Medicago truncatula. In the first, we inoculated each plant with the rhizobia Ensifer meliloti and with one of 40 genotypes of the parasitic root‐knot nematode Meloidogyne hapla. In the second experiment, we inoculated all plants with rhizobia and half of the plants with a genetically variable population of nematodes. Using the number of nematode galls as a proxy for infection severity, we found that plant genotypes differed in susceptibility to nematode infection, and nematode genotypes differed in infectivity. Second, we showed that there was a genetic correlation between the number of mutualistic structures formed by rhizobia (nodules) and the number of parasitic structures formed by nematodes . Finally, we found that nematodes disrupt the rhizobia mutualism: nematode‐infected plants formed fewer nodules and had less nodule biomass than uninfected plants. Our results demonstrate that there is genetic conflict between attracting rhizobia and repelling nematodes in Medicago. If genetic conflict with parasitism is a general feature of mutualism, it could account for the maintenance of genetic variation in partner quality and influence the evolutionary dynamics of positive species interactions.Genetic variation for partner quality in mutualisms is an evolutionary paradox. One possible resolution to this puzzle is that there is a tradeoff between partner quality and other fitness‐related traits. Here, we tested whether susceptibility to parasitism is one such tradeoff in the mutualism between legumes and nitrogen‐fixing bacteria (rhizobia). We performed two greenhouse experiments with the legume  Medicago truncatula, a close relative of alfalfa. Legumes like Medicago depend on nitrogen provided by mutualistic bacteria (rhizobia) to grow, but they are also infected by parasitic worms called nematodes, which steal plant nutrients. Both microorganisms live in unique structures  on plant roots. We showed that the benefits of mutualism and the costs of parasitism are predicted by the number of mutualistic structures (nodules) and the number of parasitic structures , respectively. Second, we found that there is a genetic tradeoff between attracting mutualists and repelling parasites in Medicago truncatula: plant genotypes that formed more rhizobia nodules also formed more nematode galls. Finally, we found that nematodes disrupt the rhizobia mutualism. Nematode‐infected plants formed fewer rhizobia nodules and less total nodule biomass than uninfected plants. Our research addresses an enduring evolutionary puzzle: why is there so much variation in the benefits provided by mutualists when natural selection should weed out low‐quality partners? Tradeoffs between benefits provided by mutualists and their susceptibility to parasites could resolve this paradox.Cooperative species interactions, known as mutualisms, are vital for organisms from plants to humans. For example, beneficial microbes in the human gut are a necessary component of digestive health. However, parasites often infect their hosts via mechanisms that are extraordinarily similar to those used by mutualists, which may create a tradeoff between attracting mutualists and resisting parasites. In this study, we investigated whether this tradeoff exists, and how parasites impact mutualism function in the barrelclover Nearly all species require mutualists to carry out crucial biological functions Shapira . InsectsThe maintenance of genetic variation for partner quality in mutualisms is an evolutionary paradox  is a promising system for testing for genetic tradeoffs between mutualism and parasitism. In this mutualism, rhizobia provide their plant host with nitrogen, and the plant trades carbohydrates in return. Plants house rhizobia in root organs called nodules Fig. . HoweverMedicago truncatula. Using two greenhouse‐based inoculation experiments, we addressed four questions: (1) How do rhizobia and nematodes impact fitness in co‐infected plants?; (2) Is there genetic variation in plant susceptibility to nematodes?; (3) Is there genetic conflict between plant responses to mutualistic rhizobia and parasitic nematodes?; and (4) How do parasitic nematodes impact the rhizobia mutualism? We found a genetic tradeoff between attracting rhizobia and repelling nematodes, and that nematodes disrupt the legume‐rhizobia mutualism by deterring nodulation. Our results suggest that genetic conflict with nematodes may maintain variation in partner quality in the legume‐rhizobia mutualism, and that genetic tradeoffs with parasitism may be an important overlooked source of variation in positive species interactions.In this report, we describe genetic conflict between plant responses to mutualistic rhizobia and parasitic nematodes in the model legume Medicago truncatula is an annual plant native to the Mediterranean  in the rhizobia mutualism. The M. truncatula accessions used for this study came from the French National Institute for Agricultural Research (INRA), and the US National Plant Germplasm System (NPGS) Western Regional Plant Introduction Station. These accessions were collected throughout M. truncatula’s native range in the Mediterranean. There is genetic variation among accessions in a number of ecologically important traits, including the rhizobial mutualism , and maintained these nematodes on tomato plants (cv. Rutgers) in growth chambers and greenhouses at the University of Toronto.ean Cook . Becausee et al. . We obtaIt is important to note that we used allopatric populations of plants, rhizobia, and nematodes for this study. Any genetic tradeoffs between mutualism and parasitism may differ in sympatry and allopatry because sympatric plant, rhizobia, and nematode populations have potentially coevolved, while those in allopatry have not. It is not immediately clear whether to expect the genetic correlation between mutualist affinity and parasite susceptibility to be stronger or weaker in sympatric populations.M. truncatula’s response to mutualistic rhizobia and parasitic nematodes. In both experiments, we scarified M. truncatula seeds with a razor blade, sterilized them in bleach and ethanol, and stratified them in the dark at 4°C for 36 hours on sterile water agar plates  agar media, re‐plated colonies three times, and inoculated liquid TY media with these cultures. We diluted liquid cultures to an OD600 reading of 0.1, following previous methods  nematodes from individual egg masses . We did not include a nematode‐only treatment because Medicago grows poorly under nitrogen‐poor conditions without rhizobia  and found that fruit mass and seed number were tightly correlated . We counted the number of nodules and galls on each root system under a dissecting microscope. To capture differences in nodule size, we haphazardly harvested up to 10 large nodules on each plant. Nodules were stored in 2 ml tubes containing silica desiccant and synthetic polyester for a month until they dried out, and we weighed the dried nodules collected from each plant to the nearest 1 μg. We estimated total nodule biomass for each plant by multiplying total nodule number by mean nodule mass. After counting nodules and galls and harvesting nodules, we dried the roots in a drying oven for approximately one week and weighed them to the nearest 1 mg.We checked flowering and collected ripe fruit daily throughout both experiments. Upon harvesting the plants, we stored the roots at 4°C in zip‐top plastic bags until processing. We dried the aboveground tissue in a drying oven for approximately one week and weighed it to the nearest 1 mg. We weighed all fruits each plant produced to measure total fruit mass. To verify that fruit mass was an accurate measurement of reproductive success, we measured the correlation between fruit mass and seed number for a subset of plants ((g)lmer function in the lme4 package  for categorical variables , and the number of nematode eggs in the inoculum as fixed effects, and block as a random effect. We log‐transformed aboveground biomass for analysis. We included a fixed effect of root mass in this and subsequent analyses to control for differences in overall root system size and foraging ability, as well as differences in the root space available for the formation of symbiotic structures .In Experiment 1, we tested for genetic variation in infectivity among nematode genotypes, and for a plant genotype‐by‐nematode genotype interaction. A genotype‐by‐genotype interaction for gall number would indicate that the number of galls formed depends on the combination of plant and nematode genotypes. In this analysis, we included random effects of plant genotype, nematode genotype, plant genotype × nematode genotype, and block. We included fixed effects of root mass, researcher , and the number of nematode eggs in the inoculum. We log‐transformed gall number for this analysis because the log transformation met parametric statistical assumptions much better than a Poisson or negative binomial generalized linear mixed model (GLMM). When testing for the genotype‐by‐genotype interaction, we excluded plant genotype–nematode genotype combinations with fewer than three replicates.glmmADMB , and random effects of plant genotype and block. Gall number was zero‐inflated and overdispersed, so we fit a zero‐inflated negative binomial GLMM using the R package To test for genetic conflict between plant responses to mutualistic rhizobia and parasitic nematodes, we estimated the genetic correlation between nodule number and gall number. We estimated the genetic correlation between nodule and gall number by calculating the correlation between the average numbers of nodules and galls each plant genotype produced. To estimate genotype means for gall number, we extracted the conditional modes of the genotype random effect from a model that included fixed effects of root mass and researcher, and random effects of genotype and block. We included these covariates to statistically account for other sources of variation in nodule and gall number; we included the researcher who counted the nodules and galls in an attempt to account for technical variation and proficiency of researchers. We also controlled for plant size in an attempt to reduce the influence of overall size of a plant on gall and nodule number.Because we found evidence that nematodes disrupt the mutualism by inhibiting nodulation (see Results), we used estimates of nodulation from the rhizobia‐only treatment to estimate the genetic correlation between nodule and gall formation. We estimated genotype means for nodule number using a model similar to the gall model, specified a negative binomial error distribution, and allowed for zero inflation in both models.We also estimated the genetic correlation between gall number and the change in nodule number between the two treatments. We estimated genotype means for nodule number in nematode‐infected plants using a similar model to the one used to estimate nodule number in the rhizobia‐only treatment. We subtracted the genotype mean for nodule number in nematode‐infected plants from the genotype mean for nodule number in uninfected plants to calculate the change in nodule number for each genotype.glmmadmb in the R package glmmADMB  and root mass as fixed effects, and random effects of genotype, block, treatment × genotype, and treatment × block. The treatment × block interaction is necessary when analyzing split‐plot experiments to allow the effect of nematode treatment to vary across blocks (Altman and Krzywinski N = 22) with at least three replicates that flowered and fruited in each treatment, to test for treatment × genotype interactions.We ran similar analyses to compare aboveground biomass, flowering time, and total fruit mass between nematode‐infected and uninfected plants. We log‐transformed all three variables for analysis, and omitted the fixed effect of root mass. For flowering time and total fruit mass, we analyzed a subset of genotypes , indicating that there is genetic variation in plant susceptibility to nematode infection. In addition, there was