Apodemus sylvaticus was used as a model species of small and forest-dwelling mammals, which are more likely to be affected by gaps in cover such as those resulting from road construction. We confront genetic patterns from opposite and same roadsides from samples of three highways and used computer simulations to infer migration rates between opposite roadsides. Genetic patterns from 302 samples (ca. 100 per highway) suggest that the highway barrier effect for wood mouse is due to road surface avoidance. However, from the simulations we estimated a migration rate of about 5% between opposite roadsides, indicating that some limited gene flow across highways does occur. To reduce highway impact on population genetic diversity and structure, possible mitigation measures could include retrofitting of culverts and underpasses to increase their attractiveness and facilitate their use by wood mice and other species, and setting aside roadside strips without vegetation removal to facilitate establishment and dispersal of small mammals.Road barrier effect is among the foremost negative impacts of roads on wildlife. Knowledge of the factors responsible for the road barrier effect is crucial to understand and predict species’ responses to roads, and to improve mitigation measures in the context of management and conservation. We built a set of hypothesis aiming to infer the most probable cause of road barrier effect (traffic effect or road surface avoidance), while controlling for the potentially confounding effects road width, traffic volume and road age. The wood mouse  Roads are ubiquitous features of contemporary landscapes worldwide and have a considerable impact on wildlife ,2. RoadsSus scrofa it is high traffic volume [Assessing the main drivers that influence road avoidance behavior is necessary to better understand and manage this barrier effect ,13,14. Ic volume . HoweverComparison of genetic patterns has been used to assess population subdivision due to roads ,9. Our sApodemus sylvaticus, a vagile species but for which there is evidence of low road crossing rates [We focused our hypothesis testing on a small mammal, as this group can be particularly affected by the road barrier effect. For example, several studies using capture-mark-recapture and translocation techniques ,6,16,17 ng rates , being eng rates , as a seng rates , and as ng rates .We used microsatellite data to compare genetic patterns among wood mouse populations on the same and opposite sides of three highways of similar width but different traffic volumes and age. To quantify the strength of the genetic patterns, we examined if individuals from opposite highway verges were more genetically distinct than those sampled at a distance several times greater on the same side of the highway. We also estimated probable migration rates between opposite roadside populations. Studies such as this provide valuable insight for the development of appropriate measures to mitigate the road barrier effect, including prioritizing and defining the best locations and designs for wildlife passages, since their effectiveness depends on whether the animals avoid the roads themselves or the traffic they carry.(i) road width, since larger or extra traffic lanes may influence road crossing [(ii) traffic volume, as it may reduce the probability of successful road crossing [(iii) road age, as there is a time lag between landscape change and its effect on spatial genetic patterns [The sampling sites were located along three highways on the Iberian Peninsula, one in Portugal and two in Spain . The widcrossing ,28, and crossing ,17; (ii)crossing  and eliccrossing ; and (iipatterns .Quercus suber) and holm oak (Q. ilex), with an understory composed of a mosaic of crops, grasslands, shrublands, fallow lands, and by extensive farming and livestock [Cistus, Erica, Lavandula, and Ulex. The sampling sites were chosen to be in areas where the highways pass through dense montado , since wood mice may be less abundant in more open woodland [We sampled fenced highway verges, which are known to host high densities of wood mice ,33. The ivestock . Shrublawoodland ,37.For each highway, we analyzed two sampling sites to assess the consistency of genetic patterns, with each site comprising two trap lines (one in each side of the highway). Distance between sites was ca. 3500 m for AP6, 1500 m for A2 and 1200 m for AP51, and the minimum distance between the Spanish highways (AP6 and AP51) was 13 km. Distances between sampling sites were greater than four home range diameters  of the largest territories reported for wood mice, ca. 5.04 ha . ConsideHighways in the Iberian Peninsula have numerous regularly spaced culverts (about one per km) for water drainage. Close to the sampling sites, there was a culvert in the first site of A2 and AP6. The first A2 site also had an overpass nearby, while both the first AP6 site and the first AP51 site had a nearby underpass. There was a viaduct in between the A2 sites (ca. 500 m in length and about 100 m from the first site) and in between the AP6 sites (ca. 200 m in length and about 150 m from the second site), and an overpass between the AP51 sites at about 130 m from the first site.™ live traps, placed 10–20 m apart, mostly in the highway verges and where higher capture rates were expected (near oak trees or shrubs), along ca. 400 m of the highway and up to 50 m from the pavement. Where required, oral permission to access private land to conduct the study was obtained from the owners. Permission to access highway verges was obtained from highway companies. Bread fried in rancid oil was used as bait and cotton-nesting material was provided inside each trap as bedding to protect captives from low temperatures. In addition, traps were hidden under vegetation cover to protect animals from adverse weather conditions and to avoid detection by predators. Traps were reviewed at dawn to minimize the time that animals were kept inside.Sampling was conducted between February and May of 2010. At each study site, sampling was carried out until about 25 adult wood mice were sampled from each side of the highway, which was generally achieved in less than 15 consecutive sampling days. Each trap line had 60–100 baited ShermanEach individual captured was weighted, sexed and marked with a fur-clipping code denoting trap line identification, and released at capture location. Individual marking aimed to detect road crossings and to avoid resampling individuals. Individuals of less than 15.5 g were classified as juveniles and those above this weight as adults ,40. For Capture and handling of animals were in conformity with Portuguese and Spanish nature conservation directives  and in compliance with the European Communities Council Directive 86/609/EEC for animal experiments, and were carried out under the permit of Dirección General del Medio Ambiente de la Junta de Castilla y León  and of Instituto da Conservação da Natureza e das Florestas (254/2009/CAPT). The ethics committee for Animal Care and Use from the Faculdade de Ciências da Universidade de Lisboa—Organismo Responsável pelo Bem-Estar dos Animais, ORBEA—approved all procedures for capture and handling (form 1/2015 ORBEA).Apodemus sylvaticus, A. agrarius, A. flavicollis and A. draco: As7, As11, As20 and As34 [Genomic DNA was extracted from all samples using the EZNA Tissue DNA Kit (Omega BioTek) following the standard protocol for animal tissue. We obtained complete multilocus genotypes by PCR amplification of nine microsatellite loci isolated from and As34 , TNF(CA)and As34 , SFM2 [4and As34 , and SCFand As34   and linkage equilibrium using, respectively, a probability test and a likelihood ratio test in the program GENEPOP 4.2 . We usedd method . We calcd method . We usedd method ,53 to ded method  in GENALFST, specified by the user, and the population samples are used for testing the null hypothesis of genetic homogeneity. We tested three scenarios for an FST of 0.008 , i.e. an estimate of power, was determined using Fisher’s method to combine exact P-values across loci.We evaluated the statistical power of the microsatellite data set to detect population differentiation using POWSIM 4.1 . This prFST and related measures, and allele frequency-based genetic distance.To compare genetic differentiation patterns between highways we performed different analyses, as the lag time for detecting a new barrier can be highly dependent on the analytical techniques used ,56,57. TGenetic differentiation was tested in GENEPOP using a log-likelihood (G)-based test , withoutFST [G”ST [DEST [GenoDive 2.0b24 [FST) estimates with an ENA  correction. We also used the chord distance (Dc) [Dc has been applied in landscape genetic studies [FST in detecting the effects of recent barriers to gene flow [We estimated FST  and, becST [G”ST  and DESTST [DEST  using Gee 2.0b24 . Signifie 2.0b24  to obtaince (Dc)  to measu studies ,66, bein studies . Also, aene flow . Chord dFor the genetic differentiation estimates, we compared results across roadsides against those from same roadside using a differentiation index (dGD) ,68. We cTo estimate migration rates between opposite roadsides, we carried out computer simulations parameterized for five variables . SimulatNe, estimates from LDNe [Simulated populations had 54 individuals . rom LDNe ,75, a nuFST, G”ST, DEST and observed heterozygosity (Ho) in each generation, based on samples of 25 individuals from each population. From these datasets we plotted the 5–95% envelope and superimposed the observed values for comparison.Simulations were run for 1000 generations and the barrier was introduced at generation 500. One thousand replicates were computed for each of the five tested between-roadside migration rate values. Simulations were performed in a model written in NetLogo 5.3  that mimNe for the roadside sites, for the other parameters we did not have empirical results and thus the chosen values were taken from the literature (mutation rate) or subjective guesses (e.g. same roadside immigrants). Therefore, in order to understand how the model parameters could have affected our results, we performed a sensitivity analysis to explore multiple model parameterizations , but there were