982 resultados para Population sizes


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We collected and analyzed 500 samples of human milk, from five Brazilian cities (100 from each) to detect methicillin-resistant strains of Staphylococcus aureus (MRSA) producing enterotoxins. We found 57 strains of MRSA, and the mecA gene, responsible for resistance, was detected in all of them using a specific molecular probe. We examined 40 strains for the presence of four enterotoxins, after selecting a subset that included all strains from each region, except for the largest sample, from which 10 were randomly selected. Among these two presented enterotoxin B, and growth in human colostrum and trypicase soy broth. After 5 h of incubation at 37°C, population sizes were already higher than 9.4 x 105 UFC/ml and enterotoxin was released into culture medium and colostrum. Our results stress the importance of hygiene, sanitary measures, and appropriate preservation conditions to avoid the proliferation of S. aureus in human milk.

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Experimental evolution is the study of evolutionary processes occurring in experimental populations in response to conditions imposed by the experimenter. This research approach is increasingly used to study adaptation, estimate evolutionary parameters, and test diverse evolutionary hypotheses. Long applied in vaccine development, experimental evolution also finds new applications in biotechnology. Recent technological developments provide a path towards detailed understanding of the genomic and molecular basis of experimental evolutionary change, while new findings raise new questions that can be addressed with this approach. However, experimental evolution has important limitations, and the interpretation of results is subject to caveats resulting from small population sizes, limited timescales, the simplified nature of laboratory environments, and, in some cases, the potential to misinterpret the selective forces and other processes at work.

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The reproductive assurance hypothesis emphasizes that self-fertilization should evolve in species with reduced dispersal capability, low population size or experiencing recurrent bottlenecks. Our work investigates the ecological components of the habitats colonized by the snail, Galba truncatula, that may influence the evolution of selfing. Galba truncatula is a preferential selfer inhabiting freshwater habitats, which vary with respect to the degree of permanence. We considered with a population genetic approach the spatial and the temporal degree of isolation of populations of G. truncatula. We showed that patches at distances of only a few meters are highly structured. The effective population sizes appear quite low, in the order of 10 individuals or less. This study indicates that individuals of the species G. truncatula are likely to be alone in a site and have a low probability of finding a partner from a nearby site to reproduce. These results emphasize the advantage of selfing in this species.

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Small mammals are found naturally infected by Schistosoma mansoni, becoming a confounding factor for control programs of schistosomiasis in endemic areas. The aims of this study were: to investigate the infection rates by S. mansoni on the water-rat Nectomys squamipes during four years in endemic areas of Sumidouro, state of Rio de Janeiro, using mark-recapture technique; to compare two diagnostic methods for schistosomiasis; and to evaluate the effects of the chemotherapy in the human infected population on the rodent infection rates. The rodent infection rates of S. mansoni increased when rodent population sizes were lower. Coprology and serology results presented the same trends along time and were correlated. Serology could detect recent infection, including the false negatives in the coprology. The chemotherapy in the humans could not interrupt the rodent infection. Rodents can increase the schistosomiaisis transmission where it already exists, they probably maintain the transmission cycle in the nature and can be considered as biological indicators of the transmission sites of this parasite since they are highly susceptible to infection. The water-rats may present different levels of importance in the transmission dynamics of S. mansoni infection cycle for each area, and can be considered important wild-reservoirs of this human disease.

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Investigating the mechanisms underlying female mate choice is important for sexual-selection theory, but also for population-genetic studies, because distinctive breeding strategies affect differently the dynamics of gene diversity within populations. Using field-monitoring, genetic-assignment, and laboratory-rearing methods, we investigated chorus attendance, mating success and offspring fitness in a population of lek-breeding tree-frogs (Hyla arborea) to test whether female choice is driven by good genes or complementary genes. Chorus attendance explained approximately 50% of the variance in male mating success, but did not correlate with offspring fitness. By contrast, offspring body mass and growth rate correlated with male attractiveness, measured as the number of matings obtained per night of calling. Genetic similarity between mating partners did not depart from random, and did not affect offspring fitness. We conclude that females are able to choose good partners under natural settings and obtain benefits from the good genes, rather than compatible genes, their offspring inherit. This heritability of fitness is likely to reduce effective population sizes below values previously estimated.

