Uta stansburiana) that is found in habitats with both dark (lava) and light colored (granite) substrates. We conducted a limited experiment for adult phenotypic plasticity in laboratory conditions. We recorded both substrate and lizard color patterns in the field to determine whether lizards tended to match their substrate. Finally we examined genetic variation in a gene (melanocortin 1 receptor) that has been shown to affect lizard color in other species and in a presumably neutral gene . Populations were sampled in the immediate area of the lava flows as well as from a more distant site to examine the role of population structure. Our captive Uta did not change color to match their background. We show that side-blotched lizards tend to match the substrate on which it was caught in the field and that variation in the melanocortin 1 receptor gene does not correlate well with color pattern in this population. Perhaps the most remarkable result is that this population of side-blotched lizards shows extremely high levels of variation at both genetic markers, in the sense of allele numbers, with relatively low levels of between-allele sequence variation. Genetic variation across this small region was as great or greater than that seen in samples of pelagic fish species collected worldwide. Statistical analysis of genetic variation suggests rapid population expansion may be responsible for the high levels of variation.Recently, studies of adaptive color variation have become popular as models for examining the genetics of natural selection. We examined color pattern polymorphism and genetic variation in a population of side-blotched lizards ( Recently there has been increased focus on the genetic basis of color variation in animals because of the potential for color to be influenced by natural selection for background matching, thermoregulation, and sexual selection, e.g. Uta stansburiana) that reside in the Cima Volcanic Field in San Bernardino County, California , that is known to affect color pattern in other species of vertebrates We examined gene flow and demography by comparing mtDNA sequence among color morphs and among geographic localities. Finally, we conducted a preliminary examination of the genetic basis of the color polymorphism by surveying genetic variation in a candidate locus, melanocortin 1 receptor .We collected samples from two geographic sites: The Cima Volcanic Field and adjacent habitats (N = 110), and the Desert Studies Center (N = 17) . The Geological Color Chart was selected to measure dorsal color since lizards rely on substrate (rock) matching for predator avoidance ad libitum with a 12 hour light/dark schedule. Heat lamps were used during the day to maintain a temperature of 25–31°C and allow behavioral thermoregulation. We recorded dorsal colors with the Munsell Color Geological Rock-Color Chart every week for 52 weeks to measure any color change. Since color is thought to be affected by temperature in most lizard species  each lizard was measured at four temperature intervals: inactive (16.5–17.5°C), room (20 – 21°C), warm (25.5 – 28.5°C), and basking (30.5 – 32°C).Twelve individuals were collected and maintained in captivity to test whether dorsal color is a plastic trait in these populations. This sample consisted of 6 light, and 6 dark individuals. Lizards were reared in separate 10-gallon glass aquaria. Aquaria were supplied with white sand, a granite rock for basking, and a granite rock refuge. This substrate best matched an extreme light habitat, like that of the granite sands in the Mojave National Preserve. Lizards were fed crickets ND4) and cytochrome-B (cytb), and one nuclear locus, melanocortin 1 receptor (Mc1r) (Tables S2 and S3). We chose to use mitochondrial markers for investigation of population structure due to their high sensitivity to population subdivision because of female inheritance and effective haploidy. Mc1r was selected because it is a key switch in a signal transduction pathway in melanin-producing cells Mc1r polymorphisms have been found to be strongly associated with color differences in some desert squamates U. stansburiana color morphs.We extracted DNA from alcohol preserved tail tissue using a DNEASY extraction kit . Following extraction, the template DNA was amplified using Polymerase Chain Reaction (PCR) for two mitochondrial loci: NADH dehydrogenase subunit 4 , and Thermosensitive Alkaline Phosphatase . We sequenced purified product in both directions using Elim Biopharm’s DNA sequencing services, which use ABI 3730xl Sequencers . Sequencing primers (Table S4) were designed from initial sequence data. Individuals with poor sequence quality, unique occurrence of heterozygosity, or unique sequences were re-sequenced. For the autosomal U. stansburiana product by using the BlastN program at the NCBI website (http://blast.ncbi.nlm.nih.gov/Blast.cgi). We used MacClade 4.08a Sequence data were aligned and edited using the computer program Sequencher 3.1.1 . Sequences were confirmed to be Haplotype trees for both mitochondrial and nuclear sequence were created using MrBayes 3.1.2 Population genetic analyses were performed using Arlequin 3.5 r) h, For each defined group, we used pairwise mismatch distribution to test for recent population size expansion j, Analyses of molecular variance .U. stansburiana do experience plasticity due to temperature. Lizards tend to be darker when cool. These results are compatible with other studies of lizard coloration Our tests for phenotypic plasticity due to temperature suggest that Of the 12 captive lizards housed on light substrate, only 6 lived 15 weeks or longer. All six short-lived lizards and three of the six longer-lived lizards showed no changes in dorsal color. Three of the 6 lizards that lived 15 weeks or longer showed variation in dorsal color, but this variation did not appear adaptive . IndividUta stansburiana is probably not due to phenotypic plasticity.To summarize, only 4 of the 12 lizards changed color, and only one became slightly lighter and stayed lighter on the extremely light substrate. Overall, there is no trend towards a color change to match substrate, certainly not in time scales that would be relevant to predator avoidance. This suggests that cryptic coloration in this population of cytb and 754 basepairs of nd4, for a total of 1840 basepairs. We identified 65 haplotypes with 71 polymorphic sites for cytb, and 46 haplotypes with 56 polymorphic sites for nd4. Combining the two genes resulted in a total of 81 unique mitochondrial haplotypes. We sequenced 701 basepairs of the autosomal gene Mc1r with 42 polymorphic sites and 66 haplotypes estimated using the haplotypes considered most likely by PHASE. Haplotype phylogenies for Mc1r and the combined mtDNA data are shown in Sequencing of mitochondrial genes produced 1086 basepairs of .Cytb shows the most variation. Haplotype diversity is extremely high (h = .979) with 65 haplotypes. Sequence diversity is also high . The pairwise mismatch analysis of cytb shows a unimodal distribution  and Tajima’s D is significantly negative . ND4 also shows similarly high molecular diversity  as well as unimodal distribution of pairwise mismatches  and a negative Tajima’s D .Data for the entire sample of 127 individuals show a substantial amount of molecular variation  and 2.CND4 and cytb) shows diversity statistics that are consistent with the individual mitochondrial genes  as well as a unimodal distribution of pairwise mismatches  and significantly negative Tajima’s D . Maximum sequence divergence between any two mitochondrial haplotypes was only 1.25%. Most of the high diversity at the nucleotide level is due to the large number and fairly equal distribution of haplotypes.The combined mitochondrial dataset  with 66 haplotypes in 127 individuals. Sequence diversity is also high . Tests for mismatch distribution show a unimodal distribution  and Tajima’s D deviates from neutrality . Maximum sequence divergence between any two Mc1r haplotypes was 1.28%. All these values are consistent with those from the mitochondrial loci.As expected, the autosomal gene Mc1r diversity, PHASE could not assign haplotype identities to all genotypes with high probabilities, and it is possible that the diversity values were inflated because of misassigned haplotypes. In order to be conservative, we reanalyzed the data by examining all possible haplotype designations for each individual with multiple possible genotypes and preferentially choosing the genotype that minimized the probability that PHASE artificially created excess diversity. This was done by preferentially assigning genotypes that involved one of the two most common haplotypes  even if PHASE estimated higher probabilities for genotypes with rarer haplotypes. If none of the possible genotypes contained one of these common haplotypes, genotypes were chosen if they contained a haplotype that is homozygous in at least one other individual, and therefore is known to exist with certainty. Two individuals were dropped from the analysis because they could not be assigned genotypes under these criteria. Arlequin analysis shows that this reassignment of haplotypes did not significantly alter the diversity of the Mc1r sample. There were 71 unique sequences in the 125 individuals (h = 0.898) and nucleotide diversity values were similar to the PHASE predicted data set . Pairwise mismatch and Tajima’s D values were also similar . This suggests that the high diversity values for this locus are not due to PHASE artifacts.However, because of the high The high levels of diversity seen in the overall sample could potentially be due to restricted gene flow between the Desert Studies Center and the Lava collecting sites, or incipient reproductive isolation between light and dark lizards. Therefore we examine population structure based on geography or color in the next section.If selection for background matching has resulted in reproductive isolation between light and dark lizards, or if geographic barriers have isolated regions of our study area, population structure statistics may reveal differences among these groups even if there is no phylogenetic signal separating them. Given that mitochondrial genes do not undergo recombination and that separate analysis of the mitochondrial genes shows they have similar values for all diversity and population structure statistics, we will only describe the statistics for the combined mtDNA.j = .964, p = 0.001). Mc1r does show a weak and statistically significant ΦST , however Jost’s D is not statistically significantly different from 0 . Molecular diversity, mismatch distributions and Tajima’s D statistics are compatible with the overall values, which suggests that population subdivision is not solely responsible for any of the high diversity values for the combined analysis.Mc1r; the P-values are just marginally insignificant .When comparing dark and