Conservation strategies are increasingly driven by our understanding of the processes and patterns of gene flow across complex landscapes. The expansion of population genetic approaches into traditional agricultural systems requires understanding how social factors contribute to that landscape, and thus to gene flow. This study incorporates extensive farmer interviews and population genetic analysis of barley landraces (Hordeum vulgare) to build a holistic picture of farmer-mediated geneflow in an ancient, traditional agricultural system in the highlands of Ethiopia. We analyze barley samples at 14 microsatellite loci across sites at varying elevations and locations across a contiguous mountain range, and across farmer-identified barley types and management strategies. Genetic structure is analyzed using population-based and individual-based methods, including measures of population differentiation and genetic distance, multivariate Principal Coordinate Analysis, and Bayesian assignment tests. Phenotypic analysis links genetic patterns to traits identified by farmers. We find that differential farmer management strategies lead to markedly different patterns of population structure across elevation classes and barley types. The extent to which farmer seed management appears as a stronger determinant of spatial structure than the physical landscape highlights the need for incorporation of social, landscape, and genetic data for the design of conservation strategies in human-influenced landscapes. In all kinds of landscapes throughout the world, the extent to which populations are structured across space and time is mediated by pathways of connectivity and physical, behavioral, and temporal barriers to dispersal. The past decade has seen the development of a suite of tools with which to understand the processes and patterns of gene flow across complex landscapes, and the ways in which landscape features affect the structure of populations  in a traditional agroecosystem in southern Ethiopia. The southern Ethiopian highlands present an ideal study system for this investigation, due to the region's mountainous and heterogeneous landscape, diversity of ethnic and cultural groups and social structures, high levels of crop diversity, and the continuing the presence of traditional seed exchange institutions such as local markets and gifting between family and neighbors.A population genetics approach to conservation has been expanded to include research into traditional agricultural systems, where decisions by farmers regarding how and where to access diversity can determine patterns of geneflow, as well as isolation, drift, and local adaptation . Native vegetation includes mixed deciduous woodlands, dry evergreen montane forest, and alpine grasslands. Annual rainfall is bimodal, and mean annual temperatures range from 10°C to 25°C (MoA 2000).kebeles  of 500–1000 families. These are the smallest division of the federal government and are the scale at which many extension activities are organized. The Gamo highlands are spread across five districts, each made up of ten to twenty communities, within the Gamo-Gofa zone and the Southern Nations, Nationalities, and Peoples Region (SNNPR) of Ethiopia.These densely populated highlands are home to nearly one million people FDRE . The regAgriculture in the Gamo highlands is based on a diverse combination of annual and perennial crops, agroforestry, and livestock management , mid-altitude (2500–2700 m), and high (2800–3000 m) . The composition of barley varieties in each community was compared using a Bray–Curtis similarity index using EstimateS software . Genetic differentiation between sites, varieties, and elevation groups was estimated using F-statistics, and analysis of molecular variance (amova) was calculated to partition genetic diversity between sites and varieties. These analyses were performed using Genalex Software  of allele frequencies at each community, variety, and variety within community was performed in JMP. Resulting axes were then analyzed for clustering by location and elevation.Multiple linear regressions as well as Mantel tests were used to test the extent to which pairwise Individual genotypes were then analyzed to identify cryptic population structures. Genalex was used to run a principal coordinate analysis (PCoA) on all multilocus genotypes, as well as on samples from six-rowed and two-rowed varieties separately. Significant differences in values for PCoA axes were used to identify distinct population segments.a priori population identification, was carried out in STRUCTURE software , as well as with geographic distance . According to surveyed farmers, seed flow largely occurs between communities of the same elevation, and farmers identify distinctive low- and high-elevation varieties.One quarter of barley fields were planted with seed from local markets, and this percentage decreases at higher elevations. Households in the Gamo attend, on average, four different markets each week, and communities share markets with nearby communities. Six-rowed varieties were more widespread in the markets, with each variety found in an average of 4.8 markets of the eight surveyed markets, while two-rowed varieties were found in an average of two markets each. Six-rowed varieties were also less expensive, sold for an average of 2.7 Ethiopian birr per kg, while seed for two-rowed varieties sold for an average of 4.2 birr per kg. The distribution of named barley varieties across the Gamo landscape, as measured by a Bray–Curtis index of similarity between variety names in each community (Bray and Curtis Bmac223) had 25 alleles; the least (Bmac579 and Bmac316) had four each. One locus (Bmac136) did not amplify in the majority of samples and is excluded from further analyses.Samples were genotyped at 14 microsatellite loci, with a total of 132 alleles  was heterozygous at one or more loci, reflecting low levels of outcrossing. ci Table . DespiteHe) at each site ranged from 0.49 to 0.63 (Table He = 0.65) than mid- and high-elevation sites (He = 0.57 and 0.55). The lowest levels of heterozygosity were found in two two-rowed varieties (He = 0.40 and 0.42), while the highest were found in varieties of mixed row type found only at low elevations (He = 0.61 and 0.67).Expected heterozygosity (amova) partitions 11% of diversity between sites, indicating low but significant structure at the community scale. Overall FST between communities at all loci is 0.137, and pairwise FST values ranged from 0.02 to 0.15. FST values at each locus range from 0.08 to 0.15, with one outlier (Bmac579) at 0.35.Analysis of molecular variance , and to a lesser extent with geographic distance between sites (P < 0.03) based on Mantel tests.Structure between farmer-named varieties represents 15% of the genetic variance, based on Principal component analysis (PCA) of allele frequencies of sites and varieties identified three distinct clusters Fig. . The firThe most evident pattern in both population-based and individual-based analyses is the distinctiveness of barley varieties unique to low populations. A principal coordinate analysis (PCoA) of 682 multilocus genotypes displays the distinct nature of low-elevation varieties Fig. A. Genotya priori populations. One low-elevation site (Bula) remains as an FST outlier; without this site, pairwise FST values between sites are not significantly correlated with elevation differences, and FST among the remaining sites is 0.09. amova indicates that sites account for 8% of variation, while variety names account for 5% of variation.With the removal of specific low-elevation varieties, the remaining six-rowed barley varieties across eleven sites show little spatial structure based on FST values between communities retain a weak but significant relationship with distance (P < 0.01), and PCA of allele frequencies for sites and varieties show both north–south and elevation patterns in these varieties. Individual PCoA of genotypes also identifies weak, but significant clustering along north–south and elevation gradients (P < 0.001).However, pairwise STRUCTURE analysis at k = 2 through 10 do not indicate population assignments associated with site or variety. Using the δk method, the most likely structure lies at k = 5, and analysis identifies a clinal pattern across the region, as inferred populations are drawn disproportionately from northern or southern sites, or high or mid-elevations. Two inferred populations contain nearly entirely northern low- and mid-elevation individuals, while two contain a mix of high-elevation northern samples and southern samples from all elevations, indicating a gradient across the region Fig. A. The fiFST between communities was 0.222, and pairwise FST values ranged from 0.039 to 0.224. amova partitions 23% of variation between communities, indicating strong differentiation. Pairwise FST was correlated with geographic distance between communities . In addition, contrary to findings in six-rowed samples, variety names were correlated with genetic differentiation, with amova partitioning 25% of genetic variation between varieties. PCA of allele frequencies for each variety and community ; however, there was no differentiation by location or elevation.For common six-rowed varieties, seed weight and flowering time traits showed geographic patterns coincident with the observed genetic structure. Samples from northern mid- and low elevations had higher seed weights and shorter flower times than samples from high elevations and southern sites, the same split identified by STRUCTURE Fig. . Among tOur results indicate disparate patterns of exchange and isolation between elevation zones and barley types, with two patterns arising. The first is the distinctiveness and diversity of low-elevation varieties. The second is the marked difference in population structure between six- and two-rowed barley types, which indicates that farmer management affects crop population structure, independent of the physical landscape.Samples from low-elevation communities differ from those at high- and mid-elevation communities at several loci, and the two southern low communities especially have significantly different allele frequencies from other sites and from each other. PCoA and STRUCTURE analysis show that differentiation of low-elevation communities is driven by a specific set of varieties that are grown only at these elevations, while more widespread varieties do not show structure by elevation. This indicates that seed exchange does occur across altitudinal gradients for some named varieties. Population structure corresponding to elevation is common in landrace barley. In India, altitude was seen to be the largest factor in the structure of landrace barley populations (Pandey et al. The similarity of low-elevation varieties throughout the study area at several loci, and the relative similarity of high-elevation communities to one another, also suggests the possibility that there is differential selection occurring between high and low communities. Recent studies of crop landraces have shown patterns of asymmetrical adaptation, in which high altitude populations are more narrowly adapted than low-elevation populations (Mercer et al. In this study, high-elevation samples of all types have longer flowering times than their lower-elevation counterparts Table , Fig. 6.Farmers in low-elevation communities may select for a different set of conditions, or may not employ strong selection, allowing diverse genotypes to remain