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Rare species have restricted geographic ranges, habitat specialization, and/or small population sizes. Datasets on rare species distribution usually have few observations, limited spatial accuracy and lack of valid absences; conversely they provide comprehensive views of species distributions allowing to realistically capture most of their realized environmental niche. Rare species are the most in need of predictive distribution modelling but also the most difficult to model. We refer to this contrast as the "rare species modelling paradox" and propose as a solution developing modelling approaches that deal with a sufficiently large set of predictors, ensuring that statistical models aren't overfitted. Our novel approach fulfils this condition by fitting a large number of bivariate models and averaging them with a weighted ensemble approach. We further propose that this ensemble forecasting is conducted within a hierarchic multi-scale framework. We present two ensemble models for a test species, one at regional and one at local scale, each based on the combination of 630 models. In both cases, we obtained excellent spatial projections, unusual when modelling rare species. Model results highlight, from a statistically sound approach, the effects of multiple drivers in a same modelling framework and at two distinct scales. From this added information, regional models can support accurate forecasts of range dynamics under climate change scenarios, whereas local models allow the assessment of isolated or synergistic impacts of changes in multiple predictors. This novel framework provides a baseline for adaptive conservation, management and monitoring of rare species at distinct spatial and temporal scales.

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What are the best voting systems in terms of utilitarianism? Or in terms of maximin, or maximax? We study these questions for the case of three alternatives and a class of structurally equivalent voting rules. We show that plurality, arguably the most widely used voting system, performs very poorly in terms of remarkable ideals of justice, such as utilitarianism or maximin, and yet is optimal in terms of maximax. Utilitarianism is bestapproached by a voting system converging to the Borda count, while the best way to achieve maximin is by means of a voting system converging to negative voting. We study the robustness of our results across different social cultures, measures of performance, and population sizes.

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The effects of patch size and isolation on metapopulation dynamics have received wide empirical support and theoretical formalization. By contrast, the effects of patch quality seem largely underinvestigated, partly due to technical difficulties in properly assessing quality. Here we combine habitat-quality modeling with four years of demographic monitoring in a metapopulation of greater white-toothed shrews (Crocidura russula) to investigate the role of patch quality on metapopulation processes. Together, local patch quality and connectivity significantly enhanced local population sizes and occupancy rates (R2 = 14% and 19%, respectively). Accounting for the quality of patches connected to the focal one and acting as potential sources improved slightly the model explanatory power for local population sizes, pointing to significant source-sink dynamics. Local habitat quality, in interaction with connectivity, also increased colonization rate (R2 = 28%), suggesting the ability of immigrants to target high-quality patches. Overall, patterns were best explained when assuming a mean dispersal distance of 800 m, a realistic value for the species under study. Our results thus provide evidence that patch quality, in interaction with connectivity, may affect major demographic processes.

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Accurate detection of subpopulation size determinations in bimodal populations remains problematic yet it represents a powerful way by which cellular heterogeneity under different environmental conditions can be compared. So far, most studies have relied on qualitative descriptions of population distribution patterns, on population-independent descriptors, or on arbitrary placement of thresholds distinguishing biological ON from OFF states. We found that all these methods fall short of accurately describing small population sizes in bimodal populations. Here we propose a simple, statistics-based method for the analysis of small subpopulation sizes for use in the free software environment R and test this method on real as well as simulated data. Four so-called population splitting methods were designed with different algorithms that can estimate subpopulation sizes from bimodal populations. All four methods proved more precise than previously used methods when analyzing subpopulation sizes of transfer competent cells arising in populations of the bacterium Pseudomonas knackmussii B13. The methods' resolving powers were further explored by bootstrapping and simulations. Two of the methods were not severely limited by the proportions of subpopulations they could estimate correctly, but the two others only allowed accurate subpopulation quantification when this amounted to less than 25% of the total population. In contrast, only one method was still sufficiently accurate with subpopulations smaller than 1% of the total population. This study proposes a number of rational approximations to quantifying small subpopulations and offers an easy-to-use protocol for their implementation in the open source statistical software environment R.

