908 resultados para population model


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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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A size-structured plant population model is developed to study the evolution of pathogen-induced leaf shedding under various environmental conditions. The evolutionary stable strategy (ESS) of the leaf shedding rate is determined for two scenarios: i) a constant leaf shedding strategy and ii) an infection load driven leaf shedding strategy. The model predicts that ESS leaf shedding rates increase with nutrient availability. No effect of plant density on the ESS leaf shedding rate is found even though disease severity increases with plant density. When auto-infection, that is increased infection due to spores produced on the plant itself, plays a key role in further disease increase on the plant, shedding leaves removes disease that would otherwise contribute to disease increase on the plant itself. Consequently leaf shedding responses to infections may evolve. When external infection, that is infection due to immigrant spores, is the key determinant, shedding a leaf does not reduce the force of infection on the leaf shedding plant. In this case leaf shedding will not evolve. Under a low external disease pressure adopting an infection driven leaf shedding strategy is more efficient than adopting a constant leaf shedding strategy, since a plant adopting an infection driven leaf shedding strategy does not shed any leaves in the absence of infection, even when leaf shedding rates are high. A plant adopting a constant leaf shedding rate sheds the same amount of leaves regardless of the presence of infection. Based on the results we develop two hypotheses that can be tested if the appropriate plant material is available.

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Bovine tuberculosis (TB)is an important economic disease. Badgers (Meles meles) are the wildlife source implicated in many cattle outbreaks of TB in Britain, and extensive badger control is a controversial option to reduce the disease. A badger and cattle population model was developed, simulating TB epidemiology; badger ecology, including postcull social perturbation; and TB-related farm management. An economic cost-benefit module was integrated into the model to assess whether badger control offers economic benefits. Model results strongly indicate that although, if perturbation were restricted, extensive badger culling could reduce rates in cattle, overall an economic loss would be more likely than a benefit. Perturbation of the badger population was a key factor determining success or failure of control. The model highlighted some important knowledge gaps regarding both the spatial and temporal characteristics of perturbation that warrant further research.

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A size-structured plant population model is developed to study the evolution of pathogen-induced leaf shedding under various environmental conditions. The evolutionary stable strategy (ESS) of the leaf shedding rate is determined for two scenarios: i) a constant leaf shedding strategy and ii) an infection load driven leaf shedding strategy. The model predicts that ESS leaf shedding rates increase with nutrient availability. No effect of plant density on the ESS leaf shedding rate is found even though disease severity increases with plant density. When auto-infection, that is increased infection due to spores produced on the plant itself, plays a key role in further disease increase on the plant, shedding leaves removes disease that would otherwise contribute to disease increase on the plant itself. Consequently leaf shedding responses to infections may evolve. When external infection, that is infection due to immigrant spores, is the key determinant, shedding a leaf does not reduce the force of infection on the leaf shedding plant. In this case leaf shedding will not evolve. Under a low external disease pressure adopting an infection driven leaf shedding strategy is more efficient than adopting a constant leaf shedding strategy, since a plant adopting an infection driven leaf shedding strategy does not shed any leaves in the absence of infection, even when leaf shedding rates are high. A plant adopting a constant leaf shedding rate sheds the same amount of leaves regardless of the presence of infection. Based on the results we develop two hypotheses that can be tested if the appropriate plant material is available.

