Population Genetics of an Imperiled Crayfish from the White River Drainage of Missouri, USA

Transcription

1 Freshwater Crayfish 16: , 2008 Copyright 2008 International Association of Astacology ISBN: print / online Population Genetics of an Imperiled Crayfish from the White River Drainage of Missouri, USA James W. F etzner Jr. 1, and robert J. distefano 2 1 Carnegie Museum of Natural History, Section of Invertebrate Zoology, 4400 Forbes Avenue, Pittsburgh, PA USA 2 Missouri Department of Conservation, Resource Science Center, 1110 South College Avenue, Columbia, MO USA Corresponding Author FetznerJ@CarnegieMNH.Org Abstract. The Williams crayfish, Orconectes (Procericambarus) williamsi, is a globally vulnerable and Missouri state imperiled crayfish known only from small tributaries in the upper White River drainage basin in southwestern Missouri and northern Arkansas. In this study, 24 sampling localities for O. williamsi were examined for levels of genetic variation within a 659 base pair region of the mitochondrial cytochrome oxidase I gene. Orconectes williamsi was found to be quite variable across its range, with a total of 53 distinct haplotypes being detected among the 326 sampled individuals. A nested clade phylogeographic analysis (NCPA) of O. williamsi populations resulted in four distinct haplotype networks that were quite divergent from one another. The majority of populations from the eastern portion of the Missouri range grouped into a single large network that was further divided into three distinct subgroups. The populations associated with the different networks detected by the NCPA were quite different from each other and should be considered evolutionary significant units (ESUs), as they are reciprocally monophyletic (i.e., show fixed haplotype differences) for their respective mtdna profiles. In addition, the three divergent population subgroups that make up the main network should each be considered an individual conservation management unit (MU). [Keywords. genetic variation; Nested Clade Phylogeographic Analysis; Orconectes williamsi; Orconectes meeki meeki; phylogeography; population genetics]. INTRODUCTION The Williams crayfish, Orconectes williamsi Fitzpatrick, was originally described from three localities in the headwaters of the White River in northwestern Arkansas (Fitzpatrick 1966). The species was later found by Pflieger (1987; 1996) in Missouri during his statewide crayfish survey, and was collected by him from nine localities in four southern Missouri counties (Barry, Christian, Stone and Taney)(Figure 1). Recent survey work by the Missouri Department of Conservation (MDC) indicates that this species occurs at several additional sites within the state. Orconectes williamsi has been designated as imperiled in Missouri and vulnerable globally by MDC (Missouri Natural Heritage Program 2008), and in 1996 the American Fisheries Society (AFS) Endangered Species Committee assigned it the status of special concern (Taylor et al. 1996). Recently, however, this same committee has re-evaluated the North American crayfish fauna (Taylor et al. 2007) and has assigned the Williams crayfish a status of currently stable, a change made in part based on field collections made for this and related studies (Westhoff et al. 2006). In addition, we are not currently aware of any imminent threats to this crayfish s existence in the White River drainage of Missouri. However, the construction of the 17,400 hectare Table Rock Reservoir in 1958 fragmented the known Missouri populations, and similar situations have been cause for concern with other rare stream organisms (Pflieger 1997; Mattingly and Galat 2002). Additionally, recent observations (DiStefano, personal observation) indicate that several streams in this river 131 drainage (e.g., Swan Creek and Woods Fork of Bull Creek) are suffering from unstable and shifting substrate and deposited fine sediments, presumably resulting from recent or current land use practices (Bayless and Vitello 2002). Because of its limited distribution, its imperiled state-level status, and the apparent degradation of some suitable habitat in parts of its range, it is reasonable to anticipate that biologists will be required to develop conservation management (or recovery) plans for O. williamsi in the future. Under this scenario, an array of baseline data about this species will be necessary for developing and implementing those plans. One important component of that baseline data is an assessment of genetic variability both within and among known populations of this species to determine whether subpopulations exist and whether these should be targeted for conservation efforts. Baseline data for many rare or threatened aquatic organisms (Richter et al. 1997), such as salmonids and other fishes (e.g., Stockwell et al. 1998; Taylor et al. 2003; Hurt and Hedrick 2004) or even invertebrates (e.g., Wetzel et al. 2004; Dewalt et al. 2005), has aided in understanding population processes and has been extremely helpful in conserving species. Unfortunately, in many similar scenarios, species have become so rare that collection of genetic material is either difficult or discouraged due to the organism s rarity (e.g., Sinclair 2001). In order to avoid such problems, this study was undertaken to document present day genetic variation which can then serve as baseline data if conservation action is warranted at some point in the future.

2 Freshwater CrayFish 132 A Vol. 16 C B Figure 1. Map showing the previously published distribution of Orconectes williamsi. A, Map showing the regional detail relative to the eastern USA. B, Map showing the area of detail that encompases the species known distribution. C, Map depicting previously published sampling locations of the Williams crayfish (black dots) in Missouri and Arkansas prior to conducting this study (data taken from Fitzpatrick 1966 and Pflieger 1987; 1996). Figure 2. Map showing sampling locations for Orconectes williamsi ( ) and Orconectes meeki meeki ( ) specimens examined in this study. See Figure 1 inset for regional detail and map orientation.