significant variation in gall number among nematode genotypes in Experiment 1 . There was no significant plant genotype × nematode genotype interaction .In both experiments, there was significant variation among plant genotypes in the number of galls formed (controlling for root biomass) . In another study of nodulation in M. truncatula, this genotype also formed more nodules than 90% of 250 accessions surveyed . However, there was a significant positive genetic correlation between gall number and the change in nodule number between the two treatments .There was no significant genetic correlation between gall number and the number of nodules produced in the presence of nematodes, regardless of whether the outlier genotype HM170 was included in the analysis , indicating that the parasite's effect on the legume–rhizobia mutualism is not merely a byproduct of lower overall performance in infected plants. Moreover, we found that a plant's affinity for rhizobia and susceptibility to nematodes were genetically correlated: plants that formed more nodules with rhizobia were more heavily infected by nematodes. Our results suggest that genetic conflict with parasitic nematodes is an important factor shaping the Medicago‐rhizobia mutualism. If genetic conflict with parasitism is a general feature of many mutualisms, it may contribute to the maintenance of genetic variation for partner quality and influence evolution in positive species interactions.Here, we showed that an ecologically relevant parasite disrupts the mutualism between leguminous plants and nitrogen‐fixing rhizobial bacteria. ‐infected Medicago plants formed 23% fewer nodules and 19% less total nodule biomass per gram of root than uninfected plants , demonstrating that both the plant and the parasite have the genetic capacity to evolve in response to the other. However, we found no evidence for genotype‐by‐genotype interactions between plants and nematodes that would facilitate coevolution in the system.Our results demonstrate that there is standing genetic variation for ier Fig. D—were laTwo competing hypotheses have been advanced to account for the impact of parasites on mutualism function: resource allocation tradeoffs and changes in host defense status (De Román et al. Medicago truncatula’s susceptibility to nematode infection was genetically correlated with its affinity for mutualistic rhizobia (Fig. bia Fig. A. Plant bia Fig. A. This oMedicago is consistent with molecular genetic work in the legume Lotus japonicus showing that mutants that do not form nodules are also resistant to nematode infection (Weerasinghe et al. The genetic correlation between attracting rhizobia and repelling nematodes in M. truncatula, is one mechanism that can contribute to the maintenance of genetic variation for partner quality in mutualisms (Heath and Stinchcombe Medicago populations.A genetic correlation underlying the tradeoff between attracting mutualists and repelling parasites, like the one we documented in Although there are surprisingly few estimates of the genetic tradeoff between mutualism and antagonism, widespread tradeoffs at the phenotypic level suggest that genetic conflict between positive and negative species interactions may be extremely common. For example, trypanosomatid parasites of firebugs mimic the vertical transmission mechanisms of their host's bacterial symbionts, such that symbiont transmission is associated with a risk of parasite infection (Salem et al. Genetic tradeoffs can result from two distinct processes, which have very different evolutionary implications. Some tradeoffs represent fundamental biophysical constraints and are therefore inescapable, while other tradeoffs reflect linkage disequilibrium that has not been broken up by recombination or pleiotropy that has not been alleviated by gene duplication or tissue‐ or ontogenetic stage‐specific gene regulation. Although our data do not directly address this question, we hypothesize that the genetic correlation between affinity for mutualists and susceptibility to parasites—at least in the legume–rhizobia–nematode system—may be evolutionarily labile rather than fundamentally inescapable. The existence of an outlier genotype that seems to have escaped the genetic tradeoff is consistent with this hypothesis. One crucial factor that may influence the genetic correlation between mutualism and parasitism in this and other systems is the frequency of coinfection by both symbionts. In populations where coinfection is rare, there should be little selection acting to degrade the correlation because under these circumstances, hosts are not exposed to parasite infection when establishing mutualisms. By contrast, populations may evolve ways to ameliorate the tradeoff where coinfection is common. In populations where coinfection is common, selection should favor genotypes that have evolved mechanisms to escape the tradeoff between attracting mutualists and repelling parasites. Future work could test this hypothesis by comparing the strength of the genetic tradeoff between mutualism and parasitism in populations that differ in their histories of parasite infection.Our study joins a number of others demonstrating that an evolutionary genetic approach to mutualism can yield meaningful new insights about these positive species interactions Heath . A recenGenetic conflict with parasites could significantly alter the rate and trajectory of evolution in mutualisms. The impact of this conflict on mutualism evolution depends on three factors about which little is known in any system: the degree of overlap in the genetic pathways controlling the two symbioses; how parasites disrupt mutualistic partnerships; and the ecological factors that mediate conflict. All three of these factors warrant further study in the legume–rhizobia mutualism, and a diverse array of other positive species interactions.Associate Editor: A. GardnerSupporting MaterialClick here for additional data file.


Dimorphandra exaltata, from the Brazilian Atlantic Forest, a hotspot for conservation. We coupled species distribution models and geospatial assessment based on herbarium records with population genetic analyses to evaluate its genetic status and extinction risk, and to suggest conservation measures. Dimorphandra exaltata shows low genetic diversity, inbreeding, and genetic evidence of decrease in population size, indicating that the species is genetically depleted. Geospatial assessment classified the species as Endangered. Species distribution models projected a decrease in range size in the near future (2050). The genetic status of the species suggests low adaptive potential, which compromises its chances of survival in the face of ongoing climatic change. Altogether, our coupled analyses show that the species is even more threatened than indicated by geospatial analyses alone. Thus, conservation measures that take into account genetic data and the impacts of climate change in the species should be implemented.Although there is a consensus among conservation biologists about the importance of genetic information, the assessment of extinction risk and conservation decision-making generally do not explicitly consider this type of data. Genetic data can be even more important in species where little other information is available. In this study, we investigated a poorly known legume tree,  Information used to decide if a species is at risk of extinction, and what threatened category it falls into is generally based on ecological and demographic data such as the number of known individuals, actual or projected declines in population size, and the extent of occurrence (EOO) or area of occupancy (AOO)4. The EOO is an estimate of the total area currently occupied by a taxon and the risks within this area4. The AOO is a metric of current occupation of suitable habitats within the EOO, and measures the risks to a taxon occurring within small patches or in few patches within the EOO4. Demographic information is fundamental in conservation biology, but in several species, it is difficult to directly estimate.Habitat loss, overexploitation of natural resources, invasion by alien species, and global climate change are among the most important factors that threaten biodiversity, and can synergistically act to increase species extinction risk in the future6. The “genetic health” of a population or species is dependent on its genetic diversity and inbreeding level. Rare and endangered species tend to have reduced genetic diversity within populations and low gene flow rates among them, because in general the populations are small and highly disjointed7. Furthermore, habitat loss and fragmentation processes can lead to the disruption of pollination and dispersion, resulting in low reproductive success and making populations more isolated and prone to inbreeding depression, i.e., a reduction in the capacity for survival and reproduction of the offspring of inbreeders8.There is a consensus among conservation biologists as to the importance of genetic factors in determining the fates of populations or species, but these factors are not generally used to define the conservation status of a speciesE), a fundamental parameter for the conservation of threatened species11. The NE of an actual population can be defined as the size of an ideal population that suffers the same magnitude of genetic drift as the actual population; this genetic drift is generally measured as a loss of heterozygosity, increase of identity by descent, or change in allele frequency over time12. The difficulty and impracticality of directly counting individuals in most species, coupled with the importance of genetic parameters in putatively threatened species, led to the use of NE in place of census population size in species conservation. Furthermore, several population genetic tools based on coalescent theory are currently available for estimating the temporal dynamics of NE and detecting population genetic structure and migration rates among populations15. Information about these genetic parameters could be used to gain knowledge about how global habitat loss, fragmentation and novel environment will affect a species and thus help to optimize its conservation20. These genetic studies are even more important in poorly known species, as they could help to infer a species’ conservation status and aid in making decisions about its conservation.The genetic diversity and degree of inbreeding in a population are directly dependent on the effective population size . Although D. exaltata is the type species of Dimorphandra as described by Schott in 182721, there are only a few herbarium records  potential geographical distribution to investigate current habitat suitability and project the impact of climate change on the species. Based on the genetic and ecological data, we suggest conservation measures for the species.Here, we performed population genetic analyses to assess the genetic status of est Fig. ; Table 128, we considered the estimates without null allele correction. No significant linkage disequilibrium between loci was observed in any comparison after Bonferroni correction. To estimate the genetic diversity and structure of D. exaltata we also included the seven isolated individuals of the Atlantic Forest in addition to the three sampled populations. These individuals from three sites with distances ranging from 31.5 to 95.7 km were analysed together  after Bonferroni correction, with estimated values of 0.195 and 0.178 (P < 0.05), indicating deviation from Hardy-Weinberg equilibrium in these populations  and RST of 0.120 (P = 0.000), indicating moderate genetic divergence among populations  ranged from 13.5 to 22.7, indicating low number of reproductive individuals (Table Em) ranged from 0.086 from SER to ESM to 5.653 from ESM to SER , isothermality (Bio3), mean temperature of warmest quarter (Bio10), precipitation of wettest quarter (Bio16), and precipitation of driest quarter (Bio17). The values of TSS and AUC for model evaluation ranged from 0.333 