Bathymodiolus thermophilus. Eight allozyme loci and DNA sequences of four nuclear genes were added to previously published sequences of the cytochrome c oxidase subunit I gene. Our data confirm the presence of two barriers to gene flow, one located at the Easter Microplate (between 21°33′S and 31°S) recently described as a hybrid zone, and the second positioned between 7°25′S and 14°S with each affecting different loci. Coalescence analysis indicates a single vicariant event at the origin of divergence between clades for all nuclear loci, although the clines are now spatially discordant. We thus hypothesize that the Easter Microplate barrier has recently been relaxed after a long period of isolation and that some genetic clines have escaped the barrier and moved northward where they have subsequently been trapped by a reinforcing barrier to gene flow between 7°25′S and 14°S.Comparative phylogeography of deep-sea hydrothermal vent species has uncovered several genetic breaks between populations inhabiting northern and southern latitudes of the East Pacific Rise. However, the geographic width and position of genetic clines are variable among species. In this report, we further characterize the position and strength of barriers to gene flow between populations of the deep-sea vent mussel  Genetic structure is easier to detect and understand in a one-dimensional system than in a two-dimension space When detecting a genetic cline, one should consider the possibility that the location of this cline may be due to the presence of a natural barrier to dispersal because clines are expected to be trapped by such a barrier The geographic region in which a balance between dispersal and selection is maintained is defined as a tension zone. Tension zones tend to stabilize over natural barriers to dispersal Deep-sea hydrothermal vents are patchily distributed along mid-ocean ridges and back-arc basins. Along the East Pacific Rise (EPR), they follow a one-dimension pattern, ideal for testing an isolation-by-distance model of populations Alvinella pompejana displayed an abrupt separation of the populations across the equator Bathymodiolus thermophilus exhibited a smooth clinal distribution of mitochondrial lineages along the EPR (13°N to 21°33′S) B. aff. thermophilus further south (31°S–32°S) Comparative phylogeographic analyses of deep-sea hydrothermal vent species have previously shown the presence of a genetic break between the northern and southern regions of the EPR Bathymodiolus species have been supposed to be long-distance dispersers because of their planktotrophic mode of larval development Bathymodiolus have been confirmed in several population genetic studies showing the absence of genetic differentiation across the Atlantic et al.Bathymodiolus units, Audzijonyte & Vrijenhoek et al.B. thermophilus and B. aff. thermophilus (renamed B. antarcticus by the authors). One of the loci, S-Adenosyl Homocysteine Hydrolase (SAHH), displayed a discordant cline position with fixed substitutions around the geographic zone previously identified by Plouviez et al.The likely cause of the clines observed at the EPR has been a source of debate. Although Plouviez In the present study, we obtained allozyme and DNA sequence datasets for four nuclear genes including the SAHH marker and analysed this new dataset together with mitochondrial haplotypes previously obtained from the EPR mussels to further investigate how genetic diversity is structured across the EPR and more specifically to test for the homogeneity of gene divergences across identified barriers. We obtained evidence for the existence of two barriers, including the one positioned at 7°25′S–14°S. We thus propose that a pair of (semi-)permeable barriers along the EPR is likely responsible for the geographically discordant clinal distribution of alleles in this region.No specific permits were required to perform field studies described in this article. No specific permissions were required to access geographic localities and sample specimens . The locations are not privately owned or protected in any way. The field studies did not involve endangered or protected species.Bathymodiolus thermophilus specimens were sampled from seven deep-sea hydrothermal vent fields along the East Pacific Rise (EPR) from 9°50′N to 21°33′S , Mannose phosphate isomerase , Octopine deshydrogenase , Leucine amino peptidase , Glucose phosphate isomerase , Malate deshydrogenase-1 and -2 , and Hexokinase-1 . Alleles were numbered according to their relative mobility from the most frequent allele (labelled as 100) previously determined for the Atlantic species B. azoricus, this species was used as a reference  were estimated for each population along the EPR. The overall genetic differentiation across populations was estimated at all loci using Weir & Cockerham's θ estimator The program Genetix 4.05.2 et al.B. thermophilus were identified from cytochrome oxidase I gene (mtCOI) sequences previously obtained by Plouviez et al.  gene were also designed from the cDNA sequence data . Sequences from Sulfotransferase were sorted in two paralogous genes called Sulfo1 and Sulfo2 from individual allele recaptures, respectively. Because of the low number of sequences recaptured from Sulfo2, only Sulfo1 sequences were used in this study.Genomic DNA was extracted using a CTAB-PVP extraction procedure following Jolly z et al. , Table 1z et al.  were obtet al.et al.et al.et al.Faure http://www.codoncode.com/aligner/). Sequence alignments were initially performed with ClustalW in vitro recombinants and putative artefactual/somatic mutations. Recombinants between different individuals (1–2% of the dataset for each population) from the same PCR set were detected (and removed) based on abnormal combinations of the 5′-tails.DNA sequences obtained from the MR-cloning method were visualized and edited using CodonCode Aligner 2.0.6 (nπ) and Watterson's theta (wθ) were estimated using DnaSP 4.10.3 www.fluxus-engineering.com) B. thermophilus and B. azoricus . This test compares polymorphism and divergence at several loci to detect if at least one of these loci displays a departure from neutral evolution. This test was preferred to the McDonald-Kreitman Neutrality of loci was also tested using a multi-loci Hudson-Kreitman-Aguadé test HKA,  performestφ, estimated with DnaSP 4.10.3 stφ values in the matrix, the EF1α gene and some of the populations for which, at least one gene was missing were discarded from the analysis . An RFLP analysis was then performed using the Hinf I site to detect N/S individuals by screening all individuals from the Bathymodiolus collection. Incubation of PCR-products was done at 37°C for 1.5 hour in a 20 μl total volume containing 17 μl of PCR product, 1X buffer (supplied by the manufacturer) and 10 U of Hinf I (Ozyme™).A B. thermophilus populations located along the EPR. Among the eight allozyme loci, four  were nearly monomorphic with the most frequent allele occurring at a frequency greater than 95% in all populations. The remaining four loci  exhibited enough polymorphism to investigate their allelic distribution over the range of the EPR. Genetic differentiation was very low and not statistically significant overall , showing the absence of any strong genetic structure at allozyme loci along this portion of the EPR. The Mantel Spearman test showed a slight but significant correlation  between the genetic distance (θ/(1-θ)) and the geographic distance between vent fields  population size (NN being slightly higher than SN). However, expansion cannot be confirmed because of the overlap range of Highest Posterior Density among north, south and ancestral populations.The Monmonier analysis identified a barrier between 7°25′S and 14°S for all tested loci  and φst  barrier . An Isol barrier . The estion size , indicatB. thermophilus and B. azoricus across the Isthmus of Panama, divergence times between clades 1 and 2 were estimated at 0.6–0.9 Mya for mtCOI, conforming to geological estimates of the ages of the transform faults in the 7°25′S–14°S area  and using a 8–12 Mya calibration time obtained from the splitting of 4°S area . In cont4°S area . DivergeB. thermophilus and B. azoricus, indicative of balancing or strong purifying selection.The multi-locus HKA test showed a significant departure from neutral evolution (P < 0.02) among genes within clade 1 (no departure among genes within clade 2), indicating that at least one gene could be under selection. Sulfo1 displayed the highest divergence to polymorphism deviation when compared to other genes. The removal of Sulfo1 (possible outlier) from the dataset led the HKA test to refit the model of neutral evolution (P > 0.31). This gene displayed a polymorphism/divergence ratio of 8.66: a value that is more than eight times greater than expected (1.05) with a very low divergence between The RFLP analysis of the SAHH marker revealed that only 13 individuals south of the 7°25′S–14°S barrier displayed at least one nuclear allele corresponding to the northern clade. Except for one individual showing two northern-type alleles in the southern populations, all of these individuals possessed one allele of each clade. These N/S individuals were mainly located at 14°S and decreased abruptly in frequency further south . No N/S Bathymodiolus have high dispersal capabilities B. thermophilus supports this hypothesis in showing a complete lack of differentiation at allozyme markers between the northern EPR  and the Galapagos sites The unpredictable nature of fluid circulation and the high level of fragmentation found at deep-sea hydrothermal vents should result in species with high dispersal capabilities in order to promote long-distance (re)colonization of new vent sites Bathymodiolus thermophilus is impacted by two barriers to gene flow along the EPR: the so-called Easter Microplate barrier .Previous and present works strongly support the hypothesis that the population structure of stφ with geographic distances at the mtCOI locus (significant Mantel Spearman tests) likely reflects the occurrence of a tension zone that originated at the Easter Microplate .The Monmonier analysis and coalescence analyses statistically detected the presence of a barrier to gene flow at 7°25′S–14°S using nuclear and COI genes. Sulfo1 and SAHH loci both showed two sets of divergent alleles distributed in the 9°50′N–7°25′S and 14°S–21°33′S regions, with an almost reciprocal monophyly. The gene encoding Lyso exhibited two sets of divergent alleles that were geographically interspersed over the whole EPR and PAR, indicating that they were able to cross both the Easter Microplate and the 7°25′S–14°S barriers. However, the 1-bp deletion allele found at a high frequency in populations from 14°S-21°33′S was not observed from 9°50′S to 7°25′S nor within individuals from 38°S. The sample size  is far too low to exclude the absence of this deletion at 38°S. The absence of the deletion in the 9°50′N and 7°25′S individuals, however, strongly suggests that the spread of this new deletion has been blocked since its first occurrence in the southern populations (at least across the 7°25′S–14°S barrier). This deletion is however old enough to provide recombinant alleles at a high frequency between the two Lyso divergent clades, as the deletion is present at the tip of both divergent clades see . The geoet al.Mpi, Odh, Mdh 2 and Hk) because of their low level of polymorphism.The barrier was however not sufficient to create an allele frequency shift at allozyme markers, highlighting an apparent discrepancy among marker types . Discrepancies in the genetic differentiation observed with allozyme and DNA markers have regularly been suggested to result from selection at allozyme loci, sometimes claimed to be under balancing selection Geologic and hydrodynamic conditions from the equator to 15°S are consistent with limited gene flow observed for multiple species between north and south EPR Based on tectonic plate history, the Easter Microplate barrier is older than the 7°25′S–14°S barrier. The Easter Microplate originated from the progressive offsetting of the Pacific-Antarctic Ridge (PAR) along with the ‘old’ EPR (Nazca Pacific spreading centre) about 3.88 Mya . This offsetting progressively expanded with the formation of an overlapping spreading center OSC: see . Ridge oet al.et al.et al.st, Contrasting results among genes across the Easter Microplate are in accordance with the presence of a tension zone at the latitude of Easter Island as proposed by Johnson The hypothesis of a relaxation of the barrier at the Easter Microplate is also supported by the geological formation of the microplate itself. If initiated by the offsetting of the PAR and ‘old’ EPR, the plate formation was achieved when the ends of the two expanding ridges joined together following a clockwise rotation with the setting up of insular volcanic arcs (Orongo and Pito rifts) about 2.5–1.75 Mya  were similar to those estimated at the Easter Microplate boundary between the PAC and SEPR clades of mtCOI and EF1α. This convergence in divergence times found at two distinct spatial locations, as well as the fact that nuclear mutation rates should be lower than that of the mtCOI  under differential ecological selection out of four genes is highly unlikely. This therefore suggests that allele frequency shifts are linked to tension zones and are thus able to move. Together with what we know of the geological history of the EPR, the hypothesis of an interchange of clines from the southern barrier to the northern barrier explains the geographic discordance of cline positions.To conclude, we have shown that the clinal distribution of mtCOI haplotypes along the EPR was in fact due to highly dynamic historical/geological processes. A system of two genetic barriers to gene flow, in which one would be progressively relaxed  and the other enforced , can explain the discordant distribution of genetic clines. A volcanic arc joining PAR and EPR probably played an important role in setting up of a secondary contact zone  between individuals across the Easter Microplate. The proposed relaxation/enforcement scenario of barriers is consistent with the occurrence of a biogeographic transition zone along the southern EPR (resulting from the overlap of the North-EPR and the South-Easter Microplate biogeographic provinces) to explain the high diversity of vent fauna species observed between 17°25′S and 21°33′S Table S1GenBank accession numbers of each unique sequence and their geographic distribution. Numbers correspond to the number of individuals having the accession number in a given population. For example, accession numbers KC858658 through KC858662 all have a single individuals recovered in the 9°50′N population.(DOCX)Click here for additional data file.