3 2008 Fetzner and distefano PoPulation Genetics of the Williams crayfish 133 A comprehensive survey was recently completed which examined the distribution of O. williamsi in the upper White River drainage of Missouri, and documented several previously unknown populations (Westhoff et al. 2006). We chose to integrate the study of O. williamsi population genetics along with this initial distribution study. Our purpose was to collect genetic samples from every known locality of the species in order to assess levels of genetic variation within and among populations and to determine if unique population elements exist that should be protected into the future through managed conservation efforts. Specimens MATERIALS AND METHODS A total of 388 O. williamsi specimens were collected during June through August of the field seasons, from 24 different sampling sites located in the upper White River drainage of southwestern Missouri (Table 1, Figure 2). All specimens were collected by MDC staff in conjunction with their survey project for this same species. Unfortunately, some samples were degraded or not in sufficient quantities for analysis and thus only 326 of the specimens actually produced viable sequence data. Voucher specimens (Appendix 1) for 14 of the 24 O. williamsi and 1 Orconectes meeki meeki (Faxon) sampling locations were retained and have been deposited in the Carnegie Museum of Natural History (CMNH) crustacean collection. Field collections were attempted from 71 different stream segments, selected by a proportionally-stratified (by stream order) random approach, from a total of 223 possible segments. Additionally, all 9 sites previously reported as harboring O. williamsi (Pflieger 1996) were revisited. An attempt was also made, where possible, to collect 20 individuals from each site for genetic analyses in order to obtain robust estimates of haplotype frequencies and levels of within population variation. After specimens were collected, muscle tissue samples (either abdominal muscle or chela muscle) were placed into labeled 2 ml screw-top sample vials containing 900 µl of cell lysis buffer (10 mm Tris, 100 mm EDTA, 20% SDS, ph 8.0) and 9 µl Proteinase K (10 mg ml -1 ). Samples were then shipped at ambient temperatures to the CMNH anywhere from one week to one month after collections were initially made in order to continue the DNA extraction process. Additionally, six populations of O. m. meeki (79 specimens), two populations of Orconectes luteus (Creaser) (20 specimens) and five specimens from a single population of Orconectes virilis (Hagen), were also collected from the same general geographic vicinity to serve as comparative material for estimates of genetic variation both within and among species. Samples of Procambarus pictus (Hobbs) (N = 5) and Procambarus seminolae Hobbs (N = 2) were also included as outgroups (Table 1). DNA Extraction, Amplification and Sequencing DNA was extracted using a high salt precipitation method previously described (Crandall et al. 1999). In brief, after receiving the samples at the laboratory they were allowed to incubate overnight at 58 C. The extraction continued the following day after cooling the samples to room temperature and adding 4 µl of RNase A (20 mg ml -1 ). The samples were incubated at 37 C for one hour, Figure 3. Isolation by distance analyses (Mantel test) for Orconectes williamsi populations. Pairwise F ST distances (y-axis) are plotted against pairwise geographical ( = great circle) distances (x-axis) for all 24 populations. after which 300 µl of 7.5 M ammonium acetate was added and the samples were then mixed and placed on ice for 15 minutes. The samples were then centrifuged at high speed for 5 minutes and the supernatant was added to 900 µl of isopropanol. Samples were then inverted several times to precipitate the DNA and placed at -20 C overnight. The next day, the samples were centrifuged and the pellet was washed with 500 µl of 70% ethanol. After drying the pellet completely, 50 to 200 µl of TLE buffer (10 mm Tris, 0.1 mm EDTA, ph 8.0) was added to resuspend the DNA. The quantity of DNA was then checked using a spectrophotometer and dilutions were made to give a final concentration of 100 ng µl -1 for use in PCR. Polymerase chain reaction (PCR) amplifications were conducted in a total volume of 25 µl using the universal primers of Folmer et al. (1994), which amplify a 659 base pair (bp) segment from the 5-prime end of the cytochrome c oxidase I (COI) gene. Primers and their sequences are LCO1490 5' GGTCAACAAATCATAAAGATATTG 3' and HCO2198 5' TAAACTTCAGGGTGACCAAAAAATCA 3'. Each reaction contained the following components: 1x PCR buffer, 3 mm magnesium chloride, 1.25 mm each dntp, 1 µm each primer Figure 4. Results of principal coordinates analysis of haplotype variation in Orconectes williamsi. Numbers next to dots indicate population numbers as listed in Table 1. The first 3 axes accounted for 51.4% of the variation.

