949 resultados para population size


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Understanding the spatial integrity and connectivity of jellyfish blooms is important for ecologists and coastal stakeholders alike. Previous studies have shown that the distribution of jellyfish blooms can display a marked consistency in space and time, suggesting that such patterns cannot be attributed to passive processes alone. In the present study, we used a combination of microsatellite markers and mitochondrial cytochrome oxidase I sequences to investigate genetic structuring of the scyphozoan jellyfish Rhizostoma octopus in the Irish and Celtic Seas. The mitochondrial data indicated far higher levels of population differentiation than the microsatellites: ΦST[MT] = 0.300 vs. ΦST[NUC] = 0.013. Simulation studies indicated that the low levels of nuclear differentiation were not the result of limited power because of low levels of polymorphism. These findings, supported by palaeodistribution modelling and mismatch distribution analysis, are consistent with expansion of R. octopus from a single, limited refugium after the Last Glacial Maximum, followed by subsequent isolation, and that the discrepancy between the mitochondrial and nuclear markers is a result of the nuclear loci taking longer to reach mutation–drift equilibrium following the expansion as a result of their four-fold larger effective population size. The populations studied are probably not well connected via gene flow, and thus genetically as well as geographically distinct, although our findings also highlight the need to use a combination of organellar and nuclear markers to enable a more complete understanding of population demography and structure, particularly for species with large effective population sizes.

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Free-roaming dogs (FRD) represent a potential threat to the quality of life in cities from an ecological, social and public health point of view. One of the most urgent concerns is the role of uncontrolled dogs as reservoirs of infectious diseases transmittable to humans and, above all, rabies. An estimate of the FRD population size and characteristics in a given area is the first step for any relevant intervention programme. Direct count methods are still prominent because of their non-invasive approach, information technologies can support such methods facilitating data collection and allowing for a more efficient data handling. This paper presents a new framework for data collection using a topological algorithm implemented as ArcScript in ESRI® ArcGIS software, which allows for a random selection of the sampling areas. It also supplies a mobile phone application for Android® operating system devices which integrates Global Positioning System (GPS) and Google Maps™. The potential of such a framework was tested in 2 Italian regions. Coupling technological and innovative solutions associated with common counting methods facilitate data collection and transcription. It also paves the way to future applications, which could support dog population management systems.

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Dissertação de Mestrado, Biologia Marinha, Especialização em Ecologia e Conservação, Faculdade de Ciências do Mar e do Ambiente, Universidade do Algarve, 2007

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Fluctuations in ammonium (NH4+), measured as NH4-N loads using an ion-selective electrode installed at the inlet of a sewage treatment plant, showed a distinctive pattern which was associated to weekly (i.e., commuters) and seasonal (i.e., holidays) fluctuations of the population. Moreover, population size estimates based on NH4-N loads were lower compared to census data. Diurnal profiles of benzoylecgonine (BE) and 11-nor-9-carboxy-Δ9-tetrahydrocannabinol (THC-COOH) were shown to be strongly correlated to NH4-N. Characteristic patterns, which reflect the prolonged nocturnal activity of people during the weekend, could be observed for BE, cocaine, and a major metabolite of MDMA (i.e., 4-hydroxy-3-methoxymethamphetamine). Additional 24 h composite samples were collected between February and September 2013. Per-capita loads (i.e., grams per day per 1000 inhabitants) were computed using census data and NH4-N measurements. Normalization with NH4-N did not modify the overall pattern, suggesting that the magnitude of fluctuations in the size of the population is negligible compared to those of illicit drug loads. Results show that fluctuations in the size of the population over longer periods of time or during major events can be monitored using NH4-N loads: either using raw NH4-N loads or population size estimates based on NH4-N loads, if information about site-specific NH4-N population equivalents is available.