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This study aimed to evaluate the impact of genetically modified (GM) wheat with introduced pm3b mildew resistance transgene, on two types of root-colonizing microorganisms, namely pseudomonads and arbuscular mycorrhizal fungi (AMF). Our investigations were carried out in field trials over three field seasons and at two locations. Serial dilution in selective King's B medium and microscopy were used to assess the abundance of cultivable pseudomonads and AMF, respectively. We developed a denaturing gradient gel electrophoresis (DGGE) method to characterize the diversity of the pqqC gene, which is involved in Pseudomonas phosphate solubilization. A major result was that in the first field season Pseudomonas abundances and diversity on roots of GM pm3b lines, but also on non-GM sister lines were different from those of the parental lines and conventional wheat cultivars. This indicates a strong effect of the procedures by which these plants were created, as GM and sister lines were generated via tissue cultures and propagated in the greenhouse. Moreover, Pseudomonas population sizes and DGGE profiles varied considerably between individual GM lines with different genomic locations of the pm3b transgene. At individual time points, differences in Pseudomonas and AMF accumulation between GM and control lines were detected, but they were not consistent and much less pronounced than differences detected between young and old plants, different conventional wheat cultivars or at different locations and field seasons. Thus, we conclude that impacts of GM wheat on plant-beneficial root-colonizing microorganisms are minor and not of ecological importance. The cultivation-independent pqqC-DGGE approach proved to be a useful tool for monitoring the dynamics of Pseudomonas populations in a wheat field and even sensitive enough for detecting population responses to altered plant physiology.

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Background: Natural selection and genetic drift are major forces responsible for temporal genetic changes in populations. Furthermore, these evolutionary forces may interact with each other. Here we study the impact of an ongoing adaptive process at the molecular genetic level by analyzing the temporal genetic changes throughout 40 generations of adaptation to a common laboratory environment. Specifically, genetic variability, population differentiation and demographic structure were compared in two replicated groups of Drosophila subobscura populations recently sampled from different wild sources. Results: We found evidence for a decline in genetic variability through time, along with an increase in genetic differentiation between all populations studied. The observed decline in genetic variability was higher during the first 14 generations of laboratory adaptation. The two groups of replicated populations showed overall similarity in variability patterns. Our results also revealed changing demographic structure of the populations during laboratory evolution, with lower effective population sizes in the early phase of the adaptive process. One of the ten microsatellites analyzed showed a clearly distinct temporal pattern of allele frequency change, suggesting the occurrence of positive selection affecting the region around that particular locus. Conclusion: Genetic drift was responsible for most of the divergence and loss of variability between and within replicates, with most changes occurring during the first generations of laboratory adaptation. We also found evidence suggesting a selective sweep, despite the low number of molecular markers analyzed. Overall, there was a similarity of evolutionary dynamics at the molecular level in our laboratory populations, despite distinct genetic backgrounds and some differences in phenotypic evolution.

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BACKGROUND: The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractable for many realistic evolutionary models, and the use of Bayesian inference has therefore been limited to very simple models. The situation changed recently with the advent of Approximate Bayesian Computation (ABC) algorithms allowing one to obtain parameter posterior distributions based on simulations not requiring likelihood computations. RESULTS: Here we present ABCtoolbox, a series of open source programs to perform Approximate Bayesian Computations (ABC). It implements various ABC algorithms including rejection sampling, MCMC without likelihood, a Particle-based sampler and ABC-GLM. ABCtoolbox is bundled with, but not limited to, a program that allows parameter inference in a population genetics context and the simultaneous use of different types of markers with different ploidy levels. In addition, ABCtoolbox can also interact with most simulation and summary statistics computation programs. The usability of the ABCtoolbox is demonstrated by inferring the evolutionary history of two evolutionary lineages of Microtus arvalis. Using nuclear microsatellites and mitochondrial sequence data in the same estimation procedure enabled us to infer sex-specific population sizes and migration rates and to find that males show smaller population sizes but much higher levels of migration than females. CONCLUSION: ABCtoolbox allows a user to perform all the necessary steps of a full ABC analysis, from parameter sampling from prior distributions, data simulations, computation of summary statistics, estimation of posterior distributions, model choice, validation of the estimation procedure, and visualization of the results.