4 134 Freshwater CrayFish Vol. 16 Table 1. Locality data for populations of O. williamsi and outgroups that were examined in this study. N is the number of sampled individuals. Haplotype and nucleotide diversity values for each population were generated by Arlequin. The haplotype column lists the haplotype number (see Table 2) and its relative frequency in the population, in parentheses. The Clade column indicates the population s primary clade membership in the haplotype network (see Figure 5). No. Species Population County State N Lat Lon Nucleotide Diversity Haplotype Diversity Haplotype (Abs. freq) Clade 1 Orconectes williamsi Roaring River Barry MO (9), 53(2), 54(1) 4 2 Orconectes williamsi Rock Creek Barry MO (13), 48(1), 49(1), 50(1), 3 51(1) 3 Orconectes williamsi Bull Creek Christian MO (16), 14(1), 16(2) 1a 4 Orconectes williamsi Elkhorn Creek Christian MO (3), 15(1) 1a 5 Orconectes williamsi Guffy Creek Christian MO (2) 1b 6 Orconectes williamsi Lost Creek Christian MO (5), 20(2) 1a 7 Orconectes williamsi Rantz Cave Christian MO (2) 1a 8 Orconectes williamsi Woods Fork of Bull Cr. Christian MO (5), 12(2), 13(1) 1a 9 Orconectes williamsi Goff Creek 1 Stone MO (12), 3(2), 4(2) 1a 10 Orconectes williamsi Goff Creek 2 Stone MO (14), 3(3), 4(2) 1a 11 Orconectes williamsi Little Indian Creek 1 Stone MO (3), 41(9), 43(1), 44(3), 2 45(1), 46(1) 12 Orconectes williamsi Little Indian Creek 2 Stone MO (5), 41(1), 42(1), 44(1) 2 13 Orconectes williamsi West Fork Bear Creek Stone MO (2), 6(14), 7(1), 8(1), 10(1) 1a 14 Orconectes williamsi West Fork Roark Creek Stone MO (5), 25(1), 29(9), 30(1), 33(1) 1b 15 Orconectes williamsi Cane Creek Taney MO (19), 39(1) 1c 16 Orconectes williamsi Dry Branch Bear Creek Taney MO (7), 5(1), 6(1), 9(3), 1a 17 Orconectes williamsi East Fork Roark Creek Taney MO (8), 29(10), 31(1) 1b 18 Orconectes williamsi Emory Creek Taney MO (16), 11(2), 17(1) 1a 19 Orconectes williamsi Fall Creek Taney MO (9), 35(4), 36(1), 37(1) 1b 20 Orconectes williamsi Gray Branch Taney MO (8) 1b 21 Orconectes williamsi Long Creek Taney MO (3) 1c 22 Orconectes williamsi North Emory Creek Taney MO (18), 15(1), 18(1) 1a 23 Orconectes williamsi Roark Creek Taney MO (5), 29(12), 32(1) 1b 24 Orconectes williamsi Turkey Creek Taney MO (10), 21(1), 22(1), 23(1), 24(1), 27(3), 28(1), 29(1) 1b 25 Orconectes meeki meeki Little Indian Creek 1 Stone MO (2) 26 Orconectes meeki meeki Little Indian Creek 2 Stone MO (1) 27 Orconectes meeki meeki Rock Creek Barry MO (8), 63(2), 64(1), 65(3), 66(2), 67(2), 68(1), 69(1) 28 Orconectes meeki meeki Rock House Creek Barry MO (5), 57(13), 58(2) 29 Orconectes meeki meeki South Ance (=Aunts) Stone MO (13), 60(6), 61(1) Creek 30 Orconectes meeki meeki Wooley Creek Stone MO (7), 56(9) Outgroups Orconectes luteus Fassnight Creek Greene MO (10) 32 Orconectes luteus South Creek Greene MO (10) 33 Orconectes virilis East Prong Little Creek Ozark MO (1), 72(2), 73(2) 34 Procambarus pictus South Fork Black Creek Clay FL (3), 75(1),76(1) 35 Procambarus seminolae Mud Creek Lowndes GA (2) TOTAL 432

5 2008 Fetzner and distefano PoPulation Genetics of the Williams crayfish 135 Table 2. A, The number of O. williamsi individuals containing each detected haplotype and the distribution of those haplotypes among the sampled populations. Note that there is no haplotype 36. B, Haplotypes for outgroup taxa. Ome = Orconectes meeki meeki, Olu = Orconectes luteus, Ovi = Orconectes virilis, Ppi = Procambarus pictus, Pse = Procambarus seminolae. A. No. Population N Roaring River Rock Creek Bull Creek Elkhorn Creek Guffy Creek Lost Creek Rantz Cave Wood s Fork of Bull Creek Goff Creek Goff Creek Little Indian Creek Little Indian Creek West Fork Bear Creek West Fork Roark Creek Cane Creek Dry Branch Bear Creek East Fork Roark Creek Emory Creek Fall Creek Gray Branch Long Creek North Emory Creek Roark Creek Turkey Creek TOTALS B. Haplotypes (Abs. freq) No. Population N Outgroups* 25 Little Indian Creek 1 (Ome) Little Indian Creek 2 (Ome) Rock Creek (Ome) Rock House Creek (Ome) South Ance (=Aunta) Creek (Ome) Wooley Creek (Ome) Fassnight Creek (Olu) South Creek (Olu) East Fork Little Creek (Ovi) South Fork Black Creek (Ppi) Mud Creek (Pse) 2 2 TOTALS