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In some fishes, water chemistry or temperature affects sex determination or creates sex-specific selection pressures. The resulting population sex ratios are hard to predict from laboratory studies if the environmental triggers interact with other factors, whereas in field studies, singular observations of unusual sex ratios may be particularly prone to selective reporting. Long-term monitoring largely avoids these problems. We studied a population of grayling (Thymallus thymallus) in Lake Thun, Switzerland, that has been monitored since 1948. Samples of spawning fish have been caught about 3 times/week around spawning season, and water temperature at the spawning site has been continuously recorded since 1970. We used scale samples collected in different years to determine the average age of spawners (for life-stage specific analyses) and to identify the cohort born in 2003 (an extraordinarily warm year). Recent tissue samples were genotyped on microsatellite markers to test for genetic bottlenecks in the past and to estimate the genetically effective population size (N(e) ). Operational sex ratios changed from approximately 65% males before 1993 to approximately 85% males from 1993 to 2011. Sex ratios correlated with the water temperatures the fish experienced in their first year of life. Sex ratios were best explained by the average temperature juvenile fish experienced during their first summer. Grayling abundance is declining, but we found no evidence of a strong genetic bottleneck that would explain the apparent lack of evolutionary response to the unequal sex ratio. Results of other studies show no evidence of endocrine disruptors in the study area. Our findings suggest temperature affects population sex ratio and thereby contributes to population decline. Persistencia de Proporción de Sexos Desigual en una Población de Tímalos (Salmonidae) y el Posible Papel del Incremento de la Temperatura.

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Six large-bodied, ≥ 120 g, woodpecker species are listed as near-threatened to critically endangered by the International Union for Conservation of Nature (IUCN). The small population paradigm assumes that these populations are likely to become extinct without an increase in numbers, but the combined influences of initial population size and demographic rates, i.e., annual adult survival and fecundity, may drive population persistence for these species. We applied a stochastic, stage-based single-population model to available demographic rates for Dryocopus and Campephilus woodpeckers. In particular, we determined the change in predicted extinction rate, i.e., proportion of simulated populations that went extinct within 100 yr, to concomitant changes in six input parameters. To our knowledge, this is the first study to evaluate the combined importance of initial population size and demographic rates for the persistence of large-bodied woodpeckers. Under a worse-case scenario, the median time to extinction was 7 yr (range: 1–32). Across the combinations of other input values, increasing initial population size by one female induced, on average, 0.4%–3.2% (range: 0%–28%) reduction in extinction rate. Increasing initial population size from 5–30 resulted in extinction rates < 0.05 under limited conditions: (1) all input values were intermediate, or (2) Allee effect present and annual adult survival ≥ 0.8. Based on our model, these species can persist as rare, as few as five females, and thus difficult-to-detect, populations provided they maintain ≥ 1.1 recruited females annually per adult female and an annual adult survival rate ≥ 0.8. Athough a demographic-based population viability analysis (PVA) is useful to predict how extinction rate changes across scenarios for life-history attributes, the next step for modeling these populations should incorporate more easily acquired data on changes in patch occupancy to make predictions about patch colonization and extinction rates.

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We hypothesized that although large populations may appear able to withstand predation and disturbance, added stochasticity in population growth rate (λ) increases the risk of dramatic population declines. Approximately half of the Aleutian Islands' population of Least Auklets (Aethia pusilla) breed at one large colony at Kiska Island in the presence of introduced Norway rats (Rattus norvegicus) whose population erupts periodically. We evaluated two management plans, do nothing or eradicate rats, for this colony, and performed stochastic elasticity analysis to focus future research and management. Our results indicated that Least Auklets breeding at Kiska Island had the lowest absolute value of growth rate and more variable λ's (neither statistically significant) during 2001-2010, when compared with rat-free colonies at Buldir and Kasatochi islands. We found variability in the annual proportional change in population size among islands with Kiska Island having the fastest rate of decline, 78% over 20 years. Under the assumption that the eradication of rats would result in vital rates similar to those observed at rat-free Buldir and Kasatochi islands, we found the projected population decline decreased from 78% to 24% over 20 years. Overall, eradicating rats at Kiska Island is not likely to increase Least Auklet vital rates, but will decrease the amount of variation in λ, resulting in a significantly slower rate of population decline. We recommend the eradication of rats from Kiska Island to decrease the probability of dramatic population declines and ensure the future persistence of this important colony.

