GCC  on biodiversity loss. Using 279 georeferenced Iberian accessions, we used classes of three intraspecific genetic units of the annual plant Arabidopsis thaliana obtained from the genetic analyses of nuclear SNPs (single nucleotide polymorphisms), chloroplast SNPs, and the vernalization requirement for flowering. We used SDM (species distribution models), including climate, vegetation, and soil data, at the whole‐species and genetic‐unit levels. We compared model outputs for present environmental conditions and with a particularly severe GCC scenario. SDM accuracy was high for genetic units with smaller distribution ranges. Kernel density plots identified the environmental variables underpinning potential distribution ranges of genetic units. Combinations of environmental variables accounted for potential distribution ranges of genetic units, which shrank dramatically with GCC at almost all levels. Only two genetic clusters increased their potential distribution ranges with GCC. The application of SDM to intraspecific genetic units provides a detailed picture on the biogeographical patterns of distinct genetic groups based on different genetic criteria. Our approach also allowed us to pinpoint the genetic changes, in terms of genetic background and physiological requirements for flowering, that Iberian A. thaliana may experience with a GCC scenario applying SDM to intraspecific genetic units.Genetic diversity provides insight into heterogeneous demographic and adaptive history across organisms’ distribution ranges. For this reason, decomposing single species into genetic units may represent a powerful tool to better understand biogeographical patterns as well as improve predictions of the effects of  Classical taxonomic designations  may not represent the ecological and evolutionary units that matter most to understand the mechanisms that shape biogeographical patterns. Despite its elusiveness, a species can be described as an assemblage of genetic lineages varying in their genetic inter‐relationship and spatial distribution. Such intraspecific genetic structure, whatever its extent, is accounted for by populational processes that determine allelic frequencies  and long‐term demographic fate. Hence, tackling intraspecific genetic variation is unavoidable if we aim to comprehend key topics in biological sciences including evolution, biogeography, conservation biology, and species response to climate change   to use, which in turn determines the sampling effort required for obtaining genetic data of interest , chloroplastic SNPs, and phenotypic variation in the vernalization requirement for flowering time. We have already learned that genetic variation of A. thaliana is geographically structured in the Iberian Peninsula because of the multiple Pleistocene refugia contained in the SW part of the species’ range in Eurasia  with genetic analyses using a collection of 279 populations of the annual plant Hoffmann . It is wHoffmann . We usedA. thaliana into consistent genetic units, which capture intraspecific variation from different sources of genetic variation, to better look into the effects of GCC on plant distribution ranges and genetic diversity. The sources of genetic variation used allow the inference of genetic units that capture the heterogeneous demographic and adaptive history of A. thaliana across its distribution range in the Iberian Peninsula. In this study, we address the following specific questions. First, how do SDM predict the current distribution of A. thaliana and that of its intraspecific genetic units in the Iberian Peninsula? Second, which are the environmental variables that account for the distribution of genetic units? And third, which are the main methodological limitations that have to be addressed to improve our GCC predictions based on intraspecific genetic variation?Here, we decompose Arabidopsis thaliana (L.) Heyhn. (Brassicaceae) from the Iberian Peninsula  collected during the period 2004–2009. Arabidopsis thaliana is an annual, self‐compatible, and self‐fertile plant exhibiting a persistent seed bank  using the VeraCode method through CEGEN genotyping service (http://www.cegen.org).The chloroplast genome was analyzed with 15 SNPs with an average distance of 7.6 kb between adjacent SNPs, covering most of the chloroplast genome. Eight of these SNPs were selected from DNA polymorphisms previously described in a worldwide collection of A. thaliana accession, the OVR  was quantified by calculating the proportion of nonflowering individuals when grown without a previous vernalization treatment for flowering induction, as previously described  and 4.2 ± 0.7%  of individuals with obligate vernalization requirement, respectively .For each A. thaliana accessions based on nuclear SNPs were assessed by Bayesian means using the model‐based algorithm implemented in STRUCTURE v.2.2. . STRUCTURE inferred four genetic clusters in the Iberian Peninsula , which was consistent with previous studies , 0.60 ± 0.02 (N = 58), 0.80 ± 0.03 (N = 38), and 0.75 ± 0.03 (N = 33) for genetic clusters C1, C2, C3, and C4, respectively. In this study, we assigned each accession to the genetic cluster whose membership coefficient was equal or higher than 0.5, giving a total of 116, 36, 31, and 29 accessions for genetic clusters C1, C2, C3, and C4, respectively.The genetic relationships among All 15 chloroplast SNPs were polymorphic and yielded 14 chloroplast haplotypes, that is, chlorotypes. The relationship among chlorotypes was analyzed using the median‐joining algorithm implemented in NETWORK v.4.6.1.2. . Accessions were classified into three chlorotype groups  based on the topology of the chlorotype network . The final number of accessions included in each chlorotype group was 102 for A (6 chlorotypes), 63 for B (5 chlorotypes), and 16 for C (3 chlorotypes), respectively .A. thaliana as species and of each of its genetic units. Finally, we projected the model into a GCC scenario.We used MaxEnt v.3.3.3k , the CORINE Land Cover 2000  and the Soil Geographical Database from Eurasia v.4 , respectively.We considered three sources of environmental predictors as factors determining the distribution of A. thaliana accessions were climatically characterized by annual mean temperature (BIO1), mean diurnal temperature range (BIO2), temperature seasonality (BIO4), annual precipitation (BIO12), and precipitation seasonality (BIO15). With respect to land use, accessions were characterized by the percentage of agricultural land and the percentage of urbanized area within a circular area (500 m radius) around the GPS coordinate of A. thaliana accessions. The rest of the circular area was occupied by woody vegetation. Finally, the soil pH was also assigned to each A. thaliana accession.Eight model predictors were chosen from these sources. Of these, five were bioclimatic variables with a degree of collinearity (Spearman's correlation coefficient) lower than 0.7. The 279 As our goal was not to compare multiple GCC scenarios but to split a species into genetic units to show their GCC‐driven range fluctuations, we chose the 2070 RCP8.5  greenhouse gas concentration scenario that predicts high emissions and surface temperature changes to exceed 2°C by the second half of this century in the Mediterranean IPCC . We ran β‐regularization coefficients, the solution offered by MaxEnt to relax model fit, and performed 10‐fold cross‐validation. After checking that there was no model improvement, which means lack of strong bias in occurrence data  in all simulations. Background selection is also critical in MaxEnt when extrapolating to novel environmental scenarios , nuclear genetic clusters and chlorotype groups. AUC test values  and habitats with lower percentages of agricultural land .The potential distribution range of the species Fig. a was maiN = 82; mean BIO1 ± SE = 10.25 ± 0.22°C; Table S2). The potential distribution range of non‐OVR accessions was determined by pH and to a lesser extent by annual mean temperature  and warmer environments .As far as OVR categories are concerned Fig. b, the poN = 116; mean pH ± SE = 5.39 ± 0.06; Table S2) and colder annual mean temperatures  increasing the occurrence probability of C1 accessions. Cluster C2 was explained by precipitation seasonality and percentage of agricultural land  and lower percentage of agricultural land . Cluster C3 was also accounted for by the percentage of agricultural land and precipitation seasonality  and higher precipitation seasonality . The potential distribution range of cluster C4 was mainly explained by precipitation seasonality and temperature seasonality  and higher seasonality in temperature .The potential distribution ranges of nuclear genetic clusters Fig. c were alN = 102; mean pH ± SE = 5.63 ± 0.09; Table S2) and higher agricultural land . Group B was mainly explained by precipitation seasonality and pH  and less acidic soils . Group C was accounted for by annual mean temperature .Finally, the potential distribution ranges of the three chlorotype groups Fig. d were exd values applied to the distribution of predicted occurrence cells of each environmental variable for each genetic unit .We have shown that decomposing a species into intraspecific genetic units increases our understanding of potential range fluctuations under a GCC scenario in line with other studies , genetic clusters (N = 212) and chlorotype groups (N = 181).Figure S2. Genetic structure of Iberian Arabidopsis thaliana accessions estimated with STRUCTURE and nuclear SNPs. Accessions are depicted as horizontal bars divided in segments representing the estimated membership proportions of genetic clusters (K) fitted in the model. Yellow, blue, green and red depict genetic clusters C1, C2, C3 and C4, respectively. Accessions are arranged according to estimated cluster memberships proportions for K = 4.Figure S3. Chlorotype network of Arabidopsis thaliana accessions estimated with NETWORK. Chlorotype groups  include closely related chlorotypes for the sake of simplicity. Each branch corresponds to one mutational step between chlorotypes. Non‐observed mutational steps between chlorotypes are indicated by perpendicular dashes. Circle size is proportional to the number of accessions within chlorotypes.Table S1. Cohen's d and differences between OVR categories, nuclear genetic clusters and chlorotype genetic groups for each environmental variable.Table S2. Mean (±SE) altitude and mean (±SE) values for genetic units and environmental variables included in SDM.Table S3. Climatic variable percent contribution to the fit of the models.Click here for additional data file.


