006. GENALEX 6: genetic analysis in Excel. Population genetic software for teaching and research. Mol. Ecol. Notes, 6:288-295.
--. 2012. GENALEX 6.5: genetic analysis in Excel. Population genetic software for teaching and research--an update. Bioinformatics, 28:2537-2539.
Rousset, F. C. 2008. GENEPOP '007: a complete re-implementation of the genepop software for Windows and Linux. Mol. Ecol. Resoueces, 8:103-106.
Schiffman, P. M. 1994. Promotion of exotic weed establishment by endangered giant kangaroo rats (Dipodomys ingens) in a California grassland. Biodivers. Conserv., 3:524-537.
Selkoe, K. A. and R. J. Toonen. 2006. Microsatellites for ecologists: a practical guide to using and evaluating microsatellite markers. Ecol. Letters, 9:615-629.
Shaw, W. T. 1934. The ability of the giant kangaroo rat as a harvester and storer of seeds. J. Mammal., 15:275-286.
Toro, M. A. .and A. Caballero. 2005. Characterization and conservation of genetic diversity in subdivided populations. Philos. T. Roy. Soc. B, 360:1367-1371.
U.S. Fish and Wildlife Service. 1998. Recovery plan for upland species of the San Joaquin Valley, California. Pordand, OR, U.S.A.
Wang, J. 2004. Application of the one-migrant-per-generation rule to conservation and management. Conserv. Biol., 18:332-343.
Whisson, D. A. 1999. Modified bait stations for California ground squirrel control in endangered kangaroo rat habitat. Wildlife Soc. Bull., 27:172-177.
Wilcove, D. S., D. Rothstein, J. Dubow, A. Philips, and E. Losos. 1998. Quantifying threats to imperiled species in the United States. Biosci., 48:607-615.
Williams, D. F. 1992. Geographic distribution and population status of the giant kangaroo rat, Dipodomys ingens (Rodentia, Heteromyidae). p. 130-328. In: D. F. William, S. Byrne and T. A. Rado (eds.). Endangered and Sensitive Species of the San Joaquin Valley, California: Their Biology, Management and Conservation. California Energy Commission, Sacramento, U.S.A.
Williams, D. F., M. K. Davis, .and L. P. Hamilton. 1995. Distribution, population size, and habitat features of giant kangaroo rats in the northern segment of their geographical range. California Department of Fish and Game, Bird and Mammal Conservation Program Report 95-01.
Williams, D. F., and K. S. Kilburn. 1991. Dipodomys ingens. Mamm. Species, 377:1-7.
Submitted 21 April 2015 Accepted 22 December 2015
(1) Corresponding author: e-mail: firstname.lastname@example.org
NICOLE C. BLACKHAWK, DAVID J. GERMANO (1) and PAUL T. SMITH
Department of Biology, California State University, Bakersfield 93311
TABLE 1.--Observed allele frequencies by locus and population of the giant kangaroo rat (Dipodomys ingens) from the southern San Joaquin Valley, California. Loci Ds3, Dsl9, and Ds28 from Lokern were not in Hardy-Weinberg Equilibrium (P < 0.05) Group n Allele size (bp) Ds1 185 189 193 196 Lokern 20 0.150 0.125 0.050 0.000 North Lokern 20 0.125 0.275 0.000 0.000 Midway 10 0.000 0.100 0.000 0.000 Derby Acres 20 0.100 0.025 0.000 0.000 Buttonwillow 20 0.125 0.075 0.000 0.150 Northwest Belridge 11 0.136 0.182 0.045 0.045 Ds3 169 189 193 197 Lokern 20 0.075 0.850 0.000 0.075 North Lokern 20 0.000 0.975 0.025 0.000 Midway 10 0.100 0.850 0.050 0.000 Derby Acres 20 0.100 0.425 0.475 0.000 Buttonwillow 20 0.000 1.000 0.000 0.000 Northwest Belridge 11 0.045 0.773 0.182 0.000 Ds19 117 123 127 129 Lokern 7 0.000 0.000 