light lizards, population structure analysis of mtDNA indicates weak but statistically significant substructure in mitochondrial loci, but only when the Desert Studies Center individuals are included . When the Desert Studies Center animals are removed from the analysis, no significant ΦST or Jost’s D values are found. Although ΦST and Jost’s D values show low levels of differentiation for Holbrookia maculata (Common Lesser Eared Lizard) and Sceloporus undulatus (Eastern Fence Lizard) vary in color based on substrate habitat, but show no physiological color change over time when reared on an intermediate colored substrate. Other studies suggest that captive reared hatchlings of other lizard species in similar systems develop to match maternal coloration, not substrate color U. stansburiana it is appropriate to consider the role of natural selection for local substrate matching in shaping observed phenotypic variation.Our small experiment suggests that adult phenotypic plasticity may not explain the dramatic color variation in our population of side-blotched lizards residing on different substrates. When housed on light substrates, most lizards did not change color, and those that did changed very little. However, our study of adult phenotypic plasticity and the conclusion that color matching is an evolved condition should be considered preliminary. Sample size in our experiment was very small, mostly because of the Federally protected status of our study site. We examined only one possible direction of color change (dark to light) and the ability of these lizards to change to match dark substrate was not tested. In addition, we examined only adults. Color matching may occur during the development of hatchlings. Finally, a lack of phenotypic plasticity is not synonymous with heritability. Accurate estimation of heritability requires very large sample sizes and complex breeding designs to eliminate maternal effects. But it would be possible to conduct a smaller comparison of female/offspring phenotypic similarity.Mc1r did not show any correlation to color based on phylogenetic and population genetic analyses. Rosenblum et al. Mc1r is highly associated with lighter color variants of Little Striped Whiptail, Aspidocelis inornata and Chaetodipus intermedius. However, many other species showing color variation also show no correlation between color and Mc1r e.g. [43 44 45 46 ]. Most polymorphic sites in our Mc1r sequences are synonymous base changes, and the 5 non-synonymous base changes are found in too few individuals to correlate with color variation. Although we were unable to sequence the entire gene coding region, we were able to include the nucleotide sites known to affect color variation in reptiles [3 44].h) and diversity estimates for π and θ are higher in our limited lava field area than seen in some globally sampled data sets in other taxa. Diversity is higher even when comparing U. stansburiana to other taxa that show adaptive color variation on lava flows. For instance dark variants of pocket mice, Chaetodipus intermedius, on lava fields across Arizona and New Mexico have a π of about.002 for Mc1rMc1rMc1r θ estimates are double that (θ = .010). Our diversity estimates are comparable to values found in marine fish samples taken over a global scale. For instance, the Pelagic Wahoo, Acanthocybium solandri, collected from multiple oceans around the world, has high values of genetic diversity  for cytbHolocentrus ascensionis, also showed similar levels of cytb diversity (h = .976 and π = .006) h = 0.979, π = .007 and θ = .016 for cytb in an area easily small enough to walk across in a day. The high levels of genetic variation in Uta stansburiana are even more geographically localized. The Desert Studies Center samples were all collected within an area <5 km across . Yet the haplotype diversity of this sample is 0.985. We also examined subdivision among the three separated areas within the Lava sample. If we restrict our inference to the south west corner of the lava only, the haplotype diversity for cytb was 0.960 (n = 65), with the highest allele frequency = 0.123 . Yet the two most separated samples were less than 10 km apart, and most samples were much closer. The fact that genetic variation in worldwide populations of highly vagile marine fish is similar to genetic variation of our lizards on a single lava field indicates extraordinary variation.Perhaps the most interesting result of our study is that both mitochondrial DNA and autosomal DNA show an extraordinary amount of diversity in our sample. Haplotype diversity , 0.69 (N = 39) and 0.76 (n = 29), although even these localities contain samples collected over tens or hundreds of kilometers. Mulcahy et al Phrynosoma mcalli for ND4 sequence variation and found haplotype diversities of 0.555, 0.730, 0.762, and 0.942. However the site with the largest h value contained samples separated by over 75 km and surely included separate populations with independent drift effects on allele frequencies. Corso et al Liolemis across their entire ranges in Brazil and reported h values of 0.384 (L. arambarensis) and 0.813 .Reported sequence and haplotype diversities in DNA sequencing studies of lizards have tended to be high , consistent with population growth or positive selection. The fact that both a mitochondrial and an autosomal gene show similar patterns suggest that population growth is more likely than selection.Mc1r is highly variable in our samples, it does not correlate with the observed color differences. Still, this variability, along with the extreme variability seen in our mitochondrial DNA, suggests that this species may be undergoing population expansion and may have a large population size in the Cima Lava Field.Investigation of this system shows a clear distribution of lighter animals on granite and associated rocks and darker animals on dark, basalt rock. Our tests and related studies suggest that this variation in color is not due to phenotypic plasticity. Although the candidate locus U. stansburiana to determine if this diversity is consistent in other locations. The Pisgah Volcano, also in San Bernardino County, is a younger volcano with a population of U. stansburiana that varies in color U. stansburiana that do not inhabit lava fields should be investigated as well to ensure this level of variation is not common in this species. Finally other candidate color genes should be sequenced to see if they correlate with different dorsal color variants. This work contributes to our knowledge of adaptive traits on novel habitats, and will hopefully lead to future studies identifying the underlying mechanisms of the color polymorphism associated with habitats with dramatically contrasting substrate colors.Future studies should investigate similar lava field systems of Table S1Collection Data.(DOC)Click here for additional data file.Table S2Polymerase Chain Reaction Recipes.(DOC)Click here for additional data file.Table S3Polymerase Chain Reaction Protocols.(DOC)Click here for additional data file.Table S4PCR and Sequencing Primers.(DOC)Click here for additional data file.Table S5Munsell Geological Rock-Color Chart Color Calls.(DOC)Click here for additional data file.


Identifying which factors shape the distribution of intraspecific genetic diversity is central in evolutionary and conservation biology. In the marine realm, the absence of obvious barriers to dispersal can make this task more difficult. Nevertheless, recent studies have provided valuable insights into which factors may be shaping genetic structure in the world's oceans. These studies were, however, generally conducted on marine organisms with larval dispersal. Here, using a seascape genetics approach, we show that marine productivity and sea surface temperature are correlated with genetic structure in a highly mobile, widely distributed marine mammal species, the short-beaked common dolphin. Isolation by distance also appears to influence population divergence over larger geographical scales (i.e. across different ocean basins). We suggest that the relationship between environmental variables and population structure may be caused by prey behaviour, which is believed to determine common dolphins' movement patterns and preferred associations with certain oceanographic conditions. Our study highlights the role of oceanography in shaping genetic structure of a highly mobile and widely distributed top marine predator. Thus, seascape genetic studies can potentially track the biological effects of ongoing climate-change at oceanographic interfaces and also inform marine reserve design in relation to the distribution and genetic connectivity of charismatic and ecologically important megafauna. Identifying environmental conditions underlying the division of species into smaller units is central for understanding ecological and evolutionary processes and for the conservation management of biodiversity. In highly mobile species that are distributed across continuous environments with few barriers to dispersal, it is expected that persistent gene flow will stifle genetic differentiation and speciation. Nevertheless, there is growing recognition that gene flow can be limited even in the absence of geographical barriers, both in terrestrial and aquatic environments Pontoporia blainvillei) Sousa chinensis) The study of connectivity in marine systems can be challenging due to the absence of obvious barriers to dispersal and generally large population sizes of marine organisms that often resist genetic divergence, leading to low statistical power to detect population structure Delphinus, the short-beaked common dolphin. Common dolphins occur in all oceans from tropical to temperate waters. Two species and four subspecies are currently recognized: the short-beaked common dolphin, Delphinus delphis Linnaeus, 1758, distributed in continental shelf and pelagic waters of the Atlantic and Pacific Oceans; the long-beaked common dolphin, Delphinus capensis Gray, 1828, distributed in nearshore tropical and temperate waters of the Pacific and southern Atlantic waters; D. d. ponticus Barabash, 1935, restricted to the Black sea; and D. c. tropicalis van Bree, 1971, restricted to the Indian Ocean et al. unpublished data; In this study we use as model a highly mobile, widely distributed cetacean species belonging to the genus Short-beaked common dolphins are known to occur in large groups of dozens to hundreds of individuals. Although their social structure is still poorly understood, individuals seem to group irrespective of genetic relationships, with possible gender and age segregation et al. unpublished data), off the Eastern et al. unpublished data). Particular oceanographic characteristics, such as ocean currents and temperature and salinity differences have been pointed out as likely factors limiting movement of short-beaked common dolphins . CITES permits