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The objective of this work was to estimate the coefficient of parentage and to understand the genetic structure of 90 elite soybean cultivars, which are adapted to different Brazilian environments. A total of 4,005 coefficients of parentage (f) were obtained and used to group the cultivars by UPGMA method. The constructed dendrogram showed several related cultivar groups which shared similar ancestors and clearly showed the genetic structure of the main Brazilian cultivars. Effective population sizes (Ne) were also estimated for cultivars in different generations. The average f = 0.2124 value, obtained from cultivars classified into four decades according to the release year, suggested effective soybean population sizes of 11 and 13 calculated using arithmetic and weighted means, respectively. The relatively small Ne and the high parentage coefficient support the conclusion that there is a high similarity degree among the main soybean cultivars in Brazil.

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Most butterfly monitoring protocols rely on counts along transects (Pollard walks) to generate species abundance indices and track population trends. It is still too often ignored that a population count results from two processes: the biological process (true abundance) and the statistical process (our ability to properly quantify abundance). Because individual detectability tends to vary in space (e.g., among sites) and time (e.g., among years), it remains unclear whether index counts truly reflect population sizes and trends. This study compares capture-mark-recapture (absolute abundance) and count-index (relative abundance) monitoring methods in three species (Maculinea nausithous and Iolana iolas: Lycaenidae; Minois dryas: Satyridae) in contrasted habitat types. We demonstrate that intraspecific variability in individual detectability under standard monitoring conditions is probably the rule rather than the exception, which questions the reliability of count-based indices to estimate and compare specific population abundance. Our results suggest that the accuracy of count-based methods depends heavily on the ecology and behavior of the target species, as well as on the type of habitat in which surveys take place. Monitoring programs designed to assess the abundance and trends in butterfly populations should incorporate a measure of detectability. We discuss the relative advantages and inconveniences of current monitoring methods and analytical approaches with respect to the characteristics of the species under scrutiny and resources availability.

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There is still limited understanding of the processes underlying benthic species dynamics in marine coastal habitats, which are of disproportionate importance in terms of productivity and biodiversity. The life-history traits of long-lived benthic species in these habitats are particularly poorly documented. In this study, we assessed decadal patterns of population dynamics for ten sponge and anthozoan species that play key structural roles in coralligenous outcrops (~25 m depth) in two areas of the NW Mediterranean Sea. This study was based on examination of a unique long-term photographic series, which allowed analysis of population dynamics over extensive spatial and time spans for the very first time. Specifically, 671 individuals were censused annually over periods of 25-, 15-, and 5-years. This long-term study quantitatively revealed a common life-history pattern among the ten studied species, despite the fact they present different growth forms. Low mortality rates (3.4% yr−1 for all species combined) and infrequent recruitment events (mean value of 3.1±0.5 SE recruits yr−1) provided only a very small fraction of the new colonies required to maintain population sizes. Overall, annual mortality and recruitment rates did not differ significantly among years; however, some species displayed important mortality events and recruitment pulses, indicating variability among species. Based on the growth rates of these 10 species, we projected their longevity and, obtained a mean estimated age of 25-200 years. Finally, the low to moderate turnover rates (mean value 0.80% yr−1) observed among the coralligenous species were in agreement with their low dynamics and persistence. These results offer solid baseline data and reveal that these habitats are among the most vulnerable to the current increases of anthropogenic disturbances.