0.000 0.286 Derby Acres 2 0.500 0.000 0.500 0.000 Buttonwillow 7 0.000 0.286 0.143 0.357 Northwest Belridge 1 0.000 1.000 0.000 0.000 Ds28 196 206 208 212 Lokern 20 0.000 0.200 0.000 0.650 North Lokern 20 0.125 0.025 0.000 0.700 Midway 10 0.000 0.150 0.150 0.700 Derby Acres 20 0.000 0.025 0.000 0.950 Buttonwillow 20 0.000 0.125 0.000 0.675 Northwest Belridge 11 0.000 0.045 0.000 0.864 Ds30 233 235 246 252 Lokern 20 0.000 0.100 0.000 0.150 North Lokern 20 0.100 0.000 0.000 0.200 Midway 10 0.400 0.000 0.050 0.000 Derby Acres 20 0.425 0.000 0.000 0.000 Buttonwillow 20 0.075 0.125 0.000 0.275 Northwest Belridge 11 0.045 0.000 0.000 0.136 Di5 184 190 193 Lokern 20 0.000 0.025 0.975 North Lokern 20 0.150 0.050 0.800 Midway 10 0.150 0.150 0.700 Derby Acres 19 0.000 0.132 0.868 Buttonwillow 20 0.000 0.150 0.850 Northwest Belridge 11 0.000 0.000 1.000 Di12E 210 220 224 227 Lokern 20 0.000 0.300 0.125 0.025 North Lokern 20 0.050 0.500 0.100 0.000 Midway 10 0.050 0.200 0.500 0.000 Derby Acres 19 0.150 0.675 0.025 0.000 Buttonwillow 20 0.025 0.250 0.225 0.000 Northwest Belridge 11 0.000 0.364 0.045 0.091 Group Allele size (bp) Ds1 213 215 217 219 221 Lokern 0.025 0.050 0.200 0.000 0.050 North Lokern 0.000 0.000 0.075 0.000 0.025 Midway 0.000 0.300 0.000 0.000 0.000 Derby Acres 0.000 0.025 0.000 0.025 0.000 Buttonwillow 0.050 0.150 0.025 0.000 0.075 Northwest Belridge 0.091 0.000 0.227 0.000 0.000 Ds3 Lokern North Lokern Midway Derby Acres Buttonwillow Northwest Belridge Ds19 131 139 145 Lokern 0.000 0.286 0.429 Derby Acres 0.000 0.000 0.000 Buttonwillow 0.214 0.000 0.000 Northwest Belridge 0.000 0.000 0.000 Ds28 216 222 226 Lokern 0.100 0.050 0.000 North Lokern 0.125 0.000 0.025 Midway 0.000 0.000 0.000 Derby Acres 0.000 0.000 0.025 Buttonwillow 0.125 0.075 0.000 Northwest Belridge 0.091 0.000 0.000 Ds30 254 256 258 261 263 Lokern 0.075 0.000 0.150 0.000 0.275 North Lokern 0.050 0.075 0.000 0.000 0.325 Midway 0.000 0.000 0.150 0.050 0.050 Derby Acres 0.000 0.000 0.000 0.375 0.000 Buttonwillow 0.050 0.050 0.000 0.175 0.100 Northwest Belridge 0.273 0.000 0.091 0.000 0.091 Di5 Lokern North Lokern Midway Derby Acres Buttonwillow Northwest Belridge Di12E 233 237 Lokern 0.000 0.550 North Lokern 0.000 0.350 Midway 0.000 0.250 Derby Acres 0.000 0.150 Buttonwillow 0.075 0.425 Northwest Belridge 0.000 0.500 Group Allele size (bp) Ds1 223 227 229 231 Lokern 0.000 0.200 0.150 0.000 North Lokern 0.000 0.375 0.125 0.000 Midway 0.050 0.250 0.000 0.300 Derby Acres 0.100 0.700 0.000 0.025 Buttonwillow 0.000 0.175 0.175 0.000 Northwest Belridge 0.000 0.091 0.180 0.000 Ds3 Lokern North Lokern Midway Derby Acres Buttonwillow Northwest Belridge Ds19 Lokern Derby Acres Buttonwillow Northwest Belridge Ds28 Lokern North Lokern Midway Derby Acres Buttonwillow Northwest Belridge Ds30 265 267 269 271 283 Lokern 0.000 0.050 0.125 0.000 0.075 North Lokern 0.025 0.100 0.075 0.000 0.050 Midway 0.150 0.150 0.000 0.000 0.000 Derby Acres 0.150 0.000 0.025 0.025 0.000 Buttonwillow 0.000 0.000 0.025 0.000 0.125 Northwest Belridge 0.182 0.045 0.045 0.000 0.091 Di5 Lokern North Lokern Midway Derby Acres Buttonwillow Northwest Belridge Di12E Lokern North Lokern Midway Derby Acres Buttonwillow Northwest Belridge Table 2.