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PubMed2001

Spatially structured metapopulation models: global and local assessment of metapopulation capacity.

We model metapopulation dynamics in finite networks of discrete habitat patches with given areas and spatial locations. We define and analyze two simple and ecologically intuitive measures of the capacity of the habitat patch network to support a viable metapopulation. Metapopulation persistence capacity lambda(M) defines the threshold condition for long-term metapopulation persistence as lambda(M)>delta, where delta is defined by the extinction and colonization rate parameters of the focal species. Metapopulation invasion capacity lambda(I) sets the condition for successful invasion of an empty network from one small local population as lambda(I)>delta. The metapopulation capacities lambda(M) and lambda(I) are defined as the leading eigenvalue or a comparable quantity of an appropriate "landscape" matrix. Based on these definitions, we present a classification of a very general class of deterministic, continuous-time and discrete-time metapopulation models. Two specific models are analyzed in greater detail: a spatially realistic version of the continuous-time Levins model and the discrete-time incidence function model with propagule size-dependent colonization rate and a rescue effect. In both models we assume that the extinction rate increases with decreasing patch area and that the colonization rate increases with patch connectivity. In the spatially realistic Levins model, the two types of metapopulation capacities coincide, whereas the incidence function model possesses a strong Allee effect characterized by lambda(I)=0. For these two models, we show that the metapopulation capacities can be considered as simple sums of contributions from individual habitat patches, given by the elements of the leading eigenvector or comparable quantities. We may therefore assess the significance of particular habitat patches, including new patches that might be added to the network, for the metapopulation capacities of the network as a whole. We derive useful approximations for both the threshold conditions and the equilibrium states in the two models. The metapopulation capacities and the measures of the dynamic significance of particular patches can be calculated for real patch networks for applications in metapopulation ecology, landscape ecology, and conservation biology.

Animals↗

PubMed2002

Evaluation of a forage allocation model for Theodore Roosevelt National Park.

We developed a forage allocation model using a deterministic, linear optimization module in a commercially available spreadsheet package to help resource managers in Theodore Roosevelt National Park (TRNP), North Dakota determine optimum numbers of four ungulate species, bison (Bison bison), elk (Cervus elaphus), mule deer (Odocoileus hemionus), and feral horses, in the Park. TRNP staff actively managed bison, elk, and feral horse numbers within bounds suggested by our model from 1983 to 1996. During this period, we measured vegetation at 8 grassland and 12 wooded sites at 1-3 year intervals to determine if model solutions were appropriate for maintaining stable conditions in important plant communities in the Park. The data we recorded at these sites indicated minimal change in plant communities from 1983 to 1996. Changes in most vegetation categories that we expected when animal numbers exceeded model optimums for short periods (decreases in coverage/stem numbers of palatable plant species, increases in bare ground or unpalatable plant species) did not occur consistently under high or low precipitation conditions. The lack of sensitivity of our model to decreases in overall production of palatable plant species that occurred due to drought, fire, expansion of black-tailed prairie dog (Cynomys ludovicianus) colonies, and the spread of leafy spurge (Euphorbia esula) in areas of the Park where we did not have monitoring sites suggested that the model under-estimated the total number of ungulates that the Park could support. Management for population levels of ungulates defined by the model probably led to over protection of common plant communities and insufficient protection of rare plant communities. Detecting changes in rare plant communities could have been accomplished by re-designing our vegetation monitoring program, but changing emphasis to protection of rare plants would have likely promoted under use of grazing-tolerant habitat types, dissatisfaction in tourists visiting the Park to see large mammals, and large increases in cost and intrusiveness of management activities such as fencing and control of ungulate populations. The model was a flawed representation of grazing dynamics in TRNP, but we believe it succeeded in making management personnel aware of the biological constraints they face when making management decisions.

Animals↗

PubMed2005

Evaluation of radiation dose to patients during abdominal embolizations.

BACKGROUND: Abdominal embolization procedures performed using digital subtraction angiography (DSA) is on the increase in the present-day scenario owing to their diagnostic and therapeutic values. These procedures involve prolonged fluoroscopy times and may tend to impart high radiation dose to patients if adequate radiation safety measures are not taken. AIM: To evaluate radiation dose imparted to patients and the work practices involved therein during abdominal embolization procedures. MATERIALS AND METHODS: Forty-two patients who underwent abdominal embolizations performed using DSA equipment were included in the study. Dose area product (DAP) was measured using DAP meter and values obtained were used for calculating entrance surface dose (ESD). Work practices of personnel involved in conducting the procedure were evaluated based on the choice of field sizes, selection of appropriate fluoro-modes, and optimization techniques. RESULTS AND CONCLUSIONS: The mean ESD values during hepatic embolization, renal embolization, splenic artery embolization and transarterial chemoembolization (TACE) were 1.2, 1.01, 1.19, and 1.03, respectively. No deterministic effects of radiation, such as transient or main erythema, were noticed for a few patients whose doses exceeded the threshold doses.