6 136 Freshwater CrayFish Vol. 16 Figure 5. Haplotype network for Orconectes williamsi. Numbers inside circles and boxes represent the haplotype numbers as in Tables 2 and 5. Numbers along branches indicate the base pair positions (see Table 3) where the mutation occurred on that branch, and an asterisk (*) indicates an amino acid substitution occurred. Boxes indicate the inferred root of each network (Castello and Templeton 1994). Small solid black circles along the branches are inferred intermediate haplotypes that were not detected in the sample. and 0.6 units of Taq DNA polymerase (Promega Corp., Madison, Wisconsin, USA) and 250 ng of sample DNA. The PCR cycling conditions included an initial denaturation step of 2 minutes at 96 C followed by 45 cycles at 95 C for 20 seconds, 52 C for 25 seconds, and 72 C for 2 minutes. A final extension at 72 C for 7 minutes was then conducted followed by a hold at 4 C until the samples could be processed further. The PCR products were then run on a 1% agarose gel and the bands excised for sequencing. Before sequencing, the amplified DNA was purified from the gel slices using the GeneClean III kit (QBiogene, Solon, Ohio, USA) and concentrated into 10 µl of TLE buffer (see above). Sequencing reactions were conducted in a total volume of 10 µl using the DTCS Quickstart Kit from Beckman-Coulter (Fullerton, California, USA). Each (quarter) reaction contained 2 µl of DTCS ready reaction mix, 1.0 µl of the concentrated GeneClean DNA, 2 µl of primer (10 µm), and 5 µl ultrapure water. Sequencing primers were the same as those used in the initial PCR reaction. The cycle sequencing protocol followed the manufacturer s recommendations with the exception that 40 cycles were used rather than 30. After amplification, the sequencing products were cleaned using Sephadex G 50 fine (Sigma-Aldrich, St. Louis, Missouri, USA) columns, dried down, and resuspended in 35 µl formamide before running on a Beckman CEQ 2000XL automated capillary DNA sequencer. The sequences obtained from the automated sequencer were initially corrected and aligned using the program Sequencher ver. 4.5 (GeneCodes Corp., Ann Arbor, Michigan, USA) and adjusted, as appropriate, by eye. Nested Clade Phylogeographic Analysis (NCPA) A haplotype network was constructed using the program TCS v1.18 (Clement et al. 2000). This program first takes population sequence data and collapses the data set down to where only distinct haplotypes remain, but also retains information on the frequencies of each haplotype. The program then tries to connect each unique haplotype into a growing network by using information on the number of mutational differences detected between sequences. However, sometimes not all haplotypes can be connected unambiguously into a single network because the maximum number of substitutions to establish a parsimonious connection has been exceeded at the 95% confidence level. This maximum number of substitutions is directly related to the length of the analyzed sequences. Once a network has been generated, specific nesting procedures are used to assign haplotypes into clades following the methods of Templeton (1998), Templeton