In addition, STAT3 is now known to be present in cardiac mitochondria and to exert actions that regulate the electron transport chain, reactive oxygen species production, and mitochondrial permeability transition pore opening. These non-canonical actions of STAT3 are enhanced by S727 phosphorylation. The molecular basis for the mitochondrial actions of STAT3 is poorly understood, but STAT3 is known to interact with a critical subunit of complex I and to regulate complex I function. Dysfunctional complex I has been implicated in ischemic injury, heart failure, and the aging process. Evidence also indicates that STAT3 is protective to the heart under chronic stress conditions, including hypertension, pregnancy, and advanced age. Paradoxically, the accumulation of unphosphorylated STAT3 (U-STAT3) in the nucleus has been suggested to drive pathological cardiac hypertrophy and inflammation via non-canonical gene expression, perhaps involving a distinct acetylation profile. U-STAT3 may also regulate chromatin stability. Our understanding of how the non-canonical genomic and mitochondrial actions of STAT3 in the heart are regulated and coordinated with the canonical actions of STAT3 is rudimentary. Here, we present an overview of what is currently known about the pleotropic actions of STAT3 in the heart in order to highlight controversies and unresolved issues.The transcription factor, signal transducer and activator of transcription 3 (STAT3), has been implicated in protecting the heart from acute ischemic injury under both basal conditions and as a crucial component of pre- and post-conditioning protocols. A number of anti-oxidant and antiapoptotic genes are upregulated by STAT3  Signal transducer and activator of transcription 3 (STAT3) is both a transcription factor and signaling molecule that modulates mitochondrial function –5. In thvia the angiotensin II type 1 (AT1) receptor, which contains a JAK2 binding site in the C-terminus, as well as by upregulating expression of IL-6 family cytokines  in cardiac myocytes by agonists that engage membrane receptors directly coupled to activation of Just Another Kinase (JAK) 1 or JAK2 tyrosine kinases  in cardi–14, althytokines –25.Besides functioning as a transcription factor STAT3 is now known to have poorly understood non-genomic actions in mitochondria that modulate respiration, reactive oxygen species (ROS) formation, and opening of the mitochondrial permeability transition pore (mPTP) , 4, 5. Ovia intermolecular phosphorylated tyrosine–SH2 interactions. The amino acid sequence of STAT3 is highly conserved across species. STAT3 is modified at specific residues by a number of posttranslational modifications with functional consequences, most notably by phosphorylation and acetylation  in their promoter  of STAT3 was implicated in recruitment of BRD4, a component of the activated positive transcriptional elongation factor (P-TEFb) complex, and induction of anti-apoptotic genes in HepG2 cells , or by interfering with the function of the TAD Table  55–61).–61.55–61in vitro and in vivo and IL-6-mediated reporter expression. Interestingly, evidence was reported that ROS may differentially affect STAT3 binding to DNA depending upon the nucleotide sequence of the promoter element, suggesting that the profile of genes activated by STAT3 may be modulated by oxidative stress  depletion . Glutathry genes . These cry genes . WhetherEvidence was recently reported that the redox-sensitivity of STAT3 has physiological relevance as well in the context of redox signaling by cytokines involving hydrogen peroxide generation. Peroxiredoxin-2 was shown to associate with STAT3 in HEK293T cells in response to treatment with IL-6 or oncostatin M . This asS-nitrosylation is a recently reported redox-related posttranslational modification that inhibits STAT3 activation. In microglial cells, endogenous NO from iNOS or treatment with s-nitrosoglutathione inhibited STAT3-induced gene expression and proliferation . STAT3 wvia an impact on transcription factors and intracellular increases in Ca2+, which activates calmodulin and the serine/threonine phosphatase calcineurin (not shown) (via NFAT) or de-represses cardiac gene expression via Ca2+/calmodulin-dependent protein kinases II (CamKII). ERK1/2 also has protective effects on mitochondria via phosphorylation and inhibition of GSK3-β, which prevents opening of mPTP  (via phosphorylation of mTOR complex 1 (mTORC1), Bad, and Bax (not shown). Akt activation is linked to protective gene expression too.Signal transducer and activator of transcription 3 signaling in cardiac myocytes in context is best illustrated by the induction of phosphorylation events downstream of LIF-induced dimerization of its membrane receptor LIFR with gp130 Figure . LIFR ant shown) . This in of mPTP . The phoI (HKII) . Akt maySignal transducer and activator of transcription 3 has been implicated in protecting the heart from acute myocardial injury due to ischemia and ischemia–reperfusion , 3. STATL, and c-FLIPS) and cardioprotective (COX-2 and HO-1) proteins normally induced in delayed preconditioning (via a mutant gp130 receptor was associated with a worse outcome in subacute MI due in part to increased inflammation (Definitive evidence that STAT3 protects the heart from acute ischemic injury has been obtained from cardiac myocyte-targeted STAT3 knockout (KO) mice. Smith et al. reported that depletion of cardiac STAT3 did not affect infarct size; however, STAT3 was found to be crucial for preconditioning protocols . Hilfikeitioning . Using aitioning . Deletioitioning . Nonetheitioning . SOCS3 iitioning . In lighammation . The impammation .Two major signaling pathways have been identified as contributing to the infarct-sparing effect of pre- or postconditioning. The Reperfusion Injury Salvage Kinases (RISK) pathway was identified first and entails activation with reperfusion of pro-survival kinases extracellular regulated kinase 1/2 (ERK1/2) and Akt that converge on mitochondria to decrease mPTP opening . The SurBesides, TNF, other agonists have been implicated in SAFE signaling, including sphingosine-1-phosphate, insulin, and IL-10 , 81, 82,The heart is more vulnerable to ischemia–reperfusion injury in late pregnancy, and this is associated with impaired activation of protective signaling, including STAT3 . In addiin vivo and in vitro was associated with downregulation of a- and β-myosin heavy chain (MHC) and derangement of sarcomeres. However, adult STAT3 KO hearts display normal levels of α- and β-MHC and SERCA2a . Evidence also indicates that STAT3 is protective to the heart under chronic stress conditions, such as hypertension, pregnancy, and advanced age. The protective role of STAT3 in hypertension-induced cardiac hypertrophy has not been well studied, but in addition to involving transcriptional events likely involves non-canonical interactions with NF-κB (see below). In pregnancy and with aging, STAT3 in cardiac myocytes has been shown to be a critical determinant of endothelial function and health, although by different mechanisms: induction of protective anti-oxidant genes is important in pregnancy, whereas loss of STAT3-mediated repression of miR-199a expression may contribute to endothelial dysfunction in the heart with aging. The mechanism by which STAT3 represses gene expression in the heart is not known, as is the question of whether gene repression and induction by STAT3 involve distinct posttranslational regulatory mechanisms.parallel dimers that tightly bind to GAS elements in promoters and induce gene expression via assembly of an enhanceosome. Canonical signaling is associated with both inflammation  and unphosphorylated STAT3 (U-STAT3) . In canoammation  [althougal means ] and the c-FLIPS , 72, 73. c-FLIPS , 44. S72 c-FLIPS , 50.aka latent STAT3) arises from canonical STAT3 signaling-induced STAT3 expression  STAT3 has been shown to interact with canonical NF-κB signaling, as well as with the non-canonical NF-kB pathway , 98, 108 cytosol . Exactly cytosol . The tem cytosol .−/− pro-B cells, deficient activities of complexes I and II were restored by expressing mutant STAT3 proteins with a phosphorylation refractory Y705F residue and either an intact S727 or a phosphomimetic S727 residue  assembly in mitochondria . DecreasThe mechanism by which STAT3 protects complex I and modulates mitochondrial metabolism is not known Figure . The repGRIM19 is the only hydrophobic protein in the hydrophilic portion of the matrix arm of complex I , 149. Sivia interaction with GRIM19, contributes to stabilizing the junction region between the matrix and membrane arms of complex I  and de-active (D) –165. The+ T cells, mitochondrial STAT3  was implicated in the formation of ETC supercomplexes downstream of IL-6 (The protective actions of STAT3 on respiration may involve other scenarios. Recently, mitochondrial-targeted STAT3 was shown to be required for the protective actions of prohibitin 1 against TNF-induced mitochondrial stress and apoptosis of cultured intestinal epithelial cells . Prohibi of IL-6 . FormatiThe non-canonical actions of STAT3 involve gene induction by U-STAT3 that may sustain a hypertrophic and inflammatory gene program in the heart in response to hypertension; however, definitive evidence for that conclusion is lacking. In addition, U-STAT3 or non-tyrosine phosphorylated STAT3 may have a role in genomic stability in the heart particularly under stress conditions. Although STAT3 is also known to interact with NF-κB in non-cardiac cells by various means, the importance if this interaction to the heart is not well studied. Evidence that STAT3 attenuates the contribution of NF-κB to hypertrophy and inflammation in the heart due to pressure overload would suggest that STAT3 activation could be exploited to protect the heart from hypertension-induced cardiac remodeling. Finally, STAT3 has been implicated in regulating mitochondrial respiration and limiting ROS production from the ETC. However, the molecular basis for the direct protective actions of STAT3 on mitochondria is not established. The finding that hearts of mice overexpressing a mitochondrial targeted STAT3 are protected from ischemia–reperfusion injury provides some hope that the mitochondrial actions of STAT3 could be exploited therapeutically.via interaction with other transcription factors such as NF-κB, sustaining presumably an inflammatory and pro-hypertrophic effect. U-STAT3 may function as well in chromatin organization and assembly. While there is growing consensus for the importance of a non-genomic role of STAT3 in mitochondria, the molecular basis by which STAT3 modulates ETC activity and ROS production is not known, nor how that may affect mitochondrial redox status. All these actions of STAT3 raise a question as how to target it therapeutically to favor its beneficial actions in order to prevent or reverse adverse cardiac remodeling. Further investigation into how STAT3 is regulated is crucial to achieving this goal.Much has been revealed about the role of STAT3 in the heart under acute stress such as ischemia and ischemia–reperfusion, and chronic stress such as pregnancy and aging. There is a general consensus that STAT3, in response to external stimuli, acts as a multifaceted protective protein by maintaining cellular homeostasis and antioxidant defenses. The activation and