General Economic and Demographic Background and Projections for Indiana Library Services.
ERIC Educational Resources Information Center
Foust, James D.; Tower, Carl B.
Before future library needs can be estimated, economic and demographic variables that influence the demand for library services must be projected and estimating equations relating library needs to economic and demographic parameters developed. This study considers the size, location and age-sex characteristics of Indiana's current population and…
Estimating demographic parameters using a combination of known-fate and open N-mixture models
Schmidt, Joshua H.; Johnson, Devin S.; Lindberg, Mark S.; Adams, Layne G.
2015-01-01
Accurate estimates of demographic parameters are required to infer appropriate ecological relationships and inform management actions. Known-fate data from marked individuals are commonly used to estimate survival rates, whereas N-mixture models use count data from unmarked individuals to estimate multiple demographic parameters. However, a joint approach combining the strengths of both analytical tools has not been developed. Here we develop an integrated model combining known-fate and open N-mixture models, allowing the estimation of detection probability, recruitment, and the joint estimation of survival. We demonstrate our approach through both simulations and an applied example using four years of known-fate and pack count data for wolves (Canis lupus). Simulation results indicated that the integrated model reliably recovered parameters with no evidence of bias, and survival estimates were more precise under the joint model. Results from the applied example indicated that the marked sample of wolves was biased toward individuals with higher apparent survival rates than the unmarked pack mates, suggesting that joint estimates may be more representative of the overall population. Our integrated model is a practical approach for reducing bias while increasing precision and the amount of information gained from mark–resight data sets. We provide implementations in both the BUGS language and an R package.
Estimating demographic parameters using a combination of known-fate and open N-mixture models.
Schmidt, Joshua H; Johnson, Devin S; Lindberg, Mark S; Adams, Layne G
2015-10-01
Accurate estimates of demographic parameters are required to infer appropriate ecological relationships and inform management actions. Known-fate data from marked individuals are commonly used to estimate survival rates, whereas N-mixture models use count data from unmarked individuals to estimate multiple demographic parameters. However, a joint approach combining the strengths of both analytical tools has not been developed. Here we develop an integrated model combining known-fate and open N-mixture models, allowing the estimation of detection probability, recruitment, and the joint estimation of survival. We demonstrate our approach through both simulations and an applied example using four years of known-fate and pack count data for wolves (Canis lupus). Simulation results indicated that the integrated model reliably recovered parameters with no evidence of bias, and survival estimates were more precise under the joint model. Results from the applied example indicated that the marked sample of wolves was biased toward individuals with higher apparent survival rates than the unmarked pack mates, suggesting that joint estimates may be more representative of the overall population. Our integrated model is a practical approach for reducing bias while increasing precision and the amount of information gained from mark-resight data sets. We provide implementations in both the BUGS language and an R package.
Chapter 8: Demographic characteristics and population modeling
Scott H. Stoleson; Mary J. Whitfield; Mark K. Sogge
2000-01-01
An understanding of the basic demography of a species is necessary to estimate and evaluate population trends. The relative impact of different demographic parameters on growth rates can be assessed through a sensitivity analysis, in which different parameters are altered singly to assess the effect on population growth. Identification of critical parameters can allow...
Jiao, Y.; Lapointe, N.W.R.; Angermeier, P.L.; Murphy, B.R.
2009-01-01
Models of species' demographic features are commonly used to understand population dynamics and inform management tactics. Hierarchical demographic models are ideal for the assessment of non-indigenous species because our knowledge of non-indigenous populations is usually limited, data on demographic traits often come from a species' native range, these traits vary among populations, and traits are likely to vary considerably over time as species adapt to new environments. Hierarchical models readily incorporate this spatiotemporal variation in species' demographic traits by representing demographic parameters as multi-level hierarchies. As is done for traditional non-hierarchical matrix models, sensitivity and elasticity analyses are used to evaluate the contributions of different life stages and parameters to estimates of population growth rate. We applied a hierarchical model to northern snakehead (Channa argus), a fish currently invading the eastern United States. We used a Monte Carlo approach to simulate uncertainties in the sensitivity and elasticity analyses and to project future population persistence under selected management tactics. We gathered key biological information on northern snakehead natural mortality, maturity and recruitment in its native Asian environment. We compared the model performance with and without hierarchy of parameters. Our results suggest that ignoring the hierarchy of parameters in demographic models may result in poor estimates of population size and growth and may lead to erroneous management advice. In our case, the hierarchy used multi-level distributions to simulate the heterogeneity of demographic parameters across different locations or situations. The probability that the northern snakehead population will increase and harm the native fauna is considerable. Our elasticity and prognostic analyses showed that intensive control efforts immediately prior to spawning and/or juvenile-dispersal periods would be more effective (and probably require less effort) than year-round control efforts. Our study demonstrates the importance of considering the hierarchy of parameters in estimating population growth rate and evaluating different management strategies for non-indigenous invasive species. ?? 2009 Elsevier B.V.
Population models for passerine birds: structure, parameterization, and analysis
Noon, B.R.; Sauer, J.R.; McCullough, D.R.; Barrett, R.H.
1992-01-01
Population models have great potential as management tools, as they use infonnation about the life history of a species to summarize estimates of fecundity and survival into a description of population change. Models provide a framework for projecting future populations, determining the effects of management decisions on future population dynamics, evaluating extinction probabilities, and addressing a variety of questions of ecological and evolutionary interest. Even when insufficient information exists to allow complete identification of the model, the modelling procedure is useful because it forces the investigator to consider the life history of the species when determining what parameters should be estimated from field studies and provides a context for evaluating the relative importance of demographic parameters. Models have been little used in the study of the population dynamics of passerine birds because of: (1) widespread misunderstandings of the model structures and parameterizations, (2) a lack of knowledge of life histories of many species, (3) difficulties in obtaining statistically reliable estimates of demographic parameters for most passerine species, and (4) confusion about functional relationships among demographic parameters. As a result, studies of passerine demography are often designed inappropriately and fail to provide essential data. We review appropriate models for passerine bird populations and illustrate their possible uses in evaluating the effects of management or other environmental influences on population dynamics. We identify environmental influences on population dynamics. We identify parameters that must be estimated from field data, briefly review existing statistical methods for obtaining valid estimates, and evaluate the present status of knowledge of these parameters.
Demographic estimation methods for plants with unobservable life-states
Kery, M.; Gregg, K.B.; Schaub, M.
2005-01-01
Demographic estimation of vital parameters in plants with an unobservable dormant state is complicated, because time of death is not known. Conventional methods assume that death occurs at a particular time after a plant has last been seen aboveground but the consequences of assuming a particular duration of dormancy have never been tested. Capture-recapture methods do not make assumptions about time of death; however, problems with parameter estimability have not yet been resolved. To date, a critical comparative assessment of these methods is lacking. We analysed data from a 10 year study of Cleistes bifaria, a terrestrial orchid with frequent dormancy, and compared demographic estimates obtained by five varieties of the conventional methods, and two capture-recapture methods. All conventional methods produced spurious unity survival estimates for some years or for some states, and estimates of demographic rates sensitive to the time of death assumption. In contrast, capture-recapture methods are more parsimonious in terms of assumptions, are based on well founded theory and did not produce spurious estimates. In Cleistes, dormant episodes lasted for 1-4 years (mean 1.4, SD 0.74). The capture-recapture models estimated ramet survival rate at 0.86 (SE~ 0.01), ranging from 0.77-0.94 (SEs # 0.1) in anyone year. The average fraction dormant was estimated at 30% (SE 1.5), ranging 16 -47% (SEs # 5.1) in anyone year. Multistate capture-recapture models showed that survival rates were positively related to precipitation in the current year, but transition rates were more strongly related to precipitation in the previous than in the current year, with more ramets going dormant following dry years. Not all capture-recapture models of interest have estimable parameters; for instance, without excavating plants in years when they do not appear aboveground, it is not possible to obtain independent timespecific survival estimates for dormant plants. We introduce rigorous computer algebra methods to identify the parameters that are estimable in principle. As life-states are a prominent feature in plant life cycles, multi state capture-recapture models are a natural framework for analysing population dynamics of plants with dormancy.
Understanding the demographic drivers of realized population growth rates.
Koons, David N; Arnold, Todd W; Schaub, Michael
2017-10-01
Identifying the demographic parameters (e.g., reproduction, survival, dispersal) that most influence population dynamics can increase conservation effectiveness and enhance ecological understanding. Life table response experiments (LTRE) aim to decompose the effects of change in parameters on past demographic outcomes (e.g., population growth rates). But the vast majority of LTREs and other retrospective population analyses have focused on decomposing asymptotic population growth rates, which do not account for the dynamic interplay between population structure and vital rates that shape realized population growth rates (λt=Nt+1/Nt) in time-varying environments. We provide an empirical means to overcome these shortcomings by merging recently developed "transient life-table response experiments" with integrated population models (IPMs). IPMs allow for the estimation of latent population structure and other demographic parameters that are required for transient LTRE analysis, and Bayesian versions additionally allow for complete error propagation from the estimation of demographic parameters to derivations of realized population growth rates and perturbation analyses of growth rates. By integrating available monitoring data for Lesser Scaup over 60 yr, and conducting transient LTREs on IPM estimates, we found that the contribution of juvenile female survival to long-term variation in realized population growth rates was 1.6 and 3.7 times larger than that of adult female survival and fecundity, respectively. But a persistent long-term decline in fecundity explained 92% of the decline in abundance between 1983 and 2006. In contrast, an improvement in adult female survival drove the modest recovery in Lesser Scaup abundance since 2006, indicating that the most important demographic drivers of Lesser Scaup population dynamics are temporally dynamic. In addition to resolving uncertainty about Lesser Scaup population dynamics, the merger of IPMs with transient LTREs will strengthen our understanding of demography for many species as we aim to conserve biodiversity during an era of non-stationary global change. © 2017 by the Ecological Society of America.
Modeling and predicting community responses to events using cultural demographics
NASA Astrophysics Data System (ADS)
Jaenisch, Holger M.; Handley, James W.; Hicklen, Michael L.
2007-04-01
This paper describes a novel capability for modeling and predicting community responses to events (specifically military operations) related to demographics. Demographics in the form of words and/or numbers are used. As an example, State of Alabama annual demographic data for retail sales, auto registration, wholesale trade, shopping goods, and population were used; from which we determined a ranked estimate of the sensitivity of the demographic parameters on the cultural group response. Our algorithm and results are summarized in this paper.
An open-population hierarchical distance sampling model
Sollmann, Rachel; Beth Gardner,; Richard B Chandler,; Royle, J. Andrew; T Scott Sillett,
2015-01-01
Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for direct estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for island scrub-jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying number of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.
An open-population hierarchical distance sampling model.
Sollmann, Rahel; Gardner, Beth; Chandler, Richard B; Royle, J Andrew; Sillett, T Scott
2015-02-01
Modeling population dynamics while accounting for imperfect detection is essential to monitoring programs. Distance sampling allows estimating population size while accounting for imperfect detection, but existing methods do not allow for estimation of demographic parameters. We develop a model that uses temporal correlation in abundance arising from underlying population dynamics to estimate demographic parameters from repeated distance sampling surveys. Using a simulation study motivated by designing a monitoring program for Island Scrub-Jays (Aphelocoma insularis), we investigated the power of this model to detect population trends. We generated temporally autocorrelated abundance and distance sampling data over six surveys, using population rates of change of 0.95 and 0.90. We fit the data generating Markovian model and a mis-specified model with a log-linear time effect on abundance, and derived post hoc trend estimates from a model estimating abundance for each survey separately. We performed these analyses for varying numbers of survey points. Power to detect population changes was consistently greater under the Markov model than under the alternatives, particularly for reduced numbers of survey points. The model can readily be extended to more complex demographic processes than considered in our simulations. This novel framework can be widely adopted for wildlife population monitoring.
Population growth of Yellowstone grizzly bears: Uncertainty and future monitoring
Harris, R.B.; White, Gary C.; Schwartz, C.C.; Haroldson, M.A.
2007-01-01
Grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem of the US Rocky Mountains have recently increased in numbers, but remain vulnerable due to isolation from other populations and predicted reductions in favored food resources. Harris et al. (2006) projected how this population might fare in the future under alternative survival rates, and in doing so estimated the rate of population growth, 1983–2002. We address issues that remain from that earlier work: (1) the degree of uncertainty surrounding our estimates of the rate of population change (λ); (2) the effect of correlation among demographic parameters on these estimates; and (3) how a future monitoring system using counts of females accompanied by cubs might usefully differentiate between short-term, expected, and inconsequential fluctuations versus a true change in system state. We used Monte Carlo re-sampling of beta distributions derived from the demographic parameters used by Harris et al. (2006) to derive distributions of λ during 1983–2002 given our sampling uncertainty. Approximate 95% confidence intervals were 0.972–1.096 (assuming females with unresolved fates died) and 1.008–1.115 (with unresolved females censored at last contact). We used well-supported models of Haroldson et al. (2006) and Schwartz et al. (2006a,b,c) to assess the strength of correlations among demographic processes and the effect of omitting them in projection models. Incorporating correlations among demographic parameters yielded point estimates of λ that were nearly identical to those from the earlier model that omitted correlations, but yielded wider confidence intervals surrounding λ. Finally, we suggest that fitting linear and quadratic curves to the trend suggested by the estimated number of females with cubs in the ecosystem, and using AICc model weights to infer population sizes and λ provides an objective means to monitoring approximate population trajectories in addition to demographic analysis.
Spatially explicit dynamic N-mixture models
Zhao, Qing; Royle, Andy; Boomer, G. Scott
2017-01-01
Knowledge of demographic parameters such as survival, reproduction, emigration, and immigration is essential to understand metapopulation dynamics. Traditionally the estimation of these demographic parameters requires intensive data from marked animals. The development of dynamic N-mixture models makes it possible to estimate demographic parameters from count data of unmarked animals, but the original dynamic N-mixture model does not distinguish emigration and immigration from survival and reproduction, limiting its ability to explain important metapopulation processes such as movement among local populations. In this study we developed a spatially explicit dynamic N-mixture model that estimates survival, reproduction, emigration, local population size, and detection probability from count data under the assumption that movement only occurs among adjacent habitat patches. Simulation studies showed that the inference of our model depends on detection probability, local population size, and the implementation of robust sampling design. Our model provides reliable estimates of survival, reproduction, and emigration when detection probability is high, regardless of local population size or the type of sampling design. When detection probability is low, however, our model only provides reliable estimates of survival, reproduction, and emigration when local population size is moderate to high and robust sampling design is used. A sensitivity analysis showed that our model is robust against the violation of the assumption that movement only occurs among adjacent habitat patches, suggesting wide applications of this model. Our model can be used to improve our understanding of metapopulation dynamics based on count data that are relatively easy to collect in many systems.
Nichols, James D.; Hines, James E.
2002-01-01
We first consider the estimation of the finite rate of population increase or population growth rate, u i , using capture-recapture data from open populations. We review estimation and modelling of u i under three main approaches to modelling openpopulation data: the classic approach of Jolly (1965) and Seber (1965), the superpopulation approach of Crosbie & Manly (1985) and Schwarz & Arnason (1996), and the temporal symmetry approach of Pradel (1996). Next, we consider the contributions of different demographic components to u i using a probabilistic approach based on the composition of the population at time i + 1 (Nichols et al., 2000b). The parameters of interest are identical to the seniority parameters, n i , of Pradel (1996). We review estimation of n i under the classic, superpopulation, and temporal symmetry approaches. We then compare these direct estimation approaches for u i and n i with analogues computed using projection matrix asymptotics. We also discuss various extensions of the estimation approaches to multistate applications and to joint likelihoods involving multiple data types.
Nichols, J.D.; Hines, J.E.
2002-01-01
We first consider the estimation of the finite rate of population increase or population growth rate, lambda sub i, using capture-recapture data from open populations. We review estimation and modelling of lambda sub i under three main approaches to modelling open-population data: the classic approach of Jolly (1965) and Seber (1965), the superpopulation approach of Crosbie & Manly (1985) and Schwarz & Arnason (1996), and the temporal symmetry approach of Pradel (1996). Next, we consider the contributions of different demographic components to lambda sub i using a probabilistic approach based on the composition of the population at time i + 1 (Nichols et al., 2000b). The parameters of interest are identical to the seniority parameters, gamma sub i, of Pradel (1996). We review estimation of gamma sub i under the classic, superpopulation, and temporal symmetry approaches. We then compare these direct estimation approaches for lambda sub i and gamma sub i with analogues computed using projection matrix asymptotics. We also discuss various extensions of the estimation approaches to multistate applications and to joint likelihoods involving multiple data types.
Trask, Amanda E; Bignal, Eric M; McCracken, Davy I; Piertney, Stuart B; Reid, Jane M
2017-09-01
A population's effective size (N e ) is a key parameter that shapes rates of inbreeding and loss of genetic diversity, thereby influencing evolutionary processes and population viability. However, estimating N e , and identifying key demographic mechanisms that underlie the N e to census population size (N) ratio, remains challenging, especially for small populations with overlapping generations and substantial environmental and demographic stochasticity and hence dynamic age-structure. A sophisticated demographic method of estimating N e /N, which uses Fisher's reproductive value to account for dynamic age-structure, has been formulated. However, this method requires detailed individual- and population-level data on sex- and age-specific reproduction and survival, and has rarely been implemented. Here, we use the reproductive value method and detailed demographic data to estimate N e /N for a small and apparently isolated red-billed chough (Pyrrhocorax pyrrhocorax) population of high conservation concern. We additionally calculated two single-sample molecular genetic estimates of N e to corroborate the demographic estimate and examine evidence for unobserved immigration and gene flow. The demographic estimate of N e /N was 0.21, reflecting a high total demographic variance (σ2dg) of 0.71. Females and males made similar overall contributions to σ2dg. However, contributions varied among sex-age classes, with greater contributions from 3 year-old females than males, but greater contributions from ≥5 year-old males than females. The demographic estimate of N e was ~30, suggesting that rates of increase of inbreeding and loss of genetic variation per generation will be relatively high. Molecular genetic estimates of N e computed from linkage disequilibrium and approximate Bayesian computation were approximately 50 and 30, respectively, providing no evidence of substantial unobserved immigration which could bias demographic estimates of N e . Our analyses identify key sex-age classes contributing to demographic variance and thus decreasing N e /N in a small age-structured population inhabiting a variable environment. They thereby demonstrate how assessments of N e can incorporate stochastic sex- and age-specific demography and elucidate key demographic processes affecting a population's evolutionary trajectory and viability. Furthermore, our analyses show that N e for the focal chough population is critically small, implying that management to re-establish genetic connectivity may be required to ensure population viability. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.
Gardner, Beth; Reppucci, Juan; Lucherini, Mauro; Royle, J. Andrew
2010-01-01
We develop a hierarchical capture–recapture model for demographically open populations when auxiliary spatial information about location of capture is obtained. Such spatial capture–recapture data arise from studies based on camera trapping, DNA sampling, and other situations in which a spatial array of devices records encounters of unique individuals. We integrate an individual-based formulation of a Jolly-Seber type model with recently developed spatially explicit capture–recapture models to estimate density and demographic parameters for survival and recruitment. We adopt a Bayesian framework for inference under this model using the method of data augmentation which is implemented in the software program WinBUGS. The model was motivated by a camera trapping study of Pampas cats Leopardus colocolo from Argentina, which we present as an illustration of the model in this paper. We provide estimates of density and the first quantitative assessment of vital rates for the Pampas cat in the High Andes. The precision of these estimates is poor due likely to the sparse data set. Unlike conventional inference methods which usually rely on asymptotic arguments, Bayesian inferences are valid in arbitrary sample sizes, and thus the method is ideal for the study of rare or endangered species for which small data sets are typical.
Gardner, Beth; Reppucci, Juan; Lucherini, Mauro; Royle, J Andrew
2010-11-01
We develop a hierarchical capture-recapture model for demographically open populations when auxiliary spatial information about location of capture is obtained. Such spatial capture-recapture data arise from studies based on camera trapping, DNA sampling, and other situations in which a spatial array of devices records encounters of unique individuals. We integrate an individual-based formulation of a Jolly-Seber type model with recently developed spatially explicit capture-recapture models to estimate density and demographic parameters for survival and recruitment. We adopt a Bayesian framework for inference under this model using the method of data augmentation which is implemented in the software program WinBUGS. The model was motivated by a camera trapping study of Pampas cats Leopardus colocolo from Argentina, which we present as an illustration of the model in this paper. We provide estimates of density and the first quantitative assessment of vital rates for the Pampas cat in the High Andes. The precision of these estimates is poor due likely to the sparse data set. Unlike conventional inference methods which usually rely on asymptotic arguments, Bayesian inferences are valid in arbitrary sample sizes, and thus the method is ideal for the study of rare or endangered species for which small data sets are typical.
Does probability of occurrence relate to population dynamics?
Thuiller, Wilfried; Münkemüller, Tamara; Schiffers, Katja H.; Georges, Damien; Dullinger, Stefan; Eckhart, Vincent M.; Edwards, Thomas C.; Gravel, Dominique; Kunstler, Georges; Merow, Cory; Moore, Kara; Piedallu, Christian; Vissault, Steve; Zimmermann, Niklaus E.; Zurell, Damaris; Schurr, Frank M.
2014-01-01
Hutchinson defined species' realized niche as the set of environmental conditions in which populations can persist in the presence of competitors. In terms of demography, the realized niche corresponds to the environments where the intrinsic growth rate (r) of populations is positive. Observed species occurrences should reflect the realized niche when additional processes like dispersal and local extinction lags do not have overwhelming effects. Despite the foundational nature of these ideas, quantitative assessments of the relationship between range-wide demographic performance and occurrence probability have not been made. This assessment is needed both to improve our conceptual understanding of species' niches and ranges and to develop reliable mechanistic models of species geographic distributions that incorporate demography and species interactions.The objective of this study is to analyse how demographic parameters (intrinsic growth rate r and carrying capacity K ) and population density (N ) relate to occurrence probability (Pocc ). We hypothesized that these relationships vary with species' competitive ability. Demographic parameters, density, and occurrence probability were estimated for 108 tree species from four temperate forest inventory surveys (Québec, western USA, France and Switzerland). We used published information of shade tolerance as indicators of light competition strategy, assuming that high tolerance denotes high competitive capacity in stable forest environments.Interestingly, relationships between demographic parameters and occurrence probability did not vary substantially across degrees of shade tolerance and regions. Although they were influenced by the uncertainty in the estimation of the demographic parameters, we found that r was generally negatively correlated with Pocc, while N, and for most regions K, was generally positively correlated with Pocc. Thus, in temperate forest trees the regions of highest occurrence probability are those with high densities but slow intrinsic population growth rates. The uncertain relationships between demography and occurrence probability suggests caution when linking species distribution and demographic models.
Servanty, Sabrina; Converse, Sarah J.; Bailey, Larissa L.
2014-01-01
The reintroduction of threatened and endangered species is now a common method for reestablishing populations. Typically, a fundamental objective of reintroduction is to establish a self-sustaining population. Estimation of demographic parameters in reintroduced populations is critical, as these estimates serve multiple purposes. First, they support evaluation of progress toward the fundamental objective via construction of population viability analyses (PVAs) to predict metrics such as probability of persistence. Second, PVAs can be expanded to support evaluation of management actions, via management modeling. Third, the estimates themselves can support evaluation of the demographic performance of the reintroduced population, e.g., via comparison with wild populations. For each of these purposes, thorough treatment of uncertainties in the estimates is critical. Recently developed statistical methods - namely, hierarchical Bayesian implementations of state-space models - allow for effective integration of different types of uncertainty in estimation. We undertook a demographic estimation effort for a reintroduced population of endangered whooping cranes with the purpose of ultimately developing a Bayesian PVA for determining progress toward establishing a self-sustaining population, and for evaluating potential management actions via a Bayesian PVA-based management model. We evaluated individual and temporal variation in demographic parameters based upon a multi-state mark-recapture model. We found that survival was relatively high across time and varied little by sex. There was some indication that survival varied by release method. Survival was similar to that observed in the wild population. Although overall reproduction in this reintroduced population is poor, birds formed social pairs when relatively young, and once a bird was in a social pair, it had a nearly 50% chance of nesting the following breeding season. Also, once a bird had nested, it had a high probability of nesting again. These results are encouraging considering that survival and reproduction have been major challenges in past reintroductions of this species. The demographic estimates developed will support construction of a management model designed to facilitate exploration of management actions of interest, and will provide critical guidance in future planning for this reintroduction. An approach similar to what we describe could be usefully applied to many reintroduced populations.
Population demographics, survival, and reporduction: Alaska sea otter research
Monson, Daniel H.; Bodkin, James L.; Doak, D.F.; Estes, James A.; Tinker, M.T.; Siniff, D.B.; Maldini, Daniela; Calkins, Donald; Atkinson, Shannon; Meehan, Rosa
2004-01-01
The fundamental force behind population change is the balance between age-specific survival and reproductive rates. Thus, understanding population demographics is crucial when trying to interpret trends in population change over time. For many species, demographic rates change as the population’s status (i.e., relative to prey resources) varies. Indices of body condition indicative of individual energy reserves can be a useful gauge of population status. Integrated studies designed to measure (1) population trends; (2) current population status; and (3) demographic rates will provide the most complete picture of the factors driving observed population changes. In particular, estimates of age specific survival and reproduction in conjunction with measures of population change can be integrated into population matrix models useful in explaining observed trends. We focus here on the methods used to measure demographic rates in sea otters, and note the importance of comparable methods between studies. Next, we review the current knowledge of the influence of population status on demographic parameters. We end with examples of the power of matrix modeling as a tool to integrate various types of demographic information for detecting otherwise hard to detect changes in demographic parameters.
Nilsen, Erlend B; Strand, Olav
2018-01-01
We developed a model for estimating demographic rates and population abundance based on multiple data sets revealing information about population age- and sex structure. Such models have previously been described in the literature as change-in-ratio models, but we extend the applicability of the models by i) using time series data allowing the full temporal dynamics to be modelled, by ii) casting the model in an explicit hierarchical modelling framework, and by iii) estimating parameters based on Bayesian inference. Based on sensitivity analyses we conclude that the approach developed here is able to obtain estimates of demographic rate with high precision whenever unbiased data of population structure are available. Our simulations revealed that this was true also when data on population abundance are not available or not included in the modelling framework. Nevertheless, when data on population structure are biased due to different observability of different age- and sex categories this will affect estimates of all demographic rates. Estimates of population size is particularly sensitive to such biases, whereas demographic rates can be relatively precisely estimated even with biased observation data as long as the bias is not severe. We then use the models to estimate demographic rates and population abundance for two Norwegian reindeer (Rangifer tarandus) populations where age-sex data were available for all harvested animals, and where population structure surveys were carried out in early summer (after calving) and late fall (after hunting season), and population size is counted in winter. We found that demographic rates were similar regardless whether we include population count data in the modelling, but that the estimated population size is affected by this decision. This suggest that monitoring programs that focus on population age- and sex structure will benefit from collecting additional data that allow estimation of observability for different age- and sex classes. In addition, our sensitivity analysis suggests that focusing monitoring towards changes in demographic rates might be more feasible than monitoring abundance in many situations where data on population age- and sex structure can be collected.
Doherty, P.F.; Kendall, W.L.; Sillett, S.; Gustafson, M.; Flint, B.; Naughton, M.; Robbins, C.S.; Pyle, P.; Macintyre, Ian G.
2006-01-01
The effects of fishery practices on black-footed (Phoebastria nigripes) and Laysan albatross (Phoebastria immutabilis) continue to be a source of contention and uncertainty. Some of this uncertainty is a result of a lack of estimates of albatross demographic parameters such as survival. To begin to address these informational needs, a database of albatross banding and encounter records was constructed. Due to uncertainty concerning data collection and validity of assumptions required for mark-recapture analyses, these data should be used with caution. Although demographic parameter estimates are of interest to many, band loss rates, temporary emigration rates, and discontinuous banding effort can confound these estimates. We suggest a number of improvements in data collection that can help ameliorate problems, including the use of double banding and collecting data using a `robust? design. Additionally, sustained banding and encounter efforts are needed to maximize the value of these data. With these modifications, the usefulness of the banding data could be improved markedly.
Devenish Nelson, Eleanor S.; Harris, Stephen; Soulsbury, Carl D.; Richards, Shane A.; Stephens, Philip A.
2010-01-01
Background Demographic models are widely used in conservation and management, and their parameterisation often relies on data collected for other purposes. When underlying data lack clear indications of associated uncertainty, modellers often fail to account for that uncertainty in model outputs, such as estimates of population growth. Methodology/Principal Findings We applied a likelihood approach to infer uncertainty retrospectively from point estimates of vital rates. Combining this with resampling techniques and projection modelling, we show that confidence intervals for population growth estimates are easy to derive. We used similar techniques to examine the effects of sample size on uncertainty. Our approach is illustrated using data on the red fox, Vulpes vulpes, a predator of ecological and cultural importance, and the most widespread extant terrestrial mammal. We show that uncertainty surrounding estimated population growth rates can be high, even for relatively well-studied populations. Halving that uncertainty typically requires a quadrupling of sampling effort. Conclusions/Significance Our results compel caution when comparing demographic trends between populations without accounting for uncertainty. Our methods will be widely applicable to demographic studies of many species. PMID:21049049
Modeling structured population dynamics using data from unmarked individuals
Grant, Evan H. Campbell; Zipkin, Elise; Thorson, James T.; See, Kevin; Lynch, Heather J.; Kanno, Yoichiro; Chandler, Richard; Letcher, Benjamin H.; Royle, J. Andrew
2014-01-01
The study of population dynamics requires unbiased, precise estimates of abundance and vital rates that account for the demographic structure inherent in all wildlife and plant populations. Traditionally, these estimates have only been available through approaches that rely on intensive mark–recapture data. We extended recently developed N-mixture models to demonstrate how demographic parameters and abundance can be estimated for structured populations using only stage-structured count data. Our modeling framework can be used to make reliable inferences on abundance as well as recruitment, immigration, stage-specific survival, and detection rates during sampling. We present a range of simulations to illustrate the data requirements, including the number of years and locations necessary for accurate and precise parameter estimates. We apply our modeling framework to a population of northern dusky salamanders (Desmognathus fuscus) in the mid-Atlantic region (USA) and find that the population is unexpectedly declining. Our approach represents a valuable advance in the estimation of population dynamics using multistate data from unmarked individuals and should additionally be useful in the development of integrated models that combine data from intensive (e.g., mark–recapture) and extensive (e.g., counts) data sources.
Sam Rossman; Charles B. Yackulic; Sarah P. Saunders; Janice Reid; Ray Davis; Elise F. Zipkin
2016-01-01
Occupancy modeling is a widely used analytical technique for assessing species distributions and range dynamics. However, occupancy analyses frequently ignore variation in abundance of occupied sites, even though site abundances affect many of the parameters being estimated (e.g., extinction, colonization, detection probability). We introduce a new model (âdynamic
An improved approximate-Bayesian model-choice method for estimating shared evolutionary history
2014-01-01
Background To understand biological diversification, it is important to account for large-scale processes that affect the evolutionary history of groups of co-distributed populations of organisms. Such events predict temporally clustered divergences times, a pattern that can be estimated using genetic data from co-distributed species. I introduce a new approximate-Bayesian method for comparative phylogeographical model-choice that estimates the temporal distribution of divergences across taxa from multi-locus DNA sequence data. The model is an extension of that implemented in msBayes. Results By reparameterizing the model, introducing more flexible priors on demographic and divergence-time parameters, and implementing a non-parametric Dirichlet-process prior over divergence models, I improved the robustness, accuracy, and power of the method for estimating shared evolutionary history across taxa. Conclusions The results demonstrate the improved performance of the new method is due to (1) more appropriate priors on divergence-time and demographic parameters that avoid prohibitively small marginal likelihoods for models with more divergence events, and (2) the Dirichlet-process providing a flexible prior on divergence histories that does not strongly disfavor models with intermediate numbers of divergence events. The new method yields more robust estimates of posterior uncertainty, and thus greatly reduces the tendency to incorrectly estimate models of shared evolutionary history with strong support. PMID:24992937
Ring, Caroline L; Pearce, Robert G; Setzer, R Woodrow; Wetmore, Barbara A; Wambaugh, John F
2017-09-01
The thousands of chemicals present in the environment (USGAO, 2013) must be triaged to identify priority chemicals for human health risk research. Most chemicals have little of the toxicokinetic (TK) data that are necessary for relating exposures to tissue concentrations that are believed to be toxic. Ongoing efforts have collected limited, in vitro TK data for a few hundred chemicals. These data have been combined with biomonitoring data to estimate an approximate margin between potential hazard and exposure. The most "at risk" 95th percentile of adults have been identified from simulated populations that are generated either using standard "average" adult human parameters or very specific cohorts such as Northern Europeans. To better reflect the modern U.S. population, we developed a population simulation using physiologies based on distributions of demographic and anthropometric quantities from the most recent U.S. Centers for Disease Control and Prevention National Health and Nutrition Examination Survey (NHANES) data. This allowed incorporation of inter-individual variability, including variability across relevant demographic subgroups. Variability was analyzed with a Monte Carlo approach that accounted for the correlation structure in physiological parameters. To identify portions of the U.S. population that are more at risk for specific chemicals, physiologic variability was incorporated within an open-source high-throughput (HT) TK modeling framework. We prioritized 50 chemicals based on estimates of both potential hazard and exposure. Potential hazard was estimated from in vitro HT screening assays (i.e., the Tox21 and ToxCast programs). Bioactive in vitro concentrations were extrapolated to doses that produce equivalent concentrations in body tissues using a reverse dosimetry approach in which generic TK models are parameterized with: 1) chemical-specific parameters derived from in vitro measurements and predicted from chemical structure; and 2) with physiological parameters for a virtual population. For risk-based prioritization of chemicals, predicted bioactive equivalent doses were compared to demographic-specific inferences of exposure rates that were based on NHANES urinary analyte biomonitoring data. The inclusion of NHANES-derived inter-individual variability decreased predicted bioactive equivalent doses by 12% on average for the total population when compared to previous methods. However, for some combinations of chemical and demographic groups the margin was reduced by as much as three quarters. This TK modeling framework allows targeted risk prioritization of chemicals for demographic groups of interest, including potentially sensitive life stages and subpopulations. Published by Elsevier Ltd.
Navascués, Miguel; Hardy, Olivier J; Burgarella, Concetta
2009-03-01
This work extends the methods of demographic inference based on the distribution of pairwise genetic differences between individuals (mismatch distribution) to the case of linked microsatellite data. Population genetics theory describes the distribution of mutations among a sample of genes under different demographic scenarios. However, the actual number of mutations can rarely be deduced from DNA polymorphisms. The inclusion of mutation models in theoretical predictions can improve the performance of statistical methods. We have developed a maximum-pseudolikelihood estimator for the parameters that characterize a demographic expansion for a series of linked loci evolving under a stepwise mutation model. Those loci would correspond to DNA polymorphisms of linked microsatellites (such as those found on the Y chromosome or the chloroplast genome). The proposed method was evaluated with simulated data sets and with a data set of chloroplast microsatellites that showed signal for demographic expansion in a previous study. The results show that inclusion of a mutational model in the analysis improves the estimates of the age of expansion in the case of older expansions.
Conn, P.B.; Kendall, W.L.; Samuel, M.D.
2004-01-01
Estimates of waterfowl demographic parameters often come from resighting studies where birds fit with individually identifiable neck collars are resighted at a distance. Concerns have been raised about the effects of collar loss on parameter estimates, and the reliability of extrapolating from collared individuals to the population. Models previously proposed to account for collar loss do not allow survival or harvest parameters to depend on neck collar presence or absence. Also, few models have incorporated recent advances in mark-recapture theory that allow for multiple states or auxiliary encounters such as band recoveries. We propose a multistate model for tag loss in which the presence or absence of a collar is considered as a state variable. In this framework, demographic parameters are corrected for tag loss and questions related to collar effects on survival and recovery rates can be addressed. Encounters of individuals between closed sampling periods also can be incorporated in the analysis. We discuss data requirements for answering questions related to tag loss and sampling designs that lend themselves to this purpose. We illustrate the application of our model using a study of lesser snow geese (Chen caerulescens caerulescens).
Developing population models with data from marked individuals
Hae Yeong Ryu,; Kevin T. Shoemaker,; Eva Kneip,; Anna Pidgeon,; Patricia Heglund,; Brooke Bateman,; Thogmartin, Wayne E.; Reşit Akçakaya,
2016-01-01
Population viability analysis (PVA) is a powerful tool for biodiversity assessments, but its use has been limited because of the requirements for fully specified population models such as demographic structure, density-dependence, environmental stochasticity, and specification of uncertainties. Developing a fully specified population model from commonly available data sources – notably, mark–recapture studies – remains complicated due to lack of practical methods for estimating fecundity, true survival (as opposed to apparent survival), natural temporal variability in both survival and fecundity, density-dependence in the demographic parameters, and uncertainty in model parameters. We present a general method that estimates all the key parameters required to specify a stochastic, matrix-based population model, constructed using a long-term mark–recapture dataset. Unlike standard mark–recapture analyses, our approach provides estimates of true survival rates and fecundities, their respective natural temporal variabilities, and density-dependence functions, making it possible to construct a population model for long-term projection of population dynamics. Furthermore, our method includes a formal quantification of parameter uncertainty for global (multivariate) sensitivity analysis. We apply this approach to 9 bird species and demonstrate the feasibility of using data from the Monitoring Avian Productivity and Survivorship (MAPS) program. Bias-correction factors for raw estimates of survival and fecundity derived from mark–recapture data (apparent survival and juvenile:adult ratio, respectively) were non-negligible, and corrected parameters were generally more biologically reasonable than their uncorrected counterparts. Our method allows the development of fully specified stochastic population models using a single, widely available data source, substantially reducing the barriers that have until now limited the widespread application of PVA. This method is expected to greatly enhance our understanding of the processes underlying population dynamics and our ability to analyze viability and project trends for species of conservation concern.
Demography of birds in a neotropical forest: Effects of allometry, taxonomy, and ecology
Brawn, J.D.; Karr, J.R.; Nichols, J.D.
1995-01-01
Comparative demographic studies of terrestrial vertebrates have included few samples of species from tropical forests. We analyzed 9 yr of mark-recapture data and estimated demographic parameters for 25 species of birds inhabiting lowland forests in central Panama. These species were all songbirds (Order Passeriformes) ranging in mass from 7 to 57 g. Using Jolly-Seber stochastic models for open populations, we estimated annual survival rate, population size, and recruitment between sampling periods for each species. We then explored relationships between these parameters and attributes such as body size, phylogenetic affiliation, foraging guild, and social behavior. Larger birds had comparatively long life-spans and low recruitment, but body size was not associated with population size. After adjusting for effects of body size, we found no association between phylogenetic affiliation and any demographic trait. Ecological attributes, especially foraging guild, were more clearly associated with interspecific variation in all demographic traits. Ant-followers had comparatively long life-spans, but species that participate in flocks did not live longer than solitary species. The allometric associations we observed were consistent with those demonstrated in other studies of vertebrates; thus. these relationships appear to be robust. Our finding that ecological factors were more influential than phylogenetic affiliation contrasts with comparative studies of temperate-zone birds and suggests that the relative importance of environmental vs. historical factors varies geographically.
Comparative demographics of a Hawaiian forest bird community
Guillaumet, Alban; Woodworth, Bethany L.; Camp, Richard J.; Paxton, Eben H.
2016-01-01
Estimates of demographic parameters such as survival and reproductive success are critical for guiding management efforts focused on species of conservation concern. Unfortunately, reliable demographic parameters are difficult to obtain for any species, but especially for rare or endangered species. Here we derived estimates of adult survival and recruitment in a community of Hawaiian forest birds, including eight native species (of which three are endangered) and two introduced species at Hakalau Forest National Wildlife Refuge, Hawaiʻi. Integrated population models (IPM) were used to link mark–recapture data (1994–1999) with long-term population surveys (1987–2008). To our knowledge, this is the first time that IPM have been used to characterize demographic parameters of a whole avian community, and provides important insights into the life history strategies of the community. The demographic data were used to test two hypotheses: 1) arthropod specialists, such as the ‘Akiapōlā‘au Hemignathus munroi, are ‘slower’ species characterized by a greater relative contribution of adult survival to population growth, i.e. lower fecundity and increased adult survival; and 2) a species’ susceptibility to environmental change, as reflected by its conservation status, can be predicted by its life history traits. We found that all species were characterized by a similar population growth rate around one, independently of conservation status, origin (native vs non-native), feeding guild, or life history strategy (as measured by ‘slowness’), which suggested that the community had reached an equilibrium. However, such stable dynamics were achieved differently across feeding guilds, as demonstrated by a significant increase of adult survival and a significant decrease of recruitment along a gradient of increased insectivory, in support of hypothesis 1. Supporting our second hypothesis, we found that slower species were more vulnerable species at the global scale than faster ones. The possible causes and conservation implications of these patterns are discussed.
Making do with less: Must sparse data preclude informed harvest strategies for European waterbirds?
Johnson, Fred A.; Alhainen, Mikko; Fox, Anthony D.; Madsen, Jesper; Guillemain, Matthieu
2018-01-01
The demography of many European waterbirds is not well understood because most countries have conducted little monitoring and assessment, and coordination among countries on waterbird management has little precedent. Yet intergovernmental treaties now mandate the use of sustainable, adaptive harvest strategies, whose development is challenged by a paucity of demographic information. In this study, we explore how a combination of allometric relationships, fragmentary monitoring and research information, and expert judgment can be used to estimate the parameters of a theta-logistic population model, which in turn can be used in a Markov decision process to derive optimal harvesting strategies. We show how to account for considerable parametric uncertainty, as well as for different management objectives. We illustrate our methodology with a poorly understood population of taiga bean geese (Anser fabalis fabalis), which is a popular game bird in Fennoscandia. Our results for taiga bean geese suggest that they may have demographic rates similar to other, well-studied species of geese, and our model-based predictions of population size are consistent with the limited monitoring information available. Importantly, we found that by using a Markov decision process, a simple scalar population model may be sufficient to guide harvest management of this species, even if its demography is age-structured. Finally, we demonstrated how two different management objectives can lead to very different optimal harvesting strategies, and how conflicting objectives may be traded off with each other. This approach will have broad application for European waterbirds by providing preliminary estimates of key demographic parameters, by providing insights into the monitoring and research activities needed to corroborate those estimates, and by producing harvest management strategies that are optimal with respect to the managers’ objectives, options, and available demographic information.
Kendall, W.L.; Nichols, J.D.; Hines, J.E.
1997-01-01
Statistical inference for capture-recapture studies of open animal populations typically relies on the assumption that all emigration from the studied population is permanent. However, there are many instances in which this assumption is unlikely to be met. We define two general models for the process of temporary emigration, completely random and Markovian. We then consider effects of these two types of temporary emigration on Jolly-Seber (Seber 1982) estimators and on estimators arising from the full-likelihood approach of Kendall et al. (1995) to robust design data. Capture-recapture data arising from Pollock's (1982) robust design provide the basis for obtaining unbiased estimates of demographic parameters in the presence of temporary emigration and for estimating the probability of temporary emigration. We present a likelihood-based approach to dealing with temporary emigration that permits estimation under different models of temporary emigration and yields tests for completely random and Markovian emigration. In addition, we use the relationship between capture probability estimates based on closed and open models under completely random temporary emigration to derive three ad hoc estimators for the probability of temporary emigration, two of which should be especially useful in situations where capture probabilities are heterogeneous among individual animals. Ad hoc and full-likelihood estimators are illustrated for small mammal capture-recapture data sets. We believe that these models and estimators will be useful for testing hypotheses about the process of temporary emigration, for estimating demographic parameters in the presence of temporary emigration, and for estimating probabilities of temporary emigration. These latter estimates are frequently of ecological interest as indicators of animal movement and, in some sampling situations, as direct estimates of breeding probabilities and proportions.
Fay, Rémi; Weimerskirch, Henri; Delord, Karine; Barbraud, Christophe
2015-09-01
1. Our understanding of demographic processes is mainly based on analyses of traits from the adult component of populations. Early-life demographic traits are poorly known mainly for methodological reasons. Yet, survival of juvenile and immature individuals is critical for the recruitment into the population and thus for the whole population dynamic, especially for long-lived species. This bias currently restrains our ability to fully understand population dynamics of long-lived species and life-history theory. 2. The goal of this study was to estimate the early-life demographic parameters of a long-lived species with a long immature period (9-10 years), to test for sex and age effects on these parameters and to identify the environmental factors encountered during the period of immaturity that may influence survival and recruitment. 3. Using capture-mark-recapture multievent models allowing us to deal with uncertain and unobservable individual states, we analysed a long-term data set of wandering albatrosses to estimate both age- and sex-specific early-life survival and recruitment. We investigated environmental factors potentially driving these demographic traits using climatic and fisheries covariates and tested for density dependence. 4. Our study provides for the first time an estimate of annual survival during the first 2 years at sea for an albatross species (0·801 ± 0·014). Both age and sex affected early-life survival and recruitment processes of this long-lived seabird species. Early-life survival and recruitment were highly variable across years although the sensitivity of young birds to environmental variability decreased with age. Early-life survival was negatively associated with sea surface temperature, and recruitment rate was positively related to both Southern Annular Mode and sea surface temperature. We found strong evidence for density-dependent mortality of juveniles. Population size explained 41% of the variation of this parameter over the study period. 5. These results indicate that early-life survival and recruitment were strongly age and sex dependent in a dimorphic long-lived species. In addition, early-life demographic parameters were affected by natal environmental conditions and by environmental conditions faced during the period of immaturity. Finally, our results constitute one of the first demonstrations of density dependence on juvenile survival in seabirds, with major consequences for our understanding of population dynamics in seabirds. © 2015 The Authors. Journal of Animal Ecology © 2015 British Ecological Society.
A less field-intensive robust design for estimating demographic parameters with Mark-resight data
McClintock, B.T.; White, Gary C.
2009-01-01
The robust design has become popular among animal ecologists as a means for estimating population abundance and related demographic parameters with mark-recapture data. However, two drawbacks of traditional mark-recapture are financial cost and repeated disturbance to animals. Mark-resight methodology may in many circumstances be a less expensive and less invasive alternative to mark-recapture, but the models developed to date for these data have overwhelmingly concentrated only on the estimation of abundance. Here we introduce a mark-resight model analogous to that used in mark-recapture for the simultaneous estimation of abundance, apparent survival, and transition probabilities between observable and unobservable states. The model may be implemented using standard statistical computing software, but it has also been incorporated into the freeware package Program MARK. We illustrate the use of our model with mainland New Zealand Robin (Petroica australis) data collected to ascertain whether this methodology may be a reliable alternative for monitoring endangered populations of a closely related species inhabiting the Chatham Islands. We found this method to be a viable alternative to traditional mark-recapture when cost or disturbance to species is of particular concern in long-term population monitoring programs. ?? 2009 by the Ecological Society of America.
Hierarchial mark-recapture models: a framework for inference about demographic processes
Link, W.A.; Barker, R.J.
2004-01-01
The development of sophisticated mark-recapture models over the last four decades has provided fundamental tools for the study of wildlife populations, allowing reliable inference about population sizes and demographic rates based on clearly formulated models for the sampling processes. Mark-recapture models are now routinely described by large numbers of parameters. These large models provide the next challenge to wildlife modelers: the extraction of signal from noise in large collections of parameters. Pattern among parameters can be described by strong, deterministic relations (as in ultrastructural models) but is more flexibly and credibly modeled using weaker, stochastic relations. Trend in survival rates is not likely to be manifest by a sequence of values falling precisely on a given parametric curve; rather, if we could somehow know the true values, we might anticipate a regression relation between parameters and explanatory variables, in which true value equals signal plus noise. Hierarchical models provide a useful framework for inference about collections of related parameters. Instead of regarding parameters as fixed but unknown quantities, we regard them as realizations of stochastic processes governed by hyperparameters. Inference about demographic processes is based on investigation of these hyperparameters. We advocate the Bayesian paradigm as a natural, mathematically and scientifically sound basis for inference about hierarchical models. We describe analysis of capture-recapture data from an open population based on hierarchical extensions of the Cormack-Jolly-Seber model. In addition to recaptures of marked animals, we model first captures of animals and losses on capture, and are thus able to estimate survival probabilities w (i.e., the complement of death or permanent emigration) and per capita growth rates f (i.e., the sum of recruitment and immigration rates). Covariation in these rates, a feature of demographic interest, is explicitly described in the model.
[Demographic analysis of the blue shark, Prionace glauca, in the North Atlantic Ocean].
Gao, Chun-xia; Dai, Xiao-jie; Tian, Si-quan; Wu, Feng; Zhu, Jiang-feng
2016-02-01
The blue shark, Prionace glauca, is the main by-catch species in tuna longline fishery. As one of top species in the oceanic food webs, the blue shark plays an important role in the marine ecosystem. Traditional stock assessment methods are difficult to accurately evaluate the population dynamic for this shark because of limited data. Based on life-history parameters of the blue shark in the North Atlantic, demographic analysis was employed to estimate the demographic parameters and evaluate the potential exploitation for the blue shark. Moreover, we discussed the relationship between age at first capture and critical value of fishing mortality corresponding to the value of intrinsic rate of natural increase 0. The results showed that the survival rate (S) of blue shark from 0.719 to 0.820, intrinsic rate of natural increase (r0) from 0.250 to 0.381, time of population doubling (tx2) from 1.819 to 2.773 years, reproduction rate per generation (R0) from 6.600 to 22.255, and generation time (G) from 8.498 to 10.162 years. The sensitivity analysis for the life history parameters revealed that the uncertainties of natural mortality existed in the first age class, age at maturity and maximum age had slight influence on the demographic parameters. Fishing mortality (Fc) increased with the age at first capture. When the age at first capture (tc) was more than five, there was no obvious relationship between Fc and tc.
Applying stochastic small-scale damage functions to German winter storms
NASA Astrophysics Data System (ADS)
Prahl, B. F.; Rybski, D.; Kropp, J. P.; Burghoff, O.; Held, H.
2012-03-01
Analyzing insurance-loss data we derive stochastic storm-damage functions for residential buildings. On district level we fit power-law relations between daily loss and maximum wind speed, typically spanning more than 4 orders of magnitude. The estimated exponents for 439 German districts roughly range from 8 to 12. In addition, we find correlations among the parameters and socio-demographic data, which we employ in a simplified parametrization of the damage function with just 3 independent parameters for each district. A Monte Carlo method is used to generate loss estimates and confidence bounds of daily and annual storm damages in Germany. Our approach reproduces the annual progression of winter storm losses and enables to estimate daily losses over a wide range of magnitudes.
Whittington, Jesse; Sawaya, Michael A
2015-01-01
Capture-recapture studies are frequently used to monitor the status and trends of wildlife populations. Detection histories from individual animals are used to estimate probability of detection and abundance or density. The accuracy of abundance and density estimates depends on the ability to model factors affecting detection probability. Non-spatial capture-recapture models have recently evolved into spatial capture-recapture models that directly include the effect of distances between an animal's home range centre and trap locations on detection probability. Most studies comparing non-spatial and spatial capture-recapture biases focussed on single year models and no studies have compared the accuracy of demographic parameter estimates from open population models. We applied open population non-spatial and spatial capture-recapture models to three years of grizzly bear DNA-based data from Banff National Park and simulated data sets. The two models produced similar estimates of grizzly bear apparent survival, per capita recruitment, and population growth rates but the spatial capture-recapture models had better fit. Simulations showed that spatial capture-recapture models produced more accurate parameter estimates with better credible interval coverage than non-spatial capture-recapture models. Non-spatial capture-recapture models produced negatively biased estimates of apparent survival and positively biased estimates of per capita recruitment. The spatial capture-recapture grizzly bear population growth rates and 95% highest posterior density averaged across the three years were 0.925 (0.786-1.071) for females, 0.844 (0.703-0.975) for males, and 0.882 (0.779-0.981) for females and males combined. The non-spatial capture-recapture population growth rates were 0.894 (0.758-1.024) for females, 0.825 (0.700-0.948) for males, and 0.863 (0.771-0.957) for both sexes. The combination of low densities, low reproductive rates, and predominantly negative population growth rates suggest that Banff National Park's population of grizzly bears requires continued conservation-oriented management actions.
Stochastic Modeling of Empirical Storm Loss in Germany
NASA Astrophysics Data System (ADS)
Prahl, B. F.; Rybski, D.; Kropp, J. P.; Burghoff, O.; Held, H.
2012-04-01
Based on German insurance loss data for residential property we derive storm damage functions that relate daily loss with maximum gust wind speed. Over a wide range of loss, steep power law relationships are found with spatially varying exponents ranging between approximately 8 and 12. Global correlations between parameters and socio-demographic data are employed to reduce the number of local parameters to 3. We apply a Monte Carlo approach to calculate German loss estimates including confidence bounds in daily and annual resolution. Our model reproduces the annual progression of winter storm losses and enables to estimate daily losses over a wide range of magnitude.
"Birds of a Feather" Fail Together: Exploring the Nature of Dependency in SME Defaults.
Calabrese, Raffaella; Andreeva, Galina; Ansell, Jake
2017-08-11
This article studies the effects of incorporating the interdependence among London small business defaults into a risk analysis framework using the data just before the financial crisis. We propose an extension from standard scoring models to take into account the spatial dimensions and the demographic characteristics of small and medium-sized enterprises (SMEs), such as legal form, industry sector, and number of employees. We estimate spatial probit models using different distance matrices based only on the spatial location or on an interaction between spatial locations and demographic characteristics. We find that the interdependence or contagion component defined on spatial and demographic characteristics is significant and that it improves the ability to predict defaults of non-start-ups in London. Furthermore, including contagion effects among SMEs alters the parameter estimates of risk determinants. The approach can be extended to other risk analysis applications where spatial risk may incorporate correlation based on other aspects. © 2017 Society for Risk Analysis.
Ikezaki, Yuka; Suyama, Yoshihisa; Middleton, Beth A; Tsumura, Yoshihiko; Teshima, Kousuke; Tachida, Hidenori; Kusumi, Junko
2016-11-01
Studies of natural genetic variation can elucidate the genetic basis of phenotypic variation and the past population structure of species. Our study species, Taxodium distichum, is a unique conifer that inhabits the flood plains and swamps of North America. Morphological and ecological differences in two varieties, T. distichum var. distichum (bald cypress) and T. distichum var. imbricarium (pond cypress), are well known, but little is known about the level of genetic differentiation between the varieties and the demographic history of local populations. We analyzed nucleotide polymorphisms at 47 nuclear loci from 96 individuals collected from the Mississippi River Alluvial Valley (MRAV), and Gulf Coastal populations in Texas, Louisiana, and Florida using high-throughput DNA sequencing. Standard population genetic statistics were calculated, and demographic parameters were estimated using a composite-likelihood approach. Taxodium distichum in North America can be divided into at least three genetic groups, bald cypress in the MRAV and Texas, bald cypress in Florida, and pond cypress in Florida. The levels of genetic differentiation among the groups were low but significant. Several loci showed the signatures of positive selection, which might be responsible for local adaptation or varietal differentiation. Bald cypress was genetically differentiated into two geographical groups, and the boundary was located between the MRAV and Florida. This differentiation could be explained by population expansion from east to west. Despite the overlap of the two varieties' ranges, they were genetically differentiated in Florida. The estimated demographic parameters suggested that pond cypress split from bald cypress during the late Miocene. © 2016 Botanical Society of America.
Brown, Jason L; Weber, Jennifer J; Alvarado-Serrano, Diego F; Hickerson, Michael J; Franks, Steven J; Carnaval, Ana C
2016-01-01
Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatial distribution of genetic diversity within taxa. We propose a novel method that predicts spatially explicit genetic and demographic landscapes of populations under future climatic conditions. We use carefully parameterized SDMs as estimates of the spatial distribution of suitable habitats and landscape dispersal permeability under present-day, past, and future conditions. We use empirical genetic data and approximate Bayesian computation to estimate unknown demographic parameters. Finally, we employ these parameters to simulate realistic and complex models of responses to future environmental shifts. We contrast parameterized models under current and future landscapes to quantify the expected magnitude of change. We implement this framework on neutral genetic data available from Penstemon deustus. Our results predict that future climate change will result in geographically widespread declines in genetic diversity in this species. The extent of reduction will heavily depend on the continuity of population networks and deme sizes. To our knowledge, this is the first study to provide spatially explicit predictions of within-species genetic diversity using climatic, demographic, and genetic data. Our approach accounts for climatic, geographic, and biological complexity. This framework is promising for understanding evolutionary consequences of climate change, and guiding conservation planning. © 2016 Botanical Society of America.
Choi, Chang-Yong; Lee, Ki-Sup; Poyarkov, Nikolay D.; Park, Jin-Young; Lee, Hansoo; Takekawa, John Y.; Smith, Lacy M.; Ely, Craig R.; Wang, Xin; Cao, Lei; Fox, Anthony D.; Goroshko, Oleg; Batbayar, Nyambayar; Prosser, Diann J.; Xiao, Xiangming
2016-01-01
Waterbird survival rates are a key component of demographic modeling used for effective conservation of long-lived threatened species. The Swan Goose (Anser cygnoides) is globally threatened and the most vulnerable goose species endemic to East Asia due to its small and rapidly declining population. To address a current knowledge gap in demographic parameters of the Swan Goose, available datasets were compiled from neck-collar resighting and telemetry studies, and two different models were used to estimate their survival rates. Results of a mark-resighting model using 15 years of neck-collar data (2001–2015) provided age-dependent survival rates and season-dependent encounter rates with a constant neck-collar retention rate. Annual survival rate was 0.638 (95% CI: 0.378–0.803) for adults and 0.122 (95% CI: 0.028–0.286) for first-year juveniles. Known-fate models were applied to the single season of telemetry data (autumn 2014) and estimated a mean annual survival rate of 0.408 (95% CI: 0.152–0.670) with higher but non-significant differences for adults (0.477) vs. juveniles (0.306). Our findings indicate that Swan Goose survival rates are comparable to the lowest rates reported for European or North American goose species. Poor survival may be a key demographic parameter contributing to their declining trend. Quantitative threat assessments and associated conservation measures, such as restricting hunting, may be a key step to mitigate for their low survival rates and maintain or enhance their population.
Bayesian statistics: estimating plant demographic parameters
James S. Clark; Michael Lavine
2001-01-01
There are times when external information should be brought tobear on an ecological analysis. experiments are never conducted in a knowledge-free context. The inference we draw from an observation may depend on everything else we know about the process. Bayesian analysis is a method that brings outside evidence into the analysis of experimental and observational data...
Better living through conifer removal: A demographic analysis of sage-grouse vital rates.
Severson, John P; Hagen, Christian A; Tack, Jason D; Maestas, Jeremy D; Naugle, David E; Forbes, James T; Reese, Kerry P
2017-01-01
Sagebrush (Artemisia spp.) obligate wildlife species such as the imperiled greater sage-grouse (Centrocercus urophasianus) face numerous threats including altered ecosystem processes that have led to conifer expansion into shrub-steppe. Conifer removal is accelerating despite a lack of empirical evidence on grouse population response. Using a before-after-control-impact design at the landscape scale, we evaluated effects of conifer removal on two important demographic parameters, annual survival of females and nest survival, by monitoring 219 female sage-grouse and 225 nests in the northern Great Basin from 2010 to 2014. Estimates from the best treatment models showed positive trends in the treatment area relative to the control area resulting in an increase of 6.6% annual female survival and 18.8% nest survival relative to the control area by 2014. Using stochastic simulations of our estimates and published demographics, we estimated a 25% increase in the population growth rate in the treatment area relative to the control area. This is the first study to link sage-grouse demographics with conifer removal and supports recommendations to actively manage conifer expansion for sage-grouse conservation. Sage-grouse have become a primary catalyst for conservation funding to address conifer expansion in the West, and these findings have important implications for other ecosystem services being generated on the wings of species conservation.
Demography of the Pacific walrus (Odobenus rosmarus divergens): 1974-2006
Taylor, Rebecca L.; Udevitz, Mark S.
2015-01-01
Global climate change may fundamentally alter population dynamics of many species for which baseline population parameter estimates are imprecise or lacking. Historically, the Pacific walrus is thought to have been limited by harvest, but it may become limited by global warming-induced reductions in sea ice. Loss of sea ice, on which walruses rest between foraging bouts, may reduce access to food, thus lowering vital rates. Rigorous walrus survival rate estimates do not exist, and other population parameter estimates are out of date or have well-documented bias and imprecision. To provide useful population parameter estimates we developed a Bayesian, hidden process demographic model of walrus population dynamics from 1974 through 2006 that combined annual age-specific harvest estimates with five population size estimates, six standing age structure estimates, and two reproductive rate estimates. Median density independent natural survival was high for juveniles (0.97) and adults (0.99), and annual density dependent vital rates rose from 0.06 to 0.11 for reproduction, 0.31 to 0.59 for survival of neonatal calves, and 0.39 to 0.85 for survival of older calves, concomitant with a population decline. This integrated population model provides a baseline for estimating changing population dynamics resulting from changing harvests or sea ice.
Kery, M.; Gregg, K.B.
2003-01-01
1. Most plant demographic studies follow marked individuals in permanent plots. Plots tend to be small, so detectability is assumed to be one for every individual. However, detectability could be affected by factors such as plant traits, time, space, observer, previous detection, biotic interactions, and especially by life-state. 2. We used a double-observer survey and closed population capture-recapture modelling to estimate state-specific detectability of the orchid Cleistes bifaria in a long-term study plot of 41.2 m2. Based on AICc model selection, detectability was different for each life-state and for tagged vs. previously untagged plants. There were no differences in detectability between the two observers. 3. Detectability estimates (SE) for one-leaf vegetative, two-leaf vegetative, and flowering/fruiting states correlated with mean size of these states and were 0.76 (0.05), 0.92 (0.06), and 1 (0.00), respectively, for previously tagged plants, and 0.84 (0.08), 0.75 (0.22), and 0 (0.00), respectively, for previously untagged plants. (We had insufficient data to obtain a satisfactory estimate of previously untagged flowering plants). 4. Our estimates are for a medium-sized plant in a small and intensively surveyed plot. It is possible that detectability is even lower for larger plots and smaller plants or smaller life-states (e.g. seedlings) and that detectabilities < 1 are widespread in plant demographic studies. 5. State-dependent detectabilities are especially worrying since they will lead to a size- or state-biased sample from the study plot. Failure to incorporate detectability into demographic estimation methods introduces a bias into most estimates of population parameters such as fecundity, recruitment, mortality, and transition rates between life-states. We illustrate this by a simple example using a matrix model, where a hypothetical population was stable but, due to imperfect detection, wrongly projected to be declining at a rate of 8% per year. 6. Almost all plant demographic studies are based on models for discrete states. State and size are important predictors both for demographic rates and detectability. We suggest that even in studies based on small plots, state- or size-specific detectability should be estimated at least at some point to avoid biased inference about the dynamics of the population sampled.
Coates, Peter S.; Prochazka, Brian G.; Ricca, Mark A.; Halstead, Brian J.; Casazza, Michael L.; Blomberg, Erik J.; Brussee, Brianne E.; Wiechman, Lief; Tebbenkamp, Joel; Gardner, Scott C.; Reese, Kerry P.
2018-01-01
Consideration of ecological scale is fundamental to understanding and managing avian population growth and decline. Empirically driven models for population dynamics and demographic processes across multiple spatial scales can be powerful tools to help guide conservation actions. Integrated population models (IPMs) provide a framework for better parameter estimation by unifying multiple sources of data (e.g., count and demographic data). Hierarchical structure within such models that include random effects allow for varying degrees of data sharing across different spatiotemporal scales. We developed an IPM to investigate Greater Sage-Grouse (Centrocercus urophasianus) on the border of California and Nevada, known as the Bi-State Distinct Population Segment. Our analysis integrated 13 years of lek count data (n > 2,000) and intensive telemetry (VHF and GPS; n > 350 individuals) data across 6 subpopulations. Specifically, we identified the most parsimonious models among varying random effects and density-dependent terms for each population vital rate (e.g., nest survival). Using a joint likelihood process, we integrated the lek count data with the demographic models to estimate apparent abundance and refine vital rate parameter estimates. To investigate effects of climatic conditions, we extended the model to fit a precipitation covariate for instantaneous rate of change (r). At a metapopulation extent (i.e. Bi-State), annual population rate of change λ (er) did not favor an overall increasing or decreasing trend through the time series. However, annual changes in λ were driven by changes in precipitation (one-year lag effect). At subpopulation extents, we identified substantial variation in λ and demographic rates. One subpopulation clearly decoupled from the trend at the metapopulation extent and exhibited relatively high risk of extinction as a result of low egg fertility. These findings can inform localized, targeted management actions for specific areas, and status of the species for the larger Bi-State.
Modeling seasonal measles transmission in China
NASA Astrophysics Data System (ADS)
Bai, Zhenguo; Liu, Dan
2015-08-01
A discrete-time deterministic measles model with periodic transmission rate is formulated and studied. The basic reproduction number R0 is defined and used as the threshold parameter in determining the dynamics of the model. It is shown that the disease will die out if R0 < 1 , and the disease will persist in the population if R0 > 1 . Parameters in the model are estimated on the basis of demographic and epidemiological data. Numerical simulations are presented to describe the seasonal fluctuation of measles infection in China.
The impact of roads on the demography of grizzly bears in Alberta.
Boulanger, John; Stenhouse, Gordon B
2014-01-01
One of the principal factors that have reduced grizzly bear populations has been the creation of human access into grizzly bear habitat by roads built for resource extraction. Past studies have documented mortality and distributional changes of bears relative to roads but none have attempted to estimate the direct demographic impact of roads in terms of both survival rates, reproductive rates, and the interaction of reproductive state of female bears with survival rate. We applied a combination of survival and reproductive models to estimate demographic parameters for threatened grizzly bear populations in Alberta. Instead of attempting to estimate mean trend we explored factors which caused biological and spatial variation in population trend. We found that sex and age class survival was related to road density with subadult bears being most vulnerable to road-based mortality. A multi-state reproduction model found that females accompanied by cubs of the year and/or yearling cubs had lower survival rates compared to females with two year olds or no cubs. A demographic model found strong spatial gradients in population trend based upon road density. Threshold road densities needed to ensure population stability were estimated to further refine targets for population recovery of grizzly bears in Alberta. Models that considered lowered survival of females with dependant offspring resulted in lower road density thresholds to ensure stable bear populations. Our results demonstrate likely spatial variation in population trend and provide an example how demographic analysis can be used to refine and direct conservation measures for threatened species.
The Impact of Roads on the Demography of Grizzly Bears in Alberta
2014-01-01
One of the principal factors that have reduced grizzly bear populations has been the creation of human access into grizzly bear habitat by roads built for resource extraction. Past studies have documented mortality and distributional changes of bears relative to roads but none have attempted to estimate the direct demographic impact of roads in terms of both survival rates, reproductive rates, and the interaction of reproductive state of female bears with survival rate. We applied a combination of survival and reproductive models to estimate demographic parameters for threatened grizzly bear populations in Alberta. Instead of attempting to estimate mean trend we explored factors which caused biological and spatial variation in population trend. We found that sex and age class survival was related to road density with subadult bears being most vulnerable to road-based mortality. A multi-state reproduction model found that females accompanied by cubs of the year and/or yearling cubs had lower survival rates compared to females with two year olds or no cubs. A demographic model found strong spatial gradients in population trend based upon road density. Threshold road densities needed to ensure population stability were estimated to further refine targets for population recovery of grizzly bears in Alberta. Models that considered lowered survival of females with dependant offspring resulted in lower road density thresholds to ensure stable bear populations. Our results demonstrate likely spatial variation in population trend and provide an example how demographic analysis can be used to refine and direct conservation measures for threatened species. PMID:25532035
Westine, Carl D; Spybrook, Jessaca; Taylor, Joseph A
2013-12-01
Prior research has focused primarily on empirically estimating design parameters for cluster-randomized trials (CRTs) of mathematics and reading achievement. Little is known about how design parameters compare across other educational outcomes. This article presents empirical estimates of design parameters that can be used to appropriately power CRTs in science education and compares them to estimates using mathematics and reading. Estimates of intraclass correlations (ICCs) are computed for unconditional two-level (students in schools) and three-level (students in schools in districts) hierarchical linear models of science achievement. Relevant student- and school-level pretest and demographic covariates are then considered, and estimates of variance explained are computed. Subjects: Five consecutive years of Texas student-level data for Grades 5, 8, 10, and 11. Science, mathematics, and reading achievement raw scores as measured by the Texas Assessment of Knowledge and Skills. Results: Findings show that ICCs in science range from .172 to .196 across grades and are generally higher than comparable statistics in mathematics, .163-.172, and reading, .099-.156. When available, a 1-year lagged student-level science pretest explains the most variability in the outcome. The 1-year lagged school-level science pretest is the best alternative in the absence of a 1-year lagged student-level science pretest. Science educational researchers should utilize design parameters derived from science achievement outcomes. © The Author(s) 2014.
Inter-Individual Variability in High-Throughput Risk ...
We incorporate realistic human variability into an open-source high-throughput (HT) toxicokinetics (TK) modeling framework for use in a next-generation risk prioritization approach. Risk prioritization involves rapid triage of thousands of environmental chemicals, most which have little or no existing TK data. Chemicals are prioritized based on model estimates of hazard and exposure, to decide which chemicals should be first in line for further study. Hazard may be estimated with in vitro HT screening assays, e.g., U.S. EPA’s ToxCast program. Bioactive ToxCast concentrations can be extrapolated to doses that produce equivalent concentrations in body tissues using a reverse TK approach in which generic TK models are parameterized with 1) chemical-specific parameters derived from in vitro measurements and predicted from chemical structure; and 2) with physiological parameters for a virtual population. Here we draw physiological parameters from realistic estimates of distributions of demographic and anthropometric quantities in the modern U.S. population, based on the most recent CDC NHANES data. A Monte Carlo approach, accounting for the correlation structure in physiological parameters, is used to estimate ToxCast equivalent doses for the most sensitive portion of the population. To quantify risk, ToxCast equivalent doses are compared to estimates of exposure rates based on Bayesian inferences drawn from NHANES urinary analyte biomonitoring data. The inclusion
Are camera surveys useful for assessing recruitment in white-tailed deer?
M. Colter Chitwood; Marcus A. Lashley; John C. Kilgo; Michael J. Cherry; L. Mike Conner; Mark Vukovich; H. Scott Ray; Charles Ruth; Robert J. Warren; Christopher S. DePerno; Christopher E. Moorman
2017-01-01
Camera surveys commonly are used by managers and hunters to estimate white-tailed deer Odocoileus virginianus density and demographic rates. Though studies have documented biases and inaccuracies in the camera survey methodology, camera traps remain popular due to ease of use, cost-effectiveness, and ability to survey large areas. Because recruitment is a key parameter...
Using global sensitivity analysis of demographic models for ecological impact assessment.
Aiello-Lammens, Matthew E; Akçakaya, H Resit
2017-02-01
Population viability analysis (PVA) is widely used to assess population-level impacts of environmental changes on species. When combined with sensitivity analysis, PVA yields insights into the effects of parameter and model structure uncertainty. This helps researchers prioritize efforts for further data collection so that model improvements are efficient and helps managers prioritize conservation and management actions. Usually, sensitivity is analyzed by varying one input parameter at a time and observing the influence that variation has over model outcomes. This approach does not account for interactions among parameters. Global sensitivity analysis (GSA) overcomes this limitation by varying several model inputs simultaneously. Then, regression techniques allow measuring the importance of input-parameter uncertainties. In many conservation applications, the goal of demographic modeling is to assess how different scenarios of impact or management cause changes in a population. This is challenging because the uncertainty of input-parameter values can be confounded with the effect of impacts and management actions. We developed a GSA method that separates model outcome uncertainty resulting from parameter uncertainty from that resulting from projected ecological impacts or simulated management actions, effectively separating the 2 main questions that sensitivity analysis asks. We applied this method to assess the effects of predicted sea-level rise on Snowy Plover (Charadrius nivosus). A relatively small number of replicate models (approximately 100) resulted in consistent measures of variable importance when not trying to separate the effects of ecological impacts from parameter uncertainty. However, many more replicate models (approximately 500) were required to separate these effects. These differences are important to consider when using demographic models to estimate ecological impacts of management actions. © 2016 Society for Conservation Biology.
Tinker, M. Timothy; Doak, Daniel F.; Estes, James A.; Hatfield, Brian B.; Staedler, Michelle M.; Gross, Arthur
2006-01-01
Reliable information on historical and current population dynamics is central to understanding patterns of growth and decline in animal populations. We developed a maximum likelihood-based analysis to estimate spatial and temporal trends in age/sex-specific survival rates for the threatened southern sea otter (Enhydra lutris nereis), using annual population censuses and the age structure of salvaged carcass collections. We evaluated a wide range of possible spatial and temporal effects and used model averaging to incorporate model uncertainty into the resulting estimates of key vital rates and their variances. We compared these results to current demographic parameters estimated in a telemetry-based study conducted between 2001 and 2004. These results show that survival has decreased substantially from the early 1990s to the present and is generally lowest in the north-central portion of the population's range. The greatest temporal decrease in survival was for adult females, and variation in the survival of this age/sex class is primarily responsible for regulating population growth and driving population trends. Our results can be used to focus future research on southern sea otters by highlighting the life history stages and mortality factors most relevant to conservation. More broadly, we have illustrated how the powerful and relatively straightforward tools of information-theoretic-based model fitting can be used to sort through and parameterize quite complex demographic modeling frameworks. ?? 2006 by the Ecological Society of America.
Ikezaki, Yuka; Suyama, Yoshihisa; Middleton, Beth A.; Tsumura, Yoshihiko; Teshima, Kousuke; Tachida, Hidenori; Kusumi, Junko
2016-01-01
PREMISE OF THE STUDY: Studies of natural genetic variation can elucidate the genetic basis of phenotypic variation and the past population structure of species. Our study species, Taxodium distichum, is a unique conifer that inhabits the flood plains and swamps of North America. Morphological and ecological differences in two varieties, T. distichum var. distichum (bald cypress) and T. distichum var. imbricarium (pond cypress), are well known, but little is known about the level of genetic differentiation between the varieties and the demographic history of local populations.METHODS: We analyzed nucleotide polymorphisms at 47 nuclear loci from 96 individuals collected from the Mississippi River Alluvial Valley (MRAV), and Gulf Coastal populations in Texas, Louisiana, and Florida using high-throughput DNA sequencing. Standard population genetic statistics were calculated, and demographic parameters were estimated using a composite-likelihood approach.KEY RESULTS: Taxodium distichum in North America can be divided into at least three genetic groups, bald cypress in the MRAV and Texas, bald cypress in Florida, and pond cypress in Florida. The levels of genetic differentiation among the groups were low but significant. Several loci showed the signatures of positive selection, which might be responsible for local adaptation or varietal differentiation.CONCLUSIONS: Bald cypress was genetically differentiated into two geographical groups, and the boundary was located between the MRAV and Florida. This differentiation could be explained by population expansion from east to west. Despite the overlap of the two varieties’ ranges, they were genetically differentiated in Florida. The estimated demographic parameters suggested that pond cypress split from bald cypress during the late Miocene.
Whittington, Jesse; Sawaya, Michael A.
2015-01-01
Capture-recapture studies are frequently used to monitor the status and trends of wildlife populations. Detection histories from individual animals are used to estimate probability of detection and abundance or density. The accuracy of abundance and density estimates depends on the ability to model factors affecting detection probability. Non-spatial capture-recapture models have recently evolved into spatial capture-recapture models that directly include the effect of distances between an animal’s home range centre and trap locations on detection probability. Most studies comparing non-spatial and spatial capture-recapture biases focussed on single year models and no studies have compared the accuracy of demographic parameter estimates from open population models. We applied open population non-spatial and spatial capture-recapture models to three years of grizzly bear DNA-based data from Banff National Park and simulated data sets. The two models produced similar estimates of grizzly bear apparent survival, per capita recruitment, and population growth rates but the spatial capture-recapture models had better fit. Simulations showed that spatial capture-recapture models produced more accurate parameter estimates with better credible interval coverage than non-spatial capture-recapture models. Non-spatial capture-recapture models produced negatively biased estimates of apparent survival and positively biased estimates of per capita recruitment. The spatial capture-recapture grizzly bear population growth rates and 95% highest posterior density averaged across the three years were 0.925 (0.786–1.071) for females, 0.844 (0.703–0.975) for males, and 0.882 (0.779–0.981) for females and males combined. The non-spatial capture-recapture population growth rates were 0.894 (0.758–1.024) for females, 0.825 (0.700–0.948) for males, and 0.863 (0.771–0.957) for both sexes. The combination of low densities, low reproductive rates, and predominantly negative population growth rates suggest that Banff National Park’s population of grizzly bears requires continued conservation-oriented management actions. PMID:26230262
Complex Population Dynamics and the Coalescent Under Neutrality
Volz, Erik M.
2012-01-01
Estimates of the coalescent effective population size Ne can be poorly correlated with the true population size. The relationship between Ne and the population size is sensitive to the way in which birth and death rates vary over time. The problem of inference is exacerbated when the mechanisms underlying population dynamics are complex and depend on many parameters. In instances where nonparametric estimators of Ne such as the skyline struggle to reproduce the correct demographic history, model-based estimators that can draw on prior information about population size and growth rates may be more efficient. A coalescent model is developed for a large class of populations such that the demographic history is described by a deterministic nonlinear dynamical system of arbitrary dimension. This class of demographic model differs from those typically used in population genetics. Birth and death rates are not fixed, and no assumptions are made regarding the fraction of the population sampled. Furthermore, the population may be structured in such a way that gene copies reproduce both within and across demes. For this large class of models, it is shown how to derive the rate of coalescence, as well as the likelihood of a gene genealogy with heterochronous sampling and labeled taxa, and how to simulate a coalescent tree conditional on a complex demographic history. This theoretical framework encapsulates many of the models used by ecologists and epidemiologists and should facilitate the integration of population genetics with the study of mathematical population dynamics. PMID:22042576
Dunham, Kylee; Grand, James B.