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The potential risk of agricultural pesticides to mammals typically depends on internal concentrations within individuals, and these are determined by the amount ingested and by absorption, distribution, metabolism, and excretion (ADME). Pesticide residues ingested depend, amongst other things, on individual spatial choices which determine how much and when feeding sites and areas of pesticide application overlap, and can be calculated using individual-based models (IBMs). Internal concentrations can be calculated using toxicokinetic (TK) models, which are quantitative representations of ADME processes. Here we provide a population model for the wood mouse (Apodemus sylvaticus) in which TK submodels were incorporated into an IBM representation of individuals making choices about where to feed. This allows us to estimate the contribution of individual spatial choice and TK processes to risk. We compared the risk predicted by four IBMs: (i) “AllExposed-NonTK”: assuming no spatial choice so all mice have 100% exposure, no TK, (ii) “AllExposed-TK”: identical to (i) except that the TK processes are included where individuals vary because they have different temporal patterns of ingestion in the IBM, (iii) “Spatial-NonTK”: individual spatial choice, no TK, and (iv) “Spatial-TK”: individual spatial choice and with TK. The TK parameters for hypothetical pesticides used in this study were selected such that a conventional risk assessment would fail. Exposures were standardised using risk quotients (RQ; exposure divided by LD50 or LC50). We found that for the exposed sub-population including either spatial choice or TK reduced the RQ by 37–85%, and for the total population the reduction was 37–94%. However spatial choice and TK together had little further effect in reducing RQ. The reasons for this are that when the proportion of time spent in treated crop (PT) approaches 1, TK processes dominate and spatial choice has very little effect, and conversely if PT is small spatial choice dominates and TK makes little contribution to exposure reduction. The latter situation means that a short time spent in the pesticide-treated field mimics exposure from a small gavage dose, but TK only makes a substantial difference when the dose was consumed over a longer period. We concluded that a combined TK-IBM is most likely to bring added value to the risk assessment process when the temporal pattern of feeding, time spent in exposed area and TK parameters are at an intermediate level; for instance wood mice in foliar spray scenarios spending more time in crop fields because of better plant cover.

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We formulate an agent-based population model of Escherichia coli cells which incorporates a description of the chemotaxis signalling cascade at the single cell scale. The model is used to gain insight into the link between the signalling cascade dynamics and the overall population response to differing chemoattractant gradients. Firstly, we consider how the observed variation in total (phosphorylated and unphosphorylated) signalling protein concentration affects the ability of cells to accumulate in differing chemoattractant gradients. Results reveal that a variation in total cell protein concentration between cells may be a mechanism for the survival of cell colonies across a wide range of differing environments. We then study the response of cells in the presence of two different chemoattractants.In doing so we demonstrate that the population scale response depends not on the absolute concentration of each chemoattractant but on the sensitivity of the chemoreceptors to their respective concentrations. Our results show the clear link between single cell features and the overall environment in which cells reside.

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

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Conservation strategies for long-lived vertebrates require accurate estimates of parameters relative to the populations' size, numbers of non-breeding individuals (the “cryptic” fraction of the population) and the age structure. Frequently, visual survey techniques are used to make these estimates but the accuracy of these approaches is questionable, mainly because of the existence of numerous potential biases. Here we compare data on population trends and age structure in a bearded vulture (Gypaetus barbatus) population from visual surveys performed at supplementary feeding stations with data derived from population matrix-modelling approximations. Our results suggest that visual surveys overestimate the number of immature (<2 years old) birds, whereas subadults (3–5 y.o.) and adults (>6 y.o.) were underestimated in comparison with the predictions of a population model using a stable-age distribution. In addition, we found that visual surveys did not provide conclusive information on true variations in the size of the focal population. Our results suggest that although long-term studies (i.e. population matrix modelling based on capture-recapture procedures) are a more time-consuming method, they provide more reliable and robust estimates of population parameters needed in designing and applying conservation strategies. The findings shown here are likely transferable to the management and conservation of other long-lived vertebrate populations that share similar life-history traits and ecological requirements.

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The Janzen–Connell hypothesis proposes that specialized herbivores maintain high numbers of tree species in tropical forests by restricting adult recruitment so that host populations remain at low densities. We tested this prediction for the large timber tree species, Swietenia macrophylla, whose seeds and seedlings are preyed upon by small mammals and a host-specific moth caterpillar Steniscadia poliophaea, respectively. At a primary forest site, experimental seed additions to gaps – canopy-disturbed areas that enhance seedling growth into saplings – over three years revealed lower survival and seedling recruitment closer to conspecific trees and in higher basal area neighborhoods, as well as reduced subsequent seedling survival and height growth. When we included these Janzen–Connell effects in a spatially explicit individual-based population model, the caterpillar's impact was critical to limiting Swietenia's adult tree density, with a > 10-fold reduction estimated at 300 years. Our research demonstrates the crucial but oft-ignored linkage between Janzen–Connell effects on offspring and population-level consequences for a long-lived, potentially dominant tree species.