no recaptures on opposite sides of the highways, i.e. no road crossings were detected.NullFreq indicated a higher frequency of null alleles at the same locus, but the estimated null allele frequencies for As11 were greater than 0.1 only in four of the 12 sampling lines, and never exceeded 0.2  also suggested that the possible presence of null alleles did not introduce a significant bias in our analyses. Significant linkage disequilibrium was found only between loci As20 and As34 at two sampling lines of highway A2 and between As20 and SCFM9 at two sampling lines of highway AP6. Therefore, we decided not to exclude any loci from further analyses. Overall, our data indicated similar levels of genetic variation, inbreeding and relatedness among the 12 sampling lines, with the mean number of alleles per locus ranging from 13.3 to 17.0, the mean observed heterozygosity from 0.76 to 0.85, the inbreeding coefficient from 0.09 to 0.17, and the mean pairwise relatedness from 0.02 to 0.06 . Based on the POWSIM analyses, the statistical power of our microsatellite panel for detecting genetic differentiation was high, with a probability of 85% or more of detecting FST ≥ 0.008.We genotyped 302 adults , corresponding to a minimum of 23 samples per sampling line. There was no missing data . The errFST and related metrics (p<0.05) and the estimates of genetic distance Dc  both between opposite roadsides and same-roadside sampling lines for all three highways. This was corroborated by the significant values of  Dc Figs . Values Dc between opposite and same-roadside sampling lines provided evidence for higher average across-road differentiation for highways AP6 and AP51 (FST were similar (not shown).The resampling-based test for differences in genetic distance and AP51 . For higFST, G”ST, and DEST  could be interpreted as suggesting high migration rates between opposite sides of highways, but genetic differentiation measured by FST is constrained when within-population heterozygosity is high [FST, but much shorter using standardized GST. Actually, the magnitude of standardized GST values we found between opposite roadsides is comparable to that obtained between populations 0.85–3 Km apart in a study of microgeographic structure in wood mice [The low  is high ,103,104, is high  showed tood mice .FST values between highway sides: 0.018–0.048 [FST with high subpopulation heterozygosity [FST. This lag time should increase with larger Ne, and this reasoning has been used to explain the lack of genetic differentiation between common vole Microtus arvalis populations separated by a 25-year-old motorway [Myodes glareolus populations separated by a highway of the same age could be expected because such time period corresponds to 25–50 generations of bank voles. In the common vole study, support for the inference of a very large Ne may be due to the assumption that the motorway led to two completely isolated populations, which might be an extreme scenario given the evidence of road crossing attempts by the species [Similarly to our case, previous road genetic studies in small mammals have found non-significant or low 18–0.048 ; 0.0018 18–0.048 ; and 0.018–0.048 . This mazygosity  or the lmotorway . In contmotorway  asserted species ,106. Mor species ,68, with species ,107 and  species ,68.Ne for the roadside sites ranged between 20 and 100 , is not likely to mistake a population with moderately small Ne for one with large Ne (and vice-versa), is robust to equilibrium immigration rates up to 0.1, and performs well in populations with skewed sex ratio or non-random variance in reproductive success [Nb) that produced the cohort(s) from which the sample was taken or of a quantity intermediate between Nb and Ne [Ne per generation, but the downward bias tends to be less in species in which the reproductive lifespan approaches the generation length [Ne within the range of the LDNe estimates across sampling lines. The rationale for this choice was that, given our estimates of contemporary Ne and the large annual population fluctuations of wood mice [Ne may be expected to be moderate [Ne is larger than we assumed, as possibly indicated by the values of FST (<0.05) and DEST (>0.1) between opposite sides of the highways (Table E in Ne may explain why we were able to detect significant across-road genetic differentiation after 20 generations of wood mice. It could be argued that the fact that we detected differentiation even for the newest highways (ca. 10-years-old) could be due to the relatively small roadside samples used in this study [Our LDNe estimates of  A in Ne ,97. The  success ,109,110.b and Ne ,111. Recn length   is small [In agreement with previous genetic studies pertaining to roads, which generally found reduced but ongoing gene flow between opposite roadside populations Click here for additional data file.S2 FileTable A). Original and adjusted p-values for the HWE test (Table B). Loci with possible null alleles identified by MICRO-CHECKER (Table C). Estimates of genetic diversity for each trap line (Table D). Estimates of genetic differentiation between opposite highway sides for each of the three studied highways (Table E). Estimates of genetic differentiation between same-roadside sampling lines for the three studied highways (Table F). Sensitivity analyses of FST, G”ST, DEST and Ho to variation in the model parameters: ‘Population size’, ‘Initial alleles’, ‘Mutation model’, ‘Mutation rate’ and ‘Same-roadside immigrants’ . Values of FST, G”ST, DEST and Ho through time (generations) estimated from computer simulations for different migration rates after a ‘highway’ replaces at generation 500 a previous scenario of panmixia and assuming a multigeneration Ne of 20 or 100 for each roadside site .Estimates of effective population size using LDNe and ONeSAMP ((PDF)Click here for additional data file.S3 FileCode for the simulation model.(NLOGO)Click here for additional data file.


The process of niche construction can alter the trajectory of natural selection through organism-environment feedback. As such, the mechanism and impact of niche construction can be better investigated along environmental gradients. Here we investigate how the process of niche construction affects the distribution of genotypes and fitness landscape along an environmental gradient under three selection regimes, namely heterozygote superiority, genetic loci which dictates niche construction ability being either selectively neutral or non-neutral. Using a spatially explicit cellular automaton, we show that niche construction can stratify genetic diversity by forming band-like distributions consisting of different genotypic compositions and promote reproduction isolation by forming a divide with reduced average fitness along the gradients, termed a fitness valley. The band structure and the presence of a fitness valley depend on heterogeneous environments, resource-dependent fitness and the selection acting on the gene loci affecting the niche-constructing ability. Our work adds to the growing body of evidence on criticizing species distribution models which assume that the environment alone can determine species distributions. Based on the results, we argue that conservation planning should target preserving or restoring environmental gradients. Organisms are not passively selected by their ambient environment but coevolve with their environment through either direct niche construction  or indirect life-history activities  The fitness of an organism is a rather context-based term, depending on whether its niche requirement matches the characteristics of inhabited environment. A highly fit genotype in one environment does not warrant a high fitness in other environments. Consequently, species often exhibit large variation of morphological traits and life-history strategies at regional scales e.g. . Such vaWe here investigate how the process of niche construction interacts with resources along an environmental gradient and how it further affects genetic structures and polymorphism patterns. Using a spatially explicit model of population genetics on lattices, we demonstrate the pattern of genetic diversity and population fitness along the environmental gradient. Specifically, two questions on how population genetics and fitness landscape change along environmental gradients are addressed. First, species distribution models  have been widely used in conservation management to project the potential distribution of a focal species or genotype based on detected relationships between species observed distribution and environmental characteristics e.g. . An undeSecond, to promote diversification and polymorphism in adaptive evolution, species need to possess certain reproduction barriers after disruptive selection to prohibit remixing E and AE at generation t (R) in a specific cell is governed by three processes :To examine the spatial distributions of different genotypes that differentially affect local nutrient content via the process of niche construction along a linear environmental gradient, we built a spatially-explicit individual-based cellular automaton (CA) on 200×200 lattices, where each cell contains a random-mating diploid individual with two dialelic loci where E and A contribute to a two-locus fitness, Following Laland et al. E ; A ; the coefficient A locus ) by the additive term  .where y) of the cell, k can be considered an indicator of the gradient of the environmental resource. To ensure the resource ranges from 0 to 1 along y axis we let In the individual-based CA model, we introduced a linear environmental gradient along the vertical direction of the lattices (increasing from bottom to top). Specifically, we assume that the coefficient of independent resource renewal  of this cell was then updated according to Eq.(1).where H index to describe the genetic diversity for individuals on each row in the lattices We used the Shannon S represents the number of genotypes and n. Shannon's H ranges from 0 to lnS and increases either when there is a high number of genotypes or when genotype frequencies are even. The minimum genetic diversity occurs when only one genotype exists (H  =  0), whilst the maximum genetic diversity occurs when the frequencies of all nine genotypes are equal (i.e. Hmax  =  2.198).where H index, also showed a step-wise form  of the resource-dependent component to the overall fitness, except for the extreme case when When the selection acts on locus E , , , there aE  for predicting species' potential range in novel environment, and forecasting range shift due to environmental changes. Four assumptions are typical of a SDM Individual-based models (IBMs) are a power tool to examine complex dynamic behavior and emerging patterns Speciation most often happens via allopatric divergence where new species arise from reproduction isolation after separation by dispersal barriers. Doebeli & Dieckmann