Acacia pycnantha by comparing the genetic diversity and structure between populations in the native Australian range and the invasive range in South Africa. This approach also allowed us to explore how human actions altered genetic structure before and after the introduction of A. pycnantha into South Africa. We hypothesized that extensive movement and replanting in A. pycnantha’s Australian range prior to its introduction to South Africa might result in highly admixed genotypes in the introduced range, comparable genetic diversity in both ranges, and therefore preclude an accurate determination of native provenance(s) of invasive populations.The influence of introduction history and post-introduction dynamics on genetic diversity and structure has been a major research focus in invasion biology. However, genetic diversity and structure in the invasive range can also be affected by human-mediated processes in the native range prior to species introductions, an aspect often neglected in invasion biology. Here we aim to trace the native provenance of the invasive tree A. pycnantha in South Africa are as genetically diverse as native populations, and could not be assigned to particular native range regions.In the native range Bayesian assignment tests identified three genetic clusters with substantial admixture and could not clearly differentiate previously identified genetic entities, corroborating admixture as a result of replantings within Australia. Assignment tests that included invasive populations from South Africa indicated similar levels of admixture compared to Australian populations and a lack of genetic structure. Invasive populations of A. pycnantha in Australia has been greatly altered through various planting initiatives. Specifically, there is little geographic structure and high levels of admixture. While numerous introduction history scenarios may explain the levels of admixture observed in South Africa, planting records of A. pycnantha in Australia suggest that populations were probably already admixed before propagules were introduced to South Africa. These findings have important implications for the management of invasive A. pycnantha populations in South Africa, especially for classical biological control, and more broadly, for studies that aim to understand the evolutionary dynamics of the invasion process.Our results indicate that the genetic structure of  The effect of invasion history on genetic diversity has been documented for numerous species e.g. -3. Many Disentangling the deterministic and stochastic processes that underlie the genetic diversity and structure of successful invaders is problematic , but hasTree species introduced for forestry represent a particularly interesting case to explore genetic diversity and structure. These species are typically sampled over large parts of the native range and in large numbers prior to introduction in order to maximize genetic diversity, environmental sampling, and thus evolutionary/breeding potential . ExtensiAcacia pycnantha (Benth.) to South Africa [Acacia pycnantha, commonly known as the golden wattle, is native to south eastern Australia and was introduced to South Africa on two separate occasions in 1865 and 1893 as a potential source of tanbark and for dune reclamation purposes [A. pycnantha showed the species to be a promising candidate for tanbark production. While the exact size of both introduction events is unknown, the redistribution of ca. 22–29 million seeds sourced within South Africa throughout the coastal regions of the country is documented [A. pycnantha is now invasive in parts of South Africa [Given the complex introduction histories often associated with forestry species, elucidating the processes that shape genetic diversity in the invasive ranges requires accurate and detailed introduction records . Such reh Africa . Acacia purposes . Experimcumented ,21. LikeA. pycnantha is structured into two distinct ecotypes (the dryland and wetland forms) which show a propensity for hybridization [A. pycnantha in southern Australia and this may obscure phylogeographic signatures in the native range. Given the known impacts of cultivation on the genetic makeup of invasive species, including Australian acacias [A. pycnantha populations in South Africa. Specifically, we asked: 1) What is the genetic structure in the native range of A. pycnantha? 2) How much of the genetic diversity in A. pycnantha’s native range has been introduced to South Africa? 3) Can source populations of A. pycnantha invading South Africa be identified? 4) Does admixture of geographically isolated genotypes from Australia occur in South Africa?In its native range, dization . South Adization . However acacias , our oveThere was evidence of null alleles at one locus (Plop 18) in eight of the populations and so this locus was excluded in further analyses. Tests for Hardy Weinberg equilibrium (HWE) carried out on the remaining seven microsatellites showed that 153 out of 168 locus-by-site comparisons met expectations under HWE. Fifteen locus-by-site comparisons showed an excess of homozygotes. Of these, only three populations out of the 24 sampled populations showed more than one locus deviating from HWE. Three loci  were out of HWE for at least three sampled populations. However, in these cases homozygote excess was not attributed to the presence of null alleles in the dataset.NA), unbiased genetic diversity (HS), and allelic richness (RS) were not significantly different in the native range  than in the invasive range (South Africa). Furthermore, populations in the native range were slightly more structured than populations in the invasive range  was slightly higher in the invaded range than in the native range (Table NP) were found in the invaded ranges in South Africa than in the native range  it is highly unlikely that this region is a putative source region because of the marked differences observed in leaf morphologies that correspond to distinct ecotypes not found in South Africa [Bayesian assignment analyses in STRUCTURE revealed three different genetic clusters as the optimal number among native range populations while four genetic clusters were identified for the combined native and invasive range datasets  and some Victorian populations (populations HG and NAT)  but considerable differentiation among populations 13%) whereas the majority of genetic variation resided within populations (86%) (Table % whereas) Figure .A. pycnantha’s native distribution in south eastern Australia . Like many other wattles, A. pycnantha was heavily harvested in the wild as early as the 1840s. The unsustainable harvesting of wattle bark from natural populations prompted authorities in Victoria to appoint a Wattle Bark Board in 1878 [A. pycnantha plantation were established at Bundaleer, South Australia; during this period testing and dissemination of both Australian native species and alien species was well underway within Australia . These practices may have resulted in substantial mixing of genetic material in A. pycnantha’s native range, providing many opportunities for interbreeding to occur between previously allopatric populations [A. pycnantha within South Africa following introduction may also explain high levels of admixture observed in the invasive range, but it seems more likely that seeds introduced to South Africa in 1893 came from already admixed sources [Our results make sense as ustralia . Trial pustralia . It has  in 1878 . This Bo in 1878 . For exa in 1878  mentionsulations . On the  sources .A. pycnantha in Australia simply reflects a species with high levels of gene flow. We consider this unlikely, as numerous authors have previously noted that native A. pycnantha populations appear to be structured into two distinct ecotypes [A. pycnantha in its native range, like A. mearnsii[A. melanoxylon[It is also conceivable that the lack of genetic structure and high levels of admixture observed for ecotypes ,28 and tecotypes . Also, mecotypes ,30) - in mearnsii and A. mlanoxylon.A. pycnantha within Australia predates its introduction to South Africa [The role of genetic admixture in successful establishment and invasion has been documented for numerous species ,33,34. Th Africa ,27, makih Africa . Furtherh Africa .A. pycnantha because admixed propagules of A. pycnantha have most likely been introduced to South Africa. However, separate introductions of the biological control agent, the gall-forming wasp Trichilogaster signiventris, from the dryland  and the wetland regions of A. pycnantha (Mt Compass) had differential success in South Africa. Such differences in biocontrol efficacy can be indicative of native provenance. It would be useful to test this hypothesis, in line with other work on the influence of phylogeographic structure on the efficacy of biological control , as parol  and at seven sites from the invaded ranges in South Africa , allelic richness (RS), observed and expected heterozygosities (HO and HE), fixation indices (FST) and inbreeding coefficients (FIS) for invasive and native ranges and within populations. The mean number of private alleles (NP) per population was computed in GenAlex v. 6 [STAT version 2.9.3.2 [Microchecker version 2.2.3  was usedironment . ARLEQUIironment  was usedlex v. 6 . Statist 2.9.3.2 .K) present in both the native range and the combined native and invasive range datasets, and to assign individuals probabilistically to these clusters (for K = 1–10). For both analyses, the admixture model with correlated allele frequencies was chosen and 10 replicates of each value of K were run. Each run consisted of a burnin of 10000 MCMC steps, followed by 1000000 iterations. The method of Evanno et al.[Bayesian clustering methods implemented in the programme STRUCTURE version 2.3.4  were useno et al. was usedTo assess the distribution of genotypes in the native and invasive ranges a covariance standardised Principal Co-ordinate Analysis (PCoA) implemented in GenAlex version 6  was usedThe authors declare that they have no competing interests.All authors developed the project and participated in field collections. JLR and JN analysed the data and led the writing of the manuscript. All authors were involved in data interpretation and writing and read, edited, and approved the final manuscript.Plots of the rate of change (delta K) based on STRUCTURE results.Click here for filePolymorphic microsatellites and multiplexes used in this study.Click here for file


