Caenorhabditis elegans population subject to three different environments: a control environment, an environment polluted with uranium, and a high salt concentration environment. We found a heritability decrease in the polluted environments for fecundity and early growth, two traits that were the most heritable in the control environment. The genetic structure of the traits was particularly affected in the uranium polluted environment, probably due to generally low heritability in this environment. This could prevent selection from acting on traits despite the strong selection pressures exerted on them. Moreover, phenotypic traits were more strongly affected in the salt than in the uranium environment and the heritabilities were also lower in the latter environment. Consequently the decrease in heritability was not proportional to the population fitness reduction in the polluted environments. Our results suggest that pollution can alter the genetic structure of a C. elegans population, and thus modify its evolutionary potential.When pollution occurs in an environment, populations present suffer numerous negative and immediate effects on their life history traits. Their evolutionary potential to live in a highly stressful environment will depend on the selection pressure strengths and on the genetic structure, the trait heritability, and the genetic correlations between them. If expression of this structure changes in a stressful environment, it becomes necessary to quantify these changes to estimate the evolutionary potential of the population in this new environment. We studied the genetic structure for survival, fecundity, and early and late growth in isogenic lines of a  G) ), and high salt concentration (addition of 308 mM NaCl). The wells were seeded with 75 µl of a 5:1 mixture of OP50 (same UV treatment as the six-well plates). In our experiment, the term “isogenic” does not correspond exactly to our lines, as there was heterozygosity in our population  with a very low variance parameter [V = diag(k) * Vp * 0.05], where Vp is the phenotypic variance and k is the dimension of V (i.e. number of traits). There was one exception for survival. In this case we fixed the environmental  variance to one. For the multivariate analyses with four different traits, we used the models to estimate different random and environmental variances and covariances between the pairs of traits. In the models that analysed the same trait across the three different environments, the traits were measured on different individuals, which fixed the environmental covariance to zero Vw), where Vb and Vw were respectively the between and within-line variance and n was the number of lines , environmental [VE = VP—VG] and genetic variances [VG = tVP], and the genetic covariance between traits using rG corresponds to genetic correlation between traits 1 and 2; and VG1 and VG2 are the genetic variance for trait 1 and 2, respectively  than in the salt environment  and three times higher than in the uranium environment  was opposite in sign to the phenotypic correlation, but non-significant  results did not only yield additive genetic variance, probably because there is a large number of epistatic interactions due to an experimental bottleneck that was linked to how the lines were created. This additional effect would be cryptic in a large panmictic population. Other quantitative genetic designs may not be subject to this drawback. For example, an ‘animal model’ [C. elegans because we cannot differentiate between individuals without separating them, as in our experiment. For the same reasons, and due to the difficulties in controlling all the offspring if they come from outcrossing or self-fertilization, it is very hard to create a half-sib/full-sib design experiment for this species. Besides, ILT has been shown to provide a better estimation of heritability than the parent–offspring regression method [The heritability  and theirs (12°C and 24°C), which affects average growth, reproduction [Survival heritability was absent or extremely low (thus difficult to detect) in the control environment, compared to the other traits. This may be due to its genetic regulation. Survival is regulated by a few genes that have large effects contrary to growth or reproductive traits, which are regulated by many genes that have small effects on heritability ,49 (in C elegans ). Herita [et al.  studied oduction , and heroduction .The decrease in early growth and fecundity heritabilities in both polluted environments was consistent with several previous laboratory or field studies, although some studies showed the opposite response . HerDaphnia magna at 20°C, but apparently this was mostly due to the decrease in dominance variance [et al. [Pirata piraticus, and they associated this to a decrease in additive genetic variance caused by the cadmium environment. They suggested that the expression of growth in that species involved different sets of genes in different environments. In a stressful environment, gene expression governing normal traits can be masked by other alleles involved in detoxification [C. elegans [Heritabilities were extremely low in the uranium environment. Several studies have suggested that phenotypic variation in stressful environments seems to be related to the type of new environment being experienced ,54. The variance . Nonethe [et al.  observedfication . Indeed, elegans ,58, whicWe detected cross-environment genetic correlations between the control and uranium environments for fecundity and for late growth. This indicated a partial overlap between the genes involved in the expression of these traits in both environments , despiteet al. [C. elegans had adapted to an environment polluted with a pesticide, there was no adaptation cost for reproduction when they were subsequently moved to the control environment or an environment polluted with a second pesticide. In contrast, Jansen et al. [D. magna populations that were exposed to a pesticide, and that it was conditional on the new environmental conditions. Adapted populations of D. magna suffered no costs in the control environment, but were more parasitized, which suggested that this population had a higher susceptibility to other stresses. In contrast, adaptation costs to cadmium were seen in the control environment, D. magna growth [D. melanogaster fecundity [There was a negative genetic correlation for early growth between the uranium and salt environments, which indicated that there was a cost to adapting to the presence of these pollutants. Lopes et al.  found thn et al.  suggestea growth , and D. ecundity . The advC. elegans . C. possible . Sperm ppossible . Investmpossible . Consequpossible , to crea elegans . However elegans .There were a number of genetic correlations for the populations raised in the salt environment and they covered the same combination of traits. When compared to the control, the changes in sign for correlations involving late growth in salt could be explained by the considerable developmental delay in this environment. Unlike the other environments, most individuals started laying eggs after 72 h, and even after 144 h. We could therefore say that early and late growth in the control and uranium environments corresponded to early growth in the salt environment and that the genetic structure between growth and fecundity was close to that of the control environment. In contrast, the genetic correlations in the control became zero in the uranium environment, especially the values for fecundity. Interestingly, in the uranium environment, the phenotypic correlations were similar to the control environment because there were significant environmental correlations see . PreviouD. melanogaster increased its tolerance to cadmium. They suggested that the links between genes involved in fecundity, survival, and development period in a control environment may be disrupted due to the addition of tolerance genes that are expressed in the presence of cadmium. It is also the case for the natural birch-feeding insect, Priophorus pallipes. The genetic correlation between body size and development time was positive when foliage quality was good and negative or low when the resource quality was close to zero [G matrix, e.g. the emergence of trade-offs [G matrix was already affected from the moment pollutants appeared in the environment. This is why it is important to investigate why some pollutants or specific genetic conditions promote G matrix stability or instability.Tolerance mechanisms that are governed by gene expression ensure the survival of individuals under highly stressful conditions, such as pollution, but they also affect the expression of genetic structure . Shirley to zero . Evoluti to zero . Hence, ade-offs ,74,75, tThe decrease in heritability was higher in the uranium environment than in the salt environment , althougC. elegans lines allowed us to analyse, in one generation, the effects of pollutants on the genetic structure of life history traits. Our findings confirm that the decrease in heritability in polluted environments was probably due to the expression of different sets of genes, such as tolerance genes—mtl , or hsp (heat shock protein) genes, that disrupt genetic structure, especially when C. elegans is subject to sudden uranium pollution. Moreover the decrease in heritability was not linearly correlated to fitness reduction in polluted environments. The extremely low heritability in the uranium environment could prevent selection, despite the strong selection pressures on the traits. Finally, when individuals had adapted to one polluted environment, there seems to be a genetic cost to living in other polluted environments. Pollution can break down the genetic structure of life history traits in a population of C. elegans and thus affect its evolutionary potential.The use of S1 FigEstimates are presented with their 95% Bayesian credibility intervals.(DOCX)Click here for additional data file.S2 FigVP) is split into environmental (VE) and genetic variances (VG). Estimates were obtained using multivariate models of the different traits when subject to the same environment.Estimates are presented with their 95% Bayesian credibility intervals. Phenotypic variance ((DOCX)Click here for additional data file.S3 FigAverage values (mean ± sd) are shown for each of the 14 isogenic lines.(DOCX)Click here for additional data file.S1 TableModels are presented for different traits within the same environment and for the same trait across different environments, with (Cov) or without (No Cov) the inclusion of genetic covariance between traits. When ΔDIC > 5, the model including genetic covariance is a better estimate of data.(DOC)Click here for additional data file.S2 TableCorrelations are presented with their 95% Bayesian credibility intervals (in brackets). Values in bold are significant estimates.(DOCX)Click here for additional data file.