--Descriptive statistics for six populations across seven loci, including the mean sample size (n), proportion of polymorhphic loci (P), number of alleles ([N.sub.A]), number of effective alleles ([N.sub.c]), information index (I), observed heterozygosity ([H.sub.o]), expected heterozygosity ([H.sub.E]), the mean number of private alleles, and the fixation (F) indices of the giant kangaroo rat (Dipodomys ingens) from the southern San Joaquin Valley, California Population n P [N.sub.a] [N.sub.e] I Lokem 18.14 1.00 4.71 3.26 1.10 Midway 8.57 0.86 3.57 2.30 0.92 Derby Acres 17.27 1.00 3.71 1.95 0.78 Buttonwillow 18.14 0.86 4.86 3.57 1.16 Northwest Belridge 9.57 0.71 4.14 2.88 0.88 North Lokern 17.14 0.86 4.14 2.36 0.89 Total 14.81 0.88 4.19 2.72 0.96 [H.sub.o] Mean # of Population (SE) [H.sub.E] private alleles F Lokem 0.46(0.15) 0.54 0.30 0.16 Midway 0.51(0.13) 0.48 0.18 -0.06 Derby Acres 0.38(0.11) 0.44 0.20 0.10 Buttonwillow 0.50(0.13) 0.56 0.18 0.08 Northwest Belridge 0.44(0.15) 0.42 0.00 -0.06 North Lokern 0.50(0.14) 0.43 0.14 -0.15 Total 0.47(0.05) 0.48 0.02 TABLE 3.--Population comparisons of six populations of the giant kangaroo rat (Dipodomys ingens) in the southern San Joaquin Valley using an analysis of molecular variance (AMOVA) % df SS MS variation [PHI] P Among populations 5 84.30 16.86 18 Within populations 95 340.20 3.58 82 0.183 <0.001 Total 100 424.50 TABLE 4.--Estimates of F-statistics across six populations of the giant kangaroo rat (Dipodomys ingens) in the southern San Joaquin Valley by locus [F.sub.IS]: standard genetic variation within populations; [F.sub.ST] standard genetic variation between populations; [F.sub.IT]: to partition genetic variation Locus [F.sub.IS] [F.sub.ST] [F.sub.IT] Dsl -0.013 0.099 ** 0.087 * Ds3 0.138 * 0.256 ** 0.359 ** Dsl9 0.930 ** 0.085 ** 0.936 ** Ds28 0.143 * 0.043 ** 0.180 ** Ds30 -0.057 0.110 ** 0.060 * Di5 -0.078 0.054 ** -0.020 Di12E -0.146 0.100 ** -0.031 Total 0.056 ** 0.106 ** 0.156 ** Significant difference at * P < 0.05; ** P < 0.01 Table 5.--Pairwise values of [F.sub.ST], [[PHI].sub.PT], and Nei's genetic distance for six populations of the giant kangaroo rat (Dipodomys ingens) in the southern San Joaquin Valley, California Pairwise Pairwise Nei's [F.sub.ST] [[PHI].sub.PT] pairwise Populations value distance Lokern vs. Midway 0.100 * 0.169 ** 0.247 Lokern vs. Derby Acres 0.202 * 0.311 ** 0.443 Lokern vs. Buttonwillow 0.018 * 0.031 ** 0.121 Lokern vs. Northwest Belridge 0.018 0.031 0.247 Lokern vs. North Lokern 0.047 * 0.089 ** 0.119 Midway vs. Derby Acres 0.171 * 0.284 ** 0.344 Midway vs. Buttonwillow 0.074 * 0.128 ** 0.192 Midway vs. Northwest Belridge 0.107 * 0.193 ** 0.353 Midway vs. North Lokern 0.096 * 0.189 ** 0.175 Derby Acres vs. Buttonwillow 0.191 * 0.298 ** 0.387 Derby Acres vs. Northwest 0.170 * 0.277 ** 0.452 Belridge Derby Acres vs. North Lokern 0.170 * 0.296 ** 0.304 Buttonwillow vs. Northwest 0.043 * 0.074 ** 0.175 Belridge Buttonwillow vs. North Lokern 0.054 * 0.101 ** 0.121 Northwest Belridge vs. North 0.049 * 0.100 ** 0.229 Lokern Significant difference at * P < 0.05 with Bonferroni correction using GENEPOP; ** P <0.05 using GENALEX
|Printer friendly Cite/link Email Feedback|
|Author:||Blackhawk, Nicole C.; Germano, David J.; Smith, Paul T.|
|Publication:||The American Midland Naturalist|
|Date:||Apr 1, 2016|
|Previous Article:||Genetic diversity and population structure of the endemic disjunct species, helenium virginicum (Asteraceae).|
|Next Article:||Birth mass scaling in elk (Cervus elaphus).|