Plus ça change (plus c’est la meme chose) hypothesis. A discussion on the consequences of these hypotheses is what this essay aimed at.Microevolution due to pollution can occur mainly through genetic drift bottlenecks, especially of small sized populations facing intense lethal pulses of contaminants, through mutations, increasing allelic diversity, and through natural selection, with the disappearance of the most sensitive genotypes. This loss of genotypes can lead to serious effects if coupled to specific hypothetical scenarios. These may be categorized as leading, first, to the loss of alleles—the recessive tolerance inheritance hypothesis. Second, leading to a reduction of the population growth rate—the mutational load and fitness costs hypotheses. Third, leading to an increased susceptibility of further genetic erosion both at future inputs of the same contaminant—differential physiological recovery, endpoints (dis)association, and differential phenotypic plasticity hypotheses—and at sequential or simultaneous inputs of other contaminants—the multiple stressors differential tolerance hypothesis. Species in narrowly fluctuating environments (tropics and deep sea) may have a particularly high susceptibility to genetic erosion—the  In theory, environmental contaminants can produce microevolutionary changes through the violation of each of the five assumptions of the Hardy–Weinberg theorem: absence of mutations (and the subsidiary assumption on meiotic drive), genetic drift, non-random mating, gene flow, and natural selection. The violation of the subsidiary assumption on sex-linked loci  at partially lethal or at sublethal concentrations, respectively.The violation of the assumptions of the Hardy–Weinberg theorem corresponds to Bickam’s categories of population genetic impacts Bickham , with thThe loss of genetic diversity due to pollution—contaminant driven genetic erosion  habitats, ecosystems and landscapes diversity, (ii) species diversity and (iii) genetic diversity Dowes . This laAlready in 2002, van Straalen and Timmermans wrote “Our review has singled out several studies showing that environmental stress may significantly reduce the genetic variation in a population. In this sense the genetic erosion hypothesis is confirmed”. Later works reinforced this claim for a wide range of taxonomic groups, exhibiting different modes of reproduction and inhabiting both terrestrial and aquatic  environments . As with physiological recovery, if at least some tolerant genotypes remaining in a genetically eroded population after a partially lethal pulse of a stressor are those more sensitive to or less able to cope with, by acclimation and phenotypic plasticity, a latter long-term sublethal exposure to the same stressor, then an enhanced genetic erosion is possible.The endpoints association hypothesis postulates that tolerant genotypes to lethal levels of a contaminant are also tolerant to sublethal levels. This might be so, namely, if mechanisms conferring tolerance to both levels are the same   and median clonal lethal concentrations (LC50) of 12 clonal lineages of the freshwater microcrustacean cladoceran Daphnia longispina were highly correlated . A sensitive genotype, i.e. with a significantly lower median effective contaminant concentration, will only be wiped out if almost all of its individuals perish, stop reproducing or emigrate. This reasoning demands for the concept of “critically sensitive” genotypes, which are those meeting both criteria: being sensitive and with a low (non-genetic) variation. This was the case in an experiment carried out with artificial laboratory populations of D. longispina comprising five clonal lineages, which differed in their tolerance to lethal levels of a metal rich AMD  were calculated for each clonal lineage using the software Priprobit (Sakuma P) was computed adding the environmental variance (VE) and the genetic variance (VG), VE being determined with approximate estimates of standard deviation values from the models fitted to mortality versus concentration and approximate values of broad sense heritability for each chemical being determined as VG/VP /LC50,48h, in percentage. For each chemical, a clonal lineage was categorized as critically sensitive if its LC75,48h was similar to or below the average of the set of LC50,48h for the twelve clonal lineages. For each pair of chemicals, inversely sensitive clonal lineages were those critically sensitive to one of the chemicals but not to the other. Therefore, safely co-tolerant clonal lineages were those neither critically co-sensitive nor inversely sensitive.Also for comparative purposes, the response variation of each genotype was evaluated with its relative spread of sensitivity, which is the difference between the lower and the upper quartiles relatively to the median effective concentration, i.e. , while for copper, zinc and deltamethrin the variation was larger  Fig. . The witr = 0.73; p < 0.01) presented seven safely co-tolerant and no inversely sensitive clonal lineages , the number of inversely sensitive clonal lineages varied between four and nine out of 12; Zn|deltamethrin being the worst-case scenario for paired exposures, with only three safely co-tolerant clonal lineages.The only correlated pair of chemicals  would indicate a small difference between partially lethal and fully lethal concentrations, at the population level, and, thus, a small increase in environmental concentrations would more easily determine the elimination of all genotypes. Similarly, such an increase would wipe out the genotypes with low relative spreads of sensitivity for each chemical, like the 28 % value (with copper).50,48h), assuming that clonal lineages here used were representative of natural reference populations. This assumption was far from being fulfilled because the clonal lineages were established with the aim of maximizing the genetic variation in the tolerance to lethal levels of copper. The clonal lineage found to be critically sensitive to all tested metals would always be at a high risk and, therefore, the sequential exposure to intermediately lethal levels of two metals would not change much the risk of its most probable elimination. It is the number of inversely sensitive genotypes that expresses the increased susceptibility to future stressors. Considering the potential for genetic erosion due to an intermediately lethal pulse of each tested chemical and assuming that all clonal lineages critically sensitive to each chemical would be killed, it would be expected that 17 (cadmium) up to 42 % (copper and zinc) of the clonal lineages could be eliminated. However, the loss of genotypes could almost double, attaining 75 %, if a pulse of deltamethrin was followed or preceded by a pulse of zinc, both at intermediately lethal concentrations. This reasoning emphasizes the usefulness of the safely co-tolerant genotype concept, to discuss the potential of contaminant driven genetic erosion by directional selective pressures.Copper and zinc, with the largest number of critically sensitive genotypes—five out of 12, i.e. 42 %—were the chemicals posing the highest relative risk of genetic erosion at an intermediately lethal concentration  model (Sheldon The  Sheldon  to short Sheldon . Linking Sheldon .Despite this model being bound to hard-part morphologies and geological timescales, also species and populations’ sensitivity thresholds in narrowly fluctuating environments could more easily be exceeded Parsons , by, forThe genetic erosion hypothesis is demonstrated but some of the associated hypotheses here discussed are far from being sufficiently tested. Several studies were carried out, as explicitly suggested by Hoffmann and Parsons , with is


Pinus-dominated forests. The nutcracker’s encompasses known barriers to dispersal for other species, and glaciated and unglaciated areas. Clark’s nutcrackers also irruptively disperse long distances in search of pine seed crops, creating the potential for gene flow among populations. Using the highly variable mitochondrial DNA control region, seven microsatellite loci, and species distribution modeling, we examined the effects of glaciations and dispersal barriers on population genetic patterns and population structure of nutcrackers. We sequenced 900 bp of mitochondrial control region for 169 individuals from 15 populations and analysed seven polymorphic microsatellite loci for 13 populations across the Clark’s nutcracker range. We used species distribution modeling and a range of phylogeographic analyses to examine evolutionary history. Clark’s nutcracker populations are not highly differentiated throughout their range, suggesting high levels of gene flow among populations, though we did find some evidence of isolation by distance and peripheral isolation. Our analyses suggested expansion from a single refugium after the last glacial maximum, but patterns of genetic diversity and paleodistribution modeling of suitable habitat were inconclusive as to the location of this refugium. Potential barriers to dispersal (e.g. mountain ranges) do not appear to restrict gene flow in Clark’s nutcracker, and postglacial expansion likely occurred quickly from a single refugium located south of the ice sheets.The genetic impact of barriers and Pleistocene glaciations on high latitude resident species has not been widely investigated. The Clark’s nutcracker is an endemic North American corvid closely associated with  Phylogeography is the study of processes underlying spatial and temporal dimensions of genetic variation . PatternThe repeated glaciations and climate oscillations of the Pleistocene epoch provide a natural tool to address population responses to large-scale landscape changes. Multiple expansions and contractions of ice sheets created a dynamic landscape that repeatedly fragmented historical populations, alternately creating barriers to dispersal and creating new habitats for colonization ,11. DuriHigh latitude resident bird species provide a unique opportunity to investigate patterns of postglacial and barrier-mediated dispersal; historical events shaping current population structure should be particularly evident in these species. Non-migratory species have the potential to retain patterns of genetic variation longer due to limited dispersal, allowing researchers to make inferences about past historic events -16. For Nucifraga columbiana) is a high latitude resident corvid species (Family Corvidae) that inhabits North American coniferous forests. Much of the published work on this species has focused on spatial cognition exhibited by their extensive food caching behaviours [Pinus species [Pinus species. Their close association with pine-dominated forests is due to a specialised diet of pine seeds, which influences dispersal patterns of both nutcrackers and seeds [Pinus-dominated subalpine areas [Clark’s nutcracker  approved by the University of Lethbridge Animal Welfare Committee using guidelines set by the Canadian Council on Animal Care (CCAC). Banding in Canada was performed under Canadian Wildlife Service banding permit #10425W (2007) and #10804 (2008 onward) and in the US under US Fish and Wildlife banding permit #23522. All netting and blood sampling was conducted under the appropriate state, provincial, federal, and institutional authorities; detailed permit information is