Eucalyptus morrisbyi. We assessed arthropod and fungal communities on both juvenile and adult foliage. The community variation was related to previous levels of marsupial browsing, as well as the variation in the physicochemical properties of leaves using near-infrared spectroscopy. We found highly significant differences in community composition, abundance and diversity parameters between eucalypt source populations in the common garden, and these were comparable to differences between the distinctive juvenile and adult foliage. The physicochemical properties assessed accounted for a significant percentage of the community variation but did not explain fully the community differences between populations and foliage types. Similarly, while differences in population susceptibility to a major marsupial herbivore may result in diffuse genetic effects on the dependent community, this still did not account for the large genetic-based differences in dependent communities between populations. Our results emphasize the importance of maintaining the populations of this rare species as separate management units, as not only are the populations highly genetically structured, this variation may alter the trajectory of biotic colonization of conservation plantings.Plant genetic and ontogenetic variation can significantly impact dependent fungal and arthropod communities. However, little is known of the relative importance of these extended genetic and ontogenetic effects within a species. Using a common garden trial, we compared the dependent arthropod and fungal community on 222 progeny from two highly differentiated populations of the endangered heteroblastic tree species,  Plant genetic variation has an extended effect on dependent community and ecosystem processes in many differing systems Populus system, which established a framework for community and ecosystem genetics research using clonally replicated tree genotypes planted in common gardens The effects of genetic variation on foundation trees can occur at multiple genetic scales. Variation in extended genetic effects on dependent communities can occur across geographic races Eucalyptus, where significant differences in morphology and physicochemical properties occur between juvenile and adult foliage of many species In addition to genetic variation, developmental changes in plants are known to affect herbivory and physicochemical processes Eucalyptus dominates the landscape of Australia, comprising nearly 900 taxa (EUCLID 2006). A single tree can support a large abundance and diversity of organisms, influencing ecological processes Eucalyptus globulus, due to its commercial importance in the plantation industry. However, the genus Eucalyptus has many rare species, often occurring naturally as small isolated populations which can be highly genetically differentiated Eucalyptus morrisbyi, a rare eucalypt species restricted to just four small populations in Tasmania. This species is of particular relevance due to the ongoing activity in in situ and ex situ conservation The tree genus E. morrisbyi in relation to dependent arthropod and fungal communities. We assessed the two main populations of E. morrisbyi in a single common environment trial, addressing four main questions: First, does genetic and ontogenetic variation influence community composition? Second, what is the relative influence of these genetic and ontogenetic effects? Third, what are the key organisms responsible for community responses? Finally, what are the mechanisms driving differences in communities and what is the impact of previous marsupial browsing?In this study, we examined the genetic and ontogenetic variability of E. morrisbyi was undertaken under a Tasmanian Department of Primary Industries, Parks, Water and Environment permit (TLF14060). Permission to access the trial was obtained from Forestry Tasmania.The sampling performed in this study of the rare species Eucalyptus morrisbyi is endemic to the island of Tasmania, Australia. The species consists of four populations, two main populations and the other two with only a few individuals ex situ plantings at multiple sites capture a large array of the genetic diversity in both of the main populations. These plantings have recently revealed genetic-based variation in Trichosurus vulpecula (brushtail possum) browsing with the CH population being heavily browsed, causing poor growth and delayed ontogenetic transition to the adult foliage E. morrisbyi, Calvert's Hill and Risdon Hill. It was established at Geeveston, Tasmania, Australia  in October 1999 from seedlings grown from open-pollinated seed from maternal trees in the natural populations. Seed from each maternal tree is a family and 30 families from each of the CH and RH populations were planted in a randomized block design The common garden field trial used for the study consisted of families from the two main native populations of nd and 23rd of 2007. Samples for community assessment were collected as single branches cut from the mid canopy of the northeast aspect of individual trees. Leaves were removed from the branches in the laboratory, total dry weight obtained, and number of leaves estimated. Following previous approaches Trees were sampled on May 22−1 resolution. Five leaves per sample were scanned four times on either side of the midrib toward the tip and base of each leaf, resulting in forty scans per sample. Recorded wavelengths for each sample are the means of all scans from the five leaves . The 220 wavelengths obtained from the NIR analysis were reduced to 20 principal components, which were used to summarize the variation in physicochemical properties Samples for assessment of the physicochemical properties of leaves were collected in the same manner as the community samples, with single branches cut from the mid canopy of the northeast aspect of individual trees. Ten to thirty fully expanded leaves from the sampling years growth were collected from each branch, freeze-dried and analyzed for their physicochemical differences using near-infrared spectroscopy (NIR). Freeze-dried leaves from each sample were scanned using a Bruker MPA FT-NIR spectrometer with a fiber-optic probe. Spectral wavelengths for each sample were obtained from the 780–2500 nm range at a 4 cmT. vulpecula browsing susceptibility of E. morrisbyi trees assessed in the same experimental common environment trial used in this study. Variation in T. vulpecula damage was linked to differences in key chemical and physical foliar properties. Due to the degree of impact that this marsupial herbivore has on the trees, it is possible they influence the dependent arthropod and fungal community. Hence, in this paper we examine the relative influence that previous browsing by T. vulpecula has had on the dependent community. Assessment of T. vulpecula browsing on each tree across the trial was performed in 2005 Mann et. al. (2012) showed clear genetic-based differences in The influence of genetic and ontogenetic variation on dependent arthropod and fungal community composition were tested separately in Primer  using two models  calculated sequentially (Type I SS). Spatial variation within the trial (replicate) was accounted for first in all analyses in order to remove the effect before the main effects of interest using models III and IV . Similar and VII .T. vulpecula browsing (model III vs. V).The proportion of variation influencing dependent community composition was calculated using components of variation obtained from the PERMANOVA analysis for each effect and covariate, following Anderson, et al. (2008). Total variance in each model was calculated by adding these components of variation and the residual variance, with negative components treated as zero BiodiversityR in R. The parameters calculated included richness, abundance, Shannon diversity index and Pielou's evenness. Community parameters were analysed for genetic variation using a mixed model (model I) with the significance of random effects tested with the one-tailed likelihood ratio test and the fixed population effect with a Wald-F test. A paired sample t-test was used to analyse variation in community parameters between foliage types. Significance values for population effects and foliage types effects were adjusted to p = 0.0125 for community parameters using the Bonferroni method to correct for false discovery rates due to multiple testing asreml and t.test in R 2.15.3 Community parameters were calculated for each sample from the weighted symptom scores using kruskal.test and t.test in R 2.15.3.Individual symptoms were analyzed using a nonparametric Kruskal-Wallis test for population differences and a paired sample t-test for foliage type differences on the standardized abundance scores. Only symptoms found on at least ten percent of all trees from their respective data sets were subject to univariate analyses. Significance values were corrected using Bonferroni adjustment of p-values based on the number of organisms analyzed from each data set to account for multiple testing. Symptoms found significant in the univariate analyses were then used to determine which symptoms were influencing the variation in community composition between populations and foliage types. Univariate analyses of symptoms were undertaken using 2 or t-test values, from highest to lowest . Following the principles of stepwise multiple regression Significant symptoms were ranked based on their univariate Kruskal Χ1,221 = 10.9, p<0.001), however the family within population effect was not significant . This significant variation is also shown in the ordination space derived from the CAP analysis with the two populations clearly separated , however, components of variation obtained from the PERMANOVA analysis showed that its influence was small  when compared with the population (genetic) effect (9.5%). To test if the difference between populations was due to an effect of the presence of adult foliage on the RH population, we tested for a difference in community composition between RH trees with only juvenile foliage and those with both juvenile and adult foliage. This difference was not significant , indicating the population differences were not due to the presence of adult foliage.A total of 60 symptoms of arthropod and fungal species were identified on the sampled juvenile leaves between the two populations in the common garden trial. We found highly significant differences in arthropod and fungal communities on the juvenile leaves from RH and CH populations . On juvenile leaves, 5.7% of the variation in dependent community composition was explained by physicochemical properties of leaves, population 7.8% and spatial variation (ie. replicate) within the trial 1.3%. Trichosurus vulpecula browsing also significantly influenced variation in dependent community composition  when accounted for first in the analyses. By comparing the reduction in the percent variation attributed to physicochemical properties of leaves and population differences before and after including T. vulpecula browsing as a covariate, it was shown that T. vulpecula browsing removed 44% of the variation in physicochemical properties  and 9.5% of the differences in community between populations. The browsing effect was still significant  when placed after the principal components derived from the NIR spectra of juvenile foliage, indicating physicochemical properties do not account fully for the effect T. vulpecula browsing on community differences between populations. However, significance was lost  when browsing was accounted for last in the analysis, indicating that the community effect of T. vulpecula browsing can be explained by a combination of population and physicochemical differences. The genetic effect (population) remained highly significant in each model. Overall, T. vulpecula browsing explained 2.6% of the variation in dependent community composition, physicochemical properties of leaves 2.8%, population 7.1% and spatial variation within the trial 1.3%  and variation in possum browsing. We tested whether population alone accounted for variation in the community after accounting for these two factors. By comparing the reduction in the percent variation attributed to population differences before and after including the NIR spectra principal components as covariates, we showed physicochemical properties of leaves accounted for 18% of the differences in community composition between populations. However, there were still significant differences in dependent community composition between populations  were found to be significantly different between populations based on juvenile leaf samples after a Bonferroni adjustment to p = 0.00125 . On averTeratosphaeria spp. and adult leaf beetle Paropsisterna spp., which both had a greater abundance on the CH population . This difference is clearly seen in the ordination space derived from the CAP analysis . However, the variance components obtained from the PERMANOVA analysis showed that this influence was small  when compared with the foliage type effect (13%).A total of 60 symptoms of dependent arthropod and fungal species were identified on the RH population samples having both juvenile and adult foliage. There were highly significant differences in dependent communities on juvenile and adult leaves of the RH population . Over all samples, the total influence of physicochemical properties of leaves explained 7.5%, ontogenetic variation 7.9% and spatial variation (ie. replicate) in the trial an insignificant 0.9% of the variation in dependent community composition  and possum browsing (genetic only). The variation explained by genetic effects in this study was solely driven by differences between populations rather than families. Only four plant systems have quantified the size of genetic-based variation on dependent communities Populus–32–93%; Oenothera–30%; Quercus–7–26%). The other system studied the genetic variation found in a natural forest patch and showed less genetic influence (Brosimum–3.7–4.8%). The genetic effects found in our study were smaller than those found in other systems, but were still statistically significant. Our low genetic effect compared to other studies may be in part due to the scoring techniques as the other studies have assessed live organisms as opposed to the symptom-based approach used in this study. As mentioned in the Our study shows that both genetic (9.5%) and ontogenetic (13.0%) variation in Brosimum system in unexpected ways, despite Brosmium being evergreen trees located in warmer tropical climates. The high diversity of trees found in tropical regions Eucalyptus species co-occurring in sclerophyll forests Brosimum and current study, respectively. A study of insect herbivores in a tropical lowland forest in New Guinea has shown that host specificity decreases with increasing number of tree species in a forest Eucalyptus system, the lower relative