in the population. The diversity of both alleles and phenotypic characteristics found within communities and named varieties, and the fact that low-elevation varieties have lower seed weight, indicating potentially lower grain quality, suggest a lack of strong directional selection at low elevations.Six- and two-rowed barley populations have distinctly different population structures, suggesting that differential management and exchange strategies can lead to different spatial genetic patterns on the same physical landscape.Two-rowed varieties show spatial clustering between nearby communities, indicating movement between neighboring communities, although not over long distances, and a lack of strong barriers to exchange due to elevation. Two-rowed barley also shows distinct clustering by farmer-named variety. PCA and STRUCTURE analysis indicate that variety names describe genetically distinguishable entities, even in cases in which physical characteristics such as seed color and size are similar between varieties, implying attention to variety management in these types. The phenotypic data also distinguish between named varieties, most clearly in seed weight.Six-rowed varieties, however, show a much larger-scale spatial pattern. Neither sites nor varieties represent distinct genetic entities. Instead, there is a broader pattern spanning the northern and southern portions of the range, as well as the elevation gradient. These patterns are evident both in the genetic data and the phenotypic data, with significant differences between northern low and mid-elevation populations and southern and high populations Figs A and 6. That variety names do not play a meaningful role in the genetic structure of these varieties indicate that there is significant gene flow between them, despite identifiable differences in seed color and other characteristics used by farmers for identification. However, it is quite plausible that landraces may retain distinct morphological characteristics in the face of high geneflow, even when neutral variation does not distinguish between them. Farmers select seed based on specific identifiable traits for each variety, and therefore, those varieties may share the specific genes responsible for this distinctiveness, while showing little differentiation at neutral loci (Barnaud et al. There are several features of barley seed exchange, as discussed by farmers throughout the interview process, that provide insight into the observed patterns in barley population structure. The first is farmer focus on perceived agroecological adaptation when acquiring seed. The elevation from which seed originates is the primary factor used by farmers in seed acquisition, and thus, seed exchange occurs more frequently and in greater volumes between farmers and communities at similar elevations. This practice is likely related to the genetic isolation of barley in low-elevation communities.Interviews indicated that, as barley is less important at low elevations, not only do low-elevation farms cultivate fewer barley varieties, they are also less seed secure for barley. At high elevations, lower levels of seed turnover create conditions for greater selection, both natural and by farmers, and therefore greater adaptation to local conditions. These practices, and the lesser importance of barley to low-elevation farmers in the Gamo, may shed light on the different differences in diversity and structure of high- and low-elevation barley.The second lesson learned through the interview process is the differentiation in strategies used by farmers in the management of two-rowed and six-rowed types. The differential use and management strategies large plots, often intermixed with new seed, and selected for productivity, as opposed to small plots cultivated for specific taste, color, and texture qualities may be responsible for the difference in population structure between these barley types. The greater prevalence and lower price of six-rowed varieties in markets suggests that markets are a stronger force in the structuring of six-rowed varieties, and the long-distance exchange evident in genetic and phenotypic patterns. Farmers are less dependent on markets for the procurement of seed for two-rowed varieties, acquiring seed from friends, family, and neighbors. This strategy provides a level of explanation for both the tight clustering between nearby communities and the genetic fidelity to variety names found in two-rowed varieties.These farmer interviews provide explanatory information for the observed genetic patterns, without which the genetic data may be misinterpreted or cryptic. The structure seen in these populations cannot be understood purely in the context of physical barriers or divergent selection pressures. Interpretation requires knowledge of reluctance to exchange seed with low-elevation communities, and differential management for two- and six-rowed varieties, which can only be gleaned through concurrent social science methods.Landscape and conservation genetic methods are increasingly being adapted for use in human-influenced systems, such as those where agriculture, livestock husbandry and grazing, hunting, and harvesting are key components. In these landscapes, neither the physical landscape nor the biology of the organism of interest can fully explain the patterns and processes of population structure; rather, the social landscape of farmer management and exchange determines the distribution of genetic diversity of numerous species. In addition, conservation scientists and practitioners in agricultural landscapes are increasingly recognizing the importance of considering farmers' economic and cultural needs in designing appropriate strategies (Garcia et al. In the Gamo highlands, farmer management of seed and seed exchange leads to three distinct sets of population processes in the same physical landscape: isolation and diversification of low-elevation varieties, broad geographic patterns in productive varieties, and clustering by location and variety name in specialty varieties. Farmer interviews regarding management provide crucial information about the extent and directionality of seed flow and factors influencing selection. These social landscape features interact with steep altitudinal gradients over space to create specific genetic patterns, and those patterns and processes will differ between landscapes, species, and societies. An understanding of the social landscape is required to both capture the underlying ecology and to design appropriate strategies for conservation.


Anopheles atroparvus. Levels of population differentiation of An. atroparvus from southern Europe were characterized as a first attempt to elucidate patterns of population structure of this former malaria vector. Results are discussed in light of a hypothetical situation of re-establishment of malaria transmission.There is a growing concern that global climate change will affect the potential for pathogen transmission by insect species that are vectors of human diseases. One of these species is the former European malaria vector, Genetic and phenotypic variation was analysed in nine mosquito samples collected from five European countries, using eight microsatellite loci and geometric morphometrics on 21 wing landmarks.FST <0.086) and phenotypic differentiation were detected among An. atroparvus populations spanning over 3,000 km distance. Genetic differentiation (0.202 <FST <0.299) was higher between the sibling species An. atroparvus and Anopheles maculipennis s.s. Differentiation between sibling species was not so evident at the phenotype level.Levels of genetic diversity were comparable to those reported for tropical malaria vectors. Low levels of genetic . While these results may suggest considerable levels of gene flow, other explanations such as the effect of historical population perturbations can also be hypothesized.Levels of population differentiation within  Under the present scenario of human-driven environmental changes, global climate change is one the most relevant concerns. Climatic predictions point to a significant increase of summer droughts in south-western European regions over the next 60 years, but there is also an increased risk for more frequent flash floods during the same period . Since tca. 243 million cases, and an estimated 863,000 deaths attributed to malaria [Malaria is the vector-borne disease with the highest impact in the World's human population. In 2008, there were th century [Malaria was endemic in Europe until the mid 20 century . The era century . Since t century .Although the risk of malaria re-emergence is uncertain for Western/Southern European countries, the present climate change situation gave rise to some concern. One of the reasons was a predicted increase in mosquito vectorial capacity, especially in the southern countries of Europe and the Mediterranean . This inAnopheles maculipennis complex that are still widely distributed throughout the continent [Anopheles atroparvus, Anopheles labranchiae and Anopheles sacharovi were the main malaria vectors in the European region. In Europe, the distribution of An. atroparvus ranges from Britain to Russia (north Caucasus). It is absent in some Mediterranean regions, such as southern Italy, Greece and Turkey [The former European malaria vectors were mainly members of the ontinent . This cod Turkey .An. atroparvus and its sibling species has decreased in the last decades. However, the concern with malaria re-emergence has resulted in a revival of interest in European Anopheles mosquitoes. In this context, knowledge about the population structure and levels of gene flow in this species is of major importance to infer the potential for the re-establishment and spreading of malaria transmission under a scenario of local introduction of parasites. Furthermore, if necessary, it will be a critical tool for the design of vector control plans. In this study, genetic and phenotypic variation was analysed, using microsatellites and geometric morphometrics, in order to determine patterns of population structure of An. atroparvus in Southern Europe.Because its importance as a disease vector has declined, research on the biology of Adult mosquitoes were sampled by indoors resting collections  that took place in summer time (June to October) between 2006 and 2008 in 9 collection sites from five European countries Figure . All sitAn. maculipennis complex was carried out by PCR-RFLP using protocols derived from those described by Proft et al [® Flexi Buffer , 2.5 mM MgCl2, 200 μM dNTP's , 5 μM of each primer and 1U of Go Taq polymerase . The thermal cycling profile was as follows: 94°C for 5 min; 34 cycles of 94°C for 30 sec, 53°C for 30 sec and 72°C for 30 sec, followed by a final extension at 72°C for 7 min. A RFLP protocol allowed the identification of four sibling species of the An. maculipennis complex . For the restriction reaction, 5 μl of each ITS2 PCR product was added to 1X restriction enzyme buffer  and 1.25U of Cfo 1  enzyme, in a total volume of 20 μl, followed by incubation for 3 h at 37°C. Digested fragments were separated by electrophoresis on an ethidium bromide stained 2% agarose gel, showing sizes that were diagnostic for each species. For those specimens presenting restriction fragments with lengths compatible with An. labranchiae/An. maculipennis s.s. (300 bp), a second enzymatic digestion was performed with HpaII  using the same RFLP protocol as above. The diagnostic restriction patterns