2016-01-01
We examined the effects of complexity and priors on the accuracy of models used to estimate ecological and observational processes, and to make predictions regarding population size and structure. State-space models are useful for estimating complex, unobservable population processes and making predictions about future populations based on limited data. To better understand the utility of state space models in evaluating population dynamics, we used them in a Bayesian framework and compared the accuracy of models with differing complexity, with and without informative priors using sequential importance sampling/resampling (SISR). Count data were simulated for 25 years using known parameters and observation process for each model. We used kernel smoothing to reduce the effect of particle depletion, which is common when estimating both states and parameters with SISR. Models using informative priors estimated parameter values and population size with greater accuracy than their non-informative counterparts. While the estimates of population size and trend did not suffer greatly in models using non-informative priors, the algorithm was unable to accurately estimate demographic parameters. This model framework provides reasonable estimates of population size when little to no information is available; however, when information on some vital rates is available, SISR can be used to obtain more precise estimates of population size and process. Incorporating model complexity such as that required by structured populations with stage-specific vital rates affects precision and accuracy when estimating latent population variables and predicting population dynamics. These results are important to consider when designing monitoring programs and conservation efforts requiring management of specific population segments.
Sartain-Iverson, Autumn R.; Hart, Kristen M.; Fujisaki, Ikuko; Cherkiss, Michael S.; Pollock, Clayton; Lundgren, Ian; Hillis-Starr, Zandy
2016-01-01
Hawksbill sea turtles (Eretmochelys imbricata) are circumtropically distributed and listed as Critically Endangered by the IUCN (Meylan & Donnelly 1999; NMFS & USFWS 1993). To aid in population recovery and protection, the Hawksbill Recovery Plan identified the need to determine demographic information for hawksbills, such as distribution, abundance, seasonal movements, foraging areas (sections 121 and 2211), growth rates, and survivorship (section 2213, NMFS & USFWS 1993). Mark-recapture analyses are helpful in estimating demographic parameters and have been used for hawksbills throughout the Caribbean (e.g., Richardson et al. 1999; Velez-Zuazo et al. 2008); integral to these studies are recaptures at the nesting site as well as remigration interval estimates (Hays 2000). Estimates of remigration intervals (the duration between nesting seasons) are critical to marine turtle population estimates and measures of nesting success (Hays 2000; Richardson et al. 1999). Although hawksbills in the Caribbean generally show natal philopatry and nesting-site fidelity (Bass et al. 1996; Bowen et al. 2007), exceptions to this have been observed for hawksbills and other marine turtles (Bowen & Karl 2007; Diamond 1976; Esteban et al. 2015; Hart et al. 2013). This flexibility in choosing a nesting beach could therefore affect the apparent remigration interval and subsequently, region-wide population counts.
Refusal bias in HIV prevalence estimates from nationally representative seroprevalence surveys.
Reniers, Georges; Eaton, Jeffrey
2009-03-13
To assess the relationship between prior knowledge of one's HIV status and the likelihood to refuse HIV testing in populations-based surveys and explore its potential for producing bias in HIV prevalence estimates. Using longitudinal survey data from Malawi, we estimate the relationship between prior knowledge of HIV-positive status and subsequent refusal of an HIV test. We use that parameter to develop a heuristic model of refusal bias that is applied to six Demographic and Health Surveys, in which refusal by HIV status is not observed. The model only adjusts for refusal bias conditional on a completed interview. Ecologically, HIV prevalence, prior testing rates and refusal for HIV testing are highly correlated. Malawian data further suggest that amongst individuals who know their status, HIV-positive individuals are 4.62 (95% confidence interval, 2.60-8.21) times more likely to refuse testing than HIV-negative ones. On the basis of that parameter and other inputs from the Demographic and Health Surveys, our model predicts downward bias in national HIV prevalence estimates ranging from 1.5% (95% confidence interval, 0.7-2.9) for Senegal to 13.3% (95% confidence interval, 7.2-19.6) for Malawi. In absolute terms, bias in HIV prevalence estimates is negligible for Senegal but 1.6 (95% confidence interval, 0.8-2.3) percentage points for Malawi. Downward bias is more severe in urban populations. Because refusal rates are higher in men, seroprevalence surveys also tend to overestimate the female-to-male ratio of infections. Prior knowledge of HIV status informs decisions to participate in seroprevalence surveys. Informed refusals may produce bias in estimates of HIV prevalence and the sex ratio of infections.
Geographic variation in survival and migratory tendency among North American Common Mergansers
Pearce, J.M.; Reed, J.A.; Flint, Paul L.
2005-01-01
Movement ecology and demographic parameters for the Common Merganser (Mergus merganser americanus) in North America are poorly known. We used band-recovery data from five locations across North America spanning the years 1938-1998 to examine migratory patterns and estimate survival rates. We examined competing time-invariant, age-graduated models with program MARK to study sources of variation in survival and reporting probability. We considered age, sex, geographic location, and the use of nasal saddles on hatching year birds at one location as possible sources of variation. Year-of-banding was included as a covariate in a post-hoc analysis. We found that migratory tendency, defined as the average distance between banding and recovery locations, varied geographically. Similarly, all models accounting for the majority of variation in recovery and survival probabilities included location of banding. Models that included age and sex received less support, but we lacked sufficient data to adequately assess these parameters. Model-averaged estimates of annual survival ranged from 0.21 in Michigan to 0.82 in Oklahoma. Heterogeneity in migration tendency and survival suggests that demographic patterns may vary across geographic scales, with implications for the population dynamics of this species.
Norman, Janette A.; Blackmore, Caroline J.; Rourke, Meaghan; Christidis, Les
2014-01-01
Mitochondrial sequence data is often used to reconstruct the demographic history of Pleistocene populations in an effort to understand how species have responded to past climate change events. However, departures from neutral equilibrium conditions can confound evolutionary inference in species with structured populations or those that have experienced periods of population expansion or decline. Selection can affect patterns of mitochondrial DNA variation and variable mutation rates among mitochondrial genes can compromise inferences drawn from single markers. We investigated the contribution of these factors to patterns of mitochondrial variation and estimates of time to most recent common ancestor (TMRCA) for two clades in a co-operatively breeding avian species, the white-browed babbler Pomatostomus superciliosus. Both the protein-coding ND3 gene and hypervariable domain I control region sequences showed departures from neutral expectations within the superciliosus clade, and a two-fold difference in TMRCA estimates. Bayesian phylogenetic analysis provided evidence of departure from a strict clock model of molecular evolution in domain I, leading to an over-estimation of TMRCA for the superciliosus clade at this marker. Our results suggest mitochondrial studies that attempt to reconstruct Pleistocene demographic histories should rigorously evaluate data for departures from neutral equilibrium expectations, including variation in evolutionary rates across multiple markers. Failure to do so can lead to serious errors in the estimation of evolutionary parameters and subsequent demographic inferences concerning the role of climate as a driver of evolutionary change. These effects may be especially pronounced in species with complex social structures occupying heterogeneous environments. We propose that environmentally driven differences in social structure may explain observed differences in evolutionary rate of domain I sequences, resulting from longer than expected retention times for matriarchal lineages in the superciliosus clade. PMID:25181547
An assessment of bird habitat quality using population growth rates
Knutson, M.G.; Powell, L.A.; Hines, R.K.; Friberg, M.A.; Niemi, G.J.
2006-01-01
Survival and reproduction directly affect population growth rate (lambda) making lambda a fundamental parameter for assessing habitat quality. We used field data, literature review, and a computer simulation to predict annual productivity and lambda for several species of landbirds breeding in floodplain and upland forests in the Midwestern United States. We monitored 1735 nests of 27 species; 760 nests were in the uplands and 975 were in the floodplain. Each type of forest habitat (upland and floodplain) was a source habitat for some species. Despite a relatively low proportion of regional forest cover, the majority of species had stable or increasing populations in all or some habitats, including six species of conservation concern. In our search for a simple analog for lambda, we found that only adult apparent survival, juvenile survival, and annual productivity were correlated with lambda; daily nest survival and relative abundance estimated from point counts were not. Survival and annual productivity are among the most costly demographic parameters to measure and there does not seem to be a low-cost alternative. In addition, our literature search revealed that the demographic parameters needed to model annual productivity and lambda were unavailable for several species. More collective effort across North America is needed to fill the gaps in our knowledge of demographic parameters necessary to model both annual productivity and lambda. Managers can use habitat-specific predictions of annual productivity to compare habitat quality among species and habitats for purposes of evaluating management plans.
Pierce, Gary L; Casey, Darren P; Fiedorowicz, Jess G; Seals, Douglas R; Curry, Timothy B; Barnes, Jill N; Wilson, DeMaris R; Stauss, Harald M
2013-07-01
We hypothesized that demographic/anthropometric parameters can be used to estimate effective reflecting distance (EfRD), required to derive aortic pulse wave velocity (APWV), a prognostic marker of cardiovascular risk, from peripheral waveforms and that such estimates can discriminate differences in APWV and EfRD with aging and habitual endurance exercise in healthy adults. Ascending aortic pressure waveforms were derived from peripheral waveforms (brachial artery pressure, n = 25; and finger volume pulse, n = 15) via a transfer function and then used to determine the time delay between forward- and backward-traveling waves (Δtf-b). True EfRDs were computed as directly measured carotid-femoral pulse wave velocity (CFPWV) × 1/2Δtf-b and then used in regression analysis to establish an equation for EfRD based on demographic/anthropometric data (EfRD = 0.173·age + 0.661·BMI + 34.548 cm, where BMI is body mass index). We found good agreement between true and estimated APWV (Pearson's R² = 0.43; intraclass correlation = 0.64; both P < 0.05) and EfRD (R² = 0.24; intraclass correlation = 0.40; both P < 0.05). In young sedentary (22 ± 2 years, n = 6), older sedentary (62 ± 1 years, n = 24), and older endurance-trained (61 ± 2 years, n = 14) subjects, EfRD (from demographic/anthropometric parameters), APWV, and 1/2Δtf-b (from brachial artery pressure waveforms) were 52.0 ± 0.5, 61.8 ± 0.4, and 60.6 ± 0.5 cm; 6.4 ± 0.3, 9.6 ± 0.2, and 8.1 ± 0.2 m/s; and 82 ± 3, 65 ± 1 and 76 ± 2 ms (all P < 0.05), respectively. Our results demonstrate that APWV derived from peripheral waveforms using age and BMI to estimate EfRD correlates with CFPWV in healthy adults. This method can reliably detect the distal shift of the reflecting site with age and the increase in APWV with sedentary aging that is attenuated with habitual endurance exercise.
Estimating tag loss of the Atlantic Horseshoe crab, Limulus polyphemus, using a multi-state model
Butler, Catherine Alyssa; McGowan, Conor P.; Grand, James B.; Smith, David
2012-01-01
The Atlantic Horseshoe crab, Limulus polyphemus, is a valuable resource along the Mid-Atlantic coast which has, in recent years, experienced new management paradigms due to increased concern about this species role in the environment. While current management actions are underway, many acknowledge the need for improved and updated parameter estimates to reduce the uncertainty within the management models. Specifically, updated and improved estimates of demographic parameters such as adult crab survival in the regional population of interest, Delaware Bay, could greatly enhance these models and improve management decisions. There is however, some concern that difficulties in tag resighting or complete loss of tags could be occurring. As apparent from the assumptions of a Jolly-Seber model, loss of tags can result in a biased estimate and underestimate a survival rate. Given that uncertainty, as a first step towards estimating an unbiased estimate of adult survival, we first took steps to estimate the rate of tag loss. Using data from a double tag mark-resight study conducted in Delaware Bay and Program MARK, we designed a multi-state model to allow for the estimation of mortality of each tag separately and simultaneously.
Demography of common toads after local extirpation of co-occurring midwife toads
Bosch, Jaime; Fernandez-Beaskoetxea, S; Scherer, R.; Amburgey, Staci; Muths, Erin L.
2014-01-01
Estimating demographic parameters like survival or recruitment provides insight into the state and trajectory of populations, but understanding the contexts influencing those parameters, including both biotic and abiotic factors, is particularly important for management and conservation. At a high elevation national park in Central Spain, common toads (Bufo bufo) are apparently taking advantage of the near-extirpation of the midwife toad (Alytes obstetricans), as colonization into new breeding ponds is evident. Within this scenario, we expected demographic parameters of common toad populations tobe affected favorably by the putative release from competition. However, we found the population growth rate was negative in 4 of 5 years at the long-standing population; survival probability at the long-standing population and newly-colonised breeding ponds was lower than reported for other toads living at high elevations and the probability of recruitment was inadequate to compensate for the survival rate in maintaining a positive trajectory for either of the breeding ponds. We assessed weather covariates and disease for their contribution to the context that may be limiting the common toad’s successful use of the niche vacated by the midwife toad.
Are camera surveys useful for assessing recruitment in white-tailed deer?
Chitwood, M. Colter; Lashley, Marcus A.; Kilgo, John C.; ...
2016-12-27
Camera surveys commonly are used by managers and hunters to estimate white-tailed deer Odocoileus virginianus density and demographic rates. Though studies have documented biases and inaccuracies in the camera survey methodology, camera traps remain popular due to ease of use, cost-effectiveness, and ability to survey large areas. Because recruitment is a key parameter in ungulate population dynamics, there is a growing need to test the effectiveness of camera surveys for assessing fawn recruitment. At Savannah River Site, South Carolina, we used six years of camera-based recruitment estimates (i.e. fawn:doe ratio) to predict concurrently collected annual radiotag-based survival estimates. The coefficientmore » of determination (R) was 0.445, indicating some support for the viability of cameras to reflect recruitment. Here, we added two years of data from Fort Bragg Military Installation, North Carolina, which improved R to 0.621 without accounting for site-specific variability. Also, we evaluated the correlation between year-to-year changes in recruitment and survival using the Savannah River Site data; R was 0.758, suggesting that camera-based recruitment could be useful as an indicator of the trend in survival. Because so few researchers concurrently estimate survival and camera-based recruitment, examining this relationship at larger spatial scales while controlling for numerous confounding variables remains difficult. We believe that future research should test the validity of our results from other areas with varying deer and camera densities, as site (e.g. presence of feral pigs Sus scrofa) and demographic (e.g. fawn age at time of camera survey) parameters may have a large influence on detectability. Until such biases are fully quantified, we urge researchers and managers to use caution when advocating the use of camera-based recruitment estimates.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chitwood, M. Colter; Lashley, Marcus A.; Kilgo, John C.
Camera surveys commonly are used by managers and hunters to estimate white-tailed deer Odocoileus virginianus density and demographic rates. Though studies have documented biases and inaccuracies in the camera survey methodology, camera traps remain popular due to ease of use, cost-effectiveness, and ability to survey large areas. Because recruitment is a key parameter in ungulate population dynamics, there is a growing need to test the effectiveness of camera surveys for assessing fawn recruitment. At Savannah River Site, South Carolina, we used six years of camera-based recruitment estimates (i.e. fawn:doe ratio) to predict concurrently collected annual radiotag-based survival estimates. The coefficientmore » of determination (R) was 0.445, indicating some support for the viability of cameras to reflect recruitment. Here, we added two years of data from Fort Bragg Military Installation, North Carolina, which improved R to 0.621 without accounting for site-specific variability. Also, we evaluated the correlation between year-to-year changes in recruitment and survival using the Savannah River Site data; R was 0.758, suggesting that camera-based recruitment could be useful as an indicator of the trend in survival. Because so few researchers concurrently estimate survival and camera-based recruitment, examining this relationship at larger spatial scales while controlling for numerous confounding variables remains difficult. We believe that future research should test the validity of our results from other areas with varying deer and camera densities, as site (e.g. presence of feral pigs Sus scrofa) and demographic (e.g. fawn age at time of camera survey) parameters may have a large influence on detectability. Until such biases are fully quantified, we urge researchers and managers to use caution when advocating the use of camera-based recruitment estimates.« less
Heinonen, Johannes P M; Palmer, Stephen C F; Redpath, Steve M; Travis, Justin M J
2014-01-01
Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions.
Heinonen, Johannes P. M.; Palmer, Stephen C. F.; Redpath, Steve M.; Travis, Justin M. J.
2014-01-01
Individual-based models have gained popularity in ecology, and enable simultaneous incorporation of spatial explicitness and population dynamic processes to understand spatio-temporal patterns of populations. We introduce an individual-based model for understanding and predicting spatial hen harrier (Circus cyaneus) population dynamics in Great Britain. The model uses a landscape with habitat, prey and game management indices. The hen harrier population was initialised according to empirical census estimates for 1988/89 and simulated until 2030, and predictions for 1998, 2004 and 2010 were compared to empirical census estimates for respective years. The model produced a good qualitative match to overall trends between 1989 and 2010. Parameter explorations revealed relatively high elasticity in particular to demographic parameters such as juvenile male mortality. This highlights the need for robust parameter estimates from empirical research. There are clearly challenges for replication of real-world population trends, but this model provides a useful tool for increasing understanding of drivers of hen harrier dynamics and focusing research efforts in order to inform conflict management decisions. PMID:25405860
Scaling in sensitivity analysis
Link, W.A.; Doherty, P.F.
2002-01-01
Population matrix models allow sets of demographic parameters to be summarized by a single value 8, the finite rate of population increase. The consequences of change in individual demographic parameters are naturally measured by the corresponding changes in 8; sensitivity analyses compare demographic parameters on the basis of these changes. These comparisons are complicated by issues of scale. Elasticity analysis attempts to deal with issues of scale by comparing the effects of proportional changes in demographic parameters, but leads to inconsistencies in evaluating demographic rates. We discuss this and other problems of scaling in sensitivity analysis, and suggest a simple criterion for choosing appropriate scales. We apply our suggestions to data for the killer whale, Orcinus orca.
Establishing endangered species recovery criteria using predictive simulation modeling
McGowan, Conor P.; Catlin, Daniel H.; Shaffer, Terry L.; Gratto-Trevor, Cheri L.; Aron, Carol
2014-01-01
Listing a species under the Endangered Species Act (ESA) and developing a recovery plan requires U.S. Fish and Wildlife Service to establish specific and measurable criteria for delisting. Generally, species are listed because they face (or are perceived to face) elevated risk of extinction due to issues such as habitat loss, invasive species, or other factors. Recovery plans identify recovery criteria that reduce extinction risk to an acceptable level. It logically follows that the recovery criteria, the defined conditions for removing a species from ESA protections, need to be closely related to extinction risk. Extinction probability is a population parameter estimated with a model that uses current demographic information to project the population into the future over a number of replicates, calculating the proportion of replicated populations that go extinct. We simulated extinction probabilities of piping plovers in the Great Plains and estimated the relationship between extinction probability and various demographic parameters. We tested the fit of regression models linking initial abundance, productivity, or population growth rate to extinction risk, and then, using the regression parameter estimates, determined the conditions required to reduce extinction probability to some pre-defined acceptable threshold. Binomial regression models with mean population growth rate and the natural log of initial abundance were the best predictors of extinction probability 50 years into the future. For example, based on our regression models, an initial abundance of approximately 2400 females with an expected mean population growth rate of 1.0 will limit extinction risk for piping plovers in the Great Plains to less than 0.048. Our method provides a straightforward way of developing specific and measurable recovery criteria linked directly to the core issue of extinction risk. Published by Elsevier Ltd.
EggLib: processing, analysis and simulation tools for population genetics and genomics
2012-01-01
Background With the considerable growth of available nucleotide sequence data over the last decade, integrated and flexible analytical tools have become a necessity. In particular, in the field of population genetics, there is a strong need for automated and reliable procedures to conduct repeatable and rapid polymorphism analyses, coalescent simulations, data manipulation and estimation of demographic parameters under a variety of scenarios. Results In this context, we present EggLib (Evolutionary Genetics and Genomics Library), a flexible and powerful C++/Python software package providing efficient and easy to use computational tools for sequence data management and extensive population genetic analyses on nucleotide sequence data. EggLib is a multifaceted project involving several integrated modules: an underlying computationally efficient C++ library (which can be used independently in pure C++ applications); two C++ programs; a Python package providing, among other features, a high level Python interface to the C++ library; and the egglib script which provides direct access to pre-programmed Python applications. Conclusions EggLib has been designed aiming to be both efficient and easy to use. A wide array of methods are implemented, including file format conversion, sequence alignment edition, coalescent simulations, neutrality tests and estimation of demographic parameters by Approximate Bayesian Computation (ABC). Classes implementing different demographic scenarios for ABC analyses can easily be developed by the user and included to the package. EggLib source code is distributed freely under the GNU General Public License (GPL) from its website http://egglib.sourceforge.net/ where a full documentation and a manual can also be found and downloaded. PMID:22494792
Ozturk, Onur; Arikan, Sanem; Atalay, Ayfer; Atalay, Erol O
2018-05-01
Hb G-Coushatta variant was reported from various populations' parts of the world such as Thai, Korea, Algeria, Thailand, China, Japan and Turkey. In our study, we aimed to discuss the possible historical relationships of the Hb G-Coushatta mutation with the possible migration routes of the world. For this purpose, associated haplotypes were determined using polymorphic loci in the beta globin gene cluster of hemoglobin G-Coushatta and normal populations in Denizli, Turkey. We performed statistical analysis such as haplotype analysis, Hardy-Weinberg equilibrium, measurement of genetic diversity and population differentiation parameters, analysis of molecular variance using F-statistics, historical-demographic analyses, mismatch distribution analysis of both populations and applied the test statistics in Arlequin ver. 3.5 software program. The diversity of haplotypes has been shown to indicate different genetic origins for two populations. However, AMOVA results, molecular diversity parameters and population demographic expansion times showed that the Hb G-Coushatta mutation develops on the normal population gene pool. Our estimated τ values showed the average time since the demographic expansion for normal and Hb G-Coushatta populations ranged from approximately 42,000 to 38,000 ybp, respectively. Our data suggest that Hb G-Coushatta population originate in normal population in Denizli, Turkey. These results support the hypothesis that the multiple origin of Hb G-Coushatta and indicate that mutation may have been triggered the formation of new variants on beta globin haplotypes. © 2018 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc.
EggLib: processing, analysis and simulation tools for population genetics and genomics.
De Mita, Stéphane; Siol, Mathieu
2012-04-11
With the considerable growth of available nucleotide sequence data over the last decade, integrated and flexible analytical tools have become a necessity. In particular, in the field of population genetics, there is a strong need for automated and reliable procedures to conduct repeatable and rapid polymorphism analyses, coalescent simulations, data manipulation and estimation of demographic parameters under a variety of scenarios. In this context, we present EggLib (Evolutionary Genetics and Genomics Library), a flexible and powerful C++/Python software package providing efficient and easy to use computational tools for sequence data management and extensive population genetic analyses on nucleotide sequence data. EggLib is a multifaceted project involving several integrated modules: an underlying computationally efficient C++ library (which can be used independently in pure C++ applications); two C++ programs; a Python package providing, among other features, a high level Python interface to the C++ library; and the egglib script which provides direct access to pre-programmed Python applications. EggLib has been designed aiming to be both efficient and easy to use. A wide array of methods are implemented, including file format conversion, sequence alignment edition, coalescent simulations, neutrality tests and estimation of demographic parameters by Approximate Bayesian Computation (ABC). Classes implementing different demographic scenarios for ABC analyses can easily be developed by the user and included to the package. EggLib source code is distributed freely under the GNU General Public License (GPL) from its website http://egglib.sourceforge.net/ where a full documentation and a manual can also be found and downloaded.
Plant colonization and survival along a hydrological gradient: demography and niche dynamics.
Damgaard, Christian; Merlin, Amandine; Bonis, Anne
2017-01-01
Predicting the effect of a changing environment, e.g., caused by climate change, on realized niche dynamics, and consequently, biodiversity is a challenging scientific question that needs to be addressed. One promising approach is to use estimated demographic parameters for predicting plant abundance and occurrence probabilities. Using longitudinal pinpoint cover data sampled along a hydrological gradient in the Marais poitevin grasslands, France, the effect of the gradient on the demographic probabilities of colonization and survival was estimated. The estimated probabilities and calculated elasticities of survival and colonization covaried with the observed cover of the different species along the hydrological gradient. For example, the flooding tolerant grass A. stolonifera showed a positive response in both colonization and survival to flooding, and the hydrological gradient is clearly the most likely explanation for the occurrence pattern observed for A. stolonifera. The results suggest that knowledge on the processes of colonization and survival of the individual species along the hydrological gradient is sufficient for at least a qualitative understanding of species occurrences along the gradient. The results support the hypothesis that colonization has a predominant role for determining the ecological success along the hydrological gradient compared to survival. Importantly, the study suggests that it may be possible to predict the realized niche of different species from demographic studies. This is encouraging for the important endeavor of predicting realized niche dynamics.
Fottrell, Edward; Byass, Peter; Berhane, Yemane
2008-03-25
As in any measurement process, a certain amount of error may be expected in routine population surveillance operations such as those in demographic surveillance sites (DSSs). Vital events are likely to be missed and errors made no matter what method of data capture is used or what quality control procedures are in place. The extent to which random errors in large, longitudinal datasets affect overall health and demographic profiles has important implications for the role of DSSs as platforms for public health research and clinical trials. Such knowledge is also of particular importance if the outputs of DSSs are to be extrapolated and aggregated with realistic margins of error and validity. This study uses the first 10-year dataset from the Butajira Rural Health Project (BRHP) DSS, Ethiopia, covering approximately 336,000 person-years of data. Simple programmes were written to introduce random errors and omissions into new versions of the definitive 10-year Butajira dataset. Key parameters of sex, age, death, literacy and roof material (an indicator of poverty) were selected for the introduction of errors based on their obvious importance in demographic and health surveillance and their established significant associations with mortality. Defining the original 10-year dataset as the 'gold standard' for the purposes of this investigation, population, age and sex compositions and Poisson regression models of mortality rate ratios were compared between each of the intentionally erroneous datasets and the original 'gold standard' 10-year data. The composition of the Butajira population was well represented despite introducing random errors, and differences between population pyramids based on the derived datasets were subtle. Regression analyses of well-established mortality risk factors were largely unaffected even by relatively high levels of random errors in the data. The low sensitivity of parameter estimates and regression analyses to significant amounts of randomly introduced errors indicates a high level of robustness of the dataset. This apparent inertia of population parameter estimates to simulated errors is largely due to the size of the dataset. Tolerable margins of random error in DSS data may exceed 20%. While this is not an argument in favour of poor quality data, reducing the time and valuable resources spent on detecting and correcting random errors in routine DSS operations may be justifiable as the returns from such procedures diminish with increasing overall accuracy. The money and effort currently spent on endlessly correcting DSS datasets would perhaps be better spent on increasing the surveillance population size and geographic spread of DSSs and analysing and disseminating research findings.
Eaton, Mitchell J.; Link, William A.
2011-01-01
Estimating the age of individuals in wild populations can be of fundamental importance for answering ecological questions, modeling population demographics, and managing exploited or threatened species. Significant effort has been devoted to determining age through the use of growth annuli, secondary physical characteristics related to age, and growth models. Many species, however, either do not exhibit physical characteristics useful for independent age validation or are too rare to justify sacrificing a large number of individuals to establish the relationship between size and age. Length-at-age models are well represented in the fisheries and other wildlife management literature. Many of these models overlook variation in growth rates of individuals and consider growth parameters as population parameters. More recent models have taken advantage of hierarchical structuring of parameters and Bayesian inference methods to allow for variation among individuals as functions of environmental covariates or individual-specific random effects. Here, we describe hierarchical models in which growth curves vary as individual-specific stochastic processes, and we show how these models can be fit using capture–recapture data for animals of unknown age along with data for animals of known age. We combine these independent data sources in a Bayesian analysis, distinguishing natural variation (among and within individuals) from measurement error. We illustrate using data for African dwarf crocodiles, comparing von Bertalanffy and logistic growth models. The analysis provides the means of predicting crocodile age, given a single measurement of head length. The von Bertalanffy was much better supported than the logistic growth model and predicted that dwarf crocodiles grow from 19.4 cm total length at birth to 32.9 cm in the first year and 45.3 cm by the end of their second year. Based on the minimum size of females observed with hatchlings, reproductive maturity was estimated to be at nine years. These size benchmarks are believed to represent thresholds for important demographic parameters; improved estimates of age, therefore, will increase the precision of population projection models. The modeling approach that we present can be applied to other species and offers significant advantages when multiple sources of data are available and traditional aging techniques are not practical.
Kim, Sun Jung; Park, Eun-Cheol; Kim, Sulgi; Nakagawa, Shunichi; Lung, John; Choi, Jong Bum; Ryu, Woo Sang; Min, Too Jae; Shin, Hyun Phil; Kim, Kyudam; Yoo, Ji Won
2014-03-01
To assess the overall quality of life of long-stay nursing home residents with preserved cognition, to examine whether the Centers for Medicare and Medicaid Service's Nursing Home Compare 5-star quality rating system reflects the overall quality of life of such residents, and to examine whether residents' demographics and clinical characteristics affect their quality of life. Quality of life was measured using the Participant Outcomes and Status Measures-Nursing Facility survey, which has 10 sections and 63 items. Total scores range from 20 (lowest possible quality of life) to 100 (highest). Long-stay nursing home residents with preserved cognition (n = 316) were interviewed. The average quality- of-life score was 71.4 (SD: 7.6; range: 45.1-93.0). Multilevel regression models revealed that quality of life was associated with physical impairment (parameter estimate = -0.728; P = .04) and depression (parameter estimate = -3.015; P = .01) but not Nursing Home Compare's overall star rating (parameter estimate = 0.683; P = .12) and not pain (parameter estimate = -0.705; P = .47). The 5-star quality rating system did not reflect the quality of life of long-stay nursing home residents with preserved cognition. Notably, pain was not associated with quality of life, but physical impairment and depression were. Copyright © 2014 American Medical Directors Association, Inc. Published by Elsevier Inc. All rights reserved.
Cabral, Juliano Sarmento; Bond, William J; Midgley, Guy F; Rebelo, Anthony G; Thuiller, Wilfried; Schurr, Frank M
2011-02-01
Wildflower harvesting is an economically important activity of which the ecological effects are poorly understood. We assessed how harvesting of flowers affects shrub persistence and abundance at multiple spatial extents. To this end, we built a process-based model to examine the mean persistence and abundance of wild shrubs whose flowers are subject to harvest (serotinous Proteaceae in the South African Cape Floristic Region). First, we conducted a general sensitivity analysis of how harvesting affects persistence and abundance at nested spatial extents. For most spatial extents and combinations of demographic parameters, persistence and abundance of flowering shrubs decreased abruptly once harvesting rate exceeded a certain threshold. At larger extents, metapopulations supported higher harvesting rates before their persistence and abundance decreased, but persistence and abundance also decreased more abruptly due to harvesting than at smaller extents. This threshold rate of harvest varied with species' dispersal ability, maximum reproductive rate, adult mortality, probability of extirpation or local extinction, strength of Allee effects, and carrying capacity. Moreover, spatial extent interacted with Allee effects and probability of extirpation because both these demographic properties affected the response of local populations to harvesting more strongly than they affected the response of metapopulations. Subsequently, we simulated the effects of harvesting on three Cape Floristic Region Proteaceae species and found that these species reacted differently to harvesting, but their persistence and abundance decreased at low rates of harvest. Our estimates of harvesting rates at maximum sustainable yield differed from those of previous investigations, perhaps because researchers used different estimates of demographic parameters, models of population dynamics, and spatial extent than we did. Good demographic knowledge and careful identification of the spatial extent of interest increases confidence in assessments and monitoring of the effects of harvesting. Our general sensitivity analysis improved understanding of harvesting effects on metapopulation dynamics and allowed qualitative assessment of the probability of extirpation of poorly studied species. ©2010 Society for Conservation Biology.
Bayesian Analysis of Evolutionary Divergence with Genomic Data under Diverse Demographic Models.
Chung, Yujin; Hey, Jody
2017-06-01
We present a new Bayesian method for estimating demographic and phylogenetic history using population genomic data. Several key innovations are introduced that allow the study of diverse models within an Isolation-with-Migration framework. The new method implements a 2-step analysis, with an initial Markov chain Monte Carlo (MCMC) phase that samples simple coalescent trees, followed by the calculation of the joint posterior density for the parameters of a demographic model. In step 1, the MCMC sampling phase, the method uses a reduced state space, consisting of coalescent trees without migration paths, and a simple importance sampling distribution without the demography of interest. Once obtained, a single sample of trees can be used in step 2 to calculate the joint posterior density for model parameters under multiple diverse demographic models, without having to repeat MCMC runs. Because migration paths are not included in the state space of the MCMC phase, but rather are handled by analytic integration in step 2 of the analysis, the method is scalable to a large number of loci with excellent MCMC mixing properties. With an implementation of the new method in the computer program MIST, we demonstrate the method's accuracy, scalability, and other advantages using simulated data and DNA sequences of two common chimpanzee subspecies: Pan troglodytes (P. t.) troglodytes and P. t. verus. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Demographic estimation methods for plants with dormancy
Kery, M.; Gregg, K.B.
2004-01-01
Demographic studies in plants appear simple because unlike animals, plants do not run away. Plant individuals can be marked with, e.g., plastic tags, but often the coordinates of an individual may be sufficient to identify it. Vascular plants in temperate latitudes have a pronounced seasonal life–cycle, so most plant demographers survey their study plots once a year often during or shortly after flowering. Life–states are pervasive in plants, hence the results of a demographic study for an individual can be summarized in a familiar encounter history, such as 0VFVVF000. A zero means that an individual was not seen in a year and a letter denotes its state for years when it was seen aboveground. V and F here stand for vegetative and flowering states, respectively. Probabilities of survival and state transitions can then be obtained by mere counting.Problems arise when there is an unobservable dormant state, i.e., when plants may stay belowground for one or more growing seasons. Encounter histories such as 0VF00F000 may then occur where the meaning of zeroes becomes ambiguous. A zero can either mean a dead or a dormant plant. Various ad hoc methods in wide use among plant ecologists have made strong assumptions about when a zero should be equated to a dormant individual. These methods have never been compared among each other. In our talk and in Kéry et al. (submitted), we show that these ad hoc estimators provide spurious estimates of survival and should not be used.In contrast, if detection probabilities for aboveground plants are known or can be estimated, capturerecapture (CR) models can be used to estimate probabilities of survival and state–transitions and the fraction of the population that is dormant. We have used this approach in two studies of terrestrial orchids, Cleistes bifaria (Kéry et al., submitted) and Cypripedium reginae(Kéry & Gregg, submitted) in West Virginia, U.S.A. For Cleistes, our data comprised one population with a total of 620 marked ramets over 10 years, and for Cypripedium, two populations with 98 and 258 marked ramets over 11 years. We chose the ramet (= single stem or shoot) as the demographic unit of our study since there was no way distinguishing among genets (genet = genetical individual, i.e., the “individual” that animal ecologists are mostly concerned with). This will introduce some non–independence into the data, which can nevertheless be dealt with easily by correcting variances for overdispersion. Using ramets instead of genets has the further advantage that individuals can be assigned to a state such as flowering or vegetative in an unambiguous manner. This is not possible when genets are the demographic units. In all three populations, auxiliary data was available to show that detection probability of aboveground plants was m 0.995We fitted multistate models in program MARK by specifying three states (D, V, F), even though the dormant state D does not occur in the encounter histories. Detection probability is fixed at 1 for the vegetative (V) and the flowering state (F) and at zero for the dormant state (D). Rates of survival and of state transitions as well as slopes of covariate relationships can be estimated and LRT or the AIC machinery be used to select among models. To estimate the fraction of the population in the unobservabledormant state, the encounter histories are collapsed to 0 (plant not observed aboveground) and 1 (plant observed aboveground). The Cormack–Jolly–Seber model without constraints on detection probability is used to estimate detection probability, the complement of which is the estimated fraction of the population in the dormant state.Parameter identifiability is an important issue in multi state models. We used the Catchpole–Morgan–Freeman approach to determine which parameters are estimable in principle in our multi state models. Most of 15 tested models were indeed estimable with the notable exception of the most general model, which has fully interactive state- and time-dependent survival and state transition rates. This model would become identifiable if at least some plants would be excavated in years when they do not show up aboveground.Our analyses for three analyzed populations of Cleistes and Cypripedium yielded annual ramet survival rates ranging from 0.86–0.96. Estimates of the average fraction dormant ranged from 0.02–0.30, but with up to half a population in the dormant state in some years. Ultrastructural modeling enables interesting hypotheses to be tested about the relationships of demographic rates with climatic covariates for instance. Such covariate modeling makes the CR approach particularly interesting for evolutionary–ecological questions about, e.g., the adaptive significance of the dormant state.
Dudgeon, Christine L; Pollock, Kenneth H; Braccini, J Matias; Semmens, Jayson M; Barnett, Adam
2015-07-01
Capture-mark-recapture models are useful tools for estimating demographic parameters but often result in low precision when recapture rates are low. Low recapture rates are typical in many study systems including fishing-based studies. Incorporating auxiliary data into the models can improve precision and in some cases enable parameter estimation. Here, we present a novel application of acoustic telemetry for the estimation of apparent survival and abundance within capture-mark-recapture analysis using open population models. Our case study is based on simultaneously collecting longline fishing and acoustic telemetry data for a large mobile apex predator, the broadnose sevengill shark (Notorhynchus cepedianus), at a coastal site in Tasmania, Australia. Cormack-Jolly-Seber models showed that longline data alone had very low recapture rates while acoustic telemetry data for the same time period resulted in at least tenfold higher recapture rates. The apparent survival estimates were similar for the two datasets but the acoustic telemetry data showed much greater precision and enabled apparent survival parameter estimation for one dataset, which was inestimable using fishing data alone. Combined acoustic telemetry and longline data were incorporated into Jolly-Seber models using a Monte Carlo simulation approach. Abundance estimates were comparable to those with longline data only; however, the inclusion of acoustic telemetry data increased precision in the estimates. We conclude that acoustic telemetry is a useful tool for incorporating in capture-mark-recapture studies in the marine environment. Future studies should consider the application of acoustic telemetry within this framework when setting up the study design and sampling program.
Demographic analysis from summaries of an age-structured population
Link, William A.; Royle, J. Andrew; Hatfield, Jeff S.
2003-01-01
Demographic analyses of age-structured populations typically rely on life history data for individuals, or when individual animals are not identified, on information about the numbers of individuals in each age class through time. While it is usually difficult to determine the age class of a randomly encountered individual, it is often the case that the individual can be readily and reliably assigned to one of a set of age classes. For example, it is often possible to distinguish first-year from older birds. In such cases, the population age structure can be regarded as a latent variable governed by a process prior, and the data as summaries of this latent structure. In this article, we consider the problem of uncovering the latent structure and estimating process parameters from summaries of age class information. We present a demographic analysis for the critically endangered migratory population of whooping cranes (Grus americana), based only on counts of first-year birds and of older birds. We estimate age and year-specific survival rates. We address the controversial issue of whether management action on the breeding grounds has influenced recruitment, relating recruitment rates to the number of seventh-year and older birds, and examining the pattern of variation through time in this rate.
Joint Estimation of Contamination, Error and Demography for Nuclear DNA from Ancient Humans
Slatkin, Montgomery
2016-01-01
When sequencing an ancient DNA sample from a hominin fossil, DNA from present-day humans involved in excavation and extraction will be sequenced along with the endogenous material. This type of contamination is problematic for downstream analyses as it will introduce a bias towards the population of the contaminating individual(s). Quantifying the extent of contamination is a crucial step as it allows researchers to account for possible biases that may arise in downstream genetic analyses. Here, we present an MCMC algorithm to co-estimate the contamination rate, sequencing error rate and demographic parameters—including drift times and admixture rates—for an ancient nuclear genome obtained from human remains, when the putative contaminating DNA comes from present-day humans. We assume we have a large panel representing the putative contaminant population (e.g. European, East Asian or African). The method is implemented in a C++ program called ‘Demographic Inference with Contamination and Error’ (DICE). We applied it to simulations and genome data from ancient Neanderthals and modern humans. With reasonable levels of genome sequence coverage (>3X), we find we can recover accurate estimates of all these parameters, even when the contamination rate is as high as 50%. PMID:27049965
Portrait of a small population of boreal toads (Anaxyrus boreas)
Muths, Erin; Scherer, Rick D.
2011-01-01
Much attention has been given to the conservation of small populations, those that are small because of decline, and those that are naturally small. Small populations are of particular interest because ecological theory suggests that they are vulnerable to the deleterious effects of environmental, demographic, and genetic stochasticity as well as natural and human-induced catastrophes. However, testing theory and developing applicable conservation measures for small populations is hampered by sparse data. This lack of information is frequently driven by computational issues with small data sets that can be confounded by the impacts of stressors. We present estimates of demographic parameters from a small population of Boreal Toads (Anaxyrus boreas) that has been surveyed since 2001 by using capture-recapture methods. Estimates of annual adult survival probability are high relative to other Boreal Toad populations, whereas estimates of recruitment rate are low. Despite using simple models, clear patterns emerged from the analyses, suggesting that population size is constrained by low recruitment of adults and is declining slowly. These patterns provide insights that are useful in developing management directions for this small population, and this study serves as an example of the potential for small populations to yield robust and useful information despite sample size constraints.
On the number of New World founders: a population genetic portrait of the peopling of the Americas.
Hey, Jody
2005-06-01
The founding of New World populations by Asian peoples is the focus of considerable archaeological and genetic research, and there persist important questions on when and how these events occurred. Genetic data offer great potential for the study of human population history, but there are significant challenges in discerning distinct demographic processes. A new method for the study of diverging populations was applied to questions on the founding and history of Amerind-speaking Native American populations. The model permits estimation of founding population sizes, changes in population size, time of population formation, and gene flow. Analyses of data from nine loci are consistent with the general portrait that has emerged from archaeological and other kinds of evidence. The estimated effective size of the founding population for the New World is fewer than 80 individuals, approximately 1% of the effective size of the estimated ancestral Asian population. By adding a splitting parameter to population divergence models it becomes possible to develop detailed portraits of human demographic history. Analyses of Asian and New World data support a model of a recent founding of the New World by a population of quite small effective size.
A composite likelihood approach for spatially correlated survival data
Paik, Jane; Ying, Zhiliang
2013-01-01
The aim of this paper is to provide a composite likelihood approach to handle spatially correlated survival data using pairwise joint distributions. With e-commerce data, a recent question of interest in marketing research has been to describe spatially clustered purchasing behavior and to assess whether geographic distance is the appropriate metric to describe purchasing dependence. We present a model for the dependence structure of time-to-event data subject to spatial dependence to characterize purchasing behavior from the motivating example from e-commerce data. We assume the Farlie-Gumbel-Morgenstern (FGM) distribution and then model the dependence parameter as a function of geographic and demographic pairwise distances. For estimation of the dependence parameters, we present pairwise composite likelihood equations. We prove that the resulting estimators exhibit key properties of consistency and asymptotic normality under certain regularity conditions in the increasing-domain framework of spatial asymptotic theory. PMID:24223450
A composite likelihood approach for spatially correlated survival data.
Paik, Jane; Ying, Zhiliang
2013-01-01
The aim of this paper is to provide a composite likelihood approach to handle spatially correlated survival data using pairwise joint distributions. With e-commerce data, a recent question of interest in marketing research has been to describe spatially clustered purchasing behavior and to assess whether geographic distance is the appropriate metric to describe purchasing dependence. We present a model for the dependence structure of time-to-event data subject to spatial dependence to characterize purchasing behavior from the motivating example from e-commerce data. We assume the Farlie-Gumbel-Morgenstern (FGM) distribution and then model the dependence parameter as a function of geographic and demographic pairwise distances. For estimation of the dependence parameters, we present pairwise composite likelihood equations. We prove that the resulting estimators exhibit key properties of consistency and asymptotic normality under certain regularity conditions in the increasing-domain framework of spatial asymptotic theory.
2012-03-01
O4 19.5% 14.7% Married 65.0% 61.8% Unmarried 35.0% 38.2% *2010 DoD Demographics Report D. ESTIMATION OF THE PARAMETERS The study uses the...120 $240 $360 $480 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 B id ( in $ 1 ,0 0 0 ’s ) Quality Score Bid vs Quality Score 27 VI
Climate-driven vital rates do not always mean climate-driven population.
Tavecchia, Giacomo; Tenan, Simone; Pradel, Roger; Igual, José-Manuel; Genovart, Meritxell; Oro, Daniel
2016-12-01
Current climatic changes have increased the need to forecast population responses to climate variability. A common approach to address this question is through models that project current population state using the functional relationship between demographic rates and climatic variables. We argue that this approach can lead to erroneous conclusions when interpopulation dispersal is not considered. We found that immigration can release the population from climate-driven trajectories even when local vital rates are climate dependent. We illustrated this using individual-based data on a trans-equatorial migratory seabird, the Scopoli's shearwater Calonectris diomedea, in which the variation of vital rates has been associated with large-scale climatic indices. We compared the population annual growth rate λ i , estimated using local climate-driven parameters with ρ i , a population growth rate directly estimated from individual information and that accounts for immigration. While λ i varied as a function of climatic variables, reflecting the climate-dependent parameters, ρ i did not, indicating that dispersal decouples the relationship between population growth and climate variables from that between climatic variables and vital rates. Our results suggest caution when assessing demographic effects of climatic variability especially in open populations for very mobile organisms such as fish, marine mammals, bats, or birds. When a population model cannot be validated or it is not detailed enough, ignoring immigration might lead to misleading climate-driven projections. © 2016 John Wiley & Sons Ltd.
Bayesian inference of a historical bottleneck in a heavily exploited marine mammal.
Hoffman, J I; Grant, S M; Forcada, J; Phillips, C D
2011-10-01
Emerging Bayesian analytical approaches offer increasingly sophisticated means of reconstructing historical population dynamics from genetic data, but have been little applied to scenarios involving demographic bottlenecks. Consequently, we analysed a large mitochondrial and microsatellite dataset from the Antarctic fur seal Arctocephalus gazella, a species subjected to one of the most extreme examples of uncontrolled exploitation in history when it was reduced to the brink of extinction by the sealing industry during the late eighteenth and nineteenth centuries. Classical bottleneck tests, which exploit the fact that rare alleles are rapidly lost during demographic reduction, yielded ambiguous results. In contrast, a strong signal of recent demographic decline was detected using both Bayesian skyline plots and Approximate Bayesian Computation, the latter also allowing derivation of posterior parameter estimates that were remarkably consistent with historical observations. This was achieved using only contemporary samples, further emphasizing the potential of Bayesian approaches to address important problems in conservation and evolutionary biology. © 2011 Blackwell Publishing Ltd.
Using open robust design models to estimate temporary emigration from capture-recapture data.
Kendall, W L; Bjorkland, R
2001-12-01
Capture-recapture studies are crucial in many circumstances for estimating demographic parameters for wildlife and fish populations. Pollock's robust design, involving multiple sampling occasions per period of interest, provides several advantages over classical approaches. This includes the ability to estimate the probability of being present and available for detection, which in some situations is equivalent to breeding probability. We present a model for estimating availability for detection that relaxes two assumptions required in previous approaches. The first is that the sampled population is closed to additions and deletions across samples within a period of interest. The second is that each member of the population has the same probability of being available for detection in a given period. We apply our model to estimate survival and breeding probability in a study of hawksbill sea turtles (Eretmochelys imbricata), where previous approaches are not appropriate.
Using open robust design models to estimate temporary emigration from capture-recapture data
Kendall, W.L.; Bjorkland, R.
2001-01-01
Capture-recapture studies are crucial in many circumstances for estimating demographic parameters for wildlife and fish populations. Pollock's robust design, involving multiple sampling occasions per period of interest, provides several advantages over classical approaches. This includes the ability to estimate the probability of being present and available for detection, which in some situations is equivalent to breeding probability. We present a model for estimating availability for detection that relaxes two assumptions required in previous approaches. The first is that the sampled population is closed to additions and deletions across samples within a period of interest. The second is that each member of the population has the same probability of being available for detection in a given period. We apply our model to estimate survival and breeding probability in a study of hawksbill sea turtles (Eretmochelys imbricata), where previous approaches are not appropriate.
Accounting for rate variation among lineages in comparative demographic analyses
Hope, Andrew G.; Ho, Simon Y. W.; Malaney, Jason L.; Cook, Joseph A.; Talbot, Sandra L.
2014-01-01
Genetic analyses of contemporary populations can be used to estimate the demographic histories of species within an ecological community. Comparison of these demographic histories can shed light on community responses to past climatic events. However, species experience different rates of molecular evolution, and this presents a major obstacle to comparative demographic analyses. We address this problem by using a Bayesian relaxed-clock method to estimate the relative evolutionary rates of 22 small mammal taxa distributed across northwestern North America. We found that estimates of the relative molecular substitution rate for each taxon were consistent across the range of sampling schemes that we compared. Using three different reference rates, we rescaled the relative rates so that they could be used to estimate absolute evolutionary timescales. Accounting for rate variation among taxa led to temporal shifts in our skyline-plot estimates of demographic history, highlighting both uniform and idiosyncratic evolutionary responses to directional climate trends for distinct ecological subsets of the small mammal community. Our approach can be used in evolutionary analyses of populations from multiple species, including comparative demographic studies.
Marginal regression approach for additive hazards models with clustered current status data.
Su, Pei-Fang; Chi, Yunchan
2014-01-15
Current status data arise naturally from tumorigenicity experiments, epidemiology studies, biomedicine, econometrics and demographic and sociology studies. Moreover, clustered current status data may occur with animals from the same litter in tumorigenicity experiments or with subjects from the same family in epidemiology studies. Because the only information extracted from current status data is whether the survival times are before or after the monitoring or censoring times, the nonparametric maximum likelihood estimator of survival function converges at a rate of n(1/3) to a complicated limiting distribution. Hence, semiparametric regression models such as the additive hazards model have been extended for independent current status data to derive the test statistics, whose distributions converge at a rate of n(1/2) , for testing the regression parameters. However, a straightforward application of these statistical methods to clustered current status data is not appropriate because intracluster correlation needs to be taken into account. Therefore, this paper proposes two estimating functions for estimating the parameters in the additive hazards model for clustered current status data. The comparative results from simulation studies are presented, and the application of the proposed estimating functions to one real data set is illustrated. Copyright © 2013 John Wiley & Sons, Ltd.
Ba, A; Diouf, K; Guilhaumon, F; Panfili, J
2015-10-01
Age and growth of Rhizoprionodon acutus were estimated from vertebrae age bands. From December 2009 to November 2010, 423 R. acutus between 37 and 112 cm total length (LT ) were sampled along the Senegalese coast. Marginal increment ratio was used to check annual band deposition. Three growth models were adjusted to the length at age and compared using Akaike's information criterion. The Gompertz growth model with estimated size at birth appeared to be the best and resulted in growth parameters of L∞ = 139.55 (LT ) and K = 0.17 year(-1) for females and L∞ = 126.52 (LT ) and K = 0.18 year(-1) for males. The largest female and male examined were 8 and 9 years old, but the majority was between 1 and 3 years old. Ages at maturity estimated were 5.8 and 4.8 years for females and males, respectively. These results suggest that R. acutus is a slow-growing species, which render the species particularly vulnerable to heavy fishery exploitation. The growth parameters estimated in this study are crucial for stock assessments and for demographic analyses to evaluate the sustainability of commercial harvests. © 2015 The Fisheries Society of the British Isles.
Miller, Tom E X
2007-07-01
1. It is widely accepted that density-dependent processes play an important role in most natural populations. However, persistent challenges in our understanding of density-dependent population dynamics include evaluating the shape of the relationship between density and demographic rates (linear, concave, convex), and identifying extrinsic factors that can mediate this relationship. 2. I studied the population dynamics of the cactus bug Narnia pallidicornis on host plants (Opuntia imbricata) that varied naturally in relative reproductive effort (RRE, the proportion of meristems allocated to reproduction), an important plant quality trait. I manipulated per-plant cactus bug densities, quantified subsequent dynamics, and fit stage-structured models to the experimental data to ask if and how density influences demographic parameters. 3. In the field experiment, I found that populations with variable starting densities quickly converged upon similar growth trajectories. In the model-fitting analyses, the data strongly supported a model that defined the juvenile cactus bug retention parameter (joint probability of surviving and not dispersing) as a nonlinear decreasing function of density. The estimated shape of this relationship shifted from concave to convex with increasing host-plant RRE. 4. The results demonstrate that host-plant traits are critical sources of variation in the strength and shape of density dependence in insects, and highlight the utility of integrated experimental-theoretical approaches for identifying processes underlying patterns of change in natural populations.
Finch, Colton G.; Pine, William E.; Yackulic, Charles B.; Dodrill, Michael J.; Yard, Michael D.; Gerig, Brandon S.; Coggins,, Lewis G.; Korman, Josh
2016-01-01
The Colorado River below Glen Canyon Dam, Arizona, is part of an adaptive management programme which optimizes dam operations to improve various resources in the downstream ecosystem within Grand Canyon. Understanding how populations of federally endangered humpback chub Gila cypha respond to these dam operations is a high priority. Here, we test hypotheses concerning temporal variation in juvenile humpback chub apparent survival rates and abundance by comparing estimates between hydropeaking and steady discharge regimes over a 3-year period (July 2009–July 2012). The most supported model ignored flow type (steady vs hydropeaking) and estimated a declining trend in daily apparent survival rate across years (99.90%, 99.79% and 99.67% for 2009, 2010 and 2011, respectively). Corresponding abundance of juvenile humpback chub increased temporally; open population model estimates ranged from 615 to 2802 individuals/km, and closed model estimates ranged from 94 to 1515 individuals/km. These changes in apparent survival and abundance may reflect broader trends, or simply represent inter-annual variation. Important findings include (i) juvenile humpback chub are currently surviving and recruiting in the mainstem Colorado River with increasing abundance; (ii) apparent survival does not benefit from steady fall discharges from Glen Canyon Dam; and (iii) direct assessment of demographic parameters for juvenile endangered fish are possible and can rapidly inform management actions in regulated rivers.
McGovern, Mark E.; Canning, David
2015-01-01
Based on models with calibrated parameters for infection, case fatality rates, and vaccine efficacy, basic childhood vaccinations have been estimated to be highly cost effective. We estimated the association of vaccination with mortality directly from survey data. Using 149 cross-sectional Demographic and Health Surveys, we determined the relationship between vaccination coverage and the probability of dying between birth and 5 years of age at the survey cluster level. Our data included approximately 1 million children in 68,490 clusters from 62 countries. We considered the childhood measles, bacillus Calmette-Guérin, diphtheria-pertussis-tetanus, polio, and maternal tetanus vaccinations. Using modified Poisson regression to estimate the relative risk of child mortality in each cluster, we also adjusted for selection bias that resulted from the vaccination status of dead children not being reported. Childhood vaccination, and in particular measles and tetanus vaccination, is associated with substantial reductions in childhood mortality. We estimated that children in clusters with complete vaccination coverage have a relative risk of mortality that is 0.73 (95% confidence interval: 0.68, 0.77) times that of children in a cluster with no vaccinations. Although widely used, basic vaccines still have coverage rates well below 100% in many countries, and our results emphasize the effectiveness of increasing coverage rates in order to reduce child mortality. PMID:26453618
A new model to estimate insulin resistance via clinical parameters in adults with type 1 diabetes.
Zheng, Xueying; Huang, Bin; Luo, Sihui; Yang, Daizhi; Bao, Wei; Li, Jin; Yao, Bin; Weng, Jianping; Yan, Jinhua
2017-05-01
Insulin resistance (IR) is a risk factor to assess the development of micro- and macro-vascular complications in type 1 diabetes (T1D). However, diabetes management in adults with T1D is limited by the difficulty of lacking simple and reliable methods to estimate insulin resistance. The aim of this study was to develop a new model to estimate IR via clinical parameters in adults with T1D. A total of 36 adults with adulthood onset T1D (n = 20) or childhood onset T1D (n = 16) were recruited by quota sampling. After an overnight insulin infusion to stabilize the blood glucose at 5.6 to 7.8 mmol/L, they underwent a 180-minute euglycemic-hyperinsulinemic clamp. Glucose disposal rate (GDR, mg kg -1 min -1 ) was calculated by data collected from the last 30 minutes during the test. Demographic factors (age, sex, and diabetes duration) and metabolic parameters (blood pressure, glycated hemoglobin A 1c [HbA 1c ], waist to hip ratio [WHR], and lipids) were collected to evaluate insulin resistance. Then, age at diabetes onset and clinical parameters were used to develop a model to estimate lnGDR by stepwise linear regression. From the stepwise process, a best model to estimate insulin resistance was generated, including HbA 1c , diastolic blood pressure, and WHR. Age at diabetes onset did not enter any of the models. We proposed the following new model to estimate IR as in GDR for adults with T1D: lnGDR = 4.964 - 0.121 × HbA 1c (%) - 0.012 × diastolic blood pressure (mmHg) - 1.409 × WHR, (adjusted R 2 = 0.616, P < .01). Insulin resistance in adults living with T1D can be estimated using routinely collected clinical parameters. This simple model provides a potential tool for estimating IR in large-scale epidemiological studies of adults with T1D regardless of age at onset. Copyright © 2016 John Wiley & Sons, Ltd.
A new approach to estimate parameters of speciation models with application to apes.
Becquet, Celine; Przeworski, Molly
2007-10-01
How populations diverge and give rise to distinct species remains a fundamental question in evolutionary biology, with important implications for a wide range of fields, from conservation genetics to human evolution. A promising approach is to estimate parameters of simple speciation models using polymorphism data from multiple loci. Existing methods, however, make a number of assumptions that severely limit their applicability, notably, no gene flow after the populations split and no intralocus recombination. To overcome these limitations, we developed a new Markov chain Monte Carlo method to estimate parameters of an isolation-migration model. The approach uses summaries of polymorphism data at multiple loci surveyed in a pair of diverging populations or closely related species and, importantly, allows for intralocus recombination. To illustrate its potential, we applied it to extensive polymorphism data from populations and species of apes, whose demographic histories are largely unknown. The isolation-migration model appears to provide a reasonable fit to the data. It suggests that the two chimpanzee species became reproductively isolated in allopatry approximately 850 Kya, while Western and Central chimpanzee populations split approximately 440 Kya but continued to exchange migrants. Similarly, Eastern and Western gorillas and Sumatran and Bornean orangutans appear to have experienced gene flow since their splits approximately 90 and over 250 Kya, respectively.
Forecasting the mortality rates of Malaysian population using Heligman-Pollard model
NASA Astrophysics Data System (ADS)
Ibrahim, Rose Irnawaty; Mohd, Razak; Ngataman, Nuraini; Abrisam, Wan Nur Azifah Wan Mohd
2017-08-01
Actuaries, demographers and other professionals have always been aware of the critical importance of mortality forecasting due to declining trend of mortality and continuous increases in life expectancy. Heligman-Pollard model was introduced in 1980 and has been widely used by researchers in modelling and forecasting future mortality. This paper aims to estimate an eight-parameter model based on Heligman and Pollard's law of mortality. Since the model involves nonlinear equations that are explicitly difficult to solve, the Matrix Laboratory Version 7.0 (MATLAB 7.0) software will be used in order to estimate the parameters. Statistical Package for the Social Sciences (SPSS) will be applied to forecast all the parameters according to Autoregressive Integrated Moving Average (ARIMA). The empirical data sets of Malaysian population for period of 1981 to 2015 for both genders will be considered, which the period of 1981 to 2010 will be used as "training set" and the period of 2011 to 2015 as "testing set". In order to investigate the accuracy of the estimation, the forecast results will be compared against actual data of mortality rates. The result shows that Heligman-Pollard model fit well for male population at all ages while the model seems to underestimate the mortality rates for female population at the older ages.
Linking resources with demography to understand resource limitation for bears
Reynolds-Hogland, M. J.; Pacifici, L.B.; Mitchell, M.S.
2007-01-01
1. Identifying the resources that limit growth of animal populations is essential for effective conservation; however, resource limitation is difficult to quantify. Recent advances in geographical information systems (GIS) and resource modelling can be combined with demographic modelling to yield insights into resource limitation. 2. Using long-term data on a population of black bears Ursus americanus, we evaluated competing hypotheses about whether availability of hard mast (acorns and nuts) or soft mast (fleshy fruits) limited bears in the southern Appalachians, USA, during 1981-2002. The effects of clearcutting on habitat quality were also evaluated. Annual survival, recruitment and population growth rate were estimated using capture-recapture data from 101 females. The availability of hard mast, soft mast and clearcuts was estimated with a GIS, as each changed through time as a result of harvest and succession, and then availabilities were incorporated as covariates for each demographic parameter. 3. The model with the additive availability of hard mast and soft mast across the landscape predicted survival and population growth rate. Availability of young clearcuts predicted recruitment, but not population growth or survival. 4. Availability of hard mast stands across the landscape and availability of soft mast across the landscape were more important than hard mast production and availability of soft mast in young clearcuts, respectively. 5. Synthesis and applications. Our results indicate that older stands, which support high levels of hard mast and moderate levels of soft mast, should be maintained to sustain population growth of bears in the southern Appalachians. Simultaneously, the acreage of intermediate aged stands (10-25 years), which support very low levels of both hard mast and soft mast, should be minimized. The approach used in this study has broad application for wildlife management and conservation. State and federal wildlife agencies often possess long-term data on both resource availability and capture-recapture for wild populations. Combined, these two data types can be used to estimate survival, recruitment, population growth, elasticities of vital rates and the effects of resource availability on demographic parameters. Hence data that are traditionally used to understand population trends can be used to evaluate how and why demography changes over time. ?? 2007 The Authors.
Adult survival and population growth rate in Colorado big brown bats (Eptesicus fuscus)
O'Shea, T.J.; Ellison, L.E.; Stanley, T.R.
2011-01-01
We studied adult survival and population growth at multiple maternity colonies of big brown bats (Eptesicus fuscus) in Fort Collins, Colorado. We investigated hypotheses about survival using information-theoretic methods and mark-recapture analyses based on passive detection of adult females tagged with passive integrated transponders. We constructed a 3-stage life-history matrix model to estimate population growth rate (??) and assessed the relative importance of adult survival and other life-history parameters to population growth through elasticity and sensitivity analysis. Annual adult survival at 5 maternity colonies monitored from 2001 to 2005 was estimated at 0.79 (95% confidence interval [95% CI] = 0.77-0.82). Adult survival varied by year and roost, with low survival during an extreme drought year, a finding with negative implications for bat populations because of the likelihood of increasing drought in western North America due to global climate change. Adult survival during winter was higher than in summer, and mean life expectancies calculated from survival estimates were lower than maximum longevity records. We modeled adult survival with recruitment parameter estimates from the same population. The study population was growing (?? = 1.096; 95% CI = 1.057-1.135). Adult survival was the most important demographic parameter for population growth. Growth clearly had the highest elasticity to adult survival, followed by juvenile survival and adult fecundity (approximately equivalent in rank). Elasticity was lowest for fecundity of yearlings. The relative importances of the various life-history parameters for population growth rate are similar to those of large mammals. ?? 2011 American Society of Mammalogists.
Sampling design considerations for demographic studies: a case of colonial seabirds
Kendall, William L.; Converse, Sarah J.; Doherty, Paul F.; Naughton, Maura B.; Anders, Angela; Hines, James E.; Flint, Elizabeth
2009-01-01
For the purposes of making many informed conservation decisions, the main goal for data collection is to assess population status and allow prediction of the consequences of candidate management actions. Reducing the bias and variance of estimates of population parameters reduces uncertainty in population status and projections, thereby reducing the overall uncertainty under which a population manager must make a decision. In capture-recapture studies, imperfect detection of individuals, unobservable life-history states, local movement outside study areas, and tag loss can cause bias or precision problems with estimates of population parameters. Furthermore, excessive disturbance to individuals during capture?recapture sampling may be of concern because disturbance may have demographic consequences. We address these problems using as an example a monitoring program for Black-footed Albatross (Phoebastria nigripes) and Laysan Albatross (Phoebastria immutabilis) nesting populations in the northwestern Hawaiian Islands. To mitigate these estimation problems, we describe a synergistic combination of sampling design and modeling approaches. Solutions include multiple capture periods per season and multistate, robust design statistical models, dead recoveries and incidental observations, telemetry and data loggers, buffer areas around study plots to neutralize the effect of local movements outside study plots, and double banding and statistical models that account for band loss. We also present a variation on the robust capture?recapture design and a corresponding statistical model that minimizes disturbance to individuals. For the albatross case study, this less invasive robust design was more time efficient and, when used in combination with a traditional robust design, reduced the standard error of detection probability by 14% with only two hours of additional effort in the field. These field techniques and associated modeling approaches are applicable to studies of most taxa being marked and in some cases have individually been applied to studies of birds, fish, herpetofauna, and mammals.
Accounting for rate variation among lineages in comparative demographic analyses.
Hope, Andrew G; Ho, Simon Y W; Malaney, Jason L; Cook, Joseph A; Talbot, Sandra L
2014-09-01
Genetic analyses of contemporary populations can be used to estimate the demographic histories of species within an ecological community. Comparison of these demographic histories can shed light on community responses to past climatic events. However, species experience different rates of molecular evolution, and this presents a major obstacle to comparative demographic analyses. We address this problem by using a Bayesian relaxed-clock method to estimate the relative evolutionary rates of 22 small mammal taxa distributed across northwestern North America. We found that estimates of the relative molecular substitution rate for each taxon were consistent across the range of sampling schemes that we compared. Using three different reference rates, we rescaled the relative rates so that they could be used to estimate absolute evolutionary timescales. Accounting for rate variation among taxa led to temporal shifts in our skyline-plot estimates of demographic history, highlighting both uniform and idiosyncratic evolutionary responses to directional climate trends for distinct ecological subsets of the small mammal community. Our approach can be used in evolutionary analyses of populations from multiple species, including comparative demographic studies. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.
Pagel, Tobias; Baldessarini, Ross J; Franklin, Jeremy; Baethge, Christopher
2013-05-01
Information on basic demographic and clinical characteristics of schizoaffective disorder is sparse and subject to sampling bias and low diagnostic reliability. In the present study we aimed to: (i) estimate the demographic and clinical descriptors in schizoaffective disorder patients and (ii) compare the findings with those with schizophrenia and bipolar disorder. To minimize sampling bias and low reliability, we systematically reviewed studies that simultaneously compared schizoaffective, schizophrenia, and bipolar disorder patients. We estimated demographic, clinical, and psychometric characteristics based on weighted pooling, and compared disorders by meta-analysis. We also estimated whether schizoaffective disorder is closer to schizophrenia or to bipolar disorder. We identified 50 studies that included 18312 patients. Most characteristics of the 2684 schizoaffective disorder patients fell between those of 4814 diagnosed with bipolar disorder and 10814 with schizophrenia. However, the schizoaffective group had the highest proportion of women (52%), had the youngest age at illness onset (23.3 ± 3.8 years), and had the highest standardized ratings of psychosis and depression. Differences in pooled parameters between schizoaffective versus schizophrenia and versus bipolar disorder subjects were similar. Values for patients with schizoaffective disorders mostly were intermediate between schizophrenia and bipolar disorder. However, the majority of studies showed schizoaffective patients to be more like schizophrenia than bipolar disorder patients in seven out of nine demographic and clinical categories as well as in five out of eight psychometric measures. These results remained similar when we restricted the analyses to studies with psychotic bipolar disorder patients only or to studies using the Diagnostic and Statistical Manual of Mental Disorders (DSM)-IIIR and DSM-IV only. The present study provided estimates of important characteristics of schizoaffective disorder - as balanced as possible in summarizing the findings from observational studies as unbiased as possible. The results did not support the hypothesis that schizoaffective disorder is primarily an affective disorder. The stronger resemblance of schizoaffective disorder to schizophrenia than to bipolar disorder needs further investigation. © 2013 John Wiley and Sons A/S. Published by Blackwell Publishing Ltd.
El Allaki, Farouk; Harrington, Noel; Howden, Krista
2016-11-01
The objectives of this study were (1) to estimate the annual sensitivity of Canada's bTB surveillance system and its three system components (slaughter surveillance, export testing and disease investigation) using a scenario tree modelling approach, and (2) to identify key model parameters that influence the estimates of the surveillance system sensitivity (SSSe). To achieve these objectives, we designed stochastic scenario tree models for three surveillance system components included in the analysis. Demographic data, slaughter data, export testing data, and disease investigation data from 2009 to 2013 were extracted for input into the scenario trees. Sensitivity analysis was conducted to identify key influential parameters on SSSe estimates. The median annual SSSe estimates generated from the study were very high, ranging from 0.95 (95% probability interval [PI]: 0.88-0.98) to 0.97 (95% PI: 0.93-0.99). Median annual sensitivity estimates for the slaughter surveillance component ranged from 0.95 (95% PI: 0.88-0.98) to 0.97 (95% PI: 0.93-0.99). This shows that slaughter surveillance to be the major contributor to overall surveillance system sensitivity with a high probability to detect M. bovis infection if present at a prevalence of 0.00028% or greater during the study period. The export testing and disease investigation components had extremely low component sensitivity estimates-the maximum median sensitivity estimates were 0.02 (95% PI: 0.014-0.023) and 0.0061 (95% PI: 0.0056-0.0066) respectively. The three most influential input parameters on the model's output (SSSe) were the probability of a granuloma being detected at slaughter inspection, the probability of a granuloma being present in older animals (≥12 months of age), and the probability of a granuloma sample being submitted to the laboratory. Additional studies are required to reduce the levels of uncertainty and variability associated with these three parameters influencing the surveillance system sensitivity. Crown Copyright © 2016. Published by Elsevier B.V. All rights reserved.
Portrait of a small population of boreal toads (anaxyrus boreas)
Muths, E.; Scherer, R. D.
2011-01-01
Much attention has been given to the conservation of small populations, those that are small because of decline, and those that are naturally small. Small populations are of particular interest because ecological theory suggests that they are vulnerable to the deleterious effects of environmental, demographic, and genetic stochasticity as well as natural and human-induced catastrophes. However, testing theory and developing applicable conservation measures for small populations is hampered by sparse data. This lack of information is frequently driven by computational issues with small data sets that can be confounded by the impacts of stressors. We present estimates of demographic parameters from a small population of Boreal Toads (Anaxyrus boreas) that has been surveyed since 2001 by using capturerecapture methods. Estimates of annual adult survival probability are high relative to other Boreal Toad populations, whereas estimates of recruitment rate are low. Despite using simple models, clear patterns emerged from the analyses, suggesting that population size is constrained by low recruitment of adults and is declining slowly. These patterns provide insights that are useful in developing management directions for this small population, and this study serves as an example of the potential for small populations to yield robust and useful information despite sample size constraints. ?? 2011 The Herpetologists' League, Inc.
Inferring genealogical processes from patterns of Bronze-Age and modern DNA variation in Sardinia.
Ghirotto, Silvia; Mona, Stefano; Benazzo, Andrea; Paparazzo, Francesco; Caramelli, David; Barbujani, Guido
2010-04-01
The ancient inhabitants of a region are often regarded as ancestral, and hence genetically related, to the modern dwellers (for instance, in studies of admixture), but so far, this assumption has not been tested empirically using ancient DNA data. We studied mitochondrial DNA (mtDNA) variation in Sardinia, across a time span of 2,500 years, comparing 23 Bronze-Age (nuragic) mtDNA sequences with those of 254 modern individuals from two regions, Ogliastra (a likely genetic isolate) and Gallura, and considering the possible impact of gene flow from mainland Italy. To understand the genealogical relationships between past and present populations, we developed seven explicit demographic models; we tested whether these models can account for the levels and patterns of genetic diversity in the data and which one does it best. Extensive simulation based on a serial coalescent algorithm allowed us to compare the posterior probability of each model and estimate the relevant evolutionary (mutation and migration rates) and demographic (effective population sizes, times since population splits) parameters, by approximate Bayesian computations. We then validated the analyses by investigating how well parameters estimated from the simulated data can reproduce the observed data set. We show that a direct genealogical continuity between Bronze-Age Sardinians and the current people of Ogliastra, but not Gallura, has a much higher probability than any alternative scenarios and that genetic diversity in Gallura evolved largely independently, owing in part to gene flow from the mainland.
Monitoring survival rates of landbirds at varying spatial scales: An application of the MAPS Program
Rosenberg, D.K.; DeSante, D.F.; Hines, J.E.; Bonney, Rick; Pashley, David N.; Cooper, Robert; Niles, Larry
2000-01-01
Survivorship is a primary demographic parameter affecting population dynamics, and thus trends in species abundance. The Monitoring Avian Productivity and Survivorship (MAPS) program is a cooperative effort designed to monitor landbird demographic parameters. A principle goal of MAPS is to estimate annual survivorship and identify spatial patterns and temporal trends in these rates. We evaluated hypotheses of spatial patterns in survival rates among a collection of neighboring sampling sites, such as within national forests, among biogeographic provinces, and between breeding populations that winter in either Central or South America, and compared these geographic-specific models to a model of a common survival rate among all sampling sites. We used data collected during 1992-1995 from Swainson's Thrush (Cathorus ustulatus) populations in the western region of the United States. We evaluated the ability to detect spatial and temporal patterns of survivorship with simulated data. We found weak evidence of spatial differences in survival rates at the local scale of 'location,' which typically contained 3 mist-netting stations. There was little evidence of differences in survival rates among biogeographic provinces or between populations that winter in either Central or South America. When data were pooled for a regional estimate of survivorship, the percent relative bias due to pooling 'locations' was 12 years of monitoring. Detection of spatial patterns and temporal trends in survival rates from local to regional scales will provide important information for management and future research directed toward conservation of landbirds.
Halstead, Brian J.; Wylie, Glenn D.; Casazza, Michael L.
2013-01-01
Increasing detection and capture probabilities of rare or elusive herpetofauna of conservation concern is important to inform the scientific basis for their management and recovery. The Giant Gartersnake (Thamnophis gigas) is an example of a secretive, wary, and generally difficult-to-sample species about which little is known regarding its patterns of occurrence and demography. We therefore evaluated modifications to existing traps to increase the detection and capture probabilities of the Giant Gartersnake to improve the precision with which occurrence, abundance, survival, and other demographic parameters are estimated. We found that adding a one-way valve constructed of cable ties to the small funnel opening of traps and adding hardware cloth extensions to the wide end of funnels increased capture rates of the Giant Gartersnake by 5.55 times (95% credible interval = 2.45–10.51) relative to unmodified traps. The effectiveness of these modifications was insensitive to the aquatic habitat type in which they were deployed. The snout-vent length of the smallest and largest captured snakes did not vary among trap modifications. These trap modifications are expected to increase detection and capture probabilities of the Giant Gartersnake, and show promise for increasing the precision with which demographic parameters can be estimated for this species. We anticipate that the trap modifications found effective in this study will be applicable to a variety of aquatic and semi-aquatic reptiles and amphibians and improve conservation efforts for these species.
Cross-validation to select Bayesian hierarchical models in phylogenetics.
Duchêne, Sebastián; Duchêne, David A; Di Giallonardo, Francesca; Eden, John-Sebastian; Geoghegan, Jemma L; Holt, Kathryn E; Ho, Simon Y W; Holmes, Edward C
2016-05-26
Recent developments in Bayesian phylogenetic models have increased the range of inferences that can be drawn from molecular sequence data. Accordingly, model selection has become an important component of phylogenetic analysis. Methods of model selection generally consider the likelihood of the data under the model in question. In the context of Bayesian phylogenetics, the most common approach involves estimating the marginal likelihood, which is typically done by integrating the likelihood across model parameters, weighted by the prior. Although this method is accurate, it is sensitive to the presence of improper priors. We explored an alternative approach based on cross-validation that is widely used in evolutionary analysis. This involves comparing models according to their predictive performance. We analysed simulated data and a range of viral and bacterial data sets using a cross-validation approach to compare a variety of molecular clock and demographic models. Our results show that cross-validation can be effective in distinguishing between strict- and relaxed-clock models and in identifying demographic models that allow growth in population size over time. In most of our empirical data analyses, the model selected using cross-validation was able to match that selected using marginal-likelihood estimation. The accuracy of cross-validation appears to improve with longer sequence data, particularly when distinguishing between relaxed-clock models. Cross-validation is a useful method for Bayesian phylogenetic model selection. This method can be readily implemented even when considering complex models where selecting an appropriate prior for all parameters may be difficult.
Bouillon-Pichault, Marion; Jullien, Vincent; Bazzoli, Caroline; Pons, Gérard; Tod, Michel
2011-02-01
The aim of this work was to determine whether optimizing the study design in terms of ages and sampling times for a drug eliminated solely via cytochrome P450 3A4 (CYP3A4) would allow us to accurately estimate the pharmacokinetic parameters throughout the entire childhood timespan, while taking into account age- and weight-related changes. A linear monocompartmental model with first-order absorption was used successively with three different residual error models and previously published pharmacokinetic parameters ("true values"). The optimal ages were established by D-optimization using the CYP3A4 maturation function to create "optimized demographic databases." The post-dose times for each previously selected age were determined by D-optimization using the pharmacokinetic model to create "optimized sparse sampling databases." We simulated concentrations by applying the population pharmacokinetic model to the optimized sparse sampling databases to create optimized concentration databases. The latter were modeled to estimate population pharmacokinetic parameters. We then compared true and estimated parameter values. The established optimal design comprised four age ranges: 0.008 years old (i.e., around 3 days), 0.192 years old (i.e., around 2 months), 1.325 years old, and adults, with the same number of subjects per group and three or four samples per subject, in accordance with the error model. The population pharmacokinetic parameters that we estimated with this design were precise and unbiased (root mean square error [RMSE] and mean prediction error [MPE] less than 11% for clearance and distribution volume and less than 18% for k(a)), whereas the maturation parameters were unbiased but less precise (MPE < 6% and RMSE < 37%). Based on our results, taking growth and maturation into account a priori in a pediatric pharmacokinetic study is theoretically feasible. However, it requires that very early ages be included in studies, which may present an obstacle to the use of this approach. First-pass effects, alternative elimination routes, and combined elimination pathways should also be investigated.