numbers used to export/import samples were: 07US168545/9, 08US198270/9, 2009-AU-550713, 2009-AU-57-1209, 10NZ000011, PT/CR-0060/2009, PT/LE-0043/2009, PT/CR-005372009, PT/CR-0054/2009, PT/CR-0055/2009, PT/CR-0056/2009, PT/CR-0057/2009, PT/CR-0058/2009, PT/CR-0059/2009.n = 75; the Central Eastern Atlantic (CEATL), n = 29; the Northwest Atlantic (NWATL), n = 38; the Northeast Pacific (NEPAC), n = 40; the Southwest Pacific, n = 35  and n = 39  and the Southeast Indian Ocean , n = 27 . The thermal cycler profile for the tetranucleotide loci and Dde66 and Dde70 consisted of initial denaturation at 94°C for 3 min followed by a touchdown profile for 5 cycles with the annealing temperature starting at 63°C and decreasing 2°C per cycle, followed by 30 cycles with an annealing temperature of 53°C, and a final extension step at 72°C for 10 min. The tetranucleotide loci were amplified in multiplex after optimization. For the remaining dinucleotide loci, conditions followed the original publications. All reactions included both positive and negative controls. Following amplification, samples were mixed with an internal size standard (LIZ 500) and run on an ABI 3130 Genetic Analyzer. The GeneMapper v.4.1 software  was used for sizing of allele fragments.All samples were genotyped at 14 polymorphic microsatellite loci: 7 tetranucleotide  and expected (HE) heterozygosities were calculated in Arlequin v.3.5.1 AR) calculated using FSTAT v.2.9.3 The program Micro-checker v.2.2.3 FST, estimated using FSTAT RST, estimated using Genepop v.4.0 Dspagedi v.1.3 through 10,000 permutations. RST values significantly larger then FST values indicate that mutation, in addition to drift and gene flow, has contributed to frequency differences among samples, which in some cases can be interpreted as phylogeographic signal Three different measures of population differentiation were used: the fixation index primer computer package In order to visualize relationships among putative populations based on genetic variation, we performed a principal component analysis (PCA) on a table of standardised allele frequencies using the adegenet and ade4 packages in R An analysis of molecular variance, AMOVA K) present in the dataset was implemented in the program STRUCTURE v.2.3.3 K between 1 and 8 were run with 400 000 “burn in” and 4 million MCMC replicates. The maximum log-likelihood values from all runs corresponding to each given K were checked for consistency and averaged. The K with the highest averaged maximum log-likelihood was considered the most likely number of clusters that better explains our dataset. CLUMMP v.1.1.2 distruct v.1.1 A Bayesian approach to identify the number of populations (FST/(1−FST) were regressed against the logarithm of geographical distances following a two-dimensional model RST and Jost's D values were also used. Geographic distances were measured in Google Earth by using set points and measuring either straight-line distance across oceans, or the shortest geographical distance along continental margins. The set points were chosen so as to represent the middle point of the area of distribution where the samples were collected.Isolation by distance (IBD) was evaluated using a Mantel test implemented in the program IBDWS v.3.16 3) and water turbidity measured as diffuse attenuation coefficient at 490 nm . These variables, here obtained from remote sensing data, have been previously related to habitat heterogeneity http://oceancolor.gsfc.nasa.gov/) for the period from July 2002 to October 2010 and processed using MATLAB software (www.mathworks.com). Data collected during this time period provide a characterization of the oceanographic features for each region and are robust to inter-annual oscillations , chlorophyll concentration  and the South Pacific and Southeast Indian Ocean populations (hereinafter referred to as South Indo-Pacific).FST values for each local population and then relates them to environmental factors via a generalized linear model. Here we used 10 pilot runs of 1,000 iterations to obtain the parameters of the proposal distribution used by the MCMC, and an additional burn-in of 5×106 iterations with a thinning interval of 20. The model with the highest posterior probability is the one that best explains the data Associations between genetic and environmental factors were examined using a hierarchical Bayesian method implemented in GESTE primer v.5 FST, RST and Jost's D distance matrices to identify the best one, two or three-variable fits.Additionally, we used the BIOENV procedure of Mantel tests FIS values, In total 281 short-beaked common dolphin samples were genotyped at 14 microsatellite loci . ResultsFIS values were obtained for populations from NE Pacific and SW Pacific Australia and New Zealand, which can be due to the presence of population sub-structure (i.e. Wahlund effect). In fact, this is known to be the case for common dolphins inhabiting those regions .Levels of genetic diversity, given by mean number of alleles, allelic richness and expected and observed heterozygosities were high for most populations . SignifiFST and RST comparisons showed significant levels of differentiation among all putative populations .Pairwise ulations , althougTaken as a whole, the fixation indices showed high levels of differentiation between short-beaked populations inhabiting different ocean basins. The SEIND and NEPAC populations showed the highest levels of differentiation when compared with all other short-beaked populations. Contrasting to the inter-ocean basin differentiation, lower levels of differentiation were observed between short-beaked populations inhabiting the same ocean basins.The first two principal components of the PCA analysis explained 84.35% of the variance in allele frequencies among putative populations . The firRST, which grouped the NEPAC population with Atlantic ones  at K = 3   .FST and Jost's D values were used , chlorophyll concentration (CHL) and water turbidity (KD490) was gathered for the seven oceanic regions where short-beaked common dolphins were sampled: NEATL, CEATL, NWATL, NEPAC, SWPAC_AUS, SWPAC_NZ and SEIND . Paired Hierarchical Bayesian analyses implemented in GESTE identified the model including the constant as the best one in all spatial scales considered . The secThe BIOENV procedure found strong positive correlations between oceanographic predictors and genetic differentiation for the analyses conducted at medium spatial scales . For theMantel tests and Partial Mantel tests between genetic and environmental distances were not statistically significant for any comparison, even considering different spatial scales (results not shown). Failures of these tests to detect relationships between genetic and environmental data have been previously described We used a seascape approach to investigate the interaction between a set of oceanographic variables and population structure in a highly mobile, widely distributed top marine predator, the short-beaked common dolphin. We show that sea surface temperature, chlorophyll concentration and water turbidity seem to be important factors in explaining the observed patterns of genetic structure in these dolphins, more than geographical distance alone, particularly when medium spatial scales were considered.FCT estimates for partitioning of short-beaked populations among regions within each ocean basin. The low levels of divergence found between populations inhabiting the same ocean basin may have affected the power of the program STRUCTURE to detect such differentiation, even using recently developed algorithms that account for weak differentiation The overall global pattern of genetic structure obtained here supports previous studies A pattern of isolation by distance was only observed when large spatial scales were considered, indicating that the stronger genetic differentiation observed in short-beaked common dolphins from different oceans may be an effect of geographic distance. Isolation by distance has been reported for other cetacean species, such as in the harbour porpoise All oceanographic variables tested, CHL, KD490 and SST, showed an association with population genetic structure in short-beaked common dolphins. These associations were strongest at the medium spatial scales considered. In the Pacific Ocean, CHL and KD490 were the environmental predictors that were most strongly associated with increased genetic isolation in short-beaked common dolphins. Conversely, in the Atlantic Ocean, SST was the strongest predictor associated with population divergence. Although no significant statistical differences in the 8-year average values of CHL and KD490 were detected among regions in the Pacific Ocean, a visual inspection of the regional maps shows heterogeneity in these variables among regions . HeterogChlorophyll concentration, water turbidity and SST are routinely used to map ocean primary productivity e.g. . Due to Tursiops and StenellaOrcinus orca), where resource partitioning and foraging specializations of sympatric populations occurring in the North Pacific have lead to the evolution of distinct lineages We further suggest that a behavioural mechanism such as specialization for local resources could also explain the patterns observed. Resource specialization is a common mechanism driving population structure in delphinds There are also other factors that may account for population divergence in common dolphins that were not assessed in this study. Fine-scale oceanic processes, for example, have recently been suggested to affect connectivity in common dolphins The results presented here are of particular importance for marine conservation management and design of marine protected areas (MPA). MPAs are usually designed to protect coastal regions that are either important habitats, as part of the marine ecosystem, or biodiversity hotspots Figure S1Annual fluctuation of oceanographic predictor values. Annual average values for (a) sea surface temperature, (b) chlorophyll concentration and (c) water turbidity for the different oceanographic regions.(PDF)Click here for additional data file.Table S1Mean pairwise difference between average values of a) sea surface temperature (SST), b) chlorophyll concentration (CHL) and c) water turbidity (KD490) obtained for each oceanographic region where short-beaked common dolphins were sampled for this study, with significant values of paired t-tests indicated in bold.(XLS)Click here for additional data file.Table S25 and 4×106 MCMC replicates. The log-likelihood of the data (LnP(D)) for each run and an average across 10 runs for each K are shown. The K with the highest averaged maximum log-likelihood was considered the most likely number of clusters that better explains our dataset (in bold).Individual runs for the Bayesian analysis implemented in the program STRUCTURE with a burn-in phase of 4×10(XLS)Click here for additional data file.