recruitment of STAT3 to induce both genomic and non-genomic activities is highly regulated by multiple posttranslational modifications, such as phosphorylation, acetylation, methylation, mono-ubiquitination, and oxidation. The co-ordination and integration of these posttranslational modifications in the heart in response to external stimuli is not well defined. Interestingly, non-stimulated STAT3, in the form of U-STAT3, has important genomic functions that are not well understood. In the heart, U-STAT3 may upregulate a specific sets of genes independently or All authors contributed conceptually to the manuscript. All authors authored sections of the manuscript, contributed to the figure design, and approved the final version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Urban systems present hierarchical structures at many different scales. These are observed as administrative regional delimitations which are the outcome of complex geographical, political and historical processes which leave almost indelible footprints on infrastructure such as the street network. In this work, we uncover a set of hierarchies in Britain at different scales using percolation theory on the street network and on its intersections which are the primary points of interaction and urban agglomeration. At the larger scales, the observed hierarchical structures can be interpreted as regional fractures of Britain, observed in various forms, from natural boundaries, such as National Parks, to regional divisions based on social class and wealth such as the well-known North–South divide. At smaller scales, cities are generated through recursive percolations on each of the emerging regional clusters. We examine the evolution of the morphology of the system as a whole, by measuring the fractal dimension of the clusters at each distance threshold in the percolation. We observe that this reaches a maximum plateau at a specific distance. The clusters defined at this distance threshold are in excellent correspondence with the boundaries of cities recovered from satellite images, and from previous methods using population density. Although many of these processes are the result of an imposed organization devised through administrative boundaries, some others hold communities together through strong ideological ties at the regional level, creating a strong sense of belonging. These processes are intricate cultural, political and socio-historical pathways, that have left footprints in the way communities emerge, organize, trade and change spatially. These footprints are contained in the street patterns and network, which are the main proxies for communication and exchange between settlements. It is hence not surprising that these also encompass the socio-economic history of the region. Despite the constant change and renewal of streets, we show in this work, that these footprints can still be identified and recovered.We focus on Britain, whose road network has been evolving for over 2000 years. Its origins can be traced back to the Iron Age with the Celts, but it was during the Roman occupation that a rapid expansion of the roads took place, and a network was established. In the last 200 years, this has been subjected to ongoing urban growth, and to adaptations for new extensions and modes of transport. Britain presents a rich regional structure, whose tensions lead to a fractured landscape, driven by ideologies and socio-historical trajectories. One example is the surge for the need to call for a referendum on Scottish independence 2014), and the rise of the Scottish Nationalists in the recent elections of 2014–2015. Discerning the emergent fractions that are independent of administrative provisions, but highly tied to their trajectories and ideologies, is of considerable relevance for the understanding of the dynamical regional functioning of a country. In a different paper natural csections , in ordesections ,37. Thessections –40, and sections .In detail, our algorithm is defined in terms of a distance parameter that determines clusters of intersection points in which every point has a neighbour at a distance equal or smaller than the given threshold. The algorithm can be implemented on the continuous space, or for large datasets requiring computationally demanding calculations, on a grid covering the space of points. Refer to the electronic supplementary material, appendix A for more detail on the implementation of the algorithm.2.2In this case, we are considering the ‘real’ network, where intersection points are connected if and only if there is a street connecting them. The clustering procedure is very similar to the procedure described above, but in this case the distance is given by the actual extent of the street. An open bond hence corresponds in this case to an existing street according to the different distance thresholds. Once again, the links can be re-interpreted in terms of probabilities if the distances are normalized. Details on how to implement this can be found in the electronic supplementary material, appendix B.3.3.1We analyse the process in the traditional way, by looking at the size evolution of the largest cluster at the different distance thresholds . A multidc=120 m denotes the merging of the north and south parts of London separated by the river Thames. The giant cluster can be identified with the core of London. Looking across the system, other large clusters correspond to the cores of important cities, such as Birmingham, Manchester, Liverpool, Bristol, etc. This first transition is therefore representative for a system of cities. Nevertheless, although the cores are recovered, the extent of the cities is much smaller than expected. In the next section, we will introduce a fractal analysis of the clusters at each distance threshold, and we will show that the system maximizes the value of the fractal dimension at the highest point of correlation with the urbanized space, defined through a classification of satellite images.The first transition detected at dc=540 m, encompasses the main post-industrial cities in the north: Liverpool, Manchester, Leeds and Sheffield. These are the main core cities conforming the region denominated as the ‘Northern Powerhouse’ ,1 with some others, such as Newcastle missing in the cluster. The Northern Powerhouse proposal aims at devolving power and at boosting economic growth in cities in the north, reducing the gap of wealth between these and the cities in the Southeast, mainly driven by London [The giant cluster at the next transition, y London . Such a dc=580 m, sees an expansion of that region, introducing Birmingham into the largest cluster. The following smaller transitions see the annexing of Wales into the cluster at dc=660 m, and at dc=680 m, that of Cornwall. At d=740 m before the next transition takes place, a very clear division between the Northwest and the Southeast can be observed. It is important to note at this point that such a division is not the outcome of a geographical accident of sorts, say the presence of natural barriers such as parks, mountains or rivers. In addition, it is not an artifice of taking only the intersection points, since the split is also present when the percolation is performed directly on the network. This split does not seem to be linked to the topography of the country, but to the division of wealth that we have been discussing throughout. We illustrate this in d=740 m. The map on the left shows model-based income estimates for England and Wales at the level of Middle Layer Super Output Areas for 2007/2008. These are based on census data, and hence Scotland is excluded from this map, since it has a different census to England and Wales. The black boundaries correspond to European administrative regional divisions called NUTS2 [The next transition at ed NUTS2 . The dotdc=760 m, England and Wales, with the exception of Snowdonia , merge into one region, marking the most striking transition. This is followed by smaller transitions resulting from the merging of areas with natural barriers. At d=1120 m, Scotland can clearly be distinguished as a separate region from the rest of England and Wales. Note that the split of Scotland from the rest of the country is not caused by barriers of topographic nature either. This division is of a similar type to the one encountered earlier, it is the product of a historical cultural differentiation, that has been imprinted in the evolution of the infrastructure of the country. The last important transition in the system is observed at dc=1140 m, and it corresponds to the merging of Scotland with England and Wales.At It can be argued that these results are biased, given that the connectivity between points does not take into account whether these points can or cannot be connected through roads, because these were removed. To reassure the reader, we perform the percolation on the road network and we present the results in the electronic supplementary material, appendix C. The plots and maps, see figure S2, confirm the previous analysis, although at different critical distances. These are larger, as they correspond to the length of the roads individuals need to take to travel from one intersection point to another in the urban system. An important result of percolation theory, is that the value of the critical distances will vary from dataset to dataset, and from system to system. We hence do not expect to recover the same distances for the UK if a different dataset is used, nor the same distances for different countries.The results can be summarized in a crude way, by looking at the evolution of the relevant largest clusters through a dendogram . The hie3.2Urbanized spaces have specific morphological properties that cannot be found in non-urbanized areas, and many of these are manifested in the road network. We investigate in this section, whether the clusters defined at each distance threshold can characterize the urban system in a particular morphological manner. We choose the fractal dimension as the property to analyse, given that this has been extensively researched for the morphological description of cities –49. In  for examThis section contains two subsections for the analysis of each of the systems, since the fractal dimension cannot be computed in the same way for point patterns and for a network.3.2.1multifractals [Until recently, the characterization of the fractal structure of a system consisted of a single fractal dimension. For cities, this was traditionally obtained through a box counting algorithm. Nevertheless, this measure is extremely sensitive to the dataset and the implementation. In addition, it is well recognized now, that cities are actually fractals ,53. Thesfractals , and henfractals –57.D0, D1 and D2; where D0 is the capacity dimension, and in practical terms it corresponds to the box-counting measure; D1 is the information dimension and it can be interpreted as Shannon’s entropy; and D2 is the correlation dimension, which is considered to be the most accurate one. A quick review of these measures can be found in the electronic supplementary material, appendix F. For the specific system at hand, we need to extract the characteristic fractal dimensions at each of the distance thresholds. Nevertheless, the clusters that emerge have all sorts of sizes, from individual points, to very