Abdomen↗

PubMedDate not supplied

Confidence intervals for cost-effectiveness ratios: an application of Fieller's theorem.

Application of cost-effectiveness analysis (CEA) is growing rapidly in health care. Two general approaches to analysis are differentiated by the type of data available: (i) deterministic models based upon secondary analysis of retrospective data from one or more trials and other sources; and (ii) stochastic analyses in which the design of a randomized controlled trial is adapted to collect prospectively patient-specific data on costs and effectiveness. An important methodological difference between these two approaches is in how uncertainty is handled. Deterministic CEA models typically rely upon sensitivity analysis to determine the robustness of findings to alternative assumptions, whereas stochastic (CEA) analysis, as part of prospective studies, permits the use of conventional statistical methods on the cost and effectiveness data for both inference (hypothesis testing) and estimation. This paper presents a procedure for the statistical analysis of cost-effectiveness data, with specific application to those studies for which effectiveness is measured as a binary outcome. Specifically, Fieller's Theorem was used to calculate confidence intervals for ratios of the two random variables of between-treatment differences in observed costs and effectiveness, i.e. the incremental cost-effectiveness ratio.

Computer Simulation↗

PubMed2000

Application of artificial neural networks to modeling and prediction of ambient ozone concentrations.

The deterministic modeling of ambient O3 concentrations is difficult because of the complexity of the atmospheric system in terms of the number of chemical species; the availability of accurate, time-resolved emissions data; and the required rate constants. However, other complex systems have been successfully approximated using artificial neural networks (ANNs). In this paper, ANNs are used to model and predict ambient O3 concentrations based on a limited number of measured hydrocarbon species, NOx compounds, temperature, and radiant energy. In order to examine the utility of these approaches, data from the Coastal Oxidant Assessment for Southeast Texas (COAST) program in Houston, TX, have been used. In this study, 53 hydrocarbon compounds, along with O3, nitrogen oxides, and meteorological data were continuously measured during summer 1993. Steady-state ANN models were developed to examine the ability of these models to predict current O3 concentrations from measured VOC and NOx concentrations. To predict the future concentrations of O3, dynamic models were also explored and were used for extraction of chemical information such as reactivity estimations for the VOC species. The steady-state model produced an approximation of O3 data and demonstrated the functional relationship between O3 and VOC-NOx concentrations. The dynamic models were able to the adequately predict the O3 concentration and behavior of VOC-NOx-O3 system a number of hourly intervals into the future. For 3 hr into the future, O3 concentration could be predicted with a root-mean squared error (RMSE) of 8.21 ppb. Extending the models further in time led to an RMSE of 11.46 ppb for 5-hr-ahead values. This prediction capability could be useful in determining when control actions are needed to maintain measured concentrations within acceptable value ranges.

Air Pollution↗

PubMed2004

Habitat selection and population regulation in temporally fluctuating environments.

Understanding and predicting the distribution of organisms in heterogeneous environments lies at the heart of ecology, and the theory of density-dependent habitat selection (DDHS) provides ecologists with an inferential framework linking evolution and population dynamics. Current theory does not allow for temporal variation in habitat quality, a serious limitation when confronted with real ecological systems. We develop both a stochastic equivalent of the ideal free distribution to study how spatial patterns of habitat use depend on the magnitude and spatial correlation of environmental stochasticity and also a stochastic habitat selection rule. The emerging patterns are confronted with deterministic predictions based on isodar analysis, an established empirical approach to the analysis of habitat selection patterns. Our simulations highlight some consistent patterns of habitat use, indicating that it is possible to make inferences about the habitat selection process based on observed patterns of habitat use. However, isodar analysis gives results that are contingent on the magnitude and spatial correlation of environmental stochasticity. Hence, DDHS is better revealed by a measure of habitat selectivity than by empirical isodars. The detection of DDHS is but a small component of isodar theory, which remains an important conceptual framework for linking evolutionary strategies in behavior and population dynamics.