to 1.000 and 0.611 to 1.000, respectively  based on 19 herbarium records to evaluating the conservation status of D. exaltata, we estimated an extent of occurrence (EOO) of 263 905 km2 and a much smaller area of occupancy (AOO) of 76 km2 for the species. Due to the possibility of misidentification in the only record for D. exaltata in speciesLink at Jequié, Bahia state, and because we could not find any other description for the species in Bahia in specialized literature32, we also performed the EOO and AOO analyses without this record. The estimates of EOO and AOO without Jequié were 174 936 km2 and 72 km2, respectively, similar to estimates with the complete dataset. Based on the B criteria of the IUCN, the species was classified as Low Concern according to the EOO (EOO > 20 000 km2) and as Endangered according to the AOO (AOO < 500 km2) in both analyses, with and without Jequié. In addition, following the B2 criteria, the species should also be considered Endangered because it meets the two following conditions: (a) severely fragmented populations and (b) continuous decline in area as indicated by (bi) projected EOO and (biii) continuing decline in area, extent, and/or quality of habitat.Using the Geospatial Conservation Assessment Tool softwareD. exaltata exhibits low genetic diversity, inbreeding, and evidence of a recent decrease in population size. Furthermore, species distribution models project a reduction in range size for the near future (2050). According to the geospatial criteria of the IUCN (2014), the species falls into the Endangered category of extinction risk. Altogether, our data indicate clearly that D. exaltata is a threatened species of the Atlantic Forest. The contribution of genetic data, in addition to ecological data, to establishing the extinction risk of the species and the importance of obtaining both types of data to establish measures of conservation are discussed below.Our study showed that Dimorphandra exaltata populations have lower genetic diversity (HE = 0.289–0.560) than populations of several other legume tree species from the Atlantic Forest, including Hymenaea courbaril (HE = 0.536–0.804)33, Centrolobium tomentosum (HE = 0.500–0.550)34, Inga vera (HE = 0.655–0.865)35, Copaifera langsdorffii (HE = 0.881–0.893)38, and the vulnerable Dalbergia nigra (HE = 0.682–0.798)41, all species evaluated with microsatellite markers. Another appreciation of the level of genetic diversity of D. exaltata could be based on a comparison with closely related species, which discounts the phylogenetic effect43. Dimorphandra exaltata populations exhibited considerably lower genetic diversity (mean HE per population of 0.413) than a widespread congeneric species, D. mollis, which shows a mean HE per population of 0.59444, as expected due to its more restricted distribution. Dimorphandra exaltata populations showed even lower diversity than the narrowly endemic and critically endangered congeneric species D. wilsonii, with a mean HE per population of 0.55927. Although our genetic diversity evaluation was limited to 62 individuals, from three populations and isolated individuals from Atlantic Forest due to the rarity of the species, the low genetic diversity found indicates that D. exaltata is genetically depleted.E of D. exaltata populations ranged from 13.5 to 22.7 and the estimated historical NE ranged from 11 to 700, which points to a low NE for the species. The comparison between the two NE together with the bottleneck tests point to a severe decrease in the population sizes of the species, what is probably associated with habitat loss and fragmentation in the study area. This pattern can explain the low diversity found in D. exaltata, since NE is one of the most relevant parameters to explain the patterns of genetic variation in wild populations11. These results are very important for the management of endangered species since NE of 100 and 1 000 individuals are suggested to prevent loss of genetic diversity by genetic drift for five generations and to maintain long-term evolutionary potential, respectively45.The contemporary ND. exaltata suggests considerable admixture among populations, except for the isolated individuals of the Atlantic Forest. The historical demographic analysis reinforces that the three populations were genetically connected in the past. However, we should take care in extrapolating this connectivity to the current time. In fact, during our fieldwork, we observed a very low number of individuals and they were isolated and separated by large spatial distances, mainly in eastern Atlantic Forest. Also, the land use maps showed great anthropic pressure in the areas of occurrence of the species46 , which are vulnerable and locally extinct in some areas26. Although the seed disperser of D. exaltata is not known, the similarity among species of the genus suggests a similar pattern for it. This is a matter of concern because at least 1.0 migrant per generation is necessary to counteract the genetic drift effects in the loss of diversity of populations47.The population genetic structure of s46 Fig. , which rD. exaltata is not known, it is probably similar to that of the congeneric D. wilsonii, which has self-compatibility26 but mainly performs outcrossing48. The inbreeding found in D. exaltata may be due to selfing or mating between related individuals . The small population size could favor mating among relatives or selfing in opposition to outcrossing. Increased selfing in preferentially outcrossing species is commonly found after fragmentation5. Furthermore, perennial plants, that have recently undergone habitat loss and fragmentation, such as D. exaltata, have a high probability of suffering inbreeding depression8. Therefore, inbreeding might be an additional threat to D. exaltata.Our populations showed significant inbreeding coefficients, indicating a departure from random mating within populations. Although the mating system of 45. Thus, the genetic data gathered here for D. exaltata, which showed low genetic diversity, inbreeding, and a recent reduction in population size, indicate that the “genetic health” of the species is compromised, which may decrease its adaptive capacity and threaten its survival in the wild in the near future. Thus, the genetic analyses of the species itself allow us to classify D. exaltata as a threatened species. In addition, the genetic data suggest that the species is more threatened than indicated by geospatial analyses.It is well-established that species with isolated and small populations are subject to loss of genetic diversity, a higher degree of inbreeding, and an elevated extinction risk in the wildD. exaltata in the near future (2050) suggests a decrease in the total area of occurrence, including in the area in which it is most found currently, along with a displacement toward the south. The climate is considered to be the main driver of the species’ range extent at large scales and of its long-term dynamics53. In face of climate change, the probability of survival of a species is dependent on its capacity to adapt to the new environmental conditions or to migrate to suitable habitats54. However, the genetic data showed that the adaptive potential of D. exaltata is probably compromised. Thus, the species may depend on its migration capacity to colonize new favorable areas to survive in the face of climate change. However, the current connectivity among populations of the species is likely compromised by both low seed dispersal and pollen flow. Thus, the projected reduction of areas of occurrence and their displacement may be a concern for D. exaltata.The projected distribution for D. exaltata should be classified as Endangered, according the B2 criteria4 (AOO less than 500 km2). Furthermore, it could be also considered to be in the Threatened category because the populations are severely fragmented and there is a projected decline of this area, along with the low quality of its habitat (the sub criteria of B2). The Atlantic Forest has a fragmented distribution, with a history of disturbance and low functional connectivity among fragments24. Furthermore, the D. exaltata areas of occurrence in the Atlantic Forest/Cerrado transition zone, where the species is partially sympatric with D. wilsonii, are dominated by anthropogenic landscapes due to conversion of forested areas to agricultural lands, urbanization, and fire. These are the main threat factors for D. wilsonii27 and may also play this role for D. exaltata.The geospatial assessment analyses showed that D. exaltata occurs in one of the most-inventoried regions of southeastern Brazil, only 19 occurrence records were found, demonstrating the rarity of the species. In several areas of Atlantic Forest/Cerrado transition, D. exaltata occurs together with D. wilsonii, a critically endangered species, which has a National Action Plan for its conservation27 (PAN faveiro de Wilson). It is highly recommended that this Action Plan also include D. exaltata, as the two species share similar ecological requirements and the same threat factors. Furthermore, only three records for D. exaltata were within protected areas. Protecting areas where the two Dimorphandra species co-occur will lead to protection of both threatened trees.Although D. exaltata are its low genetic diversity and its low effective population size. Considering the ecological and genetic risk factors, conservation actions are urgently needed to decrease the probability of species extinction. Firstly, we recommend more search to find new individuals/populations of the species, mainly in easternmost areas Atlantic Forest. In addition, we recommend reintroduction, ex situ conservation, and genetic rescue to increase genetic diversity and maintain genetic connectivity among its populations. Genetic rescue is a highly beneficial strategy for management of genetically depleted populations55. For this, the creation and permanent maintenance of ex situ production of saplings from seeds of trees from different populations is a priority. As the analysed populations are not very genetically divergent, saplings from different populations could be introduced into the same locality, which could increase the genetic diversity and decrease the rate of inbreeding. However, considering the high genetic divergence of individuals from the eastern Atlantic Forest in relation to other areas, we suggested reintroduction in the eastern Atlantic Forest preferentially with saplings produced by seeds from these locations. The saplings should be used to increase the sizes of current populations, which must be protected, and to reintroduce the species into suitable areas according to SDM projections. It should be noted that the current suitable areas will suffer significant reduction in even the most optimistic projection of climate changes. Thus, it is recommended to take in account this projection when choosing localities for reintroduction.The genetic analyses indicated that the main risk factors to wild persistence of Our integrative genetic and ecological framework to assess the degree to which a poorly known tree species is threatened and to guide conservation measures for that tree species, which occurs in the Atlantic Forest, a large and highly threatened biome in eastern South America, was demonstrated to be highly effective. This strategy of investigation, which includes genetic data, could be used for species in other conservation hotspots worldwide, where generally there is a lack of demographic information to establish the conservation status of species. From the results, our integrative framework supplies essential information for conservation policies.Dimorphandra exaltata is a medium to tall tree (15–30 meters), with bipinnate leaves, opposite leaflets pairs, and densely hairy petioles. Its inflorescences have a corymbe-type panicle consisting of multiple spikes. The flowers are cream or yellow with a glabrous chalice. Its fruits are flat legumes, which are almost straight, woody, and dark, indehiscent with