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Worldwide marine protected areas (MPAs) have been designated to protect marine resources, including top predators such as seabirds. There is no conclusive information on whether protected areas can improve population trends of seabirds when these are further exploited as tourist attractions, an activity that has increased in past decades. Humboldt Penguins (Spheniscus humboldti) and Magellanic Penguins (S. magellanicus) breed sympatrically on Puñihuil Islets, two small coastal islands off the west coast of Chiloé Island (41° S) in southern Chile that are subject to exploitation for tourism. Our goal was to compare the population size of the mixed colony of Humboldt and Magellanic Penguins before and after protection from unregulated tourism and freely roaming goats in 1997. For this purpose, two censuses were conducted in 2004 and 2008, and the numbers compared with those obtained in 1997 by other authors. The proportion of occupied, unoccupied, and collapsed/flooded burrows changed between years; there were 68% and 34% fewer collapsed burrows in 2004 and 2008, respectively, than in 1997. For the total number of burrows of both species, we counted 48% and 63% more burrows in 2004 and 2008, respectively, than in 1997. We counted 13% more burrows of Humboldt Penguins in 2008 than in 1997, and for Magellanic Penguins, we estimated a 64% increase in burrows in 2008. Presumably, this was as a result of habitat improvement attributable to the exclusion of tourists and the removal of goats from the islets. Although tourist visits to the islets are prohibited, tourism activities around the colonies are prevalent and need to be taken into account to promote appropriate management.

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1. Habitat fragmentation can affect pollinator and plant population structure in terms of species composition, abundance, area covered and density of flowering plants. This, in turn, may affect pollinator visitation frequency, pollen deposition, seed set and plant fitness. 2. A reduction in the quantity of flower visits can be coupled with a reduction in the quality of pollination service and hence the plants’ overall reproductive success and long-term survival. Understanding the relationship between plant population size and⁄ or isolation and pollination limitation is of fundamental importance for plant conservation. 3. Weexamined flower visitation and seed set of 10 different plant species fromfive European countries to investigate the general effects of plant populations size and density, both within (patch level) and between populations (population level), on seed set and pollination limitation. 4. Wefound evidence that the effects of area and density of flowering plant assemblages were generally more pronounced at the patch level than at the population level. We also found that patch and population level together influenced flower visitation and seed set, and the latter increased with increasing patch area and density, but this effect was only apparent in small populations. 5. Synthesis. By using an extensive pan-European data set on flower visitation and seed set we have identified a general pattern in the interplay between the attractiveness of flowering plant patches for pollinators and density dependence of flower visitation, and also a strong plant species-specific response to habitat fragmentation effects. This can guide efforts to conserve plant–pollinator interactions, ecosystem functioning and plant fitness in fragmented habitats.

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In this paper we consider the estimation of population size from onesource capture–recapture data, that is, a list in which individuals can potentially be found repeatedly and where the question is how many individuals are missed by the list. As a typical example, we provide data from a drug user study in Bangkok from 2001 where the list consists of drug users who repeatedly contact treatment institutions. Drug users with 1, 2, 3, . . . contacts occur, but drug users with zero contacts are not present, requiring the size of this group to be estimated. Statistically, these data can be considered as stemming from a zero-truncated count distribution.We revisit an estimator for the population size suggested by Zelterman that is known to be robust under potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a locally truncated Poisson likelihood which is equivalent to a binomial likelihood. This result allows the extension of the Zelterman estimator by means of logistic regression to include observed heterogeneity in the form of covariates. We also review an estimator proposed by Chao and explain why we are not able to obtain similar results for this estimator. The Zelterman estimator is applied in two case studies, the first a drug user study from Bangkok, the second an illegal immigrant study in the Netherlands. Our results suggest the new estimator should be used, in particular, if substantial unobserved heterogeneity is present.