7 2008 Fetzner and distefano PoPulation Genetics of the Williams crayfish 137 Table 3. Polymorphic sites (haplotypes) detected among the 24 populations of Orconectes williamsi for the COI gene. The # column indicates the haplotype number. Abs. Freq indicates the total number of individuals that exhibited that haplotype. The remaining columns indicate the nucleotide base pair position from the 5 end of the gene sequence examined. An asterisk (*) above the number indicates a non-synonymous (= an amino acid changing) substitution. A question mark in the table indicates an ambiguous or unresolved base while a dot. indicates a match to the base found in the sequence for haplotype #1. Note that there is no haplotype #36. * * * * * * * * * * * * * * * * Abs # Freq (68) T A T G A A A G C C T A G C T C A G T C G T A G C G C A A A C T C A A T G A C T G G A T G A A G C A T T T A A C A T A A A A C G A T C A A T A 2 (26) T (5) A T (4) T G (3) G (15) G G (1) G G C... 8 (1). G G G (3) G (1)... T A... G (2). G (2). G T (1) G (1) T (2) C (2)..... G (1) G 18 (1) C.. 19 (2) T (38) A T T..... A.... T G (1) A T G T..... A.... T G ????? 22 (1) A T T..... A.... T G C. 23 (1) A T T..... A. T.. T G (1) A T T..... A.... T G C.. 25 (1) A T T..... A.... T G T?????? 26 (2) G..... A T T..... A.... T G (3) C. A T T..... A.... T G (1) A T T..... A.... T G.... G (32) A T T..... A.... T G G (1) T... A T T..... A.... T G G (1) A T. T T..... A.... T G G (1) A T T..... A.... T G G. T.?????? 33 (1) G..... A T T..... A.... T G G (9) T.. A T T..... A.... T G (4) T.. A T G T..... A.... T G (1) T.. A T T..... A... A T G (22) G..... A.. T G A A T G T G C (1).... C. G..... A.. T G A A T G T G C (8) A... G. T C..... A... T. T. G. T..... A. T.... C T G. T.. C C C. G T G..... A (10) A.. C G. T C..... A... T. T. G. T..... A. T.... C T G. T.. C C C. G T G..... A (1) A.. C G. T C..... A... T. T G G. T..... A. T.... C T G. T.. C C C. G T G..... A (1) A.. C G. T C..... A... T T T. G. T..... A. T.... C T G. T.. C C C. G T G..... A...????? 44 (4) A... G. T C..... A... T. T. G. T..... A. T.... C T G. T.. C C C. G T G..... A A (1) A... G. T C..... A... T. T. G. T..... A. T A... C T G. T.. C C C. G T G..... A A (1) A... G. T C..... A... T. T. G. T. G... A. T.... C T G. T G. C C C. G T G.. G.. A. G.????? 47 (13) C. A A C... T.. G.... G.. A. T..... T G G T.. C C.. G T G C G... G C. C (1).. C C. A A C... T.. G.... G.. A. T..... T G G T.. C C.. G T G C G... G C. C (1) C. A A C... T.. G.... G.. A. T..... T G G T.. C C.. G T G C G... G C (1) C. A A C... T.. G.... G G. A. T..... T G G T.. C C.. G T G C G... G C.?????? 51 (1) C C. A C... T.. G.... G.. A. T..... T G G T.. C C.. G T G C G... G T. C (9) C A.... A T..... T A. G... T. G G T C.... A G T..... T G G T.. C C.. G T G C T (2) C A T..... T A. G... T. G G T C.... A G T..... T G G T.. C C.. G T G C ????? 54 (1) C A.... A T.... C T A. G... T. G G T C.... A G T..... T G G T.. C C.. G T G C T....

8 138 Freshwater CrayFish Vol. 16 Figure 6. Map showing the different clades recovered by the nested clade phylogeographic analysis (NCPA) of Orconectes williamsi populations. Large numbers indicate the clade assignment for each shaded area and are the same as those shown in Figures 4 and 5. See Figure 1 inset for regional detail and for map orientation. and Sing (1993) and Crandall and Templeton (1996). Network root probabilities, whereby each haplotype is given a probability of being the ancestral sequence which gave rise to other detected haplotypes in the network, were automatically calculated by the TCS program following the method of Castelloe and Templeton (1994). The program GEODIS v2.2 (Posada et al. 2000) was then used to test for any association between the observed genetic variation (i.e., the haplotypes) and its geographic distribution. Using this information the NCPA is able to distinguish between population history events (e.g., past fragmentation), and elements of population structure (e.g., gene flow, isolation by distance) (Templeton et al. 1995; Templeton 1998). These population processes are easily inferred using the manual NCPA inference key of Templeton (1998, 2004), or the automated system of Panchal and Beaumont (2007). Population Differentiation The program DNASP v (Rozas et al. 2003) was used to estimate levels of gene flow and genetic differentiation among populations. Gene flow estimates for haplotypes utilized the G ST measure of Nei (1973). For sequence data, estimates of gene flow and migration rates (Nm) were obtained using a variety of different measures including Fst (Hudson et al. 1992), N ST (Lynch and Crease 1990), and Gamma ST (Nei 1982). Estimates of Nm were based on Wright s Island model (Wright 1951). For genetic differentiation, the Snn statistic of Hudson (2000) was also calculated. Estimates of nucleotide and haplotype diversity within populations were obtained from the program Arlequin v2001 (Schneider et al. 2000). Estimates of population pairwise F ST were also obtained in order to conduct an isolation by distance analysis. The program GenAlEx v6.0 (Peakall and Smouse 2001) was used to conduct a Mantel test in order to test for effects of isolation by distance. This test looks for a correlation between the geographic distance among populations and their respective genetic distances. For this test, Global Positioning System (GPS) coordinates were determined for each population using Topo USA v4.0 (DeLorme, Yarmouth, Maine, USA). These coordinates were then entered into an Excel spread sheet that was used to calculate a matrix of pairwise great circle distances between populations (in kilometers) (a blank copy of this spreadsheet is available from A principal coordinates analysis was also conducted using GenAlEx using population pairwise F ST values.

9 2008 Fetzner and distefano PoPulation Genetics of the Williams crayfish 139 Figure 7. Results from the GeoDis program for Orconectes williamsi network 1. Numbers in blue (with superscript L ) indicate significantly large distances while those in red (with superscript S ) indicate significantly small values. Only those clades showing a significant value were run through the NCPA inference key. Gray boxes indicate interior clades (as opposed to tip clades). Dc = clade distance, Dn = nested clade distance, I-T = interior versus tip clades. RGF-IBD = Restricted gene flow with isolation by distance, RGF/Disp w/ LDD = Restricted gene flow/ dispersal with some long distance dispersal.