sub-cylindrical seeds21. It flowers during November–December and fruit maturation occurs in September–October21. The pollinator and seed disperser of D. exaltata are not known. However, it has been proposed21 that the pollination is performed by insects because of the similarity of its inflorescences and flowers with those of the congeneric species D. vernicosa, which is pollinated by bees of the Apidae family.D. exaltata through analyses of herbarium records. Georeferenced herbarium records of D. exaltata were obtained mainly from the speciesLink database56, but to check for duplicates and to add missing records, other databases were used as well32. Due to the similarities among several species of the genus, the records of D. exaltata were compared with those of other Dimorphandra species to avoid misidentification. We retained only the most recent records by locality to avoid bias due to differential sampling efforts in certain areas and aggregated surveys. The localities were defined as the exact coordinates of the sites available in the record or alternatively, when the coordinate of the site was not available, by the municipalities coordinates. After the filtering process, we obtained only 19 georeferenced records in the speciesLink database  and Valença (VAL) and in a municipality that do not had register for D. exaltata occurence, Santa Bárbara do Monte Verde (SBM) in the semi-deciduous Atlantic Forest. These areas are highly fragmented and disturbed due to urban pressure and soil conversion to croplands46  and six isolated in D. wilsonii62  Amplifications of all markers were performed according to61. The amplicons were submitted to capillary electrophoresis in an ABI prism 3500xl automated sequencer with GeneScan TM ROX500TM as a standard fragment  and genotyped in GeneMapper software Version 5.0 (Applied Biosystems). Scoring errors due to the presence of null alleles, stuttering, or large allele dropout were evaluated in MicroChecker version 2.2.0.228. Linkage disequilibrium for each pair of loci for each population was tested using a randomization-based test in FSTAT version 2.9.3.263.Frozen leaf or vascular tissue was used for DNA extraction according to the cetyltrimethylammonium bromide (CTAB) protocolD. exaltata populations was estimated by the following parameters: mean number of alleles per locus (A), expected and observed heterozygosity (HE and HO respectively) using ARLEQUIN 3.564 and the allelic richness (AR) using the rarefaction method of65 in FSTAT version 2.9.3.263. The number of private alleles were investigated in GenALEx 6.50367. The inbreeding coefficient (FIS) was calculated and departures from Hardy-Weinberg expectations were tested with exact tests in FSTAT version 2.9.3.263, with significance assessed after sequential Bonferroni correction for multiple comparisons. The FIS was not estimated for the AFI group because they can represent samples of more than one population. Analyses of molecular variance (AMOVA) implemented in ARLEQUIN 3.564 were used to estimate the hierarchical genetic structure and the pairwise FST and RST among populations.The genetic diversity of 58. Parameter sets assumed an admixture model with correlated allele frequencies among patches. Ten independent simulations were run with 100 000 chains as burn-in and 1 000 000 Markov chain Monte Carlo (MCMC) replicates after burn-in, testing for K = 1–8. To evaluate the best K number, the mean log likelihood of the model through all runs and ΔK statistics were used68. To visualize the individual ancestry proportion, the average of ten runs for K was calculated in CLUMPP version 1.1.269 and the bar plot membership coefficient of each individual was built in DISTRUCT 1.170.The number of genetic clusters was evaluated using a Bayesian clustering method implemented in STRUCTURE version 2.3.4NE) using the relation NE = 0.5/Θ71; Θ is the group molecular coancestry for the total number of sampled trees in each population72. The calculation of Θ was made using the equation (1), 72; Fi is the inbreeding coefficient of the i-th individual, θij is the pairwise kinship between the individual i-th and j-th38 and n is the sample size. Fi and θij were estimated in SPAGeDi 1.1 software73. We evaluated for recent reductions in population size using a test for heterozygosity excess implemented in BOTTLENECK version 1.2.0274. Populations that have suffered a recent size decrease exhibit reductions of allele numbers and heterozygosity. However, reduction in allele diversity is faster than that in heterozygosity, which leads to an excess of heterozygosity under Hardy-Weinberg equilibrium in comparison with the expectations of mutation-drift equilibrium75. Bayesian simulations were carried out using three mutation models for microsatellites, infinite allele models (IAM), stepwise mutation model (SMM), and two-phase mutation model (TPM), with 30% multi-step mutations to avoid biases due to wrong assumptions about mutation models. We ran 1 000 000 MCMC and used the Wilcoxon sign-rank test to analyse the significance of differences in heterozygosities.We estimated the contemporary effective populations sizes  and migration rates (M = m/μ), where μ is the mutation rate, were estimated using the Bayesian inference method. We considered μ = 4.76 × 10−3 mutations per locus per generation for the microsatellite loci76. The Brownian motion model for microsatellite data was defined as the mutation process of the markers and the prior distribution was set as uniform with Θ (10−5 to 100) and M (0 to 1 000). We ran 3 iterations with 2 000 000 MCMC after a burn-in of 50 000 generations, with sampling every 100 generations using a static heating scheme with four chains, swamping at every 10 chains based on an exponential temperature scheme. The independent runs were summarized to estimate the parameter values. The following models were tested: panmictic model, full migration model, zero-migration, a model with CON and ESM as one population, and a model with SER and CON as one population. We obtained the effective numbers of immigrants (NEm) using the equation (2) M * Θ = 4NEm, with the number 4 representing a scalar due to ploidy or inheritance of diploid nuclear data. The historical effective population size was estimated through the expression (3) (Θ/4μ) = ΝE.To test for models of historical gene flow among populations, we used a coalescent model implemented in MIGRATE-N 3.6.11D. exaltata, species distribution models (SDM) were performed using 19 bioclimatic variables available in the WorldClim database, with resolution of ~1 km29. To obtain a subset of uncorrelated explanatory variables, an exploratory factor analysis (EFA) was used in the psych 1.7.5 package implemented in the R environment78. The algorithms Maxent, Generalized Linear Models (GLM), Generalized Boosted Models (GBM), Artificial Neural Network (ANN), Classification tree analysis (CTA), Surface Range Envelopes (SRE), Flexible Discriminant Analysis (FDA), Multiple Adaptive Regression Splines (MARS), and Random Forest (RF) were implemented in the Biomod2 3.3-7 package in the R environment79. To evaluate model performance, we randomly subset points for training (75%) and points to test the predictive power of the models (25%). Then, we used the receiver–operating characteristic (ROC) curve and its area under curve (AUC) and the true skill statistic (TSS) to select the best models. Consensus maps were built based on five independent runs of each algorithm using the TSS as a criterion to discard low-predictive-power models (TSS > 0.7). To evaluate the impacts of future climate change on the distribution of the species, we projected its potential distribution in 2050 using the same set of variables for MIROC-ESM and BCC-CSM1-1 projections in an arc resolution of 30 s representing an intermediary and a maximum representative concentration pathway for this period, respectively.To assess the current potential distribution of D. exaltata was evaluated using the extent of occurrence (EOO) and area of occupancy (AOO), as estimated using the Geospatial Conservation Assessment Tool software30 (GeoCAT). Using this framework, we evaluated the conservation status of D. exaltata based on the International Union for the Conservation of Nature (IUCN) criteria B (EOO and AOO) to identify the threat category of the species4. The estimation of EOO was based on the minimum convex hull that contains all sites of known occurrence30. The estimation of AOO was based on the sum of squared grids of known occurrence based on grids of 2.0 km2 as suggested by IUCN guidelines30. The same dataset used in the SDM was used for geospatial analysis.The geospatial conservation status of Supporting information


Genetically related highly pathogenic avian influenza viruses (HPAIVs) of H5N6 subtype caused outbreaks simultaneously in East Asia and Europe—geographically distinct regions—during winter 2017–2018. This situation prompted us to consider whether the application of phylogeographic analysis to a particular gene segment of AIVs could provide clues for understanding how AIV had been disseminated across the continent. Here, the N6 NA genes of influenza viruses isolated across the world were subjected to phylogeographic analysis to illustrate the inter- and intracontinental dissemination of AIVs. Those isolated in East Asia during winter and in Mongolia/Siberia during summer were comingled within particular clades of the phylogeographic tree. For AIVs in one clade, their dissemination in eastern Eurasia extended from Yakutia, Russia, in the north to East Asia in the south. AIVs in western Asia, Europe, and Mongolia were also comingled within other clades, indicating that Mongolia/Siberia plays an important role in the dissemination of AIVs across the Eurasian continent. Mongolia/Siberia may therefore have played a role in the simultaneous outbreaks of H5N6 HPAIVs in Europe and East Asia during the winter of 2017–2018. In addition to the long-distance intracontinental disseminations described above, intercontinental disseminations of AIVs between Eurasia and Africa and between Eurasia and North America were also observed. Integrating these results and known migration flyways suggested that the migration of wild birds and the overlap of flyways, such as that observed in Mongolia/Siberia and along the Alaskan Peninsula, contributed to the long-distance intra- and intercontinental dissemination of AIVs. These findings highlight the importance of understanding the movement of migratory birds and the dynamics of AIVs in breeding areas—especially where several migration flyways overlap—in forecasting outbreaks caused by HPAIVs. Influenza A viruses have been isolated from birds and from various mammals, including pigs and humans . Wild waThe isolation of highly pathogenic avian influenza viruses (HPAIVs) from wild birds was rare , 16 untiDuring the winter of 2017–2018, both Asia and Europe experienced outbreaks of disease caused by H5N6 HPAIVs . SeveralIn this study, we performed a phylogeographic analysis of N6 NA genes deposited in public databases and our institutional repositories, including the H5N6 HPAIVs isolated during the winter of 2017–2018, to illustrate intra- and intercontinental dissemination of AIVs and to assess the relationship between virus dissemination and migration flyways of wild birds. Our findings should contribute to the strategic monitoring of AIVs in wild birds as part of efforts to clarify the ecology of AIVs and forecast HPAI outbreaks.The activities on sampling from wild birds in Russia were approved by the Committee on Biomedical Ethics of the Federal Research Center of Fundamental and Translational Medicine (No. 2017–16). No specific permission was required for sample collection from wild birds killed by local hunters in compliance with the Russian Federation hunting laws. Also, no permit was needed for sampling from wild birds captured alive during ringing activities in Biostations with collaboration with other research institute as part of the Russian national avian