Nb/Na) increased significantly despite sevenfold reduction of Na. These results indicated that conservation actions diminished near-term extinction risk due to genetic factors and should now focus on increasing numbers of fish in Lake Mohave to ameliorate longer-term risks. More generally, time-series analysis permitted robust testing of trends in genetic diversity, despite low precision of some metrics.Time-series analysis is used widely in ecology to study complex phenomena and may have considerable potential to clarify relationships of genetic and demographic processes in natural and exploited populations. We explored the utility of this approach to evaluate population responses to management in razorback sucker, a long-lived and fecund, but declining freshwater fish species. A core population in Lake Mohave  has experienced no natural recruitment for decades and is maintained by harvesting naturally produced larvae from the lake, rearing them in protective custody, and repatriating them at sizes less vulnerable to predation. Analyses of mtDNA and 15 microsatellites characterized for sequential larval cohorts collected over a 15-year time series revealed no changes in geographic structuring but indicated significant increase in mtDNA diversity for the entire population over time. Likewise, ratios of annual effective breeders to annual census size ( The value of time-series analysis of long-term datasets is well appreciated in ecology  and the annual effective number of breeders (Nb) are arguably most useful because they determine, in part, the evolutionary capacity of a population to respond to novel or fluctuating environmental conditions  to census size (N), or per capita effective size, that explicitly links evolutionary and demographic processes  – large, long-lived, endemics that once were abundant and broadly distributed throughout the basin ], long-lived (>50 years) member of the family Catostomidae. The biology of this species has been extensively studied (reviewed by Minckley and Marsh Morone saxatilis) that prey on adult razorback sucker of all sizes  into the late 1980s and thus became a focal point for study and conservation action Minckley . In the During the 20-year period through 2011, more than 750 000 larvae have been harvested, and more than 155 000 fish have been stocked into Lake Mohave. Most early stockings were of relatively small individuals that were apparently lost to predation  were made from 1997–2011, representing four major regions in Lake Mohave  where razorback sucker aggregate to spawn , it was not possible to examine temporal and regional differences within years for microsatellites.All individuals were characterized for variation in mtDNA, allowing us to extend the previous study  in a 311 bp fragment from the more rapidly evolving 3′ end of cytochrome g et al. . BrieflyArlequin 3.5.1.2 .Gene diversity and number of mtDNA haplotypes were obtained using the program HR) by rarefaction . Variation in HR among locations was tested by anova . Arlequin also was used to examine the distribution of genetic variation within and among samples (periods and regions) by molecular analysis of variance  among geographic regions (FCT) and among temporal samples within regions (FSC) for each year. Change in levels of variation over time was examined by ordinary least-squares regression (Microsoft excel), using individual sample estimates of HR and haplotype diversity.The number of haplotypes was corrected for sample size . saga assesses fragment allele sizes, as based on the sizing standards and provides the genotype for each individual. The software was used to manually compare results from multiple gels at the same time to insure consistency of allele assignment across gels.Fifteen dinucleotide microsatellite loci were used to characterize variation in the nuclear genome , average heterozygosity per locus (h), and multilocus equilibrium were tested using fstat version 2.9.3.2 (Goudet AR) was calculated by rarefaction via the program HP-Rare as described by Kalinowski  and by regression (excel). Distribution of genetic variation within and among years followed Weir and Cockerham  and bootstrapping (loci only).Deviations from Hardy–Weinberg equilibrium  for razorback sucker in Lake Mohave, defined as the number of reproductively capable adult individuals  was evaluated using the single census modified Peterson formula for closed populations  as 0.5Na.Calculations for repatriate population estimates used specifically for genetic analysis were adjusted to account for the sexual immaturity of most razorback sucker at the time of repatriation into Lake Mohave . The standard estimate of the repatriate population includes these potentially immature fish as long as they were released prior to March of the marking year, and they can make up a significant portion (up to 50%) of the fish encountered during March surveys. The adjusted ‘at large’ estimate excludes razorback sucker encountered that were released within a year of the marking year. This adjustment increases the likelihood that the estimate represents sexually mature razorback sucker. Because razorback sucker in Lake Mohave do not differ significantly from a 1:1 sex ratio  across sequential cohorts. Although specifically designed to estimate Ne for species with overlapping generations, the Jorde and Ryman method relies on a static life table for calculating C and G, thus resulting estimates of Ne should be viewed with caution  and single-sample  approaches. Initially, Nb was estimated using moment-based and pseudo-maximum likelihood procedures in mlne (Wang FS (Jorde and Ryman tempofs (http//www.zoologi.su.se/_ryman). For tempofs estimation, we used sampling plan 1  around F’ (and Nbf) were calculated following Waples , we multiplied estimates by the ratio C/G to calculate corrected Nb or Nbf  or the harmonic mean between 1999 and 2000 (overlapping generations), whereas the single-sample estimate of Nb obtained from larvae sampled in 1999 represents Nb in 1998.Once obtained, all estimates of r Waples . For spei Waples . The ref1 Waples . For exaNb/Na and Nbf/N af across time, we used a nonparametric ‘runs test above and below the median’ as described by Sokal and Rohlf (Ñb] and mtDNA [Ñbf]), by computing a weighted (by the coefficient of variation) harmonic mean value for each marker class . Probability values for the number of runs above and below the median were assigned via normal-distribution approximation . We evaluated the trajectory of deviations from the median value by plotting the difference of observed and median Nb/Na and Nbf/Naf.To test for nonrandom trends in nd Rohlf . First, Analysis of an additional 160 collections (3916 larvae) made from 2004–2011 yielded seven new variants, differing by only single substitutions from previously reported haplotypes (Tables S1 and S2). These new haplotypes are very rare, with the most common (CC) found at a frequency of 0.3%. Therefore, 35 haplotypes were identified in the 6347 total larvae from 259 collections.P < 0.05) levels of haplotypic richness and haplotype diversity, respectively, relative to remnant wild adult population, for a total of 19.0% of all tests. The number of significant tests is similar to 1997–2003 , with Tequila Cove exhibiting the fewest haplotypes per sample (average = 4.41) and Nine Mile area the most (average = 5.46). Bootstrap analysis of gene diversity among the four regions identified none of the six possible pairwise comparisons were significant after B-Y correction (Narum Levels of genetic variation in samples collected from 2004–2011 were characterized for haplotypic richness and haplotype diversity (Table S3). Average haplotypic richness across all samples was 5.00, with a range of 1.00–8.20. Average haplotype diversity was 0.56, ranging from 0.00 to 0.82. Of 310 total comparisons analyzed statistically, 37 and 22 of the samples exhibited significantly reduced . Most of this variation was explained by differences among temporal samples within regions , with insignificant levels of regional structure . The 2011 sample is noteworthy because it is the only year that we failed to identify differences among temporal samples.Distribution of variation within and among samples from 1997–2011 was characterized using r = 0.212, P = 0.001, Fig. r = 0.119, P = 0.065, Fig. Distribution of variation across the 15-year period also was evaluated. Regression analysis indicated that haplotypic richness of samples pooled within year increased with time . Analysis of gene diversity revealed similar results (Table S6), with estimates for loci ranging from 0.16 (Xte2) to 0.96 (Xte20) and years ranging from 0.72 (2000) to 0.76 (1997). As with allelic richness, a single factor anova failed to identify significant differences in gene diversity (Table P = 0.083), with no pattern in variation over time.Microsatellite variation was characterized using 15 loci on random subsamples of 120 individuals from each year (Table S4). Of 27 000 amplifications , only 37 (ca. 0.1%) failed to yield product. There were considerable differences in levels of variation among loci, with estimates of allelic richness (Table S5) ranging from 2.0 (Xte1) to 34.1 (Xte20). Allelic richness (averaged across loci) was less variable than mtDNA over time, ranging from 16.2 (2010) to 17.3 (1997), and differences in mean allelic richness among years , indicating that loci with more alleles were more likely to exhibit deviation from HWE. The most variable locus, Xte22, accounted for 25% (14 of 56) of observed deviations from HWE. We dropped this locus from the dataset, recalculated all estimates of genetic diversity and Ne and compared values between original and truncated datasets. Results were nearly identical between datasets, suggesting negligible effect of HWE deviations on accuracy or precision of estimates, or the validity of our conclusions. In addition, Dowling et al. (Tests for deviation from Hardy–Weinberg Equilibrium (HWE) indicated a significant deficiency of heterozygotes (after B-Y correction) at 56 of the 225 year by locus comparisons. This result is not surprising as sample sizes are large and the sampling strategy pooled across significantly different samples within years, resulting in a Wahlund effect. Such patterns of deviation could also indicate existence of null alleles; therefore, several different approaches were examined to address this issue. Significant deviations were found to be scattered across 11 of the 15 loci, indicating results reflected a sample level phenomenon (such as the Wahlund effect) and not problems with individual loci. Regression of number of significant tests per locus against allelic richness identified a significant relationship  for each locus ranged from −0.055 to 0.165 , with a jackknife average across loci of 0.063 (95% bootstrap CI 0.043–0.085). When examining individual loci, the within population component (f ≈ FIS) ranged from −0.055 to 0.164  with a jackknife average of 0.058, which was significantly different from zero (95% bootstrap CI 0.039–0.080), a result that is consistent with HWE results discussed above. The among-year component (Θ ≈ FST) was an order of magnitude smaller than that within years, ranging from 0 (Xte2 and Xte25) to 0.027 (Xte10), with a significant jackknife average of 0.005 (95% bootstrap CI 0.002–0.010).Microsatellite variation was partitioned into within-and among-year components (Table S7). Jackknife estimates of total genetic variation  in Lake Mohave; However, by 2003 wild fish comprised roughly 50%, and by 2007 represented less than 5% of Na  now make up more than 95% of Na. Overall, Na has declined sevenfold, from