influence of genetic variation found in this study may be reflecting a greater frequency of generalist herbivores compared to the other systems. This concept may be further supported by the study species being rare, with common garden trials outside of their natural populations. This distance from natural stands would reduce the occurrence of possible specialist herbivores associated with the species.There are many differences between studies quantifying host genetic effects on dependent communities. Nevertheless, the low effect values observed in our system may relate to the Teratosphaeria spp. and the leaf beetle Paropsisterna spp., were driving the differences between populations. Genetic variation in the susceptibility to both Teratosphaeria spp.Paropsisterna spp.Eucalyptus systems, with the presence of these organisms having a deleterious effect on plant growth With regard to the organisms in the community, we found only two, the fungal pathogen T. vulpecula browsing accounted for 10% of the genetic effect. This could be due to diffuse interactions T. vulpecula browsing. This interaction may be due to direct or indirect effects. Direct effects include direct ecological interference such as T. vulpecula eating preferred foliage of certain organisms feeding on the plants at the same time (e.g. competition). Indirect effects could include: (1) browsing causing the retention of juvenile foliage, influencing the abundance and richness of organisms; (2) induced changes in plant chemistry and/or morphology altering the habitat for arthropod and fungal colonization. To date, however, few studies have demonstrated induction of chemical defenses in eucalypts Investigation of the mechanisms driving the variation between communities found that previous T. vulpecula browsing and physicochemical traits did explain some of the population effect, there was still a clear genetic effect (7.1%) influencing community variation. This genetic variation may be affecting the community through: (1) traits undetected in NIR spectra; (2) variation in tree architecture We found the variation in physicochemical traits accounted for 15% of the genetic and 37% of the ontogenetic effects explaining community differences. Numerous studies have shown the importance of variation in traits, such as foliar chemistry, as mechanisms influencing herbivory The influence of genetic-based effects on community composition in this study shows the importance of maintaining the two populations of this species as distinct management units. For example, the choice of just one of these populations for conservation would lead to a different biotic community trajectory compared to the choice of the other population. Such different trajectories would depend on the stability of genetic-based differences across life history stages Figure S1Photographs of select causal organism symptoms on E. morrisbyi foliage. (a) Acrocercops laciniella, (b) Aulographina eucalypti, (c) Diphucephala colaspidoides, (d) Eurymeloides bicincta (eggs), (e) Gonipterus scuttelatus (larvae), (f) Paropsisterna spp., (g) Paropsisterna agricola (larvae), (h) Sonderhenia eucalyptorum, (i) Teratosphaera spp., and (j) Uraba lugens. Red circles highlight damage types.(PDF)Click here for additional data file.Table S1Organism identifications and symptom descriptions.(DOCX)Click here for additional data file.


Local governments play an increasingly important role in improving residents’ access to healthful food and beverages to reduce obesity and chronic disease. Cities can use multiple strategies to improve community health through, for example, land use and zoning policies, city contracting and procurement practices, sponsorship of farmers markets and community gardens, and vending and concession practices in parks and recreation facilities. With 41 cities in the Hennepin County Human Services and Public Health Department jurisdiction, the county undertook to measure the extent to which cities were engaged in making policy, systems, and environmental (PSE) changes to increase residents’ access to healthful food. The results revealed that some cities, particularly those with higher resident demand for healthful food, are making nationally recommended PSE changes, such as sponsoring farmers markets and community gardens. Cities have moved more slowly to make changes in areas with perceived negative cost consequences or lesser public demand, such as parks and recreation vending and concessions. This article describes the assessment process, survey tools, findings, and implications for other health departments seeking to undertake a similar assessment. The Centers for Disease Control and Prevention (CDC) and other major public health stakeholders have identified local governments as key players in the effort to create healthier communities, increase access to healthy foods and beverages, and reduce rates of obesity and chronic disease. CDC notes that many factors that “influence our health are created, managed, and maintained by local governments” . CDC andThe Hennepin County public health jurisdiction includes 41 cities and excludes 4 cities in the county — Minneapolis, Bloomington, Edina, and Richfield — that have their own boards of health. Our healthy food policy assessment focused on the largest 20 cities in the Hennepin County public health jurisdiction, excluding the 4 cities noted, ranging in population from 2,400 to 76,000 people. The combined population for the 20 cities totaled 569,254.Recommended Strategies and Measurements to Prevent Obesity in the United States , and parks and recreation food and beverage concessions and vending. We also designed an open-ended section where cities could add other PSE changes they had instituted such as new water spigots in City Hall, passage of a healthy community resolution, and backyard livestock zoning changes. We did not include questions in our interviews about nationally recommended PSE changes related to healthy corner stores and supermarket availability because Hennepin County had recently collected this information through a different survey effort. Nor did we cover breastfeeding policy because state law already covers breastfeeding in work-related settings.Cities were selective in their implementation of the national PSE recommendations. Although 16 of the 20 cities we assessed were at least somewhat interested in improving access to healthful foods, they varied widely in their use of local authority to make changes. Among the PSE strategies , cities Overall, it seemed that the cities that created greater access to healthful foods and beverages — particularly with community gardens and farmers markets — were those that experienced the greatest demand from residents. It also appeared that the presence of wellness committees in city halls might have supported progress toward greater access to healthful foods and beverages.Cities predominantly chose sponsorship of community gardens (12 cities) and farmers markets (11 cities) to improve healthful food access for residents. City officials noted that public demand for community gardens (9 cities) and farmers markets (6 cities) was a key motivating factor. At least 2 officials noted that their elected officials were especially enthusiastic about these approaches because gardens and markets were popular community gathering places. Three officials also observed that recent immigrant populations, particularly Southeast Asians and East Africans, were interested in owning community garden plots. In 4 instances, cities also chose to sponsor community gardens to better serve residents in multiunit rental housing who would not otherwise have the opportunity to grow their own food. At least 3 cities noted that the cost of bringing in and maintaining a water supply for the gardens was a challenge. None of the cities were equipped to accept Electronic Benefit Transfer cards from the Supplemental Nutrition Assistance Program, but 2 expressed an interest in doing so.Two cities had changed their vending machine contracts to secure a “healthy food and beverage” machine in their city hall; however, none of the cities had implemented purchasing or contracting policies for foods and beverages. Ten cities had employee wellness committees that had been actively involved in health-related activities. Seven of these were informally moving toward offering more healthful foods and beverages at meetings. However, no city had implemented a policy of offering healthful foods at meetings. In general, officials seemed reluctant to set a formal food policy and were more inclined to influence the environment by promoting healthful options rather than regulating change.Hennepin County cities have invested heavily in building a comprehensive parks and recreation infrastructure with an impressive array of community centers, indoor ice arenas, aquatic centers, baseball fields, and other athletic facilities. Parks and recreation systems often operate concession stands or vending machines in these complexes. To get a sense of the scope and potential impact, we asked parks and recreation directors to calculate the number of patrons they serve through their city athletic facilities with concession stands. Sixteen city parks and recreation systems that operate or lease concession stands or cafes had a combined 4 million patron visits annually.Twelve city parks and recreation systems sold foods and beverages through vending machines. Only 1 city had implemented a formal vending nutrition standard for foods and beverages based on the National Automatic Merchandising Association “Fit Pick” nutrition standard . This ciOur interviews with parks and recreation officials gave us insight into the factors that affected their decision making. Although parks and recreation officials are largely supportive of the idea of improving access to healthful food, they also identified numerous barriers to implementing formal nutrition standards that apply to all foods and beverages.Principal barriers identified by parks and recreation and other officials included:Fear of losing profits and revenue. Parks and recreation facilities are typically run as enterprise funds where concessions and vending fund core operational costs. Enterprise-funded centers must generate profits or make cuts in their operations and programming. At least 3 cities noted that the wholesale costs for certain healthful options were sometimes more expensive or that fresh foods have a higher likelihood of perishability, which is a financial liability. One city closed its park concessions enterprise operation because of a lack of profitability.Lack of control over concessions. Of the 16 cities with concessions, 7 have yielded control of at least 1 of the concession stands to a sports association. For many hockey and baseball teams, this is an important source of revenue.Lack of control over vending. In 11 of the 12 cities with parks vending, the vending company controlled the selection, display, and price of food and beverage options. In the 1 exception, the city buys its own products independently and does not contract with an outside vendor. Vending contracts are typically locked in for multiple years, especially beverage contracts with major national beverage companies.Inconsistency of demand. Public demand for more healthful foods and beverages is increasing, albeit gradually. Although the public is asking for healthier options, at least 6 parks and recreation directors pointed out that the public still expects less healthful options on the menu. One official noted that when families come to the swim park for a special occasion, they want to treat their kids with an ice cream or candy.Reluctance toward formal policy implementation. City officials are reticent to implement formal policies that restrict options and prefer the more flexible approach of expanding healthful food and beverage options. In 5 interviews, a city official volunteered that while the city is moving toward expanding healthier food and beverage options in City Hall or in the parks and recreation system, they did not want to formalize the approach through a written policy.Public health departments interested in conducting a similar healthful food and beverage PSE assessment may want to consider the following:If possible, embed the survey tool of PSE options in the interview process instead of conducting a written survey as a separate step. By conducting interviews, we achieved a 100% response rate from the 20 cities and obtained significantly more in-depth information than a survey alone would have yielded.Try to identify the most knowledgeable city official for crosscutting city initiatives. We most often found city planning and economic development officials to be helpful.Conduct interviews with parks and recreation officials separately from interviews with other city officials. Parks and recreation interviews were more technical; they included detailed information on food and beverage purchasing practices and enterprise operations related to vending and concession practices. This information was valuable given the significant number of patrons using athletic facilities and the important potential role they play in improving access to healthful food for residents, especially youth.Structure the interview protocol to include information on changes in practices, especially if you anticipate that few cities in your jurisdiction have implemented policy change.Share your assessment report with cities after the assessment has been completed. City officials are sometimes reluctant to be change leaders. Many cities asked us for the report to learn more about neighboring city initiatives and progress.The Hennepin County Human Services and Public Health Department is using the assessment results to identify cities interested in improving access to healthful food and as baseline data to measure future change. The results will also help the county address the barriers revealed through the assessment and develop the technical assistance necessary to institute improvements countywide.This research has several limitations. We did not establish psychometric properties of our data collection instruments. Our study design does not allow us to determine with certainty which factors most influenced greater access to healthful foods and beverages. Finally, there is limited generalizability of the findings to other locations.Conducting a municipal PSE assessment is a valuable first step for local public health departments seeking to improve residents’ access to healthful foods and beverages. The assessment can help public health departments understand not only where cities are on the continuum of possible PSE change but also identify barriers to change. The assessment will also enable public health departments to identify crosscutting themes and tailor technical assistance to meet the needs of cities interested in further improving resident access to healthful food.