10 140 Freshwater CrayFish Vol. 16 Table 4. Geographic distances in kilometers (below diagonal) and genetic distances as pairwise F ST (above diagonal) among populations of Orconectes williamsi. Overall F ST estimated among all sampled O. williamsi populations by AMOVA was F ST = (P = ). # Population Roaring River Rock Creek Bull Creek Elkhorn Creek Guffy Creek Lost Creek Rantz Cave Wood s Fork of Bull Cr Goff Creek Goff Creek Little Indian Creek Little Indian Creek West Fork Bear Creek West Fork Roark Creek Cane Creek Dry Branch Bear Creek East Fork Roark Creek Emory Creek Fall Creek Gray Branch Long Creek North Emory Creek Roark Creek Turkey Creek

11 2008 Fetzner and distefano PoPulation Genetics of the Williams crayfish 141 Table 5. Average percent (%) sequence divergence estimates (p-distances) in bold with minimum and maximum values in parentheses. A, among clades for network 1 [see Figure 6 for the groups contained in each clade] and B, among networks. Values displayed within the shaded diagonals are the average within clade (or network) sequence divergence estimates. A. Clade 1A Clade 1B Clade 1C Clade 1A 0.41 ( ) Clade 1B 1.31 ( ) 0.36 ( ) Clade 1C 1.93 ( ) 1.91 ( ) 0.15 ( ) B. Network 1 Network 2 Network 3 Network 5 Network ( ) Network ( ) 0.47 ( ) Network ( ) 3.18 ( ) 0.36 ( ) Network ( ) 2.74 ( ) 2.85 ( ) 0.21 ( ) Phylogenetic Analysis The best fit model of nucleotide substitution was selected from a total of 56 different models using the hierarchical likelihood ratio test method of Huelsenbeck and Crandall (1997) as implemented in the program MODELTEST ver 3.7 (Posada and Crandall 1998). The best fit model was then chosen using the Akaike Information Criterion (AIC). A haplotype phylogeny was then generated with PAUP* v4.0b10 (Swofford 2003) using the minimum evolution optimality criterion (Felsenstein 1981) with pairwise distances generated according to the model parameters obtained from the best-fit substitution model chosen by MODELTEST. An heuristic search was conducted using the neighbor-joining method and branch swapping was done using tree-bisection-reconnection (TBR). Confidence in the nodes of the phylogeny was assessed using the bootstrap method (Felsenstein 1985) with 100 pseudoreplicates. Sequence Variation RESULTS A total of 436 specimens were sequenced for the 659 bp region of the COI gene. In total, 76 different haplotypes were recovered for all the species examined (Table 2). Across the entire dataset, 175 nucleotide sites were found to be polymorphic and of these 156 were parsimony informative. The breakdown of haplotypes per species were as follows: O. williamsi, 53 haplotypes; O. meeki meeki, 15 haplotypes; O. luteus, one haplotype; O. virilis, three haplotypes; P. pictus, three haplotypes; P. seminolae, one haplotype. Overall, 71 variable sites were detected among the 326 O. williamsi individuals sampled (Table 3). Of these 71 sites, 16 were non-synonymous changes that resulted in amino acid substitutions. For O. meeki meeki, there were a total of 11 polymorphic sites detected among the 79 individuals sampled for this species, of which three resulted in amino acid changes. Three haplotypes were also recovered for both O. virilis and P. pictus and these haplotypes resulted in each case from only 2 mutational events. Within Population Variation For O. williamsi, nucleotide diversity estimates within populations ranged from a low of (= no variation) to a high of (Lost Creek population). Haplotype diversity within populations of O. williamsi ranged from to Values of nucleotide and haplotype diversity for O. williamsi were comparable to the values estimated for the O. meeki meeki and O. virilis populations also examined in this study (Table 1). Among Population Variation Sequence divergences among O. williamsi haplotypes ranged from a low of 0.15% to a high of 4.55% (average 2.18%) (Table 4). In contrast, divergences for O. meeki meeki ranged from a low of 0.15% to a high of 0.91% (average 0.43%). Divergence estimates between O. williamsi to the included outgroup taxa ranged from 9% to 14%. Variation in DNA sequences (haplotypes) was seen among populations, with most populations containing unique haplotypes. There was a clear correlation between the presence of a particular haplotype and its geographical distribution. Based on this pattern, O. williamsi populations were easily grouped into four major clades. One clade contained all of the populations collected east of Table Rock Reservoir, but this clade was divided into three subclades. The remaining three major clades were each represented by the three remaining populations sampled from tributaries to the south and west of Table Rock Reservoir (See Figure 6).