influenza surveillance. Sampling in Japan for viruses in this study required no permission as they are feces collected under the avian influenza surveillance of the Ministry of the Environment or samples applied for the diagnosis of avian influenza in National Institute of Animal Health in Japan. Samples from Vietnam and Cambodia are also not applicable as they originated to poultry and were collected for diagnosis.Nasal or cloacal swabs, or both, and feces were collected from poultry and wild birds in Japan, Vietnam, and Cambodia from 1977 to 2018 and preserved in media as described previously . At the http://platform.gisaid.org); accession numbers of each virus are listed in The whole genomes of the isolated viruses were obtained by using next-generation sequencing . RNA was extracted from isolated viruses by using an RNeasy Mini kit . cDNA libraries for next-generation sequencing were prepared by using an NEBNext Ultra RNA Library Prep Kit for Illumina . A total of 10 pM of synthesized cDNA libraries was mixed with 10 pM of PhiX control (Illumina) and sequenced by using a Miseq Reagent Kit . The consensus sequences were generated by using Workbench software  or FluGAS software . The N6 NA sequences of the viruses isolated in this study have been deposited in the GISAID database  trees for selected clusters of the maximum likelihood tree see  were con7 steps long to generate 10,000 trees, and the last 1000 trees were then used for Bayesian tip-association significance testing (BaTS) [P values < 0.05 were used as evidence to support correlations between traits and tree topology.Identical sequences of strains isolated from the same species, on the same date, and in the same place were removed from the N6 NA sequence alignment, and MCC trees without information about collection time were constructed. Calculations of constructed MCC trees were set as 1 × 10g (BaTS)  to evaluTo elucidate the intra- and intercontinental dissemination of genetically related AIVs by using phylogeographic analysis, a phylogenetic tree was constructed on the basis of the N6 NA genes of AIVs isolated worldwide. Phylogenetic analysis revealed that the N6 NA genes could be categorized into an Eurasian  and NortN6 NA genes of the H5N6 HPAIVs isolated in Asia and Europe during the winter of 2017–2018 were categorized into two clades, A and B , S1 Fig,The spatial and temporal relationships of clades A and B were phylogeographically analyzed by calculating the Bayes factors between the locations where AIVs were isolated . The BayLike clades A and B, clades H and J were composed of AIVs isolated in both Asia and Europe. In clade H, isolates collected in Sweden, the Netherlands, and Croatia from 2010 to 2014 were related to Mongolian isolates collected in August 2015 and to Japanese isolates in October 2015 and December 2016, with identity of 98.6% . PhylogeClades C, D, E, and F were composed exclusively of AIVs isolated in Asia. AIVs isolated in Mongolia, the Asian part of Russia, Bangladesh, and Japan after 2011 formed clade C, showing identity of 98.5% within the clade . IsolateIntracontinental movements of AIVs in Europe (clade G) or North America  were recognized. In clade G, AIVs isolated in Croatia in November 2011 and in Moscow, Russia, in October 2011, and those isolated in Sweden in September 2013, shared a common ancestor, with an identity of 99.3% . More thIntercontinental dissemination of N6 NA genes was observed in clades I, K, L, and M. Clade I consisted of AIVs isolated in Europe and Zambia, with identity of 98.7% within the clade . AIVs isClassification of clades by phylogenetic analyses revealed that some, such as clades J and K, were composed of specific subtypes or had specific host species. To investigate the statistically significant correlations between topology and subtype or host specificity, N6 NA sequence alignment was calculated for BaTS analysis . There wOf the 15 subtypes (H1–H14 and H16), 11  were calculated to cluster together in a phylogenetic tree (data not shown). Such subtype specificity was depicted in H4N6 subtypes in clades F, N, and P and in H13N6 subtypes in clades K, J, and Q.During the winter of 2017–2018, genetically closely related H5N6 HPAIVs caused disease outbreaks in Asia and Europe . Our phySeveral migratory bird flyways have been considered to contribute to AIV dissemination across Eurasia, and the regions where flyways overlap play important roles as relay points in the spread of viruses , 49. TheOverlapping of flyways also plays an important role in the intercontinental movement of AIVs between Eurasia and North America and between Eurasia and Africa. Previous studies revealed the importance of the Alaskan Peninsula, where the East Asia—Australia, the Pacific Americas, and the Mississippi Americas Flyways overlap, and a variety of AIVs were reported . Great wThere appear to be biases in traits such as host species and HA subtypes of AIVs constituting particular clades. Charadriiformes were clustered together as hosts of clade J . PreviouThe map obtained by phylogeographic analysis does not always reflect the actual movements of viruses. Linkages between geographically distant places with blanks for several years, as in clade C Click here for additional data file.S2 FigIdentified clades defined on the basis of the rule in this study are green and red, corresponding to the colors in (TIF)Click here for additional data file.S3 FigIdentified clades defined on the basis of the rule in this study are green and red, corresponding to the colors in (TIF)Click here for additional data file.S4 FigIdentified clades defined on the basis of the rule in this study are green and red, corresponding to the colors in (TIF)Click here for additional data file.S5 FigIdentified clades defined on the basis of the rule in this study are green and red, corresponding to the colors in (TIF)Click here for additional data file.S6 FigIdentified clades defined on the basis of the rule in this study are green and red, corresponding to the colors in (TIF)Click here for additional data file.S7 FigIdentified clades defined on the basis of the rule in this study are green and red, corresponding to the colors in (TIF)Click here for additional data file.S1 Table(TIF)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.


Embrapa Genetic Resources & Biotechnology (CENARGEN), one of the 42 Embrapa decentralized units. The first network-based model, RENARGEN, initiated in 2003, was followed by the National Platform for Genetic Resources (Platform RG) in 2009; and from 2014 until today Embrapa manages the conservation of genetic resources through Portfolio REGEN, in which the plant component is called Plant Genetic Resources Network (RGV). This network covers activities of enrichment, conservation, characterization, and documentation of genebanks. Embrapa's plant genetic resources are conserved in active genebanks (AGs), in long-term seed bank (Colbase), and in vitro and DNA banks. In situ and on-farm conservation are also handled at Embrapa to complement and reinforce ex situ conservation. The latest survey reveals that Embrapa has 134 AGs with ∼150,000 accessions of 1130 plant species, 123,000 accessions of 735 species within Colbase, 1250 in vitro accessions, and 12,000 DNA samples. At least 65% of this collection is documented and available to the public in the Embrapa Alelo system, which also handles quarantine, germplasm exchange, and herbarium data. By the end of 2018, the public Alelo data will be automatically migrated to the Genesys system. In the last 40 years, ∼650,000 accessions have been exchanged by Embrapa, with 70% of them imported from other countries.Brazil is one of the most biodiverse countries on Earth, holding ∼10% of the world's vascular plant species. Despite that, Brazilian agriculture is highly dependent on genetic resources originating from other countries. Embrapa  is the governmental institution that, since 1973, has been responsible for the introduction and conservation of genetic resources in Brazil. In this article, we report on the experiences that Embrapa has faced over the past 45 years to build and improve a national network for the preservation of plant genetic resources under the coordination of  Its advantageous location (between 5°N and 33°S and between 35°E and 74°W) and its large continental dimension  may be the geographic attributes that provide Brazil with the following characteristics:- Wide climate diversity, with tropical (predominant) and subtropical regions, and derivations of these climates;1;- Six vegetation biomes: Amazônia (Amazon Rainforest), Cerrado , Caatinga (Thorny Forest), Atlantic Forest, Pampas, and Pantanal (Wetlands)2;- Brazil has 33,161 species of vascular plants, which represents ∼25% of the Americas and 10% of the world plant diversity3;- Brazil is the main center of origin of the new species of vascular plants identified in the last three decades- 30% of Brazilian territory is arable land.- The largest fresh water reserves on the planet (8% of the world volume).BManihot esculenta), pineapple (Ananas comosus), peanuts (Arachis hypogaea), cocoa (Theobroma cacao), cashew , cupuassu (Theobroma grandiflorum), passion fruit (Passiflora edulis), Brazil nuts (Bertholletia excelsa), guaraná (Paullinia cupana), jaboticaba (Plinia cauliflora), and some palms such as assai (Euterpe oleracea), which is today widely consumed all over the country and exported.4 In addition, native forage species are predominantly used in the raising of livestock. On the contrary, Brazilian agriculture is highly dependent on genetic resources originating from other countries. The systematic introduction of exotic genetic resources, the ecological diversity, and the development of technologies and new varieties adapted to the different Brazilian biomes resulted in an intense and ample adaptation and expansion of several crops that are today considered, globally, as basic commodities. Today, Brazil stands out as the third largest producer of grains and the third largest exporter of agricultural products in the world, ranking first in the export of coffee, soybean, sugar, orange juice, alcohol, tobacco, beef, and chicken meat.5Several Brazilian native species are used as human food, of which we highlight cassava (Embrapa Genetic Resources & Biotechnology (CENARGEN) was created in 1974 to coordinate the activities of collection, conservation, quarantine, exchange, characterization, evaluation, and documentation of genetic resources in a collaborative way with SNPA partner institutions.4 Since then, collections of germplasm have been structured in different DUs, predominantly for plants.The Brazilian Agricultural Research System (SNPA), coordinated by Embrapa , is made up of public, federal, and state institutions; universities; private companies and foundations that conduct research in different scientific areas and different geographic regions. Embrapa is linked to the Ministry of Agriculture and Food Supply, and has 42 decentralized units (DUs) distributed throughout the country. Since its founding in 1973, Embrapa was designated to promote and facilitate the safe introduction of genetic resources. Brazil has achieved important results in agricultural research, with significant progress in the conservation and use of plant genetic resources, especially those related to food production. In this article, we report on the experiences that Embrapa has faced in the construction of a national network for the conservation and use of Brazilian plant genetic resources.6The preservation of genetic resources is essential for maintaining the natural genetic variability for use in breeding programs, especially those for food. In Brazil, this need is especially important as the predominant country's food-based crops are of foreign origin. We can mention, for example, that 90% of all species conserved in Embrapa's plant collections are of exotic species.7 The first three network projects focused on the conservation of genetic resources, while the fourth project network was composed