Social interactions between individuals living in a group can have both positive and negative effects on welfare, productivity, and health of these individuals. Negative effects of social interactions in livestock are easier to observe than positive effects. For example, laying hens may develop feather pecking, which can cause mortality due to cannibalism, and pigs may develop tail biting or excessive aggression. Several studies have shown that social interactions affect the genetic variation in a trait. Genetic improvement of socially-affected traits, however, has proven to be difficult until relatively recently. The use of classical selection methods, like individual selection, may result in selection responses opposite to expected, because these methods neglect the effect of an individual on its group mates . It has become clear that improvement of socially-affected traits requires selection methods that take into account not only the direct effect of an individual on its own phenotype but also the social genetic effects, also known as indirect genetic effects, of an individual on the phenotypes of its group mates. Here, we review the theoretical and empirical work on social genetic effects, with a focus on livestock. First, we present the theory of social genetic effects. Subsequently, we evaluate the evidence for social genetic effects in livestock and other species, by reviewing estimates of genetic parameters for direct and social genetic effects. Then we describe the results of different selection experiments. Finally, we discuss issues concerning the implementation of social genetic effects in livestock breeding programs. This review demonstrates that selection for socially-affected traits, using methods that target both the direct and social genetic effects, is a promising, but sometimes difficult to use in practice, tool to simultaneously improve production and welfare in livestock. Social interactions among individuals can have large effects on their phenotypes, both in domestic and natural populations. Such interactions affect the outcome of evolutionary processes and of domestic breeding programs ]. Such methods allow us to estimate both the breeding value for the direct effect and the breeding value for the social effect, without the need for behavioral observations. For mortality due to cannibalism in laying hens, for example, the direct effect corresponds to the victim effect, whereas the social effect corresponds to the pecker effect . With social interactions, the model needs to be extended to incorporate social effects. When social interactions occur within a group consisting of n individuals, the phenotype of individual i may be modeled as the sum of its own direct effect, and the sum of the social effects of each of its n − 1 group mates. Both the direct and social effect can be partitioned into an additive genetic and a non-heritable  component  of group member j, and ES,j the corresponding non-heritable social effect. This model applies to each of the n group members. Note that DBV and SBV are distinct breeding values. For example, when the trait of interest is survival, the DBV refers to the heritable effect of an individual on its own survival, whereas the SBV refers to the heritable effect of an individual on survival of its group mates, which may, for example, relate to aggression. So the DBV is comparable to the “classical” breeding value , the TBV in Equation 2 is entirely a heritable property of individual s Bijma, . The tots Bijma, ,(3)σTBVAnalogous to ordinary heritability, the total heritable variance can be expressed relative to the phenotypic variance  and ρTBV is the accuracy which is the correlation between the selection criterion and the total breeding value in the selection candidates , accuracy depends only on the second term in the numerator, and can thus be negative when direct and social genetic effects are negatively correlated , accuracy is always positive so that response is in the same direction as selection. However, usually a limited relatedness suffices to guarantee positive accuracy   and relatedness between group mates (r > 0) create a positive accuracy, so that response to selection is positive. Without multilevel selection (g = 0), Equation 8 reduces to Equation 6.With multilevel selection, selection is based on a linear combination of the phenotypes of the individual and the phenotype of its group mates, iSC = Prel,i . Ellen et al.  to estimate breeding values is to be preferred, because it utilizes information of all relatives and corrects for systematic environmental effects, such as herd-year-season effects . In this case, breeding values are predicted using the classical mixed animal modely is the vector of observations, b is a vector of fixed effects with incidence matrix X, a is a vector of breeding values with incidence matrix Z linking phenotypes of individuals to their own breeding value, and e is a vector of residuals. Subsequently, animals are selected on their estimated breeding value, iSC = i. When group members are unrelated, the approximate accuracy of the classical BLUP approach equals σDSA < 0], just as with individual selection (Equation 6). When groups are composed of families, however, the EBV resulting from Equation 10 is an estimate of TBV of the individuals; not of their DBV ρTBVV Bijma, . Hence, Including social genetic effects. When genetic parameters are known for both direct and social genetic effects, breeding values can be estimated using a direct-indirect effects model S,i, which is the selection criterion; iSC = TBV,i.When genetic parameters are known, breeding values can be estimated from the mixed model in Equation 12 irrespective of relatedness among group members. Muir et al. , 2013, hr = 0), half sibs (r = 0.25), or full sibs (r = 0.5). For selection based on relatives, the relationship between selection candidates and relatives kept in groups was either half sibs (relr = 0.25) or full sibs (relr = 0.5). Table To illustrate the results of the different selection methods, we calculated predicted response to selection for survival time in laying hens showing cannibalism. For this trait, accurate genetic parameters have been published, both for purebred  from a classical model, estimated total heritable variance relative to the phenotypic variance (T2) from a direct-indirect effects model, and the estimated genetic correlations between direct breeding values and social breeding values (Ar).Several studies have estimated genetic parameters for socially-affected traits. Table T2 > h2). In two populations of trees, however, a strongly negative direct-social genetic correlation was found, causing total heritable variance to be smaller than additive genetic variance . For example, for bite mark score in mink Ar was strongly positive, meaning that an individual that bites more  also attract more bites (direct effect) and vice versa , together with a negative direct-social genetic correlation.Evidence of social genetic effects may also be obtained from selection experiments aiming to utilize such effects to generate response to selection. One of the first empirical studies used group selection for increased or decreased population size in randomly formed groups of flour beetles Wade, , 1977. IMuir et al.  groups, resulting in an increase in social interactions between individuals. Moreover, treatments to limit the consequences of adverse social interactions, such as beak trimming in poultry and tail docking in pigs, will probably be banned in the future (at least in EU countries), so that the negative effects of social interactions will likely increase unless action is taken to avoid that. Actions are needed to prevent or diminish the negative effects of social interactions. In this review, we have shown that many traits show genetic variation in social effects. Moreover, we have reviewed selection methods for socially-affected traits, showing that methods exist that utilize the social genetic variation for genetic improvement. Thus, the genetic variation and selection tools required for genetic improvement of socially-affected traits are available, indicating that genetic solutions are feasible in principle. Nevertheless, successful application in commercial breeding programs faces a number of challenges, some of which we review below.For commercial livestock breeding, it is most important to estimate accurate breeding values. When the objective is to separately estimate direct and social breeding values, rather than only the total breeding value, genetic parameters for direct and social effects are required. Genetic parameters for direct and social effects cannot be estimated when group members are equally related . The optimal design for estimating direct and social genetic parameters has groups composed of two families. Moreover, the number of groups, rather than the number of individuals, is the key parameter determining accuracy of the estimated variance components. Bijma  showed tThe optimal group-composition for estimating direct and social genetic parameters differs from the optimal group-composition for estimating the TBV and maximizing response to selection. Accuracies of estimated TBVs are maximized when using groups composed of families  possible to estimate genetic parameters for direct and social effects . This occurs because direct and social genetic parameters are not statistically identifiable when fitting a fixed effect for the farm . Though direct and social genetic parameters cannot be estimated from this design, the design is ideal for the estimation of TBVs and probably also for the estimation of total genetic variance  close to one. When pcr is small to moderate, crossbred information is needed. So far, however, pcr for socially-affected traits is unknown. Results in laying hens suggest that socially-affected traits in crossbreds may differ considerably from those in purebreds. Peeters et al.  interaction may occur. Whether GxE-interactions are greater for socially-affected traits than for other traits is unknown at present. Cannibalism in laying hens is very sensitive to environmental conditions. Ellen et al. (in preparation), for example, found a 20% difference in survival when birds of the same generation were kept at two different locations. Whether such large differences imply substantial GxE-interaction is unclear. GxE-interaction due to differences between purebred and crossbred environments would reduce The expression of social