908 resultados para Population Size


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Passerines are especially vulnerable to predation at the pre-independence stage. Although the role of nest success in British farmland passerine declines is contentious, improvement in nest success through sympathetic management could play a role in their reversal. Because habitat is known to interact with predation, management options for mitigation will need to consider effects of nest predation. We present results from an observational study of a population of Common Blackbird Turdus merula on a farm which has experienced a range of agri-environment and game-management options, including a period with nest predator control, as a case study to address some of these issues. We used an information theoretic model comparison procedure to look for evidence of interactions between habitat and nest predation, and then asked whether habitat management and nest predator abundances could explain population trends at the site through their effects on nest success. Interactions were detected between measures of predator abundance and habitat variables, and these varied with nest stage - habitat within the vicinity of the nest appeared to be important at the egg stage, and nest-placement characteristics were important at the nestling stage. Although predator control appeared to have a positive influence on Blackbird breeding population size, the non-experimental set-up meant we could not eliminate other potential explanations. Variation in breeding population size did not appear to be influenced by variation in nest success alone. Our study demonstrates that observational data can only go so far in detection of such effects, and we discuss how it might be taken further. Agri-environment and game-management techniques are likely to influence nest predation pressure on farmland passerines, but the patterns, mechanisms and importance to population processes remain not wholly understood.

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Passerines are especially vulnerable to predation at the pre-independence stage. Although the role of nest success in British farmland passerine declines is contentious, improvement in nest success through sympathetic management could play a role in their reversal. Because habitat is known to interact with predation, management options for mitigation will need to consider effects of nest predation. We present results from an observational study of a population of Common Blackbird Turdus merula on a farm which has experienced a range of agri-environment and game-management options, including a period with nest predator control, as a case study to address some of these issues. We used an information theoretic model comparison procedure to look for evidence of interactions between habitat and nest predation, and then asked whether habitat management and nest predator abundances could explain population trends at the site through their effects on nest success. Interactions were detected between measures of predator abundance and habitat variables, and these varied with nest stage - habitat within the vicinity of the nest appeared to be important at the egg stage, and nest-placement characteristics were important at the nestling stage. Although predator control appeared to have a positive influence on Blackbird breeding population size, the non-experimental set-up meant we could not eliminate other potential explanations. Variation in breeding population size did not appear to be influenced by variation in nest success alone. Our study demonstrates that observational data can only go so far in detection of such effects, and we discuss how it might be taken further. Agri-environment and game-management techniques are likely to influence nest predation pressure on farmland passerines, but the patterns, mechanisms and importance to population processes remain not wholly understood.

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Two simple and frequently used capture–recapture estimates of the population size are compared: Chao's lower-bound estimate and Zelterman's estimate allowing for contaminated distributions. In the Poisson case it is shown that if there are only counts of ones and twos, the estimator of Zelterman is always bounded above by Chao's estimator. If counts larger than two exist, the estimator of Zelterman is becoming larger than that of Chao's, if only the ratio of the frequencies of counts of twos and ones is small enough. A similar analysis is provided for the binomial case. For a two-component mixture of Poisson distributions the asymptotic bias of both estimators is derived and it is shown that the Zelterman estimator can experience large overestimation bias. A modified Zelterman estimator is suggested and also the bias-corrected version of Chao's estimator is considered. All four estimators are compared in a simulation study.

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This note considers the variance estimation for population size estimators based on capture–recapture experiments. Whereas a diversity of estimators of the population size has been suggested, the question of estimating the associated variances is less frequently addressed. This note points out that the technique of conditioning can be applied here successfully which also allows us to identify sources of variation: the variance due to estimation of the model parameters and the binomial variance due to sampling n units from a population of size N. It is applied to estimators typically used in capture–recapture experiments in continuous time including the estimators of Zelterman and Chao and improves upon previously used variance estimators. In addition, knowledge of the variances associated with the estimators by Zelterman and Chao allows the suggestion of a new estimator as the weighted sum of the two. The decomposition of the variance into the two sources allows also a new understanding of how resampling techniques like the Bootstrap could be used appropriately. Finally, the sample size question for capture–recapture experiments is addressed. Since the variance of population size estimators increases with the sample size, it is suggested to use relative measures such as the observed-to-hidden ratio or the completeness of identification proportion for approaching the question of sample size choice.