Clogging is one of the main failure mechanisms encountered in industrial processes such as membrane filtration. Our understanding of the factors that govern the build-up of fouling layers and the emergence of clogs is largely incomplete, so that prevention of clogging remains an immense and costly challenge. In this paper we use a microfluidic model combined with quantitative real-time imaging to explore the influence of pore geometry and particle interactions on suspension clogging in constrictions, two crucial factors which remain relatively unexplored. We find a distinct dependence of the clogging rate on the entrance angle to a membrane pore which we explain quantitatively by deriving a model, based on transition-state theory, which describes the effect of viscous forces on the rate with which particles accumulate at the channel walls. With the same model we can also predict the effect of the particle interaction potential on the clogging rate. In both cases we find excellent agreement between our experimental data and theory. A better understanding of these clogging mechanisms and the influence of design parameters could form a stepping stone to delay or prevent clogging by rational membrane design. Clogging is encountered at many length scales, ranging from the deposition of marginally-soluble asphaltenes at pipe walls in oil recovery256911At the microscale, clogging typically results from the accumulation of molecules or dispersed particles at a membrane surface, leading to the build-up of fouling layers; initially these reduce the permeability of channels or pores and ultimately lead to a complete blockage of the flowTo enable the development of effective strategies to delay fouling and the clogging that ensues, or to prevent it from occurring altogether, a deep understanding of the fundamental mechanisms that leads to this major source of efficiency-loss is essential, yet very incomplete to date. The size ratio of particles and constriction plays an important role, where two extremes can be identified. Either a single particle can block a constriction, for instance larger contaminants in a suspension of smaller particlesIn this paper we explore the influence of pore design and particle interactions on the clogging rate in dilute suspensions. We study clog formation experimentally using multiplexed microfluidic models for dead-end filtration and quantitative imaging. We observe a strong dependency of the clogging rate on both geometry and attraction strength. To account for these effects we derive an analytical model based on transition-state theory which provides a quantitative and predictive description of our experimental data.μm. These constrictions simulate the membrane pores and are the main site of clogging events. The thirty channels, situated next to each other, are divided in five sections of six channels. We vary the entrance pore angles, defined as θ, of the constrictions perpendicular to the flow direction between the different sections with θ = 55°, 45°, 35°, 20° and 0°. The distance between the constrictions in series  is kept constant at 50 μm. We add a contaminant filter a few hundred micrometer upstream from the entrance of the device to remove large contaminants, such as dust, as these are reported to have a strong effect on the experimental observationsWe study clogging using a microfluidic device as a filtration micromodel, inspired by previous studies567Upon flowing a purely repulsive suspension of particles, with a diameter of approximately 1/10 of the pore diameter, through our filtration micromodel, we observe a distinct sequence of events. Initially, all channels are permeated by the suspension. After some time, clogs begin to appear, after which that channel, upstream from the clog, becomes filled with a layer of densely packed particles, whereas only solvent permeates downstream from the blockade. This can be easily seen in our experimental images . As the α which has clogged as a function of time. For the purely repulsive case, we see how α grows steadily over the course of several hours. These timescales are considerably larger than those reported previously for a similar geometry with θ = 0° To characterise the statistics of clogging, we use automated image analysis to identify which channels clog when. To improve statistics, we repeat these measurements with at least 3 identical devices. We can now plot the fraction of channels As the formation of a clog requires the accumulation of multiple particles at the clogging site, a minimum clogging time must exist. In other words, at least the number of particles required to form a pore-spanning aggregate must have passed for clogging to occur. In our experiments, we flow the suspensions at high fluxes, such that this minimum time is very short compared to our experimental resolution; as such, we do not observe it with statistical significance here.To quantify these data, we fit the experimental results to a Weibull model, often used to describe the kinetics of failure processesτc is the characteristic clogging time and β the stretch exponent, which reveals information about the underlying failure lifetime distribution. We find that β is close to unity for all values of θ; this indicates a well defined failure lifetime with a narrow distribution.in which, θ → 0, the characteristic clogging time decreases by almost a factor 4 as compared to the most shallow angle we study at θ = 55° . Interestingly, we see no deviations from laminar flow, within our experimental resolution of ~1 e angles . This ilEon, that needs to be crossed before aggregation can occur , such that inertial lift can be ignoredUnder flow, particles also experience a viscous force due to fluid flow around their impermeable surface. This can be approximated using the Stokes drag, neglecting lubrication effects, as These hydrodynamic forces acting on particles at the channel walls will alter the agglomeration kinetics. To describe this, we adopt the transition-state approach of Kramers21δ is the activation length, which is the range of the attractive Van Der Waals interactions, typically of order of one to a few nanometers. In an similar way, the hydrodynamic forces on the particles that act parallel to the wall, and thus perpendicular to the wall-particle bond, will aid in the natural rate of particle dissociation:where Eoff is the depth of the attractive Van Der Waals minimum. The balance between particle attachment and dissociation gives a total rate of particle accumulation as:in which Eoff ≫ kBT. As a result koff ≈ 0, so k ≈ kon and therefore agglomeration will be irreversible. For a clog to appear, a sequence of several particle aggregation events must occur; this is also what we observe experimentally in a close-up of a forming clog at a single constriction  that the next clogging event occurs at a distance Δx, where x is the channel number. If clogging of a single channel is fully independent, we should expect P to be independent of Δx. By contrast, we find a strong exponential dependence of the clog probability; this implies that it is more likely that neighboring channels clog in sequence, somewhat like a nucleation-and-growth scenario, rather than this happening as individual and uncorrelated events. It is important to note however, that this effect is subtle as compared to the large effect of pore geometry; thus, the pore geometry dependence cannot be explained only by this cooperative effect but must result from the viscous force-induced particle agglomeration as discussed above. Finally, we observe that the cooperative effect of the filter cake is much stronger for the repulsive case, which clogs much slower. This can be understood by considering the timescale of clogging relative to the time it takes to build up a filter cake. In dead-end filtration, the latter is governed only by the fluid flux and particle concentration, and is thus independent of attraction strength. If clogging occurs rapidly as compared to the build-up of the cake, its effect will be small , are introduced to a suspension of larger microparticleskBT, al and as are the radii of the larger polystyrene particles and smaller Ludox particles respectively (as ~ 7 nm) and ϕs is the volume fraction of the Ludox particles. For our experiments we choose an attraction strength U ~ 4kBT.where μm. We flow the suspension through our devices with a constant pressure of 100 mbar, controlled with an accuracy of 0.1 mbar, applied by an Elveflow OB1-MK3. By working at a constant pressure drop across the device the flow velocity per channel is constant prior to clogging and does not responds to possible clogging events in neighboring channelsWe fabricate microfluidic devices following standard soft lithography methodsRef ~ 0.4, with a particle Reynolds number Rep ~ 6 ⋅ 10−3 and a Peclet number Pe ~ 5 ⋅ 105. These values where computed at the centre position of the bottleneck, where the flow velocity is maximum; they thus represent the upper bounds for these dimensionless numbers. This ensures complete laminar flow and domination of advective displacements of the particlesAt this pressure difference the upper bound of the fluid Reynolds number becomes The flow through the channels is imaged with brighfield microscopy (Zeiss Axiovert 200) aqcuiring images at one frame per second. Examples of the images we obtain during the experiments can be found in How to cite this article: van de Laar, T. et al. Transition-state theory predicts clogging at the microscale. Sci. Rep.6, 28450; doi: 10.1038/srep28450 (2016).