Joint Inference of Population Assignment and Demographic History
Choi, Sang Chul; Hey, Jody
2011-01-01
A new approach to assigning individuals to populations using genetic data is described. Most existing methods work by maximizing Hardy–Weinberg and linkage equilibrium within populations, neither of which will apply for many demographic histories. By including a demographic model, within a likelihood framework based on coalescent theory, we can jointly study demographic history and population assignment. Genealogies and population assignments are sampled from a posterior distribution using a general isolation-with-migration model for multiple populations. A measure of partition distance between assignments facilitates not only the summary of a posterior sample of assignments, but also the estimation of the posterior density for the demographic history. It is shown that joint estimates of assignment and demographic history are possible, including estimation of population phylogeny for samples from three populations. The new method is compared to results of a widely used assignment method, using simulated and published empirical data sets. PMID:21775468
Schoenberg, Mike R; Lange, Rael T; Saklofske, Donald H; Suarez, Mariann; Brickell, Tracey A
2008-12-01
Determination of neuropsychological impairment involves contrasting obtained performances with a comparison standard, which is often an estimate of premorbid IQ. M. R. Schoenberg, R. T. Lange, T. A. Brickell, and D. H. Saklofske (2007) proposed the Child Premorbid Intelligence Estimate (CPIE) to predict premorbid Full Scale IQ (FSIQ) using the Wechsler Intelligence Scale for Children-4th Edition (WISC-IV; Wechsler, 2003). The CPIE includes 12 algorithms to predict FSIQ, 1 using demographic variables and 11 algorithms combining WISC-IV subtest raw scores with demographic variables. The CPIE was applied to a sample of children with acquired traumatic brain injury (TBI sample; n = 40) and a healthy demographically matched sample (n = 40). Paired-samples t tests found estimated premorbid FSIQ differed from obtained FSIQ when applied to the TBI sample (ps
Zimmerman, Guthrie S.; Sauer, John; Boomer, G. Scott; Devers, Patrick K.; Garrettson, Pamela R.
2017-01-01
The U.S. Fish and Wildlife Service (USFWS) uses data from the North American Breeding Bird Survey (BBS) to assist in monitoring and management of some migratory birds. However, BBS analyses provide indices of population change rather than estimates of population size, precluding their use in developing abundance-based objectives and limiting applicability to harvest management. Wood Ducks (Aix sponsa) are important harvested birds in the Atlantic Flyway (AF) that are difficult to detect during aerial surveys because they prefer forested habitat. We integrated Wood Duck count data from a ground-plot survey in the northeastern U.S. with AF-wide BBS, banding, parts collection, and harvest data to derive estimates of population size for the AF. Overlapping results between the smaller-scale intensive ground-plot survey and the BBS in the northeastern U.S. provided a means for scaling BBS indices to the breeding population size estimates. We applied these scaling factors to BBS results for portions of the AF lacking intensive surveys. Banding data provided estimates of annual survival and harvest rates; the latter, when combined with parts-collection data, provided estimates of recruitment. We used the harvest data to estimate fall population size. Our estimates of breeding population size and variability from the integrated population model (N̄ = 0.99 million, SD = 0.04) were similar to estimates of breeding population size based solely on data from the AF ground-plot surveys and the BBS (N̄ = 1.01 million, SD = 0.04) from 1998 to 2015. Integrating BBS data with other data provided reliable population size estimates for Wood Ducks at a scale useful for harvest and habitat management in the AF, and allowed us to derive estimates of important demographic parameters (e.g., seasonal survival rates, sex ratio) that were not directly informed by data.
Effects of tag loss on direct estimates of population growth rate
Rotella, J.J.; Hines, J.E.
2005-01-01
The temporal symmetry approach of R. Pradel can be used with capture-recapture data to produce retrospective estimates of a population's growth rate, lambda(i), and the relative contributions to lambda(i) from different components of the population. Direct estimation of lambda(i) provides an alternative to using population projection matrices to estimate asymptotic lambda and is seeing increased use. However, the robustness of direct estimates of lambda(1) to violations of several key assumptions has not yet been investigated. Here, we consider tag loss as a possible source of bias for scenarios in which the rate of tag loss is (1) the same for all marked animals in the population and (2) a function of tag age. We computed analytic approximations of the expected values for each of the parameter estimators involved in direct estimation and used those values to calculate bias and precision for each parameter estimator. Estimates of lambda(i) were robust to homogeneous rates of tag loss. When tag loss rates varied by tag age, bias occurred for some of the sampling situations evaluated, especially those with low capture probability, a high rate of tag loss, or both. For situations with low rates of tag loss and high capture probability, bias was low and often negligible. Estimates of contributions of demographic components to lambda(i) were not robust to tag loss. Tag loss reduced the precision of all estimates because tag loss results in fewer marked animals remaining available for estimation. Clearly tag loss should be prevented if possible, and should be considered in analyses of lambda(i), but tag loss does not necessarily preclude unbiased estimation of lambda(i).
Thogmartin, Wayne E.; Sanders-Reed, Carol A.; Szymanski, Jennifer; Pruitt, Lori; Runge, Michael C.
2017-01-01
Demographic characteristics of bats are often insufficiently described for modeling populations. In data poor situations, experts are often relied upon for characterizing ecological systems. In concert with the development of a matrix model describing Indiana bat (Myotis sodalis) demography, we elicited estimates for parameterizing this model from 12 experts. We conducted this elicitation in two stages, requesting expert values for 12 demographic rates. These rates were adult and juvenile seasonal (winter, summer, fall) survival rates, pup survival in fall, and propensity and success at breeding. Experts were most in agreement about adult fall survival (3% Coefficient of Variation) and least in agreement about propensity of juveniles to breed (37% CV). The experts showed greater concordance for adult ( mean CV, adult = 6.2%) than for juvenile parameters ( mean CV, juvenile = 16.4%), and slightly more agreement for survival (mean CV, survival = 9.8%) compared to reproductive rates ( mean CV, reproduction = 15.1%). However, survival and reproduction were negatively and positively biased, respectively, relative to a stationary dynamic. Despite the species exhibiting near stationary dynamics for two decades prior to the onset of a potential extinction-causing agent, white-nose syndrome, expert estimates indicated a population decline of -11% per year (95% CI = -2%, -20%); quasi-extinction was predicted within a century ( mean = 61 years to QE, range = 32, 97) by 10 of the 12 experts. Were we to use these expert estimates in our modeling efforts, we would have errantly trained our models to a rapidly declining demography asymptomatic of recent demographic behavior. While experts are sometimes the only source of information, a clear understanding of the temporal and spatial context of the information being elicited is necessary to guard against wayward predictions.
Navascués, Miguel; Vaxevanidou, Zafeiro; González-Martínez, Santiago C; Climent, José; Gil, Luis; Emerson, Brent C
2006-01-01
Chloroplast microsatellites are becoming increasingly popular markers for population genetic studies in plants, but there has been little focus on their potential for demographic inference. In this work the utility of chloroplast microsatellites for the study of population expansions was explored. First, we investigated the power of mismatch distribution analysis and the FS test with coalescent simulations of different demographic scenarios. We then applied those methods to empirical data obtained for the Canary Island pine (Pinus canariensis). The results of the simulations showed that chloroplast microsatellites are sensitive to sudden population growth. The power of the FS test and accuracy of demographic parameter estimates, such as the time of expansion, were reduced proportionally to the level of homoplasy within the data. The analysis of Canary Island pine chloroplast microsatellite data indicated population expansions for almost all sample localities. Demographic expansions at the island level can be explained by the colonisation of the archipelago by the pine, while population expansions of different ages in different localities within an island appear to be the result of local extinctions and recolonisation dynamics. Comparable mitochondrial DNA sequence data from a parasite of P. canariensis, the weevil Brachyderes rugatus, supports this scenario, suggesting a key role for volcanism in the evolution of pine forest communities in the Canary Islands. PMID:16911194
Variation in detection among passive infrared triggered-cameras used in wildlife research
Damm, Philip E.; Grand, James B.; Barnett, Steven W.
2010-01-01
Precise and accurate estimates of demographics such as age structure, productivity, and density are necessary in determining habitat and harvest management strategies for wildlife populations. Surveys using automated cameras are becoming an increasingly popular tool for estimating these parameters. However, most camera studies fail to incorporate detection probabilities, leading to parameter underestimation. The objective of this study was to determine the sources of heterogeneity in detection for trail cameras that incorporate a passive infrared (PIR) triggering system sensitive to heat and motion. Images were collected at four baited sites within the Conecuh National Forest, Alabama, using three cameras at each site operating continuously over the same seven-day period. Detection was estimated for four groups of animals based on taxonomic group and body size. Our hypotheses of detection considered variation among bait sites and cameras. The best model (w=0.99) estimated different rates of detection for each camera in addition to different detection rates for four animal groupings. Factors that explain this variability might include poor manufacturing tolerances, variation in PIR sensitivity, animal behavior, and species-specific infrared radiation. Population surveys using trail cameras with PIR systems must incorporate detection rates for individual cameras. Incorporating time-lapse triggering systems into survey designs should eliminate issues associated with PIR systems.
Bayesian data assimilation provides rapid decision support for vector-borne diseases
Jewell, Chris P.; Brown, Richard G.
2015-01-01
Predicting the spread of vector-borne diseases in response to incursions requires knowledge of both host and vector demographics in advance of an outbreak. Although host population data are typically available, for novel disease introductions there is a high chance of the pathogen using a vector for which data are unavailable. This presents a barrier to estimating the parameters of dynamical models representing host–vector–pathogen interaction, and hence limits their ability to provide quantitative risk forecasts. The Theileria orientalis (Ikeda) outbreak in New Zealand cattle demonstrates this problem: even though the vector has received extensive laboratory study, a high degree of uncertainty persists over its national demographic distribution. Addressing this, we develop a Bayesian data assimilation approach whereby indirect observations of vector activity inform a seasonal spatio-temporal risk surface within a stochastic epidemic model. We provide quantitative predictions for the future spread of the epidemic, quantifying uncertainty in the model parameters, case infection times and the disease status of undetected infections. Importantly, we demonstrate how our model learns sequentially as the epidemic unfolds and provide evidence for changing epidemic dynamics through time. Our approach therefore provides a significant advance in rapid decision support for novel vector-borne disease outbreaks. PMID:26136225
Laser photogrammetry improves size and demographic estimates for whale sharks
Richardson, Anthony J.; Prebble, Clare E.M.; Marshall, Andrea D.; Bennett, Michael B.; Weeks, Scarla J.; Cliff, Geremy; Wintner, Sabine P.; Pierce, Simon J.
2015-01-01
Whale sharks Rhincodon typus are globally threatened, but a lack of biological and demographic information hampers an accurate assessment of their vulnerability to further decline or capacity to recover. We used laser photogrammetry at two aggregation sites to obtain more accurate size estimates of free-swimming whale sharks compared to visual estimates, allowing improved estimates of biological parameters. Individual whale sharks ranged from 432–917 cm total length (TL) (mean ± SD = 673 ± 118.8 cm, N = 122) in southern Mozambique and from 420–990 cm TL (mean ± SD = 641 ± 133 cm, N = 46) in Tanzania. By combining measurements of stranded individuals with photogrammetry measurements of free-swimming sharks, we calculated length at 50% maturity for males in Mozambique at 916 cm TL. Repeat measurements of individual whale sharks measured over periods from 347–1,068 days yielded implausible growth rates, suggesting that the growth increment over this period was not large enough to be detected using laser photogrammetry, and that the method is best applied to estimating growth rates over longer (decadal) time periods. The sex ratio of both populations was biased towards males (74% in Mozambique, 89% in Tanzania), the majority of which were immature (98% in Mozambique, 94% in Tanzania). The population structure for these two aggregations was similar to most other documented whale shark aggregations around the world. Information on small (<400 cm) whale sharks, mature individuals, and females in this region is lacking, but necessary to inform conservation initiatives for this globally threatened species. PMID:25870776
Efficacy of using data from angler-caught Burbot to estimate population rate functions
Brauer, Tucker A.; Rhea, Darren T.; Walrath, John D.; Quist, Michael C.
2018-01-01
The effective management of a fish population depends on the collection of accurate demographic data from that population. Since demographic data are often expensive and difficult to obtain, developing cost‐effective and efficient collection methods is a high priority. This research evaluates the efficacy of using angler‐supplied data to monitor a nonnative population of Burbot Lota lota. Age and growth estimates were compared between Burbot collected by anglers and those collected in trammel nets from two Wyoming reservoirs. Collection methods produced different length‐frequency distributions, but no difference was observed in age‐frequency distributions. Mean back‐calculated lengths at age revealed that netted Burbot grew faster than angled Burbot in Fontenelle Reservoir. In contrast, angled Burbot grew slightly faster than netted Burbot in Flaming Gorge Reservoir. Von Bertalanffy growth models differed between collection methods, but differences in parameter estimates were minor. Estimates of total annual mortality (A) of Burbot in Fontenelle Reservoir were comparable between angled (A = 35.4%) and netted fish (33.9%); similar results were observed in Flaming Gorge Reservoir for angled (29.3%) and netted fish (30.5%). Beverton–Holt yield‐per‐recruit models were fit using data from both collection methods. Estimated yield differed by less than 15% between data sources and reservoir. Spawning potential ratios indicated that an exploitation rate of 20% would be required to induce recruitment overfishing in either reservoir, regardless of data source. Results of this study suggest that angler‐supplied data are useful for monitoring Burbot population dynamics in Wyoming and may be an option to efficiently monitor other fish populations in North America.
Refining mortality estimates in shark demographic analyses: a Bayesian inverse matrix approach.
Smart, Jonathan J; Punt, André E; White, William T; Simpfendorfer, Colin A
2018-01-18
Leslie matrix models are an important analysis tool in conservation biology that are applied to a diversity of taxa. The standard approach estimates the finite rate of population growth (λ) from a set of vital rates. In some instances, an estimate of λ is available, but the vital rates are poorly understood and can be solved for using an inverse matrix approach. However, these approaches are rarely attempted due to prerequisites of information on the structure of age or stage classes. This study addressed this issue by using a combination of Monte Carlo simulations and the sample-importance-resampling (SIR) algorithm to solve the inverse matrix problem without data on population structure. This approach was applied to the grey reef shark (Carcharhinus amblyrhynchos) from the Great Barrier Reef (GBR) in Australia to determine the demography of this population. Additionally, these outputs were applied to another heavily fished population from Papua New Guinea (PNG) that requires estimates of λ for fisheries management. The SIR analysis determined that natural mortality (M) and total mortality (Z) based on indirect methods have previously been overestimated for C. amblyrhynchos, leading to an underestimated λ. The updated Z distributions determined using SIR provided λ estimates that matched an empirical λ for the GBR population and corrected obvious error in the demographic parameters for the PNG population. This approach provides opportunity for the inverse matrix approach to be applied more broadly to situations where information on population structure is lacking. © 2018 by the Ecological Society of America.
Schoenberg, Mike R; Lange, Rael T; Saklofske, Donald H
2007-11-01
Establishing a comparison standard in neuropsychological assessment is crucial to determining change in function. There is no available method to estimate premorbid intellectual functioning for the Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV). The WISC-IV provided normative data for both American and Canadian children aged 6 to 16 years old. This study developed regression algorithms as a proposed method to estimate full-scale intelligence quotient (FSIQ) for the Canadian WISC-IV. Participants were the Canadian WISC-IV standardization sample (n = 1,100). The sample was randomly divided into two groups (development and validation groups). The development group was used to generate regression algorithms; 1 algorithm only included demographics, and 11 combined demographic variables with WISC-IV subtest raw scores. The algorithms accounted for 18% to 70% of the variance in FSIQ (standard error of estimate, SEE = 8.6 to 14.2). Estimated FSIQ significantly correlated with actual FSIQ (r = .30 to .80), and the majority of individual FSIQ estimates were within +/-10 points of actual FSIQ. The demographic-only algorithm was less accurate than algorithms combining demographic variables with subtest raw scores. The current algorithms yielded accurate estimates of current FSIQ for Canadian individuals aged 6-16 years old. The potential application of the algorithms to estimate premorbid FSIQ is reviewed. While promising, clinical validation of the algorithms in a sample of children and/or adolescents with known neurological dysfunction is needed to establish these algorithms as a premorbid estimation procedure.
Modeling individual effects in the Cormack-Jolly-Seber Model: A state-space formulation
Royle, J. Andrew
2008-01-01
In population and evolutionary biology, there exists considerable interest in individual heterogeneity in parameters of demographic models for open populations. However, flexible and practical solutions to the development of such models have proven to be elusive. In this article, I provide a state-space formulation of open population capture-recapture models with individual effects. The state-space formulation provides a generic and flexible framework for modeling and inference in models with individual effects, and it yields a practical means of estimation in these complex problems via contemporary methods of Markov chain Monte Carlo. A straightforward implementation can be achieved in the software package WinBUGS. I provide an analysis of a simple model with constant parameter detection and survival probability parameters. A second example is based on data from a 7-year study of European dippers, in which a model with year and individual effects is fitted.
Gutenkunst, Ryan N.; Hernandez, Ryan D.; Williamson, Scott H.; Bustamante, Carlos D.
2009-01-01
Demographic models built from genetic data play important roles in illuminating prehistorical events and serving as null models in genome scans for selection. We introduce an inference method based on the joint frequency spectrum of genetic variants within and between populations. For candidate models we numerically compute the expected spectrum using a diffusion approximation to the one-locus, two-allele Wright-Fisher process, involving up to three simultaneous populations. Our approach is a composite likelihood scheme, since linkage between neutral loci alters the variance but not the expectation of the frequency spectrum. We thus use bootstraps incorporating linkage to estimate uncertainties for parameters and significance values for hypothesis tests. Our method can also incorporate selection on single sites, predicting the joint distribution of selected alleles among populations experiencing a bevy of evolutionary forces, including expansions, contractions, migrations, and admixture. We model human expansion out of Africa and the settlement of the New World, using 5 Mb of noncoding DNA resequenced in 68 individuals from 4 populations (YRI, CHB, CEU, and MXL) by the Environmental Genome Project. We infer divergence between West African and Eurasian populations 140 thousand years ago (95% confidence interval: 40–270 kya). This is earlier than other genetic studies, in part because we incorporate migration. We estimate the European (CEU) and East Asian (CHB) divergence time to be 23 kya (95% c.i.: 17–43 kya), long after archeological evidence places modern humans in Europe. Finally, we estimate divergence between East Asians (CHB) and Mexican-Americans (MXL) of 22 kya (95% c.i.: 16.3–26.9 kya), and our analysis yields no evidence for subsequent migration. Furthermore, combining our demographic model with a previously estimated distribution of selective effects among newly arising amino acid mutations accurately predicts the frequency spectrum of nonsynonymous variants across three continental populations (YRI, CHB, CEU). PMID:19851460
Reducing bias in survival under non-random temporary emigration
Peñaloza, Claudia L.; Kendall, William L.; Langtimm, Catherine Ann
2014-01-01
Despite intensive monitoring, temporary emigration from the sampling area can induce bias severe enough for managers to discard life-history parameter estimates toward the terminus of the times series (terminal bias). Under random temporary emigration unbiased parameters can be estimated with CJS models. However, unmodeled Markovian temporary emigration causes bias in parameter estimates and an unobservable state is required to model this type of emigration. The robust design is most flexible when modeling temporary emigration, and partial solutions to mitigate bias have been identified, nonetheless there are conditions were terminal bias prevails. Long-lived species with high adult survival and highly variable non-random temporary emigration present terminal bias in survival estimates, despite being modeled with the robust design and suggested constraints. Because this bias is due to uncertainty about the fate of individuals that are undetected toward the end of the time series, solutions should involve using additional information on survival status or location of these individuals at that time. Using simulation, we evaluated the performance of models that jointly analyze robust design data and an additional source of ancillary data (predictive covariate on temporary emigration, telemetry, dead recovery, or auxiliary resightings) in reducing terminal bias in survival estimates. The auxiliary resighting and predictive covariate models reduced terminal bias the most. Additional telemetry data was effective at reducing terminal bias only when individuals were tracked for a minimum of two years. High adult survival of long-lived species made the joint model with recovery data ineffective at reducing terminal bias because of small-sample bias. The naïve constraint model (last and penultimate temporary emigration parameters made equal), was the least efficient, though still able to reduce terminal bias when compared to an unconstrained model. Joint analysis of several sources of data improved parameter estimates and reduced terminal bias. Efforts to incorporate or acquire such data should be considered by researchers and wildlife managers, especially in the years leading up to status assessments of species of interest. Simulation modeling is a very cost effective method to explore the potential impacts of using different sources of data to produce high quality demographic data to inform management.
Kamath, Pauline L.; Haroldson, Mark A.; Luikart, Gordon; Paetkau, David; Whitman, Craig L.; van Manen, Frank T.
2015-01-01
Effective population size (Ne) is a key parameter for monitoring the genetic health of threatened populations because it reflects a population's evolutionary potential and risk of extinction due to genetic stochasticity. However, its application to wildlife monitoring has been limited because it is difficult to measure in natural populations. The isolated and well-studied population of grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem provides a rare opportunity to examine the usefulness of different Ne estimators for monitoring. We genotyped 729 Yellowstone grizzly bears using 20 microsatellites and applied three single-sample estimators to examine contemporary trends in generation interval (GI), effective number of breeders (Nb) and Ne during 1982–2007. We also used multisample methods to estimate variance (NeV) and inbreeding Ne (NeI). Single-sample estimates revealed positive trajectories, with over a fourfold increase in Ne (≈100 to 450) and near doubling of the GI (≈8 to 14) from the 1980s to 2000s. NeV (240–319) and NeI (256) were comparable with the harmonic mean single-sample Ne (213) over the time period. Reanalysing historical data, we found NeV increased from ≈80 in the 1910s–1960s to ≈280 in the contemporary population. The estimated ratio of effective to total census size (Ne/Nc) was stable and high (0.42–0.66) compared to previous brown bear studies. These results support independent demographic evidence for Yellowstone grizzly bear population growth since the 1980s. They further demonstrate how genetic monitoring of Ne can complement demographic-based monitoring of Nc and vital rates, providing a valuable tool for wildlife managers.
Gasca-Pineda, Jaime; Cassaigne, Ivonne; Alonso, Rogelio A.; Eguiarte, Luis E.
2013-01-01
The amount of genetic diversity in a finite biological population mostly depends on the interactions among evolutionary forces and the effective population size (N e) as well as the time since population establishment. Because the N e estimation helps to explore population demographic history, and allows one to predict the behavior of genetic diversity through time, N e is a key parameter for the genetic management of small and isolated populations. Here, we explored an N e-based approach using a bighorn sheep population on Tiburon Island, Mexico (TI) as a model. We estimated the current (N crnt) and ancestral stable (N stbl) inbreeding effective population sizes as well as summary statistics to assess genetic diversity and the demographic scenarios that could explain such diversity. Then, we evaluated the feasibility of using TI as a source population for reintroduction programs. We also included data from other bighorn sheep and artiodactyl populations in the analysis to compare their inbreeding effective size estimates. The TI population showed high levels of genetic diversity with respect to other managed populations. However, our analysis suggested that TI has been under a genetic bottleneck, indicating that using individuals from this population as the only source for reintroduction could lead to a severe genetic diversity reduction. Analyses of the published data did not show a strict correlation between H E and N crnt estimates. Moreover, we detected that ancient anthropogenic and climatic pressures affected all studied populations. We conclude that the estimation of N crnt and N stbl are informative genetic diversity estimators and should be used in addition to summary statistics for conservation and population management planning. PMID:24147115
Lye, G C; Lepais, O; Goulson, D
2011-07-01
Four British bumblebee species (Bombus terrestris, Bombus hortorum, Bombus ruderatus and Bombus subterraneus) became established in New Zealand following their introduction at the turn of the last century. Of these, two remain common in the United Kingdom (B. terrestris and B. hortorum), whilst two (B. ruderatus and B. subterraneus) have undergone marked declines, the latter being declared extinct in 2000. The presence of these bumblebees in New Zealand provides an unique system in which four related species have been isolated from their source population for over 100 years, providing a rare opportunity to examine the impacts of an initial bottleneck and introduction to a novel environment on their population genetics. We used microsatellite markers to compare modern populations of B. terrestris, B. hortorum and B. ruderatus in the United Kingdom and New Zealand and to compare museum specimens of British B. subterraneus with the current New Zealand population. We used approximate Bayesian computation to estimate demographic parameters of the introduction history, notably to estimate the number of founders involved in the initial introduction. Species-specific patterns derived from genetic analysis were consistent with the predictions based on the presumed history of these populations; demographic events have left a marked genetic signature on all four species. Approximate Bayesian analyses suggest that the New Zealand population of B. subterraneus may have been founded by as few as two individuals, giving rise to low genetic diversity and marked genetic divergence from the (now extinct) UK population. © 2011 Blackwell Publishing Ltd.
A longitudinal analysis of nursing home outcomes.
Porell, F; Caro, F G; Silva, A; Monane, M
1998-10-01
To investigate resident and facility attributes associated with long-term care health outcomes in nursing homes. Quarterly Management Minutes Questionnaire (MMQ) survey data for Medicaid case-mix reimbursement of nursing homes in Massachusetts from 1991 to 1994, for specification of outcomes and resident attributes. Facility attributes are specified from cost report data. Multivariate logistic and "state-dependence" regression models are estimated for survival, ADL functional status, incontinence status, and mental status outcomes from longitudinal residence histories of Medicaid residents spanning 3 to 36 months in length. Outcomes are specified to be a function of resident demographic and diagnostic attributes and facility-level operating and nurse staffing attributes. The estimated parameters for resident demographic and diagnostic attributes showed a great deal of construct validity with respect to clinical expectations regarding risk factors for adverse outcomes. Few facility attributes were associated with outcomes generally, and none was significantly associated with all four outcomes. The absence of uniform associations between facility attributes and the various long-term care health outcomes studied suggests that strong facility performance on one health outcome may coexist with much weaker performance on other outcomes. This has implications for the aggregation of individual facility performance measures on multiple outcomes and the development of overall outcome performance measures.
Carlson, Paul R; Yarbro, Laura A; Madley, Kevin; Arnold, Herman; Merello, Manuel; Vanderbloemen, Lisa; McRae, Gil; Durako, Michael J
2003-01-01
We examined the response of demographic, morphological, and chemical parameters of turtle grass (Thalassia testudinum), to much-higher-than-normal rainfall associated with an El Niño event in the winter of 1997-1998. Up to 20 inches of added rain fell between December 1997 and March 1998. triggering widespread and persistent phytoplankton blooms along the west coast of Florida. Water-column chlorophyll concentrations estimated from serial Sea WiFS imagery were much higher during the El Niño event than in the previous or following years, although the timing and magnitude of phytoplankton blooms varied among sites. Seagrass samples collected in 1997, 1998, and 1999 provided an excellent opportunity to test the responsiveness of Thalassia to decline and subsequent improvement of water quality and clarity in four estuaries. Using a scoring technique based on temporal responsiveness, spatial consistency, and statistical strength of indicators, we found that several morphological parameters (Thalassia shoot density, blade width, blade number, and shoot-specific leaf area) were responsive and consistent measures of light stress. Some morphological parameters, such as rhizome apex density, responded to declines and subsequent improvement in water clarity, but lacked the statistical discriminating power necessary to be useful indicators. However, rhizome sugar, starch, and total carbohydrate concentrations also exhibited spatially and temporally consistent variation as well as statistical strength. Because changes in shoot density, as well as water clarity, affect rhizome carbohydrate levels, a composite metric based on Thalassia shoot density and rhizome carbohydrate levels together is probably more useful than either parameter alone as an indicator of seagrass health.
Between-User Reliability of Tier 1 Exposure Assessment Tools Used Under REACH.
Lamb, Judith; Galea, Karen S; Miller, Brian G; Hesse, Susanne; Van Tongeren, Martie
2017-10-01
When applying simple screening (Tier 1) tools to estimate exposure to chemicals in a given exposure situation under the Registration, Evaluation, Authorisation and restriction of CHemicals Regulation 2006 (REACH), users must select from several possible input parameters. Previous studies have suggested that results from exposure assessments using expert judgement and from the use of modelling tools can vary considerably between assessors. This study aimed to investigate the between-user reliability of Tier 1 tools. A remote-completion exercise and in person workshop were used to identify and evaluate tool parameters and factors such as user demographics that may be potentially associated with between-user variability. Participants (N = 146) generated dermal and inhalation exposure estimates (N = 4066) from specified workplace descriptions ('exposure situations') and Tier 1 tool combinations (N = 20). Interactions between users, tools, and situations were investigated and described. Systematic variation associated with individual users was minor compared with random between-user variation. Although variation was observed between choices made for the majority of input parameters, differing choices of Process Category ('PROC') code/activity descriptor and dustiness level impacted most on the resultant exposure estimates. Exposure estimates ranging over several orders of magnitude were generated for the same exposure situation by different tool users. Such unpredictable between-user variation will reduce consistency within REACH processes and could result in under-estimation or overestimation of exposure, risking worker ill-health or the implementation of unnecessary risk controls, respectively. Implementation of additional support and quality control systems for all tool users is needed to reduce between-assessor variation and so ensure both the protection of worker health and avoidance of unnecessary business risk management expenditure. © The Author 2017. Published by Oxford University Press on behalf of the British Occupational Hygiene Society.
Estimating Finite Rate of Population Increase for Sharks Based on Vital Parameters
Liu, Kwang-Ming; Chin, Chien-Pang; Chen, Chun-Hui; Chang, Jui-Han
2015-01-01
The vital parameter data for 62 stocks, covering 38 species, collected from the literature, including parameters of age, growth, and reproduction, were log-transformed and analyzed using multivariate analyses. Three groups were identified and empirical equations were developed for each to describe the relationships between the predicted finite rates of population increase (λ’) and the vital parameters, maximum age (Tmax), age at maturity (Tm), annual fecundity (f/Rc)), size at birth (Lb), size at maturity (Lm), and asymptotic length (L∞). Group (1) included species with slow growth rates (0.034 yr-1 < k < 0.103 yr-1) and extended longevity (26 yr < Tmax < 81 yr), e.g., shortfin mako Isurus oxyrinchus, dusky shark Carcharhinus obscurus, etc.; Group (2) included species with fast growth rates (0.103 yr-1 < k < 0.358 yr-1) and short longevity (9 yr < Tmax < 26 yr), e.g., starspotted smoothhound Mustelus manazo, gray smoothhound M. californicus, etc.; Group (3) included late maturing species (Lm/L∞ ≧ 0.75) with moderate longevity (Tmax < 29 yr), e.g., pelagic thresher Alopias pelagicus, sevengill shark Notorynchus cepedianus. The empirical equation for all data pooled was also developed. The λ’ values estimated by these empirical equations showed good agreement with those calculated using conventional demographic analysis. The predictability was further validated by an independent data set of three species. The empirical equations developed in this study not only reduce the uncertainties in estimation but also account for the difference in life history among groups. This method therefore provides an efficient and effective approach to the implementation of precautionary shark management measures. PMID:26576058
Size-density scaling in protists and the links between consumer-resource interaction parameters.
DeLong, John P; Vasseur, David A
2012-11-01
Recent work indicates that the interaction between body-size-dependent demographic processes can generate macroecological patterns such as the scaling of population density with body size. In this study, we evaluate this possibility for grazing protists and also test whether demographic parameters in these models are correlated after controlling for body size. We compiled data on the body-size dependence of consumer-resource interactions and population density for heterotrophic protists grazing algae in laboratory studies. We then used nested dynamic models to predict both the height and slope of the scaling relationship between population density and body size for these protists. We also controlled for consumer size and assessed links between model parameters. Finally, we used the models and the parameter estimates to assess the individual- and population-level dependence of resource use on body-size and prey-size selection. The predicted size-density scaling for all models matched closely to the observed scaling, and the simplest model was sufficient to predict the pattern. Variation around the mean size-density scaling relationship may be generated by variation in prey productivity and area of capture, but residuals are relatively insensitive to variation in prey size selection. After controlling for body size, many consumer-resource interaction parameters were correlated, and a positive correlation between residual prey size selection and conversion efficiency neutralizes the apparent fitness advantage of taking large prey. Our results indicate that widespread community-level patterns can be explained with simple population models that apply consistently across a range of sizes. They also indicate that the parameter space governing the dynamics and the steady states in these systems is structured such that some parts of the parameter space are unlikely to represent real systems. Finally, predator-prey size ratios represent a kind of conundrum, because they are widely observed but apparently have little influence on population size and fitness, at least at this level of organization. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.
Evaluating growth of the Porcupine Caribou Herd using a stochastic model
Walsh, Noreen E.; Griffith, Brad; McCabe, Thomas R.
1995-01-01
Estimates of the relative effects of demographic parameters on population rates of change, and of the level of natural variation in these parameters, are necessary to address potential effects of perturbations on populations. We used a stochastic model, based on survival and reproduction estimates of the Porcupine Caribou (Rangifer tarandus granti) Herd (PCH), during 1983-89 and 1989-92 to obtain distributions of potential population rates of change (r). The distribution of r produced by 1,000 trajectories of our simulation model (1983-89, r̄ = 0.013; 1989-92, r̄ = 0.003) encompassed the rate of increase calculated from an independent series of photo-survey data over the same years (1983-89, r = 0.048; 1989-92, r = -0.035). Changes in adult female survival had the largest effect on r, followed by changes in calf survival. We hypothesized that petroleum development on calving grounds, or changes in calving and post-calving habitats due to global climate change, would affect model input parameters. A decline in annual adult female survival from 0.871 to 0.847, or a decline in annual calf survival from 0.518 to 0.472, would be sufficient to cause a declining population, if all other input estimates remained the same. We then used these lower survival rates, in conjunction with our estimated amount of among-year variation, to determine a range of resulting population trajectories. Stochastic models can be used to better understand dynamics of populations, optimize sampling investment, and evaluate potential effects of various factors on population growth.
NASA Astrophysics Data System (ADS)
Norton, Andrew S.
An integral component of managing game species is an understanding of population dynamics and relative abundance. Harvest data are frequently used to estimate abundance of white-tailed deer. Unless harvest age-structure is representative of the population age-structure and harvest vulnerability remains constant from year to year, these data alone are of limited value. Additional model structure and auxiliary information has accommodated this shortcoming. Specifically, integrated age-at-harvest (AAH) state-space population models can formally combine multiple sources of data, and regularization via hierarchical model structure can increase flexibility of model parameters. I collected known fates data, which I evaluated and used to inform trends in survival parameters for an integrated AAH model. I used temperature and snow depth covariates to predict survival outside of the hunting season, and opening weekend temperature and percent of corn harvest covariates to predict hunting season survival. When auxiliary empirical data were unavailable for the AAH model, moderately informative priors provided sufficient information for convergence and parameter estimates. The AAH model was most sensitive to errors in initial abundance, but this error was calibrated after 3 years. Among vital rates, the AAH model was most sensitive to reporting rates (percentage of mortality during the hunting season related to harvest). The AAH model, using only harvest data, was able to track changing abundance trends due to changes in survival rates even when prior models did not inform these changes (i.e. prior models were constant when truth varied). I also compared AAH model results with estimates from the Wisconsin Department of Natural Resources (WIDNR). Trends in abundance estimates from both models were similar, although AAH model predictions were systematically higher than WIDNR estimates in the East study area. When I incorporated auxiliary information (i.e. integrated AAH model) about survival outside the hunting season from known fates data, predicted trends appeared more closely related to what was expected. Disagreements between the AAH model and WIDNR estimates in the East were likely related to biased predictions for reporting and survival rates from the AAH model.
Otárola, Mauricio Fernández; Avalos, Gerardo
2014-06-01
• Premise of the study: Environmental heterogeneity is a strong selective force shaping adaptation and population dynamics across temporal and spatial scales. Natural and anthropogenic gradients influence the variation of environmental and biotic factors, which determine population demography and dynamics. Successional gradients are expected to influence demographic parameters, but the relationship between these gradients and the species life history, habitat requirements, and degree of variation in demographic traits remains elusive.• Methods: We used the palm Euterpe precatoria to test the effect of successional stage on plant demography within a continuous population. We calculated demographic parameters for size stages and performed matrix analyses to investigate the demographic variation within primary and secondary forests of La Selva, Costa Rica.• Key results: We observed differences in mortality and recruitment of small juveniles between primary and secondary forests. Matrix models described satisfactorily the chronosequence of population changes, which were characterized by high population growth rate in disturbed areas, and decreased growth rate in old successional forests until reaching stability.• Conclusions: Different demographic parameters can be expressed in contiguous subpopulations along a gradient of successional stages with important consequences for population dynamics. Demographic variation superimposed on these gradients contributes to generate subpopulations with different demographic composition, density, and ecological properties. Therefore, the effects of spatial variation must be reconsidered in the design of demographic analyses of tropical palms, which are prime examples of subtle local adaptation. These considerations are crucial in the implementation of management plans for palm species within spatially complex and heterogeneous tropical landscapes. © 2014 Botanical Society of America, Inc.
Priol, Pauline; Mazerolle, Marc J; Imbeau, Louis; Drapeau, Pierre; Trudeau, Caroline; Ramière, Jessica
2014-06-01
Dynamic N-mixture models have been recently developed to estimate demographic parameters of unmarked individuals while accounting for imperfect detection. We propose an application of the Dail and Madsen (2011: Biometrics, 67, 577-587) dynamic N-mixture model in a manipulative experiment using a before-after control-impact design (BACI). Specifically, we tested the hypothesis of cavity limitation of a cavity specialist species, the northern flying squirrel, using nest box supplementation on half of 56 trapping sites. Our main purpose was to evaluate the impact of an increase in cavity availability on flying squirrel population dynamics in deciduous stands in northwestern Québec with the dynamic N-mixture model. We compared abundance estimates from this recent approach with those from classic capture-mark-recapture models and generalized linear models. We compared apparent survival estimates with those from Cormack-Jolly-Seber (CJS) models. Average recruitment rate was 6 individuals per site after 4 years. Nevertheless, we found no effect of cavity supplementation on apparent survival and recruitment rates of flying squirrels. Contrary to our expectations, initial abundance was not affected by conifer basal area (food availability) and was negatively affected by snag basal area (cavity availability). Northern flying squirrel population dynamics are not influenced by cavity availability at our deciduous sites. Consequently, we suggest that this species should not be considered an indicator of old forest attributes in our study area, especially in view of apparent wide population fluctuations across years. Abundance estimates from N-mixture models were similar to those from capture-mark-recapture models, although the latter had greater precision. Generalized linear mixed models produced lower abundance estimates, but revealed the same relationship between abundance and snag basal area. Apparent survival estimates from N-mixture models were higher and less precise than those from CJS models. However, N-mixture models can be particularly useful to evaluate management effects on animal populations, especially for species that are difficult to detect in situations where individuals cannot be uniquely identified. They also allow investigating the effects of covariates at the site level, when low recapture rates would require restricting classic CMR analyses to a subset of sites with the most captures.
Gupta, Manan; Joshi, Amitabh; Vidya, T N C
2017-01-01
Mark-recapture estimators are commonly used for population size estimation, and typically yield unbiased estimates for most solitary species with low to moderate home range sizes. However, these methods assume independence of captures among individuals, an assumption that is clearly violated in social species that show fission-fusion dynamics, such as the Asian elephant. In the specific case of Asian elephants, doubts have been raised about the accuracy of population size estimates. More importantly, the potential problem for the use of mark-recapture methods posed by social organization in general has not been systematically addressed. We developed an individual-based simulation framework to systematically examine the potential effects of type of social organization, as well as other factors such as trap density and arrangement, spatial scale of sampling, and population density, on bias in population sizes estimated by POPAN, Robust Design, and Robust Design with detection heterogeneity. In the present study, we ran simulations with biological, demographic and ecological parameters relevant to Asian elephant populations, but the simulation framework is easily extended to address questions relevant to other social species. We collected capture history data from the simulations, and used those data to test for bias in population size estimation. Social organization significantly affected bias in most analyses, but the effect sizes were variable, depending on other factors. Social organization tended to introduce large bias when trap arrangement was uniform and sampling effort was low. POPAN clearly outperformed the two Robust Design models we tested, yielding close to zero bias if traps were arranged at random in the study area, and when population density and trap density were not too low. Social organization did not have a major effect on bias for these parameter combinations at which POPAN gave more or less unbiased population size estimates. Therefore, the effect of social organization on bias in population estimation could be removed by using POPAN with specific parameter combinations, to obtain population size estimates in a social species.
Joshi, Amitabh; Vidya, T. N. C.
2017-01-01
Mark-recapture estimators are commonly used for population size estimation, and typically yield unbiased estimates for most solitary species with low to moderate home range sizes. However, these methods assume independence of captures among individuals, an assumption that is clearly violated in social species that show fission-fusion dynamics, such as the Asian elephant. In the specific case of Asian elephants, doubts have been raised about the accuracy of population size estimates. More importantly, the potential problem for the use of mark-recapture methods posed by social organization in general has not been systematically addressed. We developed an individual-based simulation framework to systematically examine the potential effects of type of social organization, as well as other factors such as trap density and arrangement, spatial scale of sampling, and population density, on bias in population sizes estimated by POPAN, Robust Design, and Robust Design with detection heterogeneity. In the present study, we ran simulations with biological, demographic and ecological parameters relevant to Asian elephant populations, but the simulation framework is easily extended to address questions relevant to other social species. We collected capture history data from the simulations, and used those data to test for bias in population size estimation. Social organization significantly affected bias in most analyses, but the effect sizes were variable, depending on other factors. Social organization tended to introduce large bias when trap arrangement was uniform and sampling effort was low. POPAN clearly outperformed the two Robust Design models we tested, yielding close to zero bias if traps were arranged at random in the study area, and when population density and trap density were not too low. Social organization did not have a major effect on bias for these parameter combinations at which POPAN gave more or less unbiased population size estimates. Therefore, the effect of social organization on bias in population estimation could be removed by using POPAN with specific parameter combinations, to obtain population size estimates in a social species. PMID:28306735
Bacles, C F E; Bouchard, C; Lange, F; Manicki, A; Tentelier, C; Lepais, O
2018-03-01
This study assesses whether the effective number of breeders (N b ) can be estimated using a time and cost-effective protocol using genetic sibship reconstruction from a single sample of young-of-the-year (YOY) for the purposes of Atlantic salmon Salmo salar population monitoring. N b was estimated for 10 consecutive reproductive seasons for S. salar in the River Nivelle, a small population located at the rear-edge of the species distribution area in France, chronically under its conservation limit and subjected to anthropogenic and environmental changes. Subsampling of real and simulated data showed that accurate estimates of N b can be obtained from YOY genotypes, collected at moderate random sampling intensity, achievable using routine juvenile electrofishing protocols. Spatial bias and time elapsed since spawning were found to affect estimates, which must be accounted for in sampling designs. N b estimated in autumn for S. salar in the River Nivelle was low and variable across years from 23 (95% C.I. 14-41) to 75 (53-101) and was not statistically correlated with the estimated number of returning adults, but it was positively correlated with the estimated number of YOY at age 9 months. N b was found to be lower for intermediate levels of redd aggregation, suggesting that the strength of the competition between males to access females affects reproductive success variance depending on redd spatial configuration. Thus, environmental factors such as habitat availability and quality for spawning and YOY development predominate over demographic ones (number of returning adults) in driving long-term population viability for S. salar in the River Nivelle. This study showcases N b as an integrated parameter, encompassing demographic and ecological information about a reproductive event, relevant to the assessment of both short-term effects of management practices and long-term population conservation status. © 2018 The Fisheries Society of the British Isles.
Yackel Adams, A.A.; Skagen, S.K.; Savidge, J.A.
2007-01-01
Many North American prairie bird populations have recently declined, and the causes of these declines remain largely unknown. To determine whether population limitation occurs during breeding, we evaluated the stability of a population of prairie birds using population-specific values for fecundity and postfledging survival. During 2001-2003, we radiomarked 67 female Lark Buntings (Calamospiza melanocorys) to determine annual fecundity and evaluate contributing factors such as nest survival and breeding response (number of breeding attempts and dispersal). Collectively, 67 females built 112 nests (1.67 ± 0.07 nests female−1 season−1; range: 1–3); 34 were second nests and 11 were third nests. Daily nest survival estimates were similar for initial and later nests with overall nest survival (DSR19) of 30.7% and 31.7%, respectively. Nest predation was the most common cause of failure (92%). Capture and radiomarking of females did not affect nest survival. Lark Bunting dispersal probabilities increased among females that fledged young from initial nests and females that lost their original nests late in the season. Conservative and liberal estimates of mean annual fecundity were 0.96 ±0.11 and 1.24 ± 0.09 female offspring per female, respectively. Given the fecundity and juvenile-survival estimates for this population, annual adult survival values of 71–77% are necessary to achieve a stable population. Because adult survival of prairie passerines ranges between 55% and 65%, this study area may not be capable of sustaining a stable population in the absence of immigration. We contrast our population assessment with one that assumes indirect values of fecundity and juvenile survival. To elucidate limiting factors, estimation of population-specific demographic parameters is desirable. We present an approach for selecting species and areas for evaluation of population stability.
Brian Stone; William Obermann; Stephanie Snyder
2005-01-01
Outlines new methods for estimating vehicle miles of travel (VMT) under current demographic and land use conditions and projecting VMT under alternative future conditions. Reports on the role that VMT estimates play in evaluating how changing land use patterns and demographics may ultimately affect regional air quality and forest health.
Johnson, Nicholas S.; Brenden, Travis O.; Swink, William D.; Lipps, Mathew A.
2016-01-01
Although population demographics of larval lampreys in streams have been studied extensively, demographics in lake environments have not. Here, we estimated survival and rates of metamorphosis for larval sea lamprey (Petromyzon marinus) populations residing in the Great Lakes near river mouths (hereafter termed lentic areas). Tagged larvae were stocked and a Bayesian multi-state tag-recovery model was used to investigate population parameters associated with tag recovery, including survival and metamorphosis probabilities. Compared to previous studies of larvae in streams, larval growth in lentic areas was substantially slower (Brody growth coefficient = 0.00132; estimate based on the recovery of six tagged larvae), survival was slightly greater (annual survival = 63%), and the length at which 50% of the larvae would be expected to metamorphose was substantially shorter (126 mm). Stochastic simulations were used to estimate the production of parasitic stage (juvenile) sea lamprey from a hypothetical population of larvae in a lentic environment. Production of juvenile sea lamprey was substantial because, even though larval growth in these environments was slow relative to stream environments, survival was high and length at metamorphosis was less. However, estimated production of juvenile sea lamprey was less for the lentic environment than for similar simulations for river environments where larvae grew faster. In circumstances where the cost to kill a larva with lampricide was equal and control funds are limited, sea lamprey control effort may be best directed toward larvae in streams with fast-growing larvae, because stream-produced larvae will most likely contribute to juvenile sea lamprey populations.
McGovern, Mark E; Canning, David
2015-11-01
Based on models with calibrated parameters for infection, case fatality rates, and vaccine efficacy, basic childhood vaccinations have been estimated to be highly cost effective. We estimated the association of vaccination with mortality directly from survey data. Using 149 cross-sectional Demographic and Health Surveys, we determined the relationship between vaccination coverage and the probability of dying between birth and 5 years of age at the survey cluster level. Our data included approximately 1 million children in 68,490 clusters from 62 countries. We considered the childhood measles, bacillus Calmette-Guérin, diphtheria-pertussis-tetanus, polio, and maternal tetanus vaccinations. Using modified Poisson regression to estimate the relative risk of child mortality in each cluster, we also adjusted for selection bias that resulted from the vaccination status of dead children not being reported. Childhood vaccination, and in particular measles and tetanus vaccination, is associated with substantial reductions in childhood mortality. We estimated that children in clusters with complete vaccination coverage have a relative risk of mortality that is 0.73 (95% confidence interval: 0.68, 0.77) times that of children in a cluster with no vaccinations. Although widely used, basic vaccines still have coverage rates well below 100% in many countries, and our results emphasize the effectiveness of increasing coverage rates in order to reduce child mortality. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Population viability analysis for endangered Roanoke logperch
Roberts, James H.; Angermeier, Paul; Anderson, Gregory B.
2016-01-01
A common strategy for recovering endangered species is ensuring that populations exceed the minimum viable population size (MVP), a demographic benchmark that theoretically ensures low long-term extinction risk. One method of establishing MVP is population viability analysis, a modeling technique that simulates population trajectories and forecasts extinction risk based on a series of biological, environmental, and management assumptions. Such models also help identify key uncertainties that have a large influence on extinction risk. We used stochastic count-based simulation models to explore extinction risk, MVP, and the possible benefits of alternative management strategies in populations of Roanoke logperch Percina rex, an endangered stream fish. Estimates of extinction risk were sensitive to the assumed population growth rate and model type, carrying capacity, and catastrophe regime (frequency and severity of anthropogenic fish kills), whereas demographic augmentation did little to reduce extinction risk. Under density-dependent growth, the estimated MVP for Roanoke logperch ranged from 200 to 4200 individuals, depending on the assumed severity of catastrophes. Thus, depending on the MVP threshold, anywhere from two to all five of the logperch populations we assessed were projected to be viable. Despite this uncertainty, these results help identify populations with the greatest relative extinction risk, as well as management strategies that might reduce this risk the most, such as increasing carrying capacity and reducing fish kills. Better estimates of population growth parameters and catastrophe regimes would facilitate the refinement of MVP and extinction-risk estimates, and they should be a high priority for future research on Roanoke logperch and other imperiled stream-fish species.
Estimation of demographic parameters in a tiger population from long-term camera trap data
Karanth, K. Ullas; Nichols, James D.; O'Connell, Allan F.; Nichols, James D.; Karanth, K. Ullas
2011-01-01
Chapter 7 (Karanth et al.) illustrated the use of camera trapping in combination with closed population capture–recapture (CR) models to estimate densities of tigers Panthera tigris. Such estimates can be very useful for investigating variation across space for a particular species (e.g., Karanth et al. 2004) or variation among species at a specific location. In addition, estimates of density continued at the same site(s) over multiple years are very useful for understanding and managing populations of large carnivores. Such multi-year studies can yield estimates of rates of change in abundance. Additionally, because the fates of marked individuals are tracked through time, biologists can delve deeper into factors driving changes in abundance such as rates of survival, recruitment and movement (Williams et al. 2002). Fortunately, modern CR approaches permit the modeling of populations that change between sampling occasions as a result of births, deaths, immigration and emigration (Pollock et al. 1990; Nichols 1992). Some of these early “open population” models focused on estimation of survival rates and, to a lesser extent, abundance, but more recent models permit estimation of recruitment and movement rates as well.
Tufto, Jarle; Lande, Russell; Ringsby, Thor-Harald; Engen, Steinar; Saether, Bernt-Erik; Walla, Thomas R; DeVries, Philip J
2012-07-01
1. We develop a Bayesian method for analysing mark-recapture data in continuous habitat using a model in which individuals movement paths are Brownian motions, life spans are exponentially distributed and capture events occur at given instants in time if individuals are within a certain attractive distance of the traps. 2. The joint posterior distribution of the dispersal rate, longevity, trap attraction distances and a number of latent variables representing the unobserved movement paths and time of death of all individuals is computed using Gibbs sampling. 3. An estimate of absolute local population density is obtained simply by dividing the Poisson counts of individuals captured at given points in time by the estimated total attraction area of all traps. Our approach for estimating population density in continuous habitat avoids the need to define an arbitrary effective trapping area that characterized previous mark-recapture methods in continuous habitat. 4. We applied our method to estimate spatial demography parameters in nine species of neotropical butterflies. Path analysis of interspecific variation in demographic parameters and mean wing length revealed a simple network of strong causation. Larger wing length increases dispersal rate, which in turn increases trap attraction distance. However, higher dispersal rate also decreases longevity, thus explaining the surprising observation of a negative correlation between wing length and longevity. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.
COST VS. QUALITY IN DEMOGRAPHIC MODELLING: WHEN IS A VITAL RATE GOOD ENOUGH?
This presentation will focus on the assessment of quality for demographic parameters to be used in population-level risk assessment. Current population models can handle genetic, demographic, and environmental stochasticity, density dependence, and multiple stressors. However, cu...
The use of resighting data to estimate the rate of population growth of the snail kite in Florida
Dreitz, V.J.; Nichols, J.D.; Hines, J.E.; Bennetts, R.E.; Kitchens, W.M.; DeAngelis, D.L.
2002-01-01
The rate of population growth (lambda) is an important demographic parameter used to assess the viability of a population and to develop management and conservation agendas. We examined the use of resighting data to estimate lambda for the snail kite population in Florida from 1997-2000. The analyses consisted of (1) a robust design approach that derives an estimate of lambda from estimates of population size and (2) the Pradel (1996) temporal symmetry (TSM) approach that directly estimates lambda using an open-population capture-recapture model. Besides resighting data, both approaches required information on the number of unmarked individuals that were sighted during the sampling periods. The point estimates of lambda differed between the robust design and TSM approaches, but the 95% confidence intervals overlapped substantially. We believe the differences may be the result of sparse data and do not indicate the inappropriateness of either modelling technique. We focused on the results of the robust design because this approach provided estimates for all study years. Variation among these estimates was smaller than levels of variation among ad hoc estimates based on previously reported index statistics. We recommend that lambda of snail kites be estimated using capture-resighting methods rather than ad hoc counts.
Nance, Holly A; Klimley, Peter; Galván-Magaña, Felipe; Martínez-Ortíz, Jimmy; Marko, Peter B
2011-01-01
Genetic diversity (θ), effective population size (N(e)), and contemporary levels of gene flow are important parameters to estimate for species of conservation concern, such as the globally endangered scalloped hammerhead shark, Sphyrna lewini. Therefore, we have reconstructed the demographic history of S. lewini across its Eastern Pacific (EP) range by applying classical and coalescent population genetic methods to a combination of 15 microsatellite loci and mtDNA control region sequences. In addition to significant population genetic structure and isolation-by-distance among seven coastal sites between central Mexico and Ecuador, the analyses revealed that all populations have experienced a bottleneck and that all current values of θ are at least an order of magnitude smaller than ancestral θ, indicating large decreases in N(e) (θ = 4N(e)μ), where μ is the mutation rate. Application of the isolation-with-migration (IM) model showed modest but significant genetic connectivity between most sampled sites (point estimates of Nm = 0.1-16.7), with divergence times (t) among all populations significantly greater than zero. Using a conservative (i.e., slow) fossil-based taxon-specific phylogenetic calibration for mtDNA mutation rates, posterior probability distributions (PPDs) for the onset of the decline in N(e) predate modern fishing in this region. The cause of decline over the last several thousand years is unknown but is highly atypical as a post-glacial demographic history. Regardless of the cause, our data and analyses suggest that S. lewini was far more abundant throughout the EP in the past than at present.
Nance, Holly A.; Klimley, Peter; Galván-Magaña, Felipe; Martínez-Ortíz, Jimmy; Marko, Peter B.
2011-01-01
Genetic diversity (θ), effective population size (Ne), and contemporary levels of gene flow are important parameters to estimate for species of conservation concern, such as the globally endangered scalloped hammerhead shark, Sphyrna lewini. Therefore, we have reconstructed the demographic history of S. lewini across its Eastern Pacific (EP) range by applying classical and coalescent population genetic methods to a combination of 15 microsatellite loci and mtDNA control region sequences. In addition to significant population genetic structure and isolation-by-distance among seven coastal sites between central Mexico and Ecuador, the analyses revealed that all populations have experienced a bottleneck and that all current values of θ are at least an order of magnitude smaller than ancestral θ, indicating large decreases in Ne (θ = 4Neμ), where μ is the mutation rate. Application of the isolation-with-migration (IM) model showed modest but significant genetic connectivity between most sampled sites (point estimates of Nm = 0.1–16.7), with divergence times (t) among all populations significantly greater than zero. Using a conservative (i.e., slow) fossil-based taxon-specific phylogenetic calibration for mtDNA mutation rates, posterior probability distributions (PPDs) for the onset of the decline in Ne predate modern fishing in this region. The cause of decline over the last several thousand years is unknown but is highly atypical as a post-glacial demographic history. Regardless of the cause, our data and analyses suggest that S. lewini was far more abundant throughout the EP in the past than at present. PMID:21789171
Identifying factors influencing contraceptive use in Bangladesh: evidence from BDHS 2014 data.
Hossain, M B; Khan, M H R; Ababneh, F; Shaw, J E H
2018-01-30
Birth control is the conscious control of the birth rate by methods which temporarily prevent conception by interfering with the normal process of ovulation, fertilization, and implantation. High contraceptive prevalence rate is always expected for controlling births for those countries that are experiencing high population growth rate. The factors that influence contraceptive prevalence are also important to know for policy implication purposes in Bangladesh. This study aims to explore the socio-economic, demographic and others key factors that influence the use of contraception in Bangladesh. The contraception data are extracted from the 2014 Bangladesh Demographic and Health Survey (BDHS) data which were collected by using a two stage stratified random sampling technique that is a source of nested variability. The nested sources of variability must be incorporated in the model using random effects in order to model the actual parameter effects on contraceptive prevalence. A mixed effect logistic regression model has been implemented for the binary contraceptive data, where parameters are estimated through generalized estimating equation by assuming exchangeable correlation structure to explore and identify the factors that truly affect the use of contraception in Bangladesh. The prevalence of contraception use by currently married 15-49 years aged women or their husbands is 62.4%. Our study finds that administrative division, place of residence, religion, number of household members, woman's age, occupation, body mass index, breastfeeding practice, husband's education, wish for children, living status with wife, sexual activity in past year, women amenorrheic status, abstaining status, number of children born in last five years and total children ever died were significantly associated with contraception use in Bangladesh. The odds of women experiencing the outcome of interest are not independent due to the nested structure of the data. As a result, a mixed effect model is implemented for the binary variable 'contraceptive use' to produce true estimates for the significant determinants of contraceptive use in Bangladesh. Knowing such true estimates is important for attaining future goals including increasing contraception use from 62 to 75% by 2020 by the Bangladesh government's Health, Population & Nutrition Sector Development Program (HPNSDP).
Potential population-level effects of increased haulout-related mortality of Pacific walrus calves
Udevitz, Mark S.; Taylor, Rebecca L.; Garlich-Miller, Joel L.; Quakenbush, Lori T.; Snyder, Jonathan A.
2013-01-01
Availability of summer sea ice has been decreasing in the Chukchi Sea during recent decades, and increasing numbers of Pacific walruses have begun using coastal haulouts in late summer during years when sea ice retreats beyond the continental shelf. Calves and yearlings are particularly susceptible to being crushed during disturbance events that cause the herd to panic and stampede at these large haulouts, but the potential population-level effects of this mortality are unknown. We used recent harvest data, along with previous assumptions about demographic parameters for this population, to estimate female population size and structure in 2009 and project these numbers forward using a range of assumptions about future harvests and haulout-related mortality that might result from increased use of coastal haulouts during late summer. We found that if demographic parameters were held constant, the levels of harvest that occurred during 1990–2008 would have allowed the population to grow during that period. Our projections indicate, however, that an increase in haulout-related mortality affecting only calves has a greater effect on the population than an equivalent increase in harvest-related mortality distributed among all age classes. Therefore, disturbance-related mortality of calves at coastal haulouts may have relatively important population consequences.
Bayesian data assimilation provides rapid decision support for vector-borne diseases.
Jewell, Chris P; Brown, Richard G
2015-07-06
Predicting the spread of vector-borne diseases in response to incursions requires knowledge of both host and vector demographics in advance of an outbreak. Although host population data are typically available, for novel disease introductions there is a high chance of the pathogen using a vector for which data are unavailable. This presents a barrier to estimating the parameters of dynamical models representing host-vector-pathogen interaction, and hence limits their ability to provide quantitative risk forecasts. The Theileria orientalis (Ikeda) outbreak in New Zealand cattle demonstrates this problem: even though the vector has received extensive laboratory study, a high degree of uncertainty persists over its national demographic distribution. Addressing this, we develop a Bayesian data assimilation approach whereby indirect observations of vector activity inform a seasonal spatio-temporal risk surface within a stochastic epidemic model. We provide quantitative predictions for the future spread of the epidemic, quantifying uncertainty in the model parameters, case infection times and the disease status of undetected infections. Importantly, we demonstrate how our model learns sequentially as the epidemic unfolds and provide evidence for changing epidemic dynamics through time. Our approach therefore provides a significant advance in rapid decision support for novel vector-borne disease outbreaks. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Parameter Heterogeneity In Breast Cancer Cost Regressions – Evidence From Five European Countries
Banks, Helen; Campbell, Harry; Douglas, Anne; Fletcher, Eilidh; McCallum, Alison; Moger, Tron Anders; Peltola, Mikko; Sveréus, Sofia; Wild, Sarah; Williams, Linda J.; Forbes, John
2015-01-01
Abstract We investigate parameter heterogeneity in breast cancer 1‐year cumulative hospital costs across five European countries as part of the EuroHOPE project. The paper aims to explore whether conditional mean effects provide a suitable representation of the national variation in hospital costs. A cohort of patients with a primary diagnosis of invasive breast cancer (ICD‐9 codes 174 and ICD‐10 C50 codes) is derived using routinely collected individual breast cancer data from Finland, the metropolitan area of Turin (Italy), Norway, Scotland and Sweden. Conditional mean effects are estimated by ordinary least squares for each country, and quantile regressions are used to explore heterogeneity across the conditional quantile distribution. Point estimates based on conditional mean effects provide a good approximation of treatment response for some key demographic and diagnostic specific variables (e.g. age and ICD‐10 diagnosis) across the conditional quantile distribution. For many policy variables of interest, however, there is considerable evidence of parameter heterogeneity that is concealed if decisions are based solely on conditional mean results. The use of quantile regression methods reinforce the need to consider beyond an average effect given the greater recognition that breast cancer is a complex disease reflecting patient heterogeneity. © 2015 The Authors. Health Economics Published by John Wiley & Sons Ltd. PMID:26633866
Population dynamics of mallards breeding in eastern Washington
Dugger, Bruce D.; Coluccy, John M.; Dugger, Katie M.; Fox, Trevor T.; Kraege, Donald K.; Petrie, Mark J.
2016-01-01
Variation in regional population trends for mallards breeding in the western United States indicates that additional research into factors that influence demographics could contribute to management and understanding the population demographics of mallards across North America. We estimated breeding incidence and adult female, nest, and brood survival in eastern Washington in 2006 and 2007 by monitoring female mallards with radio telemetry and tested how those parameters were influenced by study year (2006 vs. 2007), landscape type (agricultural vs. natural), and age (second year [SY] vs. after second year [ASY]). We also investigated the effects of female body condition and capture date on breeding incidence, and nest initiation date and hatch date on nest and brood survival, respectively. We included population parameters in a stage-based demographic model and conducted a perturbation analysis to identify which vital rates were most influential on population growth rate (λ). Adult female survival was best modeled with a constant weekly survival rate (0.994, SE = 0.003). Breeding incidence differed between years and was higher for birds in better body condition. Nest survival was higher for ASY females (0.276, SE = 0.118) than SY females (0.066, SE = 0.052), and higher on publicly managed lands (0.383, SE = 0.212) than agricultural (0.114, SE = 0.058) landscapes. Brood survival was best modeled with a constant rate for the 7-week monitoring period (0.50, SE = 0.155). The single variable having the greatest influence on λ was non-breeding season survival, but the combination of parameters from the breeding grounds explained a greater percent of the variance in λ. Mallard population growth rate was most sensitive to changes in non-breeding survival, nest success, brood survival, and breeding incidence. Future management decisions should focus on activities that improve these vital rates if managers want to increase the production of mallards in eastern Washington.
NASA Astrophysics Data System (ADS)
Fer, I.; Kelly, R.; Andrews, T.; Dietze, M.; Richardson, A. D.
2016-12-01
Our ability to forecast ecosystems is limited by how well we parameterize ecosystem models. Direct measurements for all model parameters are not always possible and inverse estimation of these parameters through Bayesian methods is computationally costly. A solution to computational challenges of Bayesian calibration is to approximate the posterior probability surface using a Gaussian Process that emulates the complex process-based model. Here we report the integration of this method within an ecoinformatics toolbox, Predictive Ecosystem Analyzer (PEcAn), and its application with two ecosystem models: SIPNET and ED2.1. SIPNET is a simple model, allowing application of MCMC methods both to the model itself and to its emulator. We used both approaches to assimilate flux (CO2 and latent heat), soil respiration, and soil carbon data from Bartlett Experimental Forest. This comparison showed that emulator is reliable in terms of convergence to the posterior distribution. A 10000-iteration MCMC analysis with SIPNET itself required more than two orders of magnitude greater computation time than an MCMC run of same length with its emulator. This difference would be greater for a more computationally demanding model. Validation of the emulator-calibrated SIPNET against both the assimilated data and out-of-sample data showed improved fit and reduced uncertainty around model predictions. We next applied the validated emulator method to the ED2, whose complexity precludes standard Bayesian data assimilation. We used the ED2 emulator to assimilate demographic data from a network of inventory plots. For validation of the calibrated ED2, we compared the model to results from Empirical Succession Mapping (ESM), a novel synthesis of successional patterns in Forest Inventory and Analysis data. Our results revealed that while the pre-assimilation ED2 formulation cannot capture the emergent demographic patterns from ESM analysis, constrained model parameters controlling demographic processes increased their agreement considerably.
Mitsui, Yuki; Setoguchi, Hiroaki
2012-12-28
Understanding demographic histories, such as divergence time, patterns of gene flow, and population size changes, in ecologically diverging lineages provide implications for the process and maintenance of population differentiation by ecological adaptation. This study addressed the demographic histories in two independently derived lineages of flood-resistant riparian plants and their non-riparian relatives [Ainsliaea linearis (riparian) and A. apiculata (non-riparian); A. oblonga (riparian) and A. macroclinidioides (non-riparian); Asteraceae] using an isolation-with-migration (IM) model based on variation at 10 nuclear DNA loci. The highest posterior probabilities of the divergence time parameters were estimated to be ca. 25,000 years ago for A. linearis and A. apiculata and ca. 9000 years ago for A. oblonga and A. macroclinidioides, although the confidence intervals of the parameters had broad ranges. The likelihood ratio tests detected evidence of historical gene flow between both riparian/non-riparian species pairs. The riparian populations showed lower levels of genetic diversity and a significant reduction in effective population sizes compared to the non-riparian populations and their ancestral populations. This study showed the recent origins of flood-resistant riparian plants, which are remarkable examples of plant ecological adaptation. The recent divergence and genetic signatures of historical gene flow among riparian/non-riparian species implied that they underwent morphological and ecological differentiation within short evolutionary timescales and have maintained their species boundaries in the face of gene flow. Comparative analyses of adaptive divergence in two sets of riparian/non-riparian lineages suggested that strong natural selection by flooding had frequently reduced the genetic diversity and size of riparian populations through genetic drift, possibly leading to fixation of adaptive traits in riparian populations. The two sets of riparian/non-riparian lineages showed contrasting patterns of gene flow and genetic differentiation, implying that each lineage showed different degrees of reproductive isolation and that they had experienced unique evolutionary and demographic histories in the process of adaptive divergence.
Population pharmacokinetics of aripiprazole in healthy Korean subjects.
Jeon, Ji-Young; Chae, Soo-Wan; Kim, Min-Gul
2016-04-01
Aripiprazole is widely used to treat schizophrenia and bipolar disorder. This study aimed to develop a combined population pharmacokinetic model for aripiprazole in healthy Korean subjects and to identify the significant covariates in the pharmacokinetic variability of aripiprazole. Aripiprazole plasma concentrations and demographic data were collected retrospectively from previous bioequivalence studies that were conducted in Chonbuk National University Hospital. Informed consent was obtained from subjects for cytochrome P450 (CYP) genotyping. The population pharmacokinetic parameters of aripiprazole were estimated using nonlinear mixed-effect modeling with first-order conditional estimation with interaction method. The effects of age, sex, weight, height, and CYP genotype were assessed as covariates. A total of 1,508 samples from 88 subjects in three bioequivalence studies were collected. The two-compartment model was adopted, and the final population model showed that the CYP2D6 genotype polymorphism, height and weight significantly affect aripiprazole disposition. The bootstrap and visual predictive check results were evaluated, showing that the accuracy of the pharmacokinetic model was acceptable. A population pharmacokinetic model of aripiprazole was developed for Korean subjects. CYP2D6 genotype polymorphism, weight, and height were included as significant factors affecting aripiprazole disposition. The population pharmacokinetic parameters of aripiprazole estimated in the present study may be useful for individualizing clinical dosages and for studying the concentration-effect relationship of the drug.
2010-01-01
Genetic variation and evolutionary demography of the shrimp Fenneropenaeus chinensis were investigated using sequence data of the complete mitochondrial control region (CR). Fragments of 993 bp of the CR were sequenced for 93 individuals from five localities over most of the species' range in the Yellow Sea and the Bohai Sea. There were 84 variable sites defining 68 haplotypes. Haplotype diversity levels were very high (0.95 ± 0.03-0.99 ± 0.02) in F. chinensis populations, whereas those of nucleotide diversity were moderate to low (0.66 ± 0.36%-0.84 ± 0.46%). Analysis of molecular variance and conventional population statistics (FST ) revealed no significant genetic structure throughout the range of F. chinensis. Mismatch distribution, estimates of population parameters and neutrality tests revealed that the significant fluctuations and shallow coalescence of mtDNA genealogies observed were coincident with estimated demographic parameters and neutrality tests, in implying important past-population size fluctuations or range expansion. Isolation with Migration (IM) coalescence results suggest that F. chinensis, distributed along the coasts of northern China and the Korean Peninsula (about 1000 km apart), diverged recently, the estimated time-split being 12,800 (7,400-18,600) years ago. PMID:21637498
Loman, Zachary G.; Monroe, Adrian; Riffell, Samuel K.; Miller, Darren A.; Vilella, Francisco; Wheat, Bradley R.; Rush, Scott A.; Martin, James A.
2018-01-01
Switchgrass (Panicum virgatum) intercropping is a novel forest management practice for biomass production intended to generate cellulosic feedstocks within intensively managed loblolly pine‐dominated landscapes. These pine plantations are important for early‐successional bird species, as short rotation times continually maintain early‐successional habitat. We tested the efficacy of using community models compared to individual surrogate species models in understanding influences on nest survival. We analysed nest data to test for differences in habitat use for 14 bird species in plots managed for switchgrass intercropping and controls within loblolly pine (Pinus taeda) plantations in Mississippi, USA.We adapted hierarchical models using hyper‐parameters to incorporate information from both common and rare species to understand community‐level nest survival. This approach incorporates rare species that are often discarded due to low sample sizes, but can inform community‐level demographic parameter estimates. We illustrate use of this approach in generating both species‐level and community‐wide estimates of daily survival rates for songbird nests. We were able to include rare species with low sample size (minimum n = 5) to inform a hyper‐prior, allowing us to estimate effects of covariates on daily survival at the community level, then compare this with a single‐species approach using surrogate species. Using single‐species models, we were unable to generate estimates below a sample size of 21 nests per species.Community model species‐level survival and parameter estimates were similar to those generated by five single‐species models, with improved precision in community model parameters.Covariates of nest placement indicated that switchgrass at the nest site (<4 m) reduced daily nest survival, although intercropping at the forest stand level increased daily nest survival.Synthesis and applications. Community models represent a viable method for estimating community nest survival rates and effects of covariates while incorporating limited data for rarely detected species. Intercropping switchgrass in loblolly pine plantations slightly increased daily nest survival at the research plot scale (0.1 km2), although at a local scale (50 m2) switchgrass negatively influenced nest survival. A likely explanation is intercropping shifted community composition, favouring species with greater disturbance tolerance.
A longitudinal analysis of nursing home outcomes.
Porell, F; Caro, F G; Silva, A; Monane, M
1998-01-01
OBJECTIVE: To investigate resident and facility attributes associated with long-term care health outcomes in nursing homes. DATA SOURCES: Quarterly Management Minutes Questionnaire (MMQ) survey data for Medicaid case-mix reimbursement of nursing homes in Massachusetts from 1991 to 1994, for specification of outcomes and resident attributes. Facility attributes are specified from cost report data. STUDY DESIGN: Multivariate logistic and "state-dependence" regression models are estimated for survival, ADL functional status, incontinence status, and mental status outcomes from longitudinal residence histories of Medicaid residents spanning 3 to 36 months in length. Outcomes are specified to be a function of resident demographic and diagnostic attributes and facility-level operating and nurse staffing attributes. PRINCIPAL FINDINGS: The estimated parameters for resident demographic and diagnostic attributes showed a great deal of construct validity with respect to clinical expectations regarding risk factors for adverse outcomes. Few facility attributes were associated with outcomes generally, and none was significantly associated with all four outcomes. CONCLUSIONS: The absence of uniform associations between facility attributes and the various long-term care health outcomes studied suggests that strong facility performance on one health outcome may coexist with much weaker performance on other outcomes. This has implications for the aggregation of individual facility performance measures on multiple outcomes and the development of overall outcome performance measures. PMID:9776939
Demographic rates of Golden-cheeked Warblers in an urbanizing woodland preserve
Jennifer L. Reidy; Frank R. Thompson; Grant M. Connette; Lisa O' Donnell
2018-01-01
Knowledge of demographics is important in conservation planning for endangered species. We monitored the endangered Golden-cheeked Warbler (Setophaga chrysoparia) at a large, discontinuous preserve in an urbanizing landscape in central Texas, USA, to estimate survival and productivity. We estimated adult male survival using a spatial Cormack-Jolly-...
Wood, K.V.; Nichols, J.D.; Percival, H.F.; Hines, J.E.
1998-01-01
During 1991-1993, we conducted capture-recapture studies on pig frogs, Rana grylio, in seven study locations in northcentral Florida. Resulting data were used to test hypotheses about variation in survival probability over different size-sex classes of pig frogs. We developed multistate capture-recapture models for the resulting data and used them to estimate survival rates and frog abundance. Tests provided strong evidence of survival differences among size-sex classes, with adult females showing the highest survival probabilities. Adult males and juvenile frogs had lower survival rates that were similar to each other. Adult females were more abundant than adult males in most locations at most sampling occasions. We recommended probabilistic capture-recapture models in general, and multistate models in particular, for robust estimation of demographic parameters in amphibian populations.
Using Optimisation Techniques to Granulise Rough Set Partitions
NASA Astrophysics Data System (ADS)
Crossingham, Bodie; Marwala, Tshilidzi
2007-11-01
This paper presents an approach to optimise rough set partition sizes using various optimisation techniques. Three optimisation techniques are implemented to perform the granularisation process, namely, genetic algorithm (GA), hill climbing (HC) and simulated annealing (SA). These optimisation methods maximise the classification accuracy of the rough sets. The proposed rough set partition method is tested on a set of demographic properties of individuals obtained from the South African antenatal survey. The three techniques are compared in terms of their computational time, accuracy and number of rules produced when applied to the Human Immunodeficiency Virus (HIV) data set. The optimised methods results are compared to a well known non-optimised discretisation method, equal-width-bin partitioning (EWB). The accuracies achieved after optimising the partitions using GA, HC and SA are 66.89%, 65.84% and 65.48% respectively, compared to the accuracy of EWB of 59.86%. In addition to rough sets providing the plausabilities of the estimated HIV status, they also provide the linguistic rules describing how the demographic parameters drive the risk of HIV.
Miller, Justin B; Axelrod, Bradley N; Schutte, Christian
2012-01-01
The recent release of the Wechsler Memory Scale Fourth Edition contains many improvements from a theoretical and administration perspective, including demographic corrections using the Advanced Clinical Solutions. Although the administration time has been reduced from previous versions, a shortened version may be desirable in certain situations given practical time limitations in clinical practice. The current study evaluated two- and three-subtest estimations of demographically corrected Immediate and Delayed Memory index scores using both simple arithmetic prorating and regression models. All estimated values were significantly associated with observed index scores. Use of Lin's Concordance Correlation Coefficient as a measure of agreement showed a high degree of precision and virtually zero bias in the models, although the regression models showed a stronger association than prorated models. Regression-based models proved to be more accurate than prorated estimates with less dispersion around observed values, particularly when using three subtest regression models. Overall, the present research shows strong support for estimating demographically corrected index scores on the WMS-IV in clinical practice with an adequate performance using arithmetically prorated models and a stronger performance using regression models to predict index scores.
Covariate analysis of bivariate survival data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bennett, L.E.
1992-01-01
The methods developed are used to analyze the effects of covariates on bivariate survival data when censoring and ties are present. The proposed method provides models for bivariate survival data that include differential covariate effects and censored observations. The proposed models are based on an extension of the univariate Buckley-James estimators which replace censored data points by their expected values, conditional on the censoring time and the covariates. For the bivariate situation, it is necessary to determine the expectation of the failure times for one component conditional on the failure or censoring time of the other component. Two different methodsmore » have been developed to estimate these expectations. In the semiparametric approach these expectations are determined from a modification of Burke's estimate of the bivariate empirical survival function. In the parametric approach censored data points are also replaced by their conditional expected values where the expected values are determined from a specified parametric distribution. The model estimation will be based on the revised data set, comprised of uncensored components and expected values for the censored components. The variance-covariance matrix for the estimated covariate parameters has also been derived for both the semiparametric and parametric methods. Data from the Demographic and Health Survey was analyzed by these methods. The two outcome variables are post-partum amenorrhea and breastfeeding; education and parity were used as the covariates. Both the covariate parameter estimates and the variance-covariance estimates for the semiparametric and parametric models will be compared. In addition, a multivariate test statistic was used in the semiparametric model to examine contrasts. The significance of the statistic was determined from a bootstrap distribution of the test statistic.« less
ERIC Educational Resources Information Center
Geverdt, Douglas E.