interactions might also depend on early life experiences. In laying hens, incubation and rearing conditions substantially affect feather pecking and cannibalism  individuals, also known as kin recognition  because in small groups it is a reasonable assumption that all group members interact with each other; and (2) because accurate estimation of social genetic parameters requires data on many groups Bijma, . For estvs. large groups is reasonably close to one. Whether that is the case is an empirical question. In laying hens, for example, feather pecking and mortality due to cannibalism are more problematic in larger groups  is a function of its own allele frequency for susceptibility and infectivity and of the population average susceptibility and infectivity. Again, relatedness between interacting individuals is an important component, resulting in increased response in R0. This work, therefore, suggests that breeders can considerably increase response to selection in infectious disease traits by collecting disease data from family groups. This is the case even when there is no genetic variation in infectivity, since also genetic variation in susceptibility generates social genetic effects  and by the infectivity of its social partners (social effect; Lipschutz-Powell et al., Social interactions are important for livestock genetic improvement. Applying a selection method that targets both direct and social effects will be a key factor to improve welfare and productivity of livestock simultaneously. There is growing evidence that methods are effective for animals kept in small groups. Challenges are in the application in commercial livestock breeding programs, for example in populations consisting of large groups.Esther D. Ellen wrote and prepared the manuscript for submission. T. Bas Rodenburg, J. Elizabeth Bolhuis, Egbert F. Knol, and Gerard A. A. Albers were involved in the discussion of the manuscript and reviewed the manuscript. T. Bas Rodenburg, J. Elizabeth Bolhuis, Irene Camerlink, Naomi Duijvesteijn, William M. Muir, and Piter Bijma wrote and reviewed the manuscript. Katrijn Peeters, Inonge Reimert, Ewa Sell-Kubiak, Johan A. M. van Arendonk, and Jeroen Visscher reviewed the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Bubo bubo) in the Iberian Peninsula. During the last century, the species was the object of extermination programs, suffering direct persecution by hunters until the 70’s. Moreover, during the last decades the eagle owl was severely impacted by increased mortality due to electrocution and the decline of its main prey species, the European rabbit (Oryctolagus cuniculus). In recent times, the decrease of direct persecution and the implementation of some conservation schemes have allowed the species’ demographic recovery. Yet, it remains unknown to which extent the past population decline and the later expansion have influenced the current species’ pattern of genetic diversity. We used eight microsatellite markers to genotype 235 eagle owls from ten Spanish subpopulations and analyse the presence of genetic signatures attributable to the recent population fluctuations experienced by the species. We found moderate levels of differentiation among the studied subpopulations and Bayesian analyses revealed the existence of three genetic clusters that grouped subpopulations from central, south-western and south-eastern Spain. The observed genetic structure could have resulted from recent human-induced population fragmentation, a patchy distribution of prey populations and/or the philopatric behaviour and habitat selection of the species. We detected an old population bottleneck, which occurred approximately 10,000 years ago, and significant signatures of recent demographic expansions. However, we did not find genetic signatures for a recent bottleneck, which may indicate that population declines were not severe enough to leave detectable signals on the species genetic makeup or that such signals have been eroded by the rapid demographic recovery experienced by the species in recent years.The study of the demographic history of species can help to understand the negative impact of recent population declines in organisms of conservation concern. Here, we use neutral molecular markers to explore the genetic consequences of the recent population decline and posterior recovery of the Eurasian eagle owl ( Animal populations may be reduced and isolated by both natural and anthropogenic factors. Habitat fragmentation by means of the transformation of natural and semi-natural habitat may lead to a patchy distribution of populations and communities and it is considered as a major paradigm in conservation biology . FragmenBubo bubo) in Europe experienced such dynamics in their recent history. This owl is the largest strigiform in the world and it is widely distributed in the Palearctic    and the K method , as implarvester . The secDistruct .GenAlEx to calculate pairwise FST and F’ST values between subpopulations. We used Mantel tests to analyse the relationship between the linearized estimates of pairwise FST and F’ST and the logarithm of geographical distances between pairs of populations [Ne) of groups using the LD method implemented in Neestimator 1.3 [Ne estimates assuming monogamy, excluding all allele frequencies lower than 0.05, and selecting a parametric procedure to construct 95% confidence intervals.In order to further explore the spatial pattern of genetic differentiation, we used ulations . Moreoveator 1.3 . We calcBottleneck 1.2.02 [ps), 22% multi-step mutations (pg) and a variance of 3.1 among multiple steps, as recommended for microsatellite data [The genetic signatures of the recent population bottlenecks and expansions of the Eurasian eagle owl in the Iberian Peninsula were explored using the software k 1.2.02 . We testk 1.2.02 . We assuite data . The sigk) over the range of allele sizes (r) since it is expected that during a bottleneck the random loss of alleles will result in a reduced M-ratio (M = k/r). To determine the significance of the reduction of M, the observed value is compared to a distribution of values obtained from simulated populations considering a hypothetical pre-bottleneck Ne, the mutation rates of loci (μ), the proportion of multi-step mutations (pg) and the mean size of multi-repeat mutations (Δg). Critical_M software was used to calculate critical values (Mc) set at the lower 5% tail of the distribution below which it can be assumed that the population has experienced a significant reduction in size [Neμ), considering a mutation rate (μ) of 5x10-4  and dif species .Msvar 1.3 [N1) started to decrease (or increase) linearly or exponentially some time ago (T) towards the current population size (N0). Based on this assumption and using the MCMC approach the method not only allows the estimation of N0 and N1, but also T. Mutation rates (θ = 2N0μ) were assumed under the SMM model and, as for the rest of the parameters, we considered wide uninformative priors under a lognormal distribution. The generation time of Eurasian eagle owl was set at 4 years, the average age of the reproductive population . Because we tested both recent or ancient expansion and bottleneck processes, we ran the program five independent times under the exponential growth model, using different hyperprior means for T and N0, to represent stable, decreasing or increasing demographic histories at different times , the median (50%) and upper quantile (90%) of the posterior distributions.Finally, we used svar 1.3 , 49 to int times . The totMicro-Checker indicated that null alleles may be present by detecting a significant heterozygote deficiency at five out of the eight employed markers, possibly as a consequence of cryptic population structure   . HoweverStructure analyses without considering prior population information indicated that the number of genetic clusters best fitting the data set was K = 1 (i.e. LnPr(X|K) reached a maximum value for K = 1; K = 3 was the most supported cluster solution , but in this case the distant Sierra de Huelva and Madrid SE showed the highest differentiation (0.387). Moreover, both statistics showed a significant correlation with the geographical distance between sites .For the eight populations with samples sizes higher than six individuals, all pairwise FCT = 0.02; FSC = 0.05; FIS = 0.17; FIT = 0.22; all p = 0.001). Considering these groups in a one-way ANOVA, we did not find significant differences in descriptive statistics of genetic diversity among them .Despite the low levels of genetic differentiation found among sampling sites, AMOVA analyses statistically supported the reported substructure and maximized the differentiation among the inferred clusters when Cádiz was assigned to the south-western cluster, revealing that 1.84% of the global variation is found among clusters, 4.39% among sampling sites within these three groups, 16.04% among individuals within sites and the remaining 77.73% corresponds to individual variation  F1,5 = 0.6; p = 0.58; (NE) F1,5 = 0.11; p = 0.9; (HO) F1,5 = 0.44; p = 0.67; (uHE) F1,5 = 1.15; p = 0.39; (FIS) F1,5 = 0.36; p = 0.72N, number of genotyped individuals; Bottleneck tests yielded similar results when loci that showed a significant homozygote excess were excluded from the analyses . The effective population N1 decreased over 10 times from a larger ancestral effective size estimated around 25,119 individuals , to the current effective size N0 of 3,162 . The obtained posterior densities of N0, N1 and T slightly varied over the different runs and the different priors used, depicting in all cases a population decline of one order of magnitude in the effective population size dated thousands of years ago  of 5x10-4; M, calculated as M = k/r, where k is the number of alleles and r is the range of allele sizes; MC, critical value set at the lower 5% tail of the distribution below which it can be assumed that the population has experienced a significant reduction in size.We did not find significant evidences of recent bottlenecks at any of the inferred groups using Bayesian clustering methods and AMOVAs analyses Aquila adalberti) [Aquila fasciata) [In this study we found some genetic signatures which could be in part attributable to the recent population dynamics experienced by eagle owls in the Iberian Peninsula, but also probably related with the species’ past demographic history and traits. Concretely, we found a weak but consistent pattern of genetic structure