are: An. atroparvus (389 bp fragment), An. melanoon (fragments with 108 bp and 135 bp) and after the second enzymatic digestion An. labranchiae (279 bp fragment) and An. maculipennis s.s. (201 bp fragment).Genomic DNA was extracted from single mosquitoes following a phenol-chloroform procedure . Speciesft et al . The Intft et al . PCR was® Flexi Buffer (Promega) 1.5 mM MgCl2, 200 μM dNTPs, 0.5 μM of each primer, 0.5U of Taq polymerase and 1 μl of DNA template. Cycling conditions included an initial denaturation at 94°C for 5 min, followed by 30 cycles of 94°C for 30 sec, annealing temperature  for 30 sec, elongation at 72°C for 30 sec; and a final extension step of 5 min at 72°C. Amplified fragments were separated by capillary electrophoresis in an automatic sequencer  at Yale's DNA Analysis Facility at Science Hill. Fragment sizes were scored using GeneMarker v1.4 .Ten dinucleotide repeat microsatellites were amplified using fluorescently labelled  primers previously described . PCR reai.e. number of different alleles, A), expected heterozygosity (He) inbreeding coefficient (FIS) and tests for differences of A and He among groups were computed using FSTAT v. 2.9.3.2 [Allele diversity  and hence which differentiation statistics would better describe the genetic structure of the populations sampled. Briefly, allele size at each locus was randomly permuted among allelic states  to simulate a distribution of expected RST values (pRST) and 95% confidence intervals (CI) under the null hypothesis that differences in allele sizes do not contribute to population differentiation [A permutation test available in the software SPAGEDI v. 1.3a  was usedntiation .FST estimates calculated according to Weir and Cockerham [FST [Genetic differentiation among samples was quantified by pairwise ockerham  using ARockerham . With thham [FST  were tesham [FST . This meSequential Bonferroni corrections were used to adjust critical probability values for multiple tests in order to minimize type I errors .N = 45; Aveiro, N = 52; Barrancos, N = 84; Montalegre, N = 61) and the samples from Tarragona/Spain (N = 66), Mèjanes/France (N = 47), Venice/Italy (N = 44) and Salcioara/Romania (N = 29)  medium. Slides were photographed using a Leica® MZ-7.5 stereoscopic zoom dissection microscope with a DC-300 digital camera system. In order to reduce the measurement error, specimens were digitalized twice and scored by the same person. The second session of measurement was conducted after specimens were removed and replaced under the stereomicroscope in order to take positioning error into account [Morphometric analysis was performed with four samples collected in Portugal , available in the software STATISTICA 9.0 . The Mahalanobis distance takes into account the covariance among the variables in calculating distances and it is widely used in cluster analysis and other classification techniques. With this measure, the problems of scale and correlation inherent to Euclidean distances are no longer an issue.A correlation matrix between samples was constructed using squared Mahalanobis distances , Portugal, were all identified as An. maculipennis s.s., while the remaining samples were identified as An. atroparvus.A total of 473 female mosquitoes of the An. atroparvus varied between 0.588 (MacuUF) and 0.876 (MacuI3)  while the sample from Romania had the lowest . Samples from Portugal and France showed significantly higher values of A and He  than the samples from Spain, Italy and Romania. The only sample of An. maculipennis s.s. revealed a smaller He (0.504) and A (5) than the least diverse sample of An. atroparvus (Romania).Samples of 45 individuals from each collection site were used for microsatellite analysis. Of the 10 microsatellites analysed, two (MacuO185 and MacuW149) were monomorphic in most populations, and were thus excluded from further analysis. The mean expected heterozygosity per locus in P > 0.0027; adjusted significance level for 28 pair-wise tests per sample: α' = 0.0018).Exact tests of linkage disequilibrium between pairs of loci were non-significant for all the samples after Bonferroni corrections , MacuO177 (5 out of 9 tests) and MacuGQ (4 out of 9 tests). Coincidently, these loci exhibited the presence of null alleles in most samples analysed as revealed by MICROCHECKER . For these loci, a corrected genotypic database was obtained according to the procedures described in [There were 15 significant single-locus tests of Hardy-Weinberg proportions out of 72 performed  whereas the lowest were detected between Portugal and France (0.010 ≤ FST ≤ 0.016). There was a significant correlation between linearized FST and geographic distance among An. atroparvus samples (Mantel Test: P = 0.022). However, when Romania was removed from the analysis, the correlation was no longer significant (Mantel Test: P = 0.181).Pairwise An. maculipennis s.s. were all significant and gave FST estimates above 0.200, i.e. more than two-fold greater than those among An. atroparvus samples. This differentiation was evident in the FCA  with the samples of France and An. maculipennis s.s. displaying considerably larger wings.When a PCA was conducted on the 21 wing landmarks, the two first PCs summarized 19.45% and 15.13% of the total variance, respectively. The first PC suggests some differences in the relative positions of the landmarks regarding the base of the wing. Main deformations centred on the medial of the wing on landmarks 13-14 and 15-16  and farthest samples , respectively, there was no clear pattern between phenotypic differentiation and the origin of the samples. Accordingly, there was no significant correlation between DM estimates and geographic distance between collection sites (Mantel Test: P = 0.073). No significant correlation was also observed between Mahalanobis distances and genetic distances as measured by pairwise FST (Mantel Test: P = 0.658). As opposed to genetic differentiation, comparisons between An. maculipennis s.s. and An. atroparvus did not produce the highest DM values.Pairwise phenotypic differentiation among ce Table . AlthougAn. atroparvus indicates levels of genetic diversity similar to those described for other anopheline species of tropical regions, particularly from sub-Saharan Africa. The estimates of mean expected heterozygosity (0.61≤ He ≤0.73) are within the range of those obtained for the Afrotropical primary malaria vectors Anopheles gambiae s.s. , Anophee ≤0.78; ) and Anoe ≤0.78; ). In teme ≤0.78; . The hige months ,36.An. atroparvus samples spanning over 3,000 km suggest a shallow population structure weakly correlated with geographic distance. This was evident when the most distant sample of Romania was excluded from the isolation-by-distance analysis. In addition, there was no particular pattern of population subdivision that could be attributable to the presence of two potential barriers to gene flow, the Pyrenees and the Alps. These mountain chains physically isolate the populations from the Iberian and Italian Peninsulas, respectively. For example, FST estimates between France and Portugal (0.010-0.016) were considerably lower than those between Portugal and Spain (0.048-0.056).Estimates of genetic differentiation among An. atroparvus are consistent with those observed in most primary malaria vector species from tropical climates . Among iewed in . Evidencabiensis , Anophel A and D  and Anop minimus . In the An. atroparvus samples and the only An. maculipennis s.s. sample analysed, a result consistent with their sibling species status. This was particularly evident by the FCA analysis in which there was a complete cluster separation between the two species. Values of FST between 0.20 and 0.30 are similar those described between other anopheline sibling species .An. atroparvus and An. maculipennis s.s. was not so evident. There was a partial overlapping between the clusters of the two species in the PCA. Furthermore, most An. atroparvus specimens of France shared the same dimensional space with An. maculipennis s.s. With the exception of this comparison, all the remaining An. atroparvus samples had significantly lower wing centroid sizes. These results concur with the notion of a relatively recent divergence time among the Palearctic members of the An. maculipennis complex not sufficient for the accumulation of phenotypic differences, in contrast to that of the Nearctic members of the complex [An. gambiae s.s. and An. arabiensis in which the later species displayed significantly larger measures but still with overlapping distributions [Phenotypic differentiation between  complex ,44. A siibutions .An. atroparvus, low to moderate levels of phenotypic differentiation were detected between samples by pairwise estimates of DM. However, there was no correlation between phenotypic differentiation and geographic or genetic distances. In mosquito populations, phenotypic variation is influenced by an assortment of environmental factors that include temperature, altitude, nutritional factors at the immature stages and host population distribution [Within ribution -47. The An. atroparvus were analysed for the first time over a range of more than 3,000 km.The low levels of differentiation observed were not correlated with geographic distance or with potential physical barriers separating these populations. While these results may suggest considerable levels of gene flow, other explanations such as the effect of historical population perturbations can be hypothesized. Further genetic studies involving the analysis of temporal samples of An. atroparvus will help clarifying the recent demographic history of this species. In addition, analysis should also be extended to northern European locations, where An. atroparvus populations are also established and sometimes display biological differences [The genetic and phenotypic variation among populations of the former European malaria vector ferences . Such anThe authors declare that they have no competing interests.An. maculipennis s.l. samples. Molecular analyses were done by JLV, CAS, RA, PS and TLS. JP, PS and JLV carried out the statistical analysis of the genetic data. Geometric morphometrics was performed by BA, SSC, BD and NO. The study was conceived and design by JP, BA, DF, VER, MDB, RR and GN. JP, JLV, PS, BA and BD drafted the manuscript with the contributions of TLS, VER and RA. All authors read and approved the manuscript.JLV, CAS, EF, JML, CT, HB, MDL, LT, RA, MDB, SM-C, DB, RR, GN and DF carried out mosquito surveys and morphological identification of Anopheles atroparvus in Europe Estimates of microsatellite genetic variability of ATROdiversity.pdf portable document file (*.pdf) Estimates of microsatellite genetic variability of Anopheles atroparvus in Europe Estimates of number of alleles, expected heterozigosity and inbreeding coefficient (FIS) for 8 microsatellites.Click here for file