approximately 7500 to about 1000 over the study period  early in the time series ] to those revealed by microsatellite data. However, estimates of Nbf were less precise than Nb because they are based on a single genetic locus with many rare haplotypes . Only the estimate Nbf/Naf based on mlne (mtDNA) was not significantly different from random dispersion across the time series (P = 0.21). Likewise, combined and weighted estimates for both marker classes also exhibited significant increases (P < 0.035) in Ñb/Na or Ñbf/Naf over time  or rare and endangered fishes increasingly include goals and targets that aim toward sustainability and recovery of census numbers  and genetic diversity. In general, such plans usually implicitly assume that census size and genetic diversity are directly correlated, but this is usually not the case because of intrinsic differences among species , differences in extrinsic forces that affect recruitment and survival , and/or interactions between intrinsic and extrinsic forces that alter the relationship of census size and diversity across species  but not among geographic regions. Our inability to detect such differences in 2011 is consistent with an overall increase in number of females producing offspring, which thereby reduced impacts of sampling that had previously led to observed differences among individual samples.Seven new haplotypes were identified relative to the previous seven-year period, each at low frequency , and differing by a single mutation from previously identified haplotypes. The adjacent upstream population in Lake Mead is small and, to our knowledge, does not contain these haplotypes . Unlike long-lived and age-structured razorback sucker populations, this species is essentially annual. Both of these examples illustrate the significance of long-term genetic monitoring for evaluation of trends in genetic diversity.Analyses of levels of mtDNA variation over this period provided some especially interesting results, identifying a significant increase in average number of haplotypes and genetic diversity per temporal sample over time. Observed increases in measures of diversity reflect an increase in frequency and number of rare haplotypes over time, consistent with an increase in number of females that are contributing progeny during each individual time period. In contrast to results for mtDNA, the analyses of nuclear DNA variation (as represented by 15 loci) from a subset of individuals (120 randomly selected wild-caught larvae per year) did not reveal increased diversity, as allelic richness and gene diversity were effectively unchanged over the 15-year period. This is similar to results of Osborne et al.  who repoAs noted above, differences in levels of variation exhibited by mtDNA and microsatellites observed here are likely explained by differences in modes of inheritance between mtDNA and nuclear markers. MtDNA is strictly maternally inherited, and only a single variant can be transmitted to progeny (per family); therefore, assuming equal sex ratios and no selection, the effective number of breeders measured by mtDNA is expected to be about ¼ that of an autosomal nuclear gene over evolutionary time Hedrick . Thus, mNb and Nbf) tended to remain stable, or perhaps increase over the time series  and 2003 represented a key tipping point where repatriates made up > 50% of the total spawning stock for the first time. We also observed a number of cases where Nbf exceeded Nb in 2003 through 2005. A decrease in variance of female reproductive success  during this period may have driven Nbf to higher than expected levels. It is also possible that Nbf > Nb because many low-frequency alleles were present in the mtDNA dataset, which can upwardly bias estimates of Nbf  despite sharp decline of Na over the time series. Second, the repatriation program has reduced the realized maximum life span and generation time in Lake Mohave razorback sucker, which is expected to alter relationships of Nb, Ne, and N in theory  yielded Nb = 0.95*Ne = N, which is not appreciably different from results where maximum age was 44 years . Thus, we conclude that changes in age structure do not fully explain increased Nb/Na over the 15-year study period and that compensatory effects are likely the primary cause for increase in this ratio over time in razorback sucker.To explore the possibility that changes in age structure led to increases in The case for razorback sucker illustrates the efficacy of a time-series approach as a tool to study long-lived species in quasi-natural conditions; our study clearly demonstrates maintenance (and perhaps increase) of neutral genetic diversity over time despite population decline and leads to several important hypotheses about effects of age structure, population stability, and compensation as factors in maintenance of diversity.Vipera berus), Madsen et al. Oncorhynchus tshawytscha), Hedrick et al. Puma concolor coryi), Hostetler et al. Other studies have demonstrated an increase in genetic variation over time by the addition of individuals to the system [e.g., Swedish adder  is much larger , and a number of estimation procedures that are known to differ widely in the precision of estimates that they return  based on ldne could not be distinguished from infinitely large values, despite relatively large sample sizes  and a reasonable number of marker loci (15 microsatellite loci). It is thus possible that Nb/Na of razorback sucker may be approaching an upper limit that would preclude detectability of increasing trends in the future. In this case, limited statistical power could lead a manager to erroneously draw a conclusion of ‘no temporal change’ in the ratio when, in fact, it was responding positively to management action. In practice, failure to detect differences between ‘no change’ and ‘positive response’ may not be critical for a very large population, or when Nb/Na ≥ 1.Nevertheless, our analysis suggests that there may be cases where low precision of estimates could become an important limiting factor for time-series analysis of Nb or Nb/Na would go undetected if a population bottleneck were relatively severe. This is because precision of estimates increase as Nb becomes smaller, and precision increases as Na gets larger .Simulation study , demographic intervention may be more important for immediate conservation action as described above for the razorback sucker. Thus, based on time-series data for razorback sucker, we emphasize increases in actual fish numbers as the highest management priority based on time-series analysis of genetic metrics.For most conservation applications, a decreasing trend in


Thus the fraction, f, gives an upper bound on the extent of estimability. In other words, there exists no method that can reconstruct a fraction larger than f of the entire common genetic history. For the realization of such a study, we first define a natural measure of the amount of genetic history. Next, we use a population simulator (from literature) that has at least two features. Firstly, it has the capability of providing samples from different demographies, to effectively reflect reality. Secondly, it also provides the underlying relevant genetic history, captured in its entirety, where such a measure is applicable. Finally, to compute f, we use an information content measure of the relevant genetic history. The simulator of choice provided the following demographies: Africans, Europeans, Asians and Afro-Americans.Reconstructability of population history, from genetic information of extant individuals, is studied under a simulation setting. We do not address the issue of accuracy of the reconstruction algorithms: we assume the availability of the theoretical best algorithm. On the other hand, we focus on the fraction  optimal sample size and (2) optimal sequence length for the most informative analysis. Every genetic event that is consequential to the genetic landscape of a population is captured in a topological structure called the Ancestral Recombinations Graph (ARG) . The conf, of the history that is estimable from a given sample? In other words, no matter what methodological ingenuity is employed, there is always (1 - f) fraction of the common history that is impenetrable. Let N be the number of nodes in an underlying ARG topology. Given the extant samples, let a method estimate N' ≤ N nodes. We further assume that the lengths of the edges, as well as the interconnectivity with the labels, are estimated correctly, so the estimated fraction of this ARG, defined as 0.0 ≤ N'/N ≤ 1.0, is a natural "overstimate". Let all possible methods i. Then f, the penetrable fraction, is f as In this paper, we simply use the expected number of nodes in the ARG as a measure of the relevant genetic history of the population. While this may not be precise, it is a fair proxy for the amount of the relevant genetic history. Then a well-defined question to ask is: What is the largest fraction, scriptor  of an ARscriptor  for an ef, in human populations. Such a study of attempting to "know the unknowable" is best done in a simulation setting. From literature, we pick a population simulator that has the capability of providing not only individuals from different demographies, but also the underlying ARG. This is very suitable for our experimental set-up. Next, we design an algorithm to extract the minimal descriptor from a given ARG. Thus we compute the upper bound on f, as discussed. Recall that each node of the ARG has a specific age or depth associated with it. It may be noted that the length attribute of an edge can be viewed simply as the non-negative difference between the depths of the two incident nodes. The terminal leafnode are the extant individuals. The depth of the extant individual is defined to be zero and the value progressively increases as one traverses the ARG away from the terminal leaf nodes. The nodes of the minimal descriptor are also the nodes of the underlying ARG and the same age is associated with them. Let epoch d be defined as a range of depths say  with d2 ≥ d1. Then the history density at dd, N, is measured by the number of nodes in the ARG with depth in the epoch d. Extending this notion, the estimable density at d is measured as d. We study the demography characteristics in terms of the history density and the estimable density.In this paper, we seek the value of N nodes. Then, Let tARG denote the true ARG for a given data set with bestfit model in COSI to simulate the samples with a calibrated human demography for different populations, proposed by Schaffner et al. , , ..,  derived from the segments file of COSI, where 0 <l1 <l2 < .. <M l= 1.0. Next, each node in G is annotated with one or more of these M intervals by traversing G appropriately. See Figures This is done by computing a minimal descriptor from the ARG. The input to this process is the ARG terval 0 . This ARt-coalescent if it is a coalescent node in one of the M marginal trees. Each coalescent node that is not t-coalescent is removed, following the node-removal procedure defined in [v, an edge is introduced from the parent, u, of v to each child w of v, while maintaining the same age of u as well as the child w. Also the annotation of the edges is adjusted to reflect the same flow of genetic material from u to each of w. Based on this, an mdARG is constructed in the following steps. (1) Remove the coalescent nodes that are not t-coalescent, using the node-removal procedure. See Figure G given by COSI, of the above procedure. In particular, given the ARG in Figure G', which is an mdARG. Let N be the number of nodes in G and G'. Then, Recall from  that