large clusters. As we are interested in characterizing the urban space, and ultimately in recovering the cities of the system, which are the landmark of urbanization, we impose a minimum cluster size of 600 intersections for the computation of the fractal dimension. In addition, we do not compute the fractal properties beyond a maximum distance threshold of d=540 m, since the percolation method clearly returns regions beyond this transition, moving further and further away from a configuration of cities. The methodology to compute these three dimensions follows the same algorithms described in [d=180 m. Carefully inspecting the urban system at this maximum of its morphological characterization, we observe that the clusters at this distance threshold are in excellent correspondence with the classification of urbanized space given by the Corine dataset [From the total spectrum, we select the three well-known fractal dimensions denoted by ribed in , where f dataset , which i3.2.2α of the system is computed in terms of the scaling relationship between the mass of the clusters and the diameter of the network. The mass is given by the number of intersection points N and the diameter is denoted by Let us now compute the fractal dimension of the clusters of networks that emerge from the percolation on the network. In this case, the fractal dimension d=800 m to ensure that we are well within the cities definition. In addition, in order to include as many small settlements as possible in the analysis, we use for networks a minimum cluster size of This corresponds to the same methodology implemented in . Note thd=300 m, see d=300 m, with the contours for the classified urbanized areas in black.For this case, the results show a maximum at around d=300 m. Further details of how this measure is computed can be found in the electronic supplementary material, appendix D.We quantify the level of agreement between the clusters obtained through the percolation method and the urbanized areas in the Corine dataset through a correlation measure. d=300 m might suit this specific dataset for Britain, but might not suit another dataset, nor another European country. It is not uniquely defined, because the maximum corresponds to some sort of plateau. Hence any definition in the vicinity of d=300 m would be as accurate or as inaccurate as the one for d=300 m.It is important to reiterate that the distance is not universal nor uniquely characterized. It is not universal, because it depends on the nature of the dataset. Hence a distance of 4.Throughout this work, we have shown that percolation theory can be applied to the street intersections and network, in order to uncover its intrinsic hierarchical structure. We argued that such an organization does not only relate to ideological or geographical divisions, but it represents a socio-economic polarization of the system. It has been extensively discussed that the regional development is tightly linked to the development of its infrastructure, hence it should not be surprising to find these economic patterns reflected in the density of the road network.d=540 m, it appears that the assimilation of Newcastle within the Northern Powerhouse proposal needs to be done with care, so that it is not left behind, given its weaker connectivity to the rest of the cities in the region. In this sense, many regional policies need to consider the strong ties that lie within the urban system.Regions are formed by settlements which share a stronger connectivity among themselves than among settlements of other regions. It is therefore not surprising to recover historical trajectories, and existing alliances. In this sense, looking at the highly integrated region of the cities in the north at From the perspective of the methodology, this formalism has the advantage that it can be implemented for incomplete datasets. We would have to test the robustness of the method with respect to the incompleteness of the dataset, but at this stage it is clear that the road intersections serve as a good proxy for urbanization , and thaFinally, this work has also provided a framework to define boundaries of cities in a global way, using a dataset that is open and not constrained to geographical units, such as the census data. In previous work, we developed a procedure to define cities using population density from the census . AlthougFuture research is needed to understand the mechanisms that drive the system to a maximum fractal dimension at the point where the cities reach their urban extent.


Colocasia esculenta (L.) Schott) is widely distributed in tropical and sub-tropical areas. However, its origin, diversification and dispersal remain unclear. While taro genetic diversity has been documented at the country and regional levels in Asia and the Pacific, few reports are available from Americas and Africa where it has been introduced through human migrations. We used eleven microsatellite markers to investigate the diversity and diversification of taro accessions from nineteen countries in Asia, the Pacific, Africa and America. The highest genetic diversity and number of private alleles were observed in Asian accessions, mainly from India. While taro has been diversified in Asia and the Pacific mostly via sexual reproduction, clonal reproduction with mutation appeared predominant in African and American countries investigated. Bayesian clustering revealed a first genetic group of diploids from the Asia-Pacific region and to a second diploid-triploid group mainly from India. Admixed cultivars between the two genetic pools were also found. In West Africa, most cultivars were found to have originated from India. Only one multi-locus lineage was assigned to the Asian pool, while cultivars in Madagascar originated from India and Indonesia. The South African cultivars shared lineages with Japan. The Caribbean Islands cultivars were found to have originated from the Pacific, while in Costa Rica they were from India or admixed between Indian and Asian groups. Taro dispersal in the different areas of Africa and America is thus discussed in the light of available records of voyages and settlements.Taro ( Colocasia esculenta (L.) Schott) belongs to the family Araceae and is a highly polymorphic species [dasheen, eddoes, malanga and cocoyam in the Caribbean and West Africa [Taro , a cooperative network of countries established in April 2011, whereby edible aroids are used as a model to improve clonally propagated root and tuber crops of tropical countries. A majority of the partners in the network are signatories of the FAO International Treaty on Plant Genetic Resources for Food and Agriculture (ITPGRFA), and have agreed to share taro germplasm under the ITPGRFA Multilateral System of Access and Benefit‐sharing by Contracting Parties. The genetic diversity assessment was entrusted to CIRAD  as part of the “Genetic Studies” workpackage of the project. Consequently, each partner conducted sampling in its own country and dried leaves were sent to CIRAD for genotyping. All partners have a national mandate for the collection and conservation of taro genetic resources and documentation of accompanying information. Samples were shipped to CIRAD according to the ITPGRFA guidelines using the Standard Material Transfer Agreement (SMTA).This work was conducted within the framework of the Europe-Aid project DCI-FOOD/2010/230-267 SPC “Adapting clonally propagated crops to climatic and commercial changes”. Partners of this project operate under the auspices of the International Network for Edible Aroids  and 38 were triploid (n = 36 chromosomes). Overall, 357 cultivars were analyzed  core sample with known ploidy levels [analyzed .Colocasia esculenta [Amorphophallus paeoniifolius [Taq DNA polymerase , 2 mM MgCl2, 200 μM dNTPs and 0.1 μM of forward and reverse primers and M13 tail [Genomic DNA was extracted from 150 mg of dried leaves according to the protocol described by Risterucci et al. . The quasculenta –34 and Aiifolius  were scrM13 tail . PCR cycHe), could not be used to study the genetic diversity of C. esculenta [An), average number of effective alleles (Ae'), number of private alleles (Ap), Shannon information index (I) and genetic diversity (μh) for each country, when the number of cultivars was over five, and for each continent using the GenAlex 6.5 software [Due to the ploidy of the studied species, partial heterozygosity makes it impossible to score genotypes exactly  because sculenta . The ressoftware .Dissimilarities between all pairs of cultivars were estimated based on the Dice distance  and a miTaro is mainly vegetatively propagated crop; therefore clones were expected within our sample. One clone (genet) may include several cultivars (ramets). After genotyping, each cultivar is represented by a multilocus genotype (MLG). Several cultivars (ramets) can share the same MLG (genet) or differ by few mutations because of biological or methodological reasons such as somatic mutations, scoring errors and PCR artefacts. They are then assigned to the same clonal lineage or multilocus lineage (MLL). GENOTYPE software was first used in order to determine whether small genotypic differences between MLGs were a consequence of sexual recombination or somatic mutation, by calculating frequency distribution of distances among pairs of cultivars . The hisie MLLs and unique genotypes (UG) in the sample and N is the number of cultivars analyzed. This index ranges from 0  to 1  [A second data set was obtained by keeping all UGs and only one representative for each MLL in each country. Consequently, some MLLs were shared between countries. For each country , the index of clonal diversity (R) was estimated by R = (G-1)/(N-1), where G is the number of genotypes l stand) .www.haplophyle.cirad.fr).Within a clonal lineage, in order to visualize the relationship between MLGS and their distribution between countries, a network of each MLL was built. Within the same MLL, and for each locus, two MLGs differed by a maximum of one allele. We thus proceeded as described by Scarcelli et al. . DiploidK ranging from 1 to 10, under the admixture model, using a burn-in of 500,000 iterations and 1,000,000 Markov chain Monte Carlo iterations. We evaluated the inference of K using the ad hoc statistic ΔK method [(An), (Ae'), (Ap), (I) and (μh) for each defined cluster were calculated as described above. We separately ran a new STRUCTURE analyses on each cluster in order to identify any sub-clustering within each cluster.An unrooted neighbor-joining tree was constructed with one representative of each MLL and all unique genotypes using Darwin V5 software . The genK method , as implK method . We assiGenotyping with 11 microsatellite marker loci revealed that the cultivars were partitioned into two distinct groups: one showing two alleles at all investigated loci and the second with up to three alleles at certain loci. If the ploidy level of cultivars bearing three alleles at least at one locus can be considered as triploid, the diploid status of cultivars with two alleles at all loci could not be assessed. Yet we obtained complete match between the number of alleles obtained after genotyping and the ploidy level of the cultivars checked from India, Burkina Faso and TANSAO . So, theAR), private alleles (AP), average number of effective alleles (Ae’), Shannon information