2015-01-01
The National Center for Education Statistics (NCES) Education Demographic and Geographic Estimates (EDGE) program develops geographic data to help policymakers, program administrators, and the public understand relationships between educational institutions and the communities they serve. One of the commonly used geographic data items is the NCES…
2013-01-01
Demographic estimates of population at risk often underpin epidemiologic research and public health surveillance efforts. In spite of their central importance to epidemiology and public-health practice, little previous attention has been paid to evaluating the magnitude of errors associated with such estimates or the sensitivity of epidemiologic statistics to these effects. In spite of the well-known observation that accuracy in demographic estimates declines as the size of the population to be estimated decreases, demographers continue to face pressure to produce estimates for increasingly fine-grained population characteristics at ever-smaller geographic scales. Unfortunately, little guidance on the magnitude of errors that can be expected in such estimates is currently available in the literature and available for consideration in small-area epidemiology. This paper attempts to fill this current gap by producing a Vintage 2010 set of single-year-of-age estimates for census tracts, then evaluating their accuracy and precision in light of the results of the 2010 Census. These estimates are produced and evaluated for 499 census tracts in New Mexico for single-years of age from 0 to 21 and for each sex individually. The error distributions associated with these estimates are characterized statistically using non-parametric statistics including the median and 2.5th and 97.5th percentiles. The impact of these errors are considered through simulations in which observed and estimated 2010 population counts are used as alternative denominators and simulated event counts are used to compute a realistic range fo prevalence values. The implications of the results of this study for small-area epidemiologic research in cancer and environmental health are considered. PMID:24359344
Kamath, Pauline L; Haroldson, Mark A; Luikart, Gordon; Paetkau, David; Whitman, Craig; van Manen, Frank T
2015-11-01
Effective population size (N(e)) is a key parameter for monitoring the genetic health of threatened populations because it reflects a population's evolutionary potential and risk of extinction due to genetic stochasticity. However, its application to wildlife monitoring has been limited because it is difficult to measure in natural populations. The isolated and well-studied population of grizzly bears (Ursus arctos) in the Greater Yellowstone Ecosystem provides a rare opportunity to examine the usefulness of different N(e) estimators for monitoring. We genotyped 729 Yellowstone grizzly bears using 20 microsatellites and applied three single-sample estimators to examine contemporary trends in generation interval (GI), effective number of breeders (N(b)) and N(e) during 1982-2007. We also used multisample methods to estimate variance (N(eV)) and inbreeding N(e) (N(eI)). Single-sample estimates revealed positive trajectories, with over a fourfold increase in N(e) (≈100 to 450) and near doubling of the GI (≈8 to 14) from the 1980s to 2000s. N(eV) (240-319) and N(eI) (256) were comparable with the harmonic mean single-sample N(e) (213) over the time period. Reanalysing historical data, we found N(eV) increased from ≈80 in the 1910s-1960s to ≈280 in the contemporary population. The estimated ratio of effective to total census size (N(e) /N(c)) was stable and high (0.42-0.66) compared to previous brown bear studies. These results support independent demographic evidence for Yellowstone grizzly bear population growth since the 1980s. They further demonstrate how genetic monitoring of N(e) can complement demographic-based monitoring of N(c) and vital rates, providing a valuable tool for wildlife managers. © 2015 John Wiley & Sons Ltd.
Adam Duarte,; Hatfield, Jeffrey; Todd M. Swannack,; Michael R. J. Forstner,; M. Clay Green,; Floyd W. Weckerly,
2015-01-01
Population viability analyses provide a quantitative approach that seeks to predict the possible future status of a species of interest under different scenarios and, therefore, can be important components of large-scale species’ conservation programs. We created a model and simulated range-wide population and breeding habitat dynamics for an endangered woodland warbler, the golden-cheeked warbler (Setophaga chrysoparia). Habitat-transition probabilities were estimated across the warbler's breeding range by combining National Land Cover Database imagery with multistate modeling. Using these estimates, along with recently published demographic estimates, we examined if the species can remain viable into the future given the current conditions. Lastly, we evaluated if protecting a greater amount of habitat would increase the number of warblers that can be supported in the future by systematically increasing the amount of protected habitat and comparing the estimated terminal carrying capacity at the end of 50 years of simulated habitat change. The estimated habitat-transition probabilities supported the hypothesis that habitat transitions are unidirectional, whereby habitat is more likely to diminish than regenerate. The model results indicated population viability could be achieved under current conditions, depending on dispersal. However, there is considerable uncertainty associated with the population projections due to parametric uncertainty. Model results suggested that increasing the amount of protected lands would have a substantial impact on terminal carrying capacities at the end of a 50-year simulation. Notably, this study identifies the need for collecting the data required to estimate demographic parameters in relation to changes in habitat metrics and population density in multiple regions, and highlights the importance of establishing a common definition of what constitutes protected habitat, what management goals are suitable within those protected areas, and a standard operating procedure to identify areas of priority for habitat conservation efforts. Therefore, we suggest future efforts focus on these aspects of golden-cheeked warbler conservation and ecology.
A projection of lesser prairie chicken (Tympanuchus pallidicinctus) populations range-wide
Cummings, Jonathan W.; Converse, Sarah J.; Moore, Clinton T.; Smith, David R.; Nichols, Clay T.; Allan, Nathan L.; O'Meilia, Chris M.
2017-08-09
We built a population viability analysis (PVA) model to predict future population status of the lesser prairie-chicken (Tympanuchus pallidicinctus, LEPC) in four ecoregions across the species’ range. The model results will be used in the U.S. Fish and Wildlife Service's (FWS) Species Status Assessment (SSA) for the LEPC. Our stochastic projection model combined demographic rate estimates from previously published literature with demographic rate estimates that integrate the influence of climate conditions. This LEPC PVA projects declining populations with estimated population growth rates well below 1 in each ecoregion regardless of habitat or climate change. These results are consistent with estimates of LEPC population growth rates derived from other demographic process models. Although the absolute magnitude of the decline is unlikely to be as low as modeling tools indicate, several different lines of evidence suggest LEPC populations are declining.
Williams, R C; Knowler, W C; Pettitt, D J; Long, J C; Rokala, D A; Polesky, H F; Hackenberg, R A; Steinberg, A G; Bennett, P H
1992-01-01
Complementary genetic and demographic analyses estimate the total proportion of European-American admixture in the Gila River Indian Community and trace its mode of entry. Among the 9,616 residents in the sample, 2,015 persons claim only partial Native American heritage. A procedure employing 23 alleles or haplotypes at eight loci was used to estimate the proportion of European-American admixture, m(a), for the entire sample and within six categories of Caucasian admixture calculated from demographic data, md. The genetic analysis gave an estimate of total European-American admixture in the community of 0.054 (95% confidence interval [CI] .044-.063), while an estimate from demographic records was similar, .059. Regression of m(a) on md yielded a fitted line m(a) = .922md, r = .959 (P = .0001). When total European-American admixture is partitioned between the contributing populations, Mexican-Americans have provided .671, European-Americans .305, and African-Americans .023. These results are discussed within the context of the ethnic composition of the Gila River Indian Community, the assumptions underlying the methods, and the potential that demographic data have for enriching genetic measurements of human admixture. It is concluded that, despite the severe assumptions of the mathematical methods, accurate, reliable estimates of genetic admixture are possible from allele and haplotype frequencies, even when there is little demographic information for the population. PMID:1609790
Reproductive Declines in an Endangered Seabird: Cause for Concern or Signs of Conservation Success?
Schuetz, Justin
2011-01-01
Collection and analysis of demographic data play a critical role in monitoring and management of endangered taxa. I analyzed long-term clutch size and fledgling productivity data for California least tern (Sternula antillarum browni), a federally endangered subspecies that has recently become a candidate for down-listing. While the breeding population grew from approximately 1,253 to 7,241 pairs (578%) during the study period (1988–2009) both clutch size and fledgling productivity declined. Clutch size decreased by approximately 0.27 eggs (14%) from 1990–2004 then showed a moderate increase of 0.11 eggs from 2004–2009. Estimates of fledgling productivity showed a similar pattern of decline and moderate increase even after controlling for clutch size. Sea surface temperature anomalies, an index of El Niño-Southern Oscillation activity, did not influence clutch size but were associated with fledgling productivity through a non-linear relationship. Both clutch size and fledgling productivity increased with latitude, potentially indicating a gradient of life-history trade-offs. Random site effects explained little of the overall variation in clutch size (3%) or fledgling productivity (<1%) suggesting that site characteristics beyond those associated with latitude had little bearing on either measure of reproduction. Despite intensive monitoring and management, causes of variation in key demographic parameters remain poorly understood. Long-term declines in clutch size and fledgling productivity may reflect: 1) reduced food availability, 2) increased density-dependent competition, and/or 3) age-dependent reproduction coupled with a shifting population age-structure. Until the mechanisms shaping demographic parameters and population change are better understood, the success of past management and the probability of ongoing recovery will remain difficult to characterize. PMID:21559287
Inferring responses to climate dynamics from historical demography in neotropical forest lizards
Xue, Alexander T.; Brown, Jason L.; Alvarado-Serrano, Diego F.; Rodrigues, Miguel T.; Hickerson, Michael J.; Carnaval, Ana C.
2016-01-01
We apply a comparative framework to test for concerted demographic changes in response to climate shifts in the neotropical lowland forests, learning from the past to inform projections of the future. Using reduced genomic (SNP) data from three lizard species codistributed in Amazonia and the Atlantic Forest (Anolis punctatus, Anolis ortonii, and Polychrus marmoratus), we first reconstruct former population history and test for assemblage-level responses to cycles of moisture transport recently implicated in changes of forest distribution during the Late Quaternary. We find support for population shifts within the time frame of inferred precipitation fluctuations (the last 250,000 y) but detect idiosyncratic responses across species and uniformity of within-species responses across forest regions. These results are incongruent with expectations of concerted population expansion in response to increased rainfall and fail to detect out-of-phase demographic syndromes (expansions vs. contractions) across forest regions. Using reduced genomic data to infer species-specific demographical parameters, we then model the plausible spatial distribution of genetic diversity in the Atlantic Forest into future climates (2080) under a medium carbon emission trajectory. The models forecast very distinct trajectories for the lizard species, reflecting unique estimated population densities and dispersal abilities. Ecological and demographic constraints seemingly lead to distinct and asynchronous responses to climatic regimes in the tropics, even among similarly distributed taxa. Incorporating such constraints is key to improve modeling of the distribution of biodiversity in the past and future. PMID:27432951
Inferring responses to climate dynamics from historical demography in neotropical forest lizards.
Prates, Ivan; Xue, Alexander T; Brown, Jason L; Alvarado-Serrano, Diego F; Rodrigues, Miguel T; Hickerson, Michael J; Carnaval, Ana C
2016-07-19
We apply a comparative framework to test for concerted demographic changes in response to climate shifts in the neotropical lowland forests, learning from the past to inform projections of the future. Using reduced genomic (SNP) data from three lizard species codistributed in Amazonia and the Atlantic Forest (Anolis punctatus, Anolis ortonii, and Polychrus marmoratus), we first reconstruct former population history and test for assemblage-level responses to cycles of moisture transport recently implicated in changes of forest distribution during the Late Quaternary. We find support for population shifts within the time frame of inferred precipitation fluctuations (the last 250,000 y) but detect idiosyncratic responses across species and uniformity of within-species responses across forest regions. These results are incongruent with expectations of concerted population expansion in response to increased rainfall and fail to detect out-of-phase demographic syndromes (expansions vs. contractions) across forest regions. Using reduced genomic data to infer species-specific demographical parameters, we then model the plausible spatial distribution of genetic diversity in the Atlantic Forest into future climates (2080) under a medium carbon emission trajectory. The models forecast very distinct trajectories for the lizard species, reflecting unique estimated population densities and dispersal abilities. Ecological and demographic constraints seemingly lead to distinct and asynchronous responses to climatic regimes in the tropics, even among similarly distributed taxa. Incorporating such constraints is key to improve modeling of the distribution of biodiversity in the past and future.
Conservation biology for suites of species: Demographic modeling for Pacific island kingfishers
Kesler, D.C.; Haig, S.M.
2007-01-01
Conservation practitioners frequently extrapolate data from single-species investigations when managing critically endangered populations. However, few researchers initiate work with the intent of making findings useful to conservation efforts for other species. We presented and explored the concept of conducting conservation-oriented research for suites of geographically separated populations with similar natural histories, resource needs, and extinction threats. An example was provided in the form of an investigation into the population demography of endangered Micronesian kingfishers (Todiramphus cinnamominus). We provided the first demographic parameter estimates for any of the 12 endangered Pacific Todiramphus species, and used results to develop a population projection matrix model for management throughout the insular Pacific. Further, we used the model for elasticity and simulation analyses with demographic values that randomly varied across ranges that might characterize congener populations. Results from elasticity and simulation analyses indicated that changes in breeding adult survival exerted the greatest magnitude of influence on population dynamics. However, changes in nestling survival were more consistently correlated with population dynamics as demographic rates were randomly altered. We concluded that conservation practitioners working with endangered Pacific kingfishers should primarily focus efforts on factors affecting nestling and breeder survival, and secondarily address fledgling juveniles and helpers. Further, we described how the generalized base model might be changed to focus on individual populations and discussed the potential application of multi-species models to other conservation situations. ?? 2007 Elsevier Ltd. All rights reserved.
Sanderlin, J.S.; Waser, P.M.; Hines, J.E.; Nichols, J.D.
2012-01-01
Metapopulation ecology has historically been rich in theory, yet analytical approaches for inferring demographic relationships among local populations have been few. We show how reverse-time multi-state capture-recapture models can be used to estimate the importance of local recruitment and interpopulation dispersal to metapopulation growth. We use 'contribution metrics' to infer demographic connectedness among eight local populations of banner-tailed kangaroo rats, to assess their demographic closure, and to investigate sources of variation in these contributions. Using a 7 year dataset, we show that: (i) local populations are relatively independent demographically, and contributions to local population growth via dispersal within the system decline with distance; (ii) growth contributions via local survival and recruitment are greater for adults than juveniles, while contributions involving dispersal are greater for juveniles; (iii) central populations rely more on local recruitment and survival than peripheral populations; (iv) contributions involving dispersal are not clearly related to overall metapopulation density; and (v) estimated contributions from outside the system are unexpectedly large. Our analytical framework can classify metapopulations on a continuum between demographic independence and panmixia, detect hidden population growth contributions, and make inference about other population linkage forms, including rescue effects and source-sink structures. Finally, we discuss differences between demographic and genetic population linkage patterns for our system. ?? 2011 The Royal Society.
Jenkinson, Toni-Marie; Muncer, Steven; Wheeler, Miranda; Brechin, Don; Evans, Stephen
2018-06-01
Neuropsychological assessment requires accurate estimation of an individual's premorbid cognitive abilities. Oral word reading tests, such as the test of premorbid functioning (TOPF), and demographic variables, such as age, sex, and level of education, provide a reasonable indication of premorbid intelligence, but their ability to predict other related cognitive abilities is less well understood. This study aimed to develop regression equations, based on the TOPF and demographic variables, to predict scores on tests of verbal fluency and naming ability. A sample of 119 healthy adults provided demographic information and were tested using the TOPF, FAS, animal naming test (ANT), and graded naming test (GNT). Multiple regression analyses, using the TOPF and demographics as predictor variables, were used to estimate verbal fluency and naming ability test scores. Change scores and cases of significant impairment were calculated for two clinical samples with diagnosed neurological conditions (TBI and meningioma) using the method in Knight, McMahon, Green, and Skeaff (). Demographic variables provided a significant contribution to the prediction of all verbal fluency and naming ability test scores; however, adding TOPF score to the equation considerably improved prediction beyond that afforded by demographic variables alone. The percentage of variance accounted for by demographic variables and/or TOPF score varied from 19 per cent (FAS), 28 per cent (ANT), and 41 per cent (GNT). Change scores revealed significant differences in performance in the clinical groups, particularity the TBI group. Demographic variables, particularly education level, and scores on the TOPF should be taken into consideration when interpreting performance on tests of verbal fluency and naming ability. © 2017 The British Psychological Society.
Agent-based Large-Scale Emergency Evacuation Using Real-Time Open Government Data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lu, Wei; Liu, Cheng; Bhaduri, Budhendra L
The open government initiatives have provided tremendous data resources for the transportation system and emergency services in urban areas. This paper proposes a traffic simulation framework using high temporal resolution demographic data and real time open government data for evacuation planning and operation. A comparison study using real-world data in Seattle, Washington is conducted to evaluate the framework accuracy and evacuation efficiency. The successful simulations of selected area prove the concept to take advantage open government data, open source data, and high resolution demographic data in emergency management domain. There are two aspects of parameters considered in this study: usermore » equilibrium (UE) conditions of traffic assignment model (simple Non-UE vs. iterative UE) and data temporal resolution (Daytime vs. Nighttime). Evacuation arrival rate, average travel time, and computation time are adopted as Measure of Effectiveness (MOE) for evacuation performance analysis. The temporal resolution of demographic data has significant impacts on urban transportation dynamics during evacuation scenarios. Better evacuation performance estimation can be approached by integrating both Non-UE and UE scenarios. The new framework shows flexibility in implementing different evacuation strategies and accuracy in evacuation performance. The use of this framework can be explored to day-to-day traffic assignment to support daily traffic operations.« less
Hare, Matthew P; Nunney, Leonard; Schwartz, Michael K; Ruzzante, Daniel E; Burford, Martha; Waples, Robin S; Ruegg, Kristen; Palstra, Friso
2011-06-01
Effective population size (N(e)) determines the strength of genetic drift in a population and has long been recognized as an important parameter for evaluating conservation status and threats to genetic health of populations. Specifically, an estimate of N(e) is crucial to management because it integrates genetic effects with the life history of the species, allowing for predictions of a population's current and future viability. Nevertheless, compared with ecological and demographic parameters, N(e) has had limited influence on species management, beyond its application in very small populations. Recent developments have substantially improved N(e) estimation; however, some obstacles remain for the practical application of N(e) estimates. For example, the need to define the spatial and temporal scale of measurement makes the concept complex and sometimes difficult to interpret. We reviewed approaches to estimation of N(e) over both long-term and contemporary time frames, clarifying their interpretations with respect to local populations and the global metapopulation. We describe multiple experimental factors affecting robustness of contemporary N(e) estimates and suggest that different sampling designs can be combined to compare largely independent measures of N(e) for improved confidence in the result. Large populations with moderate gene flow pose the greatest challenges to robust estimation of contemporary N(e) and require careful consideration of sampling and analysis to minimize estimator bias. We emphasize the practical utility of estimating N(e) by highlighting its relevance to the adaptive potential of a population and describing applications in management of marine populations, where the focus is not always on critically endangered populations. Two cases discussed include the mechanisms generating N(e) estimates many orders of magnitude lower than census N in harvested marine fishes and the predicted reduction in N(e) from hatchery-based population supplementation. ©2011 Society for Conservation Biology.
Compensatory effects of recruitment and survival when amphibian populations are perturbed by disease
Muths, E.; Scherer, R. D.; Pilliod, D.S.
2011-01-01
The need to increase our understanding of factors that regulate animal population dynamics has been catalysed by recent, observed declines in wildlife populations worldwide. Reliable estimates of demographic parameters are critical for addressing basic and applied ecological questions and understanding the response of parameters to perturbations (e.g. disease, habitat loss, climate change). However, to fully assess the impact of perturbation on population dynamics, all parameters contributing to the response of the target population must be estimated. We applied the reverse-time model of Pradel in Program mark to 6years of capture-recapture data from two populations of Anaxyrus boreas (boreal toad) populations, one with disease and one without. We then assessed a priori hypotheses about differences in survival and recruitment relative to local environmental conditions and the presence of disease. We further explored the relative contribution of survival probability and recruitment rate to population growth and investigated how shifts in these parameters can alter population dynamics when a population is perturbed. High recruitment rates (0??41) are probably compensating for low survival probability (range 0??51-0??54) in the population challenged by an emerging pathogen, resulting in a relatively slow rate of decline. In contrast, the population with no evidence of disease had high survival probability (range 0??75-0??78) but lower recruitment rates (0??25). Synthesis and applications.We suggest that the relationship between survival and recruitment may be compensatory, providing evidence that populations challenged with disease are not necessarily doomed to extinction. A better understanding of these interactions may help to explain, and be used to predict, population regulation and persistence for wildlife threatened with disease. Further, reliable estimates of population parameters such as recruitment and survival can guide the formulation and implementation of conservation actions such as repatriations or habitat management aimed to improve recruitment. ?? 2011 The Authors. Journal of Applied Ecology ?? 2011 British Ecological Society.
Demographic Data for Special Needs Children in Title XX Day Care. Report No. 7698.
ERIC Educational Resources Information Center
Asano, Mildred
Presented are demographic data for handicapped children in the Philadelphia area who might be eligible for federally funded (Title XX) day care services. The report consists of data tables and narrative sections for the following information: estimated number of handicapped children within catchment areas (CA's); estimated median income level of…
Ali, Sajid; Soubeyrand, Samuel; Gladieux, Pierre; Giraud, Tatiana; Leconte, Marc; Gautier, Angélique; Mboup, Mamadou; Chen, Wanquan; de Vallavieille-Pope, Claude; Enjalbert, Jérôme
2016-07-01
Inferring reproductive and demographic parameters of populations is crucial to our understanding of species ecology and evolutionary potential but can be challenging, especially in partially clonal organisms. Here, we describe a new and accurate method, cloncase, for estimating both the rate of sexual vs. asexual reproduction and the effective population size, based on the frequency of clonemate resampling across generations. Simulations showed that our method provides reliable estimates of sex frequency and effective population size for a wide range of parameters. The cloncase method was applied to Puccinia striiformis f.sp. tritici, a fungal pathogen causing stripe/yellow rust, an important wheat disease. This fungus is highly clonal in Europe but has been suggested to recombine in Asia. Using two temporally spaced samples of P. striiformis f.sp. tritici in China, the estimated sex frequency was 75% (i.e. three-quarter of individuals being sexually derived during the yearly sexual cycle), indicating strong contribution of sexual reproduction to the life cycle of the pathogen in this area. The inferred effective population size of this partially clonal organism (Nc = 998) was in good agreement with estimates obtained using methods based on temporal variations in allelic frequencies. The cloncase estimator presented herein is the first method allowing accurate inference of both sex frequency and effective population size from population data without knowledge of recombination or mutation rates. cloncase can be applied to population genetic data from any organism with cyclical parthenogenesis and should in particular be very useful for improving our understanding of pest and microbial population biology. © 2016 John Wiley & Sons Ltd.
Lapierre, Marguerite; Blin, Camille; Lambert, Amaury; Achaz, Guillaume; Rocha, Eduardo P C
2016-07-01
Recent studies have linked demographic changes and epidemiological patterns in bacterial populations using coalescent-based approaches. We identified 26 studies using skyline plots and found that 21 inferred overall population expansion. This surprising result led us to analyze the impact of natural selection, recombination (gene conversion), and sampling biases on demographic inference using skyline plots and site frequency spectra (SFS). Forward simulations based on biologically relevant parameters from Escherichia coli populations showed that theoretical arguments on the detrimental impact of recombination and especially natural selection on the reconstructed genealogies cannot be ignored in practice. In fact, both processes systematically lead to spurious interpretations of population expansion in skyline plots (and in SFS for selection). Weak purifying selection, and especially positive selection, had important effects on skyline plots, showing patterns akin to those of population expansions. State-of-the-art techniques to remove recombination further amplified these biases. We simulated three common sampling biases in microbiological research: uniform, clustered, and mixed sampling. Alone, or together with recombination and selection, they further mislead demographic inferences producing almost any possible skyline shape or SFS. Interestingly, sampling sub-populations also affected skyline plots and SFS, because the coalescent rates of populations and their sub-populations had different distributions. This study suggests that extreme caution is needed to infer demographic changes solely based on reconstructed genealogies. We suggest that the development of novel sampling strategies and the joint analyzes of diverse population genetic methods are strictly necessary to estimate demographic changes in populations where selection, recombination, and biased sampling are present. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
Scott, Finlay; Jardim, Ernesto; Millar, Colin P; Cerviño, Santiago
2016-01-01
Estimating fish stock status is very challenging given the many sources and high levels of uncertainty surrounding the biological processes (e.g. natural variability in the demographic rates), model selection (e.g. choosing growth or stock assessment models) and parameter estimation. Incorporating multiple sources of uncertainty in a stock assessment allows advice to better account for the risks associated with proposed management options, promoting decisions that are more robust to such uncertainty. However, a typical assessment only reports the model fit and variance of estimated parameters, thereby underreporting the overall uncertainty. Additionally, although multiple candidate models may be considered, only one is selected as the 'best' result, effectively rejecting the plausible assumptions behind the other models. We present an applied framework to integrate multiple sources of uncertainty in the stock assessment process. The first step is the generation and conditioning of a suite of stock assessment models that contain different assumptions about the stock and the fishery. The second step is the estimation of parameters, including fitting of the stock assessment models. The final step integrates across all of the results to reconcile the multi-model outcome. The framework is flexible enough to be tailored to particular stocks and fisheries and can draw on information from multiple sources to implement a broad variety of assumptions, making it applicable to stocks with varying levels of data availability The Iberian hake stock in International Council for the Exploration of the Sea (ICES) Divisions VIIIc and IXa is used to demonstrate the framework, starting from length-based stock and indices data. Process and model uncertainty are considered through the growth, natural mortality, fishing mortality, survey catchability and stock-recruitment relationship. Estimation uncertainty is included as part of the fitting process. Simple model averaging is used to integrate across the results and produce a single assessment that considers the multiple sources of uncertainty.
Mortality in Code Blue; can APACHE II and PRISM scores be used as markers for prognostication?
Bakan, Nurten; Karaören, Gülşah; Tomruk, Şenay Göksu; Keskin Kayalar, Sinem
2018-03-01
Code blue (CB) is an emergency call system developed to respond to cardiac and respiratory arrest in hospitals. However, in literature, no scoring system has been reported that can predict mortality in CB procedures. In this study, we aimed to investigate the effectiveness of estimated APACHE II and PRISM scores in the prediction of mortality in patients assessed using CB to retrospectively analyze CB calls. We retrospectively examined 1195 patients who were evaluated by the CB team at our hospital between 2009 and 2013. The demographic data of the patients, diagnosis and relevant de-partments, reasons for CB, cardiopulmonary resuscitation duration, mortality calculated from the APACHE II and PRISM scores, and the actual mortality rates were retrospectively record-ed from CB notification forms and the hospital database. In all age groups, there was a significant difference between actual mortality rate and the expected mortality rate as estimated using APACHE II and PRISM scores in CB calls (p<0.05). The actual mortality rate was significantly lower than the expected mortality. APACHE and PRISM scores with the available parameters will not help predict mortality in CB procedures. Therefore, novels scoring systems using different parameters are needed.
Dong, Nianbo; Lipsey, Mark W
2017-01-01
It is unclear whether propensity score analysis (PSA) based on pretest and demographic covariates will meet the ignorability assumption for replicating the results of randomized experiments. This study applies within-study comparisons to assess whether pre-Kindergarten (pre-K) treatment effects on achievement outcomes estimated using PSA based on a pretest and demographic covariates can approximate those found in a randomized experiment. Data-Four studies with samples of pre-K children each provided data on two math achievement outcome measures with baseline pretests and child demographic variables that included race, gender, age, language spoken at home, and mother's highest education. Research Design and Data Analysis-A randomized study of a pre-K math curriculum provided benchmark estimates of effects on achievement measures. Comparison samples from other pre-K studies were then substituted for the original randomized control and the effects were reestimated using PSA. The correspondence was evaluated using multiple criteria. The effect estimates using PSA were in the same direction as the benchmark estimates, had similar but not identical statistical significance, and did not differ from the benchmarks at statistically significant levels. However, the magnitude of the effect sizes differed and displayed both absolute and relative bias larger than required to show statistical equivalence with formal tests, but those results were not definitive because of the limited statistical power. We conclude that treatment effect estimates based on a single pretest and demographic covariates in PSA correspond to those from a randomized experiment on the most general criteria for equivalence.
Pup Mortality in a Rapidly Declining Harbour Seal (Phoca vitulina) Population
Hanson, Nora; Thompson, Dave; Duck, Callan; Moss, Simon; Lonergan, Mike
2013-01-01
The harbour seal population in Orkney, off the north coast of Scotland, has reduced by 65% between 2001 and 2010. The cause(s) of this decline are unknown but must affect the demographic parameters of the population. Here, satellite telemetry data were used to test the hypothesis that increased pup mortality could be a primary driver of the decline in Orkney. Pup mortality and tag failure parameters were estimated from the duration of operation of satellite tags deployed on harbour seal pups from the Orkney population (n = 24) and from another population on the west coast of Scotland (n = 24) where abundance was stable. Survival probabilities from both populations were best represented by a common gamma distribution and were not different from one another, suggesting that increased pup mortality is unlikely to be the primary agent in the Orkney population decline. The estimated probability of surviving to 6 months was 0.390 (95% CI 0.297 – 0.648) and tag failure was represented by a Gaussian distribution, with estimated mean 270 (95% CI = 198 – 288) and s.d. 21 (95% CI = 1 – 66) days. These results suggest that adult survival is the most likely proximate cause of the decline. They also demonstrate a novel technique for attaining age-specific mortality rates from telemetry data. PMID:24312239
Laufenberg, Jared S.; Clark, Joseph D.; Chandler, Richard B.
2018-01-01
Monitoring vulnerable species is critical for their conservation. Thresholds or tipping points are commonly used to indicate when populations become vulnerable to extinction and to trigger changes in conservation actions. However, quantitative methods to determine such thresholds have not been well explored. The Louisiana black bear (Ursus americanus luteolus) was removed from the list of threatened and endangered species under the U.S. Endangered Species Act in 2016 and our objectives were to determine the most appropriate parameters and thresholds for monitoring and management action. Capture mark recapture (CMR) data from 2006 to 2012 were used to estimate population parameters and variances. We used stochastic population simulations and conditional classification trees to identify demographic rates for monitoring that would be most indicative of heighted extinction risk. We then identified thresholds that would be reliable predictors of population viability. Conditional classification trees indicated that annual apparent survival rates for adult females averaged over 5 years () was the best predictor of population persistence. Specifically, population persistence was estimated to be ≥95% over 100 years when , suggesting that this statistic can be used as threshold to trigger management intervention. Our evaluation produced monitoring protocols that reliably predicted population persistence and was cost-effective. We conclude that population projections and conditional classification trees can be valuable tools for identifying extinction thresholds used in monitoring programs.
Laufenberg, Jared S; Clark, Joseph D; Chandler, Richard B
2018-01-01
Monitoring vulnerable species is critical for their conservation. Thresholds or tipping points are commonly used to indicate when populations become vulnerable to extinction and to trigger changes in conservation actions. However, quantitative methods to determine such thresholds have not been well explored. The Louisiana black bear (Ursus americanus luteolus) was removed from the list of threatened and endangered species under the U.S. Endangered Species Act in 2016 and our objectives were to determine the most appropriate parameters and thresholds for monitoring and management action. Capture mark recapture (CMR) data from 2006 to 2012 were used to estimate population parameters and variances. We used stochastic population simulations and conditional classification trees to identify demographic rates for monitoring that would be most indicative of heighted extinction risk. We then identified thresholds that would be reliable predictors of population viability. Conditional classification trees indicated that annual apparent survival rates for adult females averaged over 5 years ([Formula: see text]) was the best predictor of population persistence. Specifically, population persistence was estimated to be ≥95% over 100 years when [Formula: see text], suggesting that this statistic can be used as threshold to trigger management intervention. Our evaluation produced monitoring protocols that reliably predicted population persistence and was cost-effective. We conclude that population projections and conditional classification trees can be valuable tools for identifying extinction thresholds used in monitoring programs.
Sources, Sinks, and Model Accuracy
Spatial demographic models are a necessary tool for understanding how to manage landscapes sustainably for animal populations. These models, therefore, must offer precise and testable predications about animal population dynamics and how animal demographic parameters respond to ...
Chapter 37: Population Trends of the Marbled Murrelet Projected From Demographic Analyses
Steven B. Beissinger
1995-01-01
A demographic model of the Marbled Murrelet is developed to explore likely population trends and factors influencing them. The model was structured to use field data on juvenile ratios, collected near the end of the breeding season and corrected for date of census, to estimate fecundity. Survivorship was estimated for the murrelet based on comparative analyses of...
James A. Thrailkill; Robert G. Anthony; E. Charles Meslow
1997-01-01
Demographic characteristics of the Northern Spotted Owl (Strix occidentalis caurina) were studied on the Eugene District Bureau of Land Management, central Oregon Coast Ranges from 1989-1995. Survival rates were estimated from capture histories of banded owls using Cormack-Jolly-Seber open population models. We banded 233 owls, including 119 that...
Kokotis, Panagiotis; Katsavos, Serafeim
2015-01-01
The etiology of Bell's palsy (BP), the most common type of dysfunction of the facial nerve, remains unclear despite vigorous research. Data concerning the effects of meteorological factors (MFs) on its appearance are inconclusive. The aim of our study was to examine the demographics of a convenience sample of patients with BP and to determine the effects of several MFs in the recorded number of cases per month (cpm). We retrospectively reviewed 568 files of BP patients and concomitant data of MFs during an 84-month observation period. Information collected included age, gender, diabetic status, number of cpm (months further categorized as winter or summer), mean daily and monthly temperatures and wind speeds and monthly values of wind chill factor (WCF), a measure dependent on both temperature and wind speed. Potential correlations were estimated by univariate analyses (p = 0.05). Demographics were in line with previous research regarding age and diabetic status, but indicative of slight male preponderance. Summer months and mean monthly temperatures showed significant negative correlations with cpm (p = 0.002 and <0.000, respectively) and strong positive correlation with WCF (p < 0.000). MFs can substantially influence the possibility for BP appearance. We propose WCF as a novel, reliable estimator of the overall MF-derived risk. © 2015 S. Karger AG, Basel.
Rudershausen, Paul J.; Buckel, Jeffery A.; Dubreuil, Todd; O'Donnell, Matthew J.; Hightower, Joseph E.; Poland, Steven J.; Letcher, Benjamin H.
2014-01-01
We evaluated the performance of small (12.5 mm long) passive integrated transponder (PIT) tags and custom detection antennas for obtaining fine-scale movement and demographic data of mummichog Fundulus heteroclitus in a salt marsh creek. Apparent survival and detection probability were estimated using a Cormack Jolly Seber (CJS) model fitted to detection data collected by an array of 3 vertical antennas from November 2010 to March 2011 and by a single horizontal antenna from April to August 2011. Movement of mummichogs was monitored during the period when the array of vertical antennas was used. Antenna performance was examined in situ using tags placed in wooden dowels (drones) and in live mummichogs. Of the 44 tagged fish, 42 were resighted over the 9 mo monitoring period. The in situ detection probabilities of the drone and live mummichogs were high (~80-100%) when the ambient water depth was less than ~0.8 m. Upstream and downstream movement of mummichogs was related to hourly water depth and direction of tidal current in a way that maximized time periods over which mummichogs utilized the intertidal vegetated marsh. Apparent survival was lower during periods of colder water temperatures in December 2010 and early January 2011 (median estimate of daily apparent survival = 0.979) than during other periods of the study (median estimate of daily apparent survival = 0.992). During late fall and winter, temperature had a positive effect on the CJS detection probability of a tagged mummichog, likely due to greater fish activity over warmer periods. During the spring and summer, this pattern reversed possibly due to mummichogs having reduced activity during the hottest periods. This study demonstrates the utility of PIT tags and continuously operating autonomous detection systems for tracking fish at fine temporal scales, and improving estimates of demographic parameters in salt marsh creeks that are difficult or impractical to sample with active fishing gear.
Duangchantrasiri, Somphot; Umponjan, Mayuree; Simcharoen, Saksit; Pattanavibool, Anak; Chaiwattana, Soontorn; Maneerat, Sompoch; Kumar, N Samba; Jathanna, Devcharan; Srivathsa, Arjun; Karanth, K Ullas
2016-06-01
Recovering small populations of threatened species is an important global conservation strategy. Monitoring the anticipated recovery, however, often relies on uncertain abundance indices rather than on rigorous demographic estimates. To counter the severe threat from poaching of wild tigers (Panthera tigris), the Government of Thailand established an intensive patrolling system in 2005 to protect and recover its largest source population in Huai Kha Khaeng Wildlife Sanctuary. Concurrently, we assessed the dynamics of this tiger population over the next 8 years with rigorous photographic capture-recapture methods. From 2006 to 2012, we sampled across 624-1026 km(2) with 137-200 camera traps. Cameras deployed for 21,359 trap days yielded photographic records of 90 distinct individuals. We used closed model Bayesian spatial capture-recapture methods to estimate tiger abundances annually. Abundance estimates were integrated with likelihood-based open model analyses to estimate rates of annual and overall rates of survival, recruitment, and changes in abundance. Estimates of demographic parameters fluctuated widely: annual density ranged from 1.25 to 2.01 tigers/100 km(2) , abundance from 35 to 58 tigers, survival from 79.6% to 95.5%, and annual recruitment from 0 to 25 tigers. The number of distinct individuals photographed demonstrates the value of photographic capture-recapture methods for assessments of population dynamics in rare and elusive species that are identifiable from natural markings. Possibly because of poaching pressure, overall tiger densities at Huai Kha Khaeng were 82-90% lower than in ecologically comparable sites in India. However, intensified patrolling after 2006 appeared to reduce poaching and was correlated with marginal improvement in tiger survival and recruitment. Our results suggest that population recovery of low-density tiger populations may be slower than anticipated by current global strategies aimed at doubling the number of wild tigers in a decade. © 2015 Society for Conservation Biology.
Climate change threatens polar bear populations: a stochastic demographic analysis.
Hunter, Christine M; Caswell, Hal; Runge, Michael C; Regehr, Eric V; Amstrup, Steve C; Stirling, Ian
2010-10-01
The polar bear (Ursus maritimus) depends on sea ice for feeding, breeding, and movement. Significant reductions in Arctic sea ice are forecast to continue because of climate warming. We evaluated the impacts of climate change on polar bears in the southern Beaufort Sea by means of a demographic analysis, combining deterministic, stochastic, environment-dependent matrix population models with forecasts of future sea ice conditions from IPCC general circulation models (GCMs). The matrix population models classified individuals by age and breeding status; mothers and dependent cubs were treated as units. Parameter estimates were obtained from a capture-recapture study conducted from 2001 to 2006. Candidate statistical models allowed vital rates to vary with time and as functions of a sea ice covariate. Model averaging was used to produce the vital rate estimates, and a parametric bootstrap procedure was used to quantify model selection and parameter estimation uncertainty. Deterministic models projected population growth in years with more extensive ice coverage (2001-2003) and population decline in years with less ice coverage (2004-2005). LTRE (life table response experiment) analysis showed that the reduction in lambda in years with low sea ice was due primarily to reduced adult female survival, and secondarily to reduced breeding. A stochastic model with two environmental states, good and poor sea ice conditions, projected a declining stochastic growth rate, log lambdas, as the frequency of poor ice years increased. The observed frequency of poor ice years since 1979 would imply log lambdas approximately - 0.01, which agrees with available (albeit crude) observations of population size. The stochastic model was linked to a set of 10 GCMs compiled by the IPCC; the models were chosen for their ability to reproduce historical observations of sea ice and were forced with "business as usual" (A1B) greenhouse gas emissions. The resulting stochastic population projections showed drastic declines in the polar bear population by the end of the 21st century. These projections were instrumental in the decision to list the polar bear as a threatened species under the U.S. Endangered Species Act.
Status and trends in demography of northern spotted owls, 1985-2003
Anthony, R.G.; Forsman, E.D.; Franklin, A.B.; Anderson, D.R.; Burnham, K.P.; White, Gary C.; Schwarz, C.J.; Nichols, J.D.; Hines, J.E.; Olson, G.S.; Ackers, S.H.; Andrews, L.S.; Biswell, B.L.; Carlson, P.C.; Diller, L.V.; Dugger, K.M.; Fehring, K.E.; Fleming, T.L.; Gerhardt, R.P.; Gremel, S.A.; Gutierrez, R.J.; Happe, P.J.; Herter, D.R.; Higley, J.M.; Horn, R.B.; Irwin, L.L.; Loschl, P.J.; Reid, J.A.; Sovern, S.G.; Krausman, P.R.
2006-01-01
We analyzed demographic data from northern spotted owls (Strix occidentalis caurina) from 14 study areas in Washington, Oregon, and California for 1985-2003. The purpose of our analyses was to provide an assessment of the status and trends of northern spotted owl populations throughout most of their geographic range. The 14 study areas made up approximately 12% of the range of the subspecies and included federal, tribal, private, and mixed federal and private lands. The study areas also included all the major forest types that the subspecies inhabits. The analyses followed rigorous protocols that were developed a priori and were the result of extensive discussions and consensus among the authors. Our primary objectives were to estimate fecundity, apparent survival (??), and annual rate of population change (??) and to determine if there were any temporal trends in these population parameters. In addition to analyses of data from individual study areas, we conducted 2 meta-analyses on each demographic parameter. One meta-analysis was conducted on all 14 areas, and the other was restricted to the 8 areas that constituted the Effectiveness Monitoring Plan for northern spotted owls under the Northwest Forest Plan. The average number of years of reproductive data per study area was 14 (range = 5-19), and the average number of recapture occasions per study area was 13 (range = 4-18). Only 1 study area had 1 year old. We found no differences in apparent survival rates between sexes except for 1 area (Marin), which had only 6 years of data. Estimates of apparent survival from individual study areas indicated that there were differences among age classes with adults generally having higher survival than 1- and 2-year-olds. Apparent survival rates ranged from 0.750 (SE=0.026) to 0.886 (SE=0.010) for adults, 0.626 (SE=0.073) to 0.886 (SE=0.010) for 2-year-olds, and 0.415 (SE=0.111) to 0.860 (SE=0.017) for 1-year-olds. These estimates were comparable to survival rates from previous studies on the subspecies. We found evidence for negative time trends in survival rate
Climate change threatens polar bear populations: A stochastic demographic analysis
Hunter, C.M.; Caswell, H.; Runge, M.C.; Regehr, E.V.; Amstrup, Steven C.; Stirling, I.
2010-01-01
The polar bear (Ursus maritimus) depends on sea ice for feeding, breeding, and movement. Significant reductions in Arctic sea ice are forecast to continue because of climate warming. We evaluated the impacts of climate change on polar bears in the southern Beaufort Sea by means of a demographic analysis, combining deterministic, stochastic, environment-dependent matrix population models with forecasts of future sea ice conditions from IPCC general circulation models (GCMs). The matrix population models classified individuals by age and breeding status; mothers and dependent cubs were treated as units. Parameter estimates were obtained from a capture-recapture study conducted from 2001 to 2006. Candidate statistical models allowed vital rates to vary with time and as functions of a sea ice covariate. Model averaging was used to produce the vital rate estimates, and a parametric bootstrap procedure was used to quantify model selection and parameter estimation uncertainty. Deterministic models projected population growth in years with more extensive ice coverage (2001-2003) and population decline in years with less ice coverage (2004-2005). LTRE (life table response experiment) analysis showed that the reduction in ?? in years with low sea ice was due primarily to reduced adult female survival, and secondarily to reduced breeding. A stochastic model with two environmental states, good and poor sea ice conditions, projected a declining stochastic growth rate, log ??s, as the frequency of poor ice years increased. The observed frequency of poor ice years since 1979 would imply log ??s ' - 0.01, which agrees with available (albeit crude) observations of population size. The stochastic model was linked to a set of 10 GCMs compiled by the IPCC; the models were chosen for their ability to reproduce historical observations of sea ice and were forced with "business as usual" (A1B) greenhouse gas emissions. The resulting stochastic population projections showed drastic declines in the polar bear population by the end of the 21st century. These projections were instrumental in the decision to list the polar bear as a threatened species under the U.S. Endangered Species Act. ?? 2010 by the Ecological Society of America.
Garrick, Ryan C; Kajdacsi, Brittney; Russello, Michael A; Benavides, Edgar; Hyseni, Chaz; Gibbs, James P; Tapia, Washington; Caccone, Adalgisa
2015-01-01
Long-term population history can influence the genetic effects of recent bottlenecks. Therefore, for threatened or endangered species, an understanding of the past is relevant when formulating conservation strategies. Levels of variation at neutral markers have been useful for estimating local effective population sizes (Ne) and inferring whether population sizes increased or decreased over time. Furthermore, analyses of genotypic, allelic frequency, and phylogenetic information can potentially be used to separate historical from recent demographic changes. For 15 populations of Galápagos giant tortoises (Chelonoidis sp.), we used 12 microsatellite loci and DNA sequences from the mitochondrial control region and a nuclear intron, to reconstruct demographic history on shallow (past ∽100 generations, ∽2500 years) and deep (pre-Holocene, >10 thousand years ago) timescales. At the deep timescale, three populations showed strong signals of growth, but with different magnitudes and timing, indicating different underlying causes. Furthermore, estimated historical Ne of populations across the archipelago showed no correlation with island age or size, underscoring the complexity of predicting demographic history a priori. At the shallow timescale, all populations carried some signature of a genetic bottleneck, and for 12 populations, point estimates of contemporary Ne were very small (i.e., < 50). On the basis of the comparison of these genetic estimates with published census size data, Ne generally represented ∽0.16 of the census size. However, the variance in this ratio across populations was considerable. Overall, our data suggest that idiosyncratic and geographically localized forces shaped the demographic history of tortoise populations. Furthermore, from a conservation perspective, the separation of demographic events occurring on shallow versus deep timescales permits the identification of naturally rare versus newly rare populations; this distinction should facilitate prioritization of management action. PMID:25691990
The Threshold Bias Model: A Mathematical Model for the Nomothetic Approach of Suicide
Folly, Walter Sydney Dutra
2011-01-01
Background Comparative and predictive analyses of suicide data from different countries are difficult to perform due to varying approaches and the lack of comparative parameters. Methodology/Principal Findings A simple model (the Threshold Bias Model) was tested for comparative and predictive analyses of suicide rates by age. The model comprises of a six parameter distribution that was applied to the USA suicide rates by age for the years 2001 and 2002. Posteriorly, linear extrapolations are performed of the parameter values previously obtained for these years in order to estimate the values corresponding to the year 2003. The calculated distributions agreed reasonably well with the aggregate data. The model was also used to determine the age above which suicide rates become statistically observable in USA, Brazil and Sri Lanka. Conclusions/Significance The Threshold Bias Model has considerable potential applications in demographic studies of suicide. Moreover, since the model can be used to predict the evolution of suicide rates based on information extracted from past data, it will be of great interest to suicidologists and other researchers in the field of mental health. PMID:21909431
The threshold bias model: a mathematical model for the nomothetic approach of suicide.
Folly, Walter Sydney Dutra
2011-01-01
Comparative and predictive analyses of suicide data from different countries are difficult to perform due to varying approaches and the lack of comparative parameters. A simple model (the Threshold Bias Model) was tested for comparative and predictive analyses of suicide rates by age. The model comprises of a six parameter distribution that was applied to the USA suicide rates by age for the years 2001 and 2002. Posteriorly, linear extrapolations are performed of the parameter values previously obtained for these years in order to estimate the values corresponding to the year 2003. The calculated distributions agreed reasonably well with the aggregate data. The model was also used to determine the age above which suicide rates become statistically observable in USA, Brazil and Sri Lanka. The Threshold Bias Model has considerable potential applications in demographic studies of suicide. Moreover, since the model can be used to predict the evolution of suicide rates based on information extracted from past data, it will be of great interest to suicidologists and other researchers in the field of mental health.
ERIC Educational Resources Information Center
Population Reference Bureau, Inc., Washington, DC.
This poster-size data sheet presents population estimates and selected demographic indicators for the nation's 281 metropolitan areas. These areas are divided into 261 Metropolitan Statistical Areas (MSAs) and 20 Consolidated Metropolitan Statistical Areas (CMSAs), reporting units which replace the Standard Metropolitan Statistical Areas (SMSAs)…
Development of the PCAD Model to Assess Biological Significance of Acoustic Disturbance
2013-09-30
substantial pre-existing knowledge of foraging patterns , life-history schedules, and demographics. Therefore, it is essential to use well-studied species to...transiting areas of the post-molt migration . Using a bootstrapping approach, we simulated thousands of disturbances to achieve realistic error estimates...resident population). Given seasonal differences in calving, causes of mortality, and movement patterns , we will estimate demographic rates on a
Fixed points and limit cycles in the population dynamics of lysogenic viruses and their hosts
NASA Astrophysics Data System (ADS)
Wang, Zhenyu; Goldenfeld, Nigel
2010-07-01
Starting with stochastic rate equations for the fundamental interactions between microbes and their viruses, we derive a mean-field theory for the population dynamics of microbe-virus systems, including the effects of lysogeny. In the absence of lysogeny, our model is a generalization of that proposed phenomenologically by Weitz and Dushoff. In the presence of lysogeny, we analyze the possible states of the system, identifying a limit cycle, which we interpret physically. To test the robustness of our mean-field calculations to demographic fluctuations, we have compared our results with stochastic simulations using the Gillespie algorithm. Finally, we estimate the range of parameters that delineate the various steady states of our model.
Odioso, L L; Gibb, R D; Gerlach, R W
2000-01-01
A cross-sectional survey across broad age ranges was conducted to evaluate demographic, behavioral, and treatment parameters that impact tooth color and its perception. The sample included 180 US adults and teenagers, with a comparable representation of males and females in 6 different age strata, ranging from 13 to 64 years. Tooth color (L*a*b*) was measured on the maxillary central incisors using a spectrophotometer, and first-person satisfaction with tooth color was assessed using a five-point qualitative scale. Demographic, behavioral, and oral care parameters were modeled using multiple regression analysis. After adjusting for other explanatory variables, age, gender, coffee/tea consumption, and dental care all significantly affected yellowing (b*) and brightness (L*). Dental-visit frequency was the only factor that significantly predicted self-satisfaction with tooth color, explaining just 3% of the overall variability. First-person dissatisfaction with tooth color was common and found in most demographic and behavioral cohorts. Although age contributed to objectively measured tooth discoloration, personal satisfaction with tooth color was age-independent. These results suggest that the need or demand for esthetic dentistry may be broad-based and transcend stereotypical perceptions.
2012-01-01
Background Understanding demographic histories, such as divergence time, patterns of gene flow, and population size changes, in ecologically diverging lineages provide implications for the process and maintenance of population differentiation by ecological adaptation. This study addressed the demographic histories in two independently derived lineages of flood-resistant riparian plants and their non-riparian relatives [Ainsliaea linearis (riparian) and A. apiculata (non-riparian); A. oblonga (riparian) and A. macroclinidioides (non-riparian); Asteraceae] using an isolation-with-migration (IM) model based on variation at 10 nuclear DNA loci. Results The highest posterior probabilities of the divergence time parameters were estimated to be ca. 25,000 years ago for A. linearis and A. apiculata and ca. 9000 years ago for A. oblonga and A. macroclinidioides, although the confidence intervals of the parameters had broad ranges. The likelihood ratio tests detected evidence of historical gene flow between both riparian/non-riparian species pairs. The riparian populations showed lower levels of genetic diversity and a significant reduction in effective population sizes compared to the non-riparian populations and their ancestral populations. Conclusions This study showed the recent origins of flood-resistant riparian plants, which are remarkable examples of plant ecological adaptation. The recent divergence and genetic signatures of historical gene flow among riparian/non-riparian species implied that they underwent morphological and ecological differentiation within short evolutionary timescales and have maintained their species boundaries in the face of gene flow. Comparative analyses of adaptive divergence in two sets of riparian/non-riparian lineages suggested that strong natural selection by flooding had frequently reduced the genetic diversity and size of riparian populations through genetic drift, possibly leading to fixation of adaptive traits in riparian populations. The two sets of riparian/non-riparian lineages showed contrasting patterns of gene flow and genetic differentiation, implying that each lineage showed different degrees of reproductive isolation and that they had experienced unique evolutionary and demographic histories in the process of adaptive divergence. PMID:23273287
Robotic single port cholecystectomy: current data and future perspectives.
Angelou, Anastasios; Skarmoutsos, Athanasios; Margonis, Georgios A; Moris, Demetrios; Tsigris, Christos; Pikoulis, Emmanouil
2017-04-01
Minimally invasive techniques are used more and more frequently. Since conventional laparoscopic approach has been the gold standard, surgeons in their effort to further reduce the invasiveness of conventional laparoscopic cholecystectomy have adopted Single Incision approach. The widespread adoption of robotics has led to the inevitable hybridization of robotic technology with laparoendoscopic single-site surgery (LESS). As a result, employment of the da Vinci surgical system may allow greater surgical maneuverability, improving ergonomics. A review of the English literature was conducted to evaluate all robotic single port cholecystectomy performed till today. Demographic data, operative parameters, postoperative outcomes and materials used for the operation were collected and assessed. A total of 12 studies, including 501 patients were analyzed. Demographics and clinical characteristics of the patients was heterogeneous, but in most studies a mean BMI <30 was recorded. Intraoperative metrics like operative time, estimated blood loss and conversion rate were comparable with those in multiport conventional laparoscopy. Robotic single port cholecystectomy is a safe and feasible alternative to conventional multiport laparoscopic or manual robotic approach. However, current data do not suggest a superiority of robotic SILC over other established methods.
Johnson, Leigh F; Geffen, Nathan
2016-03-01
Different models of sexually transmitted infections (STIs) can yield substantially different conclusions about STI epidemiology, and it is important to understand how and why models differ. Frequency-dependent models make the simplifying assumption that STI incidence is proportional to STI prevalence in the population, whereas network models calculate STI incidence more realistically by classifying individuals according to their partners' STI status. We assessed a deterministic frequency-dependent model approximation to a microsimulation network model of STIs in South Africa. Sexual behavior and demographic parameters were identical in the 2 models. Six STIs were simulated using each model: HIV, herpes, syphilis, gonorrhea, chlamydia, and trichomoniasis. For all 6 STIs, the frequency-dependent model estimated a higher STI prevalence than the network model, with the difference between the 2 models being relatively large for the curable STIs. When the 2 models were fitted to the same STI prevalence data, the best-fitting parameters differed substantially between models, with the frequency-dependent model suggesting more immunity and lower transmission probabilities. The fitted frequency-dependent model estimated that the effects of a hypothetical elimination of concurrent partnerships and a reduction in commercial sex were both smaller than estimated by the fitted network model, whereas the latter model estimated a smaller impact of a reduction in unprotected sex in spousal relationships. The frequency-dependent assumption is problematic when modeling short-term STIs. Frequency-dependent models tend to underestimate the importance of high-risk groups in sustaining STI epidemics, while overestimating the importance of long-term partnerships and low-risk groups.
Pearson, Kristen Nicole; Kendall, William L.; Winkelman, Dana L.; Persons, William R.
2015-01-01
Our findings reveal evidence for skipped spawning in a potamodromous cyprinid, humpback chub (HBC; Gila cypha ). Using closed robust design mark-recapture models, we found, on average, spawning HBC transition to the skipped spawning state () with a probability of 0.45 (95% CRI (i.e. credible interval): 0.10, 0.80) and skipped spawners remain in the skipped spawning state () with a probability of 0.60 (95% CRI: 0.26, 0.83), yielding an average spawning cycle of every 2.12 years, conditional on survival. As a result, migratory skipped spawners are unavailable for detection during annual sampling events. If availability is unaccounted for, survival and detection probability estimates will be biased. Therefore, we estimated annual adult survival probability (S), while accounting for skipped spawning, and found S remained reasonably stable throughout the study period, with an average of 0.75 ((95% CRI: 0.66, 0.82), process varianceσ2 = 0.005), while skipped spawning probability was highly dynamic (σ2 = 0.306). By improving understanding of HBC spawning strategies, conservation decisions can be based on less biased estimates of survival and a more informed population model structure.
Generating Accurate Urban Area Maps from Nighttime Satellite (DMSP/OLS) Data
NASA Technical Reports Server (NTRS)
Imhoff, Marc; Lawrence, William; Elvidge, Christopher
2000-01-01
There has been an increasing interest by the international research community to use the nighttime acquired "city-lights" data sets collected by the US Defense Meteorological Satellite Program's Operational Linescan system to study issues relative to urbanization. Many researchers are interested in using these data to estimate human demographic parameters over large areas and then characterize the interactions between urban development , natural ecosystems, and other aspects of the human enterprise. Many of these attempts rely on an ability to accurately identify urbanized area. However, beyond the simple determination of the loci of human activity, using these data to generate accurate estimates of urbanized area can be problematic. Sensor blooming and registration error can cause large overestimates of urban land based on a simple measure of lit area from the raw data. We discuss these issues, show results of an attempt to do a historical urban growth model in Egypt, and then describe a few basic processing techniques that use geo-spatial analysis to threshold the DMSP data to accurately estimate urbanized areas. Algorithm results are shown for the United States and an application to use the data to estimate the impact of urban sprawl on sustainable agriculture in the US and China is described.
Population dynamics of Greater Scaup breeding on the Yukon-Kuskokwim Delta, Alaska
Flint, Paul L.; Grand, J. Barry; Fondell, Thomas F.; Morse, Julie A.
2006-01-01
Using a stochastic model, we estimated that, on average, breeding females produced 0.57 young females/nesting season. We combined this estimate of productivity with our annual estimates of adult survival and an assumed population growth rate of 1.0, then solved for an estimate of first-year survival (0.40). Under these conditions the predicted stable age distribution of breeding females (i.e., the nesting population) was 15.1% 1-year-old, 4.1% 2-year-old first-time breeders, and 80.8% 2-year-old and older, experienced breeders. We subjected this stochastic model to perturbation analyses to examine the relative effects of demographic parameters on k. The relative effects of productivity and adult survival on the population growth rate were 0.26 and 0.72, respectively. Thus, compared to productivity, proportionally equivalent changes in annual survival would have 2.8 times the effect on k. However, when we examined annual variation in predicted population size using standardized regression coefficients, productivity explained twice as much variation as annual survival. Thus, management actions focused on changes in survival or productivity have the ability to influence population size; however, substantially larger changes in productivity are required to influence population trends.
Muñoz, David J.; Miller, David A.W.; Sutherland, Chris; Grant, Evan H. Campbell
2016-01-01
The cryptic behavior and ecology of herpetofauna make estimating the impacts of environmental change on demography difficult; yet, the ability to measure demographic relationships is essential for elucidating mechanisms leading to the population declines reported for herpetofauna worldwide. Recently developed spatial capture–recapture (SCR) methods are well suited to standard herpetofauna monitoring approaches. Individually identifying animals and their locations allows accurate estimates of population densities and survival. Spatial capture–recapture methods also allow estimation of parameters describing space-use and movement, which generally are expensive or difficult to obtain using other methods. In this paper, we discuss the basic components of SCR models, the available software for conducting analyses, and the experimental designs based on common herpetological survey methods. We then apply SCR models to Red-backed Salamander (Plethodon cinereus), to determine differences in density, survival, dispersal, and space-use between adult male and female salamanders. By highlighting the capabilities of SCR, and its advantages compared to traditional methods, we hope to give herpetologists the resource they need to apply SCR in their own systems.
Developing a rich definition of the person/residence to support ...
Characterizing interindividual variation in combined chemical exposures from the use of consumer products is a challenge because of the complexity of these exposures. There are many products commercially available and individuals use combinations of products dictated by their specific needs. Product use varies with an individual’s demographics (e.g., age, gender, ethnicity, family structure, and type of residence). Exposures also occur as a result of other individuals using products in the home (e.g., painting a room exposes all individuals in a home and washing a child exposes both child and adult). Finally, characterizing applied and internal doses requires data on the physiology and behaviors of the individual. The U.S. EPA is developing probabilistic methods of modeling variation in exposure-relevant characteristics of individuals, their residences, and their families. The goal of this effort is the generation of synthetic populations whose characteristics can be used to predict chemical doses from the use of consumer products. A database of population demographics is created by linking data from the U.S. Census with data from U.S. housing surveys. Survey data are linked by matching records based on similarities in the characteristics correlated with the parameters of interest. The demographics are also combined with rules controlling product usage to refine the estimates of the products that individuals in a household may use (e.g., only adults with a you
Accurate age estimation in small-scale societies
Smith, Daniel; Gerbault, Pascale; Dyble, Mark; Migliano, Andrea Bamberg; Thomas, Mark G.
2017-01-01
Precise estimation of age is essential in evolutionary anthropology, especially to infer population age structures and understand the evolution of human life history diversity. However, in small-scale societies, such as hunter-gatherer populations, time is often not referred to in calendar years, and accurate age estimation remains a challenge. We address this issue by proposing a Bayesian approach that accounts for age uncertainty inherent to fieldwork data. We developed a Gibbs sampling Markov chain Monte Carlo algorithm that produces posterior distributions of ages for each individual, based on a ranking order of individuals from youngest to oldest and age ranges for each individual. We first validate our method on 65 Agta foragers from the Philippines with known ages, and show that our method generates age estimations that are superior to previously published regression-based approaches. We then use data on 587 Agta collected during recent fieldwork to demonstrate how multiple partial age ranks coming from multiple camps of hunter-gatherers can be integrated. Finally, we exemplify how the distributions generated by our method can be used to estimate important demographic parameters in small-scale societies: here, age-specific fertility patterns. Our flexible Bayesian approach will be especially useful to improve cross-cultural life history datasets for small-scale societies for which reliable age records are difficult to acquire. PMID:28696282
Accurate age estimation in small-scale societies.
Diekmann, Yoan; Smith, Daniel; Gerbault, Pascale; Dyble, Mark; Page, Abigail E; Chaudhary, Nikhil; Migliano, Andrea Bamberg; Thomas, Mark G
2017-08-01
Precise estimation of age is essential in evolutionary anthropology, especially to infer population age structures and understand the evolution of human life history diversity. However, in small-scale societies, such as hunter-gatherer populations, time is often not referred to in calendar years, and accurate age estimation remains a challenge. We address this issue by proposing a Bayesian approach that accounts for age uncertainty inherent to fieldwork data. We developed a Gibbs sampling Markov chain Monte Carlo algorithm that produces posterior distributions of ages for each individual, based on a ranking order of individuals from youngest to oldest and age ranges for each individual. We first validate our method on 65 Agta foragers from the Philippines with known ages, and show that our method generates age estimations that are superior to previously published regression-based approaches. We then use data on 587 Agta collected during recent fieldwork to demonstrate how multiple partial age ranks coming from multiple camps of hunter-gatherers can be integrated. Finally, we exemplify how the distributions generated by our method can be used to estimate important demographic parameters in small-scale societies: here, age-specific fertility patterns. Our flexible Bayesian approach will be especially useful to improve cross-cultural life history datasets for small-scale societies for which reliable age records are difficult to acquire.
Mining geographic variations of Plasmodium vivax for active surveillance: a case study in China.
Shi, Benyun; Tan, Qi; Zhou, Xiao-Nong; Liu, Jiming
2015-05-27
Geographic variations of an infectious disease characterize the spatial differentiation of disease incidences caused by various impact factors, such as environmental, demographic, and socioeconomic factors. Some factors may directly determine the force of infection of the disease (namely, explicit factors), while many other factors may indirectly affect the number of disease incidences via certain unmeasurable processes (namely, implicit factors). In this study, the impact of heterogeneous factors on geographic variations of Plasmodium vivax incidences is systematically investigate in Tengchong, Yunnan province, China. A space-time model that resembles a P. vivax transmission model and a hidden time-dependent process, is presented by taking into consideration both explicit and implicit factors. Specifically, the transmission model is built upon relevant demographic, environmental, and biophysical factors to describe the local infections of P. vivax. While the hidden time-dependent process is assessed by several socioeconomic factors to account for the imported cases of P. vivax. To quantitatively assess the impact of heterogeneous factors on geographic variations of P. vivax infections, a Markov chain Monte Carlo (MCMC) simulation method is developed to estimate the model parameters by fitting the space-time model to the reported spatial-temporal disease incidences. Since there is no ground-truth information available, the performance of the MCMC method is first evaluated against a synthetic dataset. The results show that the model parameters can be well estimated using the proposed MCMC method. Then, the proposed model is applied to investigate the geographic variations of P. vivax incidences among all 18 towns in Tengchong, Yunnan province, China. Based on the geographic variations, the 18 towns can be further classify into five groups with similar socioeconomic causality for P. vivax incidences. Although this study focuses mainly on the transmission of P. vivax, the proposed space-time model is general and can readily be extended to investigate geographic variations of other diseases. Practically, such a computational model will offer new insights into active surveillance and strategic planning for disease surveillance and control.
Schumacher, Carsten; Eismann, Hendrik; Sieg, Lion; Friedrich, Lars; Scheinichen, Dirk; Vondran, Florian W R; Johanning, Kai
2018-01-01
Liver transplantation is a complex intervention, and early anticipation of personnel and logistic requirements is of great importance. Early identification of high-risk patients could prove useful. We therefore evaluated prognostic values of recipient parameters commonly available in the early preoperative stage regarding postoperative 30- and 90-day outcomes and intraoperative transfusion requirements in liver transplantation. All adult patients undergoing first liver transplantation at Hannover Medical School between January 2005 and December 2010 were included in this retrospective study. Demographic, clinical, and laboratory data as well as clinical courses were recorded. Prognostic values regarding 30- and 90-day outcomes were evaluated by uni- and multivariate statistical tests. Identified risk parameters were used to calculate risk scores. There were 426 patients (40.4% female) included with a mean age of 48.6 (11.9) years. Absolute 30-day mortality rate was 9.9%, and absolute 90-day mortality rate was 13.4%. Preoperative leukocyte count >5200/μL, platelet count <91 000/μL, and creatinine values ≥77 μmol/L were relevant risk factors for both observation periods ( P < .05, respectively). A score based on these factors significantly differentiated between groups of varying postoperative outcomes and intraoperative transfusion requirements ( P < .05, respectively). A score based on preoperative creatinine, leukocyte, and platelet values allowed early estimation of postoperative 30- and 90-day outcomes and intraoperative transfusion requirements in liver transplantation. Results might help to improve timely logistic and personal strategies.
Impact of demographic and clinical parameters on video capsule transit time.
Niv, Eva; Pinchasovich, Hadassa; Yanai, Henit
2016-10-01
Small bowel (SB) capsule endoscopy (CE) studies provide data on both gastric and SB transit times (GTT and SBTT, respectively). This study aimed to evaluate the influence of demographic and clinical parameters on the GTT and SBTT. Transit times for two generations of capsules (Pillcam SB2 and SB3) were also compared. Consecutive adult patients undergoing CE were included. GTT, SBTT, and cecum arrival rates were calculated and correlated to demographics and clinical characteristics. A total of 332 CE studies were analyzed. Neither GTT nor SBTT were impacted by age or sex. SBTT was prolonged in newly diagnosed Crohn's disease (CD) patients compared with all other patients (303.1±90.3 vs. 243.6±83.6 min, P=0.02 for SB2, 267.8±63 vs. 228.6±72.3, P=0.01 for SB3, respectively). Moreover, CD patients had higher incomplete study rates compared with patients with all other diagnoses (29.4 vs. 7.3%, respectively, P=0.0116) in the SB2 subgroup. Higher cecum arrival rates were achieved by the SB3 capsule compared with SB2 (97 vs. 91%, P=0.04). Patients with prolonged gastric time or patients with incomplete studies had similar demographic and clinical characteristics as others. Age and sex apparently do not influence intestinal kinetics. Newly diagnosed CD patients have relatively prolonged SBTTs. Demographic and clinical parameters cannot predict prolonged GTT or cecum nonarrival.
Predicting Subnational Ebola Virus Disease Epidemic Dynamics from Sociodemographic Indicators
Valeri, Linda; Patterson-Lomba, Oscar; Gurmu, Yared; Ablorh, Akweley; Bobb, Jennifer; Townes, F. William; Harling, Guy
2016-01-01
Background The recent Ebola virus disease (EVD) outbreak in West Africa has spread wider than any previous human EVD epidemic. While individual-level risk factors that contribute to the spread of EVD have been studied, the population-level attributes of subnational regions associated with outbreak severity have not yet been considered. Methods To investigate the area-level predictors of EVD dynamics, we integrated time series data on cumulative reported cases of EVD from the World Health Organization and covariate data from the Demographic and Health Surveys. We first estimated the early growth rates of epidemics in each second-level administrative district (ADM2) in Guinea, Sierra Leone and Liberia using exponential, logistic and polynomial growth models. We then evaluated how these growth rates, as well as epidemic size within ADM2s, were ecologically associated with several demographic and socio-economic characteristics of the ADM2, using bivariate correlations and multivariable regression models. Results The polynomial growth model appeared to best fit the ADM2 epidemic curves, displaying the lowest residual standard error. Each outcome was associated with various regional characteristics in bivariate models, however in stepwise multivariable models only mean education levels were consistently associated with a worse local epidemic. Discussion By combining two common methods—estimation of epidemic parameters using mathematical models, and estimation of associations using ecological regression models—we identified some factors predicting rapid and severe EVD epidemics in West African subnational regions. While care should be taken interpreting such results as anything more than correlational, we suggest that our approach of using data sources that were publicly available in advance of the epidemic or in real-time provides an analytic framework that may assist countries in understanding the dynamics of future outbreaks as they occur. PMID:27732614
Katrínardóttir, Borgný; Alves, José A; Sigurjónsdóttir, Hrefna; Hersteinsson, Páll; Gunnarsson, Tómas G
2015-01-01
Distinct preference of species for habitats is most often driven by long term differences in demographic rates between habitats. Estimating variation in those rates is key for developing successful conservation strategies. Stochastic events can interact with underlying variation in habitat quality in regulating demography but the opportunities to explore such interactions are rare. Whimbrels in Iceland show a strong preference for sparsely vegetated riverplains. Such habitats in Iceland face various threats, e.g., climate change, river regulation and spread of alien plant species. In this study we compared demographic parameters of breeding Whimbrels between riverplains and other habitats before, during and after volcanic eruption events to estimate the importance of the habitats for the species and the effect of ash deposit on breeding success. We found that an estimated minimum of 23% of the Icelandic population of Whimbrels and c. 10% of the world population of the species breed in riverplain habitats in Iceland. Whimbrels bred consistently at much higher densities in riverplain habitats than in other habitats and riverplains also had higher densities of pairs with fledglings although the proportion of successful breeders was similar between habitats. Predation by livestock may have had a considerable negative effect on breeding success on our study sites. Breeding was negatively affected by the volcanic activity, probably through the effects of ash on the invertebrate food supply, with breeding success being gradually worse closer to the eruption. Breeding success was equally affected by volcanism across habitats which differed in underlying habitat quality. This study gives an example of how populations can be regulated by factors which operate at different spatial scales, such as local variation in habitat quality and stochastic events which impact larger areas.
Leveraging Distant Relatedness to Quantify Human Mutation and Gene-Conversion Rates
Palamara, Pier Francesco; Francioli, Laurent C.; Wilton, Peter R.; Genovese, Giulio; Gusev, Alexander; Finucane, Hilary K.; Sankararaman, Sriram; Sunyaev, Shamil R.; de Bakker, Paul I.W.; Wakeley, John; Pe’er, Itsik; Price, Alkes L.
2015-01-01
The rate at which human genomes mutate is a central biological parameter that has many implications for our ability to understand demographic and evolutionary phenomena. We present a method for inferring mutation and gene-conversion rates by using the number of sequence differences observed in identical-by-descent (IBD) segments together with a reconstructed model of recent population-size history. This approach is robust to, and can quantify, the presence of substantial genotyping error, as validated in coalescent simulations. We applied the method to 498 trio-phased sequenced Dutch individuals and inferred a point mutation rate of 1.66 × 10−8 per base per generation and a rate of 1.26 × 10−9 for <20 bp indels. By quantifying how estimates varied as a function of allele frequency, we inferred the probability that a site is involved in non-crossover gene conversion as 5.99 × 10−6. We found that recombination does not have observable mutagenic effects after gene conversion is accounted for and that local gene-conversion rates reflect recombination rates. We detected a strong enrichment of recent deleterious variation among mismatching variants found within IBD regions and observed summary statistics of local sharing of IBD segments to closely match previously proposed metrics of background selection; however, we found no significant effects of selection on our mutation-rate estimates. We detected no evidence of strong variation of mutation rates in a number of genomic annotations obtained from several recent studies. Our analysis suggests that a mutation-rate estimate higher than that reported by recent pedigree-based studies should be adopted in the context of DNA-based demographic reconstruction. PMID:26581902
Estimating survival and breeding probability for pond-breeding amphibians: a modified robust design
Bailey, L.L.; Kendall, W.L.; Church, D.R.; Wilbur, H.M.
2004-01-01
Many studies of pond-breeding amphibians involve sampling individuals during migration to and from breeding habitats. Interpreting population processes and dynamics from these studies is difficult because (1) only a proportion of the population is observable each season, while an unknown proportion remains unobservable (e.g., non-breeding adults) and (2) not all observable animals are captured. Imperfect capture probability can be easily accommodated in capture?recapture models, but temporary transitions between observable and unobservable states, often referred to as temporary emigration, is known to cause problems in both open- and closed-population models. We develop a multistate mark?recapture (MSMR) model, using an open-robust design that permits one entry and one exit from the study area per season. Our method extends previous temporary emigration models (MSMR with an unobservable state) in two ways. First, we relax the assumption of demographic closure (no mortality) between consecutive (secondary) samples, allowing estimation of within-pond survival. Also, we add the flexibility to express survival probability of unobservable individuals (e.g., ?non-breeders?) as a function of the survival probability of observable animals while in the same, terrestrial habitat. This allows for potentially different annual survival probabilities for observable and unobservable animals. We apply our model to a relictual population of eastern tiger salamanders (Ambystoma tigrinum tigrinum). Despite small sample sizes, demographic parameters were estimated with reasonable precision. We tested several a priori biological hypotheses and found evidence for seasonal differences in pond survival. Our methods could be applied to a variety of pond-breeding species and other taxa where individuals are captured entering or exiting a common area (e.g., spawning or roosting area, hibernacula).
Abadi, Fitsum; Barbraud, Christophe; Gimenez, Olivier
2017-03-01
Early-life demographic traits are poorly known, impeding our understanding of population processes and sensitivity to climate change. Survival of immature individuals is a critical component of population dynamics and recruitment in particular. However, obtaining reliable estimates of juvenile survival (i.e., from independence to first year) remains challenging, as immatures are often difficult to observe and to monitor individually in the field. This is particularly acute for seabirds, in which juveniles stay at sea and remain undetectable for several years. In this work, we developed a Bayesian integrated population model to estimate the juvenile survival of emperor penguins (Aptenodytes forsteri), and other demographic parameters including adult survival and fecundity of the species. Using this statistical method, we simultaneously analyzed capture-recapture data of adults, the annual number of breeding females, and the number of fledglings of emperor penguins collected at Dumont d'Urville, Antarctica, for the period 1971-1998. We also assessed how climate covariates known to affect the species foraging habitats and prey [southern annular mode (SAM), sea ice concentration (SIC)] affect juvenile survival. Our analyses revealed that there was a strong evidence for the positive effect of SAM during the rearing period (SAMR) on juvenile survival. Our findings suggest that this large-scale climate index affects juvenile emperor penguins body condition and survival through its influence on wind patterns, fast ice extent, and distance to open water. Estimating the influence of environmental covariates on juvenile survival is of major importance to understand the impacts of climate variability and change on the population dynamics of emperor penguins and seabirds in general and to make robust predictions on the impact of climate change on marine predators. © 2016 John Wiley & Sons Ltd.
Waples, Robin S; Scribner, Kim; Moore, Jennifer; Draheim, Hope; Etter, Dwayne; Boersen, Mark
2018-04-14
The idealized concept of a population is integral to ecology, evolutionary biology, and natural resource management. To make analyses tractable, most models adopt simplifying assumptions, which almost inevitably are violated by real species in nature. Here we focus on both demographic and genetic estimates of effective population size per generation (Ne), the effective number of breeders per year (Nb), and Wright's neighborhood size (NS) for black bears (Ursus americanus) that are continuously distributed in the northern lower peninsula of Michigan, USA. We illustrate practical application of recently-developed methods to account for violations of two common, simplifying assumptions about populations: 1) reproduction occurs in discrete generations, and 2) mating occurs randomly among all individuals. We use a 9-year harvest dataset of >3300 individuals, together with genetic determination of 221 parent-offspring pairs, to estimate male and female vital rates, including age-specific survival, age-specific fecundity, and age-specific variance in fecundity (for which empirical data are rare). We find strong evidence for overdispersed variance in reproductive success of same-age individuals in both sexes, and we show that constraints on litter size have a strong influence on results. We also estimate that another life-history trait that is often ignored (skip breeding by females) has a relatively modest influence, reducing Nb by 9% and increasing Ne by 3%. We conclude that isolation by distance depresses genetic estimates of Nb, which implicitly assume a randomly-mating population. Estimated demographic NS (100, based on parent-offspring dispersal) was similar to genetic NS (85, based on regression of genetic distance and geographic distance), indicating that the >36,000 km2 study area includes about 4-5 black-bear neighborhoods. Results from this expansive data set provide important insight into effects of violating assumptions when estimating evolutionary parameters for long-lived, free-ranging species. In conjunction with recently-developed analytical methodology, the ready availability of non-lethal DNA sampling methods and the ability to rapidly and cheaply survey many thousands of molecular markers should facilitate eco-evolutionary studies like this for many more species in nature.