revealed by both Bayesian clustering and AMOVAs analyses, and a significant correlation between genetic and geographical distances. In the Iberian Peninsula, spatial genetic patterns like this have been reported for other long-lived raptor species that also experienced recent population declines as the Spanish imperial eagle  , 51 and asciata) . Such spasciata) , 54. Howasciata) . Insteadasciata) , 57.Bottleneck analyses detected population expansions in some of the inferred groups, a pattern that was even consistent when excluding loci that deviate from HWE. These findings were also supported by the moderated levels of genetic diversity and the large effective population sizes estimated for the studied populations. However, it remains unclear whether subsequent demographic changes can erase the genetic signatures of recent demographic bottlenecks, which is likely to depend among other things on the population growth rate and the impact of immigration and admixture with individuals from other populations during the expansion phase [Bottleneck analyses. SMM showed a higher power, despite for most microsatellite loci TPM is thought to be more adequate [Demographic analyses failed to detect genetic signatures of recent bottlenecks in the inferred groups, which may indicate that past population declines were not severe enough to leave detectable signals on the species genetic makeup. Thus, a possibility is that the decline of eagle owl populations in the recent past has not reduced effective population sizes below the threshold that is necessary to produce genetic signals associated with such demographic events. Alternatively, the recovery and range expansion of the species over the last 40 years could have eroded some of the genetic signatures associated with local population declines. Unlike most large raptors such as eagles or vultures, the eagle owl has high reproductive rates and this may have favored a rapid demographic recovery . Furtheron phase , 66. Stuadequate .Msvar analyses found signatures of an ancient population collapse that started after the end of the last glacial period. Both this and previous studies have generally found that the Storz and Beaumont method [Bottleneck analyses [Ailuropoda melanoleuca) [Martes pennanti) [Ulmus laevis) [At the whole population level, t method  shows a analyses . Accordinoleuca) , fishersennanti)  or Europ laevis)  and Iber laevis) . Althoug laevis) . Overall laevis) , 73, 74.2). In a wider geographical context, one of the most important anthropogenic negative impacts on population connectivity are probably electrocutions. Electrocution became the major source of non-natural mortality of eagle owls after the legal protection of raptors in Spain [Although eagle owls can potentially disperse large distances, our results agree with recovery data of banded individuals and evidence of limited dispersal among subpopulations , supportin Spain , 76, 77.in Spain . In densin Spain . This efin Spain , 79.Besides, some natural factors might have also increased population fragmentation. Eagle owl traits such as philopatry, the tendency to breed close to birthplaces , 81, or HE = 0.61; [Bubo blakistoni) on Hokkaido Island in Japan, a population with a significant decline of allelic richness over the last three decades [Overall, our analyses indicate that population declines were not severe enough to leave detectable genetic signals or that such signals have been eroded by the rapid demographic recovery experienced by the species in recent years. The combination of limited dispersal and high turnover and reproductive rates might have contributed to both the observed patterns of spatial genetic structure and the short-term erosion of the genetic signatures of recent demographic bottlenecks in Iberian eagle owls. In fact, we found moderate levels of genetic diversity and no differences in descriptive statistics of genetic diversity between the inferred clusters. Somewhat lesser levels of genetic variation were reported for the Scandinavian population of eagle owls, which passed a bottleneck below a few hundreds of individuals ; and a  decades . In our  decades .S1 FigK))  and the magnitude of ΔK as a function of K  over 11 runs.(a) Without considering prior population information and (b) using population identity as prior information (“Locprior” option). Plots show the mean (± SD) log probability of the data (ln Pr(X|(DOCX)Click here for additional data file.S1 Tablea, annealing temperature; NA, number of alleles; uHE, unbiased expected heterozygosity; HO, observed heterozygosity. *Significant heterozygote deficiency after Bonferroni correction (p < 0.05).For labelled primers the dye is reported within brackets. T(DOCX)Click here for additional data file.S2 TableIn bold those values changing from the previous simulation.(DOCX)Click here for additional data file.S3 TableFST values  and F’ST values .(DOCX)Click here for additional data file.S4 TableT) represents the date of the change in population size from N0 to N1.N0 and N1 are the current and ancestral effective population sizes respectively. Time ((DOCX)Click here for additional data file.


Crematogaster (subgenus Decacrema) ants inhabiting Macaranga myrmecophytes indicated that the partners diversified synchronously and their specific association has been maintained for 20 million years. However, the mtDNA clades did not exactly match morphological species, probably owing to introgressive hybridization among younger species. In this study, we determined the congruence between nuclear simple sequence repeat  genotyping and mtDNA phylogeny to confirm the suitability of the mtDNA phylogeny for inferring the evolutionary history of Decacrema ants. Analyses of ant samples from Lambir Hills National park, northeastern Borneo, showed overall congruence between the SSR and mtDNA groupings, indicating that mtDNA markers are useful for delimiting species, at least at the local level. We also found overall high host-plant specificity of the SSR genotypes of Decacrema ants, consistent with the specificity based on the mtDNA phylogeny. Further, we detected cryptic genetic assemblages exhibiting high specificity toward particular plant species within a single mtDNA clade. This finding, which may be evidence for rapid ecological and genetic differentiation following a host shift, is a new insight into the previously suggested long-term codiversification of Decacrema ants and Macaranga plants.A previously reported mitochondrial DNA (mtDNA) phylogeny of  In addition to these two estimates of admixture proportions (K = 3 and 5), we also conducted the genotyping analysis with the value of K = 6 which is consistent with the number of mtDNA clades (see next paragraph). In spite of relatively low value of mean lnP(D) under K = 6 (lnP(D) = -1964.65.74 ± 43.66 [mean ± SD]), the SSR genotyping clearly divided the ants into 6 groups (lnP(D) may be owing to the lack of sampling size of MS4 and MS6 . These three estimates were compatible and the K = 6 clustering contained elements of both the clustering of K = 3 and K = 5  data. STRUCTURE likelihood results were compared with 6 groups . This lond K = 5 . TherefoDecacrema ants inhabiting Macaranga from a 569-bp sequence of mitochondrial COI by ML, Bayesian, and MP analyses. The phylogenetic analyses revealed five well-supported primary mtDNA clades that are identical to clades E, D, F, G1, and H of Quek et al. [We inferred the molecular phylogeny of the k et al.  Fig. 3)DecacremaDecacrema ants inhabiting Macaranga in LHNP .Decacrema taxa and STRUCTURE clearly divided the ants into five or six clusterings  were included, the same result as presented in the manuscript would be obtained: the presented taxa in the manuscript would be divided as it is and the added taxa would form a new grouping. However, if more samples from other sites were added, the same result would not be necessarily obtained. Previous mtDNA phylogenetic analysis revealed that the genetic variation among geographic populations was so high that each ant mtDNA clade was divided into geographic sub-clades . If more sensitive SSR maker than mtDNA was used, exact clustering may not be reconstructed because geographical genetic variation of SSR may reach saturation and may exceed the variation among species. The SSR genotyping conducted here was successful probably because it excluded geographical variability by using samples collected from a single site. Similar to this, Feldhaar et al. (2010) also conducted the SSR genotyping of the ants by only using samples collected from a limited region, the state of Sabah.The SSR genotyping is generally used to detect intraspecific genetic variability among individuals or populations with the use of its hypervariable polymorphism. The genotyping conducted here is an exceptional case because it was used to detect genetic variability among species within a subgenus. However, we judged this analysis to be suitable because Feldhaar et al. (2005) designed these SSR markers to delimit the sterings . If moreDecacrema genotypes. Feldhaar et al. [Decacrema ants, about 2% of individuals of the captiosa group  hybridio et al.  reportedDecacrema ants inhabiting Macaranga, it has been inferred that nuptial flights might occur at night because foundress queens were found to colonize saplings at night [Decacrema ants need to be investigated.To understand how hybridization occurs, it is essential to determine when and where the ants perform their nuptial flights. However, little is known about the environmental cues that lead to nuptial flights in tropical forests . In Decaat night . But Fiaat night  reportedDecacrema genotype preferences toward Macaranga groups or species in LHNP indicated that all genotypes  showed significant preferences and avoidances toward particular Macaranga groups or species (Pachystemon). Several coadaptations between Decacrema and Macaranga could maintain this high specificity: host selection by foundress queens [Decacrema-Macaranga mutualism [Tests of  species . Quek ets queens –57; a trs queens ,32,58,59s queens –62. The utualism .Macaranga species: MS1 preferred M. trachyphylla (smooth Pachystemon) and MS2 preferred M. lamellata (waxy Pachystemon) , which together correspond to clade H, showed significant preferences toward different ystemon) . These rift eg. ,64), in , in Macautualism .S1 FigThe Jukes-Cantor 69 (JC69) distance was used for the substitution model.(EPS)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.