index (I) and genetic diversity (μh) are shown in Ap = 25). Cultivars from Burkina Faso, Ghana and Madeira did not present any private allele, while those from Costa Rica, South Africa and Martinique had one to two private alleles. The Ap for the remaining countries from Asia and the Pacific ranged from four to seven. The Shannon Index and genetic diversity followed the same pattern, with India having the highest (I) and (μh), while South Africa and Ghana had the lowest. At the continent level, cultivars from Asia had the highest number of private alleles and genetic diversity while those from Africa, America and the Pacific had lowest genetic diversity parameter values.A total of 195 alleles were amplified from the 11 microsatellite loci in the 357 cultivars. All loci were found to be highly polymorphic. The number of alleles observed in the whole dataset ranged from four to 31 alleles per locus . GeneticUsing the Dice matrix, the NJ unrooted tree showed structuring according to the countries and a high level of clonality . Consequie no closely related genotypes were sampled. In Vanuatu, only one MLL was found to be shared with Indonesia. Five MLLs were shared between neighbouring countries . Two MLLs (45 and 51) were only shared between India and Indonesia. Within MLL45, the two MLGs shared the same alleles except that the cultivar from Indonesia was diploid [Eighteen MLLs were identified in our sample. Three MLLs  are substantially the most common in the data set. Within most MLLs, genotypes differed by only one allele. They were present either within one country or shared between different countries . Eleven K supported K = 2 as a possible value for the uppermost structure level. Using K = 2, 120 genotypes had more than 80% membership in one cluster , eight MLLs, including the widespread MLL4, and 68 UGs from 12 countries, representing genotypes which showed 2 alleles at all loci, including TANSAO diploids. They corresponded to all cultivars from the Pacific (i.e. PNG and Vanuatu), all cultivars from Asia (except India), a few ones from Indonesia, all cultivars from Caribbean islands and one from Madagascar.In the second cluster (C2), 44 genotypes were grouped, representing 29 genotypes with three alleles at at least one locus, and 15 genotypes with two alleles at all of the investigated loci. They represented seven MLLs and 37 UGs. India was represented by 26 UGs and 5 MLLs  whether they were grouped within India or shared with Indonesia or Nigeria (21 triploids and 10 diploids). The other genotypes assigned to C2 represented 10 UGs from Madagascar, Madeira, Costa Rica and Indonesia and two MLLs (MLL2 and 104) shared between Burkina Faso and Ghana and between Japan and South Africa.The 16 genotypes with membership under 80% were admixed and corresponded to 10 diploids , originating from America, is more frequently cultivated. Consequently these countries do not host important taro diversity.This is the first time that an investigation on taro diversity has been extended to Africa and America. Previous studies were conducted at country and regional levels , 33, or We could not assess the ploidy level of all cultivars analyzed. However, the number of alleles obtained with the 11 microsatellite marker loci perfectly matched the ploidy levels assessed by flow cytometry and the chromosome counts in cultivars from Burkina Faso, India and those from the TANSAO collection. All cultivars from the Pacific displayed two alleles at all loci, which is in accordance with their diploid level, as reported in previous studies , 23. BotThe highest indices of clonal diversity were obtained in countries from Asia and the Pacific. Within these countries, it seems more likely that sexual reproduction was the means by which taro genetically diversified. In the Pacific, where all cultivars are diploids, many cultivars flower naturally, insect pollinators are very active, and natural hybridization among cultivars occurs regularly , so the Our Bayesian clustering analysis showed a clear separation between diploids mainly from the Asian-Pacific region and diploids and triploids mainly from India. This is the first time that such divergence between the two genetic pools has been clearly revealed. Most previous studies did not include Indian germplasm in their sampling , 25, or Most previous studies have assigned the diploids to the Pacific pool while the triploids were grouped in the Asian pool. In our study, while the Asian-Pacific pool encompassed most diploids from Asia and the Pacific, the Indian pool encompassed all diploid and triploid Indian cultivars and only four other diploid cultivars (three from Indonesia and one from Madeira). The remaining triploids were admixed between the Asian-Pacific and Indian genetic pools. It seems that all triploids arose from the Indian pool or were hybrids between the Indian and Asian-Pacific genetic pools and subsequently spread to other countries.The two main sub-clusters found in the Asian-Pacific pool corresponded to the Asian and Pacific genetic groups reported in previous studies , 23, 25.Colocasia esculenta is not native to Africa or America and has reached these two continents through human migration. Within our sample, MLL3 and MLL4 were shared between countries from Asia, Africa and Central America. These two MLLs represented nearly a third of the cultivars (156) and corresponded to 22 MLGs. It is unlikely that a single clone was introduced to different countries on different continents directly from a single point of origin. A gradual diffusion process is more likely, with a single clonal genotype spreading from one country to another in multiple directions from its point of origin as a seedling. During this dissemination process, it probably accumulated mutations leading to different MLGs. Our data suggest that both MLLs are most likely ancient introductions from Asia and/or India. After settlement, they were exchanged between Africa and America. Indeed, vegetative propagation is reported to enable the maintenance and spread of superior individuals but also to decrease the number of sexual cycles [l cycles . ConsequDioscorea alata L.) [sonjo has the same name root as the sune from Polynesia. The name taho is also found in Madagascar but in geographically localized areas and this term is thought to be related to Timor languages [All cultivars from West Africa and from Madeira were assigned to the Indian and Asian groups, except for MLL3 which was shared with other countries and assigned to an admixed genotype between the Asian-Pacific and Indian genetic groups. So it seems likely that taro in West Africa originated from India or other Asian countries rather than from the Pacific. It remains unclear how taro reached West Africa . It seemlata L.) . This “vlata L.) . While ilata L.) , 55. Cullata L.) . Taro walata L.) , the locanguages . Indian anguages . The samanguages . As MLL1anguages , or it cMadère in Guadeloupe and Martinique which could suggest an introduction from Madeira. However, no accessions were grouped with the Madeira, i.e. Asian or Indian, gene pool. This could likely be explained by the fact that very few cultivars were analyzed. However, most present cultivars were in our sampling. Costa Rica was the only Central American country represented in our sampling, encompassing MLL 3 and 4 and one cultivar assigned to the third Indian small subgroup. MLL 3 and 4 were shared between Madeira, Japan, the Philippines and Vietnam, and also Madagascar and Réunion. Manzano et al. [In the present study, few cultivars were obtained from Central America and the Caribbean islands, and few countries were represented in the American sample. One MLL was shared between Guadeloupe, Martinique and Trinidad & Tobago; another was only shared between the first two, which is evidence of crops exchanges between Caribbean islands. All cultivars from Caribbean islands were assigned to the Pacific sub-group. Taro is also called o et al. , in an iMost diversity in taro has arisen through breeding, which has given rise to a large number of genotypes, as shown in the present study. Although taro is always propagated asexually in farmers' fields, it is an allogamous, highly heterozygous species, and natural pollinations do occur between flowering diploids. New genotypes germinating spontaneously can be clonally selected by farmers but these can also capture somaclonal variants when these appear sufficiently different form mother plants to be considered as new cultivars and renamed. Some of the genetic diversity described here reflects mutation over long periods of time in geographically widespread clonal lineages that may be very ancient. Some clonal lineages in taro have been widely distributed through migration or exchange. Further study of these widespread clones is needed to determine their geographical origins, antiquity, and likely routes of dispersal. However, taro being essential for food security in many developing countries, it appears necessary to broaden the genetic bases to facilitate farmers' varietal portfolios adaptation to climatic changes.Most of the cultivars investigated in our study could be assigned to a genetic pool, so their region or continent of origin could thus be identified. We could not, however, determine the countries from which they originated or their dispersal routes. Further studies should focus on broadening sampling from Central Asia and East Africa and on including wild accessions and herbaria specimen vouchers. The use of uni-parentally inherited molecular markers (e.g. chloroplasts) will contribute to better identification of the geographical origins and to track taro dispersal routes through countries and continents. These studies should be carried out by combining genetic, archeological and historical data.S1 FigEach branch is colour-coded according to the variety country of origin.(PDF)Click here for additional data file.S2 FigCultivars collected in 19 countries show bimodal distribution, calculated using Genotype software, with a small peak ranging from d = 0 (clonemates) to d = 8. The clonal threshold distance corresponds to the maximum distance below which distinct MLGs belong to the same clone is equal to d = 8.(DOCX)Click here for additional data file.S1 TableCultivars, cultivars names provided by each country and by SPC. Country of origin, the country where the cultivar was collected. Max number of alleles, Maximum number of alleles for the eleven loci analyzed. Assessed Ploidy Level, the ploidy level assessed by chromosome counting or flow cytometry. MLG, multilocus genotype after Genotype analysis. MLL_threshold 8, the assignment of the cultivars to MLL or UG. Genotypes_STRUCTURE, the selected genotypes, i.e. all UG and one genotype per MLL, used for Bayesian structure analysis. Structure_K2_q_0.8, is the assignation of each genotype to Clusters 1, 2 or admixed after Bayesian structure analysis.(XLSX)Click here for additional data file.S2 TableLocus name, Repeat motif, Ta, Minimum and Maximum allele sizes (bp), Number of alleles obtained within our sample and authors.(XLSX)Click here for additional data file.S3 TableN, number of genotypes within each cluster. An, total number of alleles, Ae’, number of effective alleles, AP, number of private alleles, I, Shannon's information index, μh, unbiased diversity.(XLSX)Click here for additional data file.