Expert elicitation, uncertainty, and the value of information in controlling invasive species
Johnson, Fred A.; Smith, Brian J.; Bonneau, Mathieu; Martin, Julien; Romagosa, Christina; Mazzotti, Frank J.; Waddle, J. Hardin; Reed, Robert; Eckles, Jennifer Kettevrlin; Vitt, Laurie J.
2017-01-01
We illustrate the utility of expert elicitation, explicit recognition of uncertainty, and the value of information for directing management and research efforts for invasive species, using tegu lizards (Salvator merianae) in southern Florida as a case study. We posited a post-birth pulse, matrix model in which four age classes of tegus are recognized: hatchlings, 1 year-old, 2 year-olds, and 3 + year-olds. This matrix model was parameterized using a 3-point process to elicit estimates of tegu demographic rates in southern Florida from 10 herpetology experts. We fit statistical distributions for each parameter and for each expert, then drew and pooled a large number of replicate samples from these to form a distribution for each demographic parameter. Using these distributions, as well as the observed correlations among elicited values, we generated a large sample of matrix population models to infer how the tegu population would respond to control efforts. We used the concepts of Pareto efficiency and stochastic dominance to conclude that targeting older age classes at relatively high rates appears to have the best chance of minimizing tegu abundance and control costs. We conclude that expert opinion combined with an explicit consideration of uncertainty can be valuable in conducting an initial assessment of what control strategy, effort, and monetary resources are needed to reduce and eventually eliminate the invader. Scientists, in turn, can use the value of information to focus research in a way that not only increases the efficacy of control, but minimizes costs as well.
Valdés, Luis; San-José, Esther; Ferreiro, Lucía; Golpe, Antonio; González-Barcala, Francisco-Javier; Toubes, María E; Rodríguez-Álvarez, María X; Álvarez-Dobaño, José M; Rodríguez-Núñez, Nuria; Rábade, Carlos; Gude, Francisco
2015-04-01
The differential diagnosis of malignant and tuberculous pleural effusion is frequently difficult. The aim of our study is to determine the discrimination value of demographic parameters and different biological markers in pleural fluid. In pleural fluid obtained from 106 patients with tuberculous, 250 with malignant and 218 with miscellaneous pleural effusion, clinical and analytical parameters were analysed, applying polytomous regression analysis and the receiver operating characteristic (ROC) curves. The three groups could be differentiated using the measured markers. Age, tumour necrosing factor-alpha, lactate dehydrogenase (LDH), adenosine deaminase (ADA), C-reactive protein (CRP) and carcinoembryonic antigen (CEA) were significant predictors for discriminating tuberculous from malignant pleural effusions; nucleated cells, lymphocytes, cholesterol, LDH, ADA, CRP, CEA and CA15.3 distinguish between malignant and miscellaneous pleural effusions. The ROC areas (95% confidence interval) were, 0.973 (0.953, 0.992) for tuberculous, 0.922 (0.900, 0.943) for miscellaneous, and 0.927 (0.907, 0.948) for malignant pleural effusion. The polytomous model correctly classified a significantly high proportion of patients with tuberculosis (85.8%) and cancer (81.6%). The incorrect classification rate was 17.8%, which increased to 19.5% in the correction using bootstrap. The results obtained to estimate the probability of tuberculous and malignant pleural effusion confirm that this model achieves a high diagnostic accuracy. This model should be applied to determine which patients with a pleural effusion of unknown origin would not benefit from further invasive procedures. © 2014 John Wiley & Sons Ltd.
Evaluation of harvest and information needs for North American sea ducks
Koneff, Mark D.; Zimmerman, Guthrie S.; Dwyer, Chris P.; Fleming, Kathleen K.; Padding, Paul I.; Devers, Patrick K.; Johnson, Fred A.; Runge, Michael C.; Roberts, Anthony J.
2017-01-01
Wildlife managers routinely seek to establish sustainable limits of sport harvest or other regulated forms of take while confronted with considerable uncertainty. A growing body of ecological research focuses on methods to describe and account for uncertainty in management decision-making and to prioritize research and monitoring investments to reduce the most influential uncertainties. We used simulation methods incorporating measures of demographic uncertainty to evaluate risk of overharvest and prioritize information needs for North American sea ducks (Tribe Mergini). Sea ducks are popular game birds in North America, yet they are poorly monitored and their population dynamics are poorly understood relative to other North American waterfowl. There have been few attempts to assess the sustainability of harvest of North American sea ducks, and no formal harvest strategy exists in the U.S. or Canada to guide management. The popularity of sea duck hunting, extended hunting opportunity for some populations (i.e., special seasons and/or bag limits), and population declines have led to concern about potential overharvest. We used Monte Carlo simulation to contrast estimates of allowable harvest and observed harvest and assess risk of overharvest for 7 populations of North American sea ducks: the American subspecies of common eider (Somateria mollissima dresseri), eastern and western populations of black scoter (Melanitta americana) and surf scoter (M. perspicillata), and continental populations of white-winged scoter (M. fusca) and long-tailed duck (Clangula hyemalis). We combined information from empirical studies and the opinions of experts through formal elicitation to create probability distributions reflecting uncertainty in the individual demographic parameters used in this assessment. Estimates of maximum growth (rmax), and therefore of allowable harvest, were highly uncertain for all populations. Long-tailed duck and American common eider appeared to be at high risk of overharvest (i.e., observed harvest < allowable harvest in 5–7% and 19–26% of simulations, respectively depending on the functional form of density dependence), whereas the other populations appeared to be at moderate risk to low risk (observed harvest < allowable harvest in 22–68% of simulations, again conditional on the form of density dependence). We also evaluated the sensitivity of the difference between allowable and observed harvest estimates to uncertainty in individual demographic parameters to prioritize information needs. We found that uncertainty in overall fecundity had more influence on comparisons of allowable and observed harvest than adult survival or observed harvest for all species except long-tailed duck. Although adult survival was characterized by less uncertainty than individual components of fecundity, it was identified as a high priority information need given the sensitivity of growth rate and allowable harvest to this parameter. Uncertainty about population size was influential in the comparison of observed and allowable harvest for 5 of the 6 populations where it factored into the assessment. While this assessment highlights a high degree of uncertainty in allowable harvest, it provides a framework for integration of improved data from future research and monitoring. It could also serve as the basis for harvest strategy development as management objectives and regulatory alternatives are specified by the management community.
Evaluation of harvest and information needs for North American sea ducks.
Koneff, Mark D; Zimmerman, Guthrie S; Dwyer, Chris P; Fleming, Kathleen K; Padding, Paul I; Devers, Patrick K; Johnson, Fred A; Runge, Michael C; Roberts, Anthony J
2017-01-01
Wildlife managers routinely seek to establish sustainable limits of sport harvest or other regulated forms of take while confronted with considerable uncertainty. A growing body of ecological research focuses on methods to describe and account for uncertainty in management decision-making and to prioritize research and monitoring investments to reduce the most influential uncertainties. We used simulation methods incorporating measures of demographic uncertainty to evaluate risk of overharvest and prioritize information needs for North American sea ducks (Tribe Mergini). Sea ducks are popular game birds in North America, yet they are poorly monitored and their population dynamics are poorly understood relative to other North American waterfowl. There have been few attempts to assess the sustainability of harvest of North American sea ducks, and no formal harvest strategy exists in the U.S. or Canada to guide management. The popularity of sea duck hunting, extended hunting opportunity for some populations (i.e., special seasons and/or bag limits), and population declines have led to concern about potential overharvest. We used Monte Carlo simulation to contrast estimates of allowable harvest and observed harvest and assess risk of overharvest for 7 populations of North American sea ducks: the American subspecies of common eider (Somateria mollissima dresseri), eastern and western populations of black scoter (Melanitta americana) and surf scoter (M. perspicillata), and continental populations of white-winged scoter (M. fusca) and long-tailed duck (Clangula hyemalis). We combined information from empirical studies and the opinions of experts through formal elicitation to create probability distributions reflecting uncertainty in the individual demographic parameters used in this assessment. Estimates of maximum growth (rmax), and therefore of allowable harvest, were highly uncertain for all populations. Long-tailed duck and American common eider appeared to be at high risk of overharvest (i.e., observed harvest < allowable harvest in 5-7% and 19-26% of simulations, respectively depending on the functional form of density dependence), whereas the other populations appeared to be at moderate risk to low risk (observed harvest < allowable harvest in 22-68% of simulations, again conditional on the form of density dependence). We also evaluated the sensitivity of the difference between allowable and observed harvest estimates to uncertainty in individual demographic parameters to prioritize information needs. We found that uncertainty in overall fecundity had more influence on comparisons of allowable and observed harvest than adult survival or observed harvest for all species except long-tailed duck. Although adult survival was characterized by less uncertainty than individual components of fecundity, it was identified as a high priority information need given the sensitivity of growth rate and allowable harvest to this parameter. Uncertainty about population size was influential in the comparison of observed and allowable harvest for 5 of the 6 populations where it factored into the assessment. While this assessment highlights a high degree of uncertainty in allowable harvest, it provides a framework for integration of improved data from future research and monitoring. It could also serve as the basis for harvest strategy development as management objectives and regulatory alternatives are specified by the management community.
Evaluation of harvest and information needs for North American sea ducks
Dwyer, Chris P.; Fleming, Kathleen K.; Padding, Paul I.; Devers, Patrick K.; Johnson, Fred A.; Runge, Michael C.; Roberts, Anthony J.
2017-01-01
Wildlife managers routinely seek to establish sustainable limits of sport harvest or other regulated forms of take while confronted with considerable uncertainty. A growing body of ecological research focuses on methods to describe and account for uncertainty in management decision-making and to prioritize research and monitoring investments to reduce the most influential uncertainties. We used simulation methods incorporating measures of demographic uncertainty to evaluate risk of overharvest and prioritize information needs for North American sea ducks (Tribe Mergini). Sea ducks are popular game birds in North America, yet they are poorly monitored and their population dynamics are poorly understood relative to other North American waterfowl. There have been few attempts to assess the sustainability of harvest of North American sea ducks, and no formal harvest strategy exists in the U.S. or Canada to guide management. The popularity of sea duck hunting, extended hunting opportunity for some populations (i.e., special seasons and/or bag limits), and population declines have led to concern about potential overharvest. We used Monte Carlo simulation to contrast estimates of allowable harvest and observed harvest and assess risk of overharvest for 7 populations of North American sea ducks: the American subspecies of common eider (Somateria mollissima dresseri), eastern and western populations of black scoter (Melanitta americana) and surf scoter (M. perspicillata), and continental populations of white-winged scoter (M. fusca) and long-tailed duck (Clangula hyemalis). We combined information from empirical studies and the opinions of experts through formal elicitation to create probability distributions reflecting uncertainty in the individual demographic parameters used in this assessment. Estimates of maximum growth (rmax), and therefore of allowable harvest, were highly uncertain for all populations. Long-tailed duck and American common eider appeared to be at high risk of overharvest (i.e., observed harvest < allowable harvest in 5–7% and 19–26% of simulations, respectively depending on the functional form of density dependence), whereas the other populations appeared to be at moderate risk to low risk (observed harvest < allowable harvest in 22–68% of simulations, again conditional on the form of density dependence). We also evaluated the sensitivity of the difference between allowable and observed harvest estimates to uncertainty in individual demographic parameters to prioritize information needs. We found that uncertainty in overall fecundity had more influence on comparisons of allowable and observed harvest than adult survival or observed harvest for all species except long-tailed duck. Although adult survival was characterized by less uncertainty than individual components of fecundity, it was identified as a high priority information need given the sensitivity of growth rate and allowable harvest to this parameter. Uncertainty about population size was influential in the comparison of observed and allowable harvest for 5 of the 6 populations where it factored into the assessment. While this assessment highlights a high degree of uncertainty in allowable harvest, it provides a framework for integration of improved data from future research and monitoring. It could also serve as the basis for harvest strategy development as management objectives and regulatory alternatives are specified by the management community. PMID:28419113
Ducrot, Virginie; Péry, Alexandre R R; Mons, Raphaël; Quéau, Hervé; Charles, Sandrine; Garric, Jeanne
2007-08-01
This paper presents original toxicity test designs and mathematical models that may be used to assess the deleterious effects of toxicants on Valvata piscinalis (Mollusca, Gastropoda). Results obtained for zinc, used as a reference toxicant, are presented. The feeding behavior, juvenile survival, growth, age at puberty, onset of reproduction, number of breedings during the life cycle, and fecundity were significantly altered when the snails were exposed to zinc-spiked sediments. Dynamic energy budget models (DEBtox) adequately predicted the effects of zinc on the V. piscinalis life cycle. They also provided estimates for lifecycle parameters that were used to parameterize a demographic model, based on a Z-transformed life-cycle graph. The effect threshold for the population growth rate (lambda) was estimated at 259 mg/kg dry sediment of zinc, showing that significant changes in abundance may occur at environmental concentrations. Significant effects occurring just above this threshold value were mainly caused by the severe impairment of reproductive endpoints. Sensitivity analysis showed that the value of lambda depended mainly on the juvenile survival rate. The impairment of this latter parameter may result in extinction of V. piscinalis. Finally, the present study highlights advantages of the proposed modeling approach in V. piscinalis and possible transfer to other test species and contaminants.
Population estimates of extended family structure and size.
Garceau, Anne; Wideroff, Louise; McNeel, Timothy; Dunn, Marsha; Graubard, Barry I
2008-01-01
Population-based estimates of biological family size can be useful for planning genetic studies, assessing how distributions of relatives affect disease associations with family history and estimating prevalence of potential family support. Mean family size per person is estimated from a population-based telephone survey (n = 1,019). After multivariate adjustment for demographic variables, older and non-White respondents reported greater mean numbers of total, first- and second-degree relatives. Females reported more total and first-degree relatives, while less educated respondents reported more second-degree relatives. Demographic differences in family size have implications for genetic research. Therefore, periodic collection of family structure data in representative populations would be useful. Copyright 2008 S. Karger AG, Basel.
Ecotoxicology and spatial modeling in population dynamics: an illustration with brown trout.
Chaumot, Arnaud; Charles, Sandrine; Flammarion, Patrick; Auger, Pierre
2003-05-01
We developed a multiregion matrix population model to explore how the demography of a hypothetical brown trout population living in a river network varies in response to different spatial scenarios of cadmium contamination. Age structure, spatial distribution, and demographic and migration processes are taken into account in the model. Chronic or acute cadmium concentrations affect the demographic parameters at the scale of the river range. The outputs of the model constitute population-level end points (the asymptotic population growth rate, the stable age structure, and the asymptotic spatial distribution) that allow comparing the different spatial scenarios of contamination regarding the demographic response at the scale of the whole river network. An analysis of the sensitivity of these end points to lower order parameters enables us to link the local effects of cadmium to the global demographic behavior of the brown trout population. Such a link is of broad interest in the point of view of ecotoxicological management.
Udhayarasu, Madhanlal; Ramakrishnan, Kalpana; Periasamy, Soundararajan
2017-12-01
Periodical monitoring of renal function, specifically for subjects with history of diabetic or hypertension would prevent them from entering into chronic kidney disease (CKD) condition. The recent increase in numbers may be due to food habits or lack of physical exercise, necessitates a rapid kidney function monitoring system. Presently, it is determined by evaluating glomerular filtration rate (GFR) that is mainly dependent on serum creatinine value and demographic parameters and ethnic value. Attempted here is to develop ethnic parameter based on skin texture for every individual. This value when used in GFR computation, the results are much agreeable with GFR obtained through standard modification of diet in renal disease and CKD epidemiology collaboration equations. Once correlation between CKD and skin texture is established, classification tool using artificial neural network is built to categorise CKD level based on demographic values and parameter obtained through skin texture (without using creatinine). This network when tested gives almost at par results with the network that is trained with demographic and creatinine values. The results of this Letter demonstrate the possibility of non-invasively determining kidney function and hence for making a device that would readily assess the kidney function even at home.
Estimation of the number and demographics of companion dogs in the UK
2011-01-01
Background Current estimates of the UK dog population vary, contain potential sources of bias and are based on expensive, large scale, public surveys. Here, we evaluate the potential of a variety of sources for estimation and monitoring of the companion dog population in the UK and associated demographic information. The sources considered were: a public survey; veterinary practices; pet insurance companies; micro-chip records; Kennel Club registrations; and the Pet Travel Scheme. The public survey and subpopulation estimates from veterinary practices, pet insurance companies and Kennel Club registrations, were combined to generate distinct estimates of the UK owned dog population using a Bayesian approach. Results We estimated there are 9.4 (95% CI: 8.1-11.5) million companion dogs in the UK according to the public survey alone, which is similar to other recent estimates. The population was judged to be over-estimated by combining the public and veterinary surveys (16.4, 95% CI: 12.5-21.5 million) and under-estimated by combining the public survey and insured dog numbers (4.8, 95% CI: 3.6-6.9 million). An estimate based on combining the public survey and Kennel Club registered dogs was 7.1 (95% CI: 4.5-12.9) million. Based on Bayesian estimations, 77 (95% CI: 62-92)% of the UK dog population were registered at a veterinary practice; 42 (95% CI: 29-55)% of dogs were insured; and 29 (95% CI: 17-43)% of dogs were Kennel Club registered. Breed demographics suggested the Labrador was consistently the most popular breed registered in micro-chip records, with the Kennel Club and with J. Sainsbury's PLC pet insurance. A comparison of the demographics between these sources suggested that popular working breeds were under-represented and certain toy, utility and miniature breeds were over- represented in the Kennel Club registrations. Density maps were produced from micro-chip records based on the geographical distribution of dogs. Conclusions A list containing the breed of each insured dog was provided by J. Sainsbury's PLC pet insurance without any accompanying information about the dog or owner. PMID:22112367
van Draanen, Jenna; Prelip, Michael; Upchurch, Dawn M
2018-06-01
This study investigates the associations between recent consumption of fast foods, sugar-sweetened beverages, and artificially-sweetened beverages on level of allostatic load, a measure of cumulative biological risk, in young adults in the US. Data from Wave IV of the National Longitudinal Study of Adolescent to Adult Health were analyzed. Negative binomial regression models were used to estimate the associations between consumption of fast foods, sugar-sweetened, and artificially-sweetened beverages and allostatic load. Poisson and logistic regression models were used to estimate the associations between these diet parameters and combined biomarkers of physiological subsystems that comprise our measure of allostatic load. All analyses were weighted and findings are representative of young adults in the US, ages 24-34 in 2008 (n = 11,562). Consumption of fast foods, sugar-sweetened, and artificially-sweetened beverages were associated with higher allostatic load at a bivariate level. Accounting for demographics and medication use, only artificially-sweetened beverages remained significantly associated with allostatic load. When all three dietary components were simultaneously included in a model, both sugar- and artificially-sweetened beverage consumption were associated with higher allostatic load. Differences in allostatic load emerge early in the life course and young adults consuming sugar- or artificially-sweetened beverages have higher allostatic load, net of demographics and medication use. Public health messages to young adults may need to include cautions about both sugar- and artificially-sweetened beverages.
Influence of demography and environment on persistence in toad populations
Lambert, Brad A.; Schorr, Robert A.; Schneider, Scott C.; Muths, Erin L.
2016-01-01
Effective conservation of rare species requires an understanding of how potential threats affect population dynamics. Unfortunately, information about population demographics prior to threats (i.e., baseline data) is lacking for many species. Perturbations, caused by climate change, disease, or other stressors can lead to population declines and heightened conservation concerns. Boreal toads (Anaxyrus boreas boreas) have undergone rangewide declines due mostly to the amphibian chytrid fungus Batrachochytrium dendrobatidis (Bd), with only a few sizable populations remaining in the southern Rocky Mountains, USA, that are disease-free. Despite the apparent region-wide occurrence of Bd, our focal populations in central Colorado were disease free over a 14-year capture-mark-recapture study until the recent discovery of Bd at one of the sites. We used recapture data and the Pradel reverse-time model to assess the influence of environmental and site-specific conditions on survival and recruitment. We then forecast changes in the toad populations with 2 growth models; one using an average lambda value to initiate the projection, and one using the most recent value to capture potential effects of the incursion of disease into the system. Adult survival was consistently high at the 3 sites, whereas recruitment was more variable and markedly low at 1 site. We found that active season moisture, active season length, and breeding shallows were important factors in estimating recruitment. Population growth models indicated a slight increase at 1 site but decreasing trends at the 2 other sites, possibly influenced by low recruitment. Insight into declining species management can be gained from information on survival and recruitment and how site-specific environmental factors influence these demographic parameters. Our data are particularly useful because they provide baseline data on demographics in populations before a disease outbreak and enhance our ability to detect changes in population parameters potentially caused by the disease.
Miró-Herrans, Aida T.; Al-Meeri, Ali; Mulligan, Connie J.
2014-01-01
Population migration has played an important role in human evolutionary history and in the patterning of human genetic variation. A deeper and empirically-based understanding of human migration dynamics is needed in order to interpret genetic and archaeological evidence and to accurately reconstruct the prehistoric processes that comprise human evolutionary history. Current empirical estimates of migration include either short time frames (i.e. within one generation) or partial knowledge about migration, such as proportion of migrants or distance of migration. An analysis of migration that includes both proportion of migrants and distance, and direction over multiple generations would better inform prehistoric reconstructions. To evaluate human migration, we use GPS coordinates from the place of residence of the Yemeni individuals sampled in our study, their birthplaces and their parents' and grandparents' birthplaces to calculate the proportion of migrants, as well as the distance and direction of migration events between each generation. We test for differences in these values between the generations and identify factors that influence the probability of migration. Our results show that the proportion and distance of migration between females and males is similar within generations. In contrast, the proportion and distance of migration is significantly lower in the grandparents' generation, most likely reflecting the decreasing effect of technology. Based on our results, we calculate the proportion of migration events (0.102) and mean and median distances of migration (96 km and 26 km) for the grandparent's generation to represent early times in human evolution. These estimates can serve to set parameter values of demographic models in model-based methods of prehistoric reconstruction, such as approximate Bayesian computation. Our study provides the first empirically-based estimates of human migration over multiple generations in a developing country and these estimates are intended to enable more precise reconstruction of the demographic processes that characterized human evolution. PMID:24759992
Chlyeh, G; Henry, P Y; Jarne, P
2003-09-01
The population biology of the schistosome-vector snail Bulinus truncatus was studied in an irrigation area near Marrakech, Morocco, using demographic approaches, in order to estimate life-history parameters. The survey was conducted using 2 capture-mark-recapture analyses in 2 separate sites from the irrigation area, the first one in 1999 and the second one in 2000. Individuals larger than 5 mm were considered. The capture probability varied through time and space in both analyses. Apparent survival (from 0.7 to 1 per period of 2-3 days) varied with time and space (a series of sinks was considered), as well as a square function of size. These results suggest variation in population intrinsic rate of increase. They also suggest that results from more classical analyses of population demography, aiming, for example at estimating population size, should be interpreted with caution. Together with other results obtained in the same irrigation area, they also lead to some suggestions for population control.
Hewitt, David A.; Janney, Eric C.; Hayes, Brian S.; Harris, Alta C.
2012-01-01
Despite relatively high survival in most years, both species have experienced substantial declines in the abundance of spawning fish because losses from mortality have not been balanced by recruitment of new individuals. Although capture-recapture data indicate substantial recruitment of new individuals into the adult spawning populations for SNS and river spawning LRS in some years, size data do not corroborate these estimates. In fact, fork length data indicate that all populations are largely comprised of fish that were present in the late 1990s and early 2000s. As a result, the status of the endangered sucker populations in Upper Klamath Lake remains worrisome, and the situation is most dire for shortnose suckers. Future investigations should explore the connections between sucker recruitment and survival and various environmental factors, such as water quality and disease. Our monitoring program provides a robust platform for estimating vital population parameters, evaluating the status of the populations, and assessing the effectiveness of conservation and recovery efforts.
Park, Jinoh; Kim, Hyun-Sook; Hwang, Hye Jeon; Yang, Dong Hyun; Koo, Hyun Jung; Kang, Joon-Won; Kim, Young-Hak
2017-09-01
To evaluate the geographic and demographic variabilities of the quantitative parameters of computed tomography perfusion (CTP) of the left ventricular (LV) myocardium in patients with normal coronary artery on computed tomography angiography (CTA). From a multicenter CTP registry of stress and static computed tomography, we retrospectively recruited 113 patients (mean age, 60 years; 57 men) without perfusion defect on visual assessment and minimal (< 20% of diameter stenosis) or no coronary artery disease on CTA. Using semiautomatic analysis software, quantitative parameters of the LV myocardium, including the myocardial attenuation in stress and rest phases, transmural perfusion ratio (TPR), and myocardial perfusion reserve index (MPRI), were evaluated in 16 myocardial segments. In the lateral wall of the LV myocardium, all quantitative parameters except for MPRI were significantly higher compared with those in the other walls. The MPRI showed consistent values in all myocardial walls (anterior to lateral wall: range, 25% to 27%; p = 0.401). At the basal level of the myocardium, all quantitative parameters were significantly lower than those at the mid- and apical levels. Compared with men, women had significantly higher values of myocardial attenuation and TPR. Age, body mass index, and Framingham risk score were significantly associated with the difference in myocardial attenuation. Geographic and demographic variabilities of quantitative parameters in stress myocardial CTP exist in healthy subjects without significant coronary artery disease. This information may be helpful when assessing myocardial perfusion defects in CTP.
Respondent-Driven Sampling in a Multi-Site Study of Black and Latino Men Who Have Sex with Men.
Murrill, Christopher S; Bingham, Trista; Lauby, Jennifer; Liu, Kai-Lih; Wheeler, Darrell; Carballo-Diéguez, Alex; Marks, Gary; Millett, Gregorio A
2016-02-01
Respondent-driven sampling (RDS) was used to recruit four samples of Black and Latino men who have sex with men (MSM) in three metropolitan areas to measure HIV prevalence and sexual and drug use behaviors. We compared demographic and behavioral risk characteristics of participants across sites, assessed the extent to which the RDS statistical adjustment procedure provides estimates that differ from the crude results, and summarized our experiences using RDS. From June 2005 to March 2006 a total of 2,235 MSM were recruited and interviewed: 614 Black MSM and 516 Latino MSM in New York City, 540 Black MSM in Philadelphia, and 565 Latino MSM in Los Angeles County. Crude point estimates for demographic characteristics, behavioral risk factors and HIV prevalence were calculated for each of the four samples. RDS Analysis Tool was used to obtain population-based estimates of each sampled population's characteristics. RDS adjusted estimates were similar to the crude estimates for each study sample on demographic characteristics such as age, income, education and employment status. Adjusted estimates of the prevalence of risk behaviors were lower than the crude estimates, and for three of the study samples, the adjusted HIV prevalence estimates were lower than the crude estimates. However, even the adjusted HIV prevalence estimates were higher than what has been previously estimated for these groups of MSM in these cities. Each site faced unique circumstances in implementing RDS. Our experience in using RDS among Black and Latino MSM resulted in diverse recruitment patterns and uncertainties in the estimated HIV prevalence and risk behaviors by study site. Copyright © 2016. Published by Elsevier Inc.
Understanding Past Population Dynamics: Bayesian Coalescent-Based Modeling with Covariates
Gill, Mandev S.; Lemey, Philippe; Bennett, Shannon N.; Biek, Roman; Suchard, Marc A.
2016-01-01
Effective population size characterizes the genetic variability in a population and is a parameter of paramount importance in population genetics and evolutionary biology. Kingman’s coalescent process enables inference of past population dynamics directly from molecular sequence data, and researchers have developed a number of flexible coalescent-based models for Bayesian nonparametric estimation of the effective population size as a function of time. Major goals of demographic reconstruction include identifying driving factors of effective population size, and understanding the association between the effective population size and such factors. Building upon Bayesian nonparametric coalescent-based approaches, we introduce a flexible framework that incorporates time-varying covariates that exploit Gaussian Markov random fields to achieve temporal smoothing of effective population size trajectories. To approximate the posterior distribution, we adapt efficient Markov chain Monte Carlo algorithms designed for highly structured Gaussian models. Incorporating covariates into the demographic inference framework enables the modeling of associations between the effective population size and covariates while accounting for uncertainty in population histories. Furthermore, it can lead to more precise estimates of population dynamics. We apply our model to four examples. We reconstruct the demographic history of raccoon rabies in North America and find a significant association with the spatiotemporal spread of the outbreak. Next, we examine the effective population size trajectory of the DENV-4 virus in Puerto Rico along with viral isolate count data and find similar cyclic patterns. We compare the population history of the HIV-1 CRF02_AG clade in Cameroon with HIV incidence and prevalence data and find that the effective population size is more reflective of incidence rate. Finally, we explore the hypothesis that the population dynamics of musk ox during the Late Quaternary period were related to climate change. [Coalescent; effective population size; Gaussian Markov random fields; phylodynamics; phylogenetics; population genetics. PMID:27368344
Li, Xiang; Kuk, Anthony Y C; Xu, Jinfeng
2014-12-10
Human biomonitoring of exposure to environmental chemicals is important. Individual monitoring is not viable because of low individual exposure level or insufficient volume of materials and the prohibitive cost of taking measurements from many subjects. Pooling of samples is an efficient and cost-effective way to collect data. Estimation is, however, complicated as individual values within each pool are not observed but are only known up to their average or weighted average. The distribution of such averages is intractable when the individual measurements are lognormally distributed, which is a common assumption. We propose to replace the intractable distribution of the pool averages by a Gaussian likelihood to obtain parameter estimates. If the pool size is large, this method produces statistically efficient estimates, but regardless of pool size, the method yields consistent estimates as the number of pools increases. An empirical Bayes (EB) Gaussian likelihood approach, as well as its Bayesian analog, is developed to pool information from various demographic groups by using a mixed-effect formulation. We also discuss methods to estimate the underlying mean-variance relationship and to select a good model for the means, which can be incorporated into the proposed EB or Bayes framework. By borrowing strength across groups, the EB estimator is more efficient than the individual group-specific estimator. Simulation results show that the EB Gaussian likelihood estimates outperform a previous method proposed for the National Health and Nutrition Examination Surveys with much smaller bias and better coverage in interval estimation, especially after correction of bias. Copyright © 2014 John Wiley & Sons, Ltd.
Reconstructing the historic demography of an endangered seabird
Steven R. Beissinger; Zachariah M. Peery
2007-01-01
Reducing extinction risk for threatened species requires determining which demographic parameters are depressed and causing population declines. Museum collections may constitute a unique, underutilized resource for measuring demographic changes over long time periods using age-ratio analysis. We reconstruct the historic demography of a U.S. federally endangered...
USDA-ARS?s Scientific Manuscript database
We compiled six long-term datasets from western North America to test for ecosystem-dependent demographic responses for forbs and grasses. Based on these data, we characterized 123 survivorship curves for 109 species. Three demographic parameters were extracted from these survivorship curves: surviv...
Coral reef fish populations can persist without immigration
Salles, Océane C.; Maynard, Jeffrey A.; Joannides, Marc; Barbu, Corentin M.; Saenz-Agudelo, Pablo; Almany, Glenn R.; Berumen, Michael L.; Thorrold, Simon R.; Jones, Geoffrey P.; Planes, Serge
2015-01-01
Determining the conditions under which populations may persist requires accurate estimates of demographic parameters, including immigration, local reproductive success, and mortality rates. In marine populations, empirical estimates of these parameters are rare, due at least in part to the pelagic dispersal stage common to most marine organisms. Here, we evaluate population persistence and turnover for a population of orange clownfish, Amphiprion percula, at Kimbe Island in Papua New Guinea. All fish in the population were sampled and genotyped on five occasions at 2-year intervals spanning eight years. The genetic data enabled estimates of reproductive success retained in the same population (reproductive success to self-recruitment), reproductive success exported to other subpopulations (reproductive success to local connectivity), and immigration and mortality rates of sub-adults and adults. Approximately 50% of the recruits were assigned to parents from the Kimbe Island population and this was stable through the sampling period. Stability in the proportion of local and immigrant settlers is likely due to: low annual mortality rates and stable egg production rates, and the short larval stages and sensory capacities of reef fish larvae. Biannual mortality rates ranged from 0.09 to 0.55 and varied significantly spatially. We used these data to parametrize a model that estimated the probability of the Kimbe Island population persisting in the absence of immigration. The Kimbe Island population was found to persist without significant immigration. Model results suggest the island population persists because the largest of the subpopulations are maintained due to having low mortality and high self-recruitment rates. Our results enable managers to appropriately target and scale actions to maximize persistence likelihood as disturbance frequencies increase. PMID:26582017
Akumu, Angela Oloo; English, Mike; Scott, J Anthony G; Griffiths, Ulla K
2007-07-01
Haemophilus influenzae type b (Hib) vaccine was introduced into routine immunization services in Kenya in 2001. We aimed to estimate the cost-effectiveness of Hib vaccine delivery. A model was developed to follow the Kenyan 2004 birth cohort until death, with and without Hib vaccine. Incidence of invasive Hib disease was estimated at Kilifi District Hospital and in the surrounding demographic surveillance system in coastal Kenya. National Hib disease incidence was estimated by adjusting incidence observed by passive hospital surveillance using assumptions about access to care. Case fatality rates were also assumed dependent on access to care. A price of US$ 3.65 per dose of pentavalent diphtheria-tetanus-pertussis-hep B-Hib vaccine was used. Multivariate Monte Carlo simulations were performed in order to assess the impact on the cost-effectiveness ratios of uncertainty in parameter values. The introduction of Hib vaccine reduced the estimated incidence of Hib meningitis per 100,000 children aged < 5 years from 71 to 8; of Hib non-meningitic invasive disease from 61 to 7; and of non-bacteraemic Hib pneumonia from 296 to 34. The costs per discounted disability adjusted life year (DALY) and per discounted death averted were US$ 38 (95% confidence interval, CI: 26-63) and US$ 1197 (95% CI: 814-2021) respectively. Most of the uncertainty in the results was due to uncertain access to care parameters. The break-even pentavalent vaccine price--where incremental Hib vaccination costs equal treatment costs averted from Hib disease--was US$ 1.82 per dose. Hib vaccine is a highly cost-effective intervention in Kenya. It would be cost-saving if the vaccine price was below half of its present level.
Coral reef fish populations can persist without immigration.
Salles, Océane C; Maynard, Jeffrey A; Joannides, Marc; Barbu, Corentin M; Saenz-Agudelo, Pablo; Almany, Glenn R; Berumen, Michael L; Thorrold, Simon R; Jones, Geoffrey P; Planes, Serge
2015-11-22
Determining the conditions under which populations may persist requires accurate estimates of demographic parameters, including immigration, local reproductive success, and mortality rates. In marine populations, empirical estimates of these parameters are rare, due at least in part to the pelagic dispersal stage common to most marine organisms. Here, we evaluate population persistence and turnover for a population of orange clownfish, Amphiprion percula, at Kimbe Island in Papua New Guinea. All fish in the population were sampled and genotyped on five occasions at 2-year intervals spanning eight years. The genetic data enabled estimates of reproductive success retained in the same population (reproductive success to self-recruitment), reproductive success exported to other subpopulations (reproductive success to local connectivity), and immigration and mortality rates of sub-adults and adults. Approximately 50% of the recruits were assigned to parents from the Kimbe Island population and this was stable through the sampling period. Stability in the proportion of local and immigrant settlers is likely due to: low annual mortality rates and stable egg production rates, and the short larval stages and sensory capacities of reef fish larvae. Biannual mortality rates ranged from 0.09 to 0.55 and varied significantly spatially. We used these data to parametrize a model that estimated the probability of the Kimbe Island population persisting in the absence of immigration. The Kimbe Island population was found to persist without significant immigration. Model results suggest the island population persists because the largest of the subpopulations are maintained due to having low mortality and high self-recruitment rates. Our results enable managers to appropriately target and scale actions to maximize persistence likelihood as disturbance frequencies increase. © 2015 The Author(s).
Sandoval-Castellanos, Edson; Palkopoulou, Eleftheria; Dalén, Love
2014-01-01
Inference of population demographic history has vastly improved in recent years due to a number of technological and theoretical advances including the use of ancient DNA. Approximate Bayesian computation (ABC) stands among the most promising methods due to its simple theoretical fundament and exceptional flexibility. However, limited availability of user-friendly programs that perform ABC analysis renders it difficult to implement, and hence programming skills are frequently required. In addition, there is limited availability of programs able to deal with heterochronous data. Here we present the software BaySICS: Bayesian Statistical Inference of Coalescent Simulations. BaySICS provides an integrated and user-friendly platform that performs ABC analyses by means of coalescent simulations from DNA sequence data. It estimates historical demographic population parameters and performs hypothesis testing by means of Bayes factors obtained from model comparisons. Although providing specific features that improve inference from datasets with heterochronous data, BaySICS also has several capabilities making it a suitable tool for analysing contemporary genetic datasets. Those capabilities include joint analysis of independent tables, a graphical interface and the implementation of Markov-chain Monte Carlo without likelihoods.
DnaSAM: Software to perform neutrality testing for large datasets with complex null models.
Eckert, Andrew J; Liechty, John D; Tearse, Brandon R; Pande, Barnaly; Neale, David B
2010-05-01
Patterns of DNA sequence polymorphisms can be used to understand the processes of demography and adaptation within natural populations. High-throughput generation of DNA sequence data has historically been the bottleneck with respect to data processing and experimental inference. Advances in marker technologies have largely solved this problem. Currently, the limiting step is computational, with most molecular population genetic software allowing a gene-by-gene analysis through a graphical user interface. An easy-to-use analysis program that allows both high-throughput processing of multiple sequence alignments along with the flexibility to simulate data under complex demographic scenarios is currently lacking. We introduce a new program, named DnaSAM, which allows high-throughput estimation of DNA sequence diversity and neutrality statistics from experimental data along with the ability to test those statistics via Monte Carlo coalescent simulations. These simulations are conducted using the ms program, which is able to incorporate several genetic parameters (e.g. recombination) and demographic scenarios (e.g. population bottlenecks). The output is a set of diversity and neutrality statistics with associated probability values under a user-specified null model that are stored in easy to manipulate text file. © 2009 Blackwell Publishing Ltd.
Space-Time Smoothing of Complex Survey Data: Small Area Estimation for Child Mortality.
Mercer, Laina D; Wakefield, Jon; Pantazis, Athena; Lutambi, Angelina M; Masanja, Honorati; Clark, Samuel
2015-12-01
Many people living in low and middle-income countries are not covered by civil registration and vital statistics systems. Consequently, a wide variety of other types of data including many household sample surveys are used to estimate health and population indicators. In this paper we combine data from sample surveys and demographic surveillance systems to produce small area estimates of child mortality through time. Small area estimates are necessary to understand geographical heterogeneity in health indicators when full-coverage vital statistics are not available. For this endeavor spatio-temporal smoothing is beneficial to alleviate problems of data sparsity. The use of conventional hierarchical models requires careful thought since the survey weights may need to be considered to alleviate bias due to non-random sampling and non-response. The application that motivated this work is estimation of child mortality rates in five-year time intervals in regions of Tanzania. Data come from Demographic and Health Surveys conducted over the period 1991-2010 and two demographic surveillance system sites. We derive a variance estimator of under five years child mortality that accounts for the complex survey weighting. For our application, the hierarchical models we consider include random effects for area, time and survey and we compare models using a variety of measures including the conditional predictive ordinate (CPO). The method we propose is implemented via the fast and accurate integrated nested Laplace approximation (INLA).
Hameed, Sarah O; White, J Wilson; Miller, Seth H; Nickols, Kerry J; Morgan, Steven G
2016-06-29
Demographic connectivity is fundamental to the persistence and resilience of metapopulations, but our understanding of the link between reproduction and recruitment is notoriously poor in open-coast marine populations. We provide the first evidence of high local retention and limited connectivity among populations spanning 700 km along an open coast in an upwelling system. Using extensive field measurements of fecundity, population size and settlement in concert with a Bayesian inverse modelling approach, we estimated that, on average, Petrolisthes cinctipes larvae disperse only 6.9 km (±25.0 km s.d.) from natal populations, despite spending approximately six weeks in an open-coast system that was once assumed to be broadly dispersive. This estimate differed substantially from our prior dispersal estimate (153.9 km) based on currents and larval duration and behaviour, revealing the importance of employing demographic data in larval dispersal estimates. Based on this estimate, we predict that demographic connectivity occurs predominantly among neighbouring populations less than 30 km apart. Comprehensive studies of larval production, settlement and connectivity are needed to advance an understanding of the ecology and evolution of life in the sea as well as to conserve ecosystems. Our novel approach provides a tractable framework for addressing these questions for species occurring in discrete coastal populations. © 2016 The Author(s).
[Demographic processes in the countries of Eastern Europe 1945-1990].
Shchepin, O P; Vladimirova, L I
1990-01-01
An analysis is made of changes in the demographic processes in the countries of Eastern Europe over the period from 1945 to 1990 within both the general regularities and national peculiarities according to the parameters of statics and dynamics of population movement. The positive tendencies in the demographic processes are pointed out, first of all in infant mortality rates and mean expectation of life at birth in Eastern European countries by decades reflecting the peculiarities of changes as compared with developed countries.
Relative prevalence of African Americans among bird watchers
John C. Robinson
2005-01-01
The demographics of bird watchers have recently become a topic of increased interest. Race or nationality is one demographic parameter that has been discussed in some depth. This paper further quantifies the relative prevalence of African Americans among U.S. bird watchers and identifies potential barriers that may prevent African Americans from becoming bird watchers...
Genetic Introgression and the Survival of Florida Panther Kittens
Hostetler, Jeffrey A.; Onorato, David P.; Nichols, James D.; Johnson, Warren E.; Roelke, Melody E.; O’Brien, Stephen J.; Jansen, Deborah; Oli, Madan K.
2010-01-01
Estimates of survival for the young of a species are critical for population models. These models can often be improved by determining the effects of management actions and population abundance on this demographic parameter. We used multiple sources of data collected during 1982-2008 and a live recapture-dead recovery modeling framework to estimate and model survival of Florida panther (Puma concolor coryi) kittens (age 0 – 1 year). Overall, annual survival of Florida panther kittens was 0.323 ± 0.071 (SE), which was lower than estimates used in previous population models. In 1995, female pumas from Texas (P. c. stanleyana) were released into occupied panther range as part of an intentional introgression program to restore genetic variability. We found that kitten survival generally increased with degree of admixture: F1 admixed and backcrossed to Texas kittens survived better than canonical Florida panther and backcrossed to canonical kittens. Average heterozygosity positively influenced kitten and older panther survival, whereas index of panther abundance negatively influenced kitten survival. Our results provide strong evidence for the positive population-level impact of genetic introgression on Florida panthers. Our approach to integrate data from multiple sources was effective at improving robustness as well as precision of estimates of Florida panther kitten survival, and can be useful in estimating vital rates for other elusive species with sparse data. PMID:21113436
Genetic introgression and the survival of Florida panther kittens
Hostetler, Jeffrey A.; Onorato, David P.; Nichols, James D.; Johnson, Warren E.; Roelke, Melody E.; O'Brien, Stephen J.; Jansen, Deborah; Oli, Madan K.
2010-01-01
Estimates of survival for the young of a species are critical for population models. These models can often be improved by determining the effects of management actions and population abundance on this demographic parameter. We used multiple sources of data collected during 1982–2008 and a live-recapture dead-recovery modeling framework to estimate and model survival of Florida panther (Puma concolor coryi) kittens (age 0–1 year). Overall, annual survival of Florida panther kittens was 0.323 ± 0.071 (SE), which was lower than estimates used in previous population models. In 1995, female pumas from Texas (P. c. stanleyana) were released into occupied panther range as part of an intentional introgression program to restore genetic variability. We found that kitten survival generally increased with degree of admixture: F1 admixed and backcrossed to Texas kittens survived better than canonical Florida panther and backcrossed to canonical kittens. Average heterozygosity positively influenced kitten and older panther survival, whereas index of panther abundance negatively influenced kitten survival. Our results provide strong evidence for the positive population-level impact of genetic introgression on Florida panthers. Our approach to integrate data from multiple sources was effective at improving robustness as well as precision of estimates of Florida panther kitten survival, and can be useful in estimating vital rates for other elusive species with sparse data.
Yu, Ling-Yuan; Chen, Zhen-Zhen; Zheng, Fang-Qiang; Shi, Ai-Ju; Guo, Ting-Ting; Yeh, Bao-Hua; Chi, Hsin; Xu, Yong-Yu
2013-02-01
The life table of the green lacewing, Chrysopa pallens (Rambur), was studied at 22 degrees C, a photoperiod of 15:9 (L:D) h, and 80% relative humidity in the laboratory. The raw data were analyzed using the age-stage, two-sex life table. The intrinsic rate of increase (r), the finite rate of increase (lambda), the net reproduction rate (R0), and the mean generation time (T) of Ch. pallens were 0.1258 d(-1), 1.1340 d(-1), 241.4 offspring and 43.6 d, respectively. For the estimation of the means, variances, and SEs of the population parameters, we compared the jackknife and bootstrap techniques. Although similar values of the means and SEs were obtained with both techniques, significant differences were observed in the frequency distribution and variances of all parameters. The jackknife technique will result in a zero net reproductive rate upon the omission of a male, an immature death, or a nonreproductive female. This result represents, however, a contradiction because an intrinsic rate of increase exists in this situation. Therefore, we suggest that the jackknife technique should not be used for the estimation of population parameters. In predator-prey interactions, the nonpredatory egg and pupal stages of the predator are time refuges for the prey, and the pest population can grow during these times. In this study, a population projection based on the age-stage, two-sex life table is used to determine the optimal interval between releases to fill the predation gaps and maintain the predatory capacity of the control agent.
On the Statistical Dependency of Identity Theft on Demographics
NASA Astrophysics Data System (ADS)
di Crescenzo, Giovanni
An improved understanding of the identity theft problem is widely agreed to be necessary to succeed in counter-theft efforts in legislative, financial and research institutions. In this paper we report on a statistical study about the existence of relationships between identity theft and area demographics in the US. The identity theft data chosen was the number of citizen complaints to the Federal Trade Commission in a large number of US municipalities. The list of demographics used for any such municipality included: estimated population, median resident age, estimated median household income, percentage of citizens with a high school or higher degree, percentage of unemployed residents, percentage of married residents, percentage of foreign born residents, percentage of residents living in poverty, density of law enforcement employees, crime index, and political orientation according to the 2004 presidential election. Our study findings, based on linear regression techniques, include statistically significant relationships between the number of identity theft complaints and a non-trivial subset of these demographics.
Surveillance of systemic autoimmune rheumatic diseases using administrative data.
Bernatsky, S; Lix, L; Hanly, J G; Hudson, M; Badley, E; Peschken, C; Pineau, C A; Clarke, A E; Fortin, P R; Smith, M; Bélisle, P; Lagace, C; Bergeron, L; Joseph, L
2011-04-01
There is growing interest in developing tools and methods for the surveillance of chronic rheumatic diseases, using existing resources such as administrative health databases. To illustrate how this might work, we used population-based administrative data to estimate and compare the prevalence of systemic autoimmune rheumatic diseases (SARDs) across three Canadian provinces, assessing for regional differences and the effects of demographic factors. Cases of SARDs (systemic lupus erythematosus, scleroderma, primary Sjogren's, polymyositis/dermatomyositis) were ascertained from provincial physician billing and hospitalization data. We combined information from three case definitions, using hierarchical Bayesian latent class regression models that account for the imperfect nature of each case definition. Using methods that account for the imperfect nature of both billing and hospitalization databases, we estimated the over-all prevalence of SARDs to be approximately 2-3 cases per 1,000 residents. Stratified prevalence estimates suggested similar demographic trends across provinces (i.e. greater prevalence in females-versus-males, and in persons of older age). The prevalence in older females approached or exceeded 1 in 100, which may reflect the high burden of primary Sjogren's syndrome in this group. Adjusting for demographics, there was a greater prevalence in urban-versus-rural settings. In our work, prevalence estimates had good face validity and provided useful information about potential regional and demographic variations. Our results suggest that surveillance of some rheumatic diseases using administrative data may indeed be feasible. Our work highlights the usefulness of using multiple data sources, adjusting for the error in each.
Tremblay, Marc; Vézina, Hélène
2000-01-01
Summary Intergenerational time intervals are frequently used in human population-genetics studies concerned with the ages and origins of mutations. In most cases, mean intervals of 20 or 25 years are used, regardless of the demographic characteristics of the population under study. Although these characteristics may vary from prehistoric to historical times, we suggest that this value is probably too low, and that the ages of some mutations may have been underestimated. Analyses were performed by using the BALSAC Population Register (Quebec, Canada), from which several intergenerational comparisons can be made. Family reconstitutions were used to measure interval lengths and variations in descending lineages. Various parameters were considered, such as spouse age at marriage, parental age, and reproduction levels. Mother-child and father-child intervals were compared. Intergenerational male and female intervals were also analyzed in 100 extended ascending genealogies. Results showed that a mean value of 30 years is a better estimate of intergenerational intervals than 20 or 25 years. As marked differences between male and female interval length were observed, specific values are proposed for mtDNA, autosomal, X-chromosomal, and Y-chromosomal loci. The applicability of these results for age estimates of mutations is discussed. PMID:10677323
Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks
Ruiz-Rizzo, Adriana L.; Neitzel, Julia; Müller, Hermann J.; Sorg, Christian; Finke, Kathrin
2018-01-01
Separable visual attention functions are assumed to rely on distinct but interacting neural mechanisms. Bundesen's “theory of visual attention” (TVA) allows the mathematical estimation of independent parameters that characterize individuals' visual attentional capacity (i.e., visual processing speed and visual short-term memory storage capacity) and selectivity functions (i.e., top-down control and spatial laterality). However, it is unclear whether these parameters distinctively map onto different brain networks obtained from intrinsic functional connectivity, which organizes slowly fluctuating ongoing brain activity. In our study, 31 demographically homogeneous healthy young participants performed whole- and partial-report tasks and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Report accuracy was modeled using TVA to estimate, individually, the four TVA parameters. Networks encompassing cortical areas relevant for visual attention were derived from independent component analysis of rs-fMRI data: visual, executive control, right and left frontoparietal, and ventral and dorsal attention networks. Two TVA parameters were mapped on particular functional networks. First, participants with higher (vs. lower) visual processing speed showed lower functional connectivity within the ventral attention network. Second, participants with more (vs. less) efficient top-down control showed higher functional connectivity within the dorsal attention network and lower functional connectivity within the visual network. Additionally, higher performance was associated with higher functional connectivity between networks: specifically, between the ventral attention and right frontoparietal networks for visual processing speed, and between the visual and executive control networks for top-down control. The higher inter-network functional connectivity was related to lower intra-network connectivity. These results demonstrate that separable visual attention parameters that are assumed to constitute relatively stable traits correspond distinctly to the functional connectivity both within and between particular functional networks. This implies that individual differences in basic attention functions are represented by differences in the coherence of slowly fluctuating brain activity. PMID:29662444
Ruiz-Rizzo, Adriana L; Neitzel, Julia; Müller, Hermann J; Sorg, Christian; Finke, Kathrin
2018-01-01
Separable visual attention functions are assumed to rely on distinct but interacting neural mechanisms. Bundesen's "theory of visual attention" (TVA) allows the mathematical estimation of independent parameters that characterize individuals' visual attentional capacity (i.e., visual processing speed and visual short-term memory storage capacity) and selectivity functions (i.e., top-down control and spatial laterality). However, it is unclear whether these parameters distinctively map onto different brain networks obtained from intrinsic functional connectivity, which organizes slowly fluctuating ongoing brain activity. In our study, 31 demographically homogeneous healthy young participants performed whole- and partial-report tasks and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Report accuracy was modeled using TVA to estimate, individually, the four TVA parameters. Networks encompassing cortical areas relevant for visual attention were derived from independent component analysis of rs-fMRI data: visual, executive control, right and left frontoparietal, and ventral and dorsal attention networks. Two TVA parameters were mapped on particular functional networks. First, participants with higher (vs. lower) visual processing speed showed lower functional connectivity within the ventral attention network. Second, participants with more (vs. less) efficient top-down control showed higher functional connectivity within the dorsal attention network and lower functional connectivity within the visual network. Additionally, higher performance was associated with higher functional connectivity between networks: specifically, between the ventral attention and right frontoparietal networks for visual processing speed, and between the visual and executive control networks for top-down control. The higher inter-network functional connectivity was related to lower intra-network connectivity. These results demonstrate that separable visual attention parameters that are assumed to constitute relatively stable traits correspond distinctly to the functional connectivity both within and between particular functional networks. This implies that individual differences in basic attention functions are represented by differences in the coherence of slowly fluctuating brain activity.
Silva, Mónica C; Matias, Rafael; Wanless, Ross M; Ryan, Peter G; Stephenson, Brent M; Bolton, Mark; Ferrand, Nuno; Coelho, M Manuela
2015-06-01
Analytical methods that apply coalescent theory to multilocus data have improved inferences of demographic parameters that are critical to understanding population divergence and speciation. In particular, at the early stages of speciation, it is important to implement models that accommodate conflicting gene trees, and benefit from the presence of shared polymorphisms. Here, we employ eleven nuclear loci and the mitochondrial control region to investigate the phylogeography and historical demography of the pelagic seabird White-faced Storm-petrel (Pelagodroma marina) by sampling subspecies across its antitropical distribution. Groups are all highly differentiated: global mitochondrial ΦST = 0.89 (P < 0.01) and global nuclear ΦST varies between 0.22 and 0.83 (all P < 0.01). The complete lineage sorting of the mitochondrial locus between hemispheres is corroborated by approximately half of the nuclear genealogies, suggesting a long-term antitropical divergence in isolation. Coalescent-based estimates of demographic parameters suggest that hemispheric divergence of P. marina occurred approximately 840 000 ya (95% HPD 582 000-1 170 000), in the absence of gene flow, and divergence within the Southern Hemisphere occurred 190 000 ya (95% HPD 96 000-600 000), both probably associated with the profound palaeo-oceanographic changes of the Pleistocene. A fledgling sampled in St Helena (tropical South Atlantic) suggests recent colonization from the Northern Hemisphere. Despite the great potential for long-distance dispersal, P. marina antitropical groups have been evolving as independent, allopatric lineages, and divergence is probably maintained by philopatry coupled with asynchronous reproductive phenology and local adaptation. © 2015 John Wiley & Sons Ltd.
A novel approach for choosing summary statistics in approximate Bayesian computation.
Aeschbacher, Simon; Beaumont, Mark A; Futschik, Andreas
2012-11-01
The choice of summary statistics is a crucial step in approximate Bayesian computation (ABC). Since statistics are often not sufficient, this choice involves a trade-off between loss of information and reduction of dimensionality. The latter may increase the efficiency of ABC. Here, we propose an approach for choosing summary statistics based on boosting, a technique from the machine-learning literature. We consider different types of boosting and compare them to partial least-squares regression as an alternative. To mitigate the lack of sufficiency, we also propose an approach for choosing summary statistics locally, in the putative neighborhood of the true parameter value. We study a demographic model motivated by the reintroduction of Alpine ibex (Capra ibex) into the Swiss Alps. The parameters of interest are the mean and standard deviation across microsatellites of the scaled ancestral mutation rate (θ(anc) = 4N(e)u) and the proportion of males obtaining access to matings per breeding season (ω). By simulation, we assess the properties of the posterior distribution obtained with the various methods. According to our criteria, ABC with summary statistics chosen locally via boosting with the L(2)-loss performs best. Applying that method to the ibex data, we estimate θ(anc)≈ 1.288 and find that most of the variation across loci of the ancestral mutation rate u is between 7.7 × 10(-4) and 3.5 × 10(-3) per locus per generation. The proportion of males with access to matings is estimated as ω≈ 0.21, which is in good agreement with recent independent estimates.
Reduced exposure using asymmetric cone beam processing for wide area detector cardiac CT
Bedayat, Arash; Kumamaru, Kanako; Powers, Sara L.; Signorelli, Jason; Steigner, Michael L.; Steveson, Chloe; Soga, Shigeyoshi; Adams, Kimberly; Mitsouras, Dimitrios; Clouse, Melvin; Mather, Richard T.
2011-01-01
The purpose of this study was to estimate dose reduction after implementation of asymmetrical cone beam processing using exposure differences measured in a water phantom and a small cohort of clinical coronary CTA patients. Two separate 320 × 0.5 mm detector row scans of a water phantom used identical cardiac acquisition parameters before and after software modifications from symmetric to asymmetric cone beam acquisition and processing. Exposure was measured at the phantom surface with Optically Stimulated Luminescence (OSL) dosimeters at 12 equally spaced angular locations. Mean HU and standard deviation (SD) for both approaches were compared using ROI measurements obtained at the center plus four peripheral locations in the water phantom. To assess image quality, mean HU and standard deviation (SD) for both approaches were compared using ROI measurements obtained at five points within the water phantom. Retrospective evaluation of 64 patients (37 symmetric; 27 asymmetric acquisition) included clinical data, scanning parameters, quantitative plus qualitative image assessment, and estimated radiation dose. In the water phantom, the asymmetric cone beam processing reduces exposure by approximately 20% with no change in image quality. The clinical coronary CTA patient groups had comparable demographics. The estimated dose reduction after implementation of the asymmetric approach was roughly 24% with no significant difference between the symmetric and asymmetric approach with respect to objective measures of image quality or subjective assessment using a four point scale. When compared to a symmetric approach, the decreased exposure, subsequent lower patient radiation dose, and similar image quality from asymmetric cone beam processing supports its routine clinical use. PMID:21336552
Reduced exposure using asymmetric cone beam processing for wide area detector cardiac CT.
Bedayat, Arash; Rybicki, Frank J; Kumamaru, Kanako; Powers, Sara L; Signorelli, Jason; Steigner, Michael L; Steveson, Chloe; Soga, Shigeyoshi; Adams, Kimberly; Mitsouras, Dimitrios; Clouse, Melvin; Mather, Richard T
2012-02-01
The purpose of this study was to estimate dose reduction after implementation of asymmetrical cone beam processing using exposure differences measured in a water phantom and a small cohort of clinical coronary CTA patients. Two separate 320 × 0.5 mm detector row scans of a water phantom used identical cardiac acquisition parameters before and after software modifications from symmetric to asymmetric cone beam acquisition and processing. Exposure was measured at the phantom surface with Optically Stimulated Luminescence (OSL) dosimeters at 12 equally spaced angular locations. Mean HU and standard deviation (SD) for both approaches were compared using ROI measurements obtained at the center plus four peripheral locations in the water phantom. To assess image quality, mean HU and standard deviation (SD) for both approaches were compared using ROI measurements obtained at five points within the water phantom. Retrospective evaluation of 64 patients (37 symmetric; 27 asymmetric acquisition) included clinical data, scanning parameters, quantitative plus qualitative image assessment, and estimated radiation dose. In the water phantom, the asymmetric cone beam processing reduces exposure by approximately 20% with no change in image quality. The clinical coronary CTA patient groups had comparable demographics. The estimated dose reduction after implementation of the asymmetric approach was roughly 24% with no significant difference between the symmetric and asymmetric approach with respect to objective measures of image quality or subjective assessment using a four point scale. When compared to a symmetric approach, the decreased exposure, subsequent lower patient radiation dose, and similar image quality from asymmetric cone beam processing supports its routine clinical use.
A Novel Approach for Choosing Summary Statistics in Approximate Bayesian Computation
Aeschbacher, Simon; Beaumont, Mark A.; Futschik, Andreas
2012-01-01
The choice of summary statistics is a crucial step in approximate Bayesian computation (ABC). Since statistics are often not sufficient, this choice involves a trade-off between loss of information and reduction of dimensionality. The latter may increase the efficiency of ABC. Here, we propose an approach for choosing summary statistics based on boosting, a technique from the machine-learning literature. We consider different types of boosting and compare them to partial least-squares regression as an alternative. To mitigate the lack of sufficiency, we also propose an approach for choosing summary statistics locally, in the putative neighborhood of the true parameter value. We study a demographic model motivated by the reintroduction of Alpine ibex (Capra ibex) into the Swiss Alps. The parameters of interest are the mean and standard deviation across microsatellites of the scaled ancestral mutation rate (θanc = 4Neu) and the proportion of males obtaining access to matings per breeding season (ω). By simulation, we assess the properties of the posterior distribution obtained with the various methods. According to our criteria, ABC with summary statistics chosen locally via boosting with the L2-loss performs best. Applying that method to the ibex data, we estimate θ^anc≈1.288 and find that most of the variation across loci of the ancestral mutation rate u is between 7.7 × 10−4 and 3.5 × 10−3 per locus per generation. The proportion of males with access to matings is estimated as ω^≈0.21, which is in good agreement with recent independent estimates. PMID:22960215
Estimating the Prevalence of Childhood Obesity in Alaska Using Partial, Nonrandom Measurement Data
Boles, Myde; Fink, Karol; Topol, Rebecca; Fenaughty, Andrea
2016-01-01
Although monitoring childhood obesity prevalence is critical for state public health programs to assess trends and the effectiveness of interventions, few states have comprehensive body mass index measurement systems in place. In some states, however, assorted school districts collect measurements on student height and weight as part of annual health screenings. To estimate childhood obesity prevalence in Alaska, we created a logistic regression model using such annual measurements along with public data on demographics and socioeconomic status. Our mixed-effects model-generated prevalence estimates validated well against weighted estimates, with 95% confidence intervals overlapping between methodologies among 7 of 8 participating school districts. Our methodology accounts for variation in school-level and student-level demographic factors across the state, and the approach we describe can be applied by other states that have existing nonrandom student measurement data to estimate childhood obesity prevalence. PMID:27010843
Demographic Paradoxes in the Los Angeles Voting Rights Case.
ERIC Educational Resources Information Center
Clark, William A. V.; Morrison, Peter A.
1991-01-01
How technical demographic analysis can inform and confuse judicial considerations of voting rights principles is illustrated in a review of a 1990 case brought against Los Angeles County (California). A postscripted article considers whether the court involved should rely on after-census estimates for redistricting. (SLD)
Cooper, R.J.; Mordecai, Rua S.; Mattsson, B.G.; Conroy, M.J.; Pacifici, K.; Peterson, J.T.; Moore, C.T.
2008-01-01
We describe a survey design and field protocol for the Ivory-billed Woodpecker (Campephilus principalis) search effort that will: (1) allow estimation of occupancy, use, and detection probability for habitats at two spatial scales within the bird?s former range, (2) assess relationships between occupancy, use, and habitat characteristics at those scales, (3) eventually allow the development of a population viability model that depends on patch occupancy instead of difficult-to-measure demographic parameters, and (4) be adaptive, allowing newly collected information to update the above models and search locations. The approach features random selection of patches to be searched from a sampling frame stratified and weighted by patch quality, and requires multiple visits per patch. It is adaptive within a season in that increased search activity is allowed in and around locations of strong visual and/or aural evidence, and adaptive among seasons in that habitat associations allow modification of stratum weights. This statistically rigorous approach is an improvement over simply visiting the ?best? habitat in an ad hoc fashion because we can learn from prior effort and modify the search accordingly. Results from the 2006-07 search season indicate weak relationships between occupancy and habitat (although we suggest modifications of habitat measurement protocols), and a very low detection probability, suggesting more visits per patch are required. Sample size requirements will be discussed.
The pediatric sepsis biomarker risk model: potential implications for sepsis therapy and biology.
Alder, Matthew N; Lindsell, Christopher J; Wong, Hector R
2014-07-01
Sepsis remains a major cause of morbidity and mortality in adult and pediatric intensive care units. Heterogeneity of demographics, comorbidities, biological mechanisms, and severity of illness leads to difficulty in determining which patients are at highest risk of mortality. Determining mortality risk is important for weighing the potential benefits of more aggressive interventions and for deciding whom to enroll in clinical trials. Biomarkers can be used to parse patients into different risk categories and can outperform current methods of patient risk stratification based on physiologic parameters. Here we review the Pediatric Sepsis Biomarker Risk Model that has also been modified and applied to estimate mortality risk in adult patients. We compare the two models and speculate on the biological implications of the biomarkers in patients with sepsis.
Fratini, Sara; Ragionieri, Lapo; Cannicci, Stefano
2016-01-01
The spatial distribution and the amount of intraspecific genetic variation of marine organisms are strongly influenced by many biotic and abiotic factors. Comparing biological and genetic data characterizing species living in the same habitat can help to elucidate the processes driving these variation patterns. Here, we present a comparative multispecies population genetic study on seven mangrove crabs co-occurring in the West Indian Ocean characterized by planktotrophic larvae with similar pelagic larval duration. Our main aim was to investigate whether a suite of biological, behavioural and ecological traits could affect genetic diversities of the study species in combination with historical demographic parameters. As possible current explanatory factors, we used the intertidal micro-habitat colonised by adult populations, various parameters of individual and population fecundity, and the timing of larval release. As the genetic marker, we used partial sequences of cytochrome oxidase subunit I gene. Genetic and ecological data were collected by the authors and/or gathered from primary literature. Permutational multiple regression models and ANOVA tests showed that species density and their reproductive output in combination with historical demographic parameters could explain the intraspecific genetic variation indexes across the seven species. In particular, species producing consistently less eggs per spawning event showed higher values of haplotype diversity. Moreover, Tajima’s D parameters well explained the recorded values for haplotype diversity and average γst. We concluded that current intraspecific gene diversities in crabs inhabiting mangrove forests were affected by population fecundity as well as past demographic history. The results were also discussed in terms of management and conservation of fauna in the Western Indian Ocean mangroves. PMID:27379532
Fratini, Sara; Ragionieri, Lapo; Cannicci, Stefano
2016-01-01
The spatial distribution and the amount of intraspecific genetic variation of marine organisms are strongly influenced by many biotic and abiotic factors. Comparing biological and genetic data characterizing species living in the same habitat can help to elucidate the processes driving these variation patterns. Here, we present a comparative multispecies population genetic study on seven mangrove crabs co-occurring in the West Indian Ocean characterized by planktotrophic larvae with similar pelagic larval duration. Our main aim was to investigate whether a suite of biological, behavioural and ecological traits could affect genetic diversities of the study species in combination with historical demographic parameters. As possible current explanatory factors, we used the intertidal micro-habitat colonised by adult populations, various parameters of individual and population fecundity, and the timing of larval release. As the genetic marker, we used partial sequences of cytochrome oxidase subunit I gene. Genetic and ecological data were collected by the authors and/or gathered from primary literature. Permutational multiple regression models and ANOVA tests showed that species density and their reproductive output in combination with historical demographic parameters could explain the intraspecific genetic variation indexes across the seven species. In particular, species producing consistently less eggs per spawning event showed higher values of haplotype diversity. Moreover, Tajima's D parameters well explained the recorded values for haplotype diversity and average γst. We concluded that current intraspecific gene diversities in crabs inhabiting mangrove forests were affected by population fecundity as well as past demographic history. The results were also discussed in terms of management and conservation of fauna in the Western Indian Ocean mangroves.
Ensemble-Based Parameter Estimation in a Coupled General Circulation Model
Liu, Y.; Liu, Z.; Zhang, S.; ...
2014-09-10
Parameter estimation provides a potentially powerful approach to reduce model bias for complex climate models. Here, in a twin experiment framework, the authors perform the first parameter estimation in a fully coupled ocean–atmosphere general circulation model using an ensemble coupled data assimilation system facilitated with parameter estimation. The authors first perform single-parameter estimation and then multiple-parameter estimation. In the case of the single-parameter estimation, the error of the parameter [solar penetration depth (SPD)] is reduced by over 90% after ~40 years of assimilation of the conventional observations of monthly sea surface temperature (SST) and salinity (SSS). The results of multiple-parametermore » estimation are less reliable than those of single-parameter estimation when only the monthly SST and SSS are assimilated. Assimilating additional observations of atmospheric data of temperature and wind improves the reliability of multiple-parameter estimation. The errors of the parameters are reduced by 90% in ~8 years of assimilation. Finally, the improved parameters also improve the model climatology. With the optimized parameters, the bias of the climatology of SST is reduced by ~90%. Altogether, this study suggests the feasibility of ensemble-based parameter estimation in a fully coupled general circulation model.« less
Comparative analysis of old-age mortality estimations in Africa.
Bendavid, Eran; Seligman, Benjamin; Kubo, Jessica
2011-01-01
Survival to old ages is increasing in many African countries. While demographic tools for estimating mortality up to age 60 have improved greatly, mortality patterns above age 60 rely on models based on little or no demographic data. These estimates are important for social planning and demographic projections. We provide direct estimations of older-age mortality using survey data. Since 2005, nationally representative household surveys in ten sub-Saharan countries record counts of living and recently deceased household members: Burkina Faso, Côte d'Ivoire, Ethiopia, Namibia, Nigeria, Swaziland, Tanzania, Uganda, Zambia, and Zimbabwe. After accounting for age heaping using multiple imputation, we use this information to estimate probability of death in 5-year intervals ((5)q(x)). We then compare our (5)q(x) estimates to those provided by the World Health Organization (WHO) and the United Nations Population Division (UNPD) to estimate the differences in mortality estimates, especially among individuals older than 60 years old. We obtained information on 505,827 individuals (18.4% over age 60, 1.64% deceased). WHO and UNPD mortality models match our estimates closely up to age 60 (mean difference in probability of death -1.1%). However, mortality probabilities above age 60 are lower using our estimations than either WHO or UNPD. The mean difference between our sample and the WHO is 5.9% (95% CI 3.8-7.9%) and between our sample is UNPD is 13.5% (95% CI 11.6-15.5%). Regardless of the comparator, the difference in mortality estimations rises monotonically above age 60. Mortality estimations above age 60 in ten African countries exhibit large variations depending on the method of estimation. The observed patterns suggest the possibility that survival in some African countries among adults older than age 60 is better than previously thought. Improving the quality and coverage of vital information in developing countries will become increasingly important with future reductions in mortality.
Azodi, Christina B.; Sheldon, Sallie P.; Trombulak, Stephen C.; Ardren, William R.
2015-01-01
The origin of sea lamprey (Petromyzon marinus) in Lake Champlain has been heavily debated over the past decade. Given the lack of historical documentation, two competing hypotheses have emerged in the literature. First, it has been argued that the relatively recent population size increase and concomitant rise in wounding rates on prey populations are indicative of an invasive population that entered the lake through the Champlain Canal. Second, recent genetic evidence suggests a post-glacial colonization at the end of the Pleistocene, approximately 11,000 years ago. One limitation to resolving the origin of sea lamprey in Lake Champlain is a lack of historical and current measures of population size. In this study, the issue of population size was explicitly addressed using nuclear (nDNA) and mitochondrial DNA (mtDNA) markers to estimate historical demography with genetic models. Haplotype network analysis, mismatch analysis, and summary statistics based on mtDNA noncoding sequences for NCI (479 bp) and NCII (173 bp) all indicate a recent population expansion. Coalescent models based on mtDNA and nDNA identified two potential demographic events: a population decline followed by a very recent population expansion. The decline in effective population size may correlate with land-use and fishing pressure changes post-European settlement, while the recent expansion may be associated with the implementation of the salmonid stocking program in the 1970s. These results are most consistent with the hypothesis that sea lamprey are native to Lake Champlain; however, the credibility intervals around parameter estimates demonstrate that there is uncertainty regarding the magnitude and timing of past demographic events. PMID:26539334
Reconstructing population histories from single nucleotide polymorphism data.
Sirén, Jukka; Marttinen, Pekka; Corander, Jukka
2011-01-01
Population genetics encompasses a strong theoretical and applied research tradition on the multiple demographic processes that shape genetic variation present within a species. When several distinct populations exist in the current generation, it is often natural to consider the pattern of their divergence from a single ancestral population in terms of a binary tree structure. Inference about such population histories based on molecular data has been an intensive research topic in the recent years. The most common approach uses coalescent theory to model genealogies of individuals sampled from the current populations. Such methods are able to compare several different evolutionary scenarios and to estimate demographic parameters. However, their major limitation is the enormous computational complexity associated with the indirect modeling of the demographies, which limits the application to small data sets. Here, we propose a novel Bayesian method for inferring population histories from unlinked single nucleotide polymorphisms, which is applicable also to data sets harboring large numbers of individuals from distinct populations. We use an approximation to the neutral Wright-Fisher diffusion to model random fluctuations in allele frequencies. The population histories are modeled as binary rooted trees that represent the historical order of divergence of the different populations. A combination of analytical, numerical, and Monte Carlo integration techniques are utilized for the inferences. A particularly important feature of our approach is that it provides intuitive measures of statistical uncertainty related with the estimates computed, which may be entirely lacking for the alternative methods in this context. The potential of our approach is illustrated by analyses of both simulated and real data sets.
James F. Taulman; Kimberly G. Smith; Ronald E. Thill
1998-01-01
This study investigated responses of populations of southern flying squirrels to a range of experimental even-aged and uneven-aged timber-harvest practices along a gradient of increasing disturbance intensity. The goals were to determine whether measurable demographic parameters of squirrels in experimental forests would change after logging; whether a disturbance...
The Age Parameters of the Starting Demographic Events across Russian Generations
ERIC Educational Resources Information Center
Mitrofanova, E. S.
2016-01-01
This article presents comparisons of the ages and facts of starting demographic events in Russia based on the findings of three large-scale surveys: the European Social Survey, 2006; the Generations and Gender Survey, 2004, 2007, and 2011; and Person, Family, Society, 2013. This study focuses on the intergenerational and gender differences in the…
Cros, David; Sánchez, Leopoldo; Cochard, Benoit; Samper, Patrick; Denis, Marie; Bouvet, Jean-Marc; Fernández, Jesús
2014-04-01
Explicit pedigree reconstruction by simulated annealing gave reliable estimates of genealogical coancestry in plant species, especially when selfing rate was lower than 0.6, using a realistic number of markers. Genealogical coancestry information is crucial in plant breeding to estimate genetic parameters and breeding values. The approach of Fernández and Toro (Mol Ecol 15:1657-1667, 2006) to estimate genealogical coancestries from molecular data through pedigree reconstruction was limited to species with separate sexes. In this study it was extended to plants, allowing hermaphroditism and monoecy, with possible selfing. Moreover, some improvements were made to take previous knowledge on the population demographic history into account. The new method was validated using simulated and real datasets. Simulations showed that accuracy of estimates was high with 30 microsatellites, with the best results obtained for selfing rates below 0.6. In these conditions, the root mean square error (RMSE) between the true and estimated genealogical coancestry was small (<0.07), although the number of ancestors was overestimated and the selfing rate could be biased. Simulations also showed that linkage disequilibrium between markers and departure from the Hardy-Weinberg equilibrium in the founder population did not affect the efficiency of the method. Real oil palm data confirmed the simulation results, with a high correlation between the true and estimated genealogical coancestry (>0.9) and a low RMSE (<0.08) using 38 markers. The method was applied to the Deli oil palm population for which pedigree data were scarce. The estimated genealogical coancestries were highly correlated (>0.9) with the molecular coancestries using 100 markers. Reconstructed pedigrees were used to estimate effective population sizes. In conclusion, this method gave reliable genealogical coancestry estimates. The strategy was implemented in the software MOLCOANC 3.0.
Ghana. Country Demographic Profiles, No. 5.
ERIC Educational Resources Information Center
Bureau of the Census (DOC), Suitland, MD. Population Div.
Tables of demographic information about Ghana are presented, including size of population and estimates of fertility and mortality. The data were obtained primarily from population censuses in 1960 and 1970, a 1960 post-enumeration survey, and a 1971 supplementary enquiry. Because Ghana's vital registration system is incomplete, the data are not…
Population-based estimates of pesticide intake are needed to characterize exposure for particular demographic groups based on their dietary behaviors. Regression modeling performed on measurements of selected pesticides in composited duplicate diet samples allowed (1) estimation ...
Population-based estimates of pesticide intake are needed to characterize exposure for particular demographic groups based on their dietary behaviors. Regression modeling performed on measurements of selected pesticides in composited duplicate diet samples allowed (1) estimation ...
Population-based estimates of pesticide intake are needed to characterize exposure for particular demographic groups based on their dietary behaviors. Regression modeling performed on measurements of selected pesticides in composited duplicate diet samples allowed (1) estimation ...
A statistical approach to quasi-extinction forecasting.
Holmes, Elizabeth Eli; Sabo, John L; Viscido, Steven Vincent; Fagan, William Fredric
2007-12-01
Forecasting population decline to a certain critical threshold (the quasi-extinction risk) is one of the central objectives of population viability analysis (PVA), and such predictions figure prominently in the decisions of major conservation organizations. In this paper, we argue that accurate forecasting of a population's quasi-extinction risk does not necessarily require knowledge of the underlying biological mechanisms. Because of the stochastic and multiplicative nature of population growth, the ensemble behaviour of population trajectories converges to common statistical forms across a wide variety of stochastic population processes. This paper provides a theoretical basis for this argument. We show that the quasi-extinction surfaces of a variety of complex stochastic population processes (including age-structured, density-dependent and spatially structured populations) can be modelled by a simple stochastic approximation: the stochastic exponential growth process overlaid with Gaussian errors. Using simulated and real data, we show that this model can be estimated with 20-30 years of data and can provide relatively unbiased quasi-extinction risk with confidence intervals considerably smaller than (0,1). This was found to be true even for simulated data derived from some of the noisiest population processes (density-dependent feedback, species interactions and strong age-structure cycling). A key advantage of statistical models is that their parameters and the uncertainty of those parameters can be estimated from time series data using standard statistical methods. In contrast for most species of conservation concern, biologically realistic models must often be specified rather than estimated because of the limited data available for all the various parameters. Biologically realistic models will always have a prominent place in PVA for evaluating specific management options which affect a single segment of a population, a single demographic rate, or different geographic areas. However, for forecasting quasi-extinction risk, statistical models that are based on the convergent statistical properties of population processes offer many advantages over biologically realistic models.