a cfined in . To remof significantly. Hence, we use a fixed mutation rate of 1.5 × 10-8 bp/gen in the figures. The interested reader is directed to the Additional File Given the genetic landscape of some extant samples, its underlying ARG is a plausible explanation of the observation, since it is the annotated topological structure that captures the genetic history in its totality, that is relevant to the extant samples. It can also be viewed as a generator that faithfully produces the genetic landscape of the different demographies and since it is a random graph , we use eN) for the demographies may play a role.See Figure f. Note that if there were no genetic exchange events in the ARG, this model leads to the generous overestimate of f = 1.0. Thus it is not very surprising to see a decreasing rate of recombination rate yielding increasing values of f, in each of the demography. With increase in sample size, f gradually increases but stabilizes around f = 0.65, suggesting that in all these demographies at least about 35% of the relevant genetic history is impenetrable. However, the most surprising observation comes from the experiments with different sample lengths. It turns out that f decreases with increasing sequence length. We observe that the reconstructable history of a segment s is actually smaller than the sum of the reconstructable histories of the subsegments of s. This is observed in each of the demographies in isolation, as well as when the demographies are combined into a single universal population.See Figure s1, s2, ..., ms, is indeed larger than the reconstructible history of the single segment composed of these segments. This appears to be a universal property, holding in all the demographies tested. Also, irrespective of the sample size, we observe that at least one-third of the population genetic history is impenetrable, in all the demographies.Reconstructability of common genetic history is a fundamental curiosity in the study of populations. While the population evolution models mature and the algorithms get more sophisticated, what fraction of the common and relevant genetic history of populations continues to be elusive? We present a framework that enables such an exploration. This is based on the random topological structure, the ARG and a method-independent (information-theoretic) structure called the minimal descriptor. This is applied to different demographics in a simulation setting. The most surprising observation is that the sum of the reconstructible history of each of the chromosomal segments, The framework also opens up possible new directions of investigation. Assume that the characteristics of a population can be derived, say from the linkage disequilibrium landscape and other characteristics of observed extant individuals. Then, can such a generator be used to answer the "best-practice" questions about the population: what is the (1) optimal sample size and (2) optimal sequence length for the most informative analysis.The authors declare that they have no competing interests.FU implemented the estimability algorithm. MP and FU carried out the experiments and the analysis. LP designed the study. LP and FU wrote the paper.The publication costs for this article were funded by the corresponding author's institution.BMC Genomics Volume 14 Supplement 1, 2013: Selected articles from the Eleventh Asia Pacific Bioinformatics Conference (APBC 2013): Genomics. The full contents of the supplement are available online at http://www.biomedcentral.com/bmcgenomics/supplements/14/S1.This article has been published as part of Supplementary Material.Click here for file


Fonscochlea accepta) endemic to this ecosystem, may have led to enhanced levels of within species genetic diversity. Analyses of individuals sampled and genotyped from the same springs sampled both pre (1988–1990) and post  a devastating flood event in 1992, revealed significantly higher allelic richness, reduced temporal population structuring and greater effective population sizes in nearly all post flood populations. Our results suggest that the response of individual species to disturbance and severe population bottlenecks is likely to be highly idiosyncratic and may depend on both their ecology (whether they are resilient or resistant to disturbance) and the stability of the environmental conditions (i.e. frequency and intensity of disturbances) in which they have evolved.The role of disturbance in the promotion of biological heterogeneity is widely recognised and occurs at a variety of ecological and evolutionary scales. However, within species, the impact of disturbances that decimate populations are neither predicted nor known to result in conditions that promote genetic diversity. Directly examining the population genetic consequences of catastrophic disturbances however, is rarely possible, as it requires both longitudinal genetic data sets and serendipitous timing. Our long-term study of the endemic aquatic invertebrates of the artesian spring ecosystem of arid central Australia has presented such an opportunity. Here we show a catastrophic flood event, which caused a near total population crash in an aquatic snail species ( Despite the immediate and seemingly far reaching devastation that follows intense natural disturbances, there is an extensive literature showing that such events can ultimately generate environmental conditions favourable to the survival, growth and diversification of living organisms and ecosystems, at least as measured by species diversity Circumstances allowing for testing the impact of catastrophes on any aspect of ecosystem and evolutionary dynamics are highly unusual due to the longitudinal nature of the work required combined with serendipitous timing. Some notable exceptions are studies of droughts and Darwin's finches in the Galapagos Our study of the artesian spring ecosystem of the Great Artesian Basin (GAB) in arid central Australia has provided an unparalleled opportunity to examine the impact of periodic, catastrophic disturbances on the genetic diversity of the endemic fauna that inhabit the springs. Australia's GAB is one of the largest artesian systems in the world, covering 22% of the continent Arid central Australia is subject to recurrent but irregular significant floods due to unpredictable heavy rainfall events. Native vegetation is highly responsive to such rainfall variations and the rivers, creeks and terminal drainage lakes, which are intermittent to ephemeral, are transformed by floodwaters into vast inland seas often extending thousands of square kilometres Fonscochlea accepta), changed through time.Here we investigate for the first time the effect of a catastrophic flood event on the artesian spring ecosystem of arid central Australia. Long term monitoring of the springs in our study area has allowed us to directly test the population genetic consequences of the flood by examining how genetic diversity and divergence estimates and effective population sizes of one of the endemic spring invertebrates . This spring complex is part of the Lake Eyre Supergroup No specific permits were required for the described field studies. Notification and appreciation of access to the study site was provided to the tradition owners of the GAB springs country especially Reg Dodd and the Aboriginal Lands Trust. The community of native species dependent on natural discharge of water from the Great Artesian Basin is listed as “endangered” under Australia's Environment Protection and Biodiversity Conservation (EPBC) Act 1999.Local draw-down of artesian water can result in the extinction of local springs. Major concerns for the maintenance of the springs in the study area arose during the development of the Olympic Dam mine project (BHP Billiton formerly Western Mining Corporation) because of the potential for draw-down effects from the mine's water supply borefields and their proximity to the Hermit Hill spring complex In conjunction with these monitoring programs, recent large scale population genetic and ecological studies have focused intensively on a subset of four of the seven spring groups incorporating 5 of the 16 monitoring springs (Bopeechee (HBO004), Dead Boy (HDB005), Sulphuric (HSS012 and HSS024) and West Finniss (HWF026)) Trochidrobia and Fonscochlea). We have focused our analysis on the species Fonscochlea accepta as it is both widespread and abundant in the springs at our study site, its life cycle and natural history are relatively well described and is found in both the spring vents and outflows The springs in our study area support at least six species of hydrobiid snails in two genera , when temperatures in the Australian arid interior are cooler and evaporative water loss from the springs is lowest. In order to obtain a representative sample of snails from each spring we collected sediment samples along a transect passing from the spring vent to the bottom of the main outflow tail. The number of samples taken was proportional to spring size with a minimum of ten taken in each spring. Sediment samples for each individual spring were aggregated together  then preserved in the field using ethanol. Samples were returned to the lab where they were sorted and  springs .Consistent with regional arid Australia, flooding in our study area is periodic with a major flood occurring approximately every 10–25 years and significant local flooding every 8–10 years Our genetic sampling incorporates years both pre (1988–1990) and post  this devastating flood event. Sampling gaps exist immediately prior to (1991) and following (1994) the 1992 flood and post flood sampling was most intense 10 years after the flood. Apart from 1988–1990 and 1995, no other historical genetic samples exist for these springs. Despite these gaps, the first year sampled after the flood (i.e. 1995) enables post flood consequences to be clearly defined.et al.et al.Total genomic DNA was extracted from homogenates of entire snails (approx. 