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A maximum likelihood estimator based on the coalescent for unequal migration rates and different subpopulation sizes is developed. The method uses a Markov chain Monte Carlo approach to investigate possible genealogies with branch lengths and with migration events. Properties of the new method are shown by using simulated data from a four-population n-island model and a source–sink population model. Our estimation method as coded in migrate is tested against genetree; both programs deliver a very similar likelihood surface. The algorithm converges to the estimates fairly quickly, even when the Markov chain is started from unfavorable parameters. The method was used to estimate gene flow in the Nile valley by using mtDNA data from three human populations.

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Queensland fruit fly, Bactrocera (Dacus) tryoni (QFF) is arguably the most costly horticultural insect pest in Australia. Despite this, no model is available to describe its population dynamics and aid in its management. This paper describes a cohort-based model of the population dynamics of the Queensland fruit fly. The model is primarily driven by weather variables, and so can be used at any location where appropriate meteorological data are available. In the model, the life cycle is divided into a number of discreet stages to allow physiological processes to be defined as accurately as possible. Eggs develop and hatch into larvae, which develop into pupae, which emerge as either teneral females or males. Both females and males can enter reproductive and over-wintering life stages, and there is a trapped male life stage to allow model predictions to be compared with trap catch data. All development rates are temperature-dependent. Daily mortality rates are temperature-dependent, but may also be influenced by moisture, density of larvae in fruit, fruit suitability, and age. Eggs, larvae and pupae all have constant establishment mortalities, causing a defined proportion of individuals to die upon entering that life stage. Transfer from one immature stage to the next is based on physiological age. In the adult life stages, transfer between stages may require additional and/or alternative functions. Maximum fecundity is 1400 eggs per female per day, and maximum daily oviposition rate is 80 eggs/female per day. The actual number of eggs laid by a female on any given day is restricted by temperature, density of larva in fruit, suitability of fruit for oviposition, and female activity. Activity of reproductive females and males, which affects reproduction and trapping, decreases with rainfall. Trapping of reproductive males is determined by activity, temperature and the proportion of males in the active population. Limitations of the model are discussed. Despite these, the model provides a useful agreement with trap catch data, and allows key areas for future research to be identified. These critical gaps in the current state of knowledge exist despite over 50 years of research on this key pest. By explicitly attempting to model the population dynamics of this pest we have clearly identified the research areas that must be addressed before progress can be made in developing the model into an operational tool for the management of Queensland fruit fly. (C) 2003 Published by Elsevier B.V.