Coilia nasus, and assess the contemporary possible genetic barrier between the west and east coastal waters of the East China Sea, we used amplified fragment length polymorphism (AFLP) markers to detect the genetic structure of C. nasus, in the East China Sea and Yellow Sea. Eighty-one individuals of C. nasus were collected from five locations and 12 individuals of Coilia mystus were sampled from the Yangtze River Estuary. A total of 371 loci were detected by five primer combinations, 310 of which were polymorphic (83.56%). Analysis of molecular variation (AMOVA) and pairwise fixation index (FST) revealed significant genetic differentiation among five samples, indicating limited gene flow among populations. The dendrogram for populations by neighbor-joining (NJ) cluster analysis provided evidence of a clear relationship between genetic and geographic patterns, supporting significant genetic differentiation between China coastal populations and Ariake Sea populations. Compared to the genetic divergence between C. nasus and C. mystus, the level of genetic differentiation between China and the Ariake Sea populations of C. nasus is obvious below the species level, indicating isolated populations of C. nasus in the Ariake Sea. Isolation by distance analysis revealed that direct ocean distance with deep-water at the continental slope and high salinity between west and east coastal waters of the East China Sea served as major physical barrier to C. nasus, supporting the coastal dispersal pattern in this estuarine species, and rejecting offshore dispersal strategy.In order to ascertain the taxonomic status of the Ariake Sea population of Japanese grenadier anchovy,  A continuing challenge in evolutionary biology of marine species is to understand the process by which populations become genetically distinct, in a fluid ecosystem that tends to homogenize populations . GeneticCoilia nasus, is a small to moderate-sized fish species belonging to the family Engraulidae, and is widely distributed in the Yangtze River and other major rivers, localized in the coastal waters of China, and Korea as well as the Ariake Sea of southwestern Japan [C. nasus have been found in the middle and lower reaches of the Yangtze River basin: A resident population and an anadromous population , according to the spatial structures of fish communities on the continental shelf of the East China Sea. Fish communities in East China were classified into the three groups. C. nasus belonged to the offshore community [C. nasus in China coastal waters were well studied by molecular markers and morphological characters [C. nasus in Japan. Yuan and Qin (1985) considered individuals of C. nasus from the Ariake Sea as a unique population, which distinguished it from the Chinese population on the basis of morphological differences [C. nasus showed reciprocal monophyly in the populations between China and the Ariake Sea of Japan [C. nasus? Which factor(s) might drive this phylogeographic pattern of C. nasus? Among the molecular markers available for analysis of population genetic structure, amplified fragment length polymorphism (AFLP) markers are characterized as suitable identification of individuals and populations due to their hypervariability, abundance and neutrality [ C. mystus as an outgroup, and to elucidate genetic barriers in this species. The coastal dispersal model proposed by the mtDNA marker was also tested in this study.Japanese grenadier anchovy, rn Japan ,13. Baseiewed in ). The fof spring . The eggironment . The disommunity . The genaracters ,18,19,20ferences . Based outrality ,23. To aC. nasus and C. mystus by the five primer combinations, 310 of which (83.56%), were polymorphic  and Nei’s genetic diversity (0.1016) was population Zhenjiang in the Yangtze River, whereas that with the lowest value was population Kashima in the Ariake Sea. The proportion of polymorphic loci and Nei’s genetic diversity of population Kashima was 30.00% and 0.0554, respectively. The genetic diversity of the Dongying population in the Yellow River showed a median value between the Yangtze River and the Ariake Sea populations.Population of C. nasus . The proK was 2, which revealed the Ariake Sea cluster and China cluster  . Moreover, pairwise fixation index (FST) values among populations of C. nasus were also significant (p < 0.001), ranging from 0.0732 to 0.2749 , whereas the genetic difference between Yanagawa and Kashima was the smallest . Genetic distance analysis suggested that the Zhenjiang and Kashima populations were the most different genetically (D = 0.1337), whereas the most similar populations were Yanagawa and Kashima (D = 0.0551)  , suggest< 0.001) . Genetico 0.2749 . These a 0.0551) . Further 0.0551) . Althoug 0.0551) .r = 0.90) between FST/(1 − FST) and coastal distance than that between STF/(1 − STF) and oceanic distance (r = 0.50), indicating isolation by costal distance  were used in isolation by distance (IBD) analysis. Among sample sites, the Mantel test indicated a more close relationship .C. nasus and the ocean distance between the Yangtze River and the Ariake Sea as genetic barrier proposed by previous mtDNA markers were supported by our AFLP results. The plot of FST/(1 − FST) and geographic distances (coastline distance and ocean distance) revealed a strong pattern of isolation by distance under the coastal dispersal model in C. nasus, which indicates that ocean distance separating western and eastern East China Sea is sufficiently large to restrict gene flow between samples. What about the mechanism that the ocean distance performs as genetic barrier to the dispersal of C. nasus? Considering the life history of this species and physical environment in the East China Sea, it is reasonable that large ocean distance is a physical barrier for an anadromous and estuarine species. As an estuarine species, C. nasus is sensitive to the high salinity (>30) [ C. nasus in marine waters was limited by depth (<60 m) [C. nasus.Besides historical factors, contemporary environmental factors also play a pivotal role in shaping the present-day phylogeographic pattern. Considering the population cluster tree and Bayesian analysis, the Dongying population may be genetically intermediate between Nantong/Zhenjiang and Ariake Sea samples, which coincide with the previous mtDNA result . The coaty (>30) . Additio (<60 m) . The ave (<60 m) . TherefoC. nasus from the Ariake Sea along the Korean Peninsula coastline. The present study revealed large ocean distance between the Yangtze River Estuary and the Ariake Sea was an effective contemporary physical barrier for estuarine species on both sides of the coastal waters of the East China Sea. This finding answered the unresolved question proposed by previous phylogeographic studies in the Northwestern Pacific. What is the contemporary environmental factor to maintain the genetic differentiation? The large ocean distance is the contemporary environmental factor to maintain the genetic differentiation of some species, especially the estuarine species. We surveyed the public genetic studies of estuarine species in the study area, which supported this inference. For example, three mtDNA distinct lineages were observed in redlip mullet Chelon haematocheilus, which was the typical estuarine species in the Northwestern Pacific [C. nasus, samples of Dandong from northern Yellow Sea near Korean Peninsula coastline and Tianjin from Bohai Sea were likely genetically intermediate between the East China Sea and the Japan coastal populations of C. haematocheilus. The three lineages of C. haematocheilus were thought to diverge in the three marginal seas during the Pleistocene low sea levels. The large ocean distance was the plausible reason to prevent the dispersal between China coastal waters and Japan coastal waters. Similar results were also observed in Trachidermus fasciatus [T. fasciatus based on SSR markers and they coexisted in the sample of Rongcheng from the northern Yellow Sea. Historical isolation associated with the present large ocean distance barrier has been the general explanation to elucidate the evolutionary mechanisms shaping the genetic population structure for these species.From our AFLP data and previous ISSR and mtDNA results ,20, a cl Pacific . The genasciatus . Two disLateolabrax japonicus and L. maculates [Lateolabrax species. The ocean distance between China and Japan served as a physical barrier to prevent secondary contact for Lateolabrax populations after isolation events and create allopatric speciation. Besides estuarine species, some phylogeographical pattern of some marine species in the study area can also be interpreted by this general explanation. Two geographic clades (the China and Japan clades) were detected among populations of white croaker Pennahia argentata by AFLP markers and mtDNA control region [This general explanation can also be used to explain the species divergence between aculates , which wl region ,30. Histl region . The PatEngraulis japonicus and Japanese Spanish mackerel Scomberomorus niphonius in the Northwestern Pacific revealed no significant genetic differentiation [However, the ocean distance serving as physical barrier is only applied in estuarine species, not in pelagic species. The genetic study of typical pelagic species Japanese anchovy ntiation ,33, indiC. nasus were collected in five sites along Chinese and Japanese coastal waters, including two locations (Zhenjiang and Nantong) from the Yangtze River, one location (Dongying) in the Yellow River Estuary, and two locations (Kashima and Yanagawa) from the Ariake Sea  and Wang et al. (2000) [ et al. (1979) [Genomic DNA was isolated from muscle tissue by proteinase K digestion followed by a standard phenol–chloroform method. DNA was subsequently resuspended in 100 μL of TE buffer . Procedures of AFLP were essentially based on Vos. (2000) ,34. PCR . (1979) . Sequenc i.e., with fragmented genomic DNA on agarose gel, were not used. Individuals with odd profiles, i.e., where most of the bands are not observed in other individuals, were discarded. Proportion of polymorphic loci, Nei’s genetic diversity were calculated by POPGEN (http://cc.oulu.fi/~jaspi/popgen/popgen.htm). Similarity indices were calculated using the formula S = 2Nab/(Na + Nb), genetic distances between individuals were computed using the formula D = −lnS [D in Mega 5.0. Population structure of C. nasus was investigated using the molecular variance software package (AMOVA) and F-statistics in AFLP-SURV [ et al. [AFLP bands were scored for presence (1) or absent (0), and transformed into 0/1 binary character matrix. Clearly readable AFLP bands were scored. The scoring process was performed visually three times to help ensure correct genotyping. Negative controls were run at each step of the AFLP process to check for exogenous contaminations. Samples with poor DNA quality,D = −lnS . GeneticFLP-SURV . The spaFLP-SURV . This pr[ et al. .FST/(1 − FST) were plotted against geographical distance  between sample sites of C. nasus. The strength and significance of the relationship between genetic distances and geographic distances was assessed using reduced major axis regression and Mantel tests using IBDWS (Isolation by distance web service at http://ibdws.sdsu.edu/~ibdws/). Geographical distances among samples were measured both following the coastline  and by shortest distance across open waters (ocean distances = OD). Under a coastal model of dispersion, distances between Nantong/Zhenjiang and Ariake Bay samples are longer than under the oceanic model.To test for isolation by distance , pairwisC. nasus and the contemporary physical barrier for estuarine species proposed by mtDNA results. The south to north unidirectional dispersal route of C. nasus from the Ariake Sea to Yellow Sea was our new finding. The coastal dispersal model might be one common dispersal pattern for estuarine species. The present study sheds light on some of the evolutionary mechanisms underlying the genetic differentiation for estuarine species in the Northwestern Pacific.Our results assessed the level of genetic differentiation between China and Ariake Sea populations. We confirmed the coastal dispersal model in