available upon request.From 2009-2012, we captured up to 30 individual Clark’s nutcrackers at each sampling site  using stDNA was extracted from blood, feather, and tissue samples using a modified Chelex protocol . Once ex5’-TTT GGC TAT GTA TTT CTT TGC-3’; Birt & Lemmen, unpublished data) and H1030 JCR 18 [5’-GCA AAG GGA GGA GTA TGC AG-3’) or L530 corvidCR (5’-CGC CTC TGG TTC CTA TTT CA-3’), with L46 SJ or H1030 JCR 18, respectively, to amplify two overlapping fragments. We amplified a section of the mitochondrial DNA control region (CR) using primers L46 SJ  under the following conditions: one cycle of 94°C for 120 s, 52°C for 45 s, and 72°C for 60 s, 37 cycles of 94°C for 30 s, 52°C for 45 s and 72°C for 60 s and one cycle of 72°C for five min. PCR products were run on a 0.8% agarose gel to confirm DNA amplification. Polymerase chain reactions (PCR) were performed on a Master gradient thermocycler  in a 25 μL volume containing 1x goTaq Flexi buffer , 2.5 mM MgClDNA sequencing was performed at McGill University and Génome Québec Innovation Centre on a 3730xl DNA Analyzer  or at the University of Lethbridge on a 3130 DNA Analyzer (Applied Biosystems). For in-house sequencing we used a shrimp alkaline phosphatase-exonuclease clean up followed by sequencing and sodium acetate precipitation  prior toCAC GAC GTT GTA AAA CGA C - 3’) to the 5’ end, which allowed the integration of a fluorescently labeled primer (700 nm or 800 nm) directly into the PCR product. DNA was amplified in a 10 μL reaction with 1x buffer, 1 mM MgCl2, 200 μM dNTP , 1 μM of each primer (forward and reverse), 0.05 μM of the fluorescent primer  and 0.5 units taq polymerase under the following conditions: one cycle of 94°C for 120 s, T1 for 45 s, and 72°C for 60 s, seven cycles of 94°C for 60 s, T1 for 30 s and 72°C for 45 s, 31 cycles of 94°C for 30 s, T2 for 30 s, and 72°C for 45 s, and one final elongation cycle at 72°C for five minutes  were initially screened for 32 microsatellite primer pairs developed for and used in other corvids. Thirteen additional nutcracker-specific microsatellite loci have since been developed by another independent research group [ minutes .PCR products were mixed with a stop solution , denatured for 3 min at 94°C, and run on a 6% polyacrylamide gel using a LI-COR 4300 DNA Analyzer . Alleles were scored via visual inspection, and genotypes were independently confirmed by a second person. Three controls of known allele sizes  plus a size standard were included on each gel to ensure consistent scoring along with a negative control to ensure no contamination was present.Chromatograms were edited and sequences aligned manually in MEGA v5.0 . Shared d) and nucleotide (π) diversity using DnaSP v5.10 [ST values  using Arlequin v3.5.1.3 [Genetic variation within populations was measured by calculating haplotype  were used for genetic distances and significance was tested using 9,999 permutations. A mismatch distribution was used to help visualize signatures of demographic expansion, and to test the null hypothesis of historic population growth and expansion [A Mantel’s test was performed to examine the correlation between genetic and geographic distances in GenAlEx v6.0 . We calcxpansion .K = 2-12; 100 iterations) [K cannot be set to K = 1. Alternatively, BAPS v6.0 [a priori population information and Kmax = 13. A subsequent BAPS run was then conducted using a priori population information.Genetic variation allocated within and among populations was examined using an analysis of molecular variance (AMOVA) in Arlequin v3.5.1.3 . We inverations) ; howeverAPS v6.0 , a BayesFST values [P values were corrected for multiple tests using a Benjamini-Hochberg correction for FDR [Allele frequencies, deviation from Hardy-Weinberg equilibrium (observed (Ho) versus expected (He) heterozygosity), and pairwise T values  were calT values  and P va for FDR . Allelic for FDR . A ManteK = 1-15, a burn-in of 100,000 followed by 500,000 runs, admixture assumed, correlated allele frequencies and including a priori population information 10 replicates were performed for each value of K. In STRUCTURE, it can be difficult to decide when K captures major structure in the data due to similar lnP(X|K) values, thus two additional analyses were conducted using STRUCTURE results: Bayes factor calculations [K [K = 1 is the true number of clusters. However, Bayes factors and BAPS are able to detect if K = 1, so the addition of these methods is useful in species where panmixia is a possibility. A preliminary population mixture analysis for spatial clustering of individuals in BAPS used no a priori population information and Kmax = 13. A subsequent BAPS run was then conducted using a priori population information.Bayesian clustering analyses were conducted using the programs STRUCTURE v2.3.3 ,47 and Bulations  and ΔK [tions [K  using STIn addition to our sample (field and museum) locations, geo-referenced Clark’s nutcracker locations were obtained from the Global Biodiversity Information Facility . We excluded occurrences outside of North America, without geo-references, or recorded before 1950 from modeling and further inspected accuracy by plotting points using ArcMap v10.1 . We removed duplicate records prior to model-building. Current bioclimatic data were extracted from the WORLDCLIM dataset  and LGM bioclimatic data from the Model for Interdisciplinary Research on Climate (MIROC) database  at 2.5 mMaxent v3.3.3  was usedMitochondrial DNA control region sequences n = 169;  from 15 d) values ranged from 0.583 (southern Alberta (SAB)) to 0.964 (Montana (MT), New Mexico (NM), and central California (CCA)) and nucleotide diversity (π) ranged from 0.00127 (SAB) to 0.00402 (northeastern Oregon) for populations with greater than five samples  for Utah (UT) and northeast Washington (NEWA) to 0.359 (Pcorrected = 0.100) for NM and SAB , southern California (SCA), and NEWA). The mismatch distribution did not deviate significantly from the expected signature, so we cannot reject the null hypothesis of historical population growth and expansion [R2 = 0.082, P = 0.040; R2 = 0.064, P = 0.058; not shown).Haplotype diversity  and for K = 2 in SAMOVA , with one group consisting of NM and the other of all other populations pooled. The preliminary (no a priori population information) and secondary (using a priori population information) BAPS analyses for spatial clustering of individuals found no significant differentiation between individuals or populations . Both AMOVA and SAMOVA showed that most genetic variation is contained within rather than among population groups. The highest value of between-group variation was observed when n ≤ 8), the others had a larger number of samples  to 0.123 ; R2 = 0.078, P = 0.029; Limited population differentiation was detected with a global K = 1 ) = -2625.45) and is supported by Bayes factor values (Pr (K=1) = 1) and BAPS results. STRUCTURE results suggested that the optimal number of groups was K = 1 . Furtherd K = 12 , though A total of 1563 presence records were used for training and 174 for testing the distribution models. After removing correlated bioclimatic layers, 10 layers were used for model construction . Mean area under the receiver operating curve (AUC) was 0.907 (range = 0.906 - 0.908), suggesting that the current model was highly suitable for backcasting to the paleodistribution model. Isothermality ), temperature seasonality (bio4), and mean annual temperature (bio1) were the most important variables contributing to the model at 44.3%, 37.7%, and 11.1% respectively. The current distribution predicted by the Maxent model  closely FST < 0.030) [FST = 0.070) suggest this is likely not the case. Using a combination of measures of population differentiation and clustering analyses, our study suggests high levels of population connectivity between most Clark’s nutcracker populations in North America. We found limited differentiation in mitochondrial DNA , with on< 0.030) , though High levels of haplotype, nucleotide, and allelic diversity throughout most nutcracker populations suggest large population sizes and few founder effects or population bottlenecks. The exception to this is the southern Alberta population, which exhibits reduced haplotype and nucleotide diversity for mitochondrial markers relative to the rest of the populations, though microsatellite loci have high levels of allelic richness and heterozygosity . This diPinus seed specialists, such as pygmy nuthatch (Sitta pygmaea) [Loxiaspp.) [Nucifraga caryocatactes) [Aegolius funereus) [Carduelisspp.) [Cyanocitta stelleri) [Sitta carolinensis) [Patterns of potential panmixia and limited population differentiation are not unique to Clark’s nutcracker. Many other species that undergo irruptive and seasonal dispersal also exhibit limited population differentiation despite the presence of proposed barriers to dispersal. Studies of pygmaea) , crossbiiaspp.) , and Claatactes) , found nunereus) , and Eurisspp.) , yet Stetelleri)  and whitinensis)  exhibit inensis) ,62,63, winensis) . OverallPicoides pubescens) [Pinus species that Clark’s nutcracker specializes upon  a star-like phylogeny with many low frequency single haplotypes separated from high frequency central ancestral haplotypes by few mutational steps ; 2) low bescens) ) as wellPinus species on which Clark’s nutcracker commonly feed: whitebark pine  [P. monticola) [P. flexilis) [P. ponderosa) [In addition to the aforementioned characteristics, temperate species that expanded north from a southern refugium have been shown to exhibit genetic differentiation between northern and southern populations corresponding to previously unglaciated and glaciated areas . Southericaulis) , white pnticola) , limber lexilis) ,72, and nderosa) ,74. HowePinus species in North America [Pinus species [Throughout its range, Clark’s nutcracker exhibits low levels of population differentiation and does not appear to be limited by potential barriers to dispersal, though peripheral populations may be slightly isolated. Future research could integrate additional mitochondrial markers to elucidate the location of a glacial refugium or refugia for this species. Mitochondrial markers with lower rates of mutation in corvids (e.g. cytochrome B)  may reta America ,22 and c species , furtherTable S1Summary table of Clark’s Nutcracker samples used in analyses. Sequence (mtDNA): Y = successfully sequenced. N = not sequenced. Genotyped (SSR): Y = successfully genotyped. N = not genotyped. Sources include Burg lab (wild), TS = T. Schaming, The Field Museum (TFM), Burke Museum at the University of Washington (UWBM), Museum of Southwest Biology (MSB), Louisiana State University Museum of Natural Sciences (LSU), American Museum of Natural History (AMNH), Smithsonian National Museum of Natural History (USNM), Royal Saskatchewan Museum (RSM) and Royal Alberta Museum (RAB). (XLS)Click here for additional data file.