Miscanthus is a perennial rhizomatous C4 grass native to East Asia. Endowed with great biomass yield, high ligno-cellulose composition, efficient use of radiation, nutrient and water, as well as tolerance to stress, Miscanthus has great potential as an excellent bioenergy crop. Despite of the high potential for biomass production of the allotriploid hybrid M. ×giganteus, derived from M. sacchariflorus and M. sinensis, other options need to be explored to improve the narrow genetic base of M. ×giganteus, and also to exploit other Miscanthus species, including M. sinensis (2n = 2x = 38), as bioenergy crops. In the present study, a large number of 459 M. sinensis accessions, collected from the wide geographical distribution regions in China, were genotyped using 23 SSR markers transferable from Brachypodium distachyon. Genetic diversity and population structure were assessed. High genetic diversity and differentiation of the germplasm were observed, with 115 alleles in total, a polymorphic rate of 0.77, Nei’s genetic diversity index (He) of 0.32 and polymorphism information content (PIC) of 0.26. Clustering of germplasm accessions was primarily in agreement with the natural geographic distribution. AMOVA and genetic distance analyses confirmed the genetic differentiation in the M. sinensis germplasm and it was grouped into five clusters or subpopulations. Significant genetic variation among subpopulations indicated obvious genetic differentiation in the collections, but within-subpopulation variation (83%) was substantially greater than the between-subpopulation variation (17%). Considerable phenotypic variation was observed for multiple traits among 300 M. sinensis accessions. Nine SSR markers were found to be associated with heading date and biomass yield. The diverse Chinese M. sinensis germplasm and newly identified SSR markers were proved to be valuable for breeding Miscanthus varieties with desired bioenergy traits. Miscanthus (Gramineae) is a genus of rhizomatous perennial C4 grass. The features of rapid growth, efficient use of radiation, water and nutrient, and strong tolerance to biotic and abiotic stresses make Miscanthus an attractive biofuel crop. Intensive researches done in Europe and USA proved the widely cultivated species of M. × giganteus a dedicated energy crop M. × giganteus is a sterile triploid hybrid from a spontaneous cross between M. sacchariflorus and M. senensis. The sterility of M. × giganteus make it difficult to genetically improve the species and result in the narrow genetic basis that reduce climatic adaptation and overwintering survival in some extreme conditions M. sinensis, originated from the tropical and subtropical regions of Asia and the progenitor of M. × giganteus, is one of the most important members in Miscanthus genus M. sinensis might be better than M. ×giganteus in some places Miscanthus genus, including M. sinensis, as bioenergy crops, or to enrich the genetic diversity of M. × giganteus using M. sinensis germplasm.M. ×giganteus, M. sinensis can be used not only as a genetic resource for development of new hybrids or improvement of fertile lines, but also as an alternative biofuel crop with high potential in biomass production based on a series of studies on agronomy, productivity and utilization M. sinensis germplasm shows rich morphological variability related with the distinct original environments. For development of new Miscanthus varieties, understanding of the genetic diversity and target traits of the M. sinensis germplasm is necessary. Intensive studies on Miscanthus in the past mainly focused on the biomass potential of M. ×giganteus. The studies conducted in M. sinensis included genetic map construction, QTL mapping and genetic diversity evaluation using a limited number of M. sinensis germplasm accessions MiscanthusM. sinensisAs one parent of M. sinensisM. sinensis has accumulated a broad range of genetic variation for its adaptation to various environmental conditions in China. The diverse pool of M. sinensis germplasm can be exploited to improve its tolerance to biotic and abiotic stresses or to optimize properties for cellulosic ethanol production.China is the major distribution area or diversity center of MiscanthusM. sinensisM. sinensis germplasm. In the present study, a large collection of 459 Chinese M. sinensis accessions, covering all of the distribution areas in China, was adopted. The M. sinensis collections were genotyped using 23 SSR primer pairs developed based on the genome sequence of Brachypodium distachyonM. sinensis germplasm.Transferable SSR markers are practical and efficient for genetic diversity evaluation of M. sinensis accessions. Among the 115 alleles, 16 were the rare and 90 were the frequent alleles. On the average, 4.3 alleles were detected per SSR primer pair, with a range of 1–16. For the germplasm panel, the rate of polymorphic alleles, Nei’s genetic diversity (He) and polymorphism information content (PIC) were 0.77, 0.32 and 0.26, respectively  as 1 to 10. Based on an Evano test, the result showed that 5 was the optimum k number of subpopulations, indicating at least five distinct groups in the M. sinensis panel  between G1 and G4, and the smallest (0.12) between G3 and G5  and 2nd (2010) year after establishment of the Miscanthus field. Obvious phenotypic variations were observed for heading date (156–360 days), plant height (0.61–3.35 m), and biomass yield (0.12 to 38.49 Mg/ha) in the two years . Therefore, plant height may be used as an indicator for selection of high biomass yield in Miscanthus breeding. The average plant height in 2010 was significant higher than that of 2009 across the regions from 18°50.076N to 40°32.196N (p<0.001). The plant height was relatively short for the accessions sampled outside the region of 20°-36°N, due to early heading (>36°N) and failure of transition from vegetative to reproductive growth (<20°N) respectively, indicating a close correlation between that the environmental adaptability and the original site  than the 1st year (2009) after the Miscanthus field establishment. An obvious trend of biomass decrease was observed in the two years with increase of the original latitude, except for the abnormal growth without successful reproductive stage of the accessions from Hainan (<20°N)  . The accectively . SignifiM. sinensis accessions. A total of nine markers were found to be significantly associated with heading date and biomass yield (P<0.01). Among the associated markers, five were detected across the two years  and decreased linearly with the original latitude (x2). Regression equations were obtained for 2009 and 2010, respectively, Y = 343.80+1.04x1−14.79x2  and Y = 520.71+4.31x1−39.24x2 .Results of regression analysis showed that biomass yield (Y) increased linearly with plant height  were distributed in the Yun-Gui Plateau in southwest China and the areas around He’nan province in north-central China. The altitude of the Yun-Gui Plateau is high, with an average of 936 m in Guizhou and 1388 m in Yunnan of the collected accessions. Most accessions collected in this area were clustered together in this group . He’nan M. sinensis in south and central China. All these results indicated that Hainan island in south China and Liaoning province in northeast China could not possibly be the origin of M. sinensis, and it was not be too long ago that M. sinensis spread to these areas In M. sinensis accessions were highly differentiated, possibly due to the ease in which the arista of M. sinensis seeds sticking to the bodies of animals, as well all the characteristics that Miscanthus being a wind pollinated genus M. sinensis accessions could plausibly be attributed to seed-mediated and pollen-mediated gene flow from region to region. As is well known, among a large number of alleles, only few rare alleles could account for geographic differentiation in the process of speciation. Accordingly, genetic difference existed among subpopulations but most of the genetic variation was still maintained within subpopulations. Thus further studies should be conducted to better understand the mechanism of geographic differentiation of M. sinensis germplasm in China.Furthermore, AMOVA analysis agreed with the clustering pattern, the NJ tree and the genetic distance measurements among the five subpopulations, implying that the 459 Chinese M. sinensis showed great potential to be feedstock for bioethanol M. sinensis on a wider climate range and in various environments requires enlarged genetic variability M. sinensis germplasm in this study harbored great genetic diversity, and showed significant genetic structural differentiation and significant phenotypic variation in heading date, plant height and biomass/feedstock yield. The information of the genetic structure and diversity would be useful for breeders to develop new M. sinensis cultivars and hybrids. In other words, the development of ideal cultivars and hybrids for industry purposes should greatly benefit from genetic knowledge of diverse germplasm collections at the beginning and breeding scheme design. Furthermore, researchers should understand genetic variation of quality and stress-tolerance traits of M. sinensis, including the component and degradation efficiency of lignocelluloses, and the tolerance to biotic and abiotic stresses. These traits are important in Miscanthus breeding for ideal biofuel feedstock.B. distachyon have been successfully used in the genetic diversity study on M. sinensisB. distachyon were used to estimate the genetic diversity and population structure of the Chinese M. sinensis germplasm. The neighbor-joining tree based on Nei’s M. sinensis showed an amazing degree of phenotypic polymorphism  associated with plant height, panicle height, stem diameter and yield have been reported morphism  and 4. SMiscanthus as a biomass feedstock has greatly improved our understanding of biomass yield potential, agronomy and adaptation Research on M. sinensis accessions were used in this study, including 457 accessions collected from China and two accessions from USA . Three phenotypic traits, including heading date, plant height and biomass yield, were recorded in 2009 and 2010. Heading date (HD) was recorded as the days after sprout to the date when the main stem start heading. M. sinensis is a short-day crop and its development is largely determined by the day-length. Due to this photoperiod requirement, days from sprout until reproductive growth were quite variable among the M. sinensis accessions collected from different geographical regions. Therefore, the accessions collected from Hainan (a short-day region) failed to heading when planted in Wuhan (a relatively long-day region). The heading date of several genotypes collected from Hainan was recorded as 360 days. Plant height (PH), was measured as the length from the ground to the tip of the panicle when the shoot was harvested in the following February. Biomass production (dry matter) per plant of each accession was assessed after air drying to constant weight. No specific permission was required for the field study, which was carried out in the experimental plot, a specific garden for cellulose energy plants. M. sinensis is not listed as the endangered or protected species in China.Four hundred and fifty-nine Genomic DNA was isolated from young leaves following a modified cetyltrimethyl ammonium bromide (CTAB) method B. distachyonM. sinensis , applying a touchdown amplification protocol: start with pre-denaturation step at 95°C for 3 min; followed with ten touchdown cycles of 95°C for 30 s, 60°C (decreased 0.5°C per cycle) for 30 s, and 72°C for 30 s; then 30 cycles of denaturation at 95°C for 30 s, annealing at 50∼62°C . Unique alleles were those present in one accession or one group of accessions but absent in other accessions or groups of accessions. Rare alleles were those with frequency of ≤5% in the investigated materials. Those alleles frequency >20% were classified as most frequent alleles.Several genetic parameters were estimated and cluster analysis was performed using the neighbour-joining method in PowerMarker version 3.25 4 followed by 105 iterations. Evanno’s delta K Our data was converted with the script AFLPdat stF.Analysis of molecular variance (AMOVA) was performed using Arlequin 3.11 Regression analysis of biomass yield on geographic parameters of the original habitats, heading date and plant height was carried out and the correlations were estimated as Pearson coefficient (r). All the analyses were performed using the statistical software SPSS13.0 for windows .2 indicating the fixed marker effects.Association analysis was conducted to reveal associations between the measured traits and the 115 marker alleles. A General linear model (GLM) test using posterior membership coefficients (population structure Q) as a cofactor was run in TASSEL 2.1 Table S1M. sinensis germplasm accessions.Geographical parameters and the group information for (XLS)Click here for additional data file.Table S2B. distachyon for each primer pair.Primer sequences, optimal annealing temperature (AT), number of polymorphic bands (NB) and chromosome location on the (DOC)Click here for additional data file.Table S3M. sinensis accessions in 2009 and 2010.The phenotypic data, biomass yield, plant height and heading time for each (DOC)Click here for additional data file.Table S4M. sinensis accessions.The genotypic data of 115 alleles in the (DOC)Click here for additional data file.