Poverty among Foster Children: Estimates Using the Supplemental Poverty Measure
Pac, Jessica; Waldfogel, Jane; Wimer, Christopher
2017-01-01
We use data from the Current Population Survey and the new Supplemental Poverty Measure (SPM) to provide estimates for poverty among foster children over the period 1992 to 2013. These are the first large-scale national estimates for foster children who are not included in official poverty statistics. Holding child and family demographics constant, foster children have a lower risk of poverty than other children. Analyzing income in detail suggests that foster care payments likely play an important role in reducing the risk of poverty in this group. In contrast, we find that children living with grandparents have a higher risk of poverty than other children, even after taking demographics into account. Our estimates suggest that this excess risk is likely linked to their lower likelihood of receiving foster care or other income supports. PMID:28659651
Space-Time Smoothing of Complex Survey Data: Small Area Estimation for Child Mortality
Mercer, Laina D; Wakefield, Jon; Pantazis, Athena; Lutambi, Angelina M; Masanja, Honorati; Clark, Samuel
2016-01-01
Many people living in low and middle-income countries are not covered by civil registration and vital statistics systems. Consequently, a wide variety of other types of data including many household sample surveys are used to estimate health and population indicators. In this paper we combine data from sample surveys and demographic surveillance systems to produce small area estimates of child mortality through time. Small area estimates are necessary to understand geographical heterogeneity in health indicators when full-coverage vital statistics are not available. For this endeavor spatio-temporal smoothing is beneficial to alleviate problems of data sparsity. The use of conventional hierarchical models requires careful thought since the survey weights may need to be considered to alleviate bias due to non-random sampling and non-response. The application that motivated this work is estimation of child mortality rates in five-year time intervals in regions of Tanzania. Data come from Demographic and Health Surveys conducted over the period 1991–2010 and two demographic surveillance system sites. We derive a variance estimator of under five years child mortality that accounts for the complex survey weighting. For our application, the hierarchical models we consider include random effects for area, time and survey and we compare models using a variety of measures including the conditional predictive ordinate (CPO). The method we propose is implemented via the fast and accurate integrated nested Laplace approximation (INLA). PMID:27468328
Genetic traces of east-to-west human expansion waves in Eurasia.
Chaix, Raphaëlle; Austerlitz, Frédéric; Hegay, Tatyana; Quintana-Murci, Lluís; Heyer, Evelyne
2008-07-01
In this study, we describe the landscape of human demographic expansions in Eurasia using a large continental Y chromosome and mitochondrial DNA dataset. Variation at these two uniparentally-inherited genetic systems retraces expansions that occurred in the past 60 ky, and shows a clear decrease of expansion ages from east to west Eurasia. To investigate the demographic events at the origin of this westward decrease of expansion ages, the estimated divergence ages between Eurasian populations are compared with the estimated expansion ages within each population. Both markers suggest that the demographic expansion diffused from east to west in Eurasia in a demic way, i.e., through migrations of individuals (and not just through diffusion of new technologies), highlighting the prominent role of eastern regions within Eurasia during Palaeolithic times. (c) 2008 Wiley-Liss, Inc.
Nawrotzki, Raphael J.; Jiang, Leiwen
2015-01-01
Although data for the total number of international migrant flows is now available, no global dataset concerning demographic characteristics, such as the age and gender composition of migrant flows exists. This paper reports on the methods used to generate the CDM-IM dataset of age and gender specific profiles of bilateral net (not gross) migrant flows. We employ raw data from the United Nations Global Migration Database and estimate net migrant flows by age and gender between two time points around the year 2000, accounting for various demographic processes (fertility, mortality). The dataset contains information on 3,713 net migrant flows. Validation analyses against existing data sets and the historical, geopolitical context demonstrate that the CDM-IM dataset is of reasonably high quality. PMID:26692590
Crawford, Brian A.; Moore, Clinton; Norton, Terry M.; Maerz, John C.
2018-01-01
A challenge for making conservation decisions is predicting how wildlife populations respond to multiple, concurrent threats and potential management strategies, usually under substantial uncertainty. Integrated modeling approaches can improve estimation of demographic rates necessary for making predictions, even for rare or cryptic species with sparse data, but their use in management applications is limited. We developed integrated models for a population of diamondback terrapins (Malaclemys terrapin) impacted by road-associated threats to (i) jointly estimate demographic rates from two mark-recapture datasets, while directly estimating road mortality and the impact of management actions deployed during the study; and (ii) project the population using population viability analysis under simulated management strategies to inform decision-making. Without management, population extirpation was nearly certain due to demographic impacts of road mortality, predators, and vegetation. Installation of novel flashing signage increased survival of terrapins that crossed roads by 30%. Signage, along with small roadside barriers installed during the study, increased population persistence probability, but the population was still predicted to decline. Management strategies that included actions targeting multiple threats and demographic rates resulted in the highest persistence probability, and roadside barriers, which increased adult survival, were predicted to increase persistence more than other actions. Our results support earlier findings showing mitigation of multiple threats is likely required to increase the viability of declining populations. Our approach illustrates how integrated models may be adapted to use limited data efficiently, represent system complexity, evaluate impacts of threats and management actions, and provide decision-relevant information for conservation of at-risk populations.
Mild traumatic brain injury: graph-model characterization of brain networks for episodic memory.
Tsirka, Vasso; Simos, Panagiotis G; Vakis, Antonios; Kanatsouli, Kassiani; Vourkas, Michael; Erimaki, Sofia; Pachou, Ellie; Stam, Cornelis Jan; Micheloyannis, Sifis
2011-02-01
Episodic memory is among the cognitive functions that can be affected in the acute phase following mild traumatic brain injury (MTBI). The present study used EEG recordings to evaluate global synchronization and network organization of rhythmic activity during the encoding and recognition phases of an episodic memory task varying in stimulus type (kaleidoscope images, pictures, words, and pseudowords). Synchronization of oscillatory activity was assessed using a linear and nonlinear connectivity estimator and network analyses were performed using algorithms derived from graph theory. Twenty five MTBI patients (tested within days post-injury) and healthy volunteers were closely matched on demographic variables, verbal ability, psychological status variables, as well as on overall task performance. Patients demonstrated sub-optimal network organization, as reflected by changes in graph parameters in the theta and alpha bands during both encoding and recognition. There were no group differences in spectral energy during task performance or on network parameters during a control condition (rest). Evidence of less optimally organized functional networks during memory tasks was more prominent for pictorial than for verbal stimuli. Copyright © 2010 Elsevier B.V. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Y.; Liu, Z.; Zhang, S.
Parameter estimation provides a potentially powerful approach to reduce model bias for complex climate models. Here, in a twin experiment framework, the authors perform the first parameter estimation in a fully coupled ocean–atmosphere general circulation model using an ensemble coupled data assimilation system facilitated with parameter estimation. The authors first perform single-parameter estimation and then multiple-parameter estimation. In the case of the single-parameter estimation, the error of the parameter [solar penetration depth (SPD)] is reduced by over 90% after ~40 years of assimilation of the conventional observations of monthly sea surface temperature (SST) and salinity (SSS). The results of multiple-parametermore » estimation are less reliable than those of single-parameter estimation when only the monthly SST and SSS are assimilated. Assimilating additional observations of atmospheric data of temperature and wind improves the reliability of multiple-parameter estimation. The errors of the parameters are reduced by 90% in ~8 years of assimilation. Finally, the improved parameters also improve the model climatology. With the optimized parameters, the bias of the climatology of SST is reduced by ~90%. Altogether, this study suggests the feasibility of ensemble-based parameter estimation in a fully coupled general circulation model.« less
Effects of harvest and climate on population dynamics of northern bobwhites in south Florida
Rolland, V.; Hostetler, J.A.; Hines, T.C.; Johnson, F.A.; Percival, H.F.; Oli, M.K.
2011-01-01
Context Hunting-related (hereafter harvest) mortality is assumed to be compensatory in many exploited species. However, when harvest mortality is additive, hunting can lead to population declines, especially on public land where hunting pressure can be intense. Recent studies indicate that excessive hunting may have contributed to the decline of a northern bobwhite (Colinus virginianus) population in south Florida. Aims This study aimed to estimate population growth rates to determine potential and actual contribution of vital rates to annual changes in population growth rates, and to evaluate the role of harvest and climatic variables on bobwhite population decline. Methods We used demographic parameters estimated from a six-year study to parameterise population matrix models and conduct prospective and retrospective perturbation analyses. Key results The stochastic population growth rate (?? S=0.144) was proportionally more sensitive to adult winter survival and survival of fledglings, nests and broods from first nesting attempts; the same variables were primarily responsible for annual changes in population growth rate. Demographic parameters associated with second nesting attempts made virtually no contribution to population growth rate. All harvest scenarios consistently revealed a substantial impact of harvest on bobwhite population dynamics. If the lowest harvest level recorded in the study period (i.e. 0.08 birds harvested per day per km2 in 2008) was applied, S would increase by 32.1%. Winter temperatures and precipitation negatively affected winter survival, and precipitation acted synergistically with harvest in affecting winter survival. Conclusions Our results suggest that reduction in winter survival due to overharvest has been an important cause of the decline in our study population, but that climatic factors might have also played a role. Thus, for management actions to be effective, assessing the contribution of primary (e.g. harvesting) but also secondary factors (e.g. climate) to population decline may be necessary. Implications Reducing hunting pressure would be necessary for the recovery of the bobwhite population at our study site. In addition, an adaptive harvest management strategy that considers weather conditions in setting harvest quota would help reverse the population decline further. ?? 2011 CSIRO.
Grant, Evan H. Campbell; Zipkin, Elise; Scott, Sillett T.; Chandler, Richard; Royle, J. Andrew
2014-01-01
Wildlife populations consist of individuals that contribute disproportionately to growth and viability. Understanding a population's spatial and temporal dynamics requires estimates of abundance and demographic rates that account for this heterogeneity. Estimating these quantities can be difficult, requiring years of intensive data collection. Often, this is accomplished through the capture and recapture of individual animals, which is generally only feasible at a limited number of locations. In contrast, N-mixture models allow for the estimation of abundance, and spatial variation in abundance, from count data alone. We extend recently developed multistate, open population N-mixture models, which can additionally estimate demographic rates based on an organism's life history characteristics. In our extension, we develop an approach to account for the case where not all individuals can be assigned to a state during sampling. Using only state-specific count data, we show how our model can be used to estimate local population abundance, as well as density-dependent recruitment rates and state-specific survival. We apply our model to a population of black-throated blue warblers (Setophaga caerulescens) that have been surveyed for 25 years on their breeding grounds at the Hubbard Brook Experimental Forest in New Hampshire, USA. The intensive data collection efforts allow us to compare our estimates to estimates derived from capture–recapture data. Our model performed well in estimating population abundance and density-dependent rates of annual recruitment/immigration. Estimates of local carrying capacity and per capita recruitment of yearlings were consistent with those published in other studies. However, our model moderately underestimated annual survival probability of yearling and adult females and severely underestimates survival probabilities for both of these male stages. The most accurate and precise estimates will necessarily require some amount of intensive data collection efforts (such as capture–recapture). Integrated population models that combine data from both intensive and extensive sources are likely to be the most efficient approach for estimating demographic rates at large spatial and temporal scales.
Estimating survival rates with time series of standing age‐structure data
Udevitz, Mark S.; Gogan, Peter J.
2012-01-01
It has long been recognized that age‐structure data contain useful information for assessing the status and dynamics of wildlife populations. For example, age‐specific survival rates can be estimated with just a single sample from the age distribution of a stable, stationary population. For a population that is not stable, age‐specific survival rates can be estimated using techniques such as inverse methods that combine time series of age‐structure data with other demographic data. However, estimation of survival rates using these methods typically requires numerical optimization, a relatively long time series of data, and smoothing or other constraints to provide useful estimates. We developed general models for possibly unstable populations that combine time series of age‐structure data with other demographic data to provide explicit maximum likelihood estimators of age‐specific survival rates with as few as two years of data. As an example, we applied these methods to estimate survival rates for female bison (Bison bison) in Yellowstone National Park, USA. This approach provides a simple tool for monitoring survival rates based on age‐structure data.
Country Demographic Profiles: Thailand.
ERIC Educational Resources Information Center
Bureau of the Census (DOC), Suitland, MD. Population Div.
This profile of the population of Thailand contains 35 tables of selected demographic information, including size of population and estimates of fertility and mortality, beginning in 1950. An adjusted distribution of the population by age and sex is given for the latest census year, as well as for 1976. Projections of the number of women of…
Climate and demography in early prehistory: using calibrated (14)C dates as population proxies.
Riede, Felix
2009-04-01
Although difficult to estimate for prehistoric hunter-gatherer populations, demographic variables-population size, density, and the connectedness of demes-are critical for a better understanding of the processes of material culture change, especially in deep prehistory. Demography is the middle-range link between climatic changes and both biological and cultural evolutionary trajectories of human populations. Much of human material culture functions as a buffer against climatic changes, and the study of prehistoric population dynamics, estimated through changing frequencies of calibrated radiocarbon dates, therefore affords insights into how effectively such buffers operated and when they failed. In reviewing a number of case studies (Mesolithic Ireland, the origin of the Bromme culture, and the earliest late glacial human recolonization of southern Scandinavia), I suggest that a greater awareness of demographic processes, and in particular of demographic declines, provides many fresh insights into what structured the archaeological record. I argue that we cannot sideline climatic and environmental factors or extreme geophysical events in our reconstructions of prehistoric culture change. The implications of accepting demographic variability as a departure point for evaluating the archaeological record are discussed.
Monticelli, David; Ramos, Jaime A.; Hines, James E.; Nichols, James D.; Spendelow, Jeffrey A.
2008-01-01
Many demographic studies on long-lived seabirds have focused on the estimation of adult survival, but much less is known about survival during the early years of life, especially in tropical species. We report analyses of a capture–recapture dataset of 685 roseate terns ringed as fledglings and adults between 1998 and 2005 on Aride Island, Seychelles, and recaptured/resighted at the same colony site over a 5 yr (2002 to 2006) period. A multistate model was used to estimate survival for different age classes, including juvenile (first-year) birds returning as non-breeding prospectors. The effect of infestation by parasites (ticks) on survival was also examined. Overall, the estimated return of first-year individuals to the natal colony was very variable, ranging from 2 to 22%. Conditioned on survival, the probability of returning from Age 2 yr onwards increased to 70%. Survival rates were best modeled as time-specific, with estimates varying from 0.02 to 1.00 (mean 0.69) in first-year birds with a marked negative effect of tick infestation. In older birds (minimum age of 2 yr), the annual estimates fell between 0.69 and 0.86 (mean 0.77). Using a components of variance approach for estimation of year-to-year variation, we found high temporal variability for first-year individuals (coefficient of variation [CV] = 65%) compared to much less variation in the survival rate of older birds (CV = 9%). These findings agree with the life-history prediction that demographic rates of juveniles are usually lower and more variable than those of older individuals. Our results are also consistent with the predicted negative effect of tick parasitism on juvenile survival. Compared with data from other roseate tern populations, survival over the first 2 yr (Age 0 to 2 yr) was 18 to 40% higher in this study, suggesting that a high ‘young’ survival rate may be an important demographic trait in this tropical population to compensate for the low annual reproductive success. Our data show that estimating survival of young individuals may be crucial to elucidating the demographic tactics of seabirds.
Gandjour, A; Ihle, P; Schubert, I
2008-02-01
The purpose of this study was to evaluate the impact of demographic changes on future health care expenditure of the German social health insurances considering the expenditures of survivors and decedents by age. The study analysed data from 269,646 members up to the age of 99 years of the AOK - one of Germany's largest social health insurers - in the State of Hesse in 2000/2001. In order to determine future health care expenditures, per-capita expenditures by age for outpatient, inpatient, rehabilitation, and nursing services of survivors and decedents (death within the next 12 months) were multiplied by the estimated number of survivors and decedents by age in Germany in 2020, 2035 und 2050. Expenditures for all ages were summed together. The paper shows that demographic changes until 2050 will lead to an increase of health care expenditures by 20% in total or less than 1% annually. Considering the future re-duction in workforce, demographic changes until 2050 will result in an estimated increase in health care expenditures per employee by about 57% (undifferentiated model). Considering the cost of survivors and decedents separately, this increase will amount to 50%. Hence, undifferentiated models overestimate the impact of demographic changes by about 10%.
Spatial and temporal demographic variation drives within-season fluctuations in sexual selection.
Kasumovic, Michael M; Bruce, Matthew J; Andrade, Maydianne C B; Herberstein, Marie E
2008-09-01
Our understanding of selection in nature stems mainly from whole-season and cross-sectional estimates of selection gradients. These estimates suggest that selection is relatively constant within, but fluctuates between seasons. However, the strength of selection depends on demographics, and because demographics can vary within seasons, there is a gap in our understanding regarding the extent to which seasonal fluctuations in demographics may cause variation in selection. Here we use two populations of the golden orb-web spider (Nephila plumipes) that differ in density to examine how demographics change within a season and whether there are correlated shifts in selection. We demonstrate that there is within-season variation in sex ratio and density at multiple spatial and temporal scales. This variation led to changes in the competitive challenges that males encountered at different times of the season and was correlated with significant variation in selection gradients on male size and weight between sampling periods. We highlight the importance of understanding the biology of the organism under study to correctly determine the relevant scale in which to examine selection. We also argue that studies may underestimate the true variation in selection by averaging values, leading to misinterpretation of the effect of selection on phenotypic evolution.
Grote, Steffi; Condit, Richard; Hubbell, Stephen; Wirth, Christian; Rüger, Nadja
2013-01-01
For trees in tropical forests, competition for light is thought to be a central process that offers opportunities for niche differentiation through light gradient partitioning. In previous studies, a canopy index based on three-dimensional canopy census data has been shown to be a good predictor of species-specific demographic rates across the entire tree community on Barro Colorado Island, Panama, and has allowed quantifying between-species variation in light response. However, almost all other forest census plots lack data on the canopy structure. Hence, this study aims at assessing whether position-based neighborhood competition indices can replace information from canopy census data and produce similar estimates of the interspecific variation of light responses. We used inventory data from the census plot at Barro Colorado Island and calculated neighborhood competition indices with varying relative effects of the size and distance of neighboring trees. Among these indices, we selected the one that was most strongly correlated with the canopy index. We then compared outcomes of hierarchical Bayesian models for species-specific recruitment and growth rates including either the canopy index or the selected neighborhood competition index as predictor. Mean posterior estimates of light response parameters were highly correlated between models (r>0.85) and indicated that most species regenerate and grow better in higher light. Both light estimation approaches consistently found that the interspecific variation of light response was larger for recruitment than for growth rates. However, the classification of species into different groups of light response, e.g. weaker than linear (decelerating) vs. stronger than linear (accelerating) differed between approaches. These results imply that while the classification into light response groups might be biased when using neighborhood competition indices, they may be useful for determining species rankings and between-species variation of light response and therefore enable large comparative studies between different forest census plots. PMID:24324723
Efficient Moment-Based Inference of Admixture Parameters and Sources of Gene Flow
Levin, Alex; Reich, David; Patterson, Nick; Berger, Bonnie
2013-01-01
The recent explosion in available genetic data has led to significant advances in understanding the demographic histories of and relationships among human populations. It is still a challenge, however, to infer reliable parameter values for complicated models involving many populations. Here, we present MixMapper, an efficient, interactive method for constructing phylogenetic trees including admixture events using single nucleotide polymorphism (SNP) genotype data. MixMapper implements a novel two-phase approach to admixture inference using moment statistics, first building an unadmixed scaffold tree and then adding admixed populations by solving systems of equations that express allele frequency divergences in terms of mixture parameters. Importantly, all features of the model, including topology, sources of gene flow, branch lengths, and mixture proportions, are optimized automatically from the data and include estimates of statistical uncertainty. MixMapper also uses a new method to express branch lengths in easily interpretable drift units. We apply MixMapper to recently published data for Human Genome Diversity Cell Line Panel individuals genotyped on a SNP array designed especially for use in population genetics studies, obtaining confident results for 30 populations, 20 of them admixed. Notably, we confirm a signal of ancient admixture in European populations—including previously undetected admixture in Sardinians and Basques—involving a proportion of 20–40% ancient northern Eurasian ancestry. PMID:23709261
Giesbrecht, Gerald F; Granger, Douglas A; Campbell, Tavis; Kaplan, Bonnie
2013-03-01
Diurnal patterns of salivary alpha amylase (sAA) in pregnant women have not previously been described. The current study employed ecological momentary assessment to examine the association between the diurnal sAA, obstetric history, maternal demographics, and mood during pregnancy. Saliva was self-collected by 83 pregnant women (89% White, age 25.3-43.0 years; mean gestational age 21.9 weeks, range 6-37 weeks; gravida 1-6) at home over three days. Results indicated that current pregnancy (gestational age and fetal sex) and maternal demographics were not related to diurnal sAA. In contrast, a history of previous miscarriage (Parameter = -.17; SE = .05; p < .05) was associated with an atypical diurnal pattern. Even after accounting for obstetric history, trait anxiety (Parameter = .16; SE = .04; p < .001) was associated with increased sAA over the day while chronic levels of fatigue (Parameter = -.06; SE = .03; p < .05) were associated with decreased sAA. In a separate model, we also tested the time varying covariation of sAA and mood. The effects of momentary mood were in contrast to those for trait mood. Both momentary depression (Parameter = .22; SE = .09; p < .01) and vigour/positive mood (Parameter = .12; SE = .04; p < .001) were associated with momentary increases in sAA while momentary anxiety and fatigue were not related to sAA. The findings suggest that basal sAA during pregnancy is sensitive to emotional arousal. Evaluating diurnal patterns of sAA holds promise for advancing understanding of how emotional arousal during pregnancy may affect fetal development. Copyright © 2012 Wiley Periodicals, Inc.
Ait Kaci Azzou, S; Larribe, F; Froda, S
2016-10-01
In Ait Kaci Azzou et al. (2015) we introduced an Importance Sampling (IS) approach for estimating the demographic history of a sample of DNA sequences, the skywis plot. More precisely, we proposed a new nonparametric estimate of a population size that changes over time. We showed on simulated data that the skywis plot can work well in typical situations where the effective population size does not undergo very steep changes. In this paper, we introduce an iterative procedure which extends the previous method and gives good estimates under such rapid variations. In the iterative calibrated skywis plot we approximate the effective population size by a piecewise constant function, whose values are re-estimated at each step. These piecewise constant functions are used to generate the waiting times of non homogeneous Poisson processes related to a coalescent process with mutation under a variable population size model. Moreover, the present IS procedure is based on a modified version of the Stephens and Donnelly (2000) proposal distribution. Finally, we apply the iterative calibrated skywis plot method to a simulated data set from a rapidly expanding exponential model, and we show that the method based on this new IS strategy correctly reconstructs the demographic history. Copyright © 2016. Published by Elsevier Inc.
Estimating risk reduction required to break even in a health promotion program.
Ozminkowski, Ronald J; Goetzel, Ron Z; Santoro, Jan; Saenz, Betty-Jo; Eley, Christine; Gorsky, Bob
2004-01-01
To illustrate a formula to estimate the amount of risk reduction required to break even on a corporate health promotion program. A case study design was implemented. Base year (2001) health risk and medical expenditure data from the company, along with published information on the relationships between employee demographics, health risks, and medical expenditures, were used to forecast demographics, risks, and expenditures for 2002 through 2011 and estimate the required amount of risk reduction. Motorola. 52,124 domestic employees. Demographics included age, gender, race, and job type. Health risks for 2001 were measured via health risk appraisal. Risks were noted as either high or low and related to exercise/eating habits, body weight, blood pressure, blood sugar levels, cholesterol levels, depression, stress, smoking/drinking habits, and seat belt use. Medical claims for 2001 were used to calculate medical expenditures per employee. Assuming a dollar 282 per employee program cost, Motorola employees would need to reduce their lifestyle-related health risks by 1.08% to 1.42% per year to break even on health promotion programming, depending upon the discount rate. Higher or lower program investments would change the risk reduction percentages. Employers can use information from published studies, along with their own data, to estimate the amount of risk reduction required to break even on their health promotion programs.
Rotella, J.J.; Link, W.A.; Chambert, T.; Stauffer, G.E.; Garrott, R.A.
2012-01-01
1.Life-history theory predicts that those vital rates that make larger contributions to population growth rate ought to be more strongly buffered against environmental variability than are those that are less important. Despite the importance of the theory for predicting demographic responses to changes in the environment, it is not yet known how pervasive demographic buffering is in animal populations because the validity of most existing studies has been called into question because of methodological deficiencies. 2.We tested for demographic buffering in the southern-most breeding mammal population in the world using data collected from 5558 known-age female Weddell seals over 30years. We first estimated all vital rates simultaneously with mark-recapture analysis and then estimated process variance and covariance in those rates using a hierarchical Bayesian approach. We next calculated the population growth rate's sensitivity to changes in each of the vital rates and tested for evidence of demographic buffering by comparing properly scaled values of sensitivity and process variance in vital rates. 3.We found evidence of positive process covariance between vital rates, which indicates that all vital rates are affected in the same direction by changes in annual environment. Despite the positive correlations, we found strong evidence that demographic buffering occurred through reductions in variation in the vital rates to which population growth rate was most sensitive. Process variation in vital rates was inversely related to sensitivity measures such that variation was greatest in breeding probabilities, intermediate for survival rates of young animals and lowest for survival rates of older animals. 4.Our work contributes to a small but growing set of studies that have used rigorous methods on long-term, detailed data to investigate demographic responses to environmental variation. The information from these studies improves our understanding of life-history evolution in stochastic environments and provides useful information for predicting population responses to future environmental change. Our results for an Antarctic apex predator also provide useful baselines from a marine ecosystem when its top- and middle-trophic levels were not substantially impacted by human activity. ?? 2011 The Authors. Journal of Animal Ecology ?? 2011 British Ecological Society.
Estimating the absolute wealth of households.
Hruschka, Daniel J; Gerkey, Drew; Hadley, Craig
2015-07-01
To estimate the absolute wealth of households using data from demographic and health surveys. We developed a new metric, the absolute wealth estimate, based on the rank of each surveyed household according to its material assets and the assumed shape of the distribution of wealth among surveyed households. Using data from 156 demographic and health surveys in 66 countries, we calculated absolute wealth estimates for households. We validated the method by comparing the proportion of households defined as poor using our estimates with published World Bank poverty headcounts. We also compared the accuracy of absolute versus relative wealth estimates for the prediction of anthropometric measures. The median absolute wealth estimates of 1,403,186 households were 2056 international dollars per capita (interquartile range: 723-6103). The proportion of poor households based on absolute wealth estimates were strongly correlated with World Bank estimates of populations living on less than 2.00 United States dollars per capita per day (R(2) = 0.84). Absolute wealth estimates were better predictors of anthropometric measures than relative wealth indexes. Absolute wealth estimates provide new opportunities for comparative research to assess the effects of economic resources on health and human capital, as well as the long-term health consequences of economic change and inequality.
Estimating the absolute wealth of households
Gerkey, Drew; Hadley, Craig
2015-01-01
Abstract Objective To estimate the absolute wealth of households using data from demographic and health surveys. Methods We developed a new metric, the absolute wealth estimate, based on the rank of each surveyed household according to its material assets and the assumed shape of the distribution of wealth among surveyed households. Using data from 156 demographic and health surveys in 66 countries, we calculated absolute wealth estimates for households. We validated the method by comparing the proportion of households defined as poor using our estimates with published World Bank poverty headcounts. We also compared the accuracy of absolute versus relative wealth estimates for the prediction of anthropometric measures. Findings The median absolute wealth estimates of 1 403 186 households were 2056 international dollars per capita (interquartile range: 723–6103). The proportion of poor households based on absolute wealth estimates were strongly correlated with World Bank estimates of populations living on less than 2.00 United States dollars per capita per day (R2 = 0.84). Absolute wealth estimates were better predictors of anthropometric measures than relative wealth indexes. Conclusion Absolute wealth estimates provide new opportunities for comparative research to assess the effects of economic resources on health and human capital, as well as the long-term health consequences of economic change and inequality. PMID:26170506
Kim, Michael E; Orth, Robert C; Fallon, Sara C; Lopez, Monica E; Brandt, Mary L; Zhang, Wei; Bisset, George S
2015-04-01
Despite a recent focus on the preferential use of ultrasound over CT for pediatric appendicitis, most children transferred from community hospitals still undergo diagnostic CT scans. The purpose of this study was to evaluate CT techniques performed for children with acute appendicitis at nonpediatric treatment centers. All patients treated for acute appendicitis at our tertiary-care pediatric hospital from July 1, 2011, through June 30, 2012, were identified. Patient demographics, imaging modality used to diagnoses appendicitis (CT or ultrasound), location (home or referral institution), and CT technique parameters were collected. The estimated mean organ radiation dose, number of imaging phases, and use of contrast media were evaluated at home and referral institutions. During the study period, 1215 patients underwent appendectomies after imaging, with 442 (36.4%) imaged at referral facilities. Most referral patients received a diagnosis by CT (n=384, 87%), compared with 73 of 773 (9.4%) who received a diagnosis by CT at the home institution. The estimated mean (±SD) organ radiation dose was not statistically significantly different between home and referral institutions (13.5±7.3 vs 12.9±6.4 mGy; p=0.58) for single-phase examinations. Of 384 referral patients, 344 had images available for review. In total, 40% (138/344) of patients from referral centers were imaged with suboptimal CT techniques: 50 delayed phase only, 52 dual phase (eight of which were imaged twice in delayed phase), eight triple phase, and 36 without IV contrast agent. CT parameters and radiation doses from single-phase examinations in children with appendicitis were similar at nonpediatric treatment centers and a tertiary care children's hospital. Future educational outreach should focus on optimizing other technical parameters.
Prakash, Ravi; Isac, Shajy; Washington, Reynold; Halli, Shiva S.
2016-01-01
Background In Indian context, limited attempts have been made to estimate the mortality risks among people living with HIV (PLHIV). We estimated the rates of mortality among PLHIV covered under an integrated HIV-prevention cum care and support programme implemented in Karnataka state, India, and attempted to identify the key programme components associated with the higher likelihood of their survival. Methods Retrospective programme data of 55,801 PLHIV registered with the Samastha programme implemented in Karnataka state during 2006–11 was used. Kaplan-Meier survival methods were used to estimate the ten years expected survival probabilities and Cox-proportional hazard model was used to examine the factors associated with risk of mortality among PLHIV. We also calculated mortality rates (per 1000 person-year) across selected demographic and clinical parameters. Results Of the total PLHIV registered with the programme, about nine percent died within the 5-years of programme period with an overall death rate of 38 per 1000 person-years. The mortality rate was higher among males, aged 18 and above, among illiterates, and those residing in rural areas. While the presence of co-infections such as Tuberculosis leads to higher mortality rate, adherence to ART was significantly associated with reduction in overall death rate. Cox proportional hazard model revealed that increase in CD4 cell counts and exposure to intensive care and support programme for at least two years can bring significant reduction in risk of death among PLHIV [(hazard ratio: 0.234; CI: 0.211–0.260) & (hazard ratio: 0.062; CI: 0.054–0.071), respectively] even after adjusting the effect of other socio-demographic, economic and health related confounders. Conclusion Study confirms that while residing in rural areas and presence of co-infection significantly increases the mortality risk among PLHIV, adherence to ART and improvement in CD4 counts led to significant reduction in their mortality risk. Longer exposure to the intervention contributed significantly to reduce mortality among PLHIV. PMID:27253974
NASA Astrophysics Data System (ADS)
Tong, M.; Xue, M.
2006-12-01
An important source of model error for convective-scale data assimilation and prediction is microphysical parameterization. This study investigates the possibility of estimating up to five fundamental microphysical parameters, which are closely involved in the definition of drop size distribution of microphysical species in a commonly used single-moment ice microphysics scheme, using radar observations and the ensemble Kalman filter method. The five parameters include the intercept parameters for rain, snow and hail/graupel, and the bulk densities of hail/graupel and snow. Parameter sensitivity and identifiability are first examined. The ensemble square-root Kalman filter (EnSRF) is employed for simultaneous state and parameter estimation. OSS experiments are performed for a model-simulated supercell storm, in which the five microphysical parameters are estimated individually or in different combinations starting from different initial guesses. When error exists in only one of the microphysical parameters, the parameter can be successfully estimated without exception. The estimation of multiple parameters is found to be less robust, with end results of estimation being sensitive to the realization of the initial parameter perturbation. This is believed to be because of the reduced parameter identifiability and the existence of non-unique solutions. The results of state estimation are, however, always improved when simultaneous parameter estimation is performed, even when the estimated parameters values are not accurate.
An analysis of population and social change in London wards in the 1980s.
Congdon, P
1989-01-01
"This paper discusses the estimation and projection of small area populations in London, [England] and considers trends in intercensal social and demographic indices which can be calculated using these estimates. Information available annually on vital statistics and electorates is combined with detailed data from the Census Small Area Statistics to derive demographic component based population estimates for London's electoral wards over five year periods. The availability of age disaggregated population estimates permits derivation of small area social indicators for intercensal years, for example, of unemployment and mortality. Trends in spatial inequality of such indicators during the 1980s are analysed and point to continuing wide differentials. A typology of population and social indicators gives an indication of the small area distribution of the recent population turnaround in inner London, and of its association with other social processes such as gentrification and ethnic concentration." excerpt
Combining band recovery data and Pollock's robust design to model temporary and permanent emigration
Lindberg, M.S.; Kendall, W.L.; Hines, J.E.; Anderson, M.G.
2001-01-01
Capture-recapture models are widely used to estimate demographic parameters of marked populations. Recently, this statistical theory has been extended to modeling dispersal of open populations. Multistate models can be used to estimate movement probabilities among subdivided populations if multiple sites are sampled. Frequently, however, sampling is limited to a single site. Models described by Burnham (1993, in Marked Individuals in the Study of Bird Populations, 199-213), which combined open population capture-recapture and band-recovery models, can be used to estimate permanent emigration when sampling is limited to a single population. Similarly, Kendall, Nichols, and Hines (1997, Ecology 51, 563-578) developed models to estimate temporary emigration under Pollock's (1982, Journal of Wildlife Management 46, 757-760) robust design. We describe a likelihood-based approach to simultaneously estimate temporary and permanent emigration when sampling is limited to a single population. We use a sampling design that combines the robust design and recoveries of individuals obtained immediately following each sampling period. We present a general form for our model where temporary emigration is a first-order Markov process, and we discuss more restrictive models. We illustrate these models with analysis of data on marked Canvasback ducks. Our analysis indicates that probability of permanent emigration for adult female Canvasbacks was 0.193 (SE = 0.082) and that birds that were present at the study area in year i - 1 had a higher probability of presence in year i than birds that were not present in year i - 1.
Population, internal migration, and economic growth: an empirical analysis.
Moreland, R S
1982-01-01
The role of population growth in the development process has received increasing attention during the last 15 years, as manifested in the literature in 3 broad categories. In the 1st category, the effects of rapid population growth on the growth of income have been studied with the use of simulation models, which sometimes include endogenous population growth. The 2nd category of the literature is concerned with theoretical and empirical studies of the economic determinants of various demographic rates--most usually fertility. Internal migration and dualism is the 3rd population development category to recieve attention. An attempt is made to synthesize developments in these 3 categories by estimating from a consistent set of data a 2 sector economic demographic model in which the major demographic rates are endogenous. Due to the fact that the interactions between economic and demographic variables are nonlinear and complex, the indirect effects of changes in a particular variable may depend upon the balance of numerical coefficients. For this reason it was felt that the model should be empirically grounded. A brief overview of the model is provided, and the model is compared to some similar existing models. Estimation of the model's 9 behavior equations is discussed, followed by a "base run" simulation of a developing country "stereotype" and a report of a number of policy experiments. The relatively new field of economic determinants of demographic variables was drawn upon in estimating equations to endogenize demographic phenomena that are frequently left exogenous in simulation models. The fertility and labor force participation rate functions are fairly standard, but a step beyong existing literature was taken in the life expectancy and intersectorial migration equations. On the economic side, sectoral savings functions were estimated, and it was found that the marginal propensity to save is lower in agriculture than in nonagriculture. Testing to see the effect of a population's age structure on savings rather than assuming a particular direction as Coale-Hoover and Simon do in their models, it was found that a higher proportion of children compete with savings in agriculture but complement savings in industrial areas. This was consistent with the economic value of children in agricultural and nonagricultural regions of less developed countries. The estimated production functions showed that marginal products of labor were considerably higher in agriculture than in nonagriculture. As with other simulation models, the effect of reducing fertility was to accelerate income growth. Reductions in rural fertility were more equitable and raised the overall level of per capita income more than similar efforts directed to urban areas only.
Hightower, Joseph E.; Pollock, Kenneth H.
2013-01-01
Striped bass Morone saxatilis in inland reservoirs play an important role ecologically and in supporting recreational fishing. To manage these populations, biologists need information about abundance and mortality. Abundance estimates can be used to assess the effectiveness of stocking programs that maintain most reservoir striped bass populations. Mortality estimates can indicate the relative impact of fishing versus natural mortality and the need for harvest regulation. The purpose of this chapter is to evaluate tagging studies as a way of obtaining information about abundance and mortality. These approaches can be grouped into three broad categories: tag recapture, tag return, and telemetry. Tag-recapture methods are typically used to estimate population size and other demographic parameters but are often difficult to apply in large systems. A fishing tournament can be an effective way of generating tagging or recapture effort in large systems, compared to using research sampling only. Tag-return methods that rely on angler harvest and catch and release can be used to estimate fishing (F) and natural (M) mortality rates and are a practical approach in large reservoirs. The key to success in tag-return studies is to build in auxiliary studies to estimate short-term tagging mortality, short- and longterm tag loss, reporting rate, and mortality associated with catch and release. F and M can also be estimated using telemetry tags. Advantages of this approach are that angler nonreporting does not bias estimates and fish with transmitters provide useful ecological data. Cost can be a disadvantage of telemetry studies; thus, combining telemetry tags with conventional tag returns in an integrated analysis is often the optimal approach. In summary, tagging methods can be a powerful tool for assessing the effectiveness of inland striped bass stocking programs and the relative impact of fishing versus natural mortality
Mitchell, Lewis; Frank, Morgan R.; Harris, Kameron Decker; Dodds, Peter Sheridan; Danforth, Christopher M.
2013-01-01
We conduct a detailed investigation of correlations between real-time expressions of individuals made across the United States and a wide range of emotional, geographic, demographic, and health characteristics. We do so by combining (1) a massive, geo-tagged data set comprising over 80 million words generated in 2011 on the social network service Twitter and (2) annually-surveyed characteristics of all 50 states and close to 400 urban populations. Among many results, we generate taxonomies of states and cities based on their similarities in word use; estimate the happiness levels of states and cities; correlate highly-resolved demographic characteristics with happiness levels; and connect word choice and message length with urban characteristics such as education levels and obesity rates. Our results show how social media may potentially be used to estimate real-time levels and changes in population-scale measures such as obesity rates. PMID:23734200
Mitchell, Lewis; Frank, Morgan R; Harris, Kameron Decker; Dodds, Peter Sheridan; Danforth, Christopher M
2013-01-01
We conduct a detailed investigation of correlations between real-time expressions of individuals made across the United States and a wide range of emotional, geographic, demographic, and health characteristics. We do so by combining (1) a massive, geo-tagged data set comprising over 80 million words generated in 2011 on the social network service Twitter and (2) annually-surveyed characteristics of all 50 states and close to 400 urban populations. Among many results, we generate taxonomies of states and cities based on their similarities in word use; estimate the happiness levels of states and cities; correlate highly-resolved demographic characteristics with happiness levels; and connect word choice and message length with urban characteristics such as education levels and obesity rates. Our results show how social media may potentially be used to estimate real-time levels and changes in population-scale measures such as obesity rates.
Liu, Shenglin; Hansen, Michael M; Jacobsen, Magnus W
2016-10-01
We analysed 81 whole genome sequences of threespine sticklebacks from Pacific North America, Greenland and Northern Europe, representing 16 populations. Principal component analysis of nuclear SNPs grouped populations according to geographical location, with Pacific populations being more divergent from each other relative to European and Greenlandic populations. Analysis of mitogenome sequences showed Northern European populations to represent a single phylogeographical lineage, whereas Greenlandic and particularly Pacific populations showed admixture between lineages. We estimated demographic history using a genomewide coalescence with recombination approach. The Pacific populations showed gradual population expansion starting >100 Kya, possibly reflecting persistence in cryptic refuges near the present distributional range, although we do not rule out possible influence of ancient admixture. Sharp population declines ca. 14-15 Kya were suggested to reflect founding of freshwater populations by marine ancestors. In Greenland and Northern Europe, demographic expansion started ca. 20-25 Kya coinciding with the end of the Last Glacial Maximum. In both regions, marine and freshwater populations started to show different demographic trajectories ca. 8-9 Kya, suggesting that this was the time of recolonization. In Northern Europe, this estimate was surprisingly late, but found support in subfossil evidence for presence of several freshwater fish species but not sticklebacks 12 Kya. The results demonstrate distinctly different demographic histories across geographical regions with potential consequences for adaptive processes. They also provide empirical support for previous assumptions about freshwater populations being founded independently from large, coherent marine populations, a key element in the Transporter Hypothesis invoked to explain the widespread occurrence of parallel evolution across freshwater stickleback populations. © 2016 John Wiley & Sons Ltd.
Gebru, Timnit; Krause, Jonathan; Wang, Yilun; Chen, Duyun; Deng, Jia; Aiden, Erez Lieberman; Fei-Fei, Li
2017-01-01
The United States spends more than $250 million each year on the American Community Survey (ACS), a labor-intensive door-to-door study that measures statistics relating to race, gender, education, occupation, unemployment, and other demographic factors. Although a comprehensive source of data, the lag between demographic changes and their appearance in the ACS can exceed several years. As digital imagery becomes ubiquitous and machine vision techniques improve, automated data analysis may become an increasingly practical supplement to the ACS. Here, we present a method that estimates socioeconomic characteristics of regions spanning 200 US cities by using 50 million images of street scenes gathered with Google Street View cars. Using deep learning-based computer vision techniques, we determined the make, model, and year of all motor vehicles encountered in particular neighborhoods. Data from this census of motor vehicles, which enumerated 22 million automobiles in total (8% of all automobiles in the United States), were used to accurately estimate income, race, education, and voting patterns at the zip code and precinct level. (The average US precinct contains ∼1,000 people.) The resulting associations are surprisingly simple and powerful. For instance, if the number of sedans encountered during a drive through a city is higher than the number of pickup trucks, the city is likely to vote for a Democrat during the next presidential election (88% chance); otherwise, it is likely to vote Republican (82%). Our results suggest that automated systems for monitoring demographics may effectively complement labor-intensive approaches, with the potential to measure demographics with fine spatial resolution, in close to real time. PMID:29183967
Gebru, Timnit; Krause, Jonathan; Wang, Yilun; Chen, Duyun; Deng, Jia; Aiden, Erez Lieberman; Fei-Fei, Li
2017-12-12
The United States spends more than $250 million each year on the American Community Survey (ACS), a labor-intensive door-to-door study that measures statistics relating to race, gender, education, occupation, unemployment, and other demographic factors. Although a comprehensive source of data, the lag between demographic changes and their appearance in the ACS can exceed several years. As digital imagery becomes ubiquitous and machine vision techniques improve, automated data analysis may become an increasingly practical supplement to the ACS. Here, we present a method that estimates socioeconomic characteristics of regions spanning 200 US cities by using 50 million images of street scenes gathered with Google Street View cars. Using deep learning-based computer vision techniques, we determined the make, model, and year of all motor vehicles encountered in particular neighborhoods. Data from this census of motor vehicles, which enumerated 22 million automobiles in total (8% of all automobiles in the United States), were used to accurately estimate income, race, education, and voting patterns at the zip code and precinct level. (The average US precinct contains ∼1,000 people.) The resulting associations are surprisingly simple and powerful. For instance, if the number of sedans encountered during a drive through a city is higher than the number of pickup trucks, the city is likely to vote for a Democrat during the next presidential election (88% chance); otherwise, it is likely to vote Republican (82%). Our results suggest that automated systems for monitoring demographics may effectively complement labor-intensive approaches, with the potential to measure demographics with fine spatial resolution, in close to real time. Copyright © 2017 the Author(s). Published by PNAS.
Norton, Aaron T.; Allen, Thomas J.; Sims, Charles L.
2010-01-01
Using data from a US national probability sample of self-identified lesbian, gay, and bisexual adults (N = 662), this article reports population parameter estimates for a variety of demographic, psychological, and social variables. Special emphasis is given to information with relevance to public policy and law. Compared with the US adult population, respondents were younger, more highly educated, and less likely to be non-Hispanic White, but differences were observed between gender and sexual orientation groups on all of these variables. Overall, respondents tended to be politically liberal, not highly religious, and supportive of marriage equality for same-sex couples. Women were more likely than men to be in a committed relationship. Virtually all coupled gay men and lesbians had a same-sex partner, whereas the vast majority of coupled bisexuals were in a heterosexual relationship. Compared with bisexuals, gay men and lesbians reported stronger commitment to a sexual-minority identity, greater community identification and involvement, and more extensive disclosure of their sexual orientation to others. Most respondents reported experiencing little or no choice about their sexual orientation. The importance of distinguishing among lesbians, gay men, bisexual women, and bisexual men in behavioral and social research is discussed. PMID:20835383
Gottscho, Andrew D; Marks, Sharyn B; Jennings, W Bryan
2014-01-01
The North American deserts were impacted by both Neogene plate tectonics and Quaternary climatic fluctuations, yet it remains unclear how these events influenced speciation in this region. We tested published hypotheses regarding the timing and mode of speciation, population structure, and demographic history of the Mojave Fringe-toed Lizard (Uma scoparia), a sand dune specialist endemic to the Mojave Desert of California and Arizona. We sampled 109 individual lizards representing 22 insular dune localities, obtained DNA sequences for 14 nuclear loci, and found that U. scoparia has low genetic diversity relative to the U. notata species complex, comparable to that of chimpanzees and southern elephant seals. Analyses of genotypes using Bayesian clustering algorithms did not identify discrete populations within U. scoparia. Using isolation-with-migration (IM) models and a novel coalescent-based hypothesis testing approach, we estimated that U. scoparia diverged from U. notata in the Pleistocene epoch. The likelihood ratio test and the Akaike Information Criterion consistently rejected nested speciation models that included parameters for migration and population growth of U. scoparia. We reject the Neogene vicariance hypothesis for the speciation of U. scoparia and define this species as a single evolutionarily significant unit for conservation purposes. PMID:25360285
Growth of children living in the outskirts of Ankara: impact of low socio-economic status.
Gültekin, Timur; Hauspie, Roland; Susanne, Charles; Güleç, Erksin
2006-01-01
Most studies of the growth of Turkish schoolchildren are limited to large cities and to subjects from high socio-economic background. Very little is known about growth and development of rural, suburban and low socio-economic children in Turkey. The purpose of this study is to compare height and weight of school-aged children of low socio-economic background with available growth data from high socio-economic strata, and to verify the possible influences of three socio-demographic parameters on their growth. The sample consisted of 1,052 girls and 1,223 boys, aged between 7-17 years, living in the outskirts of Ankara, a suburban area of poor socio-economic background. Centile distributions for height and weight were estimated by the LMS-method. ANOVA and Student's t-test were used to compare mean z-scores for height and weight among the various categories of the socio-demographic parameters. Children living in the outskirts of Ankara have lower mean values for height and weight when compared with growth data of upper socio-economic strata children. The differences were most pronounced during adolescence. Skinfolds were higher in girls than in boys at all ages (largest p = 0.007). There was no clear relationship between growth and the number of siblings, the number of rooms in the house, the mother's and father's education, and the father's professional status (p > 0.05), except for the height of girls (p < 0.05). It is suggested that the lower growth status of children living in the outskirts of Ankara is attributable to the poor socio-economic status of this suburban population, which has not changed over the past decades. It is postulated that the growth impairment during adolescence might be due to a reduced tempo of growth in these children.
Does Physiological Stress Slow Down Wound Healing in Patients With Diabetes?
Razjouyan, Javad; Grewal, Gurtej Singh; Talal, Talal K.; Armstrong, David G.; Mills, Joseph L.; Najafi, Bijan
2017-01-01
Background: Poor healing is an important contributing factor to amputation among patients with diabetic foot ulcers (DFUs). Physiological stress may slow wound healing and increase susceptibility to infection. Objectives: The objective was to examine the association between heart rate variability (HRV) as an indicator of physiological stress response and healing speed (HealSpeed) among outpatients with active DFUs. Design and Methods: Ambulatory patients with diabetes with DFUs (n = 25, age: 59.3 ± 8.3 years) were recruited. HRV during pre–wound dressing was measured using a wearable sensor attached to participants’ chest. HRVs were quantified in both time and frequency domains to assess physiological stress response and vagal tone (relaxation). Change in wound size between two consecutive visits was used to estimate HealSpeed. Participants were then categorized into slow healing and fast healing groups. Between the two groups, comparisons were performed for demographic, clinical, and HRV derived parameters. Associations between different descriptors of HRV and HealSpeed were also assessed. Results: HealSpeed was significantly correlated with both vagal tone (r = –.705, P = .001) and stress response (r = .713, P = .001) extracted from frequency domain. No between-group differences were observed except those from HRV-derived parameters. Models based on HRVs were the highest predictors of slow/fast HealSpeed (AUC > 0.90), while models based on demographic and clinical information had poor classification performance (AUC = 0.44). Conclusion: This study confirms an association between stress/vagal tone and wound healing in patients with DFUs. In particular, it highlights the importance of vagal tone (relaxation) in expediting wound healing. It also demonstrates the feasibility of assessing physiological stress responses using wearable technology in outpatient clinic during routine clinic visits. PMID:28436270
A discrete stage-structured model of California newt population dynamics during a period of drought.
Jones, Marjorie T; Milligan, William R; Kats, Lee B; Vandergon, Thomas L; Honeycutt, Rodney L; Fisher, Robert N; Davis, Courtney L; Lucas, Timothy A
2017-02-07
We introduce a mathematical model for studying the population dynamics under drought of the California newt (Taricha torosa), a species of special concern in the state of California. Since 2012, California has experienced a record-setting drought, and multiple studies predict drought conditions currently underway will persist and even increase in severity. Recent declines and local extinctions of California newt populations in Santa Monica Mountain streams motivate our study of the impact of drought on newt population sizes. Although newts are terrestrial salamanders, they migrate to streams each spring to breed and lay eggs. Since egg and larval stages occur in water, a precipitation deficit due to drought conditions reduces the space for newt egg-laying and the necessary habitat for larval development. To mathematically forecast newt population dynamics, we develop a nonlinear system of discrete equations that includes demographic parameters such as survival rates for newt life stages and egg production, which depend on habitat availability and rainfall. We estimate these demographic parameters using 15 years of stream survey data collected from Cold Creek in Los Angeles County, California, and our model captures the observed decline of the parameterized Cold Creek newt population. Based upon data analysis, we predict how the number of available newt egg-laying sites varies with annual precipitation. Our model allows us to make predictions about how the length and severity of drought can affect the likelihood of persistence and the time to critical endangerment of a local newt population. We predict that sustained severe drought will critically endanger the newt population but that the newt population can rebound if a drought is sufficiently short. Copyright © 2016 Elsevier Ltd. All rights reserved.
Does Physiological Stress Slow Down Wound Healing in Patients With Diabetes?
Razjouyan, Javad; Grewal, Gurtej Singh; Talal, Talal K; Armstrong, David G; Mills, Joseph L; Najafi, Bijan
2017-07-01
Poor healing is an important contributing factor to amputation among patients with diabetic foot ulcers (DFUs). Physiological stress may slow wound healing and increase susceptibility to infection. The objective was to examine the association between heart rate variability (HRV) as an indicator of physiological stress response and healing speed (Heal Speed ) among outpatients with active DFUs. Ambulatory patients with diabetes with DFUs (n = 25, age: 59.3 ± 8.3 years) were recruited. HRV during pre-wound dressing was measured using a wearable sensor attached to participants' chest. HRVs were quantified in both time and frequency domains to assess physiological stress response and vagal tone (relaxation). Change in wound size between two consecutive visits was used to estimate Heal Speed . Participants were then categorized into slow healing and fast healing groups. Between the two groups, comparisons were performed for demographic, clinical, and HRV derived parameters. Associations between different descriptors of HRV and Heal Speed were also assessed. Heal Speed was significantly correlated with both vagal tone ( r = -.705, P = .001) and stress response ( r = .713, P = .001) extracted from frequency domain. No between-group differences were observed except those from HRV-derived parameters. Models based on HRVs were the highest predictors of slow/fast Heal Speed (AUC > 0.90), while models based on demographic and clinical information had poor classification performance (AUC = 0.44). This study confirms an association between stress/vagal tone and wound healing in patients with DFUs. In particular, it highlights the importance of vagal tone (relaxation) in expediting wound healing. It also demonstrates the feasibility of assessing physiological stress responses using wearable technology in outpatient clinic during routine clinic visits.
A discrete stage-structured model of California newt population dynamics during a period of drought
Jones, Marjorie T.; Milligan, William R.; Kats, Lee B.; Vandergon, Thomas L.; Honeycutt, Rodney L.; Fisher, Robert N.; Davis, Courtney L.; Lucas, Timothy A.
2017-01-01
We introduce a mathematical model for studying the population dynamics under drought of the California newt (Taricha torosa), a species of special concern in the state of California. Since 2012, California has experienced a record-setting drought, and multiple studies predict drought conditions currently underway will persist and even increase in severity. Recent declines and local extinctions of California newt populations in Santa Monica Mountain streams motivate our study of the impact of drought on newt population sizes. Although newts are terrestrial salamanders, they migrate to streams each spring to breed and lay eggs. Since egg and larval stages occur in water, a precipitation deficit due to drought conditions reduces the space for newt egg-laying and the necessary habitat for larval development. To mathematically forecast newt population dynamics, we develop a nonlinear system of discrete equations that includes demographic parameters such as survival rates for newt life stages and egg production, which depend on habitat availability and rainfall. We estimate these demographic parameters using 15 years of stream survey data collected from Cold Creek in Los Angeles County, California, and our model captures the observed decline of the parameterized Cold Creek newt population. Based upon data analysis, we predict how the number of available newt egg-laying sites varies with annual precipitation. Our model allows us to make predictions about how the length and severity of drought can affect the likelihood of persistence and the time to critical endangerment of a local newt population. We predict that sustained severe drought will critically endanger the newt population but that the newt population can rebound if a drought is sufficiently short.
Iseki, Naoyuki; Sasaki, Akira; Toju, Hirokazu
2011-09-21
The geographical cline of the coevolving traits of weevil rostrum (mouthpart) length and camellia pericarp (fruit coat) thickness provides an opportunity to test the arms race theory of defense (pericarp thickness) and countermeasure (rostrum length) between antagonistically interacting species. By extending the previous model for the coevolution of quantitative traits to introduce nonlinear costs for exaggerated traits, the generation overlap, and density-dependent regulation in the host, we studied the evolutionarily stable (ES) pericarp thickness in the Japanese camellia (Camellia japonica) and the ES rostrum length in the camellia-weevil (Curculio camelliae). The joint monomorphic ES system has a robust outcome with nonlinear costs, and we analyzed how the traits of both species at evolutionary equilibrium depend on demographic parameters. If camellia demographic parameters vary latitudinally, data collected over the geographical scale of rostrum length and pericarp thickness should lie on an approximately linear curve with the slope less than that of the equiprobability line A/B of boring success, where A and B are coefficients for the logistic regression of boring success to pericarp thickness and rostrum length, respectively. This is a robust prediction as long as the cost of rostrum length is nonlinear (accelerating). As a result, boring success should be lower in populations with longer rostrum length, as reported in the weevil-camellia system (Toju, H., and Sota, T., 2006a. Imbalance of predator and prey armament: Geographic clines in phenotypic interface and natural selection. American Naturalist 167, 105-117). The nonlinearity (exponent) for the cost of rostrum length estimated from the geographical cline data for the weevil-camellia system was 2.2, suggesting nonlinearity between quadratic and cubic forms. Copyright © 2011 Elsevier Ltd. All rights reserved.
Alexander, Erica S; Hankins, Carol A; Machan, Jason T; Healey, Terrance T; Dupuy, Damian E
2013-03-01
To retrospectively identify the incidence and probable risk factors for rib fractures after percutaneous radiofrequency ablation (RFA) and microwave ablation (MWA) of neoplasms in the lung and to identify complications related to these fractures. Institutional review board approval was obtained for this HIPAA-compliant retrospective study. Study population was 163 patients treated with MWA and/or RFA for 195 lung neoplasms between February 2004 and April 2010. Follow-up computed tomographic images of at least 3 months were retrospectively reviewed by board-certified radiologists to determine the presence of rib fractures. Generalized estimating equations were performed to assess the effect that patient demographics, tumor characteristics, treatment parameters, and ablation zone characteristics had on development of rib fractures. Kaplan-Meier curve was used to estimate patients' probability of rib fracture after ablation as a function of time. Clinical parameters (ie, pain in ribs or chest, organ damage caused by fractured rib) were evaluated for patients with confirmed fracture. Rib fractures in proximity to the ablation zone were found in 13.5% (22 of 163) of patients. Estimated probability of fracture was 9% at 1 year and 22% at 3 years. Women were more likely than were men to develop fracture after ablation (P = .041). Patients with tumors closer to the chest wall were more likely to develop fracture (P = .0009), as were patients with ablation zones that involved visceral pleura (P = .039). No patients with rib fractures that were apparently induced by RFA and MWA had organ injury or damage related to fracture, and 9.1% (2 of 22) of patients reported mild pain. Rib fractures were present in 13.5% of patients after percutaneous RFA and MWA of lung neoplasms. Patients who had ablations performed close to the chest wall should be monitored for rib fractures.
Fertility, Human Capital, and Economic Growth over the Demographic Transition
Mason, Andrew
2009-01-01
Do low fertility and population aging lead to economic decline if couples have fewer children, but invest more in each child? By addressing this question, this article extends previous work in which the authors show that population aging leads to an increased demand for wealth that can, under some conditions, lead to increased capital per worker and higher per capita consumption. This article is based on an overlapping generations (OLG) model which highlights the quantity–quality tradeoff and the links between human capital investment and economic growth. It incorporates new national level estimates of human capital investment produced by the National Transfer Accounts project. Simulation analysis is employed to show that, even in the absence of the capital dilution effect, low fertility leads to higher per capita consumption through human capital accumulation, given plausible model parameters. PMID:20495605
Bhatia, Triptish; Gettig, Elizabeth A; Gottesman, Irving I; Berliner, Jonathan; Mishra, N N; Nimgaonkar, Vishwajit L; Deshpande, Smita N
2016-12-01
Schizophrenia (SZ) has an estimated heritability of 64-88%, with the higher values based on twin studies. Conventionally, family history of psychosis is the best individual-level predictor of risk, but reliable risk estimates are unavailable for Indian populations. Genetic, environmental, and epigenetic factors are equally important and should be considered when predicting risk in 'at risk' individuals. To estimate risk based on an Indian schizophrenia participant's family history combined with selected demographic factors. To incorporate variables in addition to family history, and to stratify risk, we constructed a regression equation that included demographic variables in addition to family history. The equation was tested in two independent Indian samples: (i) an initial sample of SZ participants (N=128) with one sibling or offspring; (ii) a second, independent sample consisting of multiply affected families (N=138 families, with two or more sibs/offspring affected with SZ). The overall estimated risk was 4.31±0.27 (mean±standard deviation). There were 19 (14.8%) individuals in the high risk group, 75 (58.6%) in the moderate risk and 34 (26.6%) in the above average risk (in Sample A). In the validation sample, risks were distributed as: high (45%), moderate (38%) and above average (17%). Consistent risk estimates were obtained from both samples using the regression equation. Familial risk can be combined with demographic factors to estimate risk for SZ in India. If replicated, the proposed stratification of risk may be easier and more realistic for family members. Copyright © 2016. Published by Elsevier B.V.
Role of demographic stochasticity in a speciation model with sexual reproduction
NASA Astrophysics Data System (ADS)
Lafuerza, Luis F.; McKane, Alan J.
2016-03-01
Recent theoretical studies have shown that demographic stochasticity can greatly increase the tendency of asexually reproducing phenotypically diverse organisms to spontaneously evolve into localized clusters, suggesting a simple mechanism for sympatric speciation. Here we study the role of demographic stochasticity in a model of competing organisms subject to assortative mating. We find that in models with sexual reproduction, noise can also lead to the formation of phenotypic clusters in parameter ranges where deterministic models would lead to a homogeneous distribution. In some cases, noise can have a sizable effect, rendering the deterministic modeling insufficient to understand the phenotypic distribution.
English Language Learners in America's Great City Schools: Demographics, Achievement and Staffing
ERIC Educational Resources Information Center
Uro, Gabriela; Barrio, Alejandra
2013-01-01
English Language Learners (ELLs) are among the fastest-growing demographic group in U.S. public schools. There are numerous recent reports documenting this phenomenon. Some reports estimate the numbers of ELLs enrolled in U.S. public schools, and other reports approximate the growth in ELL enrollment over the past five to ten years. Still, there…
ERIC Educational Resources Information Center
Costa-Font, Joan; Wittenberg, Raphael; Patxot, Concepcio; Comas-Herrera, Adelina; Gori, Cristiano; di Maio, Alessandra; Pickard, Linda; Pozzi, Alessandro; Rothgang, Heinz
2008-01-01
This study examines the sensitivity of future long-term care demand and expenditure estimates to official demographic projections in four selected European countries: Germany, Spain, Italy and the United Kingdom. It uses standardised methodology in the form of a macro-simulation exercise and finds evidence for significant differences in…
Demographic trends in Claremont California’s street tree population
Natalie S. van Doorn; E. Gregory McPherson
2018-01-01
The aim of this study was to quantify street tree population dynamics in the city of Claremont, CA. A repeated measures survey (2000 and 2014) based on a stratified random sampling approach across size classes and for the most abundant 21 species was analyzed to calculate removal, growth, and replacement planting rates. Demographic rates were estimated using a...
Attitude determination and parameter estimation using vector observations - Theory
NASA Technical Reports Server (NTRS)
Markley, F. Landis
1989-01-01
Procedures for attitude determination based on Wahba's loss function are generalized to include the estimation of parameters other than the attitude, such as sensor biases. Optimization with respect to the attitude is carried out using the q-method, which does not require an a priori estimate of the attitude. Optimization with respect to the other parameters employs an iterative approach, which does require an a priori estimate of these parameters. Conventional state estimation methods require a priori estimates of both the parameters and the attitude, while the algorithm presented in this paper always computes the exact optimal attitude for given values of the parameters. Expressions for the covariance of the attitude and parameter estimates are derived.
Predictors of early survival in Soay sheep: cohort-, maternal- and individual-level variation
Jones, Owen R; Crawley, Michael J; Pilkington, Jill G; Pemberton, Josephine M
2005-01-01
A demographic understanding of population dynamics requires an appreciation of the processes influencing survival—a demographic rate influenced by parameters varying at the individual, maternal and cohort level. There have been few attempts to partition the variance in demography contributed by each of these parameter types. Here, we use data from a feral population of Soay sheep (Ovis aries), from the island of St Kilda, to explore the relative importance of these parameter types on early survival. We demonstrate that the importance of variation occurring at the level of the individual, and maternally, far outweighs that occurring at the cohort level. The most important variables within the individual and maternal levels were birth weight and maternal age class, respectively. This work underlines the importance of using individual based models in ecological demography and we, therefore, caution against studies that focus solely on population processes. PMID:16321784
Population viability analysis with species occurrence data from museum collections.
Skarpaas, Olav; Stabbetorp, Odd E
2011-06-01
The most comprehensive data on many species come from scientific collections. Thus, we developed a method of population viability analysis (PVA) in which this type of occurrence data can be used. In contrast to classical PVA, our approach accounts for the inherent observation error in occurrence data and allows the estimation of the population parameters needed for viability analysis. We tested the sensitivity of the approach to spatial resolution of the data, length of the time series, sampling effort, and detection probability with simulated data and conducted PVAs for common, rare, and threatened species. We compared the results of these PVAs with results of standard method PVAs in which observation error is ignored. Our method provided realistic estimates of population growth terms and quasi-extinction risk in cases in which the standard method without observation error could not. For low values of any of the sampling variables we tested, precision decreased, and in some cases biased estimates resulted. The results of our PVAs with the example species were consistent with information in the literature on these species. Our approach may facilitate PVA for a wide range of species of conservation concern for which demographic data are lacking but occurrence data are readily available. ©2011 Society for Conservation Biology.
Handling nonresponse in surveys: analytic corrections compared with converting nonresponders.
Jenkins, Paul; Earle-Richardson, Giulia; Burdick, Patrick; May, John
2008-02-01
A large health survey was combined with a simulation study to contrast the reduction in bias achieved by double sampling versus two weighting methods based on propensity scores. The survey used a census of one New York county and double sampling in six others. Propensity scores were modeled as a logistic function of demographic variables and were used in conjunction with a random uniform variate to simulate response in the census. These data were used to estimate the prevalence of chronic disease in a population whose parameters were defined as values from the census. Significant (p < 0.0001) predictors in the logistic function included multiple (vs. single) occupancy (odds ratio (OR) = 1.3), bank card ownership (OR = 2.1), gender (OR = 1.5), home ownership (OR = 1.3), head of household's age (OR = 1.4), and income >$18,000 (OR = 0.8). The model likelihood ratio chi-square was significant (p < 0.0001), with the area under the receiver operating characteristic curve = 0.59. Double-sampling estimates were marginally closer to population values than those from either weighting method. However, the variance was also greater (p < 0.01). The reduction in bias for point estimation from double sampling may be more than offset by the increased variance associated with this method.
Cataife, Guido
2014-03-01
We propose the use of previously developed small area estimation techniques to monitor obesity and dietary habits in developing countries and apply the model to Rio de Janeiro city. We estimate obesity prevalence rates at the Census Tract through a combinatorial optimization spatial microsimulation model that matches body mass index and socio-demographic data in Brazil's 2008-9 family expenditure survey with Census 2010 socio-demographic data. Obesity ranges from 8% to 25% in most areas and affects the poor almost as much as the rich. Male and female obesity rates are uncorrelated at the small area level. The model is an effective tool to understand the complexity of the problem and to aid in policy design. © 2013 Published by Elsevier Ltd.
A new estimate of Ukrainian population losses during the crises of the 1930s and 1940s.
Vallin, Jacques; Meslé, France; Adamets, Serguei; Pyrozhkov, Serhii
2002-11-01
Ukraine experienced two very acute demographic crises during the Soviet era: the 1933 famine and the Second World War. While different estimates of total losses have been produced previously, we have tried here to distinguish the specific impact of the crises on mortality from their impact on fertility and migration. Taking into account all existing sources of registered data and estimates, a painstaking reconstruction of annual demographic changes has been produced and complete annual life tables have been computed for the years 1926-59. Life expectancy at birth fell to a level as low as 10 years for females and 7 for males in 1933 and plateaued around 25 for females and 15 for males in the period 1941-44.
Schwartz, Charles C.; Haroldson, Mark A.; White, Gary C.; Harris, Richard B.; Cherry, Steve; Keating, Kim A.; Moody, Dave; Servheen, Christopher
2006-01-01
During the past 2 decades, the grizzly bear (Ursus arctos) population in the Greater Yellowstone Ecosystem (GYE) has increased in numbers and expanded in range. Understanding temporal, environmental, and spatial variables responsible for this change is useful in evaluating what likely influenced grizzly bear demographics in the GYE and where future management efforts might benefit conservation and management. We used recent data from radio-marked bears to estimate reproduction (1983–2002) and survival (1983–2001); these we combined into models to evaluate demographic vigor (lambda [λ]). We explored the influence of an array of individual, temporal, and spatial covariates on demographic vigor.
Zhao, Yu-Juan; Gong, Xun
2015-07-08
Leucomeris decora and Nouelia insignis (Asteraceae) are narrowly and allopatrically distributed species, separated by the important biogeographic boundary Tanaka Line in Southwest China. Previous morphological, cytogenetic and molecular studies suggested that L. decora is sister to N. insignis. However, it is less clear how the two species diverged, whether in full isolation or occurring gene flow across the Tanaka Line. Here, we performed a molecular study at the population level to characterize genetic differentiation and decipher phylogeographic history in two closely related species based on variation examined in plastid and nuclear DNAs using a coalescent-based approach. These morphologically distinct species share plastid DNA (cpDNA) haplotypes. In contrast, Bayesian analysis of nuclear DNA (nDNA) uncovered two distinct clusters corresponding to L. decora and N. insignis. Based on the IMa analysis, no strong indication of migration was detected based on both cpDNA and nDNA sequences. The molecular data pointed to a major west-east split in nuclear DNA between the two species corresponding with the Tanaka Line. The coalescent time estimate for all cpDNA haplotypes dated to the Mid-Late Pleistocene. The estimated demographic parameters showed that the population size of L. decora was similar to that of N. insignis and both experienced limited demographic fluctuations recently. The study revealed comprehensive species divergence and phylogeographic histories of N. insignis and L. decora divided by the Tanaka Line. The phylogeographic pattern inferred from cpDNA reflected ancestrally shared polymorphisms without post-divergence gene flow between species. The marked genealogical lineage divergence in nDNA provided some indication of Tanaka Line for its role as a barrier to plant dispersal, and lent support to its importance in promoting strong population structure and allopatric divergence.
Guirao-Rico, Sara; Sánchez-Gracia, Alejandro; Charlesworth, Deborah
2017-03-01
DNA sequence diversity in genes in the partially sex-linked pseudoautosomal region (PAR) of the sex chromosomes of the plant Silene latifolia is higher than expected from within-species diversity of other genes. This could be the footprint of sexually antagonistic (SA) alleles that are maintained by balancing selection in a PAR gene (or genes) and affect polymorphism in linked genome regions. SA selection is predicted to occur during sex chromosome evolution, but it is important to test whether the unexpectedly high sequence polymorphism could be explained without it, purely by the combined effects of partial linkage with the sex-determining region and the population's demographic history, including possible introgression from Silene dioica. To test this, we applied approximate Bayesian computation-based model choice to autosomal sequence diversity data, to find the most plausible scenario for the recent history of S. latifolia and then to estimate the posterior density of the most relevant parameters. We then used these densities to simulate variation to be expected at PAR genes. We conclude that an excess of variants at high frequencies at PAR genes should arise in S. latifolia populations only for genes with strong associations with fully sex-linked genes, which requires closer linkage with the fully sex-linked region than that estimated for the PAR genes where apparent deviations from neutrality were observed. These results support the need to invoke selection to explain the S. latifolia PAR gene diversity, and encourage further work to test the possibility of balancing selection due to sexual antagonism. © 2016 John Wiley & Sons Ltd.
Wind turbines and idiopathic symptoms: The confounding effect of concurrent environmental exposures.
Blanes-Vidal, Victoria; Schwartz, Joel
2016-01-01
Whether or not wind turbines pose a risk to human health is a matter of heated debate. Personal reactions to other environmental exposures occurring in the same settings as wind turbines may be responsible of the reported symptoms. However, these have not been accounted for in previous studies. We investigated whether there is an association between residential proximity to wind turbines and idiopathic symptoms, after controlling for personal reactions to other environmental co-exposures. We assessed wind turbine exposures in 454 residences as the distance to the closest wind turbine (Dw) and number of wind turbines <1000m (Nw1000). Information on symptoms, demographics and personal reactions to exposures was obtained by a blind questionnaire. We identified confounders using confounders' selection criteria and used adjusted logistic regression models to estimate associations. When controlling only for socio-demographic characteristics, log10Dw was associated with "unnatural fatigue" (ORadj=0.38, 95%CI=0.15-1.00) and "difficulty concentrating" (ORadj=0.26, 95%CI=0.08-0.83) and Nw1000 was associated with "unnatural fatigue" (ORadj=1.35, 95%CI=1.07-1.70) and "headache" (ORadj=1.26, 95%CI=1.00-1.58). After controlling for personal reactions to noise from sources different from wind turbines and agricultural odor exposure, we did not observe a significant relationship between residential proximity to wind turbines and symptoms and the parameter estimates were attenuated toward zero. Wind turbines-health associations can be confounded by personal reactions to other environmental co-exposures. Isolated associations reported in the literature may be due to confounding bias. Copyright © 2016 Elsevier Inc. All rights reserved.
Sabre, Liis; Westerberg, Elisabet; Liik, Maarika; Punga, Anna R
2017-04-01
Self-estimated health can be used for comparison of different diseases between countries. It is important to elaborate on whether disparities in self-estimated health are due to disease-specific parameters or socioeconomic differences. In this study, we aimed at evaluating clinical and social similarities and differences in myasthenia gravis (MG) patients between comparable regions in two Baltic Sea countries, Estonia and Sweden. This cross-sectional study included southern counties in Sweden and Estonia of comparable size. All patients with a confirmed MG diagnosis were asked to answer two questionnaires including demographic and disease-specific data, lifestyle issues, and mental fatigue (Fatigue Severity Scale [FSS]). Clinical fatigue was assessed objectively through the Quantitative Myasthenia Gravis Score (QMG). Thirty-six of 92 identified patients in Estonia and 40 of 70 identified MG patients in Sweden chose to participate in the study. The demographic characteristics and symptoms reported by the patients were similar. QMG score did not differ; however, the Estonian patients scored their current subjective disease severity significantly higher (5.6 ± 2.8) compared to the Swedish patients (3.4 ± 2.3, p = .0005). Estonian patients also had significantly higher FSS scores (5.0 ± 1.7) than Swedish patients (3.5 ± 1.6; p = .001). Swedish patients were more active and performed physical activity more regularly (29.1% in Estonia and 74.2% in Sweden, p = .004). Although, the patients had comparable clinical fatigue, Estonian patients evaluated their health state as being more severe and reported more mental fatigue than Swedish patients. These data indicate large regional differences in disease perception of MG, which is important to consider in international studies.
International migration beyond gravity: A statistical model for use in population projections
Cohen, Joel E.; Roig, Marta; Reuman, Daniel C.; GoGwilt, Cai
2008-01-01
International migration will play an increasing role in the demographic future of most nations if fertility continues to decline globally. We developed an algorithm to project future numbers of international migrants from any country or region to any other. The proposed generalized linear model (GLM) used geographic and demographic independent variables only (the population and area of origins and destinations of migrants, the distance between origin and destination, the calendar year, and indicator variables to quantify nonrandom characteristics of individual countries). The dependent variable, yearly numbers of migrants, was quantified by 43653 reports from 11 countries of migration from 228 origins and to 195 destinations during 1960–2004. The final GLM based on all data was selected by the Bayesian information criterion. The number of migrants per year from origin to destination was proportional to (population of origin)0.86(area of origin)−0.21(population of destination)0.36(distance)−0.97, multiplied by functions of year and country-specific indicator variables. The number of emigrants from an origin depended on both its population and its population density. For a variable initial year and a fixed terminal year 2004, the parameter estimates appeared stable. Multiple R2, the fraction of variation in log numbers of migrants accounted for by the starting model, improved gradually with recentness of the data: R2 = 0.57 for data from 1960 to 2004, R2 = 0.59 for 1985–2004, R2 = 0.61 for 1995–2004, and R2 = 0.64 for 2000–2004. The migration estimates generated by the model may be embedded in deterministic or stochastic population projections. PMID:18824693
Yobbi, D.K.
2000-01-01
A nonlinear least-squares regression technique for estimation of ground-water flow model parameters was applied to an existing model of the regional aquifer system underlying west-central Florida. The regression technique minimizes the differences between measured and simulated water levels. Regression statistics, including parameter sensitivities and correlations, were calculated for reported parameter values in the existing model. Optimal parameter values for selected hydrologic variables of interest are estimated by nonlinear regression. Optimal estimates of parameter values are about 140 times greater than and about 0.01 times less than reported values. Independently estimating all parameters by nonlinear regression was impossible, given the existing zonation structure and number of observations, because of parameter insensitivity and correlation. Although the model yields parameter values similar to those estimated by other methods and reproduces the measured water levels reasonably accurately, a simpler parameter structure should be considered. Some possible ways of improving model calibration are to: (1) modify the defined parameter-zonation structure by omitting and/or combining parameters to be estimated; (2) carefully eliminate observation data based on evidence that they are likely to be biased; (3) collect additional water-level data; (4) assign values to insensitive parameters, and (5) estimate the most sensitive parameters first, then, using the optimized values for these parameters, estimate the entire data set.
An improved method for nonlinear parameter estimation: a case study of the Rössler model
NASA Astrophysics Data System (ADS)
He, Wen-Ping; Wang, Liu; Jiang, Yun-Di; Wan, Shi-Quan
2016-08-01
Parameter estimation is an important research topic in nonlinear dynamics. Based on the evolutionary algorithm (EA), Wang et al. (2014) present a new scheme for nonlinear parameter estimation and numerical tests indicate that the estimation precision is satisfactory. However, the convergence rate of the EA is relatively slow when multiple unknown parameters in a multidimensional dynamical system are estimated simultaneously. To solve this problem, an improved method for parameter estimation of nonlinear dynamical equations is provided in the present paper. The main idea of the improved scheme is to use all of the known time series for all of the components in some dynamical equations to estimate the parameters in single component one by one, instead of estimating all of the parameters in all of the components simultaneously. Thus, we can estimate all of the parameters stage by stage. The performance of the improved method was tested using a classic chaotic system—Rössler model. The numerical tests show that the amended parameter estimation scheme can greatly improve the searching efficiency and that there is a significant increase in the convergence rate of the EA, particularly for multiparameter estimation in multidimensional dynamical equations. Moreover, the results indicate that the accuracy of parameter estimation and the CPU time consumed by the presented method have no obvious dependence on the sample size.