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Background: Oral itraconazole (ITRA) is used for the treatment of allergic bronchopulmonary aspergillosis in patients with cystic fibrosis (CF) because of its antifungal activity against Aspergillus species. ITRA has an active hydroxy-metabolite (OH-ITRA) which has similar antifungal activity. ITRA is a highly lipophilic drug which is available in two different oral formulations, a capsule and an oral solution. It is reported that the oral solution has a 60% higher relative bioavailability. The influence of altered gastric physiology associated with CF on the pharmacokinetics (PK) of ITRA and its metabolite has not been previously evaluated. Objectives: 1) To estimate the population (pop) PK parameters for ITRA and its active metabolite OH-ITRA including relative bioavailability of the parent after administration of the parent by both capsule and solution and 2) to assess the performance of the optimal design. Methods: The study was a cross-over design in which 30 patients received the capsule on the first occasion and 3 days later the solution formulation. The design was constrained to have a maximum of 4 blood samples per occasion for estimation of the popPK of both ITRA and OH-ITRA. The sampling times for the population model were optimized previously using POPT v.2.0.[1] POPT is a series of applications that run under MATLAB and provide an evaluation of the information matrix for a nonlinear mixed effects model given a particular design. In addition it can be used to optimize the design based on evaluation of the determinant of the information matrix. The model details for the design were based on prior information obtained from the literature, which suggested that ITRA may have either linear or non-linear elimination. The optimal sampling times were evaluated to provide information for both competing models for the parent and metabolite and for both capsule and solution simultaneously. Blood samples were assayed by validated HPLC.[2] PopPK modelling was performed using FOCE with interaction under NONMEM, version 5 (level 1.1; GloboMax LLC, Hanover, MD, USA). The PK of ITRA and OH‑ITRA was modelled simultaneously using ADVAN 5. Subsequently three methods were assessed for modelling concentrations less than the LOD (limit of detection). These methods (corresponding to methods 5, 6 & 4 from Beal[3], respectively) were (a) where all values less than LOD were assigned to half of LOD, (b) where the closest missing value that is less than LOD was assigned to half the LOD and all previous (if during absorption) or subsequent (if during elimination) missing samples were deleted, and (c) where the contribution of the expectation of each missing concentration to the likelihood is estimated. The LOD was 0.04 mg/L. The final model evaluation was performed via bootstrap with re-sampling and a visual predictive check. The optimal design and the sampling windows of the study were evaluated for execution errors and for agreement between the observed and predicted standard errors. Dosing regimens were simulated for the capsules and the oral solution to assess their ability to achieve ITRA target trough concentration (Cmin,ss of 0.5-2 mg/L) or a combined Cmin,ss for ITRA and OH-ITRA above 1.5mg/L. Results and Discussion: A total of 241 blood samples were collected and analysed, 94% of them were taken within the defined optimal sampling windows, of which 31% where taken within 5 min of the exact optimal times. Forty six per cent of the ITRA values and 28% of the OH-ITRA values were below LOD. The entire profile after administration of the capsule for five patients was below LOD and therefore the data from this occasion was omitted from estimation. A 2-compartment model with 1st order absorption and elimination best described ITRA PK, with 1st order metabolism of the parent to OH-ITRA. For ITRA the clearance (ClItra/F) was 31.5 L/h; apparent volumes of central and peripheral compartments were 56.7 L and 2090 L, respectively. Absorption rate constants for capsule (kacap) and solution (kasol) were 0.0315 h-1 and 0.125 h-1, respectively. Comparative bioavailability of the capsule was 0.82. There was no evidence of nonlinearity in the popPK of ITRA. No screened covariate significantly improved the fit to the data. The results of the parameter estimates from the final model were comparable between the different methods for accounting for missing data, (M4,5,6)[3] and provided similar parameter estimates. The prospective application of an optimal design was found to be successful. Due to the sampling windows, most of the samples could be collected within the daily hospital routine, but still at times that were near optimal for estimating the popPK parameters. The final model was one of the potential competing models considered in the original design. The asymptotic standard errors provided by NONMEM for the final model and empirical values from bootstrap were similar in magnitude to those predicted from the Fisher Information matrix associated with the D-optimal design. Simulations from the final model showed that the current dosing regimen of 200 mg twice daily (bd) would provide a target Cmin,ss (0.5-2 mg/L) for only 35% of patients when administered as the solution and 31% when administered as capsules. The optimal dosing schedule was 500mg bd for both formulations. The target success for this dosing regimen was 87% for the solution with an NNT=4 compared to capsules. This means, for every 4 patients treated with the solution one additional patient will achieve a target success compared to capsule but at an additional cost of AUD $220 per day. The therapeutic target however is still doubtful and potential risks of these dosing schedules need to be assessed on an individual basis. Conclusion: A model was developed which described the popPK of ITRA and its main active metabolite OH-ITRA in adult CF after administration of both capsule and solution. The relative bioavailability of ITRA from the capsule was 82% that of the solution, but considerably more variable. To incorporate missing data, using the simple Beal method 5 (using half LOD for all samples below LOD) provided comparable results to the more complex but theoretically better Beal method 4 (integration method). The optimal sparse design performed well for estimation of model parameters and provided a good fit to the data.