Animals↗

PubMed2005

Physiologically precise simulation of multiple lung gas exchange during anaesthesia by simultaneous gas infusion and extraction.

UNLABELLED: A lung gas exchange simulator was tested which produces simultaneous uptake and/or elimination of multiple gases by an artificial test lung with physiologically realistic gas expired and exhaust gas flows, using a combination of infusion of diluting/enriching gases into the lung with lung gas extraction. A deterministic algorithm is incorporated which calculates required gas infusion and extraction flow rates for any set of possible target gas exchange values with any given set of fresh gas flows and concentrations. Six different scenarios were simulated, comprising a range of gas exchange values for each gas species which lie within a physiologically realistic range for anaesthetized patients. For each of these experiments the system was tested for 15 consecutive measurements over 25 min by measurement of gas exchange in the system using the Haldane transformation. RESULTS: the mean bias and standard error of the mean bias (SE, in parentheses) relative to the target value was: +0.001 (0.002) l min(-1) for O(2) uptake, -0.002 (0.005) l min(-1) for CO(2) production, -0.001 (0.002) l min(-1) for uptake of nitrous oxide and +0.3 (0.1) ml min(-1) for uptake of a volatile anaesthetic agent (isoflurane). The confidence limits of the mean bias were within 5% of the target value for all gases and scenarios with the exception of those where a low uptake of anaesthetic gas was specified. The confidence limits of the mean bias for the lower uptakes of isoflurane were within 10% of the target value for these scenarios and within 15% for the low uptake of N(2)O. Good accuracy and precision of this approach to lung gas exchange simulation were demonstrated, resulting in a versatile simulator.

Algorithms↗

PubMed1998

Nonlinear dynamics of 3 Hz spike-and-wave discharges recorded during typical absence seizures in children.

One-channel routine recordings of the scalp electroencephalogram (EEG) from unmedicated children strictly classified as unprovoked typical (3 c/s) absence seizures were selected. The dynamics of spike-and-wave discharges (SWD) were then examined by means of autocorrelation, correlation dimension, averaged pointwise dimension and largest Lyapunov exponent. For one EEG signal with pronounced spike-and-wave (SW) patterns, these measures were used complementary to a surrogate data method, a nonlinear (SETAR) modeling approach, and a SW simulation procedure providing five types of SW test signals. The SETAR model exhibited stationary SW dynamics, visually very similar to the EEG target signal, and with clear nonlinear structure. According to the results, the EEG episodes investigated represent low-dimensional dynamics, possibly recorded during nonstationary periods. Arguments that justify the assumption of deterministic chaos in our EEG signals were not obtained with the current methods. From the results one may conclude that two global oscillatory modes are present for the model, and three modes are active during the EEG recording period.

Algorithms↗

PubMed2005

Probabilistic ecological risk assessment of 1,2,4-trichlorobenzene at a former industrial contaminated site.

Measured concentrations of 1,2,4-trichlorobenzene (1,2,4-TCB) in soil and groundwater detected in an industrial contaminated site were used to test several probabilistic options for refining site-specific ecological risks assessment, ranging from comparison of single effects and exposure values through comparison of probabilistic distributions for exposure and effects to the use of distribution based quotients (DBQs) obtained through Monte Carlo simulations. The results of the deterministic approach, which suggest that risk exceeds a level of concern for soil organisms, were influenced mainly by the presence of hot spots reaching concentrations able to affect acutely a large proportion of species, while the large majority of the area presents 1,2,4-TCB concentrations below those reported as toxic. Ground-(pore)water concentrations were compared with aquatic ecotoxicity data in orderto obtain an estimation of the potential risk for aquifers and streams in the adjacent area as well as for soil-dwelling organisms exposed via pore water. In this case, the risk is distributed over a large proportion of the site, while the local risk of hot spots was low, showing that risk characterization based exclusively on soil concentrations might be insufficient.

Animals↗

PubMed1997

Evaluation of an on-line patient exposure meter in neuroradiology.