Cirrhimuraena chinensis Kaup) is an intertidal fish and a model organism for the study of impacts caused by topological fluctuations during the Pleistocene and current intricate hydrological conditions on fauna living in the coastal areas of China. In this study, we examined the phylogeographical pattern, population genetic profile and demographical history of C. chinensis using mitochondrial DNA (cytochrome b (cyt b) and control region (CR)) from 266 individuals sampled in seven localities across the coastal area of southeastern China. The combined data indicated high levels of haplotype diversity and low levels of nucleotide diversity. Analyses of molecular variance (AMOVA) and FST statistics suggested the absence of a significant population structure across the Chinese coast. Neutrality tests, mismatch distributions and Bayesian skyline plots uniformly indicated a recent population expansion. The phylogeographic structure of C. chinensis may be attributed to past population expansion and long-distance pelagic larval dispersal facilitated by present-day ocean currents.The Chinese beard eel ( Characterized by a series of periodic climate oscillations, the Quaternary period is thought to have had profound influences on the development of many flora and fauna in both terrestrial and aquatic environments ,2. The fCellana toreuma [Chthamalus challengeri [Cyclina sinensis [Intertidal organisms form a biotic assemblage occupying a narrow, discrete and vulnerable strip of closely linked land and sea  and are  toreuma , the colllengeri , and thesinensis . RelevanCirrhimuraena chinensis Kaup) is a nearshore warm-water demersal fish, distributed from the eastern coast of Indo-Africa to Indonesia, China and the Philippines. In China, it occurs along the coastal areas of the East China Sea, Taiwan Strait and South China Sea [C. chinensis larvae and adults therefore makes this species a good model organism to test the complex impacts brought about by sea level change during the Pleistocene and by current intricate hydrological conditions on fauna living in the coastal areas of China.The Chinese beard eel  sequences, cytochrome b (cyt b) and the control region (CR), with the aim of revealing the genetic profile of the C. chinensis population and its demographic history. By addressing these issues, we expect to provide further insights into the evolutionary mechanisms that shape the phylogeography of marine fauna living in the coastal areas of China and to elucidate the influences that medium to long pelagic larval stages have on the phylogeographic pattern for intertidal fishes.In the present study, we examined the phylogeography of b coding sequence and one 836-bp fragment from the D-loop. A total of 131 variable sites were observed, of which 87 were parsimony-informative and 160 haplotypes were observed. The overall haplotype diversity (h) and nucleotide diversity (π) were 0.967 and 0.002, respectively. Detailed information about haplotype, haplotype diversity and nucleotide diversity for each sampling locality is shown in A dataset was obtained comprising 266 individuals and containing two sequenced fragments, one 804-bp fragment from the cytochrome FST values were low and ranged from −0.007 to 0.005, with an average value of 0.001  did not detect any correlation between genetic distance and geographic distance for concatenated sequence data.Pairwise of 0.001 . Analyseof 0.001 . For theT values . A ManteD and Fu’s FS all yielded significant negative values, while the results of tests of Ramos–Onsins and Rozas’ R2 were all statistically significant  [Engraulis japonicus) [Nibea albiflora) [Scylla paramamosain) [Chthamalus challengeri) [Lipophrys pholis) [Conger myriaster) [C. chinensis is usually treated as a resident fish without a long-distance swimming ability [C. chinensis undergoes a leptocephalic stage lasting 20 to 25 days at 18 to 28 °C before metamorphosing into a juvenile fish [C. chinensis larvae are capable of dispersing for several weeks under natural oceanic circumstances. The absence of genetic structure in this species may be reasonably explained by the planktonic larval stage, playing a critical part in facilitating gene flow.Marine organisms with high dispersal capacity generally show low levels of genetic differentiation, even between distant regions ,20,21, w obesus) , Japanesponicus)  and yellbiflora) , and somamosain) , the collengeri) , the sha pholis)  and the riaster) . The plariaster) ,28. The  ability , yet a pile fish , which sC. chinensis was speculated to travel a long range, considering the length of its larval stage and the current velocity in the East China Sea, South China Sea and Taiwan Strait. Therefore, the oceanographic conditions within the studied range provide C. chinensis with appropriate natural conditions to migrate along the Chinese coast and maintain high levels of genetic connectivity among geographically separated demes. In China, C. chinensis does not display any genetic breaks or distinct lineages, but instead shows a homogeneous phylogeographic pattern.Near China’s coasts, the ocean current pattern is always intricate and variable. Water exchange and seasonal reversals in surface oceanic circulation are driven by a southwest summer and northeast winter current driven by prevailing monsoonal winds ,30,31. AD, Fu’s Fs), the results of the Ramos–Onsins and Rozas’ R2 test and the unimodal mismatch distribution curves. Additionally, the Bayesian skyline plots also provided evidence for the occurrence of a sudden population expansion approximately 7.5 thousand years (kyr) ago. Moreover, according to the four scenarios proposed by Grant and Bowen (1998) based on genetic diversity and nucleotide diversity, populations of C. chinensis with a high h value and a low π value most likely underwent a population expansion after a long-term period of low effective population size. All of these results therefore consistently support the hypothesis that C. chinensis populations along the Chinese coastal areas have experienced a population expansion.A hypothesis of population expansion was in accordance with the significant negative values of the neutrality tests (Tajima’s The late Pleistocene period (the past one million years) was dominated by a series of large glacial-interglacial oscillations , charactC. chinensis detected in our study. Low sea level led to an expansion in the spectrum of salinity and temperature in nearshore waters. Deleterious niche stresses, coupled with a reduction in formerly available habitat, would have caused massive extinction and a significant reduction in population size for numerous neritic species [C. chinensis was closely affected by both terrestrial and marine factors; hence, it most likely experienced more severe environmental stresses than oceanic organisms [C. chinensis. The remaining individuals could only have survived in potential refugia (such as the Okinawa Trough or semi-closed South China Sea) during the glacial period. With the rise of sea level after the LGM, surviving C. chinensis would have recolonized from the refugia and reoccupied the newly available habitats quickly [C. chinensis could disperse over a considerable distance by taking advantage of surface current circulations, its geographic distribution range would have been broadened, and its abundance and effective population size would have increased.The following scenario offers a plausible explanation for the post-LGM demographic expansion of  species . Being arganisms . Therefo quickly . As pelaC. chinensis were collected from December 2010, to May 2012, from seven localities along the coast of China, including the East China Sea, Taiwan Strait and South China Sea  and R916 (5'-TTTCTACTCAACCCGCTAATG-3') and by F59 (5'-TCAAAGGAATTAAATGGCG-3') and R973 (5'-GTGGACAGGGACAAGGGTA-3'), respectively. The PCR amplification was carried out in a 25-μL reaction volume containing 10 mM Tris-HCl (pH 8.3), 50 mM KCl, 1.5 mM MgCl2, 0.2 mM of each dNTP, 0.4 μM each primer, 1 U Taq polymerase  and 30 ng template DNA. For cyt b fragments, the PCR procedure consisted of an initial denaturation step at 94 °C for 3 min, followed by 30 cycles of denaturation at 94 °C for 45 s, 52 °C for 1 min, extension at 72 °C for 1 min and a final extension at 72 °C for 10 min. For CR fragments, the PCR profile consisted of an initial denaturation step at 94 °C for 3 min, followed by 30 cycles of denaturation at 94 °C for 30 s, 55 °C for 45 s, extension at 72 °C for 1 min and a final extension at 72 °C for 10 min. The newly isolated nucleotide sequences were deposited in GenBank under Accession Numbers KJ150737-KJ151281.Genomic DNA was isolated from muscle tissue by proteinase K digestion using standard phenol-chloroform methods . The cytb and CR sequences were edited and aligned in Sequencher version 4.1.4  before being incorporated into the concatenated dataset. Genetic diversity estimates of cyt b, CR sequences and the concatenated dataset, including the haplotype diversity (h) and nucleotide diversity (π), were calculated for each location and the entire population by DnaSP version 5.0 [cyt sion 5.0 .FST) were estimated using concatenated data by Arlequin version 3.5 [FST matrix and the matrix of geographic distance.To evaluate the genetic differentiation between sampling locations, population genetic distances . The phylogeographic pattern of C. chinensis may be attributed to past population expansion and long-distance pelagic larval dispersal facilitated by present-day ocean currents.