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Objectives: The aim of the study was to characterise the population pharmacokinetics (popPK) properties of itraconazole (ITRA) and its active metabolite hydroxy-ITRA in a representative paediatric population of cystic fibrosis (CF) and bone marrow transplant (BMT) patients. The goals were to determine the relative bioavailability between the two oral formulations, and to explore improved dosage regimens in these patients. Methods: All paediatric patients with CF taking oral ITRA for the treatment of allergic bronchopulmonary aspergillosis and patients undergoing BMT who were taking ITRA for prophylaxis of any fungal infection were eligible for the study. A minimum of two blood samples were drawn after the capsules and also after switching to oral solution, or vice versa. ITRA and hydroxy-ITRA plasma concentrations were measured by HPLC[1]. A nonlinear mixed-effect modelling approach (NONMEM 5.1.1) was used to describe the PK of ITRA and hydroxy-ITRA simultaneously. Simulations were used to assess dosing strategies in these patients. Results: Forty-nine patients (29CF, 20 BMT) were recruited to the study who provided 227 blood samples for the population analysis. A 1-compartment model with 1st order absorption and elimination best described ITRA kinetics, with 1st order conversion to hydroxy-ITRA. For ITRA, the apparent clearance (ClItra/F) and volume of distribution (Vitra/F) was 35.5L/h and 672L, respectively; the absorption rate constant for the capsule formulation was 0.0901 h-1 and for the oral solution formulation it was 0.959 h-1. The capsule comparative bioavailability (vs. solution) was 0.55. For hydroxy-ITRA, the apparent volume of distribution and clearance were 10.6 L and 5.28 L/h, respectively. Of several screened covariates only allometrically scaled total body weight significantly improved the fit to the data. No difference between the two populations was found. Conclusion: The developed popPK model adequately described the pharmacokinetics of ITRA and hydroxy-ITRA in paediatric patients with CF and patients undergoing BMT. High inter-patient variability confirmed previous data in CF[2], leukaemia and BMT[3] patients. From the population model, simulations showed the standard dose (5 mg/kg/day) needs to be doubled for the solution formulation and even 4 times more given of the capsules to achieve an adequate target therapeutic trough plasma concentration of 0.5 mg/L[4] in these patients.

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Gating of sensory (e.g. auditory) information has been demonstrated as a reduction in the auditory-evoked potential responses recorded in the brain of both normal animals and human subjects. Auditory gating is perturbed in schizophrenic patients and pharmacologically by drugs such as amphetamine, phencyclidine or ketamine, which precipitate schizophrenic-like symptoms in normal subjects. The neurobiological basis underlying this sensory gating can be investigated using local field potential recordings from single electrodes. In this paper we use such technology to investigate the role of cannabinoids in sensory gating. Cannabinoids represent a fundamentally new class of retrograde messengers which are released postsynaptically and bind to presynaptic receptors. In this way they allow fine-tuning of neuronal response, and in particular can lead to so-called depolarization-induced suppression of inhibition (DSI). Our experimental results show that application of the exogenous cannabinoid WIN55, 212-2 can abolish sensory gating as measured by the amplitude of local field responses in rat hippocampal region CA3. Importantly we develop a simple firing rate population model of CA3 and show that gating is heavily dependent upon the presence of a slow inhibitory (GABAB) pathway. Moreover, a simple phenomenological model of cannabinoid dynamics underlying DSI is shown to abolish gating in a manner consistent with our experimental findings.

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Roads represent a new source of mortality due to animal-vehicle risk of collision threatening log-term populations’ viability. Risk of road-kill depends on species sensitivity to roads and their specific life-history traits. The risk of road mortality for each species depends on the characteristics of roads and bioecological characteristics of the species. In this study we intend to know the importance of climatic parameters (temperature and precipitation) together with traffic and life history traits and understand the role of drought in barn owl population viability, also affected by road mortality in three scenarios: high mobility, high population density and the combination of previous scenarios (mixed) (Manuscript). For the first objective we correlated the several parameters (climate, traffic and life history traits). We used the most correlated variables to build a predictive mixed model (GLMM) the influence of the same. Using a population model we evaluated barn owl population viability in all three scenarios. Model revealed precipitation, traffic and dispersal have negative relationship with road-kills, although the relationship was not significant. Scenarios showed different results, high mobility scenario showed greater population depletion, more fluctuations over time and greater risk of extinction. High population density scenario showed a more stable population with lower risk of extinction and mixed scenario showed similar results as first scenario. Climate seems to play an indirect role on barn owl road-kills, it may influence prey availability which influences barn owl reproductive success and activity. Also, high mobility scenario showed a greater negative impact on viability of populations which may affect their ability and resilience to other stochastic events. Future research should take in account climate and how it may influence species life cycles and activity periods for a more complete approach of road-kills. Also it is important to make the best mitigation decisions which might include improving prey quality habitat.