of three crosscutting project components: curatorship, documentation, and germplasm exchange, which had a strong interaction with the other component projects of the three networks.7Starting in 2003, Embrapa has operated the first network-based model of management and conservation of genetic resources in a network called National Genetic Resources Network (RENARGEN). Considering the relevance of genetic resources as strategic assets for agricultural development, this model was improved and, in 2009, RENARGEN was replaced by the National Platform for Genetic Resources formed by four big project networks: (1) plant network, (2) animal network, (3) microbial network, and (4) network integration (transverse network).8 Of the 20 corporate portfolios approved during this period, the Strategic Management of Genetic Resources for Food, Agriculture and Bio-Industry (REGEN portfolio) was established in 2014.8 In this new model, the plant component, now called Plant Genetic Resources Network (RGV), is implementing a new phase following a restructuring of component projects. The activities of collecting wild relatives and native species of importance for agriculture and food are being reinforced, as well as in situ/on-farm conservation actions in support of ex situ conservation.9 The organization and documentation of information in the collections is a priority, and the main innovation in the RGV is the implementation of Quality Systems based on international standards, which is being established from the selection of minimum requirements.9From 2012 to 2015, Embrapa established new corporate management instruments called “Portfolios” to organize projects related to strategic themes of national relevance defined directly by the Board of Embrapa.9RGV is led by the Plant Genetic Resources Curatorship system, which coordinates germplasm banks and plant collections at a strategic level, allowing the planning of midterm (5 years) conservation actions. RGV consists of 20 component projects, of which 11 are dedicated to the conservation activities of genebanks and the other nine are of transversal actions . RGV is in vitro bank, and (4) DNA bank.10 Colbase works as a safety duplicate of the accessions maintained in AGs, to conserve seeds at −20°C for a long period.11 Embrapa also develops research and innovation to subsidize and promote in situ and on-farm conservation, both in natural environments and in agroecosystems.12Embrapa's RGV is fed by projects with specific activities for enrichment, conservation, characterization, and documentation of the collections, with the purpose of making them available for research, improvement, and food safety. Currently, Embrapa's plant genetic resources are conserved in (1) active genebanks (AGs), (2) long-term seed bank (Colbase), (3) Ex situ conservation of plant genetic resources refers to the maintenance of germplasm outside their place of origin in the short, medium, or long term. It comprises activities of enrichment through collection and exchange, documentation and proper conservation. Ex situ plant conservation at Embrapa works on germplasm acquisition through collection expeditions, exchange with institutions in Brazil and abroad, documentation, and development/improvement of methods related to ex situ conservation. The main aim is to do research on the establishment and improvement of methodologies used for ex situ collection and conservation of plant genetic resources, to ensure the physical, physiological, and genetic integrity of the collections, and also to provide the information associated with them.1310 The most recent published global survey carried out by Embrapa reports ∼150,000 accessions of 470 genera and 1130 species (native and exotic) conserved in 134 AGs; 123,000 accessions of 620 genera and 735 species in the Colbase; 1250 accessions of 24 genera and 63 species in the in vitro bank; and 12,000 accessions of 16 genera and 21 species in the DNA bank10 , in Brasília-DF. It is estimated that at least 240 genebanks are maintained in the other SNPA institutions,14 such as Agência Goiana de Assistência Técnica, Extensão Rural, e Pesquisa Agropecuária (EMATER); Empresa de Pesquisa Agropecuária de Minas Gerais (EPAMIG); Empresa de Pesquisa Agropecuária do Estado do Rio de Janeiro (PESAGRO); Empresa de Pesquisa Agropecuária e Extensão Rural de Santa Catarina (EPAGRI); Empresa Mato-grossense de Pesquisa, Assistência e Extensão Rural (EMPAER); Fundação Estadual de Pesquisa Agropecuária (FEPAGRO); Instituto Agronômico de Campinas (IAC); Instituto Agronômico de Pernambuco (IPA); Instituto Agronômico do Paraná (IAPAR); Instituto Nacional de Pesquisa da Amazônia (INPA); Universidade de Campinas (UNICAMP); and Universidade Federal Rural do Rio de Janeiro (UFRRJ).The AGs of Embrapa's RGV are organized in groups of (1) Cereals and Pseudocereals; (2) Oilseeds, Fibrous, and Leguminous; (3) Vegetables and Condiments; (4) Forages; (5) Fruits; (6) Medicinal, Aromatic, Dyes, and Insecticides; (7) Ornamental; (8) Forestry and Palm Trees; (9) Industrial; and (10) Roots and Tubers.A bank10 , involviA bank10 , in 29 EEmbrapa Eastern Amazon (with 18 AGs) in the State of Pará (North Region), Embrapa Temperate Agriculture (15) in the State of Rio Grande do Sul (Southern Region), and Embrapa Cerrados (14) in the State of Goiás . On the contrary, some Commodities Centers, which work with a large number of crops, are also responsible for maintaining many AGs, such as Embrapa Vegetables (17 AGs) in Brasília-DF  and Embrapa Cassava & Fruits (11) in Bahia (Northeast Region)  .The biggest collections are rice , soybean , beans , wheat , and sorghum (7215). Some other collections are very small, such as some native fruits, coconut (36 accessions), and strawberry (20 accessions). It is important to highlight that those collections are maintained in the field or in greenhouses, and the focus is to conserve the genetic diversity of each accession. So, in some cases, there are >150 plants of each accession in the field, as in the case of coconut.2, with modern and safe facilities to preserve, in the medium- and long-term, basic germplasm collections of plant and animal and backup of microorganism collections from Embrapa and partner institutions15 .16 From 2014 to 2016, the complete CIP's collection with 4391 accessions was safety duplicated from Peru to BGen, Brasília (back box security copy).16 It is the world's most valuable potato collection in terms of genetic diversity, containing both wild and cultivated varieties.One of the objectives of BGen is to house collections of plants, animals, and microorganisms maintained by partner institutions in Brazil and in other countries, such as the backup of the In situ and on-farm conservation is essential in conserving genetic resources and complements ex situ conservation. It covers the conservation, management, and restoration of species populations and their associated ecosystems, ensuring the evolution of species over time, in response to changing environmental conditions and the maintenance of agrobiodiversity. Embrapa develops research and innovation to promote conservation, both in natural environments and in agroecosystems, conducting biological inventories and geographic analysis for conservation planning; evaluation and development of management techniques for the sustainable use of biodiversity; ecological restoration in degraded landscapes; analysis and promotion of conservation of genetic resources by local communities and farmers.19 These studies subsidize actions and public policies for conservation, aiming not only the maintenance of species and their habitats but also of the human communities and their ways of life.19in situ conservation, important advances were made to create and establish conservation units (CUs) to protect natural areas that are threatened to disappear, such as large areas of forest in the Amazon biome. Furthermore, other important government initiatives, such as research conducted to indicate priority areas for in situ management and the prospecting of native species with potential for sustainable use, have arisen from the ratification by Brazil of the Convention on Biological Diversity in 1994.4 To achieve these objectives, the National System of Nature Conservation Units (SNUC) was established in 2000, coordinated by the Ministry of the Environment (MMA), which has promoted the creation and management of CUs at the municipal, state, and federal levels, allowing an overview of the natural areas to be preserved.20 In addition, SNUC has been establishing mechanisms that regulate the participation of the society in the management of CUs, enhancing the relationship between the State, citizens, and the environment.In the case of 21 Internationally, protected areas (PAs) are designated as lands for both CUs and traditional populations, such as indigenous lands (ILs).22 From the union of these two categories in Brazil, there are a total of 2471 units (1871 CUs + 600 ILs) covering an area equivalent to 30.2% of the Brazilian territory22 , the nine countries with an area of >2.5 million km2 devote, on average, 10% of their territories to PAs; and Brazil is the world champion in environmental protection (22The SNUC is the set of CUs that differ in two broad groups according to the form of protection and permitted uses: (1) those that need greater care due to their fragility and particularities (CU of Full Protection), and (2) those that can be used sustainably (CU of Sustainable Use).ritory22 . The relotection . In addiin situ conservation, the RGV has two component projects, one to promote the interface between in situ and ex situ conservation strategies, and the other to support collection expeditions to get cultivated species, wild species, and neglected species, in areas prone to any kind of risk or in areas considered GAPs in the genebanks, whose diversity is not yet represented in ex situ collections.9To complement 23The basic purpose of the plant germplasm exchange system is to promote the import, export, and internal transit of plant propagation material for agricultural research in a safe manner. The introduction of germplasm in Brazil is a dynamic process that aims to obtain more productive varieties resistant to pests and adapted to the soil and climatic conditions of the country. CENARGEN coordinates the exchange of plant germplasm in harmony and cooperation with the Ministry of Agriculture, Livestock and Food Supply (MAPA).24 By December 2014, a total of 660,139 accessions were exchanged, of which 482,713 were imports, 67,871 exports, and 97,558 domestic exchanges25–27  or when considered a landrace. Furthermore, all research with native species must be registered in the National System for Genetic Heritage (SisGen)29 before any publication or before the development of any commercial product arising from the use of native genetic material. Decree number 8,772/2016, in what concerns this registration, requires that the origin of the genetic heritage found under in situ conditions be informed, even if obtained from ex situ or in silico sources. Therefore, the Law and Decree that regulate access and benefit sharing in Brazil have already recognized access to dematerialized genetic resources in its framework, although this discussion is still ongoing in international level. Thus, the regulation of Law 13,123 provides that to submit a sequence to any database, a Standard Material Transfer Agreement (SMTA) with the database must be signed. Also, research utilizing genetic information obtained in silico must register the use of this information at SisGen if the research results are in any publication or product.30Although several species native to Brazil are used as human food, most of them are fruits, nuts, or tubers and roots. Brazil is mainly dependent on exotic germplasm for food. Nevertheless, native materials such as groundnut, cashew, cassava, and pineapple are of interest to other countries. However, the export of Brazil germplasm is very low. This can be explained by very restrictive