12 142 Freshwater CrayFish Vol. 16 Figure 8. Minimum evolution tree showing relationships among the 76 haplotypes detected in this study. Numbers at the nodes indicate bootstrap values for 100 pseudoreplicates. Numbers to the right of the tree for Orconectes williamsi designate network and clade membership from the NCPA analyses. Analysis of molecular variance (AMOVA) among the different sub-clades of network one indicated that 84.3% of the genetic variation detected was attributable to among groups (A g ) (clades), whereas 8.9% was attributable to among populations within groups (A p ) and only 6.8% to within populations (W p ). The F ST value calculated using the COI sequence data for O. williamsi was AMOVA results among the four different O. williamsi networks were slightly different with an increase in the variation explained by among populations within groups. Values estimated were A g = 76.2%, A p = 21.1% and W p = 2.7%. The overall F ST calculated for all networks was For O. meeki meeki, AMOVA results were as follows: A p = 64.8 and W p = 35.2 with F ST = Overall summary statistics for gene flow and genetic differentiation were as follows. The statistic of Hudson (2000) was Snn = Estimates of population subdivision and migration rates from sequences included Gamma ST = (Nm = 0.03), N ST = (Nm = 0.03) and F ST = (Nm = 0.03). These results indicate that there is a very low level of gene flow among these populations. Gene flow was also calculated from haplotypes, where G ST = (Nm = 0.49). Results of the Mantel test showed a moderate correlation between geographic and genetic distances (r = 0.36, P = 0.001) and can be seen in Figure 3. Geographic and genetic distances used for this test are shown in Table 4. Mantel test results for O. meeki meeki (graph not shown) had a similar correlation but was not significant (r = 0.326, P = 0.130). An analysis using principal coordinates analysis (PCA) was able to separate out the major O. williamsi population groups (see Figure 4). Nested Clade Phylogeographic Analysis For this data set, the maximum number of mutational steps allowed for joining a haplotype to a network was 12 steps. Beyond this upper limit, parsimonious connections are difficult to infer due to the effects of multiple substitutions. In order to connect all O. williamsi haplotypes into a single network, 16 steps would be required, which is beyond the 95% parsimony connection limit. Therefore, the analysis of O. williamsi populations resulted in four separate networks (Figure 5) each of which was then analyzed separately in the NCPA. These different networks were strongly correlated with geography (Figure 6). It is interesting to note that network one contains many missing intermediate haplotypes (haplotypes inferred to be present, but that were not sampled) between the three major subgroups in the network. This pattern suggests that these populations have been

13 2008 Fetzner and distefano PoPulation Genetics of the Williams crayfish 143 diverging for quite some time, as it would take a long time for different mutations to accumulate and reach fixation in different populations. For O. williamsi network one, there were 12 possible nested clades that could be tested for a geographic association of haplotypes, however, only six of these (Clades 1-1, 1-6, 2-1, 2-2, 3-1, and 4-1 (= total cladogram)) showed significant values and could be tested further (Figure 7). At the level of haplotypes, (Clades 1-1, 1-6) the NCPA inferred restricted gene flow with isolation by distance and restricted gene flow/dispersal with some long distance dispersal, respectively, for these clades. At all higher clades the NCPA inferred allopatric fragmentation. For network two, there were a total of three testable nested clades. However, no significant geographic association was found for any of these, suggesting panmixia in the Little Indian Creek population. Additionally, the analysis of both networks three and four could not progress any further because a minimum of two populations and two haplotypes are required in order to test for an association, and only a single population is represented in both of these networks. All haplotypes detected for O. m. meeki were grouped into a single haplotype network (data not shown). With the exception of haplotype 64, all of the haplotypes differed from one another by only a single mutational event, suggesting that these populations are closely related or only recently diverged. This is in stark contrast to the results found for O. williamsi. Phylogenetic Analyses The nucleotide substitution model selected by MODELTEST, using the Akaike Information Criterion (AIC), for these data turned out to be a special case of the general time reversible model (GTR+I+Γ). Model parameters included unequal base frequencies (π A = , π C = , π T = , π G = ), Ti/Tv ratio = , proportion of invariable sites (I) = and the gamma distribution shape parameter (Γ) = A haplotype phylogeny was then generated in PAUP* using the distance optimality criterion with maximum-likelihood distance parameters set to those listed above. An heuristic search was then performed, and only a single tree was found with a likelihood score of -lnl = (Figure 8). The tree recovered each species as a monophyletic group, but divergences (branch lengths) among the O. williamsi haplotypes are clearly much larger in comparison with those of the other species included in the study. There was a clear separation between O. williamsi populations collected east of Table Rock Reservoir and those collected from south and west of the reservoir (Figure 5). The populations east of Table Rock Reservoir also showed some clear differences based on geographic location (Figure 6), and these groups seem to represent some of the major White River tributaries in the region. Estimates of sequence divergence (Table 5) demonstrate the distinctness of the different networks and clades. It seems clear that ancestral populations of O. williamsi have diverged from one another after invading different tributaries of the White River system and very little gene flow seems apparent between these different tributaries. Differentiation among populations of O. m. meeki seems less well defined than those found for O. williamsi, at least in the geographic groupings of haplotypes in the phylogenetic tree. Branch lengths were also smaller for this species. Population Subdivision DISCUSSION Our analysis of sequence variation in the mitochondrial COI gene clearly establishes that there is a substantial amount of genetic differentiation among the various populations of O. williamsi, especially among populations from different White River subdrainages. This result is consistent with data collected for other species of freshwater crayfish (Fetzner and Crandall 2003; Fetzner, unpublished data.). Typically, genetic variation in crayfish is low within drainages, where one or a few haplotypes tend to predominate. However, this pattern does not typically hold for comparisons made among different drainages since there is very little and often no overlap in mtdna haplotypes at this geographic scale. This suggests that at least female dispersal rates are very low (a nuclear DNA marker would be needed to examine male dispersal patterns), and the exchange of individuals among different drainages appears to be a very rare event. This fact needs to be seriously considered when managing imperiled populations of freshwater crayfish. For example, allowing the use of crayfish as bait can cause serious problems if fishermen transfer crayfish from one place to another via so called bait bucket introductions (Ludwig and Leitch 1996; Simon 2002). Aside from the act of introducing non-native species of crayfish, which is a serious problem in-and-of-itself (Lodge 1993; Lodge et al. 2000), transferring crayfish from different drainages might result in negative impacts on species reproduction if adverse gene interactions develop caused by the mixing of divergent gene pools (similar to outbreeding depression), especially if the genes in question are adapted to local environments. Other scenarios and situations could also require knowledge about the genetic structure of crayfish populations (for example, aquaculture applications), but are beyond the scope of this paper. Implications for Conservation One of the major impediments to conserving rare and threatened species is often a complete lack of appropriate data to address specific conservation questions. Gathering such data is often a necessity before managers can take appropriate action to conserve rare species. A lack of available data can often hamper decision-making abilities and can lead to unfocused or misdirected species conservation efforts. Clearly, placing information relating to a species long-term sustainability into the hands of managers would be ideal. To this end, this study has gathered extensive population-level genetic data of an imperiled species of crayfish where very little data were previously available. A major goal of this study was to determine the existence and geographic distributions of any unique population groups. Results indicate that there are indeed some unique population elements within the known distribution of this species in Missouri. The Roaring River, Rock Creek, Little Indian Creek, and eastern populations are very distinct from one another (approaching 4.5% sequence divergence) and could be considered separate evolutionary significant units (ESUs) as defined by Moritz