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Spatial processes could play an important role in density-dependent population regulation because the disproportionate use of poor quality habitats as population size increases is widespread in animal populations-the so-called buffer effect. While the buffer effect patterns and their demographic consequences have been described in a number of wild populations, much less is known about how dispersal affects distribution patterns and ultimately density dependence. Here, we investigated the role of dispersal in spatial density dependence using an extraordinarily detailed dataset from a reintroduced Mauritius kestrel (Falco punctatus) population with a territorial (despotic) breeding system. We show that recruitment rates varied significantly between territories, and that territory occupancy was related to its recruitment rate, both of which are consistent with the buffer effect theory. However, we also show that restricted dispersal affects the patterns of territory occupancy with the territories close to release sites being occupied sooner and for longer as the population has grown than the territories further away. As a result of these dispersal patterns, the strength of spatial density dependence is significantly reduced. We conclude that restricted dispersal can modify spatial density dependence in the wild, which has implications for the way population dynamics are likely to be impacted by environmental change.

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The theta-logistic is a widely used generalisation of the logistic model of regulated biological processes which is used in particular to model population regulation. Then the parameter theta gives the shape of the relationship between per-capita population growth rate and population size. Estimation of theta from population counts is however subject to bias, particularly when there are measurement errors. Here we identify factors disposing towards accurate estimation of theta by simulation of populations regulated according to the theta-logistic model. Factors investigated were measurement error, environmental perturbation and length of time series. Large measurement errors bias estimates of theta towards zero. Where estimated theta is close to zero, the estimated annual return rate may help resolve whether this is due to bias. Environmental perturbations help yield unbiased estimates of theta. Where environmental perturbations are large, estimates of theta are likely to be reliable even when measurement errors are also large. By contrast where the environment is relatively constant, unbiased estimates of theta can only be obtained if populations are counted precisely Our results have practical conclusions for the design of long-term population surveys. Estimation of the precision of population counts would be valuable, and could be achieved in practice by repeating counts in at least some years. Increasing the length of time series beyond ten or 20 years yields only small benefits. if populations are measured with appropriate accuracy, given the level of environmental perturbation, unbiased estimates can be obtained from relatively short censuses. These conclusions are optimistic for estimation of theta. (C) 2008 Elsevier B.V All rights reserved.

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Genetic data obtained on population samples convey information about their evolutionary history. Inference methods can extract part of this information but they require sophisticated statistical techniques that have been made available to the biologist community (through computer programs) only for simple and standard situations typically involving a small number of samples. We propose here a computer program (DIY ABC) for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples. Such scenarios involve any combination of population divergences, admixtures and population size changes. DIY ABC can be used to compare competing scenarios, estimate parameters for one or more scenarios and compute bias and precision measures for a given scenario and known values of parameters (the current version applies to unlinked microsatellite data). This article describes key methods used in the program and provides its main features. The analysis of one simulated and one real dataset, both with complex evolutionary scenarios, illustrates the main possibilities of DIY ABC.

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We argue that population modeling can add value to ecological risk assessment by reducing uncertainty when extrapolating from ecotoxicological observations to relevant ecological effects. We review other methods of extrapolation, ranging from application factors to species sensitivity distributions to suborganismal (biomarker and "-omics'') responses to quantitative structure activity relationships and model ecosystems, drawing attention to the limitations of each. We suggest a simple classification of population models and critically examine each model in an extrapolation context. We conclude that population models have the potential for adding value to ecological risk assessment by incorporating better understanding of the links between individual responses and population size and structure and by incorporating greater levels of ecological complexity. A number of issues, however, need to be addressed before such models are likely to become more widely used. In a science context, these involve challenges in parameterization, questions about appropriate levels of complexity, issues concerning how specific or general the models need to be, and the extent to which interactions through competition and trophic relationships can be easily incorporated.

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This article introduces a new general method for genealogical inference that samples independent genealogical histories using importance sampling (IS) and then samples other parameters with Markov chain Monte Carlo (MCMC). It is then possible to more easily utilize the advantages of importance sampling in a fully Bayesian framework. The method is applied to the problem of estimating recent changes in effective population size from temporally spaced gene frequency data. The method gives the posterior distribution of effective population size at the time of the oldest sample and at the time of the most recent sample, assuming a model of exponential growth or decline during the interval. The effect of changes in number of alleles, number of loci, and sample size on the accuracy of the method is described using test simulations, and it is concluded that these have an approximately equivalent effect. The method is used on three example data sets and problems in interpreting the posterior densities are highlighted and discussed.