We have developed a multiplex assay covering 16 microsatellite loci, amplified in four polymerase chain reaction (PCR) assays, and loaded on the ABI DNA Analyzer in two separate panels. The assay was tested on 603 individuals originating from wild populations and hatchery stocks of Atlantic sturgeon. The assay was also tested on 12 individuals of European sturgeon and appeared to be almost equally useful. The multiplex assay designed in this study can be successfully applied in studies requiring high genetic resolution, such as relatedness analysis, selective breeding programs, and stock identification of Atlantic sturgeon.The online version of this article (doi:10.1007/s13353-014-0216-y) contains supplementary material, which is available to authorized users. Acipenser oxyrinchus) and European (A. sturio) sturgeons belong to the Acipenseridae, considered one of the most endangered fish families , and for planning captive breeding programs and population management , and large allele dropouts. These analyses were performed for the whole dataset and each of the five most numerous wild populations, using 1,000 randomizations and 95 % confidence interval (CI). The Brookfield 1 (Brookfield A) and probability of identity (PI and PIsibs) were calculated using GenAlEx v.6.5 software  using maximum likelihood based on the expectation–maximization (EM) algorithm. Observed heterozygosity (HO), expected heterozygosity (HE), and linkage disequilibrium between pairs of loci using 16,000 permutations were estimated with Arlequin v.3.5.1.2 (Excoffier and Lischer Peak Scanner v.1.0 software (Applied Biosystems) was used to bin, score, and output the microsatellite data. Micro-Checker v.2.2.3  forward primer for locus Ls-68 (mix 4) could form dimers. However, the amplified products were, nevertheless, clearly distinguishable and easy to score. The obtained allele ranges for each locus of the 603 individuals belonging to the main distribution area of Atlantic sturgeon were non-overlapping   could exhibit stuttering according to Micro-Checker and four loci  could be biased with null allele presence, with the frequency exceeding 0.05 for both tests . The highest An values, reaching 0.10, were obtained for AoxD297. However, as the most polymorphic locus, we consider this to be a valuable member of the multiplex assay. The An values obtained for other loci were usually close or equal to zero. The occurrence of null alleles in a large sample of individuals representing populations from a very broad geographic range is not a surprise considering the high mutation rates of the microsatellite loci ranging, on average, 5 × 10−4 per generation  to 36 (AoxD297), and averaged 15.2 per locus, making this multiplex assay a valuable tool for population analysis. Observed heterozygosity also varied strongly between the loci, often departing from the mean value of 0.60. The PIC values, which depend on both allele frequency and heterozygosity, varied between 0.17 for AoxC45 and 0.89 for AoxD234 and AoxD241. As expected, all indices of genetic polymorphism were lower for the hatchery population than for wild fish, presumably as a result of using a limited number of spawners for reproduction . For five loci, the optimal annealing temperature had to be lowered to 58 °C , and 54 °C (AoxD242) for successful amplification, but even at these temperatures, the amplification of AoxC45 and AoxD242 remained problematic. Four loci seemed to be monomorphic , the allele range sizes of Atlantic and European sturgeons did not overlap. These loci together could serve as a powerful tool for species or hybrid identification. Chassaing et al.  assays and loaded on the ABI DNA analyzer in two separate panels, can be successfully applied in the genetic analysis of populations and relatedness assignment in captive breeding programs of Atlantic sturgeon. The optimized microsatellite set may also be used for European sturgeon; however, for optimal results in this case, we recommend the addition of loci designed specifically for this species Supplementary Table 2(PDF 242 kb)Supplementary Fig. 1Multiplex PCR loading panels showing allele size range and colors assigned to microsatellite primers labeled with 6-FAM, Hex, and TAMRA for the 603 analyzed specimens of Atlantic sturgeon. (PDF 214 kb)Below are the links to the electronic supplementary material.


Ramburiella hispanica). In particular, we predict that agricultural lands constitute barriers to gene flow and hypothesize that fragmentation has restricted interpopulation dispersal and reduced local levels of genetic diversity. Our results confirmed the expectation that isolation and habitat fragmentation have reduced the genetic diversity of local populations. Landscape genetic analyses based on circuit theory showed that agricultural land offers ∽1000 times more resistance to gene flow than semi-natural habitats, indicating that patterns of dispersal are constrained by the spatial configuration of remnant patches of suitable habitat. Overall, this study shows that semi-natural habitat patches act as corridors for interpopulation gene flow and should be preserved due to the disproportionately large ecological function that they provide considering their insignificant area within these human-modified landscapes.Anthropogenic habitat fragmentation has altered the distribution and population sizes in many organisms worldwide. For this reason, understanding the demographic and genetic consequences of this process is necessary to predict the fate of populations and establish management practices aimed to ensure their viability. In this study, we analyse whether the spatial configuration of remnant semi-natural habitat patches within a chronically fragmented landscape has shaped the patterns of genetic diversity and structure in the habitat-specialist esparto grasshopper ( Anthropogenic habitat fragmentation has altered the distribution and population sizes in many organisms worldwide and can be considered one of the major threats to biodiversity  . This Mediterranean orthoptera exclusively inhabits esparto grass formations (e.g. Stipa tenacissima and Lygeum spartum), which in La Mancha region are ubiquitous plant species in any remnant semi-natural nonagricultural land. We first characterize the habitat of the species in the study area and use circuit theory to generate different isolation-by-resistance (IBR) scenarios and test the relative importance of geographical distance and the distribution of suitable habitats on contemporary patterns of genetic differentiation 2SO4, 0.01% Tween-20, EcoStart Reaction Buffer; Ecogen, Madrid, Spain), 2 mm MgCl2, 0.2 mm of each dNTP, 0.15 μm of each dye-labelled primer  and 0.1 U of Taq DNA EcoStart Polymerase (Ecogen). The PCR programme used was 9 min denaturing at 95°C followed by 40 cycles of 30 s at 94°C, 45 s at the annealing temperature (GeneMapper 3.7 (Applied Biosystems).We used a salt extraction protocol to purify genomic DNA from a hind leg of each individual . We used ArcMap 10.0  to create a vector layer that was then transformed into a raster grid (pixel size = 50 m) to be used in subsequent landscape genetic analyses (see below).In our study area, the esparto grasshopper distributes in areas with formations of the host plants AR) standardized for sample size using the program HP-Rare  using FSTAT (Goudet AR and HE) across the studied populations of esparto grasshopper. We considered four explanatory variables: (i) the proportion of suitable habitat  within a 1 km radius of the sampling site, which we hypothesize to be associated with local effective population sizes (Ne)  of each population with all other populations, an estimate of population isolation  calculating the difference between the AICc value of each model and the minimum AICc obtained among all competing models (i.e. the best model has ΔAICc = 0). Models with ΔAICc ≤ 2 were considered equivalent . The effect of predictor variables was considered significant if the 95% CI of their estimators did not cross zero  to analyse differences between males and females in interpopulation genetic differentiation (FST), deviation from Hardy–Weinberg equilibrium (FIS), mean assignment index (mAIc) and variance of the assignment index (vAIc)  Gaussian model of admixture with a linear trend surface  and the interaction parameter (w) were initially set to α = 0.99 and w = 0.6. We used deviance information criterion (DIC) values and stabilization of the Q-matrix of posterior probabilities to determine the optimal number of clusters (i.e. Kmax) for the data. Once Kmax was deduced, 180 additional replicate runs were conducted to yield a total of 200 replicate runs for Kmax. We used the 10 runs with the lowest DIC values to calculate average individual admixture proportions with Clumpp 1.1.2  that a priori are the most likely to determine the distribution and dispersal patterns in our study species. We generated different IBR scenarios assigning a range of resistance values to both habitat classes . This matrix of flat resistance distances is expected to yield similar results than the matrix of Euclidean geographical distances, but the former has been suggested to be more appropriate for comparison with models of IBR generated with Circuitscape  approach (Wang R2) with varying levels of ‘natural vegetation’/‘agricultural land’ resistance ratios  and different IBR scenarios on observed patterns of genetic differentiation McRae . We usedme McRae . We usedses Table. This alses Table. To test.3 Ersts . We alsoach Wang . We usedach Wang . Finally≥0.20; RhA105, RhA112, RhA2 and RhC2) values (Ps > 0.05).All microsatellite markers were highly polymorphic across all populations, with 12–40 alleles per locus . After a) values . We did AR and HE for each population are indicated in TableAR and HE increased significantly with the proportion of suitable habitat and decreased with isolation estimated as average genetic differentiation (FST) with other populations  (P = 0.671), deviation from Hardy–Weinberg equilibrium (FIS) (P = 0.586), mAIc (P = 0.959) and vAIc (P = 0.348) did not differ between males and females. Individual-based analyses in Tess resulted in a Kmax = 4, but three genetic clusters were scarcely represented in most populations  and they were not significantly associated with genetic differentiation, either when they were included alone in the model (TablePs > 0.2). However, genetic differentiation was positively and significantly associated with those IBR matrices considering the minimum resistance for ‘natural vegetation’ habitat (=1) and high resistance values for ‘agricultural land’ (>50)  and flat resistance distances were highly correlated  Table. Model ff R2 Fig.; Table2.FST values  was not significant and model fit increased with higher ratios of agricultural land/natural habitat resistance Fig., indicatAnalyses of genetic diversity have shown that the proportion of suitable habitat around sampling sites is positively associated with local levels of genetic diversity, suggesting that populations located in less fragmented habitat patches sustain higher effective population sizes . Thus, a general recommendation derived from both this and previous studies in the area would be implementing management practices aimed to promote the conservation of organisms that are ecologically dissimilar, but prioritizing those species that are dispersal-limited and more likely to benefit from increasing or maintaining population connectivity (Gaublomme et al. Our study indicates that a few remnant semi-natural habitat patches within a chronically and extensively fragmented landscape act as functional corridors that facilitate interpopulation gene flow and shape local levels of genetic diversity in the esparto grasshopper. These results, in conjunction with those of previous studies, indicate that the impact of land clearing for agriculture on dispersal patterns and gene flow can strongly vary even among related organisms that are expected to similarly respond to habitat fragmentation (Lange et al.