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Estimation of population size with missing zero-class is an important problem that is encountered in epidemiological assessment studies. Fitting a Poisson model to the observed data by the method of maximum likelihood and estimation of the population size based on this fit is an approach that has been widely used for this purpose. In practice, however, the Poisson assumption is seldom satisfied. Zelterman (1988) has proposed a robust estimator for unclustered data that works well in a wide class of distributions applicable for count data. In the work presented here, we extend this estimator to clustered data. The estimator requires fitting a zero-truncated homogeneous Poisson model by maximum likelihood and thereby using a Horvitz-Thompson estimator of population size. This was found to work well, when the data follow the hypothesized homogeneous Poisson model. However, when the true distribution deviates from the hypothesized model, the population size was found to be underestimated. In the search of a more robust estimator, we focused on three models that use all clusters with exactly one case, those clusters with exactly two cases and those with exactly three cases to estimate the probability of the zero-class and thereby use data collected on all the clusters in the Horvitz-Thompson estimator of population size. Loss in efficiency associated with gain in robustness was examined based on a simulation study. As a trade-off between gain in robustness and loss in efficiency, the model that uses data collected on clusters with at most three cases to estimate the probability of the zero-class was found to be preferred in general. In applications, we recommend obtaining estimates from all three models and making a choice considering the estimates from the three models, robustness and the loss in efficiency. (© 2008 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

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The estimation of effective population size from one sample of genotypes has been problematic because most estimators have been proven imprecise or biased. We developed a web-based program, ONeSAMP that uses approximate Bayesian computation to estimate effective population size from a sample of microsatellite genotypes. ONeSAMP requires an input file of sampled individuals' microsatellite genotypes along with information about several sampling and biological parameters. ONeSAMP provides an estimate of effective population size, along with 95% credible limits. We illustrate the use of ONeSAMP with an example data set from a re-introduced population of ibex Capra ibex.

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We describe and evaluate a new estimator of the effective population size (N-e), a critical parameter in evolutionary and conservation biology. This new "SummStat" N-e. estimator is based upon the use of summary statistics in an approximate Bayesian computation framework to infer N-e. Simulations of a Wright-Fisher population with known N-e show that the SummStat estimator is useful across a realistic range of individuals and loci sampled, generations between samples, and N-e values. We also address the paucity of information about the relative performance of N-e estimators by comparing the SUMMStat estimator to two recently developed likelihood-based estimators and a traditional moment-based estimator. The SummStat estimator is the least biased of the four estimators compared. In 32 of 36 parameter combinations investigated rising initial allele frequencies drawn from a Dirichlet distribution, it has the lowest bias. The relative mean square error (RMSE) of the SummStat estimator was generally intermediate to the others. All of the estimators had RMSE > 1 when small samples (n = 20, five loci) were collected a generation apart. In contrast, when samples were separated by three or more generations and Ne less than or equal to 50, the SummStat and likelihood-based estimators all had greatly reduced RMSE. Under the conditions simulated, SummStat confidence intervals were more conservative than the likelihood-based estimators and more likely to include true N-e. The greatest strength of the SummStat estimator is its flexible structure. This flexibility allows it to incorporate any, potentially informative summary statistic from Population genetic data.

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Estimation of a population size by means of capture-recapture techniques is an important problem occurring in many areas of life and social sciences. We consider the frequencies of frequencies situation, where a count variable is used to summarize how often a unit has been identified in the target population of interest. The distribution of this count variable is zero-truncated since zero identifications do not occur in the sample. As an application we consider the surveillance of scrapie in Great Britain. In this case study holdings with scrapie that are not identified (zero counts) do not enter the surveillance database. The count variable of interest is the number of scrapie cases per holding. For count distributions a common model is the Poisson distribution and, to adjust for potential heterogeneity, a discrete mixture of Poisson distributions is used. Mixtures of Poissons usually provide an excellent fit as will be demonstrated in the application of interest. However, as it has been recently demonstrated, mixtures also suffer under the so-called boundary problem, resulting in overestimation of population size. It is suggested here to select the mixture model on the basis of the Bayesian Information Criterion. This strategy is further refined by employing a bagging procedure leading to a series of estimates of population size. Using the median of this series, highly influential size estimates are avoided. In limited simulation studies it is shown that the procedure leads to estimates with remarkable small bias.