Xestospongia testudinaria and a currently undescribed Xestospongia species. We sampled across seven populations in the Wakatobi Marine National Park, SE Sulawesi (Indonesia) spanning a spatial scale of approximately 2 to 70 km, and present the first estimates of demographic connectivity for coral reef sponges. Genetic analyses showed high levels of genetic differentiation between all populations for both species, but contrasting patterns of genetic structuring for the two species. Autocorrelation analyses showed the likely dispersal distances of both species to be in the order of 60 and 140 m for Xestopongia sp. and Xestospongia testudinaria, respectively, which was supported by assignment tests that showed high levels of self-recruitment (>80%). We also found consistently high inbreeding coefficients across all populations for both species. Our study highlights the potential susceptibility of barrel sponges to environmental perturbations because they are generally long-lived, slow growing, have small population sizes and are likely to be reliant on self-recruitment. Surprisingly, despite these features we actually found the highest abundance of both barrel sponge species  at a site that has been severely impacted by humans over the last fifty years. This suggests that barrel sponges exhibit environmental adaptation to declining environmental quality and has important implications for the management and conservation of these important reef species.While estimates of connectivity are important for effective management, few such estimates are available for reef invertebrates other than for corals. Barrel sponges are one of the largest and most conspicuous members of the coral reef fauna across the Indo-Pacific and given their large size, longevity and ability to process large volumes of water, they have a major role in reef functioning. Here we used a panel of microsatellite markers to characterise the genetic structure of two barrel sponge species,  Coral reefs across the world have been seriously impacted by human activities to the extent that many reefs have been severely degraded Genetic techniques have been widely applied to estimate patterns of genetic connectivity, and more recently demographic connectivity of tropical marine species, but the focus has primarily been on corals and fish Sponges are common and important coral reef organisms across the world with a range of important roles in ecosystem functioning Xestospongia, which can reach several meters in diameter and have been suggested to reach several thousand years in age Xestospongia muta from the Caribbean has been one of the most intensively studied sponge species , which have been separated on the basis of morphology X. testudinaria and X. bergquistia, with both species being gonochoristic and oviparous, the length of the larval period is unknown, but is likely to be short (hours to days) based on studies of other sponge species X. testudinaria has been considered a single species, but a recent study by Swierts et al. X. testudinaria. With a combination of mitochondrial and nuclear markers and a morphological analysis, these authors proposed that there are at least two distinct Xestospongia species around Lembeh Island, Indonesia, each with different habitat preferences.Of the 10,000+ species of known sponges, one of the most conspicuous and charismatic are the giant barrel sponges of the genus es e.g., , far lesXestospongia spp. Xestospongia species. We aimed to: 1) measure and compare the levels of genetic and demographic connectivity between populations of the two species of Xestospongia at a range of spatial scales (2 km to 70 km); 2) estimate dispersal distances using an spatial autocorrelation analysis and assignment testing; 3) examine differences in the level of genetic diversity and inbreeding at sites with different environmental conditions; and 4) compare the abundance and size distributions at sites with different environmental and biological characteristics to consider the impacts of disturbance on population structure. The life-history characteristics and population demography of barrel sponges would appear to make sensitive to disturbance. Therefore we hypothesise that barrel sponges will show low levels of dispersal, high levels of self-recruitment and therefore must have evolved physiological traits enabling them to tolerate degraded and disturbed environments. Understanding levels of connectivity will provide insights into how these functionally important reef organisms should be managed and conserved.Given the slow growth and small census population sizes of barrel sponges, they would appear susceptible to environmental degradation and disturbance. However, large, old individuals are common on reefs suggesting that other species traits allow populations to persist. This may be explained by their ability to exist across a range of environmental conditions, their role as strong spatial competitors , their potential to tolerate environmental disturbances, or as a result of high levels of population connectivity. Identifying these traits will be increasingly important as predicted future reef impacts provides more opportunities for benthic species other than coral to dominate reef systems. We recently described the development of a panel of microsatellite markers for Seven sites see  were sam2 at each site except Sampela where 1200 m2 was surveyed. Sampling was depth restricted in line with safe diving practises (<21 m) but some barrel sponges were observed below this depth threshold. One cm3 tissue samples were collected from each sponge and preserved in 99% ethanol. Photographs and measurements were also taken of each sponge.All barrel sponges were sampled in an area approximately 250 m long between 6 and 21 m at each site, except Sampela, where the maximum depth of the reef extends to 12 m, giving a total sampling area (and population size for the site) of 2400 mThe restricted reef formation reef at Sampela (depth restricted to 12 m) allowed us to sample the entire population along a 250 m section of the reef. This survey was used for a spatial autocorrelation analysis (see below), where we mapped the location of each barrel sponge on the reef relative to each other sponge by running a transect along the base of the reef at 12 m and determining x,y coordinates (in metres) along the reef for each sponge.Xestospongia tissue samples using an Isolate Genomic DNA Mini Kit (Bioline) following the manufacturer’s protocols. We used the nine of the twelve markers developed Bell et al. Xestospongia .Genomic DNA was extracted from the ethanol preserved 4)2SO4, 1.65 mM MgCl2, 0.22 mM dNTPs), equal amounts of forward and reverse primer (see 31), and ddH20 to volume. The following cycle conditions were used: 94°C for 5 minutes; followed by 40 cycles of 94°C for 30 seconds, 60°C for 45 seconds, 72°C for 60 seconds; followed by a final extension at 72°C for 10 minutes. PCR products were visualised on a 1.5% agarose gel using ethidium bromide staining and if successfully amplified were genotyped on an ABI3730XL (Life Technologies) automated capillary sequencer. The 5′ ends of the forward primers were tagged with the fluorescent labels FAM, VIC, NED or PET. Multiplex Manager 1.2 Microsatellite loci were amplified for each sponge sample on a GeneAmp 2700 (Life Technologies) thermocycler in a final reaction volume of 12 μl containing: ∼50 ng template DNA, 1X Bioline MyTaq Red Mix  representing X. testudinaria  and X. bergquistia  from the Indo-Pacific. To visualise the genetic relationships between all samples from all populations, a Principle Coordinate Analysis (PCA) was conducted by genealex 6.3 using the pairwise matrices of Nei’s genetic distance genealex v 6.3.Because de Swierts et al. fstat v 2.9.3 genealex 6.3 genealex v 6.3 and tested for any evidence of linkage disequilibrium between all loci/population combinations with arlequin v 3.5.1.2 Allele discovery curves were generated using PopGenKit Package in the software R 2.13.1 for all Samples from Sampela. Curves that reach an asymptote indicate that the allelic diversity would not be increased by analysing additional samples. We quantified genetic diversity within each of the sampled populations for each species based on the mean number of alleles per locus and total number of alleles using genealex v 6.3. Population differentiation  and associated STR index is appropriate for population genetic studies using microsatellite loci STR index. A Mantel test for Isolation by distance was conducted using linearized STF (STF/(ST1−F) and minimum oceanographic distance (km) between sites.We used a hierarchal analysis of molecular variance  to determine the proportion of genetic variation that could be attributed to differences between sampling sites using ion FST, was alsogenealex 6.3 using the pairwise matrices of STF and Nei’s genetic distance (Ds).To visualise the genetic relationships between sampled populations, a Principle Coordinate Analysis (PCA) was conducted by structure v 2.3.2 4 iterations and 105 Markov Chain Monte Carlo (MCMC) repetitions and with K ranging from 1–7. Each individual in the data set is represented by a single vertical line, which is partitioned into K segments that represent that individual’s estimated membership fraction in each of the K inferred clusters. The appropriate K value for the data set was determined by plotting the log probability (L(K)) and ΔK across multiple runs structureharvesterclumppdistructBayesian clustering analysis in geneclass v 2.0 P>0.10) it was left unassigned. Those individuals that could not be re-assigned to any of the other populations were considered to have originated from a non-sampled location.Assignment tests were conducted using a Bayesian approach To investigate fine-scale patterns of genetic relatedness, spatial autocorrelation tests were performed by GENEALEX 6.4.1 As we sampled all sponge specimens along a 250 m section of reef at each location, this provided us with an estimate of total population size at each location. At Karang Gurita and Sampela  we also measured the approximate size of each barrel sponge. We generalised the shape of each sponge to a cylinder with