3 mm diameter) using either DNeasy Tissue Kits (QIAGEN) or NucleoSpin Tissue Kits (Macherey-Nagel). All DNA samples were screened with a panel of nine variable microsatellite markers described in Worthington Wilmer Due to the condition of snails collected from 1988–1990 and 1995 and potentially degraded DNA, all individuals from these years (and a subset of modern samples) were genotyped twice independently to ensure consistency of amplification and scoring. Loci and/or individuals for which there were amplification inconsistencies or scoring problems were excluded from the final data set.micro-checkerenePoponthe Web (http://genepop.curtain.edu.au) IS values) for each spring's temporal samples were also calculated and their significance assessed using 10,000 permutations in FSTAT v2.9.3 Prior to general analysis the data set was checked for genotyping and typographic errors using IS values were assessed. Before any pre or post flood group comparisons could be made, it was important to determine if data/years could be legitimately pooled into the pre and post flood categories. Therefore, significance of each of these genetic diversity variables was initially tested among years within each temporal (pre- and post flood) grouping for each spring using a Tukey's test conducted in R v 2.13.1 v2.9.3 To test whether within spring genetic diversity estimates changed as a result of the flood devastation and subsequent recovery, temporal data for each spring was split into either pre (1988–1990) or post  flood groupings and significance of differences in allelic richness, observed heterozygosity and FenePoponthe Web (http://genepop.curtain.edu.au) ST as estimated by theta v2.9.3 ST value and pairwise comparisons was assessed using 10,000 permutations. The critical significance threshold for the pairwise values was maintained at 5% following correction for multiple simultaneous tests using the false discovery rate (FDR) control Temporal genetic structuring among years within each of the focal springs was examined in three ways. First, pairwise exact tests of allelic composition among years were conducted using GK between 1 and 8  with a burn-in value of 100,000 and 200,000 further iterations. Based on the results from previous studies that found no difference between admixture and no-admixture KFinally, temporal population clustering was estimated using the Bayesian assignment program STRUCTURE v2.2.2 e) from genetic data. Following Aspi et al.e in the pre and post flood years for each of the focal springs. The programs were as follows 1) NEESTIMATOR v1.3 ee. We used this program to compute the likelihoods for Ne values between 5 and 1000 in increments of 5 using 10,000 Monte Carlo replicates for each value of Ne; 3) MNe v1.0 e. We set max Ne to 10,000; 4) TVMP e. We assumed a model of constant population size and used 10,000 MCMC replicates with 50 output updates. Standard errors on all Ne estimates were calculated in Excel.There are multiple methods available to infer effective population sizes  diversity associated with a small number of loci may compromise the precision and accuracy of NST values among springs within years using the same method described above for temporal estimates.In order to examine the population dynamics of the snails pre and post flood, spatial genetic structuring among the focal springs within each of the sample years was also investigated. If extensive mixing occurred due the flood, then pre flood population structure is predicted to be stronger than that post flood. If founder events are important in post flood population dynamics then we anticipate spatial structure will be stronger following the flood rather than before. We estimated spatial population structure by assessing the significance of pairwise FAll contemporary post flood snails (2002–2006) were successfully amplified and scored at the nine loci. Independent repeat amplifications of a subset of contemporary samples revealed no amplification inconsistencies or allelic drop out. In the pre flood (1988–1990) and 1995 snails four out of the nine loci either failed to amplify successfully  or produced inconsistent results across independent runs and were excluded from the analysis. For consistent pre and post flood group data comparisons, we excluded these 4 loci from the 2002–2006 data sets. All subsequent analyses and results presented therefore pertain to the reduced (5) loci datasets. However, summary genetic diversity statistics  for the contemporary samples across all 9 loci are provided  to 0.311  –3.7 , observed heterozygosities ranged from 0.180 –0.336  and F1988/89) . There wPairwise exact tests of allele frequencies among years within springs showed highly significant differences among all pre flood years in all springs where a temporal series was available . Highly ST values showed a near identical pattern to the allele frequency comparisons with highly significant differences in population structure recorded among all pre flood years and between all but one pre and post flood comparison in all springs (ST range 0.059–0.173) than post flood years (mean FST range 0.004–0.011) though four springs did record 1–2 significant post flood pairwise comparisons. The highest values were consistently between comparisons pre and post the flood (range 0.076–0.275) in all springs.Pairwise estimates of F springs . In all K = 2 (Supporting Information K) a single non-differentiated population . The strong genetic structure recorded among springs in the post flood years, especially in 1995, provides evidence that founder events rather than mixing are more important in determining population dynamic processes of the snails following the flood.Pairwise estimates of FF. accepta populations within the same artesian springs. These changes may have been precipitated by the catastrophic flood that swept through these springs in 1992. This assertion is supported by the fact that snails from two springs sampled in 1995 clearly define genetically the post flood group and that genetic signature remains in populations sampled 10 years after this catastrophic disturbance. Contrary to predictions and expectations, our data shows that nearly all post flood snail populations had significantly higher allelic richness, inbreeding co-efficients that were closer to zero, little or no temporal changes in population structure and greater effective population sizes than their pre flood counterparts. Remarkably, our results are consistent with the possibility that a catastrophic disturbance, which resulted in a severe population crash, may have lead to enhanced levels of within population genetic diversity within the recovered populations. To our knowledge, this is the first result of its kind.This study has produced an intriguing and unexpected result. Our data clearly demonstrate changes in the levels of genetic diversity, allelic composition, genetic structure  and effective population sizes of Trochidrobia snail species exhibit a significant decline in the number of springs occupied during the 1989–1992 time period. While an earlier flood event was known to have occurred in the region in 1984 An additional finding was that the system may not have been in equilibrium prior to the flood. Data from the pre flood years showed annual changes in spatial structure among springs, increasingly negative inbreeding co-efficients and consistent significant differences in temporal allele frequencies and genetic structure. While the survey results  appear tThe previously undocumented increases in genetic diversity following the catastrophic flood can be challenging to explain mechanistically. The intuitive explanation is to assume that the flood acts as a mass dispersal or mixing event for these obligate aquatic organisms. Rather, floods are extreme mortality events. In addition to our survey data , the detF. accepta was found to operate via two different mechanisms at two entirely different geographic scales F. accepta have been recorded in outflows of two of the study springs (Bopeechee 004 and Dead Boy 005) of being up to 5.6±2.8 per cm2  Our previous spatial genetic studies showed dispersal by F. accepta high enough to be detected again, by 1995 this had increased to 12/16 springs Click here for additional data file.Table S2Posterior probabilities and variances for models assuming various numbers of clusters (K) for each of the five study springs over all years. Statistics for each value of K represent average values over three separate runs. Assignment test inferred pre and post flood clusters represent average values over three separate runs where K = 2.(XLS)Click here for additional data file.Table S3ST among springs within years.Pairwise estimates of F(XLS)Click here for additional data file.


Mental imagery is an under-explored field in clinical psychology research but presents a topic of potential interest and relevance across many clinical disorders, including social phobia, schizophrenia, depression, and post-traumatic stress disorder. There is currently a lack of a guiding framework from which clinicians may select the domains or associated measures most likely to be of appropriate use in mental imagery research. We adopt an interdisciplinary approach and present a review of studies across experimental psychology and clinical psychology in order to highlight the key domains and measures most likely to be of relevance. This includes a consideration of methods for experimentally assessing the generation, maintenance, inspection and transformation of mental images; as well as subjective measures of characteristics such as image vividness and clarity. We present a guiding framework in which we propose that cognitive, subjective and clinical aspects of imagery should be explored in future research. The guiding framework aims to assist researchers in the selection of measures for assessing those aspects of mental imagery that are of most relevance to clinical psychology. We propose that a greater understanding of the role of mental imagery in clinical disorders will help drive forward advances in both theory and treatment. ► Mental imagery is of potential interest and relevance across clinical disorders. ► We highlight the key domains and measures for assessing mental imagery. ► We propose a guiding framework for the selection of measures in clinical research. ► Exploring mental imagery will help drive forward advances in theory and treatment. The experimental psychology literature on mental imagery is extensive and a considerable array of different measures have been reported to measure different abilities within the sphere of mental imagery . Howevergeneration; image maintenance; image inspection; and image transformation. In Mental imagery has featured prominently in current theoretical accounts of disorders such as PTSD , social 22.1Published studies were identified through searches of Psychological Abstracts (PsycINFO) and ISI Web of Knowledge (All databases) using keyword, title and abstract information. The initial search term ‘mental imagery’ returned 8838 articles. The search was then further refined using the terms ‘imagery measures’; ‘imagery assessment’; ‘imagery’ combined with ‘clinical’; and ‘imagery’ combined with ‘subjective’. ‘Imagery’ and ‘image’ were also searched in combination with ‘generation’, ‘maintenance’, ‘inspection’, and ‘transformation’. Related searches were carried out using the terms ‘visual working memory’ and ‘spatial working memory’ based on evidence for overlap between these constructs and mental imagery processes , whether a study assessed a specific cognitive stage of mental imagery  can be dissociated from transformations of larger environmental scenes  and from3.5phenomenological characteristics of mental imagery, that is, how mental imagery is consciously experienced. This aspect of imagery can be assessed using subjective measures in which participants rate or describe different characteristics of their conscious experience of mental imagery. One common dimension assessed by subjective measures is the vividness of a mental image, which can be used to refer both to luminosity and clarity of mental imagery, as well as the extent to which an individual's subjective experience of imagery is similar to actual perceptual experience , it has typically been held that the key facets of imagery are specific to the disorder under consideration. We will now consider the assessment of imagery in clinical psychology with specific reference to PTSD, social phobia, schizophrenia and depression and finally, bipolar disorder. Although bipolar disorder has received less attention to date in this field, we have recently proposed that imagery may play a particular role in influencing the key characteristics of the disorder .4.1PTSD may result from experiencing or viewing a traumatic event involving death, serious injury, or threat to self or others . Flashba4.1.1Imagery in PTSD has largely been assessed using techniques such as script-driven imagery procedures , and intSome researchers have attributed the success of clinical treatments of PTSD such as EMDR to modality-specific disruption of visual working memory processes e.g. . This ca4.2In social phobia, individuals fear situations such as public speaking, interviews and meeting people they do not already know . The rec4.2.14.3Schizophrenia