Brazilian laws. The law number 13,123/2015, currently in force,31 Due to limitations to expand computer equipment, the system was restricted to CENARGEN, preventing its full implementation. In 1996, SIRG underwent a reengineering work, incorporating modern information technologies, used at the time, by USDA's Germplasm Resources Information Network (GRIN), resulting in the development of the Brazilian Genetic Resources Information System (SIBRARGEN), designed to establish and maintain a centralized database on genetic resources of plant, animals, and microorganisms, and making it available through the Internet for searching the following databases: Taxonomy, Passport, Exchange, Quarantine, ex situ Conservation, Collection, Characterization, Evaluation and Use of Germplasm, Curatorship and Germplasm Banks.31 The SIBRAGEN homepage was designed with web tools (HTML and JSP) using Embrapa's network infrastructure. In its first phase, the system was implemented within Embrapa. However, other Brazilian institutions, within the SNPA, also have used it.31In the late 1980s, Embrapa/CENARGEN started the development of the Genetic Resources Information System (SIRG), which had a centralized database format with decentralized maintenance and access.7 This was done to meet the demand for germplasm exchange based on the MultiCrop Passport Data (MCPD-FAO) in the framework of the International Treaty on Plant Genetic Resources for Food and Agriculture (FAO Treaty). In this pilot test, SIBRARGEN made adjustments to comply MCPD standards and made available passport data of the cassava genebanks. Another important aspect considered in the framework of the system update was the integration of SIBRAGEN Plant Module into Global GRIN (Germplasm Resources Information Network), developed by the USDA in cooperation with Biodiversity International and the Global Crop Diversity Trust.7About 8 years using SIBRARGEN, Embrapa decided that it should be technically evaluated to adapt to future needs, both to increase user satisfaction and to improve system performance by incorporating up-to-date Web technologies. At that time, Brazil had been selected by Food and Agriculture Organization (FAO) of the United Nations to join the group of countries that would test the integration of national genetic resources information systems through a multilateral system under development by FAO.For at least three decades, Embrapa used the SIBRARGEN as the main database for all genetic resource activities, such as germplasm exchange, quarantine, and long-term conservation, carried out by Embrapa/CENARGEN. Over the years, CENARGEN has ceased to be the main responsible for the collection, conservation, regeneration, and germplasm distribution activities, which are being increasingly carried out by the curators of AGs in the Embrapa's DUs. By now, 29 DUs are involved in Plant Genetic Resources Conservation, from collection up to characterization. With this decentralization, it became necessary to develop a more modern, user-friendly, and accessible online tool that would allow the curators, in any of the DUs, to feed the system with the data related to the bank under their responsibility. CENARGEN, in this new scenario, remains responsible for coordinating the entire conservation system of Embrapa for quarantine, germplasm exchange, and for the long-term collection (Colbase).32 The system is designed to document, record, and make data publicly available. Everything about passport data, routine activities and characterization and evaluation can be documented in this system.33 It was developed in free software and is available on the Internet . It allows quick and easy access to the general public. It also includes information on quarantine, germplasm exchange, DNA, long-term conservation, in vitro conservation, and the herbarium.34 Alelo is populated by the curators and their teams in a decentralized manner, allowing the updating of the Embrapa genetic resources database.In view of the need for a new, more modern, and accessible documentation system, Embrapa, in 2011, began to develop the Alelo System. This data platform encompasses all the information related to the conservation of plant, animal, and microbial genetic resources at Embrapa.All the information about Embrapa's AGs is being migrated to Alelo platform. It is expected that all the passport data will be available for consultation by the end of 2018 and all information regarding characterization will be available by the end of 2019. 34In recent years, CENARGEN, along with Ministry of Agriculture, Livestock and Food Supply (MAPA), started to share the use of the Alelo platform with other Brazilian research institutes and universities. This can be considered the first step toward organizing and making available all the information regarding the public collections in Brazil. CENARGEN has already signed a membership and responsibility agreement with Rio de Janeiro State Agricultural Research Corporation (Pesagro), Rural Federal University of Rio de Janeiro (UFFRJ), State University of North Fluminense (UENF), State Agricultural Research Foundation (FEPAGRO-RS), and National Institute of Research of the Amazon (INPA). With the agreement, the parties are committed to exchanging confidential and nonconfidential information uploaded, downloaded, and shared through the Alelo portal.34These partnerships are not restricted to national institutions. Teams of curators from Uruguay's National Agricultural Research Institute (INIA) and the Paraguayan Institute of Agrarian Technology (IPTA) have also signed the same agreement, which allows them to perform a range of activities and duties. To work with Embrapa's teams, the curators in partner organizations participate in training on Alelo's reference modules: passport, observation, conservation, and studies for system data validation.https://www.genesys-pgr.org), a global information portal on genetic resources, which currently houses genebanks data from ∼200 countries, covering ∼11 million records, including passport, collection, characterization, and evaluation. Since Genesys data can be migrated to GRIN Global, the Alelo is compatible with GRIN Global. The main objective is to comply with the requirements of the International Treaty on Plant Genetic Resources for Food and Agriculture (ITPGRFA), ratified by Brazil in 2006.33A cooperation agreement signed between Embrapa and the Global Crop Diversity Trust will enable the automatic migration of public data on plant genetic resources generated by Embrapa to the information system Genesys .http://sweetgum.nybg.org/science/ih/) with the code CEN. In March 2005, it was accredited as a Faithful Custodian by the Genetic Patrimony Management Council of the Brazilian Ministry of Environment (CGEN/MMA). Since 1985, it has been made available online. , and in 2014 its collection is available in the Virtual Herbarium of Flora and Fungi-INCT (http://inct.florabrasil.net/).Embrapa's Herbarium, located at CENARGEN, was established in 1976, and is registered in the Index Herbariorum  (https://www.gbif.org), which is the largest online database on global biodiversity.35CEN Herbarium and its Plant Systematics Laboratory aim to study and record species of Brazilian flora and local flora, carry out expeditions to collect germplasm and support Over the last 40 years, Embrapa has developed a large and complex system for the conservation of plant genetic resources. As a National Agricultural Research Institution, it took over the responsibility of conserving >140 different crops and wild relatives, allowing Embrapa to access a very rich source of resources that culminated in the development of hundreds of projects and consequently hundreds of cultivars, patents, and processes. They all had and still have conserved genetic resources as the basis of the research.


Prunus serotina Ehrh.) (Rosaceae) is a forest tree species widespread in eastern North America, and found sporadically in the southwestern United States, Mexico, and Guatemala. IBD has been studied in relatively few North American plant taxa, and no study has rigorously sampled across the range of such a widespread species. In this study, IBD and overall genetic structure were assessed in eastern black cherry (P. serotina Ehrh. var. serotina), the widespread variety of eastern North America. Eastern North America. Prunus serotina Ehrh. var. serotina (Rosaceae). Dense sampling across the entire range of eastern black cherry was made possible by genotyping 15 microsatellite loci in 439 herbarium samples from all portions of the range. Mantel tests and STRUCTURE analyses were performed to evaluate the hypothesis of IBD and genetic structure. Mantel tests demonstrated significant but weak IBD, while STRUCTURE analyses revealed no clear geographic pattern of genetic groups. The modest geographic/genetic structure across the eastern black cherry range suggests widespread gene flow in this taxon. This is consistent with P. serotina's status as a disturbance‐associated species. Further studies should similarly evaluate IBD in species characteristic of low‐disturbance forests.Isolation by Distance (IBD) is a genetic pattern in which populations geographically closer to one another are more genetically similar to each other than populations which are farther apart. Black cherry ( D. Sauer] with a 10‐locus microsatellite dataset, Griffin and Barrett (Trillium grandiflorum (Michx.) Salisb. (R2 = 0.17) using allozymes, and a study of 10 microsatellite loci found a significant signal of IBD in diploid Galax urceolata (Poir.) Brummitt (R2 = 0.148)  with 11 microsatellite loci (R2 = 0.128/R2 = 0.067 FST/RST), as did Geraldes et al. (Populus trichocarpa Torr. & A. Gray ex Hook) (R2 = 0.2873). Victory, Gloubitz, Rhodes, and Woeste (Juglans nigra using 12 microsatellite loci (R2 = 0.006), as did Hadziabdic (Cornus florida) (R2 = 0.01). Many other studies have indirectly addressed the notion of IBD in North American plants, often through the visual interpretation of the geographic array of DNA sequence haplotypes or multivariate genetic clusters. Thirteen of the 19 native plant taxa reviewed in Soltis, Morris, McLachlan, Manos, and Soltis  Heynh. (p = 0.99) with amplified fragment length polymorphisms (AFLPs), and Kirk, Paul, Straka, and Freeland  Trin. ex Steud.  