Ambrosia artemisiifolia L.), a highly allergenic invasive species causing substantial public health issues. To do so, we looked for recent evolutionary change at the upward migration front of its adventive range in the French Alps. Based on species climatic niche models estimated at both global and regional scales we stratified our sampling design to adequately capture the species niche, and localized populations suspected of niche expansion. Using a combination of species niche modeling, landscape genetics models and common garden measurements, we then related the species genetic structure and its phenotypic architecture across the climatic niche. Our results strongly suggest that the common ragweed is rapidly adapting to local climatic conditions at its invasion front and that it currently expands its niche toward colder and formerly unsuitable climates in the French Alps (i.e. in sites where niche models would not predict its occurrence). Such results, showing that species climatic niches can evolve on very short time scales, have important implications for predictive models of biological invasions that do not account for evolutionary processes.Climatic niche shifts have been documented in a number of invasive species by comparing the native and adventive climatic ranges in which they occur. However, these shifts likely represent changes in the realized climatic niches of invasive species, and may not necessarily be driven by genetic changes in climatic affinities. Until now the role of rapid niche evolution in the spread of invasive species remains a challenging issue with conflicting results. Here, we document a likely genetically-based climatic niche expansion of an annual plant invader, the common ragweed ( Biological invasions alter the structure of native communities and can disturb ecosystem functioning worldwide . The eveShifts in climatic niches have already been documented in a number of invasive species, by comparing the native and adventive climatic ranges in which they occur ,9. HowevThe critical processes allowing niche and range expansion are known to occur at species' range margins . On the Ambrosia artemisiifolia L., Asteraceae) at its upward migration front in the French Alps. We first measured both the climatic niche of the invader in the French Alps , and its global climatic niche that combines all known native (North America) and introduced ranges throughout the world . This global niche estimates the full range of environmental conditions under which the species has been observed to survive, and thus approximate the “true” physiological limitations of the species, that is its fundamental niche [Here, we developed an original approach combining species’ climatic niche models at different spatial scales, population genetics and a common garden experiment to identify and localize rapid climatic niche expansion in the common ragweed  is a North American diploid annual weed that was transported with seed crops and forages about 150 years ago into several distinct locations across Eurasia, Australia and South America. The species has been continuously spreading since then, reaching the French Alps about sixty years ago [The common ragweed , according to a former work [A. artemisiifolia over the world. These distribution data were assembled from the Global Biodiversity Information Facility  at a minimum resolution of 2.5 arc-minutes (c. 4.5 km), and 20,000 background data from realistically reachable locations (within a buffer zone of 20 km around any presence record). Five uncorrelated climatic variables were extracted from WorldClim at a resolution of 2.5 arc-minute : maxima [et al.  for furtA. artemisiifolia (source CBNA) at 100m resolutions and 10,000 background data randomly selected in the study region, with the same procedure as for the global niche. Because we wanted to do both: stratify our sampling with the regional niche model, and provide an ecological understanding of the evolutionary processes occurring along the regional niche gradients, we needed to use a restricted number of environmental variables to estimate this niche. Based on a principal component analysis (PCA) run over 21 climatic and topographic variables at a resolution of 100m  were then tested using regression models  following a stepwise AIC procedure. Since genetic diversity should decrease as a result of selective pressures, we expected that He would be lowest at sites where the species is suspected to be adapting to new environmental conditions, and away from source populations. Similarly, FST should increases in populations highly differentiated from their ancestral populations (i.e. source populations), we thus expected a high FST in populations at the leading invasion front if they are little connected by dispersal. To investigate the genetic structure of the populations we used the Bayesian clustering program structure 2.3 [geo) and environmental distances  using Mantel tests with 999 randomizations  selected to be representative of the regional niche, including seven ones which were predicted to occur out of the species global niche (no specific permission were required for sampling at these locations since the studied species is a noxious invasive weed). The sampling was designed in a way that populations in similar environmental conditions were not spatially clustered . After Dradients . Second,rsity He  (see S1 ture 2.3  from whiage ade4 ).A. artemisiifolia in common garden or greenhouse conditions was not allowed by regional regulations: strong health issues for experimental workers and surroundings had to be anticipated. Therefore, we could also not control for maternal and epigenetic effects  the total genetic variance, or G's volume, measured as the sum of all trait variance, (2) the strength of genetic correlation, or G's shape, taken as the proportion of the total genetic variance explained by the largest eigenvector Pmax, and (3) the direction of the genetic correlations . From Gistance' ) estimatrelogram . AdditioG matrices captures genetically-based phenotypic variation  and the predicted allelic frequency in the same populations . It is important to note that observed associations between allele frequencies and traits are unlikely to be biased by the neutral genetic structure of populations because this structure is almost inexistent see  section A. artemisiifolia: temperature and radiation. Using a conservative approach, all 36 markers were excluded from the analysis of the neutral genetic structure . Analyses of allele-climate and allele-trait associations (see below) were performed for a subsample of 29 markers (out of 36) that satisfied a false discovery rate below 5%  were considered as potentially under selection, as showing a significant relationship (linear or quadratic) with at least one of the two main niche gradients of below 5% .IS = 0.441 on average, ranging from 0.110 to 0.700), but they were not significantly correlated to the niche gradients. Intra-population genetic diversity He varied from 0.035 to 0.090, and showed maximal values at the core of the temperature gradient while being reduced at the cold and warm edges , suggesting extensive gene flow between populations.Based on the remaining 204 neutral markers, we obtained generally high inbreeding coefficients within-populations , suggesting that little genetic structure exist due to spatial or environmental isolation. On the contrary and as expected, the markers suspected of adaptation (or linked to locus involved in adaptation) showed significant IBDenv  and non-significant IBDgeo .Still on the 204 neutral markers, four clusters were detected by applying the clustering algorithm STRUCTURE, with high but homogeneous levels of admixture within each population Fig D in . GloballST = 0.074, 0.078 and 0.069, respectively; Table C in ST = 0.207), an important trait for adaptation to abiotic stress [ST > FST), suggesting divergent selection on functional traits at the regional scale, potentially due to climatic gradients. Biomass was indeed related to the temperature gradient with an asymptotic relationship (reaching a maximum at high temperatures), while plant height was nearly not affected by temperature but negatively correlated with radiation. Plant shoot-root ratio and LDMC were both negatively correlated with temperature but positively with radiation  significantly decreased with decreasing temperature  was lower for cold conditions  could be explained by the ionships , are quiWe found higher phenotypic differentiation between populations than expected from demographic processes, with clinal trait variations across temperature and radiation gradients. Assuming that our common garden experiment adequately captured genetic variance, these relationships were conform to general expectations for adaptations to environmentally stressful conditions. Biomass and individual height reduction may enable plants to resist to low temperatures and high radiation and to complete their life cycle during shorter growing seasons (i.e. at high elevations). A greater investment in the above ground biomass may permit a stronger allocation to reproduction, and high leaf dry matter content confer resistance to stress by efficiently limit tissue degradation. Overall, this suggests that directional selection has acted on these traits across the species' climatic niche, favoring phenotypes with smaller stature and longer-lived leaves in populations of migration front.ST values. Moreover, Hodgins et al. [Directional selection may have been particularly important in the populations located out of the species' global climatic niche (cold and low solar radiation conditions) where estimated phenotypic evolvability has been reduced by more than 30%, relative to core and low altitude populations. Interestingly, our results diverge from those of Chun et al.  who idens et al.  also shoA. artemisiifolia during its colonization of the French Alps. Pre-introduction adaptation is unlikely to explain our results as, based on the estimation of its global climatic niche, the most adverse climatic conditions encountered in the study region have apparently never been experienced anywhere else by the