Prunus avium L.). One hundred and thirty one individuals were genotyped at ten nuclear microsatellite loci. Total genetic diversity was high (HE = 0.704), while differences between stands were small but significant . There was a significant amount of clonal reproduction in one stand, with only 11 genotypes identified among 36 trees. One stand showed a significant excess (FIS = −0.044) of heterozygosity, and one showed a deficit (FIS = 0.044). Our results demonstrate the importance of taking into account the biological and genetic characteristics of species in forest management, especially when determining a new seed stand. The small genetic differences found between seed stands indicate that a large number of stands are not required. However, they should be carefully selected and should possess adequate genetic variability to ensure low relatedness between seed trees.Microsatellite markers were used to describe the genetic variability of four seed stands of wild cherry ( Tree regeneration in sustainable forest management requires high quality and genetically variable forest reproduction material (FRM) capable of achieving all of the objectives of future forest management. Genetic diversity of species is central for ensuring sustainability and ecosystem multi-functionality in the face of an unpredictable future, particularly in the context of global climate change. ‘Close to nature forestry’ in Central Europe primarily relies on natural regeneration; however, artificial regeneration is required in areas where natural regeneration is inhibited for various reasons. Most FRM used for artificial regeneration is sourced from seedlings that were grown from seeds collected in seed stands and seed orchards.Prunus avium L.) is a valuable broadleaved tree species that occurs naturally in western Eurasia and Northern Africa. It has a mostly scattered distribution and natural regeneration prevails. It is considered highly important from an economic (timber production) and environmental perspective Wild cherry . However, wild cherry is a species with many desirable characteristics. Increasing its proportion and quality in existing deciduous and mixed forests would not only greatly increase the timber production value of these forests, but it could also provide other important functions. For example, it could be an important species for converting unnatural stands (e.g. spruce monocultures) to more natural structures.Based on the assumption that natural selection has optimised populations to their local environment, European and national guidelines Entomophily, zoochory, and generative reproduction with developed self-incompatibility mechanisms, along with vegetative propagation via root suckers, are the main generators of wild cherry's genetic composition in natural stands Four natural stands of wild cherry were sampled in Slovenia. Material was collected from at least 30 adult trees at each site. One of the stands (stand C) is managed forest while the others are unmanaged . In addiTotal DNA was extracted with the DNeasy® Plant Mini Kit (Qiagen) from approximately 20 mg of dried leaves ground in an automatic grinding mill (Retsch MM200). All individuals were genotyped at ten nuclear microsatellite loci. Two multiplex polymerase chain reactions (PCR) were carried out HE to assess overall polymorphisms. Additionally, for averages over loci we computed the average number of observed alleles A, the observed heterozygosity HO, the expected heterozygosity HE, and Wright's inbreeding coefficient FIS for each of the four seed stands. The software ARLEQUIN FST and standardized values G′ST calculated according to Hedrick Nm).For each of the microsatellite loci, we ascertained the total number of alleles, the range of allele sizes, and the gene diversity FST/(1−FST) and the natural logarithm of the geographic distance was analysed with Spearman's rank correlation and its significance was assessed through the Mantel test with the software program GENEPOP version 4.0 Spatial genetic structure was assessed according to Rousset The results showed very high polymorphism at locus EMPaS10; different alleles were distinguished by only one base, resulting in very difficult and therefore unreliable scoring. For this reason we excluded this locus from further analysis. Among the remaining nine polymorphic loci we detected a total of 71 SSR alleles in 131 individuals, with the number of alleles per locus ranging from 3 to 14 . In stanThe analysis showed, notwithstanding three separate trials, that locus UDP98-412 did not give successful amplification in a large proportion of individuals in stands C and D (35% and 33% respectively). These features could be associated with the presence of null alleles at high frequency or unreliable amplification reactions. Reliable answers could have been obtained from the analyses of offspring from controlled crossing. However, HE) was very similar across loci with the exception of locus EMPaS14, which showed more than 40% less diversity than the other loci. Moderate variation in FST (ranging from 0.014 to 0.136) and higher variation in FIS (ranging from −0.081 to 0.094) were observed among loci (Ae) varied between 1.703 for the least diverse locus EMPaS14 and 4.101 for the most various locus PceGA34. This number (Ae), which refers to an ideal Wright-Fisher population, is less than half the number of alleles of the actual stands (comparison between Ae and A) except for the most various loci EMPa015 and PceGA34, where the effective number (Ae) amounted to only one-third of the actual number of alleles (A). For the majority of loci in individual seed stands, we found no noticeable deviation from Hardy-Weinberg equilibrium when only sexually derived individuals were considered  (HE = 0.658). The comparison between observed heterozygosity (HO = 0.656) and expected heterozygosity (HE) showed that stands were on average slightly, but not significantly, inbred, with a mean inbreeding coefficient FIS = 0.001 (±0.048 SD). Two stands indicated an overall significant deviation from the Hardy-Weinberg genotypic expectation: stand D showed an excess of heterozygosity and stand B showed a deficit.Moderate genetic polymorphism was found within stands; on average approximately five alleles per locus were detected (±1.1 SD) . The proHE = 0.704±0.11 SD), while differences between stands were low but significant . Consequently, the estimated number of migrants was high (Nm = 4.2). However, the largest differences were found between stand D and stands B and C, while the differences between the others were smaller (FST/(1−FST), was not significantly related to the logarithm of the geographical distance between stands .The total genetic diversity of wild cherry from the four stands was high , a low level of inbreeding within populations (FIS = 0.012), and low differentiation among populations .Based on nuclear microsatellite markers, the genetic variability in the four natural stands of wild cherry is high. The number of alleles per locus found in this study  is compaSorbus torminalisFor the majority of loci in individual seed stands, we found no noticeable deviation from Hardy-Weinberg equilibrium . On the Previous genetic studies have shown that the genetic composition of wild cherry populations is significantly influenced by the type of reproduction Sorbus torminalis, which showed that small populations did not harbour less genetic diversity This study has shown that the size of the sampling area did not significantly affect the observed variability in the populations, with the exception of stand D, where the small size of the stand prevented the sampling of unrelated trees. A similar finding on the relationship between population size and variability was also reported in a study of The total genetic diversity of wild cherry from the four seed stands was high. Although the sampling method implied some heterogeneity, the differences between these stands were small. This pattern of variation implies that the creation of a small number of seed stands is sufficient, but that stands must be spread out over a large enough area to ensure seeds are collected from unrelated trees. The problem of clonal origin was found in stand D, where a large number of trees are of vegetative origin. Such a stand cannot perform the functions of a seed stand and should be removed from the list of registered seed stands. The highest genetic variability was detected in stand C, possibly the result of regular tending in this stand. We found that three out of four studied seed stands fully meet the conditions that a seed stand should fulfil with respect to genetic variation. These findings support the decision that Slovenia is one provenance unit for wild cherry.


Opisthopappus Shih is endemic to the Taihang Mountains, China. It grows in the crevice of cliffs and is in fragmented distribution. This genus consists of two species, namely, O. taihangensis (Ling) Shih and O. longilobus Shih, which are both endangered plants in China. This study adopted intersimple sequence repeat markers (ISSR) to analyze the genetic diversity and genetic structure from different levels  in this genus. A total of 253 loci were obtained from 27 primers, 230 of which were polymorphic loci with a proportion of polymorphic bands (PPB) of up to 90.91% at genus level. At species level, both O. taihangensis  and O. longilobus  have high genetic diversity. Their respective genetic variation mostly existed within the population. And genetic variation in O. longilobus (84.95%) was higher than that in O. taihangensis (80.45%). A certain genetic differentiation among populations in O. taihangensis was found  and genetic differentiation in O. longilobus was very small . Gene flow in different degrees  and mating system can form the existing genetic structures of these two species. Furthermore, genetic differentiation coefficient (Gst = 0.0453) between species and the clustering result based on the genetic distance showed that interspecific differentiation between O. taihangensis and O. longilobus was not significant and could occur lately. Opisthopappus Shih (Asteraceae) is a genus of perennial herbaceous plants with two species, namely, O. taihangensis (Ling) Shih and O. longilobus Shih ; and (7) Nei's genetic distance (D) and genetic identity (IN). Analysis of molecular variance (AMOVA) in GENALEX 6.4 software package [st). Based on Nei's genetic distance, NTSYS-pc 2.10e software [ package  was usedsoftware  was usedsoftware  was adopGenetic Diversity. A total of 253 ISSR bands were amplified, 230 of which were polymorphism bands. The PPB at genus level was 90.91%, 90.12% for O. taihangensis, and 95.21% for O. longilobus. Generally, at genus level, Opisthopappus showed higher genetic diversity. Nei's total genetic diversity index of Opisthopappus (Ht) was 0.2139 (Ht = 0.2173) and genetic diversity index in populations (Hs = 0.1948) of O. longilobus Shih were slightly higher than those of Opisthopappus Shih .s 0.2139 . MeanwhiPPB), number of alleles (Na), number of effective alleles (Ne), expected heterozygosity (He), Nei's genetic diversity index (H), and Shannon's information index (I) at genus level were 90.91%, 1.9467, 1.3452, 0.1675, 0.2121, and 0.3372, respectively  between two species of Opisthopappus was 0.0453, which was lower than that among populations at species level (O. taihangensis was slightly higher than O. longilobus (es level . Furtherngilobus .st) arranged from 0.122 to 0.427   . The coeradually .Genetic Variation and Structure. The AMOVA results showed that most of genetic variation in Opisthopappus existed within population (77.87%), following among populations (16.15%), and between species (5.98%) (O. longilobus within populations (84.95%) was slightly higher than that of O. taihangensis (80.45%). (5.98%) . Most ofCluster Analysis and Correlation between Geographical Distance and Genetic Distance. At population level, genetic distance between XT and GS population was lowest (0.0277) and that between LZ and WML was highest (0.1552) ((0.1552) . Accordi(0.1552) , the resr = −0.2419, P = 0.1845). Furthermore, at species level, there was no significant correlation between geographical distance and genetic distance in O. taihangensis  and O. longilobus , respectively.The results of Mantel tests showed that geographical distance among populations had no significant correlation with genetic distance  Shih and O. longilobus Shih were higher than those of herbaceous plants  and plants in narrow fields or endangered plants  [Taihangia rupestris, another cliff species endemic to the same area [Opisthopappus both had higher genetic diversity. The degree of genetic diversity in O. longilobus was slightly higher than that of O. taihangensis. The AMOVA analysis showed that most of the genetic variation existed within populations and LZ had the highest genetic diversity among six populations. T. rupestris also had similar genetic diversity and genetic structure [= 0.249) , 37 but ame area , 23. Thetructure , 23.Opisthopappus and Taihangia) endemic to the Taihang Mountains showed similar genetic structures. For T. rupestris, ancient origin and comprehensive reproductive mechanisms might be the key contributing factors for its higher genetic diversity [T. rupestris produced rich genetic variation through sexual reproduction during the long-term evolutionary process. The coexistence of asexual and sexual reproduction caused these variations to