a cone cut from the top to represent the spongocoel. We measured the maximum circumference, the height of the sponge, the diameter of the spongocoel and depth of the spongeocoel to calculate the approximate volume.Xestospongia testudinaria and X. bergquistia .The PCA to examine the relationships between all of the samples across all seven sites showed clusters of samples, which were not consistent with their geographical location, and formed four distinct groups . AMOVA sgquistia . UnfortuISF) ranging from 0.131 to 0.431 for X. testudinaria and 0.054 to 0.364 for Xestospongia sp. We found deviations from HWE at the locus level varied between sampling sites, although no population showed a significant deficiency at all loci  for X. testudinaria and Karang Gurita (KG) for Xestospongia sp. , but a strong significant positive correlation for Xestospongia sp. . Our analysis revealed significant population structure for both species across the Wakatobi . Irrespective of species, AMOVA indicated only a small proportion . For X. testudinaria, the PCA showed evidence of four main clusters including the sites to the south (TOM and TCC), the north (WAN and KG), a central group (RID and KDS) and Sampela. For Xestospongia sp., there were no obvious population clusters consistent with isolation by distance structuring.PCA plots  show theX. testudinaria: two central groups , a northern group (KG and WAN) and a southern group (TOM and TCC). STRUCTURE HARVESTER identified K = 3 for Xestospongia sp., , a northern group (KG and WAN) and a southern group (TOM and TCC). However, this was not strongly supported  as implemented in STRUCTURE HARVESTER was determined to be K = 4  and 7 forted see , which iX. testudinaria, populations with sample sizes >10 generally had a low number of excluded individuals (<12%) indicating high levels of self-recruitment. There was also evidence of sponges that could not be assigned to any of our sampled populations, with only 2–3% of sponges being assigned to an unsampled population.Our assignment testing identified high levels of self-recruitment for both species, although care is needed in the interpretation of the percentage of self-recruiting sponges for populations with small sample sizes . For X. X. testudinaria indicated that genotypes were distributed randomly for the first 5 distance classes (20–100 metres), after which the r value showed a significant positive correlation (p = 0.035) among genotypes for sponges separated by distances of 120 metres. The correlation coefficient then dropped to become significantly negative (p = 0.011) at 140 metres. Spatial autocorrelation analysis of Xestospongia sp. indicated a significant positive correlation (p = 0.008) among genotypes of sponges within the first distance class (20 metres). Values then levelled of between the next two classes and dropped below the x-axis to become significantly negative (p = 0.021) among genotypes of sponges separated by distances greater than 80 metres. Values were again significantly negative (p = 0.004) at 160 metres. These results indicated that the neighbourhood size of this X. testudinaria was approximately 140 m and for Xestospongia sp. approximately 65 metres  was lower at Sampela (337.60 m3 compared with 581.26 m3). At both these sites there appeared to be sponges of a range of size classes, suggesting recruitment has been relatively consistent. However, we did not find any small, very recent, recruits at ether site.Estimates of population size for the two species were only based on the densities of a single section of each reef (which we consider sites), but based on this we found the overall (across both species) highest abundance of sponges at Sampela and the lowest abundance at the Ridge . HoweverX. testudinaria, another X. bergquistia and the other two are likely undescribed species. Our results support the presence of a recently proposed X. testudinaria species complex in the Indo-Pacific X. testudinaria following an island model Xestospongia sp. an isolation by distance model Despite connectivity being considered a key component in understanding population dynamics and in the development of effective management plans, we still have a very poor understanding of the processes that link populations and the scales at which populations are connected. This is especially the case for non-coral reef invertebrates. Here we distinguish between multiple co-occurring species of Indo-Pacific barrel sponges based on microsatellite data, which is supported by gross morphological differences with one of the species being Amphiprion polymnus) settled within 100 m of their natal reefs, despite having a relatively short (compared to other marine species) 12-day larval duration. Estimating demographic connectivity is difficult for most marine species because of the problems in tracking microscopic larvae through the oceans. Parentage, assignment testing and spatial autocorrelation analyses are powerful tools for estimating demographic connectivity, but they are best suited for species with small census population sizes and limited dispersal capacity 2) encrusting patches, whose densities can exceed hundreds of sponge patches per m2Lamellodysidea herbacea was the most abundant in 2003 and has almost doubled in abundance over the last decade L. herbacea have not been seen. Although environmental conditions at Sampela (heavy sedimentation and high turbidity) may favour this species, its rapid increase in abundance suggests a local stock-recruitment relationship, which is likely to be supported by self-recruitment.There are currently very few estimates of demographic connectivity for most reefs organisms other than corals and fish, and even for these groups estimates are rare. While larval duration has been proposed as a predictor of larval dispersal potential, there is increasing evidence that populations may also be dependent on a high level of self-recruitment. For example, using DNA parentage data and marking via stable isotopes, Almany et al. X. testudinaria followed an island model, with three different groups consistent with their geographic position, while Xestosponiga sp. followed an isolation by distance model. Currently nothing is known of the oceanographic features of the Wakatobi or the location of any potential barriers to gene flow, so it is difficult for us to explain these patterns. However, given we found different patterns of genetic structuring for the two co-occurring barrel sponge species suggests different process are influencing gene flow between populations of these species. X. testudinaria had a larger estimated dispersal distance than Xestospongia sp. (120 m compared with 65 m), although these distances are still small compared to species with long-lived pelagic larvae, which might be in the order of 10 s to 1000 s km X. testudinaria and X. bergquistia, although larval duration and behaviours have not yet been studied extensively; this might account for the differences we reported. We found high inbreeding coefficients for nearly all populations that we sampled for both groups, with an apparent excess of homozygotes, but no patterns between sites. While null alleles might account for this result, this seems unlikely as MICROCHECKER found no evidence for null alleles in the loci that we used  gene found high levels of genetic differentiation between populations at spatial scales of several 100 km X. testudinaria, these authors also found no evidence of isolation by distance, and proposed that while limited larval dispersal may have led to differentiation among some of the populations, the patterns of genetic structure appear to be most strongly related to patterns of ocean currents.Our results are consistent with a number of earlier genetic studies on sponges using allozymes and microsatellite markers. For example, Whalan et al. Xestospongia species was unexpected during the initial collection of specimens for this study, but meant we had to split our data into two groups. Furthermore, some sponges were excluded from the analysis (n = 65) as they appeared to represent different species. As a result some care is needed in the interpretation of our data. However, the relatively low numbers of alleles for each of our loci based on an initial survey of 75 individuals One of the primary limitations to our study is the small sample size for many of our populations. The identification of multiple Xestospongia sp. species, and this was consistent with differences in the external morphology of these specimens. The taxonomic relationships between these species will be the focus of future studies. Our study is not the first to report possible undescribed species within a Xestospongia testudinaria complex Xestospongia species that was not included in the genetic analysis does have a different local habitat distribution, as specimens were mainly collected from deeper water (21 m).It is interesting that we found evidence for possibly four Xestospongia species. Their small population size coupled with these features should make barrel sponges susceptible to environmental disturbance or there must be a large selective pressure for barrel sponges to tolerate a range of environmental conditions and be able to tolerate environmental perturbations. Sampela has experienced major declines in coral cover and fish in recent years Xestospongia mutaBarrel sponges play important functional roles through their ability to filter large volumes of water The development of management plans and any assessment of system resilience requires an understanding of connectivity patterns. However, determining the probability of inter-population connectivity needs to incorporate population dynamics and the factors that control larval longevity and survival. Such information is essential for managers, but collecting this information is time consuming and is generally impractical for all reef species. However, genetic data can be used to infer patterns of genetic and demographic connectivity, but it needs to be interpreted in the context of the species’ ecology. Given that the degree of reef resilience can be altered through increased connectivity In the case of barrel sponges, populations appear largely reliant on self-recruitment, which should have important implications for their management, which coupled with their long-lived nature and apparent low level of recruitment would appear to make them susceptible to physical disturbance or fatal disease outbreaks. Despite this, barrel sponges are abundant at sites considered to have experienced high levels of degradation in the past, suggesting some level of tolerance to disturbance. Furthermore, these sites also experience heavy levels of sedimentation, suggesting some level of adaptation to these conditions. While this might appear something of a paradox, the features of barrel sponge populations means they are likely to require management at relatively local-scales  as population extinctions are unlikely to be replenished by distant larval sources.Here we report the first estimates of demographic connectivity in tropical sponges, and demonstrate barrel sponges in the Wakatobi have low dispersal distances and are likely to be heavily reliant on self-recruitment, with high levels of inbreeding. The features of these species’ would make them susceptible to disturbance but this does not appear to be the case. This provides further evidence to support the hypothesis that sponges may be likely ‘winners’ in response to any further environmental degradation.