Antillogorgia elisabethae in The Bahamas were assessed in both adults and recently settled recruits from 13 sites using microsatellite loci. Adult populations along the Little Bahama Bank (LBB) exhibited a clear pattern of isolation by distance (IBD) which described 86% of the variance in pairwise genetic distances. Estimates of dispersal based on the IBD model suggested dispersal distances along the LBB on the order of 100 m. Increasing the spatial scale to include sites separated by open ocean generated an apparent IBD signal but the relationship had a greater slope and explained less of the variance. This relationship with distance reflected both stepping stone based IBD and regional differentiation probably created by ocean currents and barriers to dispersal that are correlated with geographic distance. Analysis of recruits from 4 sites on the LBB from up to 6 years did not detect differences between years nor differences with adult populations. The result suggests that neither selection on recruits nor inter-annual variation in dispersal affected adult population structure. Assignment tests of recruits indicated the most likely sources of the recruits were the local or adjacent populations. Most of the patterning in population structure in the northern Bahamas can be explained by geographic distance and oceanographic connectivity. Recognition of these complex patterns is important in developing management plans for A. elisabethae and in understanding the effects of disturbance to adult populations of A. elisabethae and similar species with limited dispersal.Patterns of dispersal and connectivity of the Caribbean gorgonian  Antillogorgia elisabethae to assess connectivity and self-recruitment in The Bahamas.Sessile and sedentary organisms, such as the invertebrates and fishes found on coral reefs generally have life histories in which reproductive individuals produce larvae that may settle on their natal reef or disperse to other reefs. Those patterns of dispersal control connectivity, the numbers of successful migrants moving between populations, and self-recruitment, the proportion of individuals of local origin. In combination, connectivity and self-recruitment are critical in determining the dynamics of populations, the resilience of metapopulations and the evolution of species. On coral reefs, as for all threatened ecosystems accurate assessments of connectivity are critical components to developing management plans that promote the conservation and resilience of populations . In thisConnectivity among species such as octocorals is the product of a series of sequential steps starting with the production and dispersal of larvae followed by their settlement and survival . DispersStudies of connectivity among coral reef taxa have focused on scleractinian corals  and fishOctocorals, the focus of this report, are a large and diverse group of sessile marine invertebrates, which are especially abundant on coral reefs and in deeper waters. Branching forms that contain a supporting axis, colloquially known as gorgonians, are abundant on Caribbean coral reefs. Octocorals may be less sensitive to ocean acidification , but se and bleaAntillogorgia elisabethaePseudopterogorgia elisabethae, the species has been reassigned to the Antillogorgia as all Caribbean Pseudopterogorgia spp. have been reassigned to the resurrected genus Antillogorgia  (In previous studies we have established that ce (IBD) . Fine scce (IBD)  suggest ce (IBD) .Antillogorgia elisabethae tissue samples from adult colonies were collected from 13 sites in the northern Bahamas , 50 mM KCl, 200 µM dNTPs, approximately 10 ng of DNA template, 1.5–2.5 mM MgCl2, and 0.025–0.05 µM of each primer. Cycling conditions were 2 min at 94 °C, followed by 28–32 cycles at 94 °C for 30 s, 50–56 °C for 45 s and 72 °C for 45 s, with a final extension period of 10 min at 72 °C.Allelic variation was assessed by genotyping a total of 704 samples of protocol  or DNeasprotocol , Pel62, protocol  and Ael-protocol . In brie® Global IR2 DNA Sequencer System, using fluorescently labeled primers as described in PCR products were screened on 7% polyacrylamide gels in a LI-COR NENaN) and effective (eN) alleles, allele frequencies, information index, observed heterozygosity, unbiased expected heterozygosity and fixation index were determined using GenAlEx v.6.5  represented in the samples using Structure v.2.3.4  were used in different test runs in order to find the optimal value. Low λ values correspond to weakly fragmented partitions and strong spatial dependence  repetitions were set at 100,000, thinning to 100, the burn-in period was set at 200 and the correlated allele frequency model was used. Coordinate uncertainty was set to 0.5, decimal degrees. Uncertainty in the coordinates allows samples collected at the same site to be assigned to different populations, otherwise all samples are assigned to the population where they were collected. Different values of the maximum rate of Poisson process . FST was calculated with both FSTAT and with FreeNA. AMOVA was conducted using ARLEQUIN v.3.5.1.3 , but there was no consistent pattern across either loci or sites  and PR  were clearly differentiated from each other and from all of the other sites. The TOTO and AN sites were also dissimilar to most other sites but to a lesser extent. Although both sites were situated along the western edge of the Tongue of the Ocean, AN was no more similar to TOTO than to the other sites. TR, although separated from the other sites by Andros Is. and the Great Bahama Bank, also had intermediate levels of genetic differentiation to both LBB and GBB sites  had low FST values, with the adjacent CHSL and CHR having particularly low, but significantly greater than 0.0, values of 0.0280 and 0.0296 respectively. As expected from the nature of the index, FST and are shown in FST was not significantly greater than 0.0 had a Global than 0.0 . FST cald FreeNA  were verFST values is evident in the Mantel tests (P = 0.01) and the results were very similar regardless of whether geographic distance or adjusted geographic distance was used . The proportion of variance explained by the relationship was greater using geographic distance and those data are presented. As evident in FST/(1 − FST) values >0.15 are all comparisons of Exuma Sound (HC) and San Salvador (PR) with the other sites, and each of those sets of comparisons shows little change with distance and perhaps even an inverse relationship.The pattern of increasing genetic differentiation with geographic distance suggested by the el tests . Plots oA. elisabethae in The Bahamas. An initial Structure analysis, which included all 13 sites exhibited a best fit model of K = 2 (data not shown) in which colonies from Exuma Sound (HC) and San Salvador (PR) generally belonged to one population and those from the other sites to a second population. Subsequent analysis without the Exuma Sound (HC) and San Salvador (PR) collections generated highly variable results. LnP[k] values from the Structure analyses did not monotonically increase with increasing K, and there were high levels of variance at K values >3, both of which suggested the simulations were not converging. Increased steps  had no appreciable effect on the results. Repeating the analysis using all 10 loci; i.e., including those in which null alleles were present, also indicated K = 2 when all 13 sites were included  of genetic distances  identifif[137] = 0.999; adults f[137] = 0.972). As that locus was unlikely to provide useful information in subsequent analyses it was also dropped and the analyses of recruits are based on 6 loci. Statistical comparisons between sites and years were restricted to collections with 20 or more recruits. Pairwise FST  and between the CHSL adults and CHSL 2012 recruits (FST = 0.011). Numbers of recruits collected from the sites were highly variable between years and sites, with collections ranging from 0 to over 100 individuals . In totawise FST  between distance . Two cas in 2009 . As diffLarge recruit collections across multiple years were available from CHR (6 y) and CHSL (2y). Those two sites were less than 2 km apart from each other. AMOVA of those data, comparing the two sites with adults and recruits and comparing adults to recruits crossed with years, did not identify significant differences between recruits and adults, between years nor between the two sites . StructuP = 0.93). Log likelihood ratios were used to compare assignments and determine if the best assignment was a statistically (P < 0.05) better assignment than the other assignments. Only 2 of the 776 recruits could be definitively be assigned to a single source location. Assignments are presented in Given the similarity among sites along the LBB it is not surprising that assignments of recruits in Geneclass2 were almost never definitive; 46% of the assignments had probabilities less than 0.5, and only 12% of the assignments had probabilities greater than 0.90. There was no difference in those proportions between the 4 sites  probabilities and/or assignment probabilities to closer sites were similar. The inability to definitively assign LBB recruits to sites is a consequence of the IBD pattern. Close sites are genetically similar, and thus the probability of accurately assigning individuals to a single site is low.The major findings of this study are: (1) adult populations along the Little Bahama Bank (LBB) exhibited a clear pattern of isolation by distance (IBD) which described 86% of the variance in pairwise genetic distances, (2) increasing the spatial scale to include sites outside the LBB separated by larger geographic distances and open ocean generated an IBD signal but the relationship is better described as isolated clusters of populations, (3) analysis of recruits from 4 sites on the LBB from up to 6 years did not detect differences between years nor differences with adult populations consistent with the conclusion that the sources of the vast majority of recruits were the local or adjacent populations.Many marine species have larvae with long life spans and are distributed over broad expanses of ocean. Those traits and the presence of currents that can seemingly carry larvae over long distances suggest that panmixia should be common. Some reef species are undifferentiated across ocean basins , but, asA. elisabethae in The Bahamas, where the role of the different processes is dependent on geographic scale.Seascape genetics  incorporA. elisabethae along the LBB provides a remarkably good fit to an IBD model, explaining 86% of the variation in genetic differentiation along the LBB. The southern edge of the LBB does not support a continuous well developed reef community. None-the-less, sites that support A. elisabethae are apparently common enough to create stepping stone populations, which in concert with A. elisabethae larval dispersal generates an IBD model.IBD has been found in a