PURPOSE: To assess the clinical performance and usefulness of an on-line patient exposure meter installed on a neuroradiologic biplane imaging system. MATERIALS AND METHODS: A commercial on-line patient exposure meter was installed on each plane of a biplane neuroradiologic imaging system. The meter computed skin exposures on the basis of selected technique factors (tube potential and current) and information about patient location relative to the x-ray tube. Simulations were performed to measure the system accuracy with an angiographic anthropomorphic head phantom with the skin exposures measured with an ionization chamber. Skin doses were computed for 114 consecutive patients who underwent diagnostic and interventional neuroradiologic procedures. RESULTS: Agreement between measured and computed skin exposures in fluoroscopy, plain radiography, and digital imaging was generally within 5% of the true skin dose. For all fluoroscopic and radiographic procedures, total median skin doses were 1.20 and 0.64 Gy for the frontal and lateral planes, respectively. In both planes, patient skin doses resulted primarily from digital subtraction angiographic acquisitions. In 29 (25%) patients, the skin dose exceeded 2.00 Gy, but no radiation-induced deterministic effects were observed. CONCLUSION: An on-line patient exposure meter can provide accurate radiation skin dose data in patients undergoing diagnostic and therapeutic neuroradiologic procedures.

Angiography↗

PubMed2003

Ortho-Babinet polarization-interrogating filter: an interferometric approach to polarization measurement.

A novel, interferometric, polarization-interrogating filter assembly and method for the simultaneous measurement of all four Stokes parameters across a partially polarized irradiance image in a no-moving-parts, instantaneous, highly sensitive manner is described. In the reported embodiment of the filter, two spatially varying linear retarders and a linear polarizer comprise an ortho-Babinet, polarization-interrogating (OBPI) filter. The OBPI filter uniquely encodes the incident ensemble of electromagnetic wave fronts comprising a partially polarized irradiance image in a controlled, deterministic, spatially varying manner to map the complete state of polarization across the image to local variations in a superposed interference pattern. Experimental interferograms are reported along with a numerical simulation of the method.

Journal Article↗

PubMed2005

Adjusting for partially missing baseline measurements in randomized trials.

Adjustment for baseline variables in a randomized trial can increase power to detect a treatment effect. However, when baseline data are partly missing, analysis of complete cases is inefficient. We consider various possible improvements in the case of normally distributed baseline and outcome variables. Joint modelling of baseline and outcome is the most efficient method. Mean imputation is an excellent alternative, subject to three conditions. Firstly, if baseline and outcome are correlated more than about 0.6 then weighting should be used to allow for the greater information from complete cases. Secondly, imputation should be carried out in a deterministic way, using other baseline variables if possible, but not using randomized arm or outcome. Thirdly, if baselines are not missing completely at random, then a dummy variable for missingness should be included as a covariate (the missing indicator method). The methods are illustrated in a randomized trial in community psychiatry.

Data Interpretation, Statistical↗

PubMed1989

Method of stochastic prediction of population estimates based on Kendall's birth and death process.

"An attempt has been made to incorporate density and time-dependent birth and death rates into the generalized birth and death process given by Kendall (1948). The probability generating function of the process has also been investigated. A simple method of estimating the parameters of the process has been illustrated in the text. The applicability of the method for predicting the population of India, starting from the several deterministic projection figures given for any base year, is also discussed in the text."

Asia↗

PubMed2003

Shape-invariant modeling of circadian rhythms with random effects and smoothing spline ANOVA decompositions.

Medical studies often collect physiological and/or psychological measurements over time from multiple subjects, to study dynamics such as circadian rhythms. Under the assumption that the expected response functions of all subjects are the same after shift and scale transformations, shape-invariant models have been applied to analyze this kind of data. The shift and scale parameters provide efficient and interpretable data summaries, while the common shape function is usually modeled nonparametrically, to provide flexibility. However, due to the deterministic nature of the shift and scale parameters, potential correlations within a subject are ignored. Furthermore, the shape of the common function may depend on other factors, such as disease. In this article, we propose shape-invariant mixed effects models. A second-stage model with fixed and random effects is used to model individual shift and scale parameters. A second-stage smoothing spline ANOVA model is used to study potential covariate effects on the common shape function. We apply our methods to a real data set to investigate disease effects on circadian rhythms of cortisol, a hormone that is affected by stress. We find that patients with Cushing's syndrome lost circadian rhythms and their 24-hour means were elevated to very high levels. Patients with major depression had the same circadian shape and phases as normal subjects. However, their 24-hour mean levels were elevated and amplitudes were dampened for some patients.

Analysis of Variance↗

PubMed2007

Models for assisted conception data with embryo-specific covariates.