accumulate and spread [Opisthopappus was closely related to its special habitats, population regeneration, and dispersal. Individuals of Opisthopappus all grow in cliff cracks with a slope of nearly 90°  is higher than that of endemic and perennial plants  [O. longilobus Shih is lower than that of endemic and perennial plants. These indicate the presence of a certain genetic differentiation among populations in O. taihangensis; however genetic differentiation of O. longilobus is relatively small. Gene flow at different degrees (1.325 in O. taihangensis and 4.336 in O. longilobus) and mating system  can be the contributing factors to the current genetic structures in this genus. Low gene flow may cause population to adapt to the local ecological environment, thus accelerating genetic differentiation [Nm > 1, genetic differentiation among populations due to genetic drift can be prevented. For O. taihangensis or O. longilobus, AMOVA showed that genetic variation mostly existed within population . A similar phenomenon was found in T. rupestris [, resp.) , 38. Furntiation . Wright ntiation  assertedupestris , 23, impT. rupestris [Centaurea corymbosa Pourret [Opisthopappus, the Mantel test revealed that no significant correlation exists between genetic and geographical distance . Geographical isolation cannot explain the population differentiation that occurred in Antirrhinum charidemi and A. valentinum (endemic species distributed narrowly) [Arctomecon humilis (an endangered plant) [O. taihangensis and O. longilobus both have a certain medical value, which led to serious human picking and mining. These activities cause great impact on the effective size of populations and their dispersal, affecting the natural gene flow among populations. They can explain the absence of correlation between geographical and genetic distance.A significantly positive correlation exists between genetic and geographical distance for upestris , 23 and  Pourret , anotherarrowly)  and Arctd plant) . The absd plant) . Human ad plant) , reduce d plant) , 44, 45.T. rupestris, the clustering of the different populations into the two major clades agreed with the geographical distribution and its classification into the two varieties [T. rupestris, homogenizing the genetic diversity of the two varieties, namely, T. rupestris var. rupestris and T. rupestris var. ciliate [O. taihangensis and O. longilobus are similar to T. rupestris in terms of morphological difference and geographic distribution; however, the clustering result of this study shows that the respective populations of these two species do not gather but cross-cluster. Hence, interspecific genetic differentiation between two species is not significant. Their interspecific differentiation is significantly later than the two varieties of T. rupestris [O. taihangensis and O. longilobus are classified according to the split series of the upper leaves and the presence or absence of bracts below involucres. In O. taihangensis, the leaves are bipinnatifid and have pubescences attached to both sides; it does not have bracts below involucres. By contrast, most of the leaves of O. longilobus are pinnatifid except for basal leaves (bipinnatifid or near the bipinnatifid) and all leaves are smooth without pubescences; in addition, it has a pair of bracts below involucres [Dryas octopetala L. (Rosaceae) despite their significant morphological differences [Opisthopappus, the speed of interspecific genetic differentiation can be less than the speed of morphological differentiation, which may be closely related to mating system. Sexual reproduction will promote gene flow among populations, even between species, reducing the interspecific genetic differentiation. Meanwhile, in T. rupestris, the main mode of population regeneration is vegetative propagation [In arieties , 23. The ciliate . They arupestris . O. taihvolucres . Almost ferences . For Opipagation , which iGenetic Diversity and Resource Protection. The degree of genetic diversity to a certain extent reflects the capacity of species to adapt to the external environment. It not only restricts the capacity of individual and species to adapt to the environmental changes but also provides very important information for the realization and protection of species [Opisthopappus is not caused by the degree of genetic diversity but by population regeneration block and the difficulty to recovery due to habitat destruction and fragmentation. Therefore, an effective protection procedure should be developed to avoid a serious endangered situation; for example, in situ conservation through establishing a nature reserve, ex situ conservation in areas with serious habitat destruction, and manual promotion to natural regeneration can be carried out. species , 47. The


Gasterosteus aculeatus) inhabiting a pond complex in Belgjarskógur, Northeast Iceland. We used two landscape genetic approaches  and asked whether gene flow, as measured by genetic distance, was more strongly associated with Euclidean distance (isolation-by-distance) or with landscape connectivity provided by areas prone to flooding (as indicated by Carex sp. cover)? We found substantial genetic structure across the study area, with pairwise genetic distances among populations (DPS) ranging from 0.118 to 0.488. Genetic distances among populations were more strongly correlated with least-cost-path and isolation-by-resistance than with Euclidean distance, whereas the relative contribution of isolation-by-resistance and Euclidian distance could not be disentangled. These results indicate that migration among stickleback populations occurs via periodically flooded areas. Overall, this study highlights the importance of transient landscape elements influencing migration and genetic structure of populations at small spatial scales.Neutral genetic structure of natural populations is primarily influenced by migration  and drift . Migration between populations is influenced by several factors, including individual behavior, physical barriers, and environmental heterogeneity among populations. However, drift is expected to be stronger in populations with low immigration rate and small effective population size. With the technological advancement in geological information systems and spatial analysis tools, landscape genetics now allows the development of realistic migration models and increased insight to important processes influencing diversity of natural populations. In this study, we investigated the relationship between landscape connectivity and genetic distance of threespine stickleback ( Gasterosteus aculeatus) inhabiting a series of ponds in Belgjarskógur, Northeast Iceland.Much evidence exists on how natural selection and mutations shape population structure Darwin . HoweverThreespine stickleback is a common and short-lived (up to 2–3 years) fish species, which marine ancestors have repeatedly colonized a wide range of freshwater environments across the northern hemisphere since the last ice age . Phenotypic divergence of sticklebacks, in response to environmental variation, has often been assessed (Bell and Foster 2) northwest of Lake Mývatn  among population pairs simply correlated with Euclidean distance (IBD) or is it more related to landscape connectivity provided by areas prone to flooding?To gain insight to the potential role of seasonal flooding on regional genetic structure, we used two landscape genetic approaches  across 19 stickleback ponds in Belgjarskógur. We investigated the following main questions: (1) What is the extent of genetic structure of stickleback populations in Belgjarskógur? (2) Is genetic distance (DGasterosteus aculeatus subsp. leiurus) were collected from 19 ponds across Belgjarskógur during June 2009  and observed (Ho) heterozygosity as well as allelic richness (Ar) were calculated using FSTAT 2.9.3 (Goudet PS (see below) for both adjusted and unadjusted allele frequencies. However, as the results for adjusted allele frequencies were quantitatively similar (Pearson r = 0.999), we only present the results for unadjusted allele frequencies here. Markers were tested for linkage disequilibrium using FSTAT  , only results based on DPS are presented here. Effective population sizes (Ne) and their corresponding 95% confidence intervals were calculated via approximate Bayesian computation using the program ONeSAMP 1.2  using 10 runs per K, 10,000 burn in and an additional 100,000 Markov chains to determine the overall log probability of the tested value of K. The best K was identified using the method of Evanno et al. , but this was likely due to a drop in the number of alleles from 95 with all loci included to 56 when the above three loci were removed. Third, we recalculated pairwise DPS by removing each of the potentially QTL-linked loci separately as well as all three together from the data set. We then checked for correlations between these and the pairwise DPS values from the whole data. We found high positive correlations (Previous studies indicated that three of the microsatellite loci used here could be linked to quantitative trait loci (QTL) including dorsal spine length (Gac7033 and STN130), lateral plate width and height (Gac1125), and short gill raker number , with C. rostrata dominating the sedge communities  and Euclidean distance. To determine Carex cover across Belgjarskógur, we first used high-resolution  SPOT-5 satellite imagery obtained from the National Land Survey of Iceland for the years 2002/2003. Using ARCGIS 10 (ESRI), we then created a raster grid (resistance surface) (10 × 10 m) of Belgjarskógur, using the maximum-likelihood classification function to classify areas to either “water,” “Carex cover,” or “other ground cover” landscape element classes. These three classes were preidentified using five training samples for each landscape element class based on GPS-referenced locations across Belgjarskógur  for Carex cover, whereby 1 equals resistance of water (no resistance) and 100 other resistance of ground cover (high resistance). We then used ARCGIS 10 and the ARCTOOLKIT LANDSCAPE . Partial Mantel tests with 10,000 permutations were used to separate the effects of LCP/IBR from those of Euclidean distance alone. All Mantel and partial Mantel tests were calculated using the Vegan package , suggesting they might be influenced by inbreeding or nonrandom mating . Additionally, STRUCTURE analyses without these five ponds showed similar geographic clustering. In conclusion, we present the data including all stickleback from the 19 ponds below.Sticklebacks in five ponds showed significant deviations from HWE  ranged from 12 to 86. Pairwise DPS values among ponds ranged from 0.118 to 0.488. STRUCTURE analysis indicated six genetic clusters  across loci ranged between 2.70 and 4.04  and effeclusters . SticklePS and all LCP and IBR distance measurements  among ponds, least-cost-path (LCP) analyses indicated that genetic structure was more strongly related to PS) varying from 0.118 to 0.488. These genetic distances are similar to those reported in other stickleback studies  are expected to be under strong influence of genetic drift  limits local population size, and, hence, genetic drift could be expected to play an important role in shaping genetic structure across the Belgjarskógur area. However, while genetic drift and migration likely contribute to the observed levels of genetic differentiation, migration may predominate over genetic drift in our study system. This is indicated by the significant IBD, and by an even stronger association of genetic distance with periodically flooded areas. However, drift should result in random patterns of genetic differentiation.In general, populations with small effective population sizes (t Wright . In our IS) increased, potentially pointing to inbreeding or nonrandom mating , while flooding seems to be relatively rare in the highly structured Western populations (Carex sp. areas less common). Hence, we suggest that variation in flooding frequency and strength allows for different levels of migration and, thus, gene flow across the study area creating a mosaic of genetic structure across Belgjarskógur.Threespine stickleback is well known for its ability to disperse, as witnessed by frequent and repeated colonization of freshwaters from marine as well as across different freshwater habitats  and Euclidean distance on genetic structure when we used isolation-by-resistance (IBR). This is likely due to CIRCUITSCAPE overestimating the number of pathways between ponds, which will decrease the estimated resistance between the ponds , jointly with small population size and genetic drift, is an important determinant of neutral genetic structure in Belgjarskógur threespine stickleback. Our study particularly highlights the importance of considering fluctuating landscape features, such as periodic flooding events, in shaping the genetic structure of populations, which otherwise might appear geographically isolated. Such temporarily variable spatial connectivity may be relatively more important at small spatial scales, where the frequency of disturbance is expected to be greater than across larger spatial scale. We therefore suggest studies aiming to understand processes influencing diversity or conservation of local populations, should consider the impacts of temporal variation in landscape features, such as periodic fluctuation or disturbance, and the implications they have on migration.