large array of reef species including reef fishes , gastropA. elisabethae on the LBB are distributed in a linear array of populations. In such cases, the slope of the regression  can be used to estimate variance of the dispersal kernel using the equation b = 1/(4Dσ2), where D is the population density and σ2 is the variance of the dispersal kernel . Assuming the suitable habitat zone is 200 m wide the estimate of density is D = 1.48 × 105 km−1 of reef tract. If A. elisabethae was distributed continuously that would correspond to σ of 83 m. However, A. elisabethae is patchily distributed along the length of the LBB, with several kilometers of high abundance often followed by kilometers in which the species is virtually absent. In addition, all reproductive size octocoral colonies are not equally successful in either producing or fertilizing eggs  and San Salvador (PR) in Among l to EGG  but breal to EGG . Both obl to EGG . AlternaA. elisabethae in The Bahamas, is best described as sets of regional clusters. IBD can be found within areas such as the LBB when the distribution of reefs within those clusters and the sampling intensity is great enough. This illustrates how patterns of differentiation among populations are generated by a mix of IBD along reef tracts and isolating barriers occurring over larger distances and across oceanographic barriers. Porites lobata where a significant IBD pattern was identified as well as a Structure analysis that clearly divided the sites into two populations.Population structure of A. elisabethae. Similarly, the gorgonian Paramuricea clavata, which surface broods, exhibited distinct structure between regions across the Mediterranean and, as in our results, an IBD signal within some  does not preclude the possibilty of unusual events but the similarity of those recruits to adults which live for decades (Genetic analyses of recruits estimates current patterns of gene flow and thus connectivity on an ecological/demographic time scale. The population structure of the  decades  indicate decades  and “swe decades  were notAnalysis of recruits over multiple years also provides the opportunity to look for evidence of selection modulating the variability in settling recruits. Most of the recruits were collected 1 to 2 months after spawning. Selection against migrant genotypes could have occurred during that time period, but the lack of genetic difference between recruits and adult colonies suggests that maintenance of this pattern was more likely a function of local recruitment than selection limiting connectivity.A. elisabethae larvae disperse over distances most commonly on the scale of 102 m. Some larvae may settle almost immediately (A. elisabethae in Bermuda (σ, where σ is the standard deviation of the dispersal kernel. That describes the environment along the edges of both the Little Bahama and Great Bahama Bank. It suggests that population demographics is highly dependent on self-seeding. A. elisabethae is harvested in The Bahamas, with harvesters cropping colonies which are then allowed to recover. The movement of A. elisabethae larvae over distances of 10s and 100s of meters but not often further suggests that harvests or naturally occurring disturbances at those or greater scales will depress recruitment and slow recovery of populations. The slow recovery suggested by these patterns may also explain the patchy distribution of A. elisabethae where some sites have dense populations while other seemingly similar sites have few or none of the species. These differing densities may be a reflection of the history of the populations and not necessarily the suitability of the sites. Both the frequency and intensity of disturbances to marine systems and particularly coral reefs appears to be increasing (A. elisabethae low dispersal distances indicates that self-recruitment is important to the maintenance of populations. Incorporating the correct scaling in management plans will be critical to the maintenance of A. elisabethae and similar species.The available data suggest that ediately . The pre Bermuda , demonstcreasing . Underst10.7717/peerj.1019/supp-1Supplemental Information 1Click here for additional data file.10.7717/peerj.1019/supp-2Supplemental Information 2Genotypes of the individuals used in the analysesClick here for additional data file.


Nanorana parkeri, which is endemic to the Qinghai-Tibetan Plateau. Barcoding identifies major lineages W and E. Lineage W has a single origin in a refugium and Lineage E derives from three refugia. All refugia locate in river valleys and each greatly contributes to the current level of intraspecific genetic diversity. Species distribution models suggest that global climate changes will greatly influence N. parkeri, especially in the level of genetic diversity, because two former refugia will fail to provide suitable habitat. Our pipeline provides a novel application of DNA barcoding and has important implications for the conservation of biodiversity in southern areas of the Qinghai-Tibetan Plateau.Anthropogenic global climate changes are one of the greatest threats to biodiversity. Distribution modeling can predict the effects of climate changes and potentially their effects on genetic diversity. DNA barcoding quickly identifies patterns of genetic diversity. As a case study, we use DNA barcodes and distribution models to predict threats under climate changes in the frog  Climatic changes influence organisms and an understanding of how this occurs is important for conservation. More than one line of evidence documents the impact anthropogenic global climate change (GCC) exerts on organisms COI in eukaryotes) to identify matrilines and species, may serve to efficiently identify ESUs and MUs.Genetic analyses form the cornerstone of conservation planning, especially in defining objective evolutionarily significant units (ESUs) and management units (MUs) Species distribution models (SDMs) also provide information useful for conservation planning 2 and has an average elevation of about 4000 m above sea level The Qinghai-Tibetan Plateau (QTP), which covers more than 2.5 million kmIn addition to climatic drivers, geographic features also play a role in the formation of patterns of genetic diversity. In the southern QTP, two mountains stretch from east to west and the Yarlung Zangpo River   occurs bRana kukunoris, a common frog on eastern QTP, revealed a unique genetic pattern compared to other taxa in the region Because of their relatively low mobility and physiological requirements, amphibians are sensitive to environmental changes, especially temperature and precipitation. Further, amphibians retain high-resolution signals of historical responses to environmental perturbations Nanorana parkeri, a median-sized frog belonging to the family Dicroglossidae, is endemic to southern and southeastern Tibet. It occurs at elevations ranging from 2800 to 5000 m in valleys of the YZR and north of the NM N. parkeri. Using the species as model system, we test the effectiveness of a pipeline that combines DNA barcoding and SDMs to identify future threats to genetic diversity in the face of GCC.All the species included in our study  are not N. parkeri  were sequenced for all individuals using universal primers We extracted genomic DNA using standard phenol–chloroform extraction protocol Nucleotide sequences were checked by eye using LASERGENE 7.0 and aligned using CLUSTALX 1.81 COI data were conducted using Bayesian inference (BI), maximum likelihood (ML) and maximum parsimony (MP). BI analyses were performed using MrBayes 3.1.2 Phylogenetic analyses of the We built a median-joining network (MJN) using NETWORK 4.5 COI for N. parkeri, we used the divergence time between N. parkeri and N. pleskei (8.9±2.7 Ma) th generation. Burn-in and convergence of the chains were determined with Tracer 1.5 Different demographic and molecular clock models were compared using path sampling and stepping-stone sampling  [32]. EmCT and FSC. Spatial patterns of genetic diversity based on allelic richness (Ar) and π across the landscape were explored using the GDivPAL function in SPADS.We explored population structure and genetic diversity landscape using SPADS 1.0 N. parkeri, we measured the population structure by three independent analyses of molecular variance (AMOVA) To test for the influences of mountains and rivers on the genetic structure of DFs statistics We investigated past changes of effective population size using the neutral test and mismatch distributions. Tajima's N. parkeri using the maximum entropy model implemented in MAXENT 3.3.3 We inferred the potential geographic range of Random null distributions were built to test for the significance of our SDM. For this test, we built a new SDM using 39 random points . This process was repeated 100 times and the areas under the curves (AUCs) were used as null distributions N. parkeri by projecting our model on LGM climatic layers. Predicted distributions during the LGM were generated by downloading both the community climate system model (CCSM) Assuming niche conservatism over time COI sequences from 39 localities of N. parkeri, plus one sequence each from N. pleskei, N. ventripunctata and N. liebigii. The fragment consisted of 539 base pairs, of which 35 positions exhibited variation and 27 were potentially parsimony informative, resulting in 23 haplotypes in N. parkeri. All sequences were deposited in GenBank . In sublineage E1, significantly negative values of both Tajima's D and Fu's Fs supported population expansions. The mismatch distribution analyses did not reject the sudden expansion model (PSSD = 0.545 and PRAG = 0.609). In sublineages E2, Tajima's D and Fu's Fs were negative, but insignificant. In sublineage E3, Tajima's D was negative but Fu's Fs was positive, yet all values were not significant. The null hypothesis of sudden expansion model was not rejected by mismatch distribution analyses.For Lineage W, the values of Tajima's negative , which inegative  as the SN. parkeri, the AUC of our data was 0.904 and this was significant better than that of a random model (P<0.001).The AUCs from random data ranged from 0.605 to 0.800  and bootstrap proportions ≥70% and Bayesian posterior probabilities ≥90% were treated as being moderately supported. Bootstrap proportions<70% and Bayesian posterior probabilities <90% were treated as being unsupported (*).(TIF)Click here for additional data file.Figure S2River systems in the southern QTP.(TIF)Click here for additional data file.Table S1Detailed information for specimens included in this study.(XLSX)Click here for additional data file.Table S2CT, FST and FSC based on population groups suggested by SAMOVA.Values of F(XLSX)Click here for additional data file.Table S3Values of π and Ar for populations from each locality.(XLSX)Click here for additional data file.Table S4Detailed results of AUC for random and real data.(XLSX)Click here for additional data file.