Merler, Stefano; Ajelli, Marco; Fumanelli, Laura; Gomes, Marcelo F C; Piontti, Ana Pastore Y; Rossi, Luca; Chao, Dennis L; Longini, Ira M; Halloran, M Elizabeth; Vespignani, Alessandro
2015-02-01
The 2014 epidemic of Ebola virus disease in parts of west Africa defines an unprecedented health threat. We developed a model of Ebola virus transmission that integrates detailed geographical and demographic data from Liberia to overcome the limitations of non-spatial approaches in projecting the disease dynamics and assessing non-pharmaceutical control interventions. We modelled the movements of individuals, including patients not infected with Ebola virus, seeking assistance in health-care facilities, the movements of individuals taking care of patients infected with Ebola virus not admitted to hospital, and the attendance of funerals. Individuals were grouped into randomly assigned households (size based on Demographic Health Survey data) that were geographically placed to match population density estimates on a grid of 3157 cells covering the country. The spatial agent-based model was calibrated with a Markov chain Monte Carlo approach. The model was used to estimate Ebola virus transmission parameters and investigate the effectiveness of interventions such as availability of Ebola treatment units, safe burials procedures, and household protection kits. Up to Aug 16, 2014, we estimated that 38·3% of infections (95% CI 17·4-76·4) were acquired in hospitals, 30·7% (14·1-46·4) in households, and 8·6% (3·2-11·8) while participating in funerals. We noted that the movement and mixing, in hospitals at the early stage of the epidemic, of patients infected with Ebola virus and those not infected was a sufficient driver of the reported pattern of spatial spread. The subsequent decrease of incidence at country and county level is attributable to the increasing availability of Ebola treatment units (which in turn contributed to drastically decreased hospital transmission), safe burials, and distribution of household protection kits. The model allows assessment of intervention options and the understanding of their role in the decrease in incidence reported since Sept 7, 2014. High-quality data (eg, to estimate household secondary attack rate, contact patterns within hospitals, and effects of ongoing interventions) are needed to reduce uncertainty in model estimates. US Defense Threat Reduction Agency, US National Institutes of Health. Copyright © 2015 Elsevier Ltd. All rights reserved.
Statistical and Biophysical Models for Predicting Total and Outdoor Water Use in Los Angeles
NASA Astrophysics Data System (ADS)
Mini, C.; Hogue, T. S.; Pincetl, S.
2012-04-01
Modeling water demand is a complex exercise in the choice of the functional form, techniques and variables to integrate in the model. The goal of the current research is to identify the determinants that control total and outdoor residential water use in semi-arid cities and to utilize that information in the development of statistical and biophysical models that can forecast spatial and temporal urban water use. The City of Los Angeles is unique in its highly diverse socio-demographic, economic and cultural characteristics across neighborhoods, which introduces significant challenges in modeling water use. Increasing climate variability also contributes to uncertainties in water use predictions in urban areas. Monthly individual water use records were acquired from the Los Angeles Department of Water and Power (LADWP) for the 2000 to 2010 period. Study predictors of residential water use include socio-demographic, economic, climate and landscaping variables at the zip code level collected from US Census database. Climate variables are estimated from ground-based observations and calculated at the centroid of each zip code by inverse-distance weighting method. Remotely-sensed products of vegetation biomass and landscape land cover are also utilized. Two linear regression models were developed based on the panel data and variables described: a pooled-OLS regression model and a linear mixed effects model. Both models show income per capita and the percentage of landscape areas in each zip code as being statistically significant predictors. The pooled-OLS model tends to over-estimate higher water use zip codes and both models provide similar RMSE values.Outdoor water use was estimated at the census tract level as the residual between total water use and indoor use. This residual is being compared with the output from a biophysical model including tree and grass cover areas, climate variables and estimates of evapotranspiration at very high spatial resolution. A genetic algorithm based model (Shuffled Complex Evolution-UA; SCE-UA) is also being developed to provide estimates of the predictions and parameters uncertainties and to compare against the linear regression models. Ultimately, models will be selected to undertake predictions for a range of climate change and landscape scenarios. Finally, project results will contribute to a better understanding of water demand to help predict future water use and implement targeted landscaping conservation programs to maintain sustainable water needs for a growing population under uncertain climate variability.
Coalescent Processes with Skewed Offspring Distributions and Nonequilibrium Demography.
Matuszewski, Sebastian; Hildebrandt, Marcel E; Achaz, Guillaume; Jensen, Jeffrey D
2018-01-01
Nonequilibrium demography impacts coalescent genealogies leaving detectable, well-studied signatures of variation. However, similar genomic footprints are also expected under models of large reproductive skew, posing a serious problem when trying to make inference. Furthermore, current approaches consider only one of the two processes at a time, neglecting any genomic signal that could arise from their simultaneous effects, preventing the possibility of jointly inferring parameters relating to both offspring distribution and population history. Here, we develop an extended Moran model with exponential population growth, and demonstrate that the underlying ancestral process converges to a time-inhomogeneous psi-coalescent. However, by applying a nonlinear change of time scale-analogous to the Kingman coalescent-we find that the ancestral process can be rescaled to its time-homogeneous analog, allowing the process to be simulated quickly and efficiently. Furthermore, we derive analytical expressions for the expected site-frequency spectrum under the time-inhomogeneous psi-coalescent, and develop an approximate-likelihood framework for the joint estimation of the coalescent and growth parameters. By means of extensive simulation, we demonstrate that both can be estimated accurately from whole-genome data. In addition, not accounting for demography can lead to serious biases in the inferred coalescent model, with broad implications for genomic studies ranging from ecology to conservation biology. Finally, we use our method to analyze sequence data from Japanese sardine populations, and find evidence of high variation in individual reproductive success, but few signs of a recent demographic expansion. Copyright © 2018 by the Genetics Society of America.
Biased phylodynamic inferences from analysing clusters of viral sequences
Xiang, Fei; Frost, Simon D. W.
2017-01-01
Abstract Phylogenetic methods are being increasingly used to help understand the transmission dynamics of measurably evolving viruses, including HIV. Clusters of highly similar sequences are often observed, which appear to follow a ‘power law’ behaviour, with a small number of very large clusters. These clusters may help to identify subpopulations in an epidemic, and inform where intervention strategies should be implemented. However, clustering of samples does not necessarily imply the presence of a subpopulation with high transmission rates, as groups of closely related viruses can also occur due to non-epidemiological effects such as over-sampling. It is important to ensure that observed phylogenetic clustering reflects true heterogeneity in the transmitting population, and is not being driven by non-epidemiological effects. We qualify the effect of using a falsely identified ‘transmission cluster’ of sequences to estimate phylodynamic parameters including the effective population size and exponential growth rate under several demographic scenarios. Our simulation studies show that taking the maximum size cluster to re-estimate parameters from trees simulated under a randomly mixing, constant population size coalescent process systematically underestimates the overall effective population size. In addition, the transmission cluster wrongly resembles an exponential or logistic growth model 99% of the time. We also illustrate the consequences of false clusters in exponentially growing coalescent and birth-death trees, where again, the growth rate is skewed upwards. This has clear implications for identifying clusters in large viral databases, where a false cluster could result in wasted intervention resources. PMID:28852573
NASA Astrophysics Data System (ADS)
Hendricks Franssen, H. J.; Post, H.; Vrugt, J. A.; Fox, A. M.; Baatz, R.; Kumbhar, P.; Vereecken, H.
2015-12-01
Estimation of net ecosystem exchange (NEE) by land surface models is strongly affected by uncertain ecosystem parameters and initial conditions. A possible approach is the estimation of plant functional type (PFT) specific parameters for sites with measurement data like NEE and application of the parameters at other sites with the same PFT and no measurements. This upscaling strategy was evaluated in this work for sites in Germany and France. Ecosystem parameters and initial conditions were estimated with NEE-time series of one year length, or a time series of only one season. The DREAM(zs) algorithm was used for the estimation of parameters and initial conditions. DREAM(zs) is not limited to Gaussian distributions and can condition to large time series of measurement data simultaneously. DREAM(zs) was used in combination with the Community Land Model (CLM) v4.5. Parameter estimates were evaluated by model predictions at the same site for an independent verification period. In addition, the parameter estimates were evaluated at other, independent sites situated >500km away with the same PFT. The main conclusions are: i) simulations with estimated parameters reproduced better the NEE measurement data in the verification periods, including the annual NEE-sum (23% improvement), annual NEE-cycle and average diurnal NEE course (error reduction by factor 1,6); ii) estimated parameters based on seasonal NEE-data outperformed estimated parameters based on yearly data; iii) in addition, those seasonal parameters were often also significantly different from their yearly equivalents; iv) estimated parameters were significantly different if initial conditions were estimated together with the parameters. We conclude that estimated PFT-specific parameters improve land surface model predictions significantly at independent verification sites and for independent verification periods so that their potential for upscaling is demonstrated. However, simulation results also indicate that possibly the estimated parameters mask other model errors. This would imply that their application at climatic time scales would not improve model predictions. A central question is whether the integration of many different data streams (e.g., biomass, remotely sensed LAI) could solve the problems indicated here.
Breed, Greg A.; Golson, Emily A.; Tinker, M. Tim
2017-01-01
The home‐range concept is central in animal ecology and behavior, and numerous mechanistic models have been developed to understand home range formation and maintenance. These mechanistic models usually assume a single, contiguous home range. Here we describe and implement a simple home‐range model that can accommodate multiple home‐range centers, form complex shapes, allow discontinuities in use patterns, and infer how external and internal variables affect movement and use patterns. The model assumes individuals associate with two or more home‐range centers and move among them with some estimable probability. Movement in and around home‐range centers is governed by a two‐dimensional Ornstein‐Uhlenbeck process, while transitions between centers are modeled as a stochastic state‐switching process. We augmented this base model by introducing environmental and demographic covariates that modify transition probabilities between home‐range centers and can be estimated to provide insight into the movement process. We demonstrate the model using telemetry data from sea otters (Enhydra lutris) in California. The model was fit using a Bayesian Markov Chain Monte Carlo method, which estimated transition probabilities, as well as unique Ornstein‐Uhlenbeck diffusion and centralizing tendency parameters. Estimated parameters could then be used to simulate movement and space use that was virtually indistinguishable from real data. We used Deviance Information Criterion (DIC) scores to assess model fit and determined that both wind and reproductive status were predictive of transitions between home‐range centers. Females were less likely to move between home‐range centers on windy days, less likely to move between centers when tending pups, and much more likely to move between centers just after weaning a pup. These tendencies are predicted by theoretical movement rules but were not previously known and show that our model can extract meaningful behavioral insight from complex movement data.
Naujokaitis-Lewis, Ilona; Curtis, Janelle M R
2016-01-01
Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs) coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0) that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis) in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat attributes along with demographic parameters in sensitivity routines. GRIP 2.0 is an important decision-support tool that can be used to prioritize research, identify habitat-based thresholds and management intervention points to improve probability of species persistence, and evaluate trade-offs of alternative management options.
Curtis, Janelle M.R.
2016-01-01
Developing a rigorous understanding of multiple global threats to species persistence requires the use of integrated modeling methods that capture processes which influence species distributions. Species distribution models (SDMs) coupled with population dynamics models can incorporate relationships between changing environments and demographics and are increasingly used to quantify relative extinction risks associated with climate and land-use changes. Despite their appeal, uncertainties associated with complex models can undermine their usefulness for advancing predictive ecology and informing conservation management decisions. We developed a computationally-efficient and freely available tool (GRIP 2.0) that implements and automates a global sensitivity analysis of coupled SDM-population dynamics models for comparing the relative influence of demographic parameters and habitat attributes on predicted extinction risk. Advances over previous global sensitivity analyses include the ability to vary habitat suitability across gradients, as well as habitat amount and configuration of spatially-explicit suitability maps of real and simulated landscapes. Using GRIP 2.0, we carried out a multi-model global sensitivity analysis of a coupled SDM-population dynamics model of whitebark pine (Pinus albicaulis) in Mount Rainier National Park as a case study and quantified the relative influence of input parameters and their interactions on model predictions. Our results differed from the one-at-time analyses used in the original study, and we found that the most influential parameters included the total amount of suitable habitat within the landscape, survival rates, and effects of a prevalent disease, white pine blister rust. Strong interactions between habitat amount and survival rates of older trees suggests the importance of habitat in mediating the negative influences of white pine blister rust. Our results underscore the importance of considering habitat attributes along with demographic parameters in sensitivity routines. GRIP 2.0 is an important decision-support tool that can be used to prioritize research, identify habitat-based thresholds and management intervention points to improve probability of species persistence, and evaluate trade-offs of alternative management options. PMID:27547529
Demography of the Yellowstone grizzly bears
Pease, C.M.; Mattson, D.J.
1999-01-01
We undertook a demographic analysis of the Yellowstone grizzly bears (Ursus arctos) to identify critical environmental factors controlling grizzly bear vital rates, and thereby to help evaluate the effectiveness of past management and to identify future conservation issues. We concluded that, within the limits of uncertainty implied by the available data and our methods of data analysis, the size of the Yellowstone grizzly bear population changed little from 1975 to 1995. We found that grizzly bear mortality rates are about double in years when the whitebark pine crop fails than in mast years, and that the population probably declines when the crop fails and increases in mast years. Our model suggests that natural variation in whitebark pine crop size over the last two decades explains more of the perceived fluctuations in Yellowstone grizzly population size than do other variables. Our analysis used demographic data from 202 radio-telemetered bears followed between 1975 and 1992 and accounted for whitebark pine (Pinus albicaulis) crop failures during 1993-1995. We used a maximum likelihood method to estimate demographic parameters and used the Akaike Information Criteria to judge the significance of various independent variables. We identified no independent variables correlated with grizzly bear fecundity. In order of importance, we found that grizzly bear mortality rates are correlated with season, whitebark pine crop size (mast vs. nonmast year), sex, management-trapping status (never management-trapped vs. management-trapped once or more), and age. The mortality rate of bears that were management-trapped at least once was almost double that of bears that were never management-trapped, implying a source/sink (i.e., never management-trapped/management-trapped) structure. The rate at which bears move between the source and sink, estimated as the management-trapping rate (h), is critical to estimating the finite rate of increase, I>I?. We quantified h by estimating the rate at which bears that have never been management-trapped are management-trapped for the first time. It differed across seasons, was higher in nonmast than mast years, and varied with age. We calculate that I>I?=1.00 from 1975 to 1983 (four mast and five nonmast years) and 1.02 from 1984 to 1995 (seven mast and five nonmast years). Overall, we find that I>I?=1.01A? 0.04 (mean A? 1 SE) from 1975 to 1995. Our models suggest that future management should concentrate on the threats to whitebark pine, such as those posed by white pine blister rust, global warming, and fire suppression. As is currently widely recognized by Yellowstone land managers, our model also suggests that future management must compensate for the increased grizzly bear mortality that is likely to be caused by an increasing number of humans in Yellowstone.
Van Derlinden, E; Bernaerts, K; Van Impe, J F
2010-05-21
Optimal experiment design for parameter estimation (OED/PE) has become a popular tool for efficient and accurate estimation of kinetic model parameters. When the kinetic model under study encloses multiple parameters, different optimization strategies can be constructed. The most straightforward approach is to estimate all parameters simultaneously from one optimal experiment (single OED/PE strategy). However, due to the complexity of the optimization problem or the stringent limitations on the system's dynamics, the experimental information can be limited and parameter estimation convergence problems can arise. As an alternative, we propose to reduce the optimization problem to a series of two-parameter estimation problems, i.e., an optimal experiment is designed for a combination of two parameters while presuming the other parameters known. Two different approaches can be followed: (i) all two-parameter optimal experiments are designed based on identical initial parameter estimates and parameters are estimated simultaneously from all resulting experimental data (global OED/PE strategy), and (ii) optimal experiments are calculated and implemented sequentially whereby the parameter values are updated intermediately (sequential OED/PE strategy). This work exploits OED/PE for the identification of the Cardinal Temperature Model with Inflection (CTMI) (Rosso et al., 1993). This kinetic model describes the effect of temperature on the microbial growth rate and encloses four parameters. The three OED/PE strategies are considered and the impact of the OED/PE design strategy on the accuracy of the CTMI parameter estimation is evaluated. Based on a simulation study, it is observed that the parameter values derived from the sequential approach deviate more from the true parameters than the single and global strategy estimates. The single and global OED/PE strategies are further compared based on experimental data obtained from design implementation in a bioreactor. Comparable estimates are obtained, but global OED/PE estimates are, in general, more accurate and reliable. Copyright (c) 2010 Elsevier Ltd. All rights reserved.
Clinical validation of the General Ability Index--Estimate (GAI-E): estimating premorbid GAI.
Schoenberg, Mike R; Lange, Rael T; Iverson, Grant L; Chelune, Gordon J; Scott, James G; Adams, Russell L
2006-09-01
The clinical utility of the General Ability Index--Estimate (GAI-E; Lange, Schoenberg, Chelune, Scott, & Adams, 2005) for estimating premorbid GAI scores was investigated using the WAIS-III standardization clinical trials sample (The Psychological Corporation, 1997). The GAI-E algorithms combine Vocabulary, Information, Matrix Reasoning, and Picture Completion subtest raw scores with demographic variables to predict GAI. Ten GAI-E algorithms were developed combining demographic variables with single subtest scaled scores and with two subtests. Estimated GAI are presented for participants diagnosed with dementia (n = 50), traumatic brain injury (n = 20), Huntington's disease (n = 15), Korsakoff's disease (n = 12), chronic alcohol abuse (n = 32), temporal lobectomy (n = 17), and schizophrenia (n = 44). In addition, a small sample of participants without dementia and diagnosed with depression (n = 32) was used as a clinical comparison group. The GAI-E algorithms provided estimates of GAI that closely approximated scores expected for a healthy adult population. The greatest differences between estimated GAI and obtained GAI were observed for the single subtest GAI-E algorithms using the Vocabulary, Information, and Matrix Reasoning subtests. Based on these data, recommendations for the use of the GAI-E algorithms are presented.
Labrada-Martagón, Vanessa; Zenteno-Savín, Tania; Mangel, Marc
2014-01-01
Sex, age and sexual maturation are key biological parameters for aspects of life history and are fundamental information for assessing demographic changes and the reproductive viability and performance of natural populations under exploitation pressures or in response to environmental influences. Much of the information available on the reproductive condition, length at sexual maturity and sex determinations of endangered species has been derived from direct examination of the gonads in dead animals, either intentionally or incidentally caught, or from stranded individuals. However, morphological data, when used alone, do not provide accurate demographic information in sexually monomorphic marine vertebrate species (e.g. sharks, sea turtles, seabirds and cetaceans). Hormone determination is an accurate and non-destructive method that provides indirect information about sex, reproductive condition and sexual maturity of free-ranging individuals. Correlations between sex steroid concentrations and biochemical parameters, gonadal development and state, reproductive behaviour and secondary external features have been already demonstrated in many species. Different non-lethal approaches (e.g. surgical and mark–recapture procedures), with intrinsic advantages and disadvantages when applied on free-ranging organisms, have been proposed to asses sex, growth and reproductive condition. Hormone determination from blood samples will generate valuable additional demographic information needed for stock assessment and biological conservation. PMID:27293619
Long, Xi; Haakma, Reinder; Leufkens, Tim R. M.; Fonseca, Pedro; Aarts, Ronald M.
2015-01-01
Autonomic cardiorespiratory activity changes across sleep stages. However, it is unknown to what extent it is affected by between- and within-subject variability during sleep. As it is hypothesized that the variability is caused by differences in subject demographics (age, gender, and body mass index), time, and physiology, we quantified these effects and investigated how they limit reliable cardiorespiratory-based sleep staging. Six representative parameters obtained from 165 overnight heartbeat and respiration recordings were analyzed. Multilevel models were used to evaluate the effects evoked by differences in sleep stages, demographics, time, and physiology between and within subjects. Results show that the between- and within-subject effects were found to be significant for each parameter. When adjusted by sleep stages, the effects in physiology between and within subjects explained more than 80% of total variance but the time and demographic effects explained less. If these effects are corrected, profound improvements in sleep staging can be observed. These results indicate that the differences in subject demographics, time, and physiology present significant effects on cardiorespiratory activity during sleep. The primary effects come from the physiological variability between and within subjects, markedly limiting the sleep staging performance. Efforts to diminish these effects will be the main challenge. PMID:26366167
Determining the accuracy of maximum likelihood parameter estimates with colored residuals
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.; Klein, Vladislav
1994-01-01
An important part of building high fidelity mathematical models based on measured data is calculating the accuracy associated with statistical estimates of the model parameters. Indeed, without some idea of the accuracy of parameter estimates, the estimates themselves have limited value. In this work, an expression based on theoretical analysis was developed to properly compute parameter accuracy measures for maximum likelihood estimates with colored residuals. This result is important because experience from the analysis of measured data reveals that the residuals from maximum likelihood estimation are almost always colored. The calculations involved can be appended to conventional maximum likelihood estimation algorithms. Simulated data runs were used to show that the parameter accuracy measures computed with this technique accurately reflect the quality of the parameter estimates from maximum likelihood estimation without the need for analysis of the output residuals in the frequency domain or heuristically determined multiplication factors. The result is general, although the application studied here is maximum likelihood estimation of aerodynamic model parameters from flight test data.
A multifaceted approach to understanding dynamic urban processes: satellites, surveys, and censuses.
NASA Astrophysics Data System (ADS)
Jones, B.; Balk, D.; Montgomery, M.; Liu, Z.
2014-12-01
Urbanization will arguably be the most significant demographic trend of the 21st century, particularly in fast-growing regions of the developing world. Characterizing urbanization in a spatial context, however, is a difficult task given only the moderate resolution data provided by traditional sources of demographic data (i.e., censuses and surveys). Using a sample of five world "mega-cities" we demonstrate how new satellite data products and new analysis of existing satellite data, when combined with new applications of census and survey microdata, can reveal more about cities and urbanization in combination than either data type can by itself. In addition to the partially modelled Global Urban-Rural Mapping Project (GRUMP) urban extents we consider four sources of remotely sensed data that can be used to estimate urban extents; the NOAA Defense Meteorological Satellite Program (DMSP) Operational Linescan System (OLS) intercallibrated nighttime lights time series data, the newer NOAA Visible Infrared Imager Radiometer Suite (VIIRS) nighttime lights data, the German Aerospace Center (DLR) radar satellite data, and Dense Sampling Method (DSM) analysis of the NASA scatterometer data. Demographic data come from national censuses and/or georeferenced survey data from the Demographic & Health Survey (DHS) program. We overlay demographic and remotely sensed data (e.g., Figs 1, 2) to address two questions; (1) how well do satellite derived measures of urban intensity correlate with demographic measures, and (2) how well are temporal changes in the data correlated. Using spatial regression techniques, we then estimate statistical relationships (controlling for influences such as elevation, coastal proximity, and economic development) between the remotely sensed and demographic data and test the ability of each to predict the other. Satellite derived imagery help us to better understand the evolution of the built environment and urban form, while the underlying demographic data provide information regarding composition of urban population change. Combining these types of data yields important, high resolution spatial information that provides a more accurate understanding of urban processes.
Community BMI Surveillance Using an Existing Immunization Registry in San Diego, California.
Ratigan, Amanda R; Lindsay, Suzanne; Lemus, Hector; Chambers, Christina D; Anderson, Cheryl A M; Cronan, Terry A; Browner, Deirdre K; Wooten, Wilma J
2017-06-01
This study examines the demographic representativeness of the County of San Diego Body Mass Index (BMI) Surveillance System to determine if the BMI estimates being obtained from this convenience sample of individuals who visited their healthcare provider for outpatient services can be generalized to the general population of San Diego. Height and weight were transmitted from electronic health records systems to the San Diego Immunization Registry (SDIR). Age, gender, and race/ethnicity of this sample are compared to general population estimates by sub-regional area (SRA) (n = 41) to account for regional demographic differences. A < 10% difference (calculated as the ratio of the differences between the frequencies of a sub-group in this sample and general population estimates obtained from the U.S. Census Bureau) was used to determine representativeness. In 2011, the sample consisted of 352,924 residents aged 2-100 years. The younger age groups (2-11, 12-17 years) and the oldest age group (≥65 years) were representative in 90, 75, and 85% of SRAs, respectively. Furthermore, at least one of the five racial/ethnic groups was represented in 71% of SRAs. This BMI Surveillance System was found to demographically represent some SRAs well, suggesting that this registry-based surveillance system may be useful in estimating and monitoring neighborhood-level BMI data.
The re-identification risk of Canadians from longitudinal demographics
2011-01-01
Background The public is less willing to allow their personal health information to be disclosed for research purposes if they do not trust researchers and how researchers manage their data. However, the public is more comfortable with their data being used for research if the risk of re-identification is low. There are few studies on the risk of re-identification of Canadians from their basic demographics, and no studies on their risk from their longitudinal data. Our objective was to estimate the risk of re-identification from the basic cross-sectional and longitudinal demographics of Canadians. Methods Uniqueness is a common measure of re-identification risk. Demographic data on a 25% random sample of the population of Montreal were analyzed to estimate population uniqueness on postal code, date of birth, and gender as well as their generalizations, for periods ranging from 1 year to 11 years. Results Almost 98% of the population was unique on full postal code, date of birth and gender: these three variables are effectively a unique identifier for Montrealers. Uniqueness increased for longitudinal data. Considerable generalization was required to reach acceptably low uniqueness levels, especially for longitudinal data. Detailed guidelines and disclosure policies on how to ensure that the re-identification risk is low are provided. Conclusions A large percentage of Montreal residents are unique on basic demographics. For non-longitudinal data sets, the three character postal code, gender, and month/year of birth represent sufficiently low re-identification risk. Data custodians need to generalize their demographic information further for longitudinal data sets. PMID:21696636
Bayesian Parameter Estimation for Heavy-Duty Vehicles
DOE Office of Scientific and Technical Information (OSTI.GOV)
Miller, Eric; Konan, Arnaud; Duran, Adam
2017-03-28
Accurate vehicle parameters are valuable for design, modeling, and reporting. Estimating vehicle parameters can be a very time-consuming process requiring tightly-controlled experimentation. This work describes a method to estimate vehicle parameters such as mass, coefficient of drag/frontal area, and rolling resistance using data logged during standard vehicle operation. The method uses Monte Carlo to generate parameter sets which is fed to a variant of the road load equation. Modeled road load is then compared to measured load to evaluate the probability of the parameter set. Acceptance of a proposed parameter set is determined using the probability ratio to the currentmore » state, so that the chain history will give a distribution of parameter sets. Compared to a single value, a distribution of possible values provides information on the quality of estimates and the range of possible parameter values. The method is demonstrated by estimating dynamometer parameters. Results confirm the method's ability to estimate reasonable parameter sets, and indicates an opportunity to increase the certainty of estimates through careful selection or generation of the test drive cycle.« less
Luo, Shezhou; Chen, Jing M; Wang, Cheng; Xi, Xiaohuan; Zeng, Hongcheng; Peng, Dailiang; Li, Dong
2016-05-30
Vegetation leaf area index (LAI), height, and aboveground biomass are key biophysical parameters. Corn is an important and globally distributed crop, and reliable estimations of these parameters are essential for corn yield forecasting, health monitoring and ecosystem modeling. Light Detection and Ranging (LiDAR) is considered an effective technology for estimating vegetation biophysical parameters. However, the estimation accuracies of these parameters are affected by multiple factors. In this study, we first estimated corn LAI, height and biomass (R2 = 0.80, 0.874 and 0.838, respectively) using the original LiDAR data (7.32 points/m2), and the results showed that LiDAR data could accurately estimate these biophysical parameters. Second, comprehensive research was conducted on the effects of LiDAR point density, sampling size and height threshold on the estimation accuracy of LAI, height and biomass. Our findings indicated that LiDAR point density had an important effect on the estimation accuracy for vegetation biophysical parameters, however, high point density did not always produce highly accurate estimates, and reduced point density could deliver reasonable estimation results. Furthermore, the results showed that sampling size and height threshold were additional key factors that affect the estimation accuracy of biophysical parameters. Therefore, the optimal sampling size and the height threshold should be determined to improve the estimation accuracy of biophysical parameters. Our results also implied that a higher LiDAR point density, larger sampling size and height threshold were required to obtain accurate corn LAI estimation when compared with height and biomass estimations. In general, our results provide valuable guidance for LiDAR data acquisition and estimation of vegetation biophysical parameters using LiDAR data.
15 CFR 90.1 - Scope and applicability.
Code of Federal Regulations, 2014 CFR
2014-01-01
... CENSUS, DEPARTMENT OF COMMERCE PROCEDURE FOR CHALLENGING POPULATION ESTIMATES § 90.1 Scope and... number of people residing in states and their governmental units. In general, these estimates are developed by updating the population counts produced in the most recent decennial census with demographic...
Zipkin, Elise F; Sillett, T Scott; Grant, Evan H Campbell; Chandler, Richard B; Royle, J Andrew
2014-01-01
Wildlife populations consist of individuals that contribute disproportionately to growth and viability. Understanding a population's spatial and temporal dynamics requires estimates of abundance and demographic rates that account for this heterogeneity. Estimating these quantities can be difficult, requiring years of intensive data collection. Often, this is accomplished through the capture and recapture of individual animals, which is generally only feasible at a limited number of locations. In contrast, N-mixture models allow for the estimation of abundance, and spatial variation in abundance, from count data alone. We extend recently developed multistate, open population N-mixture models, which can additionally estimate demographic rates based on an organism's life history characteristics. In our extension, we develop an approach to account for the case where not all individuals can be assigned to a state during sampling. Using only state-specific count data, we show how our model can be used to estimate local population abundance, as well as density-dependent recruitment rates and state-specific survival. We apply our model to a population of black-throated blue warblers (Setophaga caerulescens) that have been surveyed for 25 years on their breeding grounds at the Hubbard Brook Experimental Forest in New Hampshire, USA. The intensive data collection efforts allow us to compare our estimates to estimates derived from capture–recapture data. Our model performed well in estimating population abundance and density-dependent rates of annual recruitment/immigration. Estimates of local carrying capacity and per capita recruitment of yearlings were consistent with those published in other studies. However, our model moderately underestimated annual survival probability of yearling and adult females and severely underestimates survival probabilities for both of these male stages. The most accurate and precise estimates will necessarily require some amount of intensive data collection efforts (such as capture–recapture). Integrated population models that combine data from both intensive and extensive sources are likely to be the most efficient approach for estimating demographic rates at large spatial and temporal scales. PMID:24634726
Changing demographics and state fiscal outlook: the case of sales taxes.
Mullins, D R; Wallace, S
1996-04-01
"Broad-scale demographic changes have implications for state and local finance in terms of the composition of the base of revenue sources and their yields. This article examines the effect of such changes on the potential future yield of consumption-based taxes. The effect of household characteristics and composition on the consumption of selected groups of goods subject to ad valorem retail sales taxes is estimated, generating demographic elasticities of consumption. These elasticities are applied to projected demographic changes in eight states through the year 2000. The results show rather wide variation in expected consumption shifts and potential tax bases across the states, with income growth having the greatest effect...." The geographical focus is on the United States. excerpt
NASA Technical Reports Server (NTRS)
Perz, Stephen G.; Walker, Robert T.; Caldas, Marcellus M.
2006-01-01
Most research featuring demographic factors in environmental change has focused on processes operating at the level of national or global populations. This paper focuses on household-level demographic life cycles among colonists in the Amazon, and evaluates the impacts on land use allocation. The analysis goes beyond prior research by including a broader suite of demographic variables, and by simultaneously assessing their impacts on multiple land uses with different economic and ecological implications. We estimate a system of structural equations that accounts for endogeneity among land uses, and the findings indicate stronger demographic effects than previous work. These findings bear implications for modeling land use, and the place of demography in environmental research.
Accelerating Wright–Fisher Forward Simulations on the Graphics Processing Unit
Lawrie, David S.
2017-01-01
Forward Wright–Fisher simulations are powerful in their ability to model complex demography and selection scenarios, but suffer from slow execution on the Central Processor Unit (CPU), thus limiting their usefulness. However, the single-locus Wright–Fisher forward algorithm is exceedingly parallelizable, with many steps that are so-called “embarrassingly parallel,” consisting of a vast number of individual computations that are all independent of each other and thus capable of being performed concurrently. The rise of modern Graphics Processing Units (GPUs) and programming languages designed to leverage the inherent parallel nature of these processors have allowed researchers to dramatically speed up many programs that have such high arithmetic intensity and intrinsic concurrency. The presented GPU Optimized Wright–Fisher simulation, or “GO Fish” for short, can be used to simulate arbitrary selection and demographic scenarios while running over 250-fold faster than its serial counterpart on the CPU. Even modest GPU hardware can achieve an impressive speedup of over two orders of magnitude. With simulations so accelerated, one can not only do quick parametric bootstrapping of previously estimated parameters, but also use simulated results to calculate the likelihoods and summary statistics of demographic and selection models against real polymorphism data, all without restricting the demographic and selection scenarios that can be modeled or requiring approximations to the single-locus forward algorithm for efficiency. Further, as many of the parallel programming techniques used in this simulation can be applied to other computationally intensive algorithms important in population genetics, GO Fish serves as an exciting template for future research into accelerating computation in evolution. GO Fish is part of the Parallel PopGen Package available at: http://dl42.github.io/ParallelPopGen/. PMID:28768689
Patel, Rita B; Mathur, Maya B; Gould, Michael; Uyeki, Timothy M; Bhattacharya, Jay; Xiao, Yang; Khazeni, Nayer
2014-01-01
Human infections with highly pathogenic avian influenza (HPAI) A (H5N1) viruses have occurred in 15 countries, with high mortality to date. Determining risk factors for morbidity and mortality from HPAI H5N1 can inform preventive and therapeutic interventions. We included all cases of human HPAI H5N1 reported in World Health Organization Global Alert and Response updates and those identified through a systematic search of multiple databases (PubMed, Scopus, and Google Scholar), including articles in all languages. We abstracted predefined clinical and demographic predictors and mortality and used bivariate logistic regression analyses to examine the relationship of each candidate predictor with mortality. We developed and pruned a decision tree using nonparametric Classification and Regression Tree methods to create risk strata for mortality. We identified 617 human cases of HPAI H5N1 occurring between December 1997 and April 2013. The median age of subjects was 18 years (interquartile range 6-29 years) and 54% were female. HPAI H5N1 case-fatality proportion was 59%. The final decision tree for mortality included age, country, per capita government health expenditure, and delay from symptom onset to hospitalization, with an area under the receiver operator characteristic (ROC) curve of 0.81 (95% CI: 0.76-0.86). A model defined by four clinical and demographic predictors successfully estimated the probability of mortality from HPAI H5N1 illness. These parameters highlight the importance of early diagnosis and treatment and may enable early, targeted pharmaceutical therapy and supportive care for symptomatic patients with HPAI H5N1 virus infection.
Moffitt, R
1989-01-01
It is difficult and risky to identify the effects of tax and transfer programs on demographic behavior. The primary concern of this article is to see if real exogenous variation in these programs' parameters exist to adequately evaluate the effects of the programs on behavior. A 1982 study examined the effect of the Aid to Families with Dependent Children (AFDC), a commonly used example of a US transfer program, on the probability that a female heads a household of children 18 years old with no adult male present. The dependent variable merged household, marital status, and fertility choice into 1 variable. The independent variables included leisure hours and income which also defined a woman's utility function. In this study, the parameters used to represent AFDC effects were not only identified by variation in the AFDC variables. 2 other studies attempting to examine AFDC's effects on demographic behavior (Hutchens [1979] and Ellwood and Bane [1985]) also failed to identify these effects. Ellwood and Bane appropriately concentrated on exogenous program variation (since benefits vary from state to state) and how it might be used in evaluating the effects of AFDC on behavior. They erroneously determined, however, that state variation should not be considered in their model. The studies reviewed in this article looked at AFDC, a program with significant intracountry parameter variation, yet these studies relied on potentially illegitimate sources of variation. Intracountry program variation is less likely to occur in Western Europe and therefore the problem of identifying effects of tax and transfer programs on demographic behavior is apt to be even more severe. Any further such studies should address these issues.
Heuveline, Patrick
2015-01-01
Estimates of excess deaths under Pol Pot's rule of Cambodia (1975-79) range from under one million to over three million. The more plausible among those, methodologically, still vary from one to two million deaths, but this range of independent point estimates has no particular statistical meaning. Stochastically reconstructing population dynamics in Cambodia from extant historical and demographic data yields interpretable distributions of the death toll and other demographic indicators. The resulting 95-percent simulation interval (1.2 to 2.8 million excess deaths) demonstrates substantial uncertainty with regards to the exact scale of mortality, yet still excludes nearly half of the previous death-toll estimates. The 1.5 to 2.25 million interval contains 69 per cent of the simulations for the actual number of excess death, more than the wider (one to two million) range of previous plausible estimates. The median value of 1.9 million excess deaths represents 21 percent of the population at risk. PMID:26218856
Estimation of pyrethroid pesticide intake using regression ...
Population-based estimates of pesticide intake are needed to characterize exposure for particular demographic groups based on their dietary behaviors. Regression modeling performed on measurements of selected pesticides in composited duplicate diet samples allowed (1) estimation of pesticide intakes for a defined demographic community, and (2) comparison of dietary pesticide intakes between the composite and individual samples. Extant databases were useful for assigning individual samples to composites, but they could not provide the breadth of information needed to facilitate measurable levels in every composite. Composite sample measurements were found to be good predictors of pyrethroid pesticide levels in their individual sample constituents where sufficient measurements are available above the method detection limit. Statistical inference shows little evidence of differences between individual and composite measurements and suggests that regression modeling of food groups based on composite dietary samples may provide an effective tool for estimating dietary pesticide intake for a defined population. The research presented in the journal article will improve community's ability to determine exposures through the dietary route with a less burdensome and costly method.
Janney, Eric C.; Hayes, Brian S.; Hewitt, David A.; Barry, Patrick M.; Scott, Alta; Koller, Justin; Johnson, Mark; Blackwood, Greta
2009-01-01
We used capture-recapture data to assess population dynamics of endangered Lost River suckers (Deltistes luxatus) and shortnose suckers (Chasmistes brevirostris) in Upper Klamath Lake, Oregon. The Cormack-Jolly-Seber method was used to estimate apparent survival probabilities, and a temporal symmetry model was used to estimate annual seniority probabilities. Information theoretic modeling was used to assess variation in parameter estimates due to time, gender, and species. In addition, length data were used to detect multiple year-class failures and events of high recruitment into adult spawning populations. Survival of adult Lost River and shortnose suckers varied substantially across years. Relatively high annual mortality was observed for the lakeshore-spawning Lost River sucker subpopulation in 2002 and for the river spawning subpopulation in 2001. Shortnose suckers experienced high mortality in 2001 and 2004. This indicates that high mortality events are not only species specific, but also are specific to subpopulations for Lost River suckers. Seniority probability estimates and length composition data indicate that recruitment of new individuals into adult sucker populations has been sparse. The overall fitness of Upper Klamath Lake sucker populations are of concern given the low observed survival in some years and the paucity of recent recruitment. During most years, estimates of survival probabilities were lower than seniority probabilities, indicating net losses in adult sucker population abundances. The evidence for decline was more marked for shortnose suckers than for Lost River suckers. Our data indicated that sucker survival for both species, but especially shortnose suckers, was sometimes low in years without any observed fish kills. This indicates that high mortality can occur over a protracted period, resulting in poor annual survival, but will not necessarily be observed in association with a fish kill. A better understanding of the factors influencing adult survival and recruitment into spawning populations is needed. Monitoring these vital parameters will provide a quantitative means to evaluate population status and assess the effectiveness of conservation and recovery efforts.
Heidari, M.; Ranjithan, S.R.
1998-01-01
In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique.In using non-linear optimization techniques for estimation of parameters in a distributed ground water model, the initial values of the parameters and prior information about them play important roles. In this paper, the genetic algorithm (GA) is combined with the truncated-Newton search technique to estimate groundwater parameters for a confined steady-state ground water model. Use of prior information about the parameters is shown to be important in estimating correct or near-correct values of parameters on a regional scale. The amount of prior information needed for an accurate solution is estimated by evaluation of the sensitivity of the performance function to the parameters. For the example presented here, it is experimentally demonstrated that only one piece of prior information of the least sensitive parameter is sufficient to arrive at the global or near-global optimum solution. For hydraulic head data with measurement errors, the error in the estimation of parameters increases as the standard deviation of the errors increases. Results from our experiments show that, in general, the accuracy of the estimated parameters depends on the level of noise in the hydraulic head data and the initial values used in the truncated-Newton search technique.
The Effect of Fertility Reduction on Economic Growth*
Ashraf, Quamrul H.; Weil, David N.; Wilde, Joshua
2014-01-01
We assess quantitatively the effect of exogenous reductions in fertility on output per capita. Our simulation model allows for effects that run through schooling, the size and age structure of the population, capital accumulation, parental time input into child-rearing, and crowding of fixed natural resources. The model is parameterized using a combination of microeconomic estimates, data on demographics and natural resource income in developing countries, and standard components of quantitative macroeconomic theory. We apply the model to examine the effect of a change in fertility from the UN medium-variant to the UN low-variant projection, using Nigerian vital rates as a baseline. For a base case set of parameters, we find that such a change would raise output per capita by 5.6 percent at a horizon of 20 years, and by 11.9 percent at a horizon of 50 years. PMID:25525283
Morrison, Cheryl L.; Springmann, Marcus J.; Iwanowicz, Deborah D.; Wade, Christopher M.
2015-01-01
A suite of tetra-nucleotide microsatellite loci were developed for the invasive giant African land snail, Achatina (=Lissachatina) fulica Bowdich, 1822, from Ion Torrent next-generation sequencing data. Ten of the 96 primer sets tested amplified consistently in 30 snails from Miami, Florida, plus 12 individuals representative of their native East Africa, Indian and Pacific Ocean regions. The loci displayed moderate levels of allelic diversity (average 5.6 alleles/locus) and heterozygosity (average 42 %). Levels of genetic diversity were sufficient to produce unique multi-locus genotypes and detect phylogeographic structuring among regional samples. The invasive A. fulica can cause extensive damage to important food crops and natural resources, including native flora and fauna. The loci characterized here will be useful for determining the origins and tracking the spread of invasions, detecting fine-scale spatial structuring and estimating demographic parameters.
How perfect can protein interactomes be?
Levy, Emmanuel D; Landry, Christian R; Michnick, Stephen W
2009-03-03
Any engineered device should certainly not contain nonfunctional components, for this would be a waste of energy and money. In contrast, evolutionary theory tells us that biological systems need not be optimized and may very well accumulate nonfunctional elements. Mutational and demographic processes contribute to the cluttering of eukaryotic genomes and transcriptional networks with "junk" DNA and spurious DNA binding sites. Here, we question whether such a notion should be applied to protein interactomes-that is, whether these protein interactomes are expected to contain a fraction of nonselected, nonfunctional protein-protein interactions (PPIs), which we term "noisy." We propose a simple relationship between the fraction of noisy interactions expected in a given organism and three parameters: (i) the number of mutations needed to create and destroy interactions, (ii) the size of the proteome, and (iii) the fitness cost of noisy interactions. All three parameters suggest that noisy PPIs are expected to exist. Their existence could help to explain why PPIs determined from large-scale studies often lack functional relationships between interacting proteins, why PPIs are poorly conserved across organisms, and why the PPI space appears to be immensely large. Finally, we propose experimental strategies to estimate the fraction of evolutionary noise in PPI networks.
King, Timothy L.; Johnson, Robin L.
2011-01-01
We document the isolation and characterization of 19 tetra-nucleotide microsatellite DNA markers in northern snakehead (Channa argus) fish that recently colonized Meadow Lake, New York City, New York. These markers displayed moderate levels of allelic diversity (averaging 6.8 alleles/locus) and heterozygosity (averaging 74.2%). Demographic analyses suggested that the Meadow Lake collection has not achieved mutation-drift equilibrium. These results were consistent with instances of deviations from Hardy–Weinberg equilibrium and the presence of some linkage disequilibrium. A comparison of individual pair-wise distances suggested the presence of multiple differentiated groups of related individuals. Results of all analyses are consistent with a pattern of multiple, recent introductions. The microsatellite markers developed for C. argus yielded sufficient genetic diversity to potentially: (1) delineate kinship; (2) elucidate fine-scale population structure; (3) define management (eradication) units; (4) estimate dispersal rates; (5) estimate population sizes; and (6) provide unique demographic perspectives of control or eradication effectiveness.
Demographic history and gene flow during silkworm domestication
2014-01-01
Background Gene flow plays an important role in domestication history of domesticated species. However, little is known about the demographic history of domesticated silkworm involving gene flow with its wild relative. Results In this study, four model-based evolutionary scenarios to describe the demographic history of B. mori were hypothesized. Using Approximate Bayesian Computation method and DNA sequence data from 29 nuclear loci, we found that the gene flow at bottleneck model is the most likely scenario for silkworm domestication. The starting time of silkworm domestication was estimated to be approximate 7,500 years ago; the time of domestication termination was 3,984 years ago. Using coalescent simulation analysis, we also found that bi-directional gene flow occurred during silkworm domestication. Conclusions Estimates of silkworm domestication time are nearly consistent with the archeological evidence and our previous results. Importantly, we found that the bi-directional gene flow might occur during silkworm domestication. Our findings add a dimension to highlight the important role of gene flow in domestication of crops and animals. PMID:25123546
Use of spatial capture-recapture modeling and DNA data to estimate densities of elusive animals
Kery, Marc; Gardner, Beth; Stoeckle, Tabea; Weber, Darius; Royle, J. Andrew
2011-01-01
Assessment of abundance, survival, recruitment rates, and density (i.e., population assessment) is especially challenging for elusive species most in need of protection (e.g., rare carnivores). Individual identification methods, such as DNA sampling, provide ways of studying such species efficiently and noninvasively. Additionally, statistical methods that correct for undetected animals and account for locations where animals are captured are available to efficiently estimate density and other demographic parameters. We collected hair samples of European wildcat (Felis silvestris) from cheek-rub lure sticks, extracted DNA from the samples, and identified each animals' genotype. To estimate the density of wildcats, we used Bayesian inference in a spatial capture-recapture model. We used WinBUGS to fit a model that accounted for differences in detection probability among individuals and seasons and between two lure arrays. We detected 21 individual wildcats (including possible hybrids) 47 times. Wildcat density was estimated at 0.29/km2 (SE 0.06), and 95% of the activity of wildcats was estimated to occur within 1.83 km from their home-range center. Lures located systematically were associated with a greater number of detections than lures placed in a cell on the basis of expert opinion. Detection probability of individual cats was greatest in late March. Our model is a generalized linear mixed model; hence, it can be easily extended, for instance, to incorporate trap- and individual-level covariates. We believe that the combined use of noninvasive sampling techniques and spatial capture-recapture models will improve population assessments, especially for rare and elusive animals.
Pichler, Gerhard; Pocivalnik, Mirjam; Riedl, Regina; Pichler-Stachl, Elisabeth; Morris, Nicholas; Zotter, Heinz; Müller, Wilhelm; Urlesberger, Berndt
2011-08-01
Interpretation of peripheral circulation in ill neonates is crucial but difficult. The aim was to analyse parameters potentially influencing peripheral oxygenation and circulation. In a prospective observational cohort study in 116 cardio-circulatory stable neonates, peripheral muscle near-infrared spectroscopy (NIRS) with venous occlusion was performed. Tissue oxygenation index (TOI), mixed venous oxygenation (SvO(2)), fractional oxygen extraction (FOE), fractional tissue oxygen extraction (FTOE), haemoglobin flow (Hbflow), oxygen delivery (DO(2)), oxygen consumption (VO(2)), and vascular resistance (VR) were assessed. Correlation coefficients between NIRS parameters and demographic parameters (gestational age, birth weight, age, actual weight, diameter of calf, subcutaneous adipose tissue), monitoring parameters (heart rate, arterial oxygen saturation (SaO(2)), mean blood pressure (MAP), core/peripheral temperature, central/peripheral capillary refill time) and laboratory parameters (haemoglobin concentration (Hb-blood), pCO(2)) were calculated. All demographic parameters except for Hbflow and DO(2) correlated with NIRS parameters. Heart rate correlated with TOI, SvO(2), VO(2) and VR. SaO(2) correlated with FOE/FTOE. MAP correlated with Hbflow, DO(2), VO(2) and VR. Core temperature correlated with FTOE. Peripheral temperature correlated with all NIRS parameters except VO(2). Hb-blood correlated with FOE and VR. pCO(2) levels correlated with TOI and SvO(2). The presence of multiple interdependent factors associated with peripheral oxygenation and circulation highlights the difficulty in interpreting NIRS data. Nevertheless, these findings have to be taken into account when analysing peripheral oxygenation and circulation data.
76 FR 30309 - Marine Mammals; File No. 16087
Federal Register 2010, 2011, 2012, 2013, 2014
2011-05-25
... authorizes taking marine mammals in California, Oregon, and Washington to investigate population status, health, demographic parameters, life history and foraging ecology of California sea lions (Zalophus...
Optimal Tuner Selection for Kalman-Filter-Based Aircraft Engine Performance Estimation
NASA Technical Reports Server (NTRS)
Simon, Donald L.; Garg, Sanjay
2011-01-01
An emerging approach in the field of aircraft engine controls and system health management is the inclusion of real-time, onboard models for the inflight estimation of engine performance variations. This technology, typically based on Kalman-filter concepts, enables the estimation of unmeasured engine performance parameters that can be directly utilized by controls, prognostics, and health-management applications. A challenge that complicates this practice is the fact that an aircraft engine s performance is affected by its level of degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. Through Kalman-filter-based estimation techniques, the level of engine performance degradation can be estimated, given that there are at least as many sensors as health parameters to be estimated. However, in an aircraft engine, the number of sensors available is typically less than the number of health parameters, presenting an under-determined estimation problem. A common approach to address this shortcoming is to estimate a subset of the health parameters, referred to as model tuning parameters. The problem/objective is to optimally select the model tuning parameters to minimize Kalman-filterbased estimation error. A tuner selection technique has been developed that specifically addresses the under-determined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine that seeks to minimize the theoretical mean-squared estimation error of the Kalman filter. This approach can significantly reduce the error in onboard aircraft engine parameter estimation applications such as model-based diagnostic, controls, and life usage calculations. The advantage of the innovation is the significant reduction in estimation errors that it can provide relative to the conventional approach of selecting a subset of health parameters to serve as the model tuning parameter vector. Because this technique needs only to be performed during the system design process, it places no additional computation burden on the onboard Kalman filter implementation. The technique has been developed for aircraft engine onboard estimation applications, as this application typically presents an under-determined estimation problem. However, this generic technique could be applied to other industries using gas turbine engine technology.
Espey, Eve; Ogburn, Tony; Leeman, Larry; Singh, Rameet; Schrader, Ronald
2013-01-01
Objective To estimate the effect of progestin-only vs. combined hormonal contraceptive pills on rates of breastfeeding continuation in postpartum women. Secondary outcomes include infant growth parameters, contraceptive method continuation and patient satisfaction with breastfeeding and contraceptive method. Methods In this randomized controlled trial, postpartum breastfeeding women who desired oral contraceptives were assigned to progestin-only vs. combined hormonal contraceptive pills. At two and eight weeks postpartum, participants completed in-person questionnaires that assessed breastfeeding continuation and contraceptive use. Infant growth parameters including weight, length and head circumference were assessed at eight weeks postpartum. Telephone questionnaires assessing breastfeeding, contraceptive continuation and satisfaction were completed at 3-7 weeks and 4 and 6 months. Breastfeeding continuation was compared between groups using Cox proportional hazards regression. Differences in baseline demographic characteristics and in variables between the two intervention groups were compared using chi-square tests, Fisher’s Exact test, or two-sample t-tests as appropriate. Results Breastfeeding continuation rates, contraceptive continuation, and infant growth parameters did not differ between users of progestin-only and combined hormonal contraceptive pills. Infant formula supplementation and maternal perception of inadequate milk supply were associated with decreased rates of breastfeeding in both groups. Conclusions Choice of combined or progestin-only birth control pills administered two weeks postpartum did not adversely affect breastfeeding continuation. PMID:22143258
Sevinc, M; Stamp, S; Ling, J; Carter, N; Talbot, D; Sheerin, N
2016-12-01
Ex vivo perfusion is used in our unit for kidneys donated after cardiac death (DCD). Perfusion flow index (PFI), resistance, and perfusate glutathione S-transferase (GST) can be measured to assess graft viability. We assessed whether measurements taken during perfusion could predict long-term outcome after transplantation. All DCD kidney transplants performed from 2002 to 2014 were included in this study. The exclusion criteria were: incomplete data, kidneys not machine perfused, kidneys perfused in continuous mode, and dual transplantation. There were 155 kidney transplantations included in the final analysis. Demographic data, ischemia times, donor hypertension, graft function, survival and machine perfusion parameters after 3 hours were analyzed. Each perfusion parameter was divided into 3 groups as high, medium, and low. Estimated glomerular filtration rate was calculated at 12 months and then yearly after transplantation. There was a significant association between graft survival and PFI and GST (P values, .020 and .022, respectively). PFI was the only independent parameter to predict graft survival. A low PFI during ex vivo hypothermic perfusion is associated with inferior graft survival after DCD kidney transplantation. We propose that PFI is a measure of the health of the graft vasculature and that a low PFI indicates vascular disease and therefore predicts a worse long-term outcome. Copyright © 2016 Elsevier Inc. All rights reserved.
Investigating the Impact of Uncertainty about Item Parameters on Ability Estimation
ERIC Educational Resources Information Center
Zhang, Jinming; Xie, Minge; Song, Xiaolan; Lu, Ting
2011-01-01
Asymptotic expansions of the maximum likelihood estimator (MLE) and weighted likelihood estimator (WLE) of an examinee's ability are derived while item parameter estimators are treated as covariates measured with error. The asymptotic formulae present the amount of bias of the ability estimators due to the uncertainty of item parameter estimators.…
Jang, Cheongjae; Ha, Junhyoung; Dupont, Pierre E.; Park, Frank Chongwoo
2017-01-01
Although existing mechanics-based models of concentric tube robots have been experimentally demonstrated to approximate the actual kinematics, determining accurate estimates of model parameters remains difficult due to the complex relationship between the parameters and available measurements. Further, because the mechanics-based models neglect some phenomena like friction, nonlinear elasticity, and cross section deformation, it is also not clear if model error is due to model simplification or to parameter estimation errors. The parameters of the superelastic materials used in these robots can be slowly time-varying, necessitating periodic re-estimation. This paper proposes a method for estimating the mechanics-based model parameters using an extended Kalman filter as a step toward on-line parameter estimation. Our methodology is validated through both simulation and experiments. PMID:28717554
Bibliography for aircraft parameter estimation
NASA Technical Reports Server (NTRS)
Iliff, Kenneth W.; Maine, Richard E.
1986-01-01
An extensive bibliography in the field of aircraft parameter estimation has been compiled. This list contains definitive works related to most aircraft parameter estimation approaches. Theoretical studies as well as practical applications are included. Many of these publications are pertinent to subjects peripherally related to parameter estimation, such as aircraft maneuver design or instrumentation considerations.
Two-dimensional advective transport in ground-water flow parameter estimation
Anderman, E.R.; Hill, M.C.; Poeter, E.P.
1996-01-01
Nonlinear regression is useful in ground-water flow parameter estimation, but problems of parameter insensitivity and correlation often exist given commonly available hydraulic-head and head-dependent flow (for example, stream and lake gain or loss) observations. To address this problem, advective-transport observations are added to the ground-water flow, parameter-estimation model MODFLOWP using particle-tracking methods. The resulting model is used to investigate the importance of advective-transport observations relative to head-dependent flow observations when either or both are used in conjunction with hydraulic-head observations in a simulation of the sewage-discharge plume at Otis Air Force Base, Cape Cod, Massachusetts, USA. The analysis procedure for evaluating the probable effect of new observations on the regression results consists of two steps: (1) parameter sensitivities and correlations calculated at initial parameter values are used to assess the model parameterization and expected relative contributions of different types of observations to the regression; and (2) optimal parameter values are estimated by nonlinear regression and evaluated. In the Cape Cod parameter-estimation model, advective-transport observations did not significantly increase the overall parameter sensitivity; however: (1) inclusion of advective-transport observations decreased parameter correlation enough for more unique parameter values to be estimated by the regression; (2) realistic uncertainties in advective-transport observations had a small effect on parameter estimates relative to the precision with which the parameters were estimated; and (3) the regression results and sensitivity analysis provided insight into the dynamics of the ground-water flow system, especially the importance of accurate boundary conditions. In this work, advective-transport observations improved the calibration of the model and the estimation of ground-water flow parameters, and use of regression and related techniques produced significant insight into the physical system.
Automated measurements of metabolic tumor volume and metabolic parameters in lung PET/CT imaging
NASA Astrophysics Data System (ADS)
Orologas, F.; Saitis, P.; Kallergi, M.
2017-11-01
Patients with lung tumors or inflammatory lung disease could greatly benefit in terms of treatment and follow-up by PET/CT quantitative imaging, namely measurements of metabolic tumor volume (MTV), standardized uptake values (SUVs) and total lesion glycolysis (TLG). The purpose of this study was the development of an unsupervised or partially supervised algorithm using standard image processing tools for measuring MTV, SUV, and TLG from lung PET/CT scans. Automated metabolic lesion volume and metabolic parameter measurements were achieved through a 5 step algorithm: (i) The segmentation of the lung areas on the CT slices, (ii) the registration of the CT segmented lung regions on the PET images to define the anatomical boundaries of the lungs on the functional data, (iii) the segmentation of the regions of interest (ROIs) on the PET images based on adaptive thresholding and clinical criteria, (iv) the estimation of the number of pixels and pixel intensities in the PET slices of the segmented ROIs, (v) the estimation of MTV, SUVs, and TLG from the previous step and DICOM header data. Whole body PET/CT scans of patients with sarcoidosis were used for training and testing the algorithm. Lung area segmentation on the CT slices was better achieved with semi-supervised techniques that reduced false positive detections significantly. Lung segmentation results agreed with the lung volumes published in the literature while the agreement between experts and algorithm in the segmentation of the lesions was around 88%. Segmentation results depended on the image resolution selected for processing. The clinical parameters, SUV (either mean or max or peak) and TLG estimated by the segmented ROIs and DICOM header data provided a way to correlate imaging data to clinical and demographic data. In conclusion, automated MTV, SUV, and TLG measurements offer powerful analysis tools in PET/CT imaging of the lungs. Custom-made algorithms are often a better approach than the manufacturer’s general analysis software at much lower cost. Relatively simple processing techniques could lead to customized, unsupervised or partially supervised methods that can successfully perform the desirable analysis and adapt to the specific disease requirements.
Advances in parameter estimation techniques applied to flexible structures
NASA Technical Reports Server (NTRS)
Maben, Egbert; Zimmerman, David C.
1994-01-01
In this work, various parameter estimation techniques are investigated in the context of structural system identification utilizing distributed parameter models and 'measured' time-domain data. Distributed parameter models are formulated using the PDEMOD software developed by Taylor. Enhancements made to PDEMOD for this work include the following: (1) a Wittrick-Williams based root solving algorithm; (2) a time simulation capability; and (3) various parameter estimation algorithms. The parameter estimations schemes will be contrasted using the NASA Mini-Mast as the focus structure.
Impact of the time scale of model sensitivity response on coupled model parameter estimation
NASA Astrophysics Data System (ADS)
Liu, Chang; Zhang, Shaoqing; Li, Shan; Liu, Zhengyu
2017-11-01
That a model has sensitivity responses to parameter uncertainties is a key concept in implementing model parameter estimation using filtering theory and methodology. Depending on the nature of associated physics and characteristic variability of the fluid in a coupled system, the response time scales of a model to parameters can be different, from hourly to decadal. Unlike state estimation, where the update frequency is usually linked with observational frequency, the update frequency for parameter estimation must be associated with the time scale of the model sensitivity response to the parameter being estimated. Here, with a simple coupled model, the impact of model sensitivity response time scales on coupled model parameter estimation is studied. The model includes characteristic synoptic to decadal scales by coupling a long-term varying deep ocean with a slow-varying upper ocean forced by a chaotic atmosphere. Results show that, using the update frequency determined by the model sensitivity response time scale, both the reliability and quality of parameter estimation can be improved significantly, and thus the estimated parameters make the model more consistent with the observation. These simple model results provide a guideline for when real observations are used to optimize the parameters in a coupled general circulation model for improving climate analysis and prediction initialization.
A Systematic Approach for Model-Based Aircraft Engine Performance Estimation
NASA Technical Reports Server (NTRS)
Simon, Donald L.; Garg, Sanjay
2010-01-01
A requirement for effective aircraft engine performance estimation is the ability to account for engine degradation, generally described in terms of unmeasurable health parameters such as efficiencies and flow capacities related to each major engine module. This paper presents a linear point design methodology for minimizing the degradation-induced error in model-based aircraft engine performance estimation applications. The technique specifically focuses on the underdetermined estimation problem, where there are more unknown health parameters than available sensor measurements. A condition for Kalman filter-based estimation is that the number of health parameters estimated cannot exceed the number of sensed measurements. In this paper, the estimated health parameter vector will be replaced by a reduced order tuner vector whose dimension is equivalent to the sensed measurement vector. The reduced order tuner vector is systematically selected to minimize the theoretical mean squared estimation error of a maximum a posteriori estimator formulation. This paper derives theoretical estimation errors at steady-state operating conditions, and presents the tuner selection routine applied to minimize these values. Results from the application of the technique to an aircraft engine simulation are presented and compared to the estimation accuracy achieved through conventional maximum a posteriori and Kalman filter estimation approaches. Maximum a posteriori estimation results demonstrate that reduced order tuning parameter vectors can be found that approximate the accuracy of estimating all health parameters directly. Kalman filter estimation results based on the same reduced order tuning parameter vectors demonstrate that significantly improved estimation accuracy can be achieved over the conventional approach of selecting a subset of health parameters to serve as the tuner vector. However, additional development is necessary to fully extend the methodology to Kalman filter-based estimation applications.
Measuring urban forestry performance and demographic associations in Massachusetts, USA
David Rines; Brian Kane; David B. Kittredge; H. Dennis P. Ryan; Brett Butler
2011-01-01
The United States Forest Service measures successful management of the urban forest by the number of communities that have achieved some or all of four parameters described by the Community Accomplishment Reporting System. The four parameters address whether a community has: (1) a management plan, (2) professional staff, (3) urban forestry ordinances/policies, and (4)...
Baena, Martha Lucía; Macías-Ordóñez, Rogelio
2012-01-01
Recent debate has highlighted the importance of estimating both the strength of sexual selection on phenotypic traits, and the opportunity for sexual selection. We describe seasonal fluctuations in mating dynamics of Leptinotarsa undecimlineata (Coleoptera: Chrysomelidae). We compared several estimates of the opportunity for, and the strength of, sexual selection and male precopulatory competition over the reproductive season. First, using a null model, we suggest that the ratio between observed values of the opportunity for sexual selections and their expected value under random mating results in unbiased estimates of the actual nonrandom mating behavior of the population. Second, we found that estimates for the whole reproductive season often misrepresent the actual value at any given time period. Third, mating differentials on male size and mobility, frequency of male fighting and three estimates of the opportunity for sexual selection provide contrasting but complementary information. More intense sexual selection associated to male mobility, but not to male size, was observed in periods with high opportunity for sexual selection and high frequency of male fights. Fourth, based on parameters of spatial and temporal aggregation of female receptivity, we describe the mating system of L. undecimlineata as a scramble mating polygyny in which the opportunity for sexual selection varies widely throughout the season, but the strength of sexual selection on male size remains fairly weak, while male mobility inversely covaries with mating success. We suggest that different estimates for the opportunity for, and intensity of, sexual selection should be applied in order to discriminate how different behavioral and demographic factors shape the reproductive dynamic of populations. PMID:22761675
Improved Estimates of Thermodynamic Parameters
NASA Technical Reports Server (NTRS)
Lawson, D. D.
1982-01-01
Techniques refined for estimating heat of vaporization and other parameters from molecular structure. Using parabolic equation with three adjustable parameters, heat of vaporization can be used to estimate boiling point, and vice versa. Boiling points and vapor pressures for some nonpolar liquids were estimated by improved method and compared with previously reported values. Technique for estimating thermodynamic parameters should make it easier for engineers to choose among candidate heat-exchange fluids for thermochemical cycles.
Link, William A; Barker, Richard J
2005-03-01
We present a hierarchical extension of the Cormack-Jolly-Seber (CJS) model for open population capture-recapture data. In addition to recaptures of marked animals, we model first captures of animals and losses on capture. The parameter set includes capture probabilities, survival rates, and birth rates. The survival rates and birth rates are treated as a random sample from a bivariate distribution, thus the model explicitly incorporates correlation in these demographic rates. A key feature of the model is that the likelihood function, which includes a CJS model factor, is expressed entirely in terms of identifiable parameters; losses on capture can be factored out of the model. Since the computational complexity of classical likelihood methods is prohibitive, we use Markov chain Monte Carlo in a Bayesian analysis. We describe an efficient candidate-generation scheme for Metropolis-Hastings sampling of CJS models and extensions. The procedure is illustrated using mark-recapture data for the moth Gonodontis bidentata.
Link, William A.; Barker, Richard J.
2005-01-01
We present a hierarchical extension of the Cormack–Jolly–Seber (CJS) model for open population capture–recapture data. In addition to recaptures of marked animals, we model first captures of animals and losses on capture. The parameter set includes capture probabilities, survival rates, and birth rates. The survival rates and birth rates are treated as a random sample from a bivariate distribution, thus the model explicitly incorporates correlation in these demographic rates. A key feature of the model is that the likelihood function, which includes a CJS model factor, is expressed entirely in terms of identifiable parameters; losses on capture can be factored out of the model. Since the computational complexity of classical likelihood methods is prohibitive, we use Markov chain Monte Carlo in a Bayesian analysis. We describe an efficient candidate-generation scheme for Metropolis–Hastings sampling of CJS models and extensions. The procedure is illustrated using mark-recapture data for the moth Gonodontis bidentata.
Estimating Convection Parameters in the GFDL CM2.1 Model Using Ensemble Data Assimilation
NASA Astrophysics Data System (ADS)
Li, Shan; Zhang, Shaoqing; Liu, Zhengyu; Lu, Lv; Zhu, Jiang; Zhang, Xuefeng; Wu, Xinrong; Zhao, Ming; Vecchi, Gabriel A.; Zhang, Rong-Hua; Lin, Xiaopei
2018-04-01
Parametric uncertainty in convection parameterization is one major source of model errors that cause model climate drift. Convection parameter tuning has been widely studied in atmospheric models to help mitigate the problem. However, in a fully coupled general circulation model (CGCM), convection parameters which impact the ocean as well as the climate simulation may have different optimal values. This study explores the possibility of estimating convection parameters with an ensemble coupled data assimilation method in a CGCM. Impacts of the convection parameter estimation on climate analysis and forecast are analyzed. In a twin experiment framework, five convection parameters in the GFDL coupled model CM2.1 are estimated individually and simultaneously under both perfect and imperfect model regimes. Results show that the ensemble data assimilation method can help reduce the bias in convection parameters. With estimated convection parameters, the analyses and forecasts for both the atmosphere and the ocean are generally improved. It is also found that information in low latitudes is relatively more important for estimating convection parameters. This study further suggests that when important parameters in appropriate physical parameterizations are identified, incorporating their estimation into traditional ensemble data assimilation procedure could improve the final analysis and climate prediction.
Dunham, Kylee; Grand, James B.
2016-10-11
The Alaskan breeding population of Steller’s eiders (Polysticta stelleri) was listed as threatened under the Endangered Species Act in 1997 in response to perceived declines in abundance throughout their breeding and nesting range. Aerial surveys suggest the breeding population is small and highly variable in number, with zero birds counted in 5 of the last 25 years. Research was conducted to evaluate competing population process models of Alaskan-breeding Steller’s eiders through comparison of model projections to aerial survey data. To evaluate model efficacy and estimate demographic parameters, a Bayesian state-space modeling framework was used and each model was fit to counts from the annual aerial surveys, using sequential importance sampling and resampling. The results strongly support that the Alaskan breeding population experiences population level nonbreeding events and is open to exchange with the larger Russian-Pacific breeding population. Current recovery criteria for the Alaskan breeding population rely heavily on the ability to estimate population viability. The results of this investigation provide an informative model of the population process that can be used to examine future population states and assess the population in terms of the current recovery and reclassification criteria.
Coscia, I; Chopelet, J; Waples, R S; Mann, B Q; Mariani, S
2016-10-01
Large variance in reproductive success is the primary factor that reduces effective population size (Ne) in natural populations. In sequentially hermaphroditic (sex-changing) fish, the sex ratio is typically skewed and biased towards the 'first' sex, while reproductive success increases considerably after sex change. Therefore, sex-changing fish populations are theoretically expected to have lower Ne than gonochorists (separate sexes), assuming all other parameters are essentially equal. In this study, we estimate Ne from genetic data collected from two ecologically similar species living along the eastern coast of South Africa: one gonochoristic, the 'santer' sea bream Cheimerius nufar, and one protogynous (female-first) sex changer, the 'slinger' sea bream Chrysoblephus puniceus. For both species, no evidence of genetic structuring, nor significant variation in genetic diversity, was found in the study area. Estimates of contemporary Ne were significantly lower in the protogynous species, but the same pattern was not apparent over historical timescales. Overall, our results show that sequential hermaphroditism may affect Ne differently over varying time frames, and that demographic signatures inferred from genetic markers with different inheritance modes also need to be interpreted cautiously, in relation to sex-changing life histories.
Raabe, Joshua K.; Gardner, Beth; Hightower, Joseph E.
2013-01-01
We developed a spatial capture–recapture model to evaluate survival and activity centres (i.e., mean locations) of tagged individuals detected along a linear array. Our spatially explicit version of the Cormack–Jolly–Seber model, analyzed using a Bayesian framework, correlates movement between periods and can incorporate environmental or other covariates. We demonstrate the model using 2010 data for anadromous American shad (Alosa sapidissima) tagged with passive integrated transponders (PIT) at a weir near the mouth of a North Carolina river and passively monitored with an upstream array of PIT antennas. The river channel constrained migrations, resulting in linear, one-dimensional encounter histories that included both weir captures and antenna detections. Individual activity centres in a given time period were a function of the individual’s previous estimated location and the river conditions (i.e., gage height). Model results indicate high within-river spawning mortality (mean weekly survival = 0.80) and more extensive movements during elevated river conditions. This model is applicable for any linear array (e.g., rivers, shorelines, and corridors), opening new opportunities to study demographic parameters, movement or migration, and habitat use.
Joint Multi-Fiber NODDI Parameter Estimation and Tractography Using the Unscented Information Filter
Reddy, Chinthala P.; Rathi, Yogesh
2016-01-01
Tracing white matter fiber bundles is an integral part of analyzing brain connectivity. An accurate estimate of the underlying tissue parameters is also paramount in several neuroscience applications. In this work, we propose to use a joint fiber model estimation and tractography algorithm that uses the NODDI (neurite orientation dispersion diffusion imaging) model to estimate fiber orientation dispersion consistently and smoothly along the fiber tracts along with estimating the intracellular and extracellular volume fractions from the diffusion signal. While the NODDI model has been used in earlier works to estimate the microstructural parameters at each voxel independently, for the first time, we propose to integrate it into a tractography framework. We extend this framework to estimate the NODDI parameters for two crossing fibers, which is imperative to trace fiber bundles through crossings as well as to estimate the microstructural parameters for each fiber bundle separately. We propose to use the unscented information filter (UIF) to accurately estimate the model parameters and perform tractography. The proposed approach has significant computational performance improvements as well as numerical robustness over the unscented Kalman filter (UKF). Our method not only estimates the confidence in the estimated parameters via the covariance matrix, but also provides the Fisher-information matrix of the state variables (model parameters), which can be quite useful to measure model complexity. Results from in-vivo human brain data sets demonstrate the ability of our algorithm to trace through crossing fiber regions, while estimating orientation dispersion and other biophysical model parameters in a consistent manner along the tracts. PMID:27147956
Reddy, Chinthala P; Rathi, Yogesh
2016-01-01
Tracing white matter fiber bundles is an integral part of analyzing brain connectivity. An accurate estimate of the underlying tissue parameters is also paramount in several neuroscience applications. In this work, we propose to use a joint fiber model estimation and tractography algorithm that uses the NODDI (neurite orientation dispersion diffusion imaging) model to estimate fiber orientation dispersion consistently and smoothly along the fiber tracts along with estimating the intracellular and extracellular volume fractions from the diffusion signal. While the NODDI model has been used in earlier works to estimate the microstructural parameters at each voxel independently, for the first time, we propose to integrate it into a tractography framework. We extend this framework to estimate the NODDI parameters for two crossing fibers, which is imperative to trace fiber bundles through crossings as well as to estimate the microstructural parameters for each fiber bundle separately. We propose to use the unscented information filter (UIF) to accurately estimate the model parameters and perform tractography. The proposed approach has significant computational performance improvements as well as numerical robustness over the unscented Kalman filter (UKF). Our method not only estimates the confidence in the estimated parameters via the covariance matrix, but also provides the Fisher-information matrix of the state variables (model parameters), which can be quite useful to measure model complexity. Results from in-vivo human brain data sets demonstrate the ability of our algorithm to trace through crossing fiber regions, while estimating orientation dispersion and other biophysical model parameters in a consistent manner along the tracts.
Goh, Joel; Pfeffer, Jeffrey; Zenios, Stefanos
2015-10-01
The existence of important socioeconomic disparities in health and mortality is a well-established fact. Many pathways have been adduced to explain inequality in life spans. In this article we examine one factor that has been somewhat neglected: People with different levels of education get sorted into jobs with different degrees of exposure to workplace attributes that contribute to poor health. We used General Social Survey data to estimate differential exposures to workplace conditions, results from a meta-analysis that estimated the effect of workplace conditions on mortality, and a model that permitted us to estimate the overall effects of workplace practices on health. We conclude that 10-38 percent of the difference in life expectancy across demographic groups can be explained by the different job conditions their members experience. Project HOPE—The People-to-People Health Foundation, Inc.
The validity of birth and pregnancy histories in rural Bangladesh.
Espeut, Donna; Becker, Stan
2015-08-28
Maternity histories provide a means of estimating fertility and mortality from surveys. The present analysis compares two types of maternity histories-birth histories and pregnancy histories-in three respects: (1) completeness of live birth and infant death reporting; (2) accuracy of the time placement of live births and infant deaths; and (3) the degree to which reported versus actual total fertility measures differ. The analysis covers a 15-year time span and is based on two data sources from Matlab, Bangladesh: the 1994 Matlab Demographic and Health Survey and, as gold standard, the vital events data from Matlab's Demographic Surveillance System. Both histories are near perfect in live-birth completeness; however, pregnancy histories do better in the completeness and time accuracy of deaths during the first year of life. Birth or pregnancy histories can be used for fertility estimation, but pregnancy histories are advised for estimating infant mortality.
Real-Time Parameter Estimation in the Frequency Domain
NASA Technical Reports Server (NTRS)
Morelli, Eugene A.
2000-01-01
A method for real-time estimation of parameters in a linear dynamic state-space model was developed and studied. The application is aircraft dynamic model parameter estimation from measured data in flight. Equation error in the frequency domain was used with a recursive Fourier transform for the real-time data analysis. Linear and nonlinear simulation examples and flight test data from the F-18 High Alpha Research Vehicle were used to demonstrate that the technique produces accurate model parameter estimates with appropriate error bounds. Parameter estimates converged in less than one cycle of the dominant dynamic mode, using no a priori information, with control surface inputs measured in flight during ordinary piloted maneuvers. The real-time parameter estimation method has low computational requirements and could be implemented
Linear Parameter Varying Control Synthesis for Actuator Failure, Based on Estimated Parameter
NASA Technical Reports Server (NTRS)
Shin, Jong-Yeob; Wu, N. Eva; Belcastro, Christine
2002-01-01
The design of a linear parameter varying (LPV) controller for an aircraft at actuator failure cases is presented. The controller synthesis for actuator failure cases is formulated into linear matrix inequality (LMI) optimizations based on an estimated failure parameter with pre-defined estimation error bounds. The inherent conservatism of an LPV control synthesis methodology is reduced using a scaling factor on the uncertainty block which represents estimated parameter uncertainties. The fault parameter is estimated using the two-stage Kalman filter. The simulation results of the designed LPV controller for a HiMXT (Highly Maneuverable Aircraft Technology) vehicle with the on-line estimator show that the desired performance and robustness objectives are achieved for actuator failure cases.
Multi-objective optimization in quantum parameter estimation
NASA Astrophysics Data System (ADS)
Gong, BeiLi; Cui, Wei
2018-04-01
We investigate quantum parameter estimation based on linear and Kerr-type nonlinear controls in an open quantum system, and consider the dissipation rate as an unknown parameter. We show that while the precision of parameter estimation is improved, it usually introduces a significant deformation to the system state. Moreover, we propose a multi-objective model to optimize the two conflicting objectives: (1) maximizing the Fisher information, improving the parameter estimation precision, and (2) minimizing the deformation of the system state, which maintains its fidelity. Finally, simulations of a simplified ɛ-constrained model demonstrate the feasibility of the Hamiltonian control in improving the precision of the quantum parameter estimation.
Cooley, Richard L.
1983-01-01
This paper investigates factors influencing the degree of improvement in estimates of parameters of a nonlinear regression groundwater flow model by incorporating prior information of unknown reliability. Consideration of expected behavior of the regression solutions and results of a hypothetical modeling problem lead to several general conclusions. First, if the parameters are properly scaled, linearized expressions for the mean square error (MSE) in parameter estimates of a nonlinear model will often behave very nearly as if the model were linear. Second, by using prior information, the MSE in properly scaled parameters can be reduced greatly over the MSE of ordinary least squares estimates of parameters. Third, plots of estimated MSE and the estimated standard deviation of MSE versus an auxiliary parameter (the ridge parameter) specifying the degree of influence of the prior information on regression results can help determine the potential for improvement of parameter estimates. Fourth, proposed criteria can be used to make appropriate choices for the ridge parameter and another parameter expressing degree of overall bias in the prior information. Results of a case study of Truckee Meadows, Reno-Sparks area, Washoe County, Nevada, conform closely to the results of the hypothetical problem. In the Truckee Meadows case, incorporation of prior information did not greatly change the parameter estimates from those obtained by ordinary least squares. However, the analysis showed that both sets of estimates are more reliable than suggested by the standard errors from ordinary least squares.