species, including in other adventive regions. Our results also show that isolation by distance, and allele surfing cannot explain the genetic clines observed along the species niche gradients. Such rapid adaptation to alpine conditions has probably happened within the last decades where an increasing number of populations have been recorded at higher elevations. This process may have been fostered by its history of multiple introductions and intense human mediated dispersal, which likely increased intra-population genetic diversity in the region . This mA. artemisiifolia is currently adapting to adverse climatic conditions of alpine environments. Hence, rapid local adaptation and climatic niche expansion of such invasive species is likely to enhance its invasion rate [To evaluate whether local adaptation has permitted niche expansion, we used an innovative stratified sampling-design based on the combination of the climatic niches of the species estimated at both global and regional scales. This allowed us locating populations currently experiencing novel climatic space compared to the known species' worldwide climatic niche. This feature is obviously dependent on the ability of the climatic niche estimations at two scales to correctly detect populations occurring out of the species' global niche . In highion rate .Pmax of G matrices). Thus, the species may have a reduced capacity to adapt toward colder temperatures and lower levels of solar radiation, which may slow down its future niche and range expansion. Further empirical and theoretical simulations studies are, however, needed to prove this true, and estimate the ultimate limits to niche expansion in this invasive species.Perhaps an important finding for predicting future spread of this species in alpine environments is that forefront  populations harbor lower genetic diversity and reduced phenotypic variation than core (low elevation) populations, as expected following sequential founder effects during colonization . Indeed,ST values) could favor local adaptation by limiting gene swamping from central populations. Second, in some conditions genetic bottlenecks have the potential to maintain certain levels of genetic variance due to the change in epistatic effects or decreased dominance effects [It might appear surprising that populations at niche edges show continuous adaptation towards more alpine climatic conditions, especially despite evidence for genetic bottlenecks; however such unexpected situation has already been reported for other invasive plants . Two mec effects . TestingA. artemisiifolia is likely adapting to novel climatic conditions, two main limitations remain in our approach: the measure of genetic variance in phenotypic traits and possibly confounding maternal or epigenetic effects.Although our results indicate that A. artemisiifolia is strictly self-incompatible and shows consistently high outcrossing rates throughout its native and invasive ranges, irrespectively of population density [ST [ST-FST comparison to be rather conservative. Our jackknife procedure confirmed that our relatively low number of mother plants still allowed us to get reasonable estimate of genetic variance . Alternatively, QTL or GWAS procedures would also further reveal the genetic basis of niche expansion in this species.The second limitation concerns the use of first generation seeds potentially leading to maternal or epigenetic effects that may have inflated our estimates of population differentiation and heritability for the different traits. Using proxies to test for maternal effects Click here for additional data file.S2 AppendixG matrix analysis.These details include allele-environment tests, population genetic structure, experimental design and maternal effects, trait-niche gradient regression models, and (DOCX)Click here for additional data file.


Aedes aegypti. One of the world’s largest urban agglomerations infested by Ae. aegypti is the Brazilian megalopolis of Sao Paulo, where >26,900 cases of dengue were reported until June 2015. Unfortunately, the dynamics of the genetic variability of Ae. aegypti in the Sao Paulo area have not been well studied. To reduce this knowledge gap, we assessed the morphogenetic variability of a population of Ae. aegypti from a densely urbanised neighbourhood of Sao Paulo. We tested if allelic patterns could vary over a short term and if wing shape could be a predictor of the genetic variation. Over a period of 14 months, we examined the variation of genetic (microsatellites loci) and morphological (wing geometry) markers in Ae. aegypti. Polymorphisms were detected, as revealed by the variability of 20 microsatellite loci  and 18 wing landmarks (quantitative estimator Qst = 0.4732). These levels of polymorphism are higher than typically expected to an exotic species. Allelic frequencies of the loci changed over time and temporal variation in the wing shape was even more pronounced, permitting high reclassification levels of chronological samples. In spite of the fact that both markers underwent temporal variation, no correlation was detected between their dynamics. We concluded that microevolution was detected despite the short observational period, but the intensities of change of the markers were discrepant. Wing shape failed from predicting allelic temporal variation. Possibly, natural selection (Qst>Fst) or variance of expressivity of wing phenotype are involved in this discrepancy. Other possibly influential factors on microevolution of Ae. aegypti are worth searching. Additionally, the implications of the rapid evolution and high polymorphism of this mosquito vector on the efficacy of control methods have yet to be investigated.Scientific research into the epidemiology of dengue frequently focuses on the microevolution and dispersion of the mosquito  Aedes (Stegomyia) aegypti Linnaeus 1762 is a widely distributed mosquito vector of dengue, the most important arboviral disease in humans. The prevention and control of the dengue virus currently depend on controlling its mosquito vector. Different methods have been proposed for dengue vector control, but many of these methods are limited by the microevolution of mosquitoes.In this context, the demography, dispersion, and evolution of these insects within urban areas have been frequently investigated. Additionally, these biological issues are of importance to professionals engaged in vector control and surveillance initiatives but are far from being satisfactorily understood. Dispersal is preferably estimated by population genetics indicators, such as gene flow, migration and genetic variability, given the difficulty and low reproducibility of mark-release-recapture methods for small mosquitoes –3.Ae. aegypti throughout the world [Aedes [Genotypic markers such as Single Nucleotide Polymorphisms (SNPs) and microsatellite loci have been largely used to investigate the microevolution of he world –8, but the world , 10. Wind [Aedes .Aedes spp. [Ae. aegypti changes over short evolutionary time periods; 2) genetic microevolution can be assessed based on wing phenotype.Despite the usefulness of microsatellite loci and wing shape, these markers have been seldom combined in a single study of biological patterns of des spp. , and as des spp.  and Vidades spp. , we formAe. aegypti over 14 months using microsatellites and wing geometry as biological markers. The chosen population came from "Subprefeitura Butanta", a small, homogeneous and densely urbanised neighbourhood of Sao Paulo City (Brazil). Globally, this city is one of the largest urban agglomerations infested by Ae. aegypti, with approximately 11,000,000 people distributed over an area of 1,523 sq. km. There were 31,101 cases of dengue reported in this City in 2014, and more than 26,900 cases were reported from January to June 2015 [To test these hypotheses, we evaluated the temporal morphogenetic variations of a single population of une 2015 .Ae. aegypti were collected in “Subprefeitura Butanta”, a relatively small, geopolitically delimited neighbourhood comprising approximately 3% of the Sao Paulo municipality, which is homogeneously and densely urbanised . Specimens were obtained from six traps placed throughout the neighbourhood , winter 2011 (WIN), spring 2011 (SPR), summer 2011/12 (SUM) and autumn 2012 (AUT12) . For the loci described by Slotman et al. [Genomic DNA was extracted with the DNeasy Blood and Tissue Kit  or standard DNA isolation   estimated as described by Weir and Cockerham [st and D were computed using Genetix V4.05 [To assess the genetic stability over time, several analyses were done. Differentiation among chronological samples was examined by Wright’s F-statistics .The right wings of all 150 females were detached, mounted on slides-coverslip and photographed according to Vidal et al. . On eachWing size was estimated by calculating the “centroid size” vector . To asseWe estimated the allometric influence of wing size on wing shape through multiple regression analysis of the Procrustes coordinates vs. centroid size. We tested the statistical significance of allometry by means of nonparametric permutation tests with 10,000 iterations using MorphoJ V1.05 software. To geometrically describe wings independently from size variation, allometric effect was removed using multivariate regression.Ae. aegypti were compared regarding wing size and shape in order to evaluate the morphological variation during the observational interim (14 months). Univariate parametric statistic tests were used to compare centroid sizes: ANOVA with Tukey post-hoc test implemented using InStat [Chronological samples of g InStat .Discriminant analysis was used to explore the degree of wing shape dissimilarity among individuals in a morphospace of canonical variables . To better visualise the shape disparity among the samples, thin-plate splines were constructed based on the regression of CV1 scores on shape coordinates (TpsRegr V1.31 ). Discrist) and metric disparity among samples were estimated and statistically compared by nonparametric permutation tests  using COV software [Quantitative estimator of intra/inter group differentiation  in the morphospace of PCs is proportional to