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The survival, absolute population size, gonotrophic cycle duration, and temporal and spatial abundance of Nyssomyia neivai (Pinto) were studied in a rural area endemic for American cutaneous leishmaniasis (ACL) in Conchal, Sao Paulo State, southeastern Brazil, using mark-release-recapture techniques and by monitoring population fluctuation. The monthly abundance exhibited a unimodal pattern, with forest and domicile habitats having the highest relative abundances. A total of 1,873 males and 3,557 females were marked and released during the six experiments, of which 4.1-13.0% of males and 4.1-11.8% of females were recaptured. Daily survivorship estimated from the decline in recaptures per day was 0.681 for males and 0.667 for females. Gonotrophic cycle duration was estimated to be 4.0 d. Absolute population size was calculated using the Lincoln Index and ranged from 861 to 4,612 males and from 2,187 to 19,739 females. The low proportion of females that reach the age when they are potentially infective suggests that N. neivai has a low biological capacity to serve as a vector and that factors such as high biting rates and opportunistic feeding behavior would be needed to enable Leishmania (Viannia) braziliensis Vianna transmission. This agreed with the epidemiological pattern of ACL in southeastern Brazil that is characterized by low incidence, with isolated cases acquired principally within domiciliary habitats.

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In order to quantify the population of Acromyrmex balzani Emery, 1890 nests and to verify whether the population dynamic of the colony is correlated with the symbiont fungus volume, the principal energy source of the colony, five nests located in grassland areas were evaluated. The nests were sprayed with neutral talcum powder to improve visualization and digging. The symbiont fungus and the entire population existent in the chambers were collected. The mean fungus volume and total nest population in excavated nests were, respectively, 74.76 ml and 1,095 individuals. Simple linear correlation analysis verified that the fungus volume grew proportionally to the number of individuals. Despite the correlation between fungus volume and population dynamic of colonies, the factors that determine this relationship are little known since other microorganisms live in association with the colony.

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Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Os tubarões enfrentam muitos obstáculos para sobreviver nos primeiros anos de vida e muitas espécies ocupam áreas de berçário. Embora estimativas de sobrevivência, particularmente para jovens, sejam essenciais para acessar, monitorar e manejar efetivamente populações animais, existem poucos cálculos destas estimativas para populações de tubarões e poucas estimativas baseadas em métodos diretos para estes animais em suas áreas de berçário. Métodos de marcação e recaptura foram utilizados no presente estudo para estimar o tamanho populacional e a sobrevivência de jovens tubarões-limão (Negaprion brevirostris) em uma área de berçário na Reserva Biológica do Atol das Rocas, Brasil. Os indivíduos foram amostrados entre 1999 e 2003 e as estimativas de tamanho populacional variaram entre 12 a 100 indivíduos jovens e a taxa de sobrevivência entre 24 e 54%, com média de 44,6% durante o período de amostragem mais robusto. A população destes tubarões jovens diminuiu ao longo de nosso estudo, ainda que as taxas de sobrevivência tenham aumentado durante o mesmo período. Mesmo um nível moderado de pesca e a remoção de fêmeas maduras em áreas adjacentes podem afetar dramaticamente pequenas populações de tubarões num berçário pequeno e isolado como o Atol das Rocas. As taxas de sobrevivência e tamanho populacional relativamente mais baixos em Rocas podem ser resultado das diferenças nas características físicas deste berçário, comparadas a outros utilizados pela espécie no Atlântico norte-ocidental. Tais parâmetros comparativamente mais baixos no Atol das Rocas sugerem a fragilidade da população jovem de tubarões-limão neste berçário.