is characterised by an array of symptoms: positive symptoms include hallucinations, delusional beliefs, disorganised speech and behaviour whereas negative symptoms include blunted emotion and lack of motivation . Mental 4.3.1The Questionnaire on Mental Imagery  has beenConsidering the reported differences in phenomenology of imagery associated with high and low schizotypy we argue this clinical group will be valuable to examine in terms of cognitive imagery processes such as image maintenance  and imagAssessment of mental imagery in schizophrenia must also take into account the presence of generalised cognitive deficits, in particular slowness of information processing and executive dysfunction . Such ge4.4Depression is associated with a range of cognitive , emotional , and behavioural  symptoms . Traditi4.4.1The Image Duration Task see has beenFor associated phenomenology the mental imagery interview  has beenAs with schizophrenia , assessm4.5Bipolar disorder is defined by manic episodes interspersed with episodes of depression . As many4.5.1In bipolar disorder, significantly higher Spontaneous Use of Imagery Scale see  scores hThe Mental Imagery Interview  has beenIn terms of cognitive imagery processes recent findings from 5This section reviews experimental and clinical measures for assessing mental imagery reported in the literature. The basis for the literature search and criteria for task selection are outlined in 5.15.1.1uppercase version of letter within the matrix. The pattern of response times using this variant task indicated that imagery for the letters was generated sequentially rather than simultaneously, with complex letters containing more segments requiring longer to imagine than simpler forms. Using this variant A variant of this procedure was developed by Kosslyn and colleagues . On each5.1.25.1.3A procedure devised by 5.1.4In a task described by See also the Image Duration Task used by 5.1.5The Image Generation  and MentFor example, the Image Generation Task  can only5.25.2.1This task initially devised by 5.2.2This is a widely-used measure of maintenance in visuo-spatial memory developed by 5.2.3Computerised change detection tasks are used to estimate the capacity of visual short-term memory . Partici5.2.4A procedure developed by 5.2.5In the developmental literature, complex span tasks are used to measure active maintenance by the central executive component of working memory . For exa5.2.65.2.7All of the described measures are best implemented in the form of computer-based assessment, although the Visual Patterns test  can be pOnly the Image Maintenance  and Imag5.35.3.15.3.2In the original study reported by 5.3.3This was originally described by 5.3.4This task was originally reported by 5.3.5This task has been described by 5.3.6In the original task reported by 5.3.75.3.85.3.9This task was first reported by 5.3.10Mental comparison tasks such as relative size , tail leMap scanning  and imag5.45.4.15.4.1.1First devised by 5.4.1.2In this task devised by 5.4.1.3Devised by 5.4.25.4.2.1A procedure first reported by 5.4.2.25.4.2.3image combination task participants are sequentially presented with two line drawings which if mentally combined together form a recognisable object . In the image subtraction task the procedure is similar, but in this case the second line drawing must be mentally removed from the first in order to form a recognisable object. A full list of the stimuli used is reproduced in Two related imagery reinterpretation procedures have been developed by 5.4.35.4.3.15.4.3.2In this procedure devised by 5.4.3.3This image integration task was devised by 5.4.4These measures incorporate aspects of image generation, maintenance, and inspection processes. The greater task complexity in comparison to the measures described previously in  may meanMental rotation tasks  are the Restructuring and synthesis measures  can prov5.55.5.1r = .92) with the original scale  . In the al scale .The QMI has been used by 5.5.2Vividness of mental imagery can be assessed using this battery of 16 questions . ParticiThe VVIQ has also been used to explore the relationship between vividness of imagery and schizotypal traits in an analogue non-clinical population .5.5.3This measure of tendency towards general imagery use was developed by Kosslyn and colleagues . It consIn bipolar disorder, significantly higher SUIS scores have been observed compared to healthy volunteers  and unip5.5.4r = .88) and test–retest reliability (r = .91) for this measure in non-clinical samples.Absorption is defined as ‘openness to absorbing and self-altering experiences’ . This 345.5.5The VVQ  consists5.5.6This task assesses preference for using imagery as opposed to verbal strategies when problem solving . In Part5.5.7A variant of the task is described by 5.5.8This is a semi-structured interview developed to explore the subjective experience, occurrence and content of mental imagery in healthy volunteers and clinical populations  inspiredThe interview has been used to explore the frequency and nature of images in social phobia  as well An adaptation of the interview has been used to assess the relationship between mental imagery and psychotic symptoms in schizophrenia . PatientThe interview has also been used to explore the frequency and nature of suicidal imagery in depression . The int5.5.9Developed and reported by 5.5.10This scale has been used to assess the perspective from which an image relating to a previously experienced social situation is experienced . Perspec5.5.11An important consideration when assessing mental imagery ability is whether to adopt objective or subjective measures. We recommend where possible that both types of method are employed, as they assess unique and separable dimensions of imagery ability. There is an abundance of measures to assess the subjective experience of imagery and these have been used in a variety of disorders including schizophrenia, depression and bipolar disorder, but the selection of measures has not been applied consistently, either between or within specific disorders. This has brought some interesting issues to light. For example, two measures of vividness of imagery have been explored in schizophrenia , but conThe Predominance of Verbal and Imagery-based Thoughts VAS  has beenVersions of the clinically orientated ‘Mental Imagery Interview’  have bee5.65.6.1These procedures are a clinical technique aiming to provoke symptomatic PTSD responses. Participants are typically presented with verbal scripts and asked to imagine the content. This procedure seems to have developed from earlier work using generic scripts targeting common fears including snake phobia and performance anxiety e.g., . More re5.6.2The IES  is a sel5.6.3In line with the observation that real-life perceptual triggers may result in flashbacks in PTSD , this la5.6.4Tabular paper diaries have been used to record the frequency and content of intrusive images as they occur in daily life . Partici5.6.5A structured interview investigating intrusive imagery in depression has been developed by 5.6.6The Impact of Event Scale  and IntrScript-driven imagery procedures  and intr5.75.7.1This is an adaptation of the IES-R  created 5.7.25.7.3This task requires participants to form mental images of future events . Partici5.7.4The clinical literature points to the emerging importance of prospective imagery across disorders. Prospective imagery has been considered in relation to schizophrenia, depression and bipolar disorder, with intriguing findings. Imagery for the future is of particular clinical interest, as findings from experimental psychology tells us that imagining oneself completing a behavior may increase the likelihood of that behavior being accomplished . Thus thOur review points to several measures for assessing prospective imagery. Voluntary and involuntary cognitive processes can show independence , though 5.85.8.1and smile to yourself” . Importantly, the initial part of each scenario is ambiguous and could also be resolved with a negative outcome (e.g. they are laughing at you). Participants are required to generate mental images of each scenario as though each one is happening to themselves. Thus the aim is to train participants to use mental imagery to generate positive resolutions when confronted with ambiguous information. Change in interpretation bias is assessed by emotional valence ratings of ambiguous test descriptions provided by participants both before and after the CBM training. Although Steel and colleagues did not demonstrate a significant change in interpretation bias following CBM in the overall sample, a significant positive relationship was observed between the self-rated use of imagery in everyday life provided by participants and change in interpretation bias. Thus participants who had a higher tendency to use mental imagery in general were more likely to develop a more positive bias through the CBM training, highlighting the possible importance of trait mental imagery ability in this regard.A computerised cognitive bias modification paradigm (CBM; based on 5.8.2Reported by 5.8.3lower pleasantness ratings of images generated in response to homographs they interpreted as positive compared to low dysphorics (Reported by sphorics .On a shortened version of the task patients with bipolar disorder reported significantly fewer positive interpretations of the homographs and a trend towards significantly more negative interpretations compared to healthy volunteers. However, when the patients with bipolar disorder did generate positive interpretations on this task, these images were rated as more vivid than those of the healthy volunteers .5.8.4There are a growing number of studies reported in the literature that have demonstrated clinical importance for the interaction between imagery and cognitive bias e.g. . Both thThe application of computerised CBM training  has demo6In this review of mental imagery research in clinical psychology we have considered findings from PTSD, social phobia, schizophrenia, depression and bipolar disorder. We have noted that studies across disorders have rarely used the same measures and the selection of measures has typically been driven by the phenomenology of the disorder in question. Unfortunately, this approach has made it difficult to compare the role of imagery across disorders or to select measures for new research in a previously unstudied disorder. This highlights the need for a guiding framework of the domains most relevant to mental imagery research in clinical psychology.per se provides a suitable basis for pursuing imagery as a treatment target in this population, e.g., in Cognitive Behavioural Therapy (A wide range of measures exist to assess the four stages of mental imagery  as revie Therapy .These findings support our argument that there may be aspects of imagery associated with clinical disorders which may be informative to consider from a cognitive point of view. For example, we have seen that bipolar disorder is associated with high imagery use in line with predictions . HoweverIn summary, we have proposed several key domains for mental imagery assessment in clinical research see . This guWe believe that thorough assessment of mental imagery as proposed here by our guiding framework will help move forward our understanding of the underlying mental imagery processes across a range of psychological disorders, and help drive forward advances in both theory and treatment. We look forward to continued growth and revision of such tasks, and the clinical questions concerning where and why they might best be deployed, as this young field continues to grow.