Bathyergus suillus), as our model. Bathyergus suillus is one of a few mammal species endemic to the Cape Floristic Region (CFR) of the Western Cape of South Africa. Its distribution is fragmented by rivers and mountains; both geographic phenomena that may act as geographical barriers to gene-flow. Using two mitochondrial fragments (cytochrome b and control region) as well as nine microsatellite loci, we determined the phylogeographic structure and gene-flow patterns at two different spatial scales . Furthermore, we investigated genetic differentiation between populations and applied Bayesian clustering and assignment approaches to our data. Nearly every population formed a genetically unique entity with significant genetic structure evident across geographic barriers such as rivers , mountains (Piketberg and Hottentots Holland Mountains) and with geographic distance at both spatial scales. Surprisingly, B. suillus was found to be paraphyletic with respect to its sister species, B. janetta–a result largely overlooked by previous studies on these taxa. A systematic revision of the genus Bathyergus is therefore necessary. This study provides a valuable insight into how the biology, life-history and habitat specificity of animals inhabiting a fossorial system may act in concert with the structure of the surrounding landscape to influence genetic distinctiveness and ultimately speciation.The distribution of genetic variation is determined through the interaction of life history, morphology and habitat specificity of a species in conjunction with landscape structure. While numerous studies have investigated this interplay of factors in species inhabiting aquatic, riverine, terrestrial, arboreal and saxicolous systems, the fossorial system has remained largely unexplored. In this study we attempt to elucidate the impacts of a subterranean lifestyle coupled with a heterogeneous landscape on genetic partitioning by using a subterranean mammal species, the Cape dune mole-rat ( The life-history of a species coupled with its ecological requirements and vagility determine its dispersal capability The structurally simple, constant and predictable subterranean niche Intuitively, given these life-history characteristics, the landscape in the form of geographic barriers  should also have a profound influence on the distribution of genetic variation in fossorial systems. Although the effect of such geographic barriers on the genetic structure and evolutionary patterns of subterranean species has been widely suggested Heterocephalus, Heliophobius, Bathyergus, Georychus, Cryptomys and FukomysThe family Bathyergidae offers an enticing opportunity to disentangle the factors which influence the spread of genetic variation in fossorial systems. The bathyergids are a monophyletic group of obligatory subterranean hystricognath rodents endemic to sub-Saharan Africa. Six genera are recognized: In spite of these suggested models and the possible influence of behaviour, morphology and the landscape on the distribution of genetic variation in fossorial taxa, previous studies focussed mostly on inter-generic relationships Bathyergus, containing two species, B. janetta and B. suillusB. suillus and B. janetta are proposed to differ in natural history, chromosome number, allozymes and mitochondrial DNA profiles, no genetic differences in either allozymes or karyotype were found by Janecek et al. et al. B. suillus and B. janetta as sister species B. suillus from the west coast area, thereby not allowing for the inclusion of possible geographic variation. Ingram et al. B. suillus from both the south- and west coast and reported B. suillus to be paraphyletic with respect to B. janetta; this led to the suggestion of higher genetic variation in this genus than previously anticipated.The solitary mole-rat species have been largely neglected in phylogeographic studies compared to their social counterparts Bathyergus suillus, as a model species to investigate the effect of a fossorial life-style on the distribution of genetic variation in a discontinuous landscape divided by barriers. Bathyergus suillus is the largest of the mole-rat species, is solitary and highly aggressive and its size  to test the model of genetic isolation, inbreeding and diminished heterozygosity proposed by Nevo B. suillus as a model, 3) to determine the phylogeographic patterns and intra-generic relationships within B. suillus and 4) to compare our results to previous studies on taxa exhibiting similar life-histories and habitat requirements and interpret the impact of a fossorial life-style on the distribution of genetic variation. By using mitochondrial (cytochrome b and control region) and nine nuclear (microsatellite) markers, we determined the distribution of genetic variation at local (Sandveld Bioregion - an area divided by the Verlorenvlei and Berg Rivers as well as the Piketberg Mountains) and regional (Cape Floristic Region- a region cleaved by major river systems and mountain ranges) spatial scales through adopting a landscape genetics approach. The influence of connectivity on spatial genetic patterns is the crux of the field of “landscape genetics” We therefore tested hypotheses on how the ecology, distribution, life-history and the connectivity of the surrounding landscape have shaped genetic variation across the distribution of B. suillus. Tissue samples were collected from five localities  in the Sandveld region - an area of Quaternary sand deposits and high species diversity situated between the Atlantic Ocean and the western branch of the Cape Fold Mountains Sampling was conducted in a hierarchical fashion across the range of L14724 and H15915; LO and E3; Total genomic DNA was extracted from tail-clippings using a commercial DNA extraction kit  following the manufacturer's protocol. Two mitochondrial DNA segments were amplified using universal primers for the amplifications and sequencing: 928 bp of the protein coding cytochrome b gene (b and 48°C for the control region) following the protocols outlined in Karsten et al. PCR amplifications followed standard protocols. In short, amplifications were carried out in a GeneAmp PCR 2700 system (Applied Biosystems) at region-specific annealing temperatures  were selected from Burland et al. Nine microsatellite loci .Genetic diversity detected within each sampling locality and summary statistics for the combined mitochondrial DNA analyses (including number of haplotypes and nucleotide (π) diversity) were calculated in Arlequin version 3.5 et al. Fluctuations in population size  in sampling localities were investigated using Fu’s Fs  and FST (microsatellites) were calculated between the Redelinghuys-, inner-Sandveld and Vredenburg localities, and between the West- and two South Coast clades. Additionally, pair-wise ΦST and FST values were calculated between localities. Significance was determined through 9 999 permutations of the data  and is efficient at detecting potential contact zones between populations The spatial location of genetic clusters in the microsatellite data within the studied areas was determined using Bayesian assignment approaches implemented in Geneland version 2.0.10 6 generations (burnin = 10 000) completed the analysis. In the case of the microsatellite data, the “Brownian” model was selected and 10 initial chains were run for 10 000 generations (burnin = 1 000); two final chains of 1×106 generations (burnin = 10 000) completed the analysis.Gene-flow among sampling localities was estimated in Lamarc version 2.1.6 b and control region sequences were congruent and the data were combined into a single sequence for subsequent analyses. Sequences of B. suillus were rooted with four Heterocephalus glaber  and two Bathyergus janetta sequences  (combined cytochrome b and control region) downloaded from GenBank in the parsimony and Bayesian analyses. For molecular dating, only the cytochrome b data were used and outgroups included B. janetta, Georychus capensis (Accession numbers: AF 012243.1 and AY 425920.1), Cryptomys hottentotus (Accession numbers: AY 425870.1 and AY 425884.1), Fukomys spp. (Accession numbers: EF 043513.1 and EF 043514.1), Heliophobius argenteocinereus (Accession number: AY 425937.1), H. glaber (Accession numbers: U 87522.1 to U 87525.1), Hystrix cristata (Accession numbers: FJ 472577.1 to FJ 472579.1), Mus caroli (Accession numbers: AB 033699.1 and AB 109795.1), Rattus rattus (Accession numbers: AB 033702.1 and AF 295545.1), Aplodontia rufa (Accession numbers: JX 420113.1 and JX 420115.1) and Xerus inauris (Accession numbers: AY 452689.1 to AY 452690).Genealogical analyses were conducted to search for phylogeographic patterns and date divergence events. As the control region matrix contained indels (insertions or deletions), these were treated as missing data in all analyses. The trees generated from the cytochrome 6 generations with sampling every 100 generations. After discarding the first 25% of the trees as burnin, a majority rule consensus tree with posterior probabilities was constructed. Posterior probabilities >0.90 and bootstraps >70% were considered acceptable support Phylogenetic trees were constructed using parsimony and Bayesian Inference approaches. For this, haplotypes were considered as the OTU. Parsimony analyses were executed in PAUP* version 4.0 Mus/Rattus (12±1 Mya) and Scuiridae/Aplodontidae (37 Mya). Runs were continued for 20×106 generations sampling every 1 000 generations (burnin = 2 000). Results were visualized in Tracer version 1.5 To obtain estimates of times of divergence for various clades, a relaxed molecular clock approach was adopted in BEAST version 1.7 Phylogenetic trees are not always sensitive enough to detect variation and relationships below the species level At the local scale, 98 specimens were sequenced  and genotyped  indicated that most of the populations were demographically stable (no expansion or contraction); however, the Struisbaai population had experienced a population expansion while the populations of Piketberg and Redelinghuys show signs of population contraction. When the data were pooled, the West Coast  and overall  distributions showed evidence of population expansions while the South Coast region  appears to be demographically contracting. No genetic bottlenecks were evident in the microsatellite data when populations were considered separately  or for tST = 0.35, FST = 0.13, p<0.001) and regional  scales. In addition, significant pairwise differentiation was evident in both datasets between all localities, both at a local and regional scale  and in the microsatellites on a local scale . Isolation-by-distance was not found for the mitochondrial data  across the Sandveld  region.Significant structure was detected in both datasets at local  when the populations were grouped (a-priori) into two respective groupings, pertaining to the West Coast  and South Coast . A similar pattern was found locally in the Sandveld  when the populations were grouped into the three respective areas constituting this region .There was also a significant partitioning of variance in both datasets  to the West Coast clade , Struisbaai and Riversdal/Sedgefield sampling areas respectively . These tThe haplotype network retrieved nineteen haploclades which could not be connected at the 95% confidence level . There wInvoking the “Admixture” model revealed ten clusters across the landscape thereby confirming the genetic distinctiveness of each sampled population (results not shown). Under the “no admixture” model eight clusters (based on the microsatellite data) were retrieved overall with virtually every sampled population clustering separately  except fB. suillus is no exception. Genetic diversity is structured between B. suillus populations across both local and regional spatial scales  may be linked to habitat fragmentation coupled to low vagility; pertinent factors to the genetic sub-structuring of subterranean taxa B. suillus was previously documented by Bray et al. et al. Such strong genetic sub-structuring points to the isolated nature of populations of fossorial species. Specifically, the isolated nature of IS) was evident within all but one of the populations  divides the distribution range of the most diverse taxa within the Bathyergidae Spalax and Nannospalaxet al. et al. Interestingly, the Cape Town and Stanford areas (that span the Hottentots Holland Mountains) group together in the genealogical analyses . This grB. Suillus at both local and regional scales. On a local scale, the Berg- and Verlorenvlei Rivers form phylogeographic barriers to gene-flow thereby structuring genetic variation  for most of the time. It is possible that gene-flow and colonization of areas may occur around the upper reaches of these rivers during dry periods , suggesting a possible colonization of the West Coast from the South Coast , differentiation of isolated populations may happen in a comparatively short period of time. Additionally, geographic barriers to gene-flow (mountains and drainage systems) and geographic distance play a significant role in structuring genetic variation within B. suillus - a factor which may partly explain the staggering radiation in fossorial species worldwide. Furthermore, a systematic revision of the genus Bathyergus is necessary, given the findings of this study.This study exemplifies a holistic approach to investigating the genetic structure within species. The life-history, biology and habitat requirements of fossorial taxa impact on the distribution and isolation of populations - here demonstrated by interpreting phylogeographic and gene-flow patterns in Figure S1Bayesian phylogram demonstrating the different mitochondrial DNA clades across the sampled distribution. Bayesian phylogram obtained from the analyses based on combined cytochrome b and control region sequences demonstrating the different mitochondrial DNA clades detected in B. suillus from localities across the Cape Floristic Region. Values above each node represent posterior probabilities (Pp) derived from the Bayesian inference (MrBayes and BEAST) analyses and those below nodes are the Maximum Parsimony values.(TIF)Click here for additional data file.Figure S2Bayesian phylogram from the BEAST analysis indicating the divergence dates between clades. Bayesian phylogram obtained from the BEAST analyses of the cytochrome b haplotypes among the 10 B. suillus sample sites across the Cape Florisitc Region. The values above each node represent the posterior probability (pP) values derived from the Bayesian inference analyses. The populations comprising the two clades evident across the distribution are shown. The divergence dates for four nodes (A–D) are indicated as bars which include the span of the divergence estimate for that particular node.(TIF)Click here for additional data file.Table S1Summary information for the microsatellite loci used in this study. Locus summary information showing the estimated proportion of null alleles (Null), percentage missing data of the total 356 alleles/locus, proportion of missing alleles/locus, the genotyping error per genotype and FIS values for each of the microsatellite loci used in this study.(DOCX)Click here for additional data file.Table S2Summary of loci which did not conform to Hardy-Weinberg Equilibrium in each population. Summary of loci which did not conform to Hardy-Weinberg Equilibrium (marked by an “x”) in each sampled population of B. suillus.(DOCX)Click here for additional data file.Table S3Microsatellite data used in this study.(XLSX)Click here for additional data file.