Jayaraman, C; Mummidisetty, C K; Jayaraman, A
2016-08-01
Accuracy of physical activity estimates predicted by activity monitoring technologies may be affected by device location, analysis algorithms, type of technology (i.e. wearable/stickable) and population demographics (disability) being studied. Consequently, the main purpose of this investigation was to study such sensor dynamics (i.e. effect of device location, type and population demographics on energy expenditure estimates) of two commercial activity monitors. It was hypothesized that device location, population studied (disability), choice of proprietary algorithm and type of technology used will significantly impact the accuracy of the predicted physical activity metrics. 10 healthy controls and eight individuals with spinal cord injury (SCI) performed structured activities in a laboratory environment. All participants wore, (i) three ActiGraph-G3TX's one each on their wrist, waist & ankle, (ii) a stickable activity monitor (Metria-IH1) on their upper-arm and (3) a Cosmed-K4B 2 metabolic unit, while performing sedentary (lying), low intensity (walk 50 steps at self-speed) and vigorous activity (a 6 minute walk test). To validate the hypothesis, the energy expenditures (EE) predicted by ActiGraph-GT3X and Metria-IH1 were benchmarked with estimated EE per Cosmed K4B 2 metabolic unit. To verify the step count accuracy predicted by ActiGraph-GT3X's and Metria-IH1, the manually calculated step count during the low intensity activity were compared to estimates from both devices. Results suggest that Metria-IH1 out-performed ActiGraph-GT3X in estimating EE during sedentary activity in both groups. The device location and population demographics, significantly affected the accuracy of predicted estimates. In conclusion, selecting activity monitor locations, analysis algorithm and choice of technology plays based on the movement threshold of population being studied can pave a better way for reliable healthcare decisions and data analytics in population with SCI.
Ritchie, Stephen R; Fraser, John D; Libby, Eric; Morris, Arthur J; Rainey, Paul B; Thomas, Mark G
2011-04-15
To estimate the burden of skin and soft tissue infection caused by Staphylococcus aureus (S. aureus), and to determine the effects of ethnicity and age on the rate of skin and soft tissue due to MRSA in the Auckland community. We reviewed the culture and susceptibility results of all wound swabs processed by Auckland's only community microbiology laboratory in 2007. Demographic data for a random sample of 1000 people who had a wound swab collected and for all people from whom a methicillin-resistant S. aureus (MRSA) strain was isolated were obtained and compared to demographic data for the total population of Auckland. S. aureus was isolated from 23853/47047 (51%) wound swab cultures performed in 2007; the estimated annual incidence of S. aureus isolation from a wound swab was 1847/100,000 people; and the estimated annual incidence of MRSA isolation from a wound swab was 145/100,000 people. Maori and Pacific people had higher rates of non-multiresistant MRSA infection compared with New Zealand European and Asian people; elderly New Zealand European people had much higher rates of multiresistant MRSA infections compared with people from other ethnic groups. S. aureus is a very common cause of disease in the community and the incidence of infection with MRSA subtypes varies with ethnicity.
Multistate modelling extended by behavioural rules: An application to migration.
Klabunde, Anna; Zinn, Sabine; Willekens, Frans; Leuchter, Matthias
2017-10-01
We propose to extend demographic multistate models by adding a behavioural element: behavioural rules explain intentions and thus transitions. Our framework is inspired by the Theory of Planned Behaviour. We exemplify our approach with a model of migration from Senegal to France. Model parameters are determined using empirical data where available. Parameters for which no empirical correspondence exists are determined by calibration. Age- and period-specific migration rates are used for model validation. Our approach adds to the toolkit of demographic projection by allowing for shocks and social influence, which alter behaviour in non-linear ways, while sticking to the general framework of multistate modelling. Our simulations yield that higher income growth in Senegal leads to higher emigration rates in the medium term, while a decrease in fertility yields lower emigration rates.
Forbidden fruit: human settlement and abundant fruit create an ecological trap for an apex omnivore.
Lamb, Clayton T; Mowat, Garth; McLellan, Bruce N; Nielsen, Scott E; Boutin, Stan
2017-01-01
Habitat choice is an evolutionary product of animals experiencing increased fitness when preferentially occupying high-quality habitat. However, an ecological trap (ET) can occur when an animal is presented with novel conditions and the animal's assessment of habitat quality is poorly matched to its resulting fitness. We tested for an ET for grizzly (brown) bears using demographic and movement data collected in an area with rich food resources and concentrated human settlement. We derived measures of habitat attractiveness from occurrence models of bear food resources and estimated demographic parameters using DNA mark-recapture information collected over 8 years (2006-2013). We then paired this information with grizzly bear mortality records to investigate kill and movement rates. Our results demonstrate that a valley high in both berry resources and human density was more attractive than surrounding areas, and bears occupying this region faced 17% lower apparent survival. Despite lower fitness, we detected a net flow of bears into the ET, which contributed to a study-wide population decline. This work highlights the presence and pervasiveness of an ET for an apex omnivore that lacks the evolutionary cues, under human-induced rapid ecological change, to assess trade-offs between food resources and human-caused mortality, which results in maladaptive habitat selection. © 2016 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.
Sleep and Health Resilience Metrics in a Large Military Cohort.
Seelig, Amber D; Jacobson, Isabel G; Donoho, Carrie J; Trone, Daniel W; Crum-Cianflone, Nancy F; Balkin, Thomas J
2016-05-01
Examine the relationship between self-reported sleep parameters and indicators of resilience in a US military population (n = 55,021). Longitudinal analyses (2001-2008) were conducted using subjective data collected from Millennium Cohort Study questionnaires and objective data from military records that included demographics, military health, and deployment information. Subjective sleep duration and insomnia symptoms were collected on the study questionnaire. Resilience metrics included lost work days, self-rated health, deployment, frequency and duration of health care utilization, and early discharge from the military. Generalized estimating equations and survival analyses were adjusted for demographic, military, behavioral, and health covariates in all models. The presence of insomnia symptoms was significantly associated with lower self-rated health, more lost work days, lower odds of deployment, higher odds of early discharge from military service early, and more health care utilization. Those self-reporting < 6 h (short sleepers) or > 8 h (long sleepers) of sleep per night had similar findings, except for the deployment outcome in which those with the shortest sleep were more likely to deploy. Poor sleep is a detriment to service members' health and readiness. Leadership should redouble efforts to emphasize the importance of healthy sleep among military service members, and future research should focus on the efficacy of interventions to promote healthy sleep and resilience in this population. A commentary on this article appears in this issue on page 963. © 2016 Associated Professional Sleep Societies, LLC.
Estimated Full Scale IQ in an Adult Heroin Addict Population.
ERIC Educational Resources Information Center
Chastain, Robert L.; And Others
The research concerning intellectual functioning in addict populations has not addressed basic questions concerning why and how intelligence quotients (IQ) might be related to drug addiction. A study was undertaken to estimate intellectual functioning based upon a demographic profile for Wechsler Adult Intelligence Scale-Revised (WAIS-R) Full…
Stommel, Manfred; Schoenborn, Charlotte A
2009-11-19
The Body Mass Index (BMI) based on self-reported height and weight ("self-reported BMI") in epidemiologic studies is subject to measurement error. However, because of the ease and efficiency in gathering height and weight information through interviews, it remains important to assess the extent of error present in self-reported BMI measures and to explore possible adjustment factors as well as valid uses of such self-reported measures. Using the combined 2001-2006 data from the continuous National Health and Nutrition Examination Survey, discrepancies between BMI measures based on self-reported and physical height and weight measures are estimated and socio-demographic predictors of such discrepancies are identified. Employing adjustments derived from the socio-demographic predictors, the self-reported measures of height and weight in the 2001-2006 National Health Interview Survey are used for population estimates of overweight & obesity as well as the prediction of health risks associated with large BMI values. The analysis relies on two-way frequency tables as well as linear and logistic regression models. All point and variance estimates take into account the complex survey design of the studies involved. Self-reported BMI values tend to overestimate measured BMI values at the low end of the BMI scale (< 22) and underestimate BMI values at the high end, particularly at values > 28. The discrepancies also vary systematically with age (younger and older respondents underestimate their BMI more than respondents aged 42-55), gender and the ethnic/racial background of the respondents. BMI scores, adjusted for socio-demographic characteristics of the respondents, tend to narrow, but do not eliminate misclassification of obese people as merely overweight, but health risk estimates associated with variations in BMI values are virtually the same, whether based on self-report or measured BMI values. BMI values based on self-reported height and weight, if corrected for biases associated with socio-demographic characteristics of the survey respondents, can be used to estimate health risks associated with variations in BMI, particularly when using parametric prediction models.
Meiklejohn, Jessica; Connor, Jennie; Kypri, Kypros
2012-01-01
Background Response rates for surveys of alcohol use are declining for all modes of administration (postal, telephone, face-to-face). Low response rates may result in estimates that are biased by selective non-response. We examined non-response bias in the NZ GENACIS survey, a postal survey of a random electoral roll sample, with a response rate of 49.5% (n = 1924). Our aim was to estimate the magnitude of non-response bias in estimating the prevalence of current drinking and heavy episodic (binge) drinking. Methods We used the “continuum of resistance” model to guide the investigation. In this model the likelihood of response by sample members is related to the amount of effort required from the researchers to elicit a response. First, the demographic characteristics of respondents and non-respondents were compared. Second, respondents who returned their questionnaire before the first reminder (early), before the second reminder (intermediate) or after the second reminder (late) were compared by demographic characteristics, 12-month prevalence of drinking and prevalence of binge drinking. Results Demographic characteristics and prevalence of binge drinking were significantly different between late respondents and early/intermediate respondents, with the demographics of early and intermediate respondents being similar to people who refused to participate while late respondents were similar to all other non-respondents. Assuming non-respondents who did not actively refuse to participate had the same drinking patterns as late respondents, the prevalence of binge drinking amongst current drinkers was underestimated. Adjusting the prevalence of binge drinkers amongst current drinkers using population weights showed that this method of adjustment still resulted in an underestimate of the prevalence. Conclusions The findings suggest non-respondents who did not actively refuse to participate are likely to have similar or more extreme drinking behaviours than late respondents, and that surveys of health compromising behaviours such as alcohol use are likely to underestimate the prevalence of these behaviours. PMID:22532858
Mandic, Sandra; Walker, Robert; Stevens, Emily; Nye, Edwin R; Body, Dianne; Barclay, Leanne; Williams, Michael J A
2013-01-01
Compared with symptom-limited cardiopulmonary exercise test (CPET), timed walking tests are cheaper, well-tolerated and simpler alternative for assessing exercise capacity in coronary artery disease (CAD) patients. We developed multivariate models for predicting peak oxygen consumption (VO2peak) from 6-minute walk test (6MWT) distance and peak shuttle walk speed for elderly stable CAD patients. Fifty-eight CAD patients (72 SD 6 years, 66% men) completed: (1) CPET with expired gas analysis on a cycle ergometer, (2) incremental 10-meter shuttle walk test, (3) two 6MWTs, (4) anthropometric assessment and (5) 30-second chair stands. Linear regression models were developed for estimating VO2peak from 6MWT distance and peak shuttle walk speed as well as demographic, anthropometric and functional variables. Measured VO2peak was significantly related to 6MWT distance (r = 0.719, p < 0.001) and peak shuttle walk speed (r = 0.717, p < 0.001). The addition of demographic (age, gender), anthropometric (height, weight, body mass index, body composition) and functional characteristics (30-second chair stands) increased the accuracy of predicting VO2peak from both 6MWT distance and peak shuttle walk speed (from 51% to 73% of VO2peak variance explained). Addition of demographic, anthropometric and functional characteristics improves the accuracy of VO2peak estimate based on walking tests in elderly individuals with stable CAD. Implications for Rehabilitation Timed walking tests are cheaper, well-tolerated and simpler alternative for assessing exercise capacity in cardiac patients. Walking tests could be used to assess individual's functional capacity and response to therapeutic interventions when symptom-limited cardiopulmonary exercise testing is not practical or not necessary for clinical reasons. Addition of demographic, anthropometric and functional characteristics improves the accuracy of peak oxygen consumption estimate based on 6-minute walk test distance and peak shuttle walk speed in elderly patients with coronary artery disease.
Combining multistate capture-recapture data with tag recoveries to estimate demographic parameters
Kendall, W.L.; Conn, P.B.; Hines, J.E.
2006-01-01
Matrix population models that allow an animal to occupy more than one state over time are important tools for population and evolutionary ecologists. Definition of state can vary, including location for metapopulation models and breeding state for life history models. For populations whose members can be marked and subsequently re-encountered, multistate mark-recapture models are available to estimate the survival and transition probabilities needed to construct population models. Multistate models have proved extremely useful in this context, but they often require a substantial amount of data and restrict estimation of transition probabilities to those areas or states subjected to formal sampling effort. At the same time, for many species, there are considerable tag recovery data provided by the public that could be modeled in order to increase precision and to extend inference to a greater number of areas or states. Here we present a statistical model for combining multistate capture-recapture data (e.g., from a breeding ground study) with multistate tag recovery data (e.g., from wintering grounds). We use this method to analyze data from a study of Canada Geese (Branta canadensis) in the Atlantic Flyway of North America. Our analysis produced marginal improvement in precision, due to relatively few recoveries, but we demonstrate how precision could be further improved with increases in the probability that a retrieved tag is reported.
Power of tests for comparing trend curves with application to national immunization survey (NIS).
Zhao, Zhen
2011-02-28
To develop statistical tests for comparing trend curves of study outcomes between two socio-demographic strata across consecutive time points, and compare statistical power of the proposed tests under different trend curves data, three statistical tests were proposed. For large sample size with independent normal assumption among strata and across consecutive time points, the Z and Chi-square test statistics were developed, which are functions of outcome estimates and the standard errors at each of the study time points for the two strata. For small sample size with independent normal assumption, the F-test statistic was generated, which is a function of sample size of the two strata and estimated parameters across study period. If two trend curves are approximately parallel, the power of Z-test is consistently higher than that of both Chi-square and F-test. If two trend curves cross at low interaction, the power of Z-test is higher than or equal to the power of both Chi-square and F-test; however, at high interaction, the powers of Chi-square and F-test are higher than that of Z-test. The measurement of interaction of two trend curves was defined. These tests were applied to the comparison of trend curves of vaccination coverage estimates of standard vaccine series with National Immunization Survey (NIS) 2000-2007 data. Copyright © 2011 John Wiley & Sons, Ltd.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hunt, W. G.; Jackman, R. E.; Hunt, T. L.
1999-07-20
The wind industry has annually reported 28-43 turbine blade strike casualties of golden eagles in the Altamont Pass Wind Resource Area, and many more carcasses have doubtless gone unnoticed. Because this species is especially sensitive to adult survival rate changes, we focused upon estimating the demographic trend of the population. In aerial surveys, we monitored survival within a sample of 179 radio-tagged eagles over a four-year period. We also obtained data on territory occupancy and reproduction of about 65 eagle pairs residing in the area. Of 61 recorded deaths of radio-tagged eagles during the four-year investigation, 23 (38%) were causedmore » by wind turbine blade strikes. Additional fatalities were unrecorded because blade strikes sometimes destroy radio transmitters. Annual survival was estimated at 0.7867 (SE=0.0263) for non-territorial eagles and 0.8964 (SE=0.0371) for territorial ones. Annual reproduction was 0.64 (SE=0.08) young per territorial pair (0.25 per female). These parameters were used to estimate population growth rates under different modeling frameworks. At present, there are indications that a reserve of non-breeding adults still exists, i.e., there is an annual territorial reoccupancy rate of 100% and a low incidence (3%) of subadults as members of breeding pairs.« less
Chan, Stephen C Y; Karczmarski, Leszek
2017-01-01
Indo-Pacific humpback dolphins (Sousa chinensis) inhabiting Hong Kong waters are thought to be among the world's most anthropogenically impacted coastal delphinids. We have conducted a 5-year (2010-2014) photo-ID study and performed the first in this region comprehensive mark-recapture analysis applying a suite of open population models and robust design models. Cormack-Jolly-Seber (CJS) models suggested a significant transient effect and seasonal variation in apparent survival probabilities as result of a fluid movement beyond the study area. Given the spatial restrictions of our study, limited by an administrative border, if emigration was to be considered negligible the estimated survival rate of adults was 0.980. Super-population estimates indicated that at least 368 dolphins used Hong Kong waters as part of their range. Closed robust design models suggested an influx of dolphins from winter to summer and increased site fidelity in summer; and outflux, although less prominent, during summer-winter intervals. Abundance estimates in summer (N = 144-231) were higher than that in winter (N = 87-111), corresponding to the availability of prey resources which in Hong Kong waters peaks during summer months. We point out that the current population monitoring strategy used by the Hong Kong authorities is ill-suited for a timely detection of a population change and should be revised.
2017-01-01
Indo-Pacific humpback dolphins (Sousa chinensis) inhabiting Hong Kong waters are thought to be among the world's most anthropogenically impacted coastal delphinids. We have conducted a 5-year (2010–2014) photo-ID study and performed the first in this region comprehensive mark-recapture analysis applying a suite of open population models and robust design models. Cormack-Jolly-Seber (CJS) models suggested a significant transient effect and seasonal variation in apparent survival probabilities as result of a fluid movement beyond the study area. Given the spatial restrictions of our study, limited by an administrative border, if emigration was to be considered negligible the estimated survival rate of adults was 0.980. Super-population estimates indicated that at least 368 dolphins used Hong Kong waters as part of their range. Closed robust design models suggested an influx of dolphins from winter to summer and increased site fidelity in summer; and outflux, although less prominent, during summer-winter intervals. Abundance estimates in summer (N = 144–231) were higher than that in winter (N = 87–111), corresponding to the availability of prey resources which in Hong Kong waters peaks during summer months. We point out that the current population monitoring strategy used by the Hong Kong authorities is ill-suited for a timely detection of a population change and should be revised. PMID:28355228
Waller, Niels G; Feuerstahler, Leah
2017-01-01
In this study, we explored item and person parameter recovery of the four-parameter model (4PM) in over 24,000 real, realistic, and idealized data sets. In the first analyses, we fit the 4PM and three alternative models to data from three Minnesota Multiphasic Personality Inventory-Adolescent form factor scales using Bayesian modal estimation (BME). Our results indicated that the 4PM fits these scales better than simpler item Response Theory (IRT) models. Next, using the parameter estimates from these real data analyses, we estimated 4PM item parameters in 6,000 realistic data sets to establish minimum sample size requirements for accurate item and person parameter recovery. Using a factorial design that crossed discrete levels of item parameters, sample size, and test length, we also fit the 4PM to an additional 18,000 idealized data sets to extend our parameter recovery findings. Our combined results demonstrated that 4PM item parameters and parameter functions (e.g., item response functions) can be accurately estimated using BME in moderate to large samples (N ⩾ 5, 000) and person parameters can be accurately estimated in smaller samples (N ⩾ 1, 000). In the supplemental files, we report annotated [Formula: see text] code that shows how to estimate 4PM item and person parameters in [Formula: see text] (Chalmers, 2012 ).
Pradhan, Sudeep; Song, Byungjeong; Lee, Jaeyeon; Chae, Jung-Woo; Kim, Kyung Im; Back, Hyun-Moon; Han, Nayoung; Kwon, Kwang-Il; Yun, Hwi-Yeol
2017-12-01
Exploratory preclinical, as well as clinical trials, may involve a small number of patients, making it difficult to calculate and analyze the pharmacokinetic (PK) parameters, especially if the PK parameters show very high inter-individual variability (IIV). In this study, the performance of a classical first-order conditional estimation with interaction (FOCE-I) and expectation maximization (EM)-based Markov chain Monte Carlo Bayesian (BAYES) estimation methods were compared for estimating the population parameters and its distribution from data sets having a low number of subjects. In this study, 100 data sets were simulated with eight sampling points for each subject and with six different levels of IIV (5%, 10%, 20%, 30%, 50%, and 80%) in their PK parameter distribution. A stochastic simulation and estimation (SSE) study was performed to simultaneously simulate data sets and estimate the parameters using four different methods: FOCE-I only, BAYES(C) (FOCE-I and BAYES composite method), BAYES(F) (BAYES with all true initial parameters and fixed ω 2 ), and BAYES only. Relative root mean squared error (rRMSE) and relative estimation error (REE) were used to analyze the differences between true and estimated values. A case study was performed with a clinical data of theophylline available in NONMEM distribution media. NONMEM software assisted by Pirana, PsN, and Xpose was used to estimate population PK parameters, and R program was used to analyze and plot the results. The rRMSE and REE values of all parameter (fixed effect and random effect) estimates showed that all four methods performed equally at the lower IIV levels, while the FOCE-I method performed better than other EM-based methods at higher IIV levels (greater than 30%). In general, estimates of random-effect parameters showed significant bias and imprecision, irrespective of the estimation method used and the level of IIV. Similar performance of the estimation methods was observed with theophylline dataset. The classical FOCE-I method appeared to estimate the PK parameters more reliably than the BAYES method when using a simple model and data containing only a few subjects. EM-based estimation methods can be considered for adapting to the specific needs of a modeling project at later steps of modeling.
Control system estimation and design for aerospace vehicles
NASA Technical Reports Server (NTRS)
Stefani, R. T.; Williams, T. L.; Yakowitz, S. J.
1972-01-01
The selection of an estimator which is unbiased when applied to structural parameter estimation is discussed. The mathematical relationships for structural parameter estimation are defined. It is shown that a conventional weighted least squares (CWLS) estimate is biased when applied to structural parameter estimation. Two approaches to bias removal are suggested: (1) change the CWLS estimator or (2) change the objective function. The advantages of each approach are analyzed.
NASA Astrophysics Data System (ADS)
Choi, Hon-Chit; Wen, Lingfeng; Eberl, Stefan; Feng, Dagan
2006-03-01
Dynamic Single Photon Emission Computed Tomography (SPECT) has the potential to quantitatively estimate physiological parameters by fitting compartment models to the tracer kinetics. The generalized linear least square method (GLLS) is an efficient method to estimate unbiased kinetic parameters and parametric images. However, due to the low sensitivity of SPECT, noisy data can cause voxel-wise parameter estimation by GLLS to fail. Fuzzy C-Mean (FCM) clustering and modified FCM, which also utilizes information from the immediate neighboring voxels, are proposed to improve the voxel-wise parameter estimation of GLLS. Monte Carlo simulations were performed to generate dynamic SPECT data with different noise levels and processed by general and modified FCM clustering. Parametric images were estimated by Logan and Yokoi graphical analysis and GLLS. The influx rate (K I), volume of distribution (V d) were estimated for the cerebellum, thalamus and frontal cortex. Our results show that (1) FCM reduces the bias and improves the reliability of parameter estimates for noisy data, (2) GLLS provides estimates of micro parameters (K I-k 4) as well as macro parameters, such as volume of distribution (Vd) and binding potential (BP I & BP II) and (3) FCM clustering incorporating neighboring voxel information does not improve the parameter estimates, but improves noise in the parametric images. These findings indicated that it is desirable for pre-segmentation with traditional FCM clustering to generate voxel-wise parametric images with GLLS from dynamic SPECT data.
ERIC Educational Resources Information Center
Finch, Holmes; Edwards, Julianne M.
2016-01-01
Standard approaches for estimating item response theory (IRT) model parameters generally work under the assumption that the latent trait being measured by a set of items follows the normal distribution. Estimation of IRT parameters in the presence of nonnormal latent traits has been shown to generate biased person and item parameter estimates. A…
An Integrated Approach for Aircraft Engine Performance Estimation and Fault Diagnostics
NASA Technical Reports Server (NTRS)
imon, Donald L.; Armstrong, Jeffrey B.
2012-01-01
A Kalman filter-based approach for integrated on-line aircraft engine performance estimation and gas path fault diagnostics is presented. This technique is specifically designed for underdetermined estimation problems where there are more unknown system parameters representing deterioration and faults than available sensor measurements. A previously developed methodology is applied to optimally design a Kalman filter to estimate a vector of tuning parameters, appropriately sized to enable estimation. The estimated tuning parameters can then be transformed into a larger vector of health parameters representing system performance deterioration and fault effects. The results of this study show that basing fault isolation decisions solely on the estimated health parameter vector does not provide ideal results. Furthermore, expanding the number of the health parameters to address additional gas path faults causes a decrease in the estimation accuracy of those health parameters representative of turbomachinery performance deterioration. However, improved fault isolation performance is demonstrated through direct analysis of the estimated tuning parameters produced by the Kalman filter. This was found to provide equivalent or superior accuracy compared to the conventional fault isolation approach based on the analysis of sensed engine outputs, while simplifying online implementation requirements. Results from the application of these techniques to an aircraft engine simulation are presented and discussed.
NASA Astrophysics Data System (ADS)
Sedaghat, A.; Bayat, H.; Safari Sinegani, A. A.
2016-03-01
The saturated hydraulic conductivity ( K s ) of the soil is one of the main soil physical properties. Indirect estimation of this parameter using pedo-transfer functions (PTFs) has received considerable attention. The Purpose of this study was to improve the estimation of K s using fractal parameters of particle and micro-aggregate size distributions in smectitic soils. In this study 260 disturbed and undisturbed soil samples were collected from Guilan province, the north of Iran. The fractal model of Bird and Perrier was used to compute the fractal parameters of particle and micro-aggregate size distributions. The PTFs were developed by artificial neural networks (ANNs) ensemble to estimate K s by using available soil data and fractal parameters. There were found significant correlations between K s and fractal parameters of particles and microaggregates. Estimation of K s was improved significantly by using fractal parameters of soil micro-aggregates as predictors. But using geometric mean and geometric standard deviation of particles diameter did not improve K s estimations significantly. Using fractal parameters of particles and micro-aggregates simultaneously, had the most effect in the estimation of K s . Generally, fractal parameters can be successfully used as input parameters to improve the estimation of K s in the PTFs in smectitic soils. As a result, ANNs ensemble successfully correlated the fractal parameters of particles and micro-aggregates to K s .
Prophylactic ranitidine treatment in critically ill children – a population pharmacokinetic study
Hawwa, Ahmed F; Westwood, Paul M; Collier, Paul S; Millership, Jeffrey S; Yakkundi, Shirish; Thurley, Gillian; Shields, Mike D; Nunn, Anthony J; Halliday, Henry L; McElnay, James C
2013-01-01
Aims To characterize the population pharmacokinetics of ranitidine in critically ill children and to determine the influence of various clinical and demographic factors on its disposition. Methods Data were collected prospectively from 78 paediatric patients (n = 248 plasma samples) who received oral or intravenous ranitidine for prophylaxis against stress ulcers, gastrointestinal bleeding or the treatment of gastro-oesophageal reflux. Plasma samples were analysed using high-performance liquid chromatography, and the data were subjected to population pharmacokinetic analysis using nonlinear mixed-effects modelling. Results A one-compartment model best described the plasma concentration profile, with an exponential structure for interindividual errors and a proportional structure for intra-individual error. After backward stepwise elimination, the final model showed a significant decrease in objective function value (−12.618; P < 0.001) compared with the weight-corrected base model. Final parameter estimates for the population were 32.1 l h−1 for total clearance and 285 l for volume of distribution, both allometrically modelled for a 70 kg adult. Final estimates for absorption rate constant and bioavailability were 1.31 h−1 and 27.5%, respectively. No significant relationship was found between age and weight-corrected ranitidine pharmacokinetic parameters in the final model, with the covariate for cardiac failure or surgery being shown to reduce clearance significantly by a factor of 0.46. Conclusions Currently, ranitidine dose recommendations are based on children's weights. However, our findings suggest that a dosing scheme that takes into consideration both weight and cardiac failure/surgery would be more appropriate in order to avoid administration of higher or more frequent doses than necessary. PMID:23016949
Adaptive Modal Identification for Flutter Suppression Control
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Drew, Michael; Swei, Sean S.
2016-01-01
In this paper, we will develop an adaptive modal identification method for identifying the frequencies and damping of a flutter mode based on model-reference adaptive control (MRAC) and least-squares methods. The least-squares parameter estimation will achieve parameter convergence in the presence of persistent excitation whereas the MRAC parameter estimation does not guarantee parameter convergence. Two adaptive flutter suppression control approaches are developed: one based on MRAC and the other based on the least-squares method. The MRAC flutter suppression control is designed as an integral part of the parameter estimation where the feedback signal is used to estimate the modal information. On the other hand, the separation principle of control and estimation is applied to the least-squares method. The least-squares modal identification is used to perform parameter estimation.
Extremes in ecology: Avoiding the misleading effects of sampling variation in summary analyses
Link, W.A.; Sauer, J.R.
1996-01-01
Surveys such as the North American Breeding Bird Survey (BBS) produce large collections of parameter estimates. One's natural inclination when confronted with lists of parameter estimates is to look for the extreme values: in the BBS, these correspond to the species that appear to have the greatest changes in population size through time. Unfortunately, extreme estimates are liable to correspond to the most poorly estimated parameters. Consequently, the most extreme parameters may not match up with the most extreme parameter estimates. The ranking of parameter values on the basis of their estimates are a difficult statistical problem. We use data from the BBS and simulations to illustrate the potential misleading effects of sampling variation in rankings of parameters. We describe empirical Bayes and constrained empirical Bayes procedures which provide partial solutions to the problem of ranking in the presence of sampling variation.
NASA Astrophysics Data System (ADS)
Wu, Fang-Xiang; Mu, Lei; Shi, Zhong-Ke
2010-01-01
The models of gene regulatory networks are often derived from statistical thermodynamics principle or Michaelis-Menten kinetics equation. As a result, the models contain rational reaction rates which are nonlinear in both parameters and states. It is challenging to estimate parameters nonlinear in a model although there have been many traditional nonlinear parameter estimation methods such as Gauss-Newton iteration method and its variants. In this article, we develop a two-step method to estimate the parameters in rational reaction rates of gene regulatory networks via weighted linear least squares. This method takes the special structure of rational reaction rates into consideration. That is, in the rational reaction rates, the numerator and the denominator are linear in parameters. By designing a special weight matrix for the linear least squares, parameters in the numerator and the denominator can be estimated by solving two linear least squares problems. The main advantage of the developed method is that it can produce the analytical solutions to the estimation of parameters in rational reaction rates which originally is nonlinear parameter estimation problem. The developed method is applied to a couple of gene regulatory networks. The simulation results show the superior performance over Gauss-Newton method.
A new Bayesian recursive technique for parameter estimation
NASA Astrophysics Data System (ADS)
Kaheil, Yasir H.; Gill, M. Kashif; McKee, Mac; Bastidas, Luis
2006-08-01
The performance of any model depends on how well its associated parameters are estimated. In the current application, a localized Bayesian recursive estimation (LOBARE) approach is devised for parameter estimation. The LOBARE methodology is an extension of the Bayesian recursive estimation (BARE) method. It is applied in this paper on two different types of models: an artificial intelligence (AI) model in the form of a support vector machine (SVM) application for forecasting soil moisture and a conceptual rainfall-runoff (CRR) model represented by the Sacramento soil moisture accounting (SAC-SMA) model. Support vector machines, based on statistical learning theory (SLT), represent the modeling task as a quadratic optimization problem and have already been used in various applications in hydrology. They require estimation of three parameters. SAC-SMA is a very well known model that estimates runoff. It has a 13-dimensional parameter space. In the LOBARE approach presented here, Bayesian inference is used in an iterative fashion to estimate the parameter space that will most likely enclose a best parameter set. This is done by narrowing the sampling space through updating the "parent" bounds based on their fitness. These bounds are actually the parameter sets that were selected by BARE runs on subspaces of the initial parameter space. The new approach results in faster convergence toward the optimal parameter set using minimum training/calibration data and fewer sets of parameter values. The efficacy of the localized methodology is also compared with the previously used BARE algorithm.
Individual heterogeneity in life histories and eco-evolutionary dynamics
Vindenes, Yngvild; Langangen, Øystein
2015-01-01
Individual heterogeneity in life history shapes eco-evolutionary processes, and unobserved heterogeneity can affect demographic outputs characterising life history and population dynamical properties. Demographic frameworks like matrix models or integral projection models represent powerful approaches to disentangle mechanisms linking individual life histories and population-level processes. Recent developments have provided important steps towards their application to study eco-evolutionary dynamics, but so far individual heterogeneity has largely been ignored. Here, we present a general demographic framework that incorporates individual heterogeneity in a flexible way, by separating static and dynamic traits (discrete or continuous). First, we apply the framework to derive the consequences of ignoring heterogeneity for a range of widely used demographic outputs. A general conclusion is that besides the long-term growth rate lambda, all parameters can be affected. Second, we discuss how the framework can help advance current demographic models of eco-evolutionary dynamics, by incorporating individual heterogeneity. For both applications numerical examples are provided, including an empirical example for pike. For instance, we demonstrate that predicted demographic responses to climate warming can be reversed by increased heritability. We discuss how applications of this demographic framework incorporating individual heterogeneity can help answer key biological questions that require a detailed understanding of eco-evolutionary dynamics. PMID:25807980
Sample Size and Item Parameter Estimation Precision When Utilizing the One-Parameter "Rasch" Model
ERIC Educational Resources Information Center
Custer, Michael
2015-01-01
This study examines the relationship between sample size and item parameter estimation precision when utilizing the one-parameter model. Item parameter estimates are examined relative to "true" values by evaluating the decline in root mean squared deviation (RMSD) and the number of outliers as sample size increases. This occurs across…
A Comparative Study of Distribution System Parameter Estimation Methods
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sun, Yannan; Williams, Tess L.; Gourisetti, Sri Nikhil Gup
2016-07-17
In this paper, we compare two parameter estimation methods for distribution systems: residual sensitivity analysis and state-vector augmentation with a Kalman filter. These two methods were originally proposed for transmission systems, and are still the most commonly used methods for parameter estimation. Distribution systems have much lower measurement redundancy than transmission systems. Therefore, estimating parameters is much more difficult. To increase the robustness of parameter estimation, the two methods are applied with combined measurement snapshots (measurement sets taken at different points in time), so that the redundancy for computing the parameter values is increased. The advantages and disadvantages of bothmore » methods are discussed. The results of this paper show that state-vector augmentation is a better approach for parameter estimation in distribution systems. Simulation studies are done on a modified version of IEEE 13-Node Test Feeder with varying levels of measurement noise and non-zero error in the other system model parameters.« less
Shkolnikov, Vladimir M; Jasilionis, Domantas; Andreev, Evgeny M; Jdanov, Dmitri A; Stankuniene, Vladislava; Ambrozaitiene, Dalia
2007-04-01
Earlier studies have found large and increasing with time differences in mortality by education and marital status in post-Soviet countries. Their results are based on independent tabulations of population and deaths counts (unlinked data). The present study provides the first census-linked estimates of group-specific mortality and the first comparison between census-linked and unlinked mortality estimates for a post-Soviet country. The study is based on a data set linking 140,000 deaths occurring in 2001-2004 in Lithuania with the population census of 2001. The same socio-demographic information about the deceased is available from both the census and death records. Cross-tabulations and Poisson regressions are used to compare linked and unlinked data. Linked and unlinked estimates of life expectancies and mortality rate ratios are calculated with standard life table techniques and Poisson regressions. For the two socio-demographic variables under study, the values from the death records partly differ from those from the census records. The deviations are especially significant for education, with 72-73%, 66-67%, and 82-84% matching for higher education, secondary education, and lower education, respectively. For marital status, deviations are less frequent. For education and marital status, unlinked estimates tend to overstate mortality in disadvantaged groups and they understate mortality in advantaged groups. The differences in inter-group life expectancy and the mortality rate ratios thus are significantly overestimated in the unlinked data. Socio-demographic differences in mortality previously observed in Lithuania and possibly other post-Soviet countries are overestimated. The growth in inequalities over the 1990s is real but might be overstated. The results of this study confirm the existence of large and widening health inequalities but call for better data.
2011-01-01
In systems biology, experimentally measured parameters are not always available, necessitating the use of computationally based parameter estimation. In order to rely on estimated parameters, it is critical to first determine which parameters can be estimated for a given model and measurement set. This is done with parameter identifiability analysis. A kinetic model of the sucrose accumulation in the sugar cane culm tissue developed by Rohwer et al. was taken as a test case model. What differentiates this approach is the integration of an orthogonal-based local identifiability method into the unscented Kalman filter (UKF), rather than using the more common observability-based method which has inherent limitations. It also introduces a variable step size based on the system uncertainty of the UKF during the sensitivity calculation. This method identified 10 out of 12 parameters as identifiable. These ten parameters were estimated using the UKF, which was run 97 times. Throughout the repetitions the UKF proved to be more consistent than the estimation algorithms used for comparison. PMID:21989173
Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior
NASA Technical Reports Server (NTRS)
Popovici, Alexandru; Zaal, Peter M. T.; Pool, Daan M.
2017-01-01
A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces.
The effects of intraspecific competition and stabilizing selection on a polygenic trait.
Bürger, Reinhard; Gimelfarb, Alexander
2004-01-01
The equilibrium properties of an additive multilocus model of a quantitative trait under frequency- and density-dependent selection are investigated. Two opposing evolutionary forces are assumed to act: (i) stabilizing selection on the trait, which favors genotypes with an intermediate phenotype, and (ii) intraspecific competition mediated by that trait, which favors genotypes whose effect on the trait deviates most from that of the prevailing genotypes. Accordingly, fitnesses of genotypes have a frequency-independent component describing stabilizing selection and a frequency- and density-dependent component modeling competition. We study how the equilibrium structure, in particular, number, degree of polymorphism, and genetic variance of stable equilibria, is affected by the strength of frequency dependence, and what role the number of loci, the amount of recombination, and the demographic parameters play. To this end, we employ a statistical and numerical approach, complemented by analytical results, and explore how the equilibrium properties averaged over a large number of genetic systems with a given number of loci and average amount of recombination depend on the ecological and demographic parameters. We identify two parameter regions with a transitory region in between, in which the equilibrium properties of genetic systems are distinctively different. These regions depend on the strength of frequency dependence relative to pure stabilizing selection and on the demographic parameters, but not on the number of loci or the amount of recombination. We further study the shape of the fitness function observed at equilibrium and the extent to which the dynamics in this model are adaptive, and we present examples of equilibrium distributions of genotypic values under strong frequency dependence. Consequences for the maintenance of genetic variation, the detection of disruptive selection, and models of sympatric speciation are discussed. PMID:15280253
[Demographic consequences of genetic load: a model of the origin of the incest taboo].
Buzin, A Iu
1987-12-01
The prohibition of copulations among near relatives may raise the fitness of population. This effect being irregular and insignificant for a distinct generation, becomes apparent in evolutionary time intervals through the natural selection of populations with incest-taboo. The "characteristic selection time" theta depends on typical population size, genetic damage and the mean rate of population growth. The estimation obtained for theta permit us to assert that the model describes the phenomenon of "socio-cultural selection" in prehistory. The model shows the demographic specificity of small populations. The problem of the number of consanguineous marriages is considered in detail. New explanation for deviation of the observed frequency of consanguineous marriages from classical estimations is proposed.
The Effect of Inappropriate Calibration: Three Case Studies in Molecular Ecology
Ho, Simon Y. W.; Saarma, Urmas; Barnett, Ross; Haile, James; Shapiro, Beth
2008-01-01
Time-scales estimated from sequence data play an important role in molecular ecology. They can be used to draw correlations between evolutionary and palaeoclimatic events, to measure the tempo of speciation, and to study the demographic history of an endangered species. In all of these studies, it is paramount to have accurate estimates of time-scales and substitution rates. Molecular ecological studies typically focus on intraspecific data that have evolved on genealogical scales, but often these studies inappropriately employ deep fossil calibrations or canonical substitution rates (e.g., 1% per million years for birds and mammals) for calibrating estimates of divergence times. These approaches can yield misleading estimates of molecular time-scales, with significant impacts on subsequent evolutionary and ecological inferences. We illustrate this calibration problem using three case studies: avian speciation in the late Pleistocene, the demographic history of bowhead whales, and the Pleistocene biogeography of brown bears. For each data set, we compare the date estimates that are obtained using internal and external calibration points. In all three cases, the conclusions are significantly altered by the application of revised, internally-calibrated substitution rates. Collectively, the results emphasise the importance of judicious selection of calibrations for analyses of recent evolutionary events. PMID:18286172
Can We Spin Straw Into Gold? An Evaluation of Immigrant Legal Status Imputation Approaches
Van Hook, Jennifer; Bachmeier, James D.; Coffman, Donna; Harel, Ofer
2014-01-01
Researchers have developed logical, demographic, and statistical strategies for imputing immigrants’ legal status, but these methods have never been empirically assessed. We used Monte Carlo simulations to test whether, and under what conditions, legal status imputation approaches yield unbiased estimates of the association of unauthorized status with health insurance coverage. We tested five methods under a range of missing data scenarios. Logical and demographic imputation methods yielded biased estimates across all missing data scenarios. Statistical imputation approaches yielded unbiased estimates only when unauthorized status was jointly observed with insurance coverage; when this condition was not met, these methods overestimated insurance coverage for unauthorized relative to legal immigrants. We next showed how bias can be reduced by incorporating prior information about unauthorized immigrants. Finally, we demonstrated the utility of the best-performing statistical method for increasing power. We used it to produce state/regional estimates of insurance coverage among unauthorized immigrants in the Current Population Survey, a data source that contains no direct measures of immigrants’ legal status. We conclude that commonly employed legal status imputation approaches are likely to produce biased estimates, but data and statistical methods exist that could substantially reduce these biases. PMID:25511332
The effect of inappropriate calibration: three case studies in molecular ecology.
Ho, Simon Y W; Saarma, Urmas; Barnett, Ross; Haile, James; Shapiro, Beth
2008-02-20
Time-scales estimated from sequence data play an important role in molecular ecology. They can be used to draw correlations between evolutionary and palaeoclimatic events, to measure the tempo of speciation, and to study the demographic history of an endangered species. In all of these studies, it is paramount to have accurate estimates of time-scales and substitution rates. Molecular ecological studies typically focus on intraspecific data that have evolved on genealogical scales, but often these studies inappropriately employ deep fossil calibrations or canonical substitution rates (e.g., 1% per million years for birds and mammals) for calibrating estimates of divergence times. These approaches can yield misleading estimates of molecular time-scales, with significant impacts on subsequent evolutionary and ecological inferences. We illustrate this calibration problem using three case studies: avian speciation in the late Pleistocene, the demographic history of bowhead whales, and the Pleistocene biogeography of brown bears. For each data set, we compare the date estimates that are obtained using internal and external calibration points. In all three cases, the conclusions are significantly altered by the application of revised, internally-calibrated substitution rates. Collectively, the results emphasise the importance of judicious selection of calibrations for analyses of recent evolutionary events.
Hill, Mary Catherine
1992-01-01
This report documents a new version of the U.S. Geological Survey modular, three-dimensional, finite-difference, ground-water flow model (MODFLOW) which, with the new Parameter-Estimation Package that also is documented in this report, can be used to estimate parameters by nonlinear regression. The new version of MODFLOW is called MODFLOWP (pronounced MOD-FLOW*P), and functions nearly identically to MODFLOW when the ParameterEstimation Package is not used. Parameters are estimated by minimizing a weighted least-squares objective function by the modified Gauss-Newton method or by a conjugate-direction method. Parameters used to calculate the following MODFLOW model inputs can be estimated: Transmissivity and storage coefficient of confined layers; hydraulic conductivity and specific yield of unconfined layers; vertical leakance; vertical anisotropy (used to calculate vertical leakance); horizontal anisotropy; hydraulic conductance of the River, Streamflow-Routing, General-Head Boundary, and Drain Packages; areal recharge rates; maximum evapotranspiration; pumpage rates; and the hydraulic head at constant-head boundaries. Any spatial variation in parameters can be defined by the user. Data used to estimate parameters can include existing independent estimates of parameter values, observed hydraulic heads or temporal changes in hydraulic heads, and observed gains and losses along head-dependent boundaries (such as streams). Model output includes statistics for analyzing the parameter estimates and the model; these statistics can be used to quantify the reliability of the resulting model, to suggest changes in model construction, and to compare results of models constructed in different ways.
Demographics as predictors of suicidal thoughts and behaviors: A meta-analysis
Huang, Xieyining; Ribeiro, Jessica D.; Musacchio, Katherine M.; Franklin, Joseph C.
2017-01-01
Background Certain demographic factors have long been cited to confer risk or protection for suicidal thoughts and behaviors. However, many studies have found weak or non-significant effects. Determining the effect strength and clinical utility of demographics as predictors is crucial for suicide risk assessment and theory development. As such, we conducted a meta-analysis to determine the effect strength and clinical utility of demographics as predictors. Methods We searched PsycInfo, PubMed, and GoogleScholar for studies published before January 1st, 2015. Inclusion criteria required that studies use at least one demographic factor to longitudinally predict suicide ideation, attempt, or death. The initial search yielded 2,541 studies, 159 of which were eligible. A total of 752 unique statistical tests were included in analysis. Results Suicide death was the most commonly studied outcome, followed by attempt and ideation. The average follow-up length was 9.4 years. The overall effects of demographic factors studied in the field as risk factors were significant but weak, and that of demographic factors studied as protective factors were non-significant. Adjusting for publication bias further reduced effect estimates. No specific demographic factors appeared to be strong predictors. The effects were consistent across multiple moderators. Conclusions At least within the narrow methodological constraints of the existing literature, demographic factors were statistically significant risk factors, but not protective factors. Even as risk factors, demographics offer very little improvement in predictive accuracy. Future studies that go beyond the limitations of the existing literature are needed to further understand the effects of demographics. PMID:28700728
Disparities in hospitalization outcomes among African-American and White prostate cancer patients.
Naik, Gurudatta; Akinyemiju, Tomi
2017-02-01
This paper aims to determine whether racial disparities exist in hospitalization outcomes among African-American and White hospitalized prostate cancer patients in the United States. We evaluated racial differences among matched groups of patients in post-operative complications, hospital length of stay and in-hospital mortality. We identified a total of 183,856 men aged 40 years and older with a primary diagnosis of prostate cancer, of which 58,701 underwent prostatectomy, through the Nationwide Inpatient Sample, and matched all African-American patients with White patients on: 1) Demographics, 2) Demographics+Clinical presentation and 3) Demographics+Clinical presentation+Treatment. Multivariable regression analyses were conducted in SAS and estimates were reported with 95% confidence intervals. African-American patients were more likely to be admitted with metastatic disease (24.8%) compared with White patients matched on demographics (17.9%), and demographics+presentation (23.6%). However, 23.9% of African-American patients received surgery compared with 38.2% and 34.2% of Whites matched on demographics and demographics+presentation, respectively. White patients had lower in-hospital mortality compared with African-American patients matched on demographics (OR: 0.72, 95% CI: 0.66-0.79), demographics+presentation (OR: 0.88, 95% CI: 0.81-0.96), but was no longer significantly lower when matched on demographics, presentation and treatment (OR: 0.92, 95% CI: 0.85-1.00). There were significant racial differences in outcomes among prostate cancer patients within the inpatient setting, even after accounting for demographic and presentation differences. Copyright © 2016 Elsevier Ltd. All rights reserved.
Nonlinear adaptive control system design with asymptotically stable parameter estimation error
NASA Astrophysics Data System (ADS)
Mishkov, Rumen; Darmonski, Stanislav
2018-01-01
The paper presents a new general method for nonlinear adaptive system design with asymptotic stability of the parameter estimation error. The advantages of the approach include asymptotic unknown parameter estimation without persistent excitation and capability to directly control the estimates transient response time. The method proposed modifies the basic parameter estimation dynamics designed via a known nonlinear adaptive control approach. The modification is based on the generalised prediction error, a priori constraints with a hierarchical parameter projection algorithm, and the stable data accumulation concepts. The data accumulation principle is the main tool for achieving asymptotic unknown parameter estimation. It relies on the parametric identifiability system property introduced. Necessary and sufficient conditions for exponential stability of the data accumulation dynamics are derived. The approach is applied in a nonlinear adaptive speed tracking vector control of a three-phase induction motor.
Data-Adaptive Bias-Reduced Doubly Robust Estimation.
Vermeulen, Karel; Vansteelandt, Stijn
2016-05-01
Doubly robust estimators have now been proposed for a variety of target parameters in the causal inference and missing data literature. These consistently estimate the parameter of interest under a semiparametric model when one of two nuisance working models is correctly specified, regardless of which. The recently proposed bias-reduced doubly robust estimation procedure aims to partially retain this robustness in more realistic settings where both working models are misspecified. These so-called bias-reduced doubly robust estimators make use of special (finite-dimensional) nuisance parameter estimators that are designed to locally minimize the squared asymptotic bias of the doubly robust estimator in certain directions of these finite-dimensional nuisance parameters under misspecification of both parametric working models. In this article, we extend this idea to incorporate the use of data-adaptive estimators (infinite-dimensional nuisance parameters), by exploiting the bias reduction estimation principle in the direction of only one nuisance parameter. We additionally provide an asymptotic linearity theorem which gives the influence function of the proposed doubly robust estimator under correct specification of a parametric nuisance working model for the missingness mechanism/propensity score but a possibly misspecified (finite- or infinite-dimensional) outcome working model. Simulation studies confirm the desirable finite-sample performance of the proposed estimators relative to a variety of other doubly robust estimators.
Pittman, Shannon E.; King, T.L.; Faurby, S.; Dorcas, M.E.
2011-01-01
In this study, we sought to determine the population stability and genetic diversity of one isolated population of the federally-threatened bog turtle (Glyptemys muhlenbergii) in North Carolina. Using capture-recapture data, we estimated adult survival and population growth rate from 1992 to 2007. We found that the population decreased from an estimated 36 adult turtles in 1994 to approximately 11 adult turtles in 2007. We found a constant adult survival of 0. 893 (SE = 0. 018, 95% confidence interval, 0. 853-0. 924) between 1992 and 2007. Using 18 microsatellite markers, we compared the genetic status of this population with five other bog turtle populations. The target population displayed allelic richness (4. 8 ?? 0. 5) and observed heterozygosity (0. 619 ?? 0. 064) within the range of the other bog turtle populations. Coalescent analysis of population growth rate, effective population size, and timing of population structuring event also indicated the genetics of the target population were comparable to the other populations studied. Estimates of effective population size were a proportion of the census size in all populations except the target population, in which the effective population size was larger than the census size (30 turtles vs. 11 turtles). We attribute the high genetic diversity in the target population to the presence of multiple generations of old turtles. This study illustrates that the demographic status of populations of long-lived species may not be reflected genetically if a decline occurred recently. Consequently, the genetic integrity of populations of long-lived animals experiencing rapid demographic bottlenecks may be preserved through conservation efforts effective in addressing demographic problems. ?? 2011 Springer Science+Business Media B.V.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rose, Amy N.; Nagle, Nicholas N.
Techniques such as Iterative Proportional Fitting have been previously suggested as a means to generate new data with the demographic granularity of individual surveys and the spatial granularity of small area tabulations of censuses and surveys. This article explores internal and external validation approaches for synthetic, small area, household- and individual-level microdata using a case study for Bangladesh. Using data from the Bangladesh Census 2011 and the Demographic and Health Survey, we produce estimates of infant mortality rate and other household attributes for small areas using a variation of an iterative proportional fitting method called P-MEDM. We conduct an internalmore » validation to determine: whether the model accurately recreates the spatial variation of the input data, how each of the variables performed overall, and how the estimates compare to the published population totals. We conduct an external validation by comparing the estimates with indicators from the 2009 Multiple Indicator Cluster Survey (MICS) for Bangladesh to benchmark how well the estimates compared to a known dataset which was not used in the original model. The results indicate that the estimation process is viable for regions that are better represented in the microdata sample, but also revealed the possibility of strong overfitting in sparsely sampled sub-populations.« less
Rose, Amy N.; Nagle, Nicholas N.
2016-08-01
Techniques such as Iterative Proportional Fitting have been previously suggested as a means to generate new data with the demographic granularity of individual surveys and the spatial granularity of small area tabulations of censuses and surveys. This article explores internal and external validation approaches for synthetic, small area, household- and individual-level microdata using a case study for Bangladesh. Using data from the Bangladesh Census 2011 and the Demographic and Health Survey, we produce estimates of infant mortality rate and other household attributes for small areas using a variation of an iterative proportional fitting method called P-MEDM. We conduct an internalmore » validation to determine: whether the model accurately recreates the spatial variation of the input data, how each of the variables performed overall, and how the estimates compare to the published population totals. We conduct an external validation by comparing the estimates with indicators from the 2009 Multiple Indicator Cluster Survey (MICS) for Bangladesh to benchmark how well the estimates compared to a known dataset which was not used in the original model. The results indicate that the estimation process is viable for regions that are better represented in the microdata sample, but also revealed the possibility of strong overfitting in sparsely sampled sub-populations.« less
da Silveira, Christian L; Mazutti, Marcio A; Salau, Nina P G
2016-07-08
Process modeling can lead to of advantages such as helping in process control, reducing process costs and product quality improvement. This work proposes a solid-state fermentation distributed parameter model composed by seven differential equations with seventeen parameters to represent the process. Also, parameters estimation with a parameters identifyability analysis (PIA) is performed to build an accurate model with optimum parameters. Statistical tests were made to verify the model accuracy with the estimated parameters considering different assumptions. The results have shown that the model assuming substrate inhibition better represents the process. It was also shown that eight from the seventeen original model parameters were nonidentifiable and better results were obtained with the removal of these parameters from the estimation procedure. Therefore, PIA can be useful to estimation procedure, since it may reduce the number of parameters that can be evaluated. Further, PIA improved the model results, showing to be an important procedure to be taken. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:905-917, 2016. © 2016 American Institute of Chemical Engineers.
Stige, Leif Chr; Ottersen, Geir; Yaragina, Natalia A; Vikebø, Frode B; Stenseth, Nils Chr; Langangen, Øystein
2018-04-01
It has been proposed that the multiple pressures of fishing and petroleum activities impact fish stocks in synergy, as fishing-induced demographic changes in a stock may lead to increased sensitivity to detrimental effects of acute oil spills. High fishing pressure may erode the demographic structure of fish stocks, lead to less diverse spawning strategies, and more concentrated distributions of offspring in space and time. Hence an oil spill may potentially hit a larger fraction of a year-class of offspring. Such a link between demographic structure and egg distribution was recently demonstrated for the Northeast Arctic stock of Atlantic cod for years 1959-1993. We here estimate that this variation translates into a two-fold variation in the maximal proportion of cod eggs potentially exposed to a large oil spill. With this information it is possible to quantitatively account for demographic structure in prospective studies of population effects of possible oil spills. Copyright © 2018 Elsevier Ltd. All rights reserved.
Estimation of the Parameters in a Two-State System Coupled to a Squeezed Bath
NASA Astrophysics Data System (ADS)
Hu, Yao-Hua; Yang, Hai-Feng; Tan, Yong-Gang; Tao, Ya-Ping
2018-04-01
Estimation of the phase and weight parameters of a two-state system in a squeezed bath by calculating quantum Fisher information is investigated. The results show that, both for the phase estimation and for the weight estimation, the quantum Fisher information always decays with time and changes periodically with the phases. The estimation precision can be enhanced by choosing the proper values of the phases and the squeezing parameter. These results can be provided as an analysis reference for the practical application of the parameter estimation in a squeezed bath.
Experimental design and efficient parameter estimation in preclinical pharmacokinetic studies.
Ette, E I; Howie, C A; Kelman, A W; Whiting, B
1995-05-01
Monte Carlo simulation technique used to evaluate the effect of the arrangement of concentrations on the efficiency of estimation of population pharmacokinetic parameters in the preclinical setting is described. Although the simulations were restricted to the one compartment model with intravenous bolus input, they provide the basis of discussing some structural aspects involved in designing a destructive ("quantic") preclinical population pharmacokinetic study with a fixed sample size as is usually the case in such studies. The efficiency of parameter estimation obtained with sampling strategies based on the three and four time point designs were evaluated in terms of the percent prediction error, design number, individual and joint confidence intervals coverage for parameter estimates approaches, and correlation analysis. The data sets contained random terms for both inter- and residual intra-animal variability. The results showed that the typical population parameter estimates for clearance and volume were efficiently (accurately and precisely) estimated for both designs, while interanimal variability (the only random effect parameter that could be estimated) was inefficiently (inaccurately and imprecisely) estimated with most sampling schedules of the two designs. The exact location of the third and fourth time point for the three and four time point designs, respectively, was not critical to the efficiency of overall estimation of all population parameters of the model. However, some individual population pharmacokinetic parameters were sensitive to the location of these times.
Robust gaze-steering of an active vision system against errors in the estimated parameters
NASA Astrophysics Data System (ADS)
Han, Youngmo
2015-01-01
Gaze-steering is often used to broaden the viewing range of an active vision system. Gaze-steering procedures are usually based on estimated parameters such as image position, image velocity, depth and camera calibration parameters. However, there may be uncertainties in these estimated parameters because of measurement noise and estimation errors. In this case, robust gaze-steering cannot be guaranteed. To compensate for such problems, this paper proposes a gaze-steering method based on a linear matrix inequality (LMI). In this method, we first propose a proportional derivative (PD) control scheme on the unit sphere that does not use depth parameters. This proposed PD control scheme can avoid uncertainties in the estimated depth and camera calibration parameters, as well as inconveniences in their estimation process, including the use of auxiliary feature points and highly non-linear computation. Furthermore, the control gain of the proposed PD control scheme on the unit sphere is designed using LMI such that the designed control is robust in the presence of uncertainties in the other estimated parameters, such as image position and velocity. Simulation results demonstrate that the proposed method provides a better compensation for uncertainties in the estimated parameters than the contemporary linear method and steers the gaze of the camera more steadily over time than the contemporary non-linear method.
Kenneth E. Skog; Robert S. Manthy
1989-01-01
This study explains and determines fuelwood consumption at the county level based on county economic and demographic conditions, and identifies U.S. counties where potential fuelwood use problems and benefits are greatest. The percentage of wood-burning households in a county is estimated and multiplied by estimated average wood consumed per wood-burning household in...
Characterizing source-sink dynamics with genetic parentage assignments
M. Zachariah Peery; Steven R. Beissinger; Roger F. House; Martine Berube; Laurie A. Hall; Anna Sellas; Per J. Palsboll
2008-01-01
Source-sink dynamics have been suggested to characterize the population structure of many species, but the prevalence of source-sink systems in nature is uncertain because of inherent challenges in estimating migration rates among populations. Migration rates are often difficult to estimate directly with demographic methods, and indirect genetic methods are subject to...
An Evaluation of Hierarchical Bayes Estimation for the Two- Parameter Logistic Model.
ERIC Educational Resources Information Center
Kim, Seock-Ho
Hierarchical Bayes procedures for the two-parameter logistic item response model were compared for estimating item parameters. Simulated data sets were analyzed using two different Bayes estimation procedures, the two-stage hierarchical Bayes estimation (HB2) and the marginal Bayesian with known hyperparameters (MB), and marginal maximum…
Estimation Methods for One-Parameter Testlet Models
ERIC Educational Resources Information Center
Jiao, Hong; Wang, Shudong; He, Wei
2013-01-01
This study demonstrated the equivalence between the Rasch testlet model and the three-level one-parameter testlet model and explored the Markov Chain Monte Carlo (MCMC) method for model parameter estimation in WINBUGS. The estimation accuracy from the MCMC method was compared with those from the marginalized maximum likelihood estimation (MMLE)…
Estimation of pharmacokinetic parameters from non-compartmental variables using Microsoft Excel.
Dansirikul, Chantaratsamon; Choi, Malcolm; Duffull, Stephen B
2005-06-01
This study was conducted to develop a method, termed 'back analysis (BA)', for converting non-compartmental variables to compartment model dependent pharmacokinetic parameters for both one- and two-compartment models. A Microsoft Excel spreadsheet was implemented with the use of Solver and visual basic functions. The performance of the BA method in estimating pharmacokinetic parameter values was evaluated by comparing the parameter values obtained to a standard modelling software program, NONMEM, using simulated data. The results show that the BA method was reasonably precise and provided low bias in estimating fixed and random effect parameters for both one- and two-compartment models. The pharmacokinetic parameters estimated from the BA method were similar to those of NONMEM estimation.
SBML-PET-MPI: a parallel parameter estimation tool for Systems Biology Markup Language based models.
Zi, Zhike
2011-04-01
Parameter estimation is crucial for the modeling and dynamic analysis of biological systems. However, implementing parameter estimation is time consuming and computationally demanding. Here, we introduced a parallel parameter estimation tool for Systems Biology Markup Language (SBML)-based models (SBML-PET-MPI). SBML-PET-MPI allows the user to perform parameter estimation and parameter uncertainty analysis by collectively fitting multiple experimental datasets. The tool is developed and parallelized using the message passing interface (MPI) protocol, which provides good scalability with the number of processors. SBML-PET-MPI is freely available for non-commercial use at http://www.bioss.uni-freiburg.de/cms/sbml-pet-mpi.html or http://sites.google.com/site/sbmlpetmpi/.
Jenouvrier, Stéphanie; Holland, Marika; Stroeve, Julienne; Barbraud, Christophe; Weimerskirch, Henri; Serreze, Mark; Caswell, Hal
2012-09-01
Sea ice conditions in the Antarctic affect the life cycle of the emperor penguin (Aptenodytes forsteri). We present a population projection for the emperor penguin population of Terre Adélie, Antarctica, by linking demographic models (stage-structured, seasonal, nonlinear, two-sex matrix population models) to sea ice forecasts from an ensemble of IPCC climate models. Based on maximum likelihood capture-mark-recapture analysis, we find that seasonal sea ice concentration anomalies (SICa ) affect adult survival and breeding success. Demographic models show that both deterministic and stochastic population growth rates are maximized at intermediate values of annual SICa , because neither the complete absence of sea ice, nor heavy and persistent sea ice, would provide satisfactory conditions for the emperor penguin. We show that under some conditions the stochastic growth rate is positively affected by the variance in SICa . We identify an ensemble of five general circulation climate models whose output closely matches the historical record of sea ice concentration in Terre Adélie. The output of this ensemble is used to produce stochastic forecasts of SICa , which in turn drive the population model. Uncertainty is included by incorporating multiple climate models and by a parametric bootstrap procedure that includes parameter uncertainty due to both model selection and estimation error. The median of these simulations predicts a decline of the Terre Adélie emperor penguin population of 81% by the year 2100. We find a 43% chance of an even greater decline, of 90% or more. The uncertainty in population projections reflects large differences among climate models in their forecasts of future sea ice conditions. One such model predicts population increases over much of the century, but overall, the ensemble of models predicts that population declines are far more likely than population increases. We conclude that climate change is a significant risk for the emperor penguin. Our analytical approach, in which demographic models are linked to IPCC climate models, is powerful and generally applicable to other species and systems. © 2012 Blackwell Publishing Ltd.
Hotaling, Scott; Muhlfeld, Clint C.; Giersch, J. Joseph; Ali, Omar; Jordan, Steve; Miller, Michael R.; Luikart, Gordon; Weisrock, David W.
2018-01-01
AimClimate warming is causing extensive loss of glaciers in mountainous regions, yet our understanding of how glacial recession influences evolutionary processes and genetic diversity is limited. Linking genetic structure with the influences shaping it can improve understanding of how species respond to environmental change. Here, we used genome-scale data and demographic modelling to resolve the evolutionary history of Lednia tumana, a rare, aquatic insect endemic to alpine streams. We also employed a range of widely used data filtering approaches to quantify how they influenced population structure results.LocationAlpine streams in the Rocky Mountains of Glacier National Park, Montana, USA.TaxonLednia tumana, a stonefly (Order Plecoptera) in the family Nemouridae.MethodsWe generated single nucleotide polymorphism data through restriction-site associated DNA sequencing to assess contemporary patterns of genetic structure for 11 L. tumana populations. Using identified clusters, we assessed demographic history through model selection and parameter estimation in a coalescent framework. During population structure analyses, we filtered our data to assess the influence of singletons, missing data and total number of markers on results.ResultsContemporary patterns of population structure indicate that L. tumana exhibits a pattern of isolation-by-distance among populations within three genetic clusters that align with geography. Mean pairwise genetic differentiation (FST) among populations was 0.033. Coalescent-based demographic modelling supported divergence with gene flow among genetic clusters since the end of the Pleistocene (~13-17 kya), likely reflecting the south-to-north recession of ice sheets that accumulated during the Wisconsin glaciation.Main conclusionsWe identified a link between glacial retreat, evolutionary history and patterns of genetic diversity for a range-restricted stonefly imperiled by climate change. This finding included a history of divergence with gene flow, an unexpected conclusion for a mountaintop species. Beyond L. tumana, this study demonstrates the complexity of assessing genetic structure for weakly differentiated species, shows the degree to which rare alleles and missing data may influence results, and highlights the usefulness of genome-scale data to extend population genetic inquiry in non-model species.
Bootstrap Standard Errors for Maximum Likelihood Ability Estimates When Item Parameters Are Unknown
ERIC Educational Resources Information Center
Patton, Jeffrey M.; Cheng, Ying; Yuan, Ke-Hai; Diao, Qi
2014-01-01
When item parameter estimates are used to estimate the ability parameter in item response models, the standard error (SE) of the ability estimate must be corrected to reflect the error carried over from item calibration. For maximum likelihood (ML) ability estimates, a corrected asymptotic SE is available, but it requires a long test and the…
NASA Technical Reports Server (NTRS)
Suit, W. T.; Cannaday, R. L.
1979-01-01
The longitudinal and lateral stability and control parameters for a high wing, general aviation, airplane are examined. Estimations using flight data obtained at various flight conditions within the normal range of the aircraft are presented. The estimations techniques, an output error technique (maximum likelihood) and an equation error technique (linear regression), are presented. The longitudinal static parameters are estimated from climbing, descending, and quasi steady state flight data. The lateral excitations involve a combination of rudder and ailerons. The sensitivity of the aircraft modes of motion to variations in the parameter estimates are discussed.
NASA Technical Reports Server (NTRS)
Klein, V.
1979-01-01
Two identification methods, the equation error method and the output error method, are used to estimate stability and control parameter values from flight data for a low-wing, single-engine, general aviation airplane. The estimated parameters from both methods are in very good agreement primarily because of sufficient accuracy of measured data. The estimated static parameters also agree with the results from steady flights. The effect of power different input forms are demonstrated. Examination of all results available gives the best values of estimated parameters and specifies their accuracies.
Ensemble-Based Parameter Estimation in a Coupled GCM Using the Adaptive Spatial Average Method
Liu, Y.; Liu, Z.; Zhang, S.; ...
2014-05-29
Ensemble-based parameter estimation for a climate model is emerging as an important topic in climate research. And for a complex system such as a coupled ocean–atmosphere general circulation model, the sensitivity and response of a model variable to a model parameter could vary spatially and temporally. An adaptive spatial average (ASA) algorithm is proposed to increase the efficiency of parameter estimation. Refined from a previous spatial average method, the ASA uses the ensemble spread as the criterion for selecting “good” values from the spatially varying posterior estimated parameter values; these good values are then averaged to give the final globalmore » uniform posterior parameter. In comparison with existing methods, the ASA parameter estimation has a superior performance: faster convergence and enhanced signal-to-noise ratio.« less
A Systematic Approach to Sensor Selection for Aircraft Engine Health Estimation
NASA Technical Reports Server (NTRS)
Simon, Donald L.; Garg, Sanjay
2009-01-01
A systematic approach for selecting an optimal suite of sensors for on-board aircraft gas turbine engine health estimation is presented. The methodology optimally chooses the engine sensor suite and the model tuning parameter vector to minimize the Kalman filter mean squared estimation error in the engine s health parameters or other unmeasured engine outputs. This technique specifically addresses the underdetermined estimation problem where there are more unknown system health parameters representing degradation than available sensor measurements. This paper presents the theoretical estimation error equations, and describes the optimization approach that is applied to select the sensors and model tuning parameters to minimize these errors. Two different model tuning parameter vector selection approaches are evaluated: the conventional approach of selecting a subset of health parameters to serve as the tuning parameters, and an alternative approach that selects tuning parameters as a linear combination of all health parameters. Results from the application of the technique to an aircraft engine simulation are presented, and compared to those from an alternative sensor selection strategy.
Estimating Soil Hydraulic Parameters using Gradient Based Approach
NASA Astrophysics Data System (ADS)
Rai, P. K.; Tripathi, S.
2017-12-01
The conventional way of estimating parameters of a differential equation is to minimize the error between the observations and their estimates. The estimates are produced from forward solution (numerical or analytical) of differential equation assuming a set of parameters. Parameter estimation using the conventional approach requires high computational cost, setting-up of initial and boundary conditions, and formation of difference equations in case the forward solution is obtained numerically. Gaussian process based approaches like Gaussian Process Ordinary Differential Equation (GPODE) and Adaptive Gradient Matching (AGM) have been developed to estimate the parameters of Ordinary Differential Equations without explicitly solving them. Claims have been made that these approaches can straightforwardly be extended to Partial Differential Equations; however, it has been never demonstrated. This study extends AGM approach to PDEs and applies it for estimating parameters of Richards equation. Unlike the conventional approach, the AGM approach does not require setting-up of initial and boundary conditions explicitly, which is often difficult in real world application of Richards equation. The developed methodology was applied to synthetic soil moisture data. It was seen that the proposed methodology can estimate the soil hydraulic parameters correctly and can be a potential alternative to the conventional method.
A variational approach to parameter estimation in ordinary differential equations.
Kaschek, Daniel; Timmer, Jens
2012-08-14
Ordinary differential equations are widely-used in the field of systems biology and chemical engineering to model chemical reaction networks. Numerous techniques have been developed to estimate parameters like rate constants, initial conditions or steady state concentrations from time-resolved data. In contrast to this countable set of parameters, the estimation of entire courses of network components corresponds to an innumerable set of parameters. The approach presented in this work is able to deal with course estimation for extrinsic system inputs or intrinsic reactants, both not being constrained by the reaction network itself. Our method is based on variational calculus which is carried out analytically to derive an augmented system of differential equations including the unconstrained components as ordinary state variables. Finally, conventional parameter estimation is applied to the augmented system resulting in a combined estimation of courses and parameters. The combined estimation approach takes the uncertainty in input courses correctly into account. This leads to precise parameter estimates and correct confidence intervals. In particular this implies that small motifs of large reaction networks can be analysed independently of the rest. By the use of variational methods, elements from control theory and statistics are combined allowing for future transfer of methods between the two fields.
Helsel, Dennis R.; Gilliom, Robert J.
1986-01-01
Estimates of distributional parameters (mean, standard deviation, median, interquartile range) are often desired for data sets containing censored observations. Eight methods for estimating these parameters have been evaluated by R. J. Gilliom and D. R. Helsel (this issue) using Monte Carlo simulations. To verify those findings, the same methods are now applied to actual water quality data. The best method (lowest root-mean-squared error (rmse)) over all parameters, sample sizes, and censoring levels is log probability regression (LR), the method found best in the Monte Carlo simulations. Best methods for estimating moment or percentile parameters separately are also identical to the simulations. Reliability of these estimates can be expressed as confidence intervals using rmse and bias values taken from the simulation results. Finally, a new simulation study shows that best methods for estimating uncensored sample statistics from censored data sets are identical to those for estimating population parameters. Thus this study and the companion study by Gilliom and Helsel form the basis for making the best possible estimates of either population parameters or sample statistics from censored water quality data, and for assessments of their reliability.
Stability and change in the clinical course of schizoaffective disorder.
Durla, Anca; Lenciu, M; Bredicean, C; Papava, I; Cristanovici, M
2013-01-01
Schizoaffective disorder currently raises several questions, one of them being related to the stability of the clinical diagnosis over time. The aim of this study is to identify the clinical and evolutional particularities in the longitudinal course of schizoaffective disorder. 44 subjects with a current diagnosis of schizoaffective disorder have been assessed prospectively. Following parameters were analyzed: socio-demographic (age at onset, gender, educational, professional and marital status at onset) and clinical (total duration of evolution, diagnosis at onset, duration of the evolution until the switch to the schizoaffective disorder diagnosis). Socio-demographic parameters are similar to those in literature and the clinical assessment revealed that schizoaffective disorder is present as a diagnosis along with the longitudinal course of other types of psychosis. Schizoaffective disorder appears as a heterogeneous pathology in terms of the longitudinal course.
Parameter estimation of qubit states with unknown phase parameter
NASA Astrophysics Data System (ADS)
Suzuki, Jun
2015-02-01
We discuss a problem of parameter estimation for quantum two-level system, qubit system, in presence of unknown phase parameter. We analyze trade-off relations for mean square errors (MSEs) when estimating relevant parameters with separable measurements based on known precision bounds; the symmetric logarithmic derivative (SLD) Cramér-Rao (CR) bound and Hayashi-Gill-Massar (HGM) bound. We investigate the optimal measurement which attains the HGM bound and discuss its properties. We show that the HGM bound for relevant parameters can be attained asymptotically by using some fraction of given n quantum states to estimate the phase parameter. We also discuss the Holevo bound which can be attained asymptotically by a collective measurement.
Image informative maps for component-wise estimating parameters of signal-dependent noise
NASA Astrophysics Data System (ADS)
Uss, Mykhail L.; Vozel, Benoit; Lukin, Vladimir V.; Chehdi, Kacem
2013-01-01
We deal with the problem of blind parameter estimation of signal-dependent noise from mono-component image data. Multispectral or color images can be processed in a component-wise manner. The main results obtained rest on the assumption that the image texture and noise parameters estimation problems are interdependent. A two-dimensional fractal Brownian motion (fBm) model is used for locally describing image texture. A polynomial model is assumed for the purpose of describing the signal-dependent noise variance dependence on image intensity. Using the maximum likelihood approach, estimates of both fBm-model and noise parameters are obtained. It is demonstrated that Fisher information (FI) on noise parameters contained in an image is distributed nonuniformly over intensity coordinates (an image intensity range). It is also shown how to find the most informative intensities and the corresponding image areas for a given noisy image. The proposed estimator benefits from these detected areas to improve the estimation accuracy of signal-dependent noise parameters. Finally, the potential estimation accuracy (Cramér-Rao Lower Bound, or CRLB) of noise parameters is derived, providing confidence intervals of these estimates for a given image. In the experiment, the proposed and existing state-of-the-art noise variance estimators are compared for a large image database using CRLB-based statistical efficiency criteria.
2012-01-01
Background For accurate estimation of the future burden of communicable diseases, the dynamics of the population at risk – namely population growth and population ageing – need to be taken into account. Accurate burden estimates are necessary for informing policy-makers regarding the planning of vaccination and other control, intervention, and prevention measures. Our aim was to qualitatively explore the impact of population ageing on the estimated future burden of seasonal influenza and hepatitis B virus (HBV) infection in the Netherlands, in the period 2000–2030. Methods Population-level disease burden was quantified using the disability-adjusted life years (DALY) measure applied to all health outcomes following acute infection. We used national notification data, pre-defined disease progression models, and a simple model of demographic dynamics to investigate the impact of population ageing on the burden of seasonal influenza and HBV. Scenario analyses were conducted to explore the potential impact of intervention-associated changes in incidence rates. Results Including population dynamics resulted in increasing burden over the study period for influenza, whereas a relatively stable future burden was predicted for HBV. For influenza, the increase in DALYs was localised within YLL for the oldest age-groups (55 and older), and for HBV the effect of longer life expectancy in the future was offset by a reduction in incidence in the age-groups most at risk of infection. For both infections, the predicted disease burden was greater than if a static demography was assumed: 1.0 (in 2000) to 2.3-fold (in 2030) higher DALYs for influenza; 1.3 (in 2000) to 1.5-fold (in 2030) higher for HBV. Conclusions There are clear, but diverging effects of an ageing population on the estimated disease burden of influenza and HBV in the Netherlands. Replacing static assumptions with a dynamic demographic approach appears essential for deriving realistic burden estimates for informing health policy. PMID:23217094
Wagener, T.; Hogue, T.; Schaake, J.; Duan, Q.; Gupta, H.; Andreassian, V.; Hall, A.; Leavesley, G.
2006-01-01
The Model Parameter Estimation Experiment (MOPEX) is an international project aimed at developing enhanced techniques for the a priori estimation of parameters in hydrological models and in land surface parameterization schemes connected to atmospheric models. The MOPEX science strategy involves: database creation, a priori parameter estimation methodology development, parameter refinement or calibration, and the demonstration of parameter transferability. A comprehensive MOPEX database has been developed that contains historical hydrometeorological data and land surface characteristics data for many hydrological basins in the United States (US) and in other countries. This database is being continuously expanded to include basins from various hydroclimatic regimes throughout the world. MOPEX research has largely been driven by a series of international workshops that have brought interested hydrologists and land surface modellers together to exchange knowledge and experience in developing and applying parameter estimation techniques. With its focus on parameter estimation, MOPEX plays an important role in the international context of other initiatives such as GEWEX, HEPEX, PUB and PILPS. This paper outlines the MOPEX initiative, discusses its role in the scientific community, and briefly states future directions.
Past primary sex-ratio estimates of 4 populations of Loggerhead sea turtle based on TSP durations.
NASA Astrophysics Data System (ADS)
Monsinjon, Jonathan; Kaska, Yakup; Tucker, Tony; LeBlanc, Anne Marie; Williams, Kristina; Rostal, David; Girondot, Marc
2016-04-01
Ectothermic species are supposed to be