Galaxiella) endemic to temperate Southern Australia. We also tested if continental shelf width has influenced connectivity among populations during low sea levels when rivers, now isolated, could have been connected. We addressed these questions by sampling each species across its range using multiple molecular markers . These data also allowed us to assess species boundaries, to refine phylogenetic affinities, and to estimate species ages. Interestingly, we found compelling evidence for cryptic species in G. pusilla, manifesting as allopatric eastern and western taxa. Our combined phylogeny and dating analysis point to an origin for the genus dating to the early Cenozoic, with three of the four species originating during the Oligocene-Miocene. Each Galaxiella species showed high levels of genetic divergences between all but the most proximate populations. Despite extensive drainage connections during recent low sea levels in southeastern Australia, populations of both species within G. pusilla maintained high levels of genetic structure. All populations experienced Late Pleistocene-Holocene population growth, possibly in response to the relaxation of arid conditions after the last glacial maximum. High levels of genetic divergence and the discovery of new cryptic species have important implications for the conservation of this already threatened group of freshwater species.The freshwater fauna of Southern Australia is primarily restricted to the southwestern and southeastern corners of the continent, and is separated by a large, arid region that is inhospitable to this biota. This geographic phenomenon has attracted considerable interest from biogeographers looking to explain evolutionary diversification in this region. Here, we employed phylogenetic and phylogeographic approaches to evaluate the effect of this barrier on a group of four galaxiid fish species ( Long-term aridity since the Oligocene created a vast desert region in southern Australia, isolating two moist temperate regions in the southwestern and southeastern parts of the continent. The biota that occupy these two regions have been isolated since at least Mid-Miocene  [1], [2]Galaxiella species is differences in the width of the continental shelf. Regions with narrow continental shelf should present limited opportunities for drainage connections during low sea levels, since few rivers are likely to connect  and G. munda (mud minnow), occur in southwestern Australia while a third species, G. pusilla , occurs in southeastern Australia . As a result, the two western species are considered ‘lower risk, near threatened’ by the Australian Society for Fish Biology (ASFB) G. pusilla is listed as ‘vulnerable’ by the ASFB, as well as in the International Union for Conservation of Nature Red List of Threatened Species Environment Protection and Biodiversity Conservation Act of 1999.Freshwater fishes in the genus ustralia . The thrGalaxiella species. The nomenclature of each Galaxiella species has remained largely stable since their description; however, their generic placement has changed. Galaxiella pusilla and G. nigrostriata were originally described as Galaxias species Brachygalaxias, from Chile Brachygalaxias were distinct from the Australian species, McDowall Brachygalaxias to Chile, proposed Galaxiella for the Australian group and described G. munda. Several molecular and morphological studies have examined broader galaxiid relationships. Waters et al. Galaxiella species to be reciprocally monophyletic and most closely related to Brachygalaxias based on mitochondrial DNA sequences. A comprehensive morphological analysis also supported the monophyly of Galaxiella and BrachygalaxiasGalaxiella and Brachygalaxias, but as sequential rather than as sister lineages, with both recovered as ancestral to the majority of other Galaxiidae species Several studies have examined the taxonomy and relationships of Galaxiella species from southwestern Australia has not been studied in detail. Smith et al. G. nigrostriata and found only one of 27 allozyme loci to be polymorphic. Phillips et al. G. munda based on mtDNA control region and found 11 haplotypes from 92 individuals that grouped into four haplogroups, each differing by 4–7 bp. In southeastern Australia, Coleman et al. G. pusilla using 11 microsatellite DNA loci and the mtDNA cytochrome oxidase I (COI) gene. Their major finding was of a deep east-west separation of G. pusilla into two lineages, consistent with the presence of two species. Coleman et al. FST values and significant genetic structure among G. pusilla populations.Molecular genetic variation within Galaxiella, a more integrative approach is needed; one that blends phylogeny and phylogeography. Although obviously relevant, previous single- and multi-locus phylogenetic analyses of Galaxiella used limited within-taxon sampling (one sample/species). Previous within-species comparisons in the two western Galaxiella species were also limited, as they addressed more specific local questions G. pusilla, Coleman et al. Galaxiella fishes. First, we use Gondwanan fragmentation and the well known geology of southern Australia to derive geologically-based calibration points for analyses and thereby estimate a time frame for diversification within the genus based on broader within-taxon sampling. This amounts to a ‘congeneric phylogeographical’ sampling approach. This has been shown to present a viable means of increasing systematic accuracy and improving historical inferences, by the recovery of polyphyly and ‘cryptic’ lineages, within vertebrate species Galaxiella species based on more extensive geographic sampling. Third, we investigate phylogeographic patterns within each Galaxiella species. Fourth, we attempt to understand the effects of aridification on the evolutionary history of Galaxiella in southern Australia and the role that sea level changes had on the evolutionary histories within each Galaxiella species in southern Australia. Specifically, if shelf width is important then populations of G. munda and G. nigrostriata from southwestern Australia and populations of G. pusilla in the western portion of their range in southeastern Australia will have a high level of genetic divergence between drainages. In contrast, populations of G. pusilla that connect hydrologically to Bass drainage during low sea levels should have low genetic divergence, while populations to the east of Bass drainage should be distinct due to the low sea level drainage divide  approval 09-1018R, Brigham Young University IACUC approval 070403 and University of Adelaide Animal Ethics Committee approval S-32-2002.Galaxiella from 40 locations spanning virtually the entire distribution of this genus in Australia . Fishes were collected with seine and dip nets and either frozen whole in liquid nitrogen or preserved in 95% ethanol in the field. Our sampling ranged from 1–11 individuals per locality, with most sites represented by 10 individuals within G. pusilla and 1–3 individuals in G. munda and G. nigrostriata, plus two sequences from GenBank for a total of 219 ingroup samples. Based on their close relationships to Galaxiella in previous molecular and morphological phylogenetic analyses Brachygalaxias bullocki and B. gothei as outgroups in our DNA analyses  and manipulated to produce bathymetric contours and low sea level drainage patterns  gene using two primers that flanked the gene. Most G. pusilla and G. munda samples were amplified using the primers Glu21 CCAGGACTAATGGCTTGAAAAA and GP.Thr27 TCTTCGGATTACAAAACCG. When this failed to produce sufficient PCR product, the gene was amplified in two halves using Glu21 - HD.GP GGRTTGTTTGAGCCTGTYTCGT and GP.505 TCTGTTCATAATGCAACCCT - GP.Thr27. For G. nigrostriata we also used the forward primers Glu18 TAACCAGGACTAATGRCTTGAA or Glu31 TGRCTTGAAAAACCACCGTTGT with HD.GP as well as the internal forward primer Sal.484 CAATGAATTTGAGGGGGRTTCTC or GN.484 CAATGAATTTGGGGTGGATT and the reverse primer GP.Thr27 or 15990 AGTTTAATTTAGAATCYTGGCTTTGG b, as well as an unusual start to the gene (different start codon as well as deletion of the third codon and deletion of the last five bases of the Glu tRNA), hence, we amplified a 631 bp region from the middle of ND6 to base 345 of cytb to confirm these sequences using the primers GalaND6F CTCTGGAAAAGGCTCCGCTG and Galacb346R CAAGAAGTAGTAATACAACACC. We also included the first two introns and the second exon of the nuclear S7 gene. All nuclear sequences were obtained by nested PCR using the following primers: 1F TGGCCTCTTCCTTGGCCGTC and 3R.24 AGCTGAGCCTTCAGGTCAGAG in the first reaction followed by 1F.2 CTCTTCCTTGGCCGTCGTTG and 3R GCCTTCAGGTCAGAGTTCAT in the second reaction. In a few cases, we had to use the internal primers 1F.2 and 2R.67 TACCTGGGARATTCCAGACTC, and 2F.2 GCCATGTTCAGTACCAGTGC plus 3R. Primers 1F and 3R are from Chow and Takeyama 2. Amplification parameters were as follows: 94°C for 3 min followed by 35 cycles of 94°C for 30 s, 48°C for 30 s, and 72°C for 90 s, and 72°C for 7 min. For the nested PCR our first reaction was 10 µL with the same PCR conditions listed above. This first PCR reaction was then diluted to 1∶99 and 1 µL from that was used in the second reaction. We examined PCR products on 1% agarose gels using SYBR safe DNA gel stain . We purified PCR products using a Montage PCR 96 plate . Sequences were also obtained via cycle sequencing with Big Dye 3.0 dye terminator ready reaction kits using 1/16th reaction size . Sequencing reactions were run with an annealing temperature of 52°C following the ABI manufacturer’s protocol. We purified sequenced products using Sephadex™ columns . Sequences were obtained using an Applied Biosystems 3730 XL automated sequencer at the Brigham Young University DNA Sequencing Center. All haplotypes obtained in this study were deposited in GenBank, accession numbers JQ697745-JQ697836. Data files containing all individuals sequenced as well as various analysis files were deposited in Dryad, doi:10.5061/dryad.c3g8h.We extracted genomic DNA from muscle tissue for each specimen using DNeasy Tissue Kits . We amplified the mtDNA cytochrome b was aligned by eye, while S7 sequences were aligned with the online version of MAFFT 6.822 b: GTR+I+G; S7: GTR+G) was estimated via AIC in ModelTest 3.7 Brachygalaxias bullocki and B. gothei. The ML trees for cytb and S7 were deposited in TreeBASE, accession number TB2:S12419 (http://purl.org/phylo/treebase/phylows/study/TB2:S12419). We calculated mean within- and among-taxon and population variation using p-distances in MEGA. We also reconstructed a haplotype network to resolve shallow relationships among closely related haplotypes b haplotypes using statistical parsimony with a 95% probability that no multiple substitutions had occurred. This failed to create a single network within both G. munda and G. nigrostriata, thus we reduced the probability to 92% and 93% respectively, at which point single networks were generated.Sequences were edited using Chromas Lite 2.0  and imported into BioEdit 7.0.5.2 b and S7, included all individuals sequenced, then ran analyses using a relaxed molecular clock in BEAST 1.6.1 Brachygalaxias and Galaxiella, as potentially congruent with the separation of Australia, Antarctica and South America. The terrestrial separation of Australia and Antarctica occurred at approximately 52 Ma Galaxiella species was assigned a minimum age of 14 million years, representing the end of the Mid-Miocene transgression and formation of the Nullarbor Limestone over most of the Eucla Basin  was estimated via AIC in ModelTest. Analyses were run for 200 million generations, with parameters logged every 10,000 generations. Multiple runs were conducted to check for stationarity and that independent runs were converging on a similar result. Output from BEAST was examined in Tracer 1.5 with 10% burn-in and the tree results were summarized using TreeAnnotator 1.7 (prerelease).We used the Bayesian *BEAST algorithm la Basin  [1]. ThiG. pusilla in greater depth as we had sampled a larger number of individuals with broader geographic coverage than the two southwestern Galaxiella species. Using DnaSP 5.10 H), haplotype diversity (Hd), and