Annona cherimola Mill.), a Neotropical fruit tree species. We present spatial analyses to (1) improve the understanding of spatial distribution of genetic diversity of cherimoya natural stands and cultivated trees in Ecuador, Bolivia and Peru based on microsatellite molecular markers (SSRs); and (2) formulate optimal conservation strategies by revealing priority areas for in situ conservation, and identifying existing diversity gaps in ex situ collections. We found high levels of allelic richness, locally common alleles and expected heterozygosity in cherimoya's putative centre of origin, southern Ecuador and northern Peru, whereas levels of diversity in southern Peru and especially in Bolivia were significantly lower. The application of GIS on a large microsatellite dataset allows a more detailed prioritization of areas for in situ conservation and targeted collection across the Andean distribution range of cherimoya than previous studies could do, i.e. at province and department level in Ecuador and Peru, respectively.There is a growing call for inventories that evaluate geographic patterns in diversity of plant genetic resources maintained on farm and in species' natural populations in order to enhance their use and conservation. Such evaluations are relevant for useful tropical and subtropical tree species, as many of these species are still undomesticated, or in incipient stages of domestication and local populations can offer yet-unknown traits of high value to further domestication. For many outcrossing species, such as most trees, inbreeding depression can be an issue, and genetic diversity is important to sustain local production. Diversity is also crucial for species to adapt to environmental changes. This paper explores the possibilities of incorporating molecular marker data into Geographic Information Systems (GIS) to allow visualization and better understanding of spatial patterns of genetic diversity as a key input to optimize conservation and use of plant genetic resources, based on a case study of cherimoya ( The local diversity of these tree species could offer yet-unknown traits of high value to further domestication Many useful tropical and subtropical tree species, even those commonly cultivated, are still in incipient stages of domestication, with their genetic resources often principally or exclusively, present The formulation of effective and efficient conservation strategies requires a thorough understanding of spatial patterns of genetic diversity Annona cherimola Mill.), an underutilized fruit tree species that belongs to the Annonaceae, a family included within the Magnoliales in the Eumagnoliid clade among the early-divergent angiosperms This study focuses on cherimoya  apply innovative spatial analysis to improve understanding of the geographic distribution of cherimoya ‘s genetic diversity in its putative native range, based on microsatellite molecular markers (SSRs); and (2) formulate optimal conservation strategies by prioritizing areas for ex situ collections  whereas the remainder trees were sampled in situ. The molecular analysis included a core set of nine microsatellite loci α-diversity and β-diversity  we applied circular neighborhood re-sampling technique resulting in a total dataset of 48,128 trees  have been sampled more intensively than others , generatin situ conservation, both of cultivated trees on farm and of natural stands. The border region between Peru and Ecuador (Piura Department and Loja Province) is another area where a high concentration of locally common alleles has been observed and may, therefore, be a second area to prioritize in situ conservation efforts. To a lesser extent, the area around Quito in Ecuador and the northern part of the Lima Department in Peru also present locally common alleles.Priority for conservation should be given to populations that retain locally common alleles; these are alleles that occur in high frequency in a limited area, and can indicate the presence of genotypes adapted to specific environments In situ conservation should focus on viable populations, where inbreeding and subsequent loss of alleles are minimal. Parameters that allow assessment of inbreeding are expected heterozygosity (He) and the fixation index (F). The fixation index (F) was used to detect areas subjected to high inbreeding depression and, as the inverse to that, excess in heterozygosity He in the study area, again confirming Cajamarca Department in northern Peru as the area with the highest genetic diversity. High He values, however, radiate towards the south  indicating higher levels of diversity in terms of heterozygosity in central Peru compared to Ecuador. F values close to 0 in the Cajamarca Department indicating that natural and cultivated cherimoya tree stands in this area have not experienced inbreeding. The highest values for F are observed in central Ecuador, suggesting that the level of inbreeding is highest in that part of cherimoya's Andean distribution range.F values, i.e. excess of heterozygosity. Most of the cherimoyas cultivated in this area are vegetatively propagated clones of the cultivar ‘Cumbe’ which resulted in highly heterozygous values from the molecular analysis, i.e. the ‘Cumbe’ accession conserved in the Spanish genebank is heterozygote for eight of the nine microsatellite loci analyzed in this study . An analysis of the average genetic distance, between the ‘Cumbe’ accession and the genotypes in each grid cell with 20 or more re-sampled trees in the study area, clearly shows lowest genetic distance values near the Peruvian capital, Lima, indicating that the cherimoya trees in this area are very similar to the cultivar ‘Cumbe’  as it is possible that populations with low allelic richness possess unique allele compositions, different from those of populations in other areas of the range, which would warrant their in situ conservation Besides ex situ collections . Only eight alleles, corresponding to 11% of the total of 71 alleles that have been found in the study area, are not represented in any accession of these collections. ex situ collections, it can be concluded that, in general, cherimoya diversity from the countries analyzed is fairly well conserved ex situ.Of the 1504 trees included in this study, 502 genotypes are currently conserved in The above results and subsequent conclusions are obviously only of practical use if the sampling performed was indeed representative for the distribution of cherimoya in the study area. Maxent species distribution modeling software was applied to model cherimoya's distribution range in Ecuador, Peru and Bolivia based on the climatic niche in which the 1504 sampled trees of our study were located. The modeled distribution was then compared with the sampled areas in these countries.Cross-validation, to evaluate the quality of the distribution model, returned an Area Under Curve (AUC) value of 0.9, which indicates good model performance In general, sampling covered most of the cherimoya-modeled distribution ; 46% of Cherimoya was predicted absent by the distribution model in a significant area of southern Peru, indicating that the environmental conditions in substantial parts of that region are not suitable for cherimoya cultivation . This exin situ conservation and germplasm collection.Our results are in line with a previous genetic study of the Spanish cherimoya collection that also distinguished populations in Ecuador and northern Peru from those in southern Peru At the allele level, our analysis confirms that, within our study area, the highest allelic richness as well as the highest number of locally common alleles are found in the area of southern Ecuador and northern Peru, i.e. the putative centre of origin of cherimoya. Northern Peru, and more specifically the Cajamarca Department, shows the highest levels of genetic diversity.The highest values of the fixation index, which is an indication of inbreeding, were found in Ecuador. Inbreeding may occur because of reduction and fragmentation of natural stands and cultivated areas, increasing the risk of allele loss, which eventually leads to genetic erosion At the population level, significant differences can be observed between the cherimoya germplasm present in the area with highest diversity (where genotypes belonging to cluster A are predominant) and genotypes found in areas with lower diversity, i.e. in southern Peru and Bolivia (represented by cluster B). Cluster A seems likely to represent material that is genetically closer to the “wild” cherimoya type. No natural cherimoya stands have been observed in Bolivia, and this probably explains why no genotypes pertaining to cluster A have been recorded there. Cluster B probably corresponds to a genepool that is genetically different from most of the wild or semi-domesticated cherimoya found in northern Peru and Ecuador and that could have formed the basis for Bolivian cherimoya cultivation. Looking at the areas of high cluster B dominance, Bolivian germplasm probably originates from southern Peru.Although most early chroniclers and scientists proposed southern Ecuador and northern Peru to be cherimoya's centre of origin ex situ collections in Ecuador, Peru and Spain. The results obtained suggest that the highest priority for further collection should be the Azuay Province in Ecuador, since cherimoya stands in this area harbor most alleles not yet included in genebanks. It is also one of the areas with the highest risk of allele loss because of the high observed levels of inbreeding, compared to other parts of the study area. An