Assisted conception routinely involves multiple embryo implantation within each recipient mother, with the outcome of interest being the number and multiplicity of live births. Here we consider the situation in which covariate information, potentially predictive of outcome, is available at the embryo level for each individual implanted embryo. This presents two challenges: firstly the outcome is measured at a higher, recipient, level than the covariates of interest; and secondly it is generally not known which of the implanted embryos developed to give a successful pregnancy. In practice such data have usually been analysed by aggregation of the embryo-level covariates to the recipient-level. Here we consider and compare two alternative approaches which respect the structure of the data alongside the aggregated approach. The first is a deterministic model with separate embryo and recipient success probabilities, each determined by a set of covariates, as first proposed by Spiers and extended by Zhou and Weinberg. The second is based on a multilevel model with the correlations between embryos in the same recipient modelled by a recipient level random effect. These models are compared using two real data sets, and the model properties further explored in a simulation study.

Analysis of Variance↗

PubMed2026

Methane and carbon dioxide emissions from wastewater treatment units linked to DOM stabilization and phosphonate-scavenging microbiomes.

Municipal wastewater treatment plants (WWTPs) are major engineered facilities for urban carbon removal, yet methane (CH4) formation and source mechanisms in downstream stages after aeration and biological nutrient removal remain poorly resolved. Process resolved monitoring at a full-scale WWTP showed that CH4 emissions were concentrated upstream, while measurable fluxes persisted in downstream sedimentation and denitrification units. Dissolved CH4 profiles showed strong attenuation of influent derived CH4 during upstream treatment, followed by a local increase after secondary clarification. Carbon dioxide (CO2) emissions peaked in the biochemical tank, consistent with rapid oxidation of labile organic carbon. Fluorescence and molecular analyses revealed a shift in dissolved organic matter (DOM) from protein like to more humic and processed molecules, while community assembly remained predominantly deterministic despite greater stochasticity in later stages. The C-P lyase catalytic core was enriched in these units, accompanied by higher phnJ transcript abundance, candidate organophosphonate features, and genomic potential. Together with BES insensitive CH4 formation in independent microcosms, these observations supported C-P lyase mediated organophosphonate utilization as a contributing pathway to local CH4 formation. Integrated evidence indicated that DOM stabilization, deterministic community filtering, potential succinate mediated cross feeding, and phosphonate scavenging jointly shaped this process. These findings show that advanced treatment units are not CH4 hotspots, but neither are they CH4 inactive zones; process resolved GHG assessments should therefore consider persistent local CH4 generation and its association with substrate restructuring and alternative phosphorus acquisition.

Dissolved organic matter↗

PubMed2005

Population biology of multispecies helminth infection: interspecific interactions and parasite distribution.

Despite evidence for the existence of interspecific interactions between helminth species, there has been no theoretical exploration of their effect on the distribution of the parasite species in a host population. We use a deterministic model for the accumulation and loss of adult worms of 2 interacting helminth species to motivate an individual-based stochastic model. The mean worm burden and variance: mean ratio (VMR) of each species, and the correlation between the two species are used to describe the distribution within different host age classes. We find that interspecific interactions can produce convex age-intensity profiles and will impact the level of aggregation (as measured by the VMR). In the absence of correlated exposure, the correlation in older age classes may be close to zero when either intra- or interspecific synergistic effects are strong. We therefore suggest examining the correlation between species in young hosts as a possible means of identifying interspecific interaction. The presence of correlation between the rates of exposure makes the interpretation of correlations between species more difficult. Finally we show that in the absence of interaction, strong positive correlations are generated by averaging across most age classes.

Animals↗

PubMed2002

A decision-tree to optimise control measures during the early stage of a foot-and-mouth disease epidemic.

A decision-tree was developed to support decision making on control measures during the first days after the declaration of an outbreak of foot-and-mouth disease (FMD). The objective of the tree was to minimise direct costs and export losses of FMD epidemics under several scenarios based on livestock and herd density in the outbreak region, the possibility of airborne spread, and the time between first infection and first detection. The starting point of the tree was an epidemiological model based on a deterministic susceptible-infectious-recovered approach. The effect of four control strategies on FMD dynamics was modelled. In addition to the standard control strategy of stamping out and culling of high-risk contact herds, strategies involving ring culling within 1 km of an infected herd, ring-vaccination within 1 km of an infected herd, and ring-vaccination within 3 km of an infected herd were assessed. An economic model converted outbreak and control effects of farming and processing operations into estimates of direct costs and export losses. Ring-vaccination is the economically optimal control strategy for densely populated livestock areas whereas ring culling is the economically optimal control strategy for sparsely populated livestock areas.

Animal Husbandry↗