nucleotide diversity (π × 100), within each G. pusilla population and clade, and for all populations combined. To test the relative contribution of genetic variation to within and between population structure in G. pusilla, we performed an analysis of molecular variance (AMOVA) G. pusilla lineages. AMOVA analyses were conducted in Arlequin 3.5 4 random permutations of the dataset.We used multiple methods to examine within and between population genetic patterns in order to investigate the role of sea level changes in structuring genetic variation. We explored patterns of genetic variation in Galaxiella in southeastern Australia by testing hypotheses of population expansion within G. pusilla using several complementary analyses of our mtDNA data. First, we tested population expansion by using 104 replicates of coalescent simulations in DnaSP to estimate Tajima’s DFSR2G. pusilla clade. In pilot BEAST runs  of cytb variation for each clade, ucld.stdev parameter distributions clumped at zero, indicating highly clock-like data. We conducted BSP runs  in BEAST with strict clocks and evolutionary models from ModelTest . Taxon-specific rates of molecular evolution were unavailable, so we used conservative uniform priors spanning known mtDNA substitution rates ranging across teleost fish diversity . Log10B10>2 units indicated definitive (very strong) evidence against the null model, while log10B10<−2 units indicated very strong evidence for the null model We further evaluated the evolutionary history of G. pusilla, we were able to obtain comparative allozyme profiles for this species. These were used to independently assess the finding by Coleman et al. Galaxias olidus, were also included in this analysis. We conducted allozyme electrophoresis of muscle homogenates on cellulose acetate gels  following Richardson et al. Since frozen tissues were available for virtually all D), following the methodology of Hammer et al. G. pusilla. Threshold probability values were adjusted for the use of multiple tests using sequential Bonferroni correction The genetic relationships among all sites were initially assessed by constructing a neighbour-joining (NJ) tree from a pairwise matrix of Nei’s G. pusilla as per Coleman et al. Our molecular datasets provided clear discrimination among all described species. In addition, they revealed major and concordant genetic discontinuities consistent with cryptic speciation in b dataset consisted of 1141 bp for 224 individual fish . Neither change is unusual for cytb among fishes  or across various animal groups b with a likelihood score of −5764.906494  for all deep nodes in the cytb dataset, with the exception of the node uniting G. munda and G. nigrostriata  = 0.212±0.090; mean π×100± s.d. = 0.059±0.014), but moderate genetic diversity within each clade . In most cases, population genetic variation was characterized by 1 or 2 haplotypes per locality, with the second haplotype almost always being rare  and only three haplotypes shared across populations (G. pusilla (N = 8) and western G. pusilla (N = 7) among-group comparisons accounted for 90.2 and 72.8% of the variation respectively. All three among-group AMOVA values were statistically significant (P<0.05).Estimates of genetic diversity based on cytb  revealedulations , 3. ResuG. pusilla population in R2 values were significant , supporting demographic-spatial expansion. Neutrality tests showed a similar pattern across G. pusilla clades, with only the R2 estimates being significant . Both Tajima’s D and Fu’s FS have been shown to be conservative tests, especially with smaller sample sizes relative to R2G. pusilla west female Ne since ∼125–50 ka, reaching its lowest point at 25 ka, followed by gradual recovery, then a sharp rise in the last ∼12 ka  rise in mean female Ne. Comparing BSPs to constant demographic models supported BSP patterns. BSP models provided a better fit to the data within each G. pusilla clade , and log10 Bayes factors provided very strong evidence against constant models .Among the neutrality statistics computed for each t ∼12 ka . Easternb and S7 datasets. Eastern and western clades were diagnosable by fully-fixed differences at eight allozyme loci  than did the G. pusilla west clade (average Nei D = 0.044).The allele frequencies at 49 putative allozyme loci for the 22 sites surveyed  *BEAST Bayesian analysis revealed congruent topological relationships among Galaxiella species. These results were congruent with relationships shown by Burridge et al. G. pusilla east and G. pusilla west using a suite of non-hypervariable nuclear genetic markers (and therefore more suitable for assessing species boundaries), were also consistent with the conclusions of Coleman et al. b analysis was found between G. pusilla species, however, bootstrap support was lower between G. munda and G. nigrostriata. Relationships between Brachygalaxias samples based on cytb were congruent with recognised species, although B. gothei rendered B. bullocki paraphyletic in the S7 gene tree. Clearly, broader sampling within B. bullocki is required to clarify relationships.Both single gene analyses  and the Galaxiella species (min. age set to 14 Ma). Essentially, analyses using the older calibration point recovered mean ages slightly more than double those recovered using the younger calibration . However, their credibility interval was broader (45–72 vs. 52–66 Ma), probably due to their much larger dataset with multiple calibration points. The remaining divergences between each Galaxiella species estimated by Burridge et al. Brachygalaxias species was similar in both studies. It is also important to recognise that our estimate of 52 Ma for the separation of Australian and South American clades is only a minimum estimate. It is quite likely that the true divergence would have occurred earlier. This implies that all of our age estimates would be underestimated if the continental separation is an appropriate calibration point.Our divergence estimates varied greatly depending on whether we used the separation of Australian and South American species (min. age set to 52 Ma) or the east-west separation between ibration . When boibration  at 14 MaGalaxiella species suggest that each represents an old lineage  which also aestivates, has a similar distribution and is often sympatric with G. nigrostriataSeparation of G. pusilla species had a mean age of 5.7 Ma  at this location, although within-species genetic breaks are present in several groups G. pusilla species at first seems perplexing, as it runs counter to predictions from current drainage patterns. Based on the unique signature found at all molecular markers examined here . Five groups of populations had shared or closely related cytb haplotypes (b divergences (<0.2%): populations 11–14, 15–16 and 20–21  sites 11–14 and 17–18; (2) sites 15–16, 19, 22; and (3) sites 20–21 ; however allozymes grouped sites 6–9 together , neither of the other two predicted patterns were supported  was created during periods of low sea level, but that populations beyond this region should not show evidence for population size expansion. Our results were not consistent with this hypothesis as we recovered genetic signatures of population expansion within all populations and clades irrespective of continental shelf width , given our small-moderate population sample sizes G. pusilla east was very recent (∼3 ka), while estimates of increases in G. pusilla west population growth was slightly older (18–14 ka). These results may be more consistent with climatic changes since the last glacial maximum, primarily the amelioration of arid conditions G. pusilla species is inaccurate. Based on the between-population patterns of genetic variation reported here, it seems intuitive that the growth/expansion of both G. pusilla species likely did not occur as a clean, unidirectional spatial expansion through drainage connections; rather, it may have corresponded to a period of wholesale average change in population size, hence the number of genetic mutations. Alternatively, the broad inferred changes in population dynamics within both species may reflect changes in the amount of between-population genetic structuring, rather than changes in population size through time.Results from historical demographic analyses provide an additional perspective on the history of lf width . AlthougGalaxiella munda and G. nigrostriata show even more extreme examples of population differentiation. Overall though, patterns were broadly similar to those in G. pusilla. Some proximate populations had low divergences . Populations 24–25 were unusual in that they are separated by considerable distance, yet they were genetically quite similar , with three of its four species established by 44–15 Ma. All Galaxiella species typically have high levels of genetic divergences between all but the most proximate populations. Despite extensive drainage connections during recent low sea levels (∼18 ka) in southeastern Australia, populations in both species of G. pusilla maintain high levels of genetic structure. Broadly, the unequivocal evidence for cryptic species within Galaxiella pusilla s.l. heightens the need for conservation efforts to prevent species loss Galaxiella species imply that many populations are likely to contain unique combinations of genetic variation that will be important in planning for their long-term conservation and evolutionary potential High levels of genetic divergence and the discovery of new cryptic species have important implications for the conservation of this threatened group of freshwater species. Molecular evidence suggests that Table S1Mean genetic divergences between species for cytochrome b calculated using p-distances. The last column represents mean within species divergences.(DOC)Click here for additional data file.Table S2Mean genetic divergences between western lineage populations of Galaxiella pusilla for cytochrome b calculated using p-distances.(DOC)Click here for additional data file.Table S3Mean genetic divergences between eastern lineage populations of Galaxiella pusilla for cytochrome b calculated using p-distances.(DOC)Click here for additional data file.Table S4Mean genetic divergences between populations of Galaxiella munda for cytochrome b calculated using p-distances.(DOC)Click here for additional data file.Table S5Mean genetic divergences between populations of Galaxiella nigrostriata for cytochrome b calculated using p-distances.(DOC)Click here for additional data file.Table S6Summary of genetic diversity of cytochrome b sequences sampled within Galaxiella pusilla populations and clades in this study. Locality numbers, the number of individuals sampled, number of haplotypes (H), haplotype diversity (Hd) with its standard deviations, nucleotide diversity (π) with its standard deviations, and the results of coalescent simulations of three neutrality statistics, Tajima’s D, Fu’s FS, Ramos-Onsins and Rozas’ R2, are shown. Within-population values only represent genetically polymorphic sites; unlisted populations were monomorphic .(DOC)Click here for additional data file.Table S7Allozyme frequencies at all variable loci for the 22 sites surveyed for Galaxiella pusilla. Site codes follow Ald1*, Ald2*, Enol*, Gapd1, Glo*, Gp, Gpi2, Pgam*, and Pk*.(DOC)Click here for additional data file.Table S8Summary of pairwise comparisons of allele frequency between sites for Galaxiella pusilla east. Due to their small sample sizes, sites 16 and 20 were pooled with a geographically-proximate neighbour (sites 15 and 21 respectively). Lower triangle = number of loci displaying statistically-significant differences in allele frequency (P<0.05 after Bonferroni correction). Upper triangle = results of determining P-value for each population pair across all loci (Fisher’s method) after Bonferroni correction; *** = P<0.001, ** = P<0.01; ns = not significant.(DOC)Click here for additional data file.Table S9Summary of pairwise comparisons of allele frequency between sites for Galaxiella pusilla west. Site 9 was excluded from the analysis due to small sample size and lack of a geographically-proximate neighbour. Format as for (DOC)Click here for additional data file.