additional priority area for germplasm collection is the transition zone from the Andes to the Amazon in Peru (in the higher elevation areas of the Departments of San Martin and Amazonas), which was not sampled in this study. According to the distribution model there is a high probability of finding cherimoya stands in this region, which probably is also high in genetic diversity, because it is adjacent to the area with the highest diversity found in this study, i.e. the Cajamarca Department in northern Peru.Most alleles identified in our study are represented in one or more of the existing in situ conservation should be the Cajamarca Department, the area with the highest levels of genetic diversity. A second area of priority should be the Loja Province in southern Ecuador, an area with a high number of locally common alleles. Both areas are assigned mostly to cluster A. Since trees pre-dominantly assigned to cluster B have a particular allelic composition in comparison to trees predominantly grouped in cluster A, genotypes of cluster B should also be considered in conservation activities. The part of Lima Department north of the Peruvian capital, which is assigned mostly to cluster B, could be prioritized for in situ conservation of genotypes from this cluster. In contrast to the low levels of allelic richness around Lima city in the southern part of the Lima Department, the northern part of this Department contains a fair number of locally common alleles.A priority for The long-term conservation of cherimoya genetic resources is far from guaranteed. As commercial prices for fruits can fluctuate, short-term incentives for farmers to maintain cherimoya as a profitable crop are reduced and a decline in commercial interest may lead to the replacement of cherimoya trees by other crops, increasing the risks of genetic erosion. Around Quito, for example, most of the traditional cherimoya cultivation is being replaced by avocado plantations, which are commercially more attractive . An increase in commercial prices for cherimoya products will not necessarily promote the conservation of the existing genetic diversity. Indeed, in our study we found low levels of genetic diversity around the Peruvian capital, Lima where the clonally propagated cultivar ‘Cumbe’ is widely cultivated, because it fetches higher prices in the market.in situ conservation on farm is through the promotion of seed or bud-for-grafting exchange between farmers A promising strategy to enhance in situ conservation - where the existing cherimoya stands and forest patches can evolve within the local environment - should be backed up by ex situ conservation of germplasm (which currently is the case for cherimoya), and be monitored periodically to assess the dynamics in diversity use and risks of genetic erosion. Ex situ collections of fruit tree species often consist of living trees, such as the cherimoya collections. This allows conservation of superior combination of alleles that can be propagated vegetatively through grafting. Additional reasons include the following: (1) many tropical and subtropical trees (including cherimoya) have seeds with recalcitrant or intermediate behavior, which cannot be stored for long-term conservation; and (2) pollen, fruits and seeds can be collected continuously for characterization, evaluation and genetic improvement once trees have reached the reproductive stage. Nevertheless, the high costs for research institutions to maintain field genebanks of woody perennial species, can be a reason to minimize ex situ collections and focus especially on in situ conservation Ex situ conservation may particularly be important for areas that suffer from inbreeding -an indicator for high rates of allelic loss and genetic erosion- such as central Ecuador in the case of cherimoya, whereas in situ conservation may be most successful in areas of high diversity where still low rates of inbreeding are observed such as in the cherimoya stands from northern Peru.Ideally, each area targeted for Despite the advances in new computational applications and the use of molecular tools, spatial analyses are still underutilized in efforts to conserve plant diversity The size of the grid cells and width of the circular neighborhood for this type of spatial analysis depends on how many plant individuals have been collected across the landscape, and the minimum number of plant individuals that is considered sufficient to make confident estimates of genetic parameters per grid cell. Application of circular neighborhood provides an effective way to decrease grid cell size, which facilitates detection of spatial patterns in genetic variation across an extensive distribution range. By re-sampling the trees in the landscape, it generates a high number of grid cells with a sufficient number of trees to make confident calculations of genetic parameters per grid cell. It also makes analyses less sensitive to grid origin definition and enables the inclusion of isolated trees in the calculation of the genetic parameters, i.e. together with their closest neighboring trees.Ideally, the sampling strategy for this type of analysis should be identified based on a pre-defined grid, aiming at measuring the same number trees per grid cell. However, due to logistical constraints and because a species simply may be more abundant in some areas than in others, in practice, sampling will always be sub-optimal to a certain degree. Of all the genetic parameters, allelic richness is most sensitive to uneven sampling and, accordingly, we have corrected sample size by rarefaction Given the sampling distribution in our study area and the fact that for the calculation of most genetic parameters, we maintained a minimum of 20 re-sampled trees per grid cell, we defined a cell size of 10 minutes and a circular neighborhood with a diameter of one degree, which enabled us to detect spatial patterns of genetic variation at administrative level one in Ecuador, Peru and Bolivia (provinces and departments). For studies of plant species, in which individuals are sampled in a more clumped distribution compared to our scattered sampling distribution and/or in lower densities across the landscape, larger grid cells and/or a larger width of circular neighborhood could be applied, always assuring a sufficient number of trees per grid cell. The overall resolution of the study will obviously be lower.Annona squamosaFollowing Frankel et al. It is difficult to compare our results with those of Lowe et al. in situ conservation of plant genetic resources on farms and in natural populations.In our study we only examined spatial patterns of genetic variation without relating them to other spatial attributes. GIS can also be used to link genetic data to available spatial information relevant to conservation of plant genetic resources, for instance to reveal short-term threats such as accessibility and long-term threats such as climate change. With this type of analysis, hotspots of diversity under threat could be identified following Myers et al. Sampling and SSR analysis: A total of 1504 cherimoya accessions have been analyzed in this study, 395 from Bolivia, 351 from Ecuador and 758 from Peru. DNA was extracted from young leaves after Data cleaning: The coordinates of the respective tree locations were checked in DIVA-GIS (www.diva-gis.org) on erroneous points based on passport data at administrative level one  with a buffer of 20 minutes (approx 30 km), and outliers based on climate data derived from the Worldclim data set Spatial analysis – Circular neighborhood: Grids for all genetic parameters were generated in DIVA-GIS and are based on a grid with a cell size of 10 minutes (which corresponds to approximate 18 km in the study area) applying a circular neighborhood with a diameter of one degree (corresponding to approximate 111 km) constructed in Excel. The circular neighborhood is used to re-sample the allelic composition of a single tree to all surrounding grid cells, in this case, 32 cells with a size of 10 minutes, within a diameter of one degree around its location. In this way, the allelic composition of each sampled tree is representative for the area within the defined buffer zone. Applying the circular neighborhood re-sampling technique resulted in a total dataset of 48,128 trees and 866,304 alleles.Spatial analysis – α-diversity: After applying circular neighborhood to all trees, genetic parameters were calculated in GenAlEx per 10-minutes grid cell, for all trees present in each cell after re-sampling. Genetic parameters included the average number of alleles per locus (Na), the number of locally common alleles per locus , average expected heterozygosity per locus (He), fixation index (F) and genetic distance (GD)  see . Na and ware see ; consequkers see . Final GSpatial analysis - β-diversity: Population structure was defined by running the software Structure  was used to identify the alleles exclusively found in trees that were sampled in situ. To visualize patterns in these alleles that are not included in any genebank, a point-to-grid richness analysis, using a 10-minutes grid, was carried out in DIVA-GIS based on the one-degree circular neighborhood re-sampled tree grid.Spatial analysis - distribution modeling: To identify how well the sampling covered the Andean distribution range of cherimoya, and thus to identify potential collection gaps, we modeled the distribution (presence only) of cherimoya in the study area using the distribution modeling program Maxent (see xent see . With thxent see , derivedAll maps were edited in ArcMap.