14 144 Freshwater CrayFish Vol. 16 (1994). Populations from east of Table Rock Reservoir should also be conserved, probably by designating the three sub-clades (1A, 1B and 1C; Figure 4) as separate management units (MUs). This will permit the maximum amount of genetic diversity to be retained and allow the species to adapt over evolutionary time. Given the relatively low abundance and restricted distribution of this species it seems prudent that managers should start protecting these populations now that distribution and genetic studies have been completed. CONCLUSIONS While all known Missouri populations have been included in this study, there is still a portion of the species distribution that remains, as yet, un-sampled. At some point, genetic data from the southern part of the species range in Arkansas, especially from the type locality, should be examined in order to give the Missouri populations context. Data from nuclear loci (i.e., microsatellites) may also be useful to examine in future studies of this species. Microsatellites are well suited to studies at a variety of taxonomic levels, such as determining gender, answering questions of relatedness and parentage, generating information on the genetic structure of populations, as well as defining relationships among species. Such analyses would also allow for the estimation of migration rates in males (i.e., the effective number of migrants, or in other terms, those migrants that successfully mate after a migration event). Such data are not available for males since the data presented in this paper are based on mitochondrial DNA (mtdna), which is only passed down through maternal lines. It is obvious that female crayfish do not tend to disperse very far from natal areas, based on the patterns of mtdna variation seen in this and other studies (Fetzner & Crandall 2003, Fetzner unpublished data). ACKNOWLEDGMENTS We would like to thank the following MDC staff for their efforts in collecting specimens for this project: Paul Horner, Jacob Westhoff, Jen Guyot, Tom Boersig, Shawna Herleth-King, Dave Combs, Eric Rahm, Sabrina Griffith, John Motsinger, and Mary Jo Griffith. Amy Salveter (USFWS) also aided in collections. We thank Charles Scott and Amy Salveter (USFWS) for help with project funding. Chris Taylor (Illinois Natural History Survey) provided taxonomic verifications. We thank two anonymous reviewers who provided helpful comments and suggestions on an earlier version of this MS. LITERATURE CITED bayless m and Vitello c (2002). White River Watershed Inventory and Assessment. Missouri Department of Conservation, Springfield, Missouri, USA. castelloe J and templeton ar (1994). Root probabilities for intraspecific gene trees under neutral coalescent theory. Molecular Phylogenetics and Evolution 3(2): clement m, Posada d and crandall Ka (2000). 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