the morphological variability of that population set. In the present case, the amount of dispersion was estimated using the procedure developed by one of us (L.S.) in  and was st scores and morphological Qst scores. Based on the FCA plot, we calculated an index of “genetic diversity” using a similar method to that used to estimate the “morphological diversity” . These genetic and morphological diversities were then compared using linear correlation analysis (α = 0.05).In order to confront molecular and morphological data, a Pearson´s correlation analysis was done (α = 0.05) between phenetic and genetic distances . We also compared between FAll 149 individuals of the five chronological samples were successfully genotyped using 20 microsatellite loci. All loci were polymorphic and comprised in total 115 alleles , which were distributed as follows: 2 (AED19), 4 (C2A8), 7 (T3A7), 7 (A10), 13 (B07), 8 (B19), 5 (AC1), 3 (AC2), 2 (AC4), 6 (AC7), 5 (AG1), 18 (AG2), 5 (AG3), 4 (AG4), 5 (AG5), 7 (AG7), 3 (CT2), 5 (A1), 2 (B2) and 4 (B3). The following unique alleles were detected in AUT11: allele 229 ; allele 179 ; 168 ; 133 ; 121 and 133 ; 149 ; 176 , WIN: 177 ; 207 ; 131 ; 154  and SUM: 151   comparisons, and most loci (13 out of 20) were in HWE.Only some departures from equilibria were significant. The pair of loci AG1-AG3 was in linkage in all chronological samples. The B07, B19, AG1, AG2 and AG4 loci occasionally presented heterozygote deficits . The T3Ast), genetic distance (D), factorial correspondence analysis (FCA) and clustering (Bayesian model) based on allele frequencies indicated that genetic structure changed over time. Some private alleles were found but all of them appeared in low frequencies. Considering that high levels of null alleles and linkage of loci could bias our interpretation, we performed the analysis with and without C2A8, T3A7 and AG1 loci but the results were quite similar (not shown). The AG1 locus was discarded from the presented analysis  because it appeared in linkage not only with AG3 locus but also with other 6 loci.The analyses of genetic fixation . Pairwise D values calculated over all loci between samples ranged from 0.027 to 0.063 and revealed slight genetic differentiation. The UPGMA dendrogram based on the genetic distance matrix , as shown in st and morphological Qst, were lower in the sub-analysis .In order to evaluate the morpho-genetic syntopic variation (in a single trap location), we also did a sub-analysis with only the samples from trap T6. In this case, the most likely k was equal to 3, which is in accordance to the three seasons sampled in trap T6 . Thus, aThe mean shape temporal variation can be visualised in the thin-plate-spline series shown in st) was 0.4732.The phenogram of chronological samples based on Mahalanobis distances  corroborStatistical analysis  of the consecutive chronological comparisons revealed that wing size increased from AUT11 to WIN, remained stable during SPR, decreased to the lowest level in SUM and reached its highest point in AUT12 , which is the most syntopic sampling, is a clear demonstration of the how microevolution may occur during a short period (three consecutive seasons).The population genetics parameters  indicated that our genetic markers are representative and our geographically-restricted collecting has successfully sampled within a single deme. Variability at the microsatellite loci was high, and the rate of change was not homogeneous. Allelic frequency profiles  indicateAe. aegypti. Even in the colder season (WIN), the genetic variability was high, what is unexpected to an exotic species (Ae. aegypti is not native from the Neotropics), as introduced populations usually undergo genetic drift and founder effect. This may reflect a rich genetic patrimony and may imply adaptation of this species to new environments, which is a limiting factor to control efforts.It is not possible to do a complete comparison between our genetic results and the data available in the literature because, as far as we know, there are not other studies which comprise all the 20 loci set employed here. We can say that, in general, the population was highly polymorphic, because the observed allelic diversity and richness are seldom found in a single population of Ae. aegypti populations from other locations across the world [The loci used here exhibited, on average, similar polymorphism levels as those reported for he world , 39–42. he world  and popuhe world . At the he world , and popAe. aegypti over time has been occasionally studied. Ordinarily, allelic frequencies of microsatellites do not change greatly in a few years. For example, another population of Ae. aegypti from Sao Paulo State (Brazil) exhibited dimorphic SNPs that remained stable for 6 years [Ae. aegypti exhibited allelic variation during the transition of dry/wet seasons, possibly driven by a bottleneck effect [Aedes japonicus, which arguably occurred as a result of the merging of two genetically distinct lineages [Allelic variation in  6 years . Genetic 6 years  and betwk effect  and Olank effect  detectedlineages .Ae. aegypti from the Brazilian neighbourhood “Subprefeitura Butanta” changed over the study interval. This is the first investigative study of the temporal variation of the wing characters of Ae. aegypti.The wing shape/size patterns of Aedes albopictus [Regarding wing shape, the significant metric disparity among all samples and the high scores of cross-validated reclassifications showed that wing shape evolved and diverged during the 14 months interval, a remarkably short time period. The levels of temporal divergence were so high as to be compatible with partial population substitution, which, however, was not supported by the microsatellite results. The most similar case in the literature is a study of the congeneric bopictus , the winst indicator (0.4732), and the level of polymorphism remained high in each chronological sample during the study interval, as indicated by the morphological diversity estimates  is a nationally important centre of trade and people travelling. Even when a single trap was analysed (trap T6), both morphological and genetic variations occurred, indicating that microevolution can be detected over just a few syntopic generations.Apparently, the velocity of the microevolution of Biological and instrumental limitations prevent wings and microsatellites from being completely mutually congruent. The analysis and interpretation of microsatellites are not equivalent to that of wing morphometrics because of the distinct nature of these markers. Microsatellites are diploid, presumably neutral and independent multiallelic loci , whereas2 = 0.0845; r = -0.2908; p = 0.4151). The observed Qst value was several times higher than the Fst value, indicating that morphological variability was lower intra-sample than inter-sample. This pattern is typically interpreted as if natural selection is acting on wing shape [In fact, results of the two types of markers were discrepant and wings patterns changed faster. The oscillation of morphological diversity was uncorrelated to the genetic diversity. This analysis was not shown, but it is noticeable by comparison between Figs ng shape .Ae. aegypti from Sao Paulo City (including older samples from Subprefeitura Butanta) and observed Qst>Fst; however, wings morphology appeared to be more stable than microsatellite allelic patterns. To understand this partial contradiction between that study [Similarly, a previous paper of ours  analysedat study  and the at study  was atemIt would be reasonable to think that wing shape is under selective pressure because wings are important to flight and mating behaviour . HoweverAn alternative explanation for the observed rapid variation of the wing characters is that quantitative polygenic traits (as supposedly occurs to insect wings ) may exhAlthough the wing does not permit us to predict fine parameters of population genetics, it may be a semi-quantitative indicator of variation and variability. The fact that wing shape is sensitive to short temporal units ascribes discriminant power to these markers. However, the absence of correlation with neutral genetic markers indicate that wing shape may not be suitable to assess microevolution. This conclusion is different from that about the usefulness of wing geometry to macroevolutionary approaches. For instance, wing shape has been increasingly proven to be adequate to diagnose species and cryptic taxa , 51–55.Ae. aegypti individuals is not broad because Subprefeitura Butanta has numerous breeding sites. This assumption is in accordance with previous observations that dispersal is restricted when breeding sites are more available [In this specific ecological context, we assume that the dispersal of vailable , 56.Microevolution has relevant implications in epidemiology. Rapid allelic frequency changes may involve non-neutral characters and occasionally affect the susceptibility of mosquitoes to insecticides and chemical repellents. The successful insertion of transgenic or benign mosquito lineages may also be influenced by microevolution.Ae. aegypti should be further investigated and taken into consideration when redesigning vector control and surveillance protocols.The development of these processes is multi-causal, and a central factor is the ecological context. A comprehensive understanding of the ecological context requires careful studies that consider biotic/abiotic local peculiarities. We propose that not only the static biological patterns but also the evolutionary dynamics of S1 FigSignificant distinctions: AUT11 X AUT12 p<0.01, WIN X SUM p<0.01, SPR X SUM p<0.01 and SUM X AUT12 p<0.001.(TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Tableo, observed heterozygosity; He, expected heterozygosity; Fis, inbreeding coefficient. In bold, significant p-values (α<0.05) following Bonferroni correction (corrected α<0.0005) rejecting Hardy—Weinberg equilibrium.—not applicable.N, sample size (number of mosquitoes); AR, allelic richness; H(XLSX)Click here for additional data file.S3 TableIn bold, significant p-values (p>0.01).—not applicable.(XLSX)Click here for additional data file.