using microsatellite markers. Durka, Bossdorf, Prati, and Auge  with microsatellite loci. This general lack of IBD in exotic species is not surprising given the potential for multiple introductions of genetically variable material to the non‐native range, and the propensity for widespread non‐native species to exhibit frequent long‐range gene flow.Previous studies do suggest that IBD is present, at least in native North American plant species. In herbaceous plants, Waselkov and Olsen  demonstr Barrett  found sis et al.  with SNPd Woeste  also foudziabdic  in flowed Soltis  exhibited Soltis . In contd Soltis  found noFreeland  and StabFreeland  found noand Auge  did findPrunus serotina Ehrh. var. serotina), a widespread eastern North American forest tree that is important ecologically as a wildlife food source  Little is restricted to the Edwards Plateau of central Texas; Prunus serotina Ehrh. var. alabamensis (C. Mohr) Little is found in Georgia, Alabama, South Carolina, and Florida; Prunus serotina Ehrh. var. salicifolia (Kunth) Koehne is found in southern Mexico and Guatemala; and Prunus serotina Ehrh. var. rufula (Wooton & Standl.) McVaugh from Texas to Guanajuato  serrated leaf margins, leaves more than 2.5× as long as wide, and persistent sepals when in fruit. One or two small leaves were removed when sufficient material was present, and labels noting that material was removed for DNA extraction were affixed to all sampled sheets. All specimens were georeferenced with Google Earth .Our group personally visited 21 herbaria (obtaining 373 specimens) and requested tissue from 13 herbaria (131 specimens) in 2014, 2015, and 2016 .Following a high‐throughput DNA extraction , including only samples from which ≥12 loci were amplified (n = 439), and including only samples from which ≥14 loci were amplified (n = 381). Mantel tests on all datasets detected similar levels of IBD (see results), and the “≥12‐locus dataset” was chosen for the remainder of our analyses to strike a balance between missing data and sample number. Mantel tests on subsets of the ≥12‐locus dataset to rule out effects of age and quality were also conducted. These subsets included an “old” dataset , a “young” dataset , and a “quality” dataset . “Quality” locations were those with relatively specific location information which did not note obviously anthropogenically altered sites . A Mantel correlogram analysis  but not of herbarium of origin (p = 0.180) on the number of loci genotyped , as were all such tests ≥12‐locus dataset subsets,   exhibited a cluster assignment of ±25%, while all other samples exhibited an assignment of exactly 25% to each cluster. In the diploidized analysis, only 18% (79 samples) had a cluster assignment of ±25%.All Mantel tests  were significant  Figure  summary 4P. serotina var. serotina range, regardless of dataset type and largely regardless of distance class. The fact that similar levels of IBD were observed in the total ≥12‐locus, “young” ≥12‐locus, and “old” ≥12‐locus datasets suggests that IBD has not changed qualitatively in this species over the past century, and that the modest signal we observed is not an artifact of comparing samples representing different collection periods. Similarly, the signal observed with the “quality” ≥12‐locus dataset suggests that low observed IBD is not a product of over‐sampling individuals from anthropogenic sites. Herbarium collections are strongly biased toward roadsides and other human‐accessible areas  fell with population number, perhaps due to the increased landscape complexity sampled with a larger population matrix. In contrast, Pelletier and Carstens , this study differed from ours in critical respects. Besides featuring an inter‐population sampling strategy, their 18 populations spanned the four Prunus serotina s.l. varieties found in Mexico and Texas. Their measure of IBD therefore combines geographic limits to gene flow due to both distance and potential reproductive incompatibility among varieties.Mantel tests establish that only 1%–2% of the variation in genetic distances among eastern black cherry individuals can be explained by straight‐line geographic distance. For comparison, geographic distance on average explained 22% of such variation in the 240 inter‐population studies reviewed in Jenkins et al. . AlthougP. serotina var. serotina's range is consistent with its life history. The species is fast‐growing  to 10 (low tolerance)  (C = 2.8) and Acer saccharinum L. (silver maple) (C = 3.5). Both are commonly found in disturbed sites. In contrast, the eastern North American tree species displaying significant inter‐populational IBD discussed above receive higher C‐values  , m McAvoy   Blume (spice bush C = 5.8, Edwards & Niesenbaum, Cercis canadensis L. (redbud C = 5.8, Wadl, Trigiano, Werner, Pooler, & Rinehart, P. serotina var. serotina and help shape our understanding of gene flow in North American forests.If the low level of IBD observed here indeed results from eastern black cherry's life history, this result requires context before any generalization is made regarding widespread North American forest trees. Fortunately, similar rangewide inter‐individual studies of widespread woody plants typical of higher quality habitats could be easily undertaken given the efficiency of the herbarium sampling strategy and the availability of microsatellite markers. For example, a set of loci developed for The authors have identified no potential conflict of interests.J.B. and J.S. conceived the ideas; L.K. and J.B. collected the data; L.K. and J.B. analyzed the data; and L.K. and J.B. led the writing. Click here for additional data file.


By combining well-established population genetic theory with high-throughput sequencing data from natural populations, major strides have recently been made in understanding how, why, and when vertebrate populations evolve crypsis. Here, we focus on background matching, a particular facet of crypsis that involves the ability of an organism to conceal itself through matching its color to the surrounding environment. While interesting in and of itself, the study of this phenotype has also provided fruitful population genetic insights into the interplay of strong positive selection with other evolutionary processes. Specifically, and predicated upon the findings of previous candidate gene association studies, a primary focus of this recent literature involves the realization that the inference of selection from DNA sequence data first requires a robust model of population demography in order to identify genomic regions which do not conform to neutral expectations. Moreover, these demographic estimates provide crucial information about the origin and timing of the onset of selective pressures associated with, for example, the colonization of a novel environment. Furthermore, such inference has revealed crypsis to be a particularly useful phenotype for investigating the interplay of migration and selection—with examples of gene flow constraining rates of adaptation, or alternatively providing the genetic variants that may ultimately sweep through the population. Here, we evaluate the underlying evidence, review the strengths and weaknesses of the many population genetic methodologies used in these studies, and discuss how these insights have aided our general understanding of the evolutionary process. The past decade has seen considerable advances in understanding the generation and maintenance of phenotypic diversity. By utilizing the power of high-throughput sequencing, large-scale long-term field studies, and well-established population genetic theory, evolutionary biologists have gained a clearer understanding of the factors underlying adaptive differentiation in natural populations. Many of these insights have stemmed from studies on natural variation in coloration  in which complementary functional tests combined with detailed population genetic analyses and field-based experimentation have led to a robust understanding of the molecular basis underlying coloration. We discuss the population genetic insights gleaned from such studies, as well as future directions of interest.In this review, we summarize examples of cryptic coloration in vertebrates. We restrict the scope to a set of study systems , and Agouti, which encodes an MC1R antagonist, the agouti signaling protein  represents one of the first vertebrate systems in which the population genetics of cryptic coloration was studied  and the oldfield mouse (P. polionotus) have recently colonized lighter soils - the Nebraska Sand Hills, formed by the deposition of wind-blown quartz-sand, Florida’s Gulf coastline, formed from glacial melt, and Florida’s Atlantic coast, formed by shells resulting from rising sea levels  have received the most attention in the scientific literature. Despite the large geographic distance, populations inhabiting light-soil environments are phenotypically more similar to one-another than they are to the nearby dark-soil populations—an observation that raised the possibility of convergent evolution in this system  and the whiptail lizard (Aspidoscelis inornata), both of which have independently converged upon a cryptic blanched phenotype, generally thought to confer selective advantage through substrate matching to avoid predation  is associated with a light phenotype, the causal mutation differs in the two species.Similar to ion Fig. . DespiteLepus americanus) is a boreal North American species that undergoes seasonal coat color change from brown to white to minimize coat color contrast in winter , even in the presence of complex demographic histories. To ensure the statistical validity of their conclusions, null distributions of HapFLK were simulated under their inferred neutral demographic model characterizing the colonization history of the Sand Hills mice. While significant background  genetic structure was observed between populations on and off the Sand Hills, the high level of differentiation observed at Agouti stood as a significant outlier that was demonstrated to be incompatible with neutrality  is not sufficiently strong  if the beneficial allele is to reach fixation  and the majority of genetic variance can be explained by major effect mutations  localized within a 100 kb region of Agouti. Thus, the causal mutations indeed appear to be few in number, of large effect, and in close genomic proximity.Interpreting their results in light of this classical theory . Alternatively, selection could target common standing genetic variation that had previously segregated neutrally or was at mutation-selection balance, potentially resulting in multiple haplotype backgrounds at the site of selection  beneficial, crypsis-related variants often appear on single haplotypes, consistent with a hard sweep model; (2) these variants are generally not found to be segregating in the ancestral environment, as may be expected if they were present as high-frequency neutral alleles prior to the environmental shift; (3) in fragmented habitats, the genotypes underlying the shared phenotype are generally different, suggesting that these populations were not ‘seeded’ with a common, ancestral variant; and (4) the inferred ages of the beneficial mutations are generally younger than the geological age of the altered environment, indicating that the variant was not segregating at the time of the shift (and thus not available for selection to act upon immediately).It has traditionally been argued that dominant alleles are more likely to contribute to adaptation than recessives due to their relative probabilities of fixation Haldane . Since dThe differing dominance patterns observed in White Sands lizards presented Laurent et al.  with a uAgouti allele studied by Linnen et al.  derived amino acid replacements in both the White Sands lizards  is of great interest because of their varying evolutionary implications, including the degree of pleiotropic effects . Together, these findings provide direct evidence for divergent natural selection favoring locally adapted pigment phenotypes. Promisingly, with recent advances in DNA extraction and sequencing techniques, it may be increasingly possible to obtain time-sampled allele frequency data through the utilization of natural history collections, even in the absence of such large-scale field experiments  did not recapitulate these results  show elevated divergence between lizards on and off the lava flow and are associated with increased pigmentation in hatchling lizards. Since plasticity itself is thought to be the target of selection in Uta, to establish the genotype to phenotype link future studies will need to assess the joint contribution of these factors.Another potential explanation from the unexpected fence lizard results may involve phenotypic plasticity . By changing the distribution of phenotypes, plastic responses may alter the direction and intensity of selection, and understanding the role of phenotypic plasticity is thus necessary for completing the genotype to phenotype to fitness map. One of the few examples of plasticity preceding adaptation through crypsis in wild populations is the side-blotched lizard (Mc1r and/or Agouti, but not at the level of specific mutations. Evidence to date largely supports a model in which the variants underlying crypsis do not pre-date the shift in selective pressure, and thus the timing of phenotypic change is limited by the slow, subsequent input of the necessary genotypic changes.Within the context of Fisher’s  GeometriAgouti and Mc1r are highly important, but not necessarily the exclusive players (e.g., Corl et al. This research also suggests a number of fruitful future directions. With regards to empirical studies, the picture emerging is one in which