Panicum miliaceum L.), one of the first domesticated crops, has been grown in Northern China for at least 10,000 years. The species is presently a minor crop, and evaluation of its genetic diversity has been very limited. In this study, we analyzed the genetic diversity of 88 accessions of broomcorn millet collected from various provinces of China. Amplification with 67 simple sequence repeat (SSR) primers revealed moderate levels of diversity in the investigated accessions. A total of 179 alleles were detected, with an average of 2.7 alleles per locus. Polymorphism information content and expected heterozygosity ranged from 0.043 to 0.729 (mean = 0.376) and 0.045 to 0.771 (mean = 0.445), respectively. Cluster analysis based on the unweighted pair group method of mathematical averages separated the 88 accessions into four groups at a genetic similarity level of 0.633. A genetic structure assay indicated a close correlation between geographical regions and genetic diversity. The uncovered information will be valuable for defining gene pools and developing breeding programs for broomcorn millet. Furthermore, the millet-specific SSR markers developed in this study should serve as useful tools for assessment of genetic diversity and elucidation of population structure in broomcorn millet.Broomcorn millet ( Panicum miliaceum L. (Poaceae); 2n = 4x = 36) is an annual warm season crop also known as proso, hog, white, yellow, or common millet [Broomcorn millet  are conserved in the National Gene Bank of the Institute of Crop Science, Chinese Academy of Agricultural Sciences . Although abundant morphological variation exists within the broomcorn millet accessions, assessment of their genetic diversity using DNA markers has been inadequate. Previous analyses of genetic variation in P. miliaceum have employed isozymes [de novo methods [More than 8700 accessions (landraces and varieties) of isozymes , RAPDs [isozymes , AFLPs [isozymes , and SSRisozymes , as well methods . The resIn this study, millet-specific SSR primers developed in our laboratory by high-throughput sequencing were used to identify polymorphisms and to analyze the genetic diversity and structure of 88 accessions comprising 56 main varieties cultivated in China and 32 parental lines.I) varied from 0.1085 to 1.5194 per locus, with an average of 0.7254, while expected heterozygosity (He) and observed heterozygosity (Ho) ranged from 0.0447 to 0.7713 (mean = 0.4447) and 0 to 0.9545 (mean = 0.2348), respectively. Some loci, such as F786, F1036, F1067, F1071, F2185, BM306, and BM344, had a Ho of 0, suggesting universal outcrossing between individuals or perhaps between wild populations and nearby cultivated broomcorn millet. The value of genetic diversity which calculated according to Nei’s 1973 (H) ranged from 0.0444 (for F1036) to 0.7669 (for F1380), with an average of 0.4419. With respect to FST, an index of genetic differentiation or the genetic distance between wild and cultivated accessions, values of the 67 applied markers ranged widely: from 0.0434 (BM114) to 0.8342 (F1071), with a mean of 0.2988. Polymorphism information content (PIC) values for each SSR ranged from 0.0434 (F1036) to 0.7288 (F1380), with an average of 0.376, indicating a moderate level of genetic diversity in Chinese broomcorn millet. In the analyzed samples, values of Na and Ne per locus were most strongly correlated with PIC , followed by I, He, and H.Using the 67 SSR primer pairs that produced clear polymorphic fragments among eight representatives during preliminary screening, we detected 179 alleles and 349 genotypes in the 88 studied accessions. Details of uncovered polymorphism levels and other parameters are given in I, H, and PIC per locus varied among populations from 0.318 to 0.619 (average = 0.497), 0.215–0.427 (average = 0.310), and 0.345–0.420 (average = 0.380), respectively. The lowest genetic parameter values were found in accessions constituting population 9; this finding implies that the accessions from population 9 were very closely related, with a majority of loci (64.2%) observed to be fixed (As evidenced by the estimates of population genetic diversity listed in be fixed . AccessiUnweighted pair-group method with arithmetic (UPGMA) cluster analysis based on genetic similarity values among the 88 broomcorn millet accessions yielded the dendrogram shown in We evaluated population structure and differentiation of the 88 accessions from different provinces using a Bayesian Markov chain Monte Carlo approach as implemented in STRUCTURE 2.2.3.K) showed clear peaks at 3 and 11, so we analyzed the genetic structure of the 88 accessions separately for these two values of K. We think that may be better for analysis of population structure of tested samples. At K = 3, three main groups could be distinguished , a weedy, diploid (2n = 18) New World species, may be an ancestor of broomcorn millet [et al. [P. miliaceum. In our study, the genetic diversity of accessions from the Mongolian Plateau was slightly higher than that of other ecotypes, perhaps because of the effects of breeding programs or other reasons requiring further investigation. Although Central Asia, China, and Central Europe have all been proposed as the specific area of domestication of broomcorn millet and its wild ancestors, the original location has not been definitively determined . In addin millet . Analysi [et al. . Those aA total of 88 broomcorn millet accessions (56 varieties and 32 parents) collected from seven main millet-producing Chinese provinces were provided by the institutions listed in et al. [−1.Seeds of each accession were sown in plastic pots (10 cm diameter) and grown under greenhouse conditions. Total genomic DNA was extracted from young leaves of 15–20-day old seedlings based on the modified cetyltrimethylammonium bromide method described by Edward et al. . The relWe used 500 pairs of SSR primers . develop2+), 0.2 µL of each 10 mM dNTP, 0.1 µL of 5 U·µL−1Taq DNA polymerase, 0.5 µL of a 5 µM solution of each primer, 1 µL of 30 ng·µL−1 genomic DNA, and 6.1 µL of ddH2O. Reactions were carried out in a PTC-100 Thermo-Cycler  using the program as follows: (1) initial denaturation at 94 °C for 5 min; (2) 39 cycles of denaturation at 94 °C for 45 s; (3) annealing at 55 °C for 50 s;(4) extension at 72 °C for 1 min;(5) a final extension at 72 °C for 10 min. The PCR-amplified products were resolved by 8% polyacrylamide gel electrophoresis, with DNA bands visualized by silver nitrate staining. Allele sizes were determined using a 50-bp DNA ladder .Polymerase chain reaction (PCR) amplifications were performed in 10 µL volumes containing 1.6 µL of 10× PCR buffer  [I). Geographical differentiation was evaluated by estimating F-statistic (FST) values among geographical regions using POPGENE. The Simpson diversity index for each SSR, also known as the polymorphism information content (PIC), was calculated using the program PIC-CALC 0.6. Using a similarity matrix generated from the proportion of shared fragments [a priori classification and divides samples into K populations according to the allele frequencies at each locus. The most likely number of genetic groups (K = 1 to 10) was estimated following the procedure of Evanno et al. [ad hoc statistic ΔK. Program settings included admixture ancestry and correlated marker frequency models, with α inferred from the data and lambda set to 1 [K.POPGENE 1.31  was usedH) , and theragments , genetico et al. , who proset to 1 . Twenty In conclusion, our data indicates there have abundant genetic variation within different ecological growth areas and complex genetic relationships between various populations of broomcorn millet. On the other hand, the millet-specific SSR markers developed in this study can be served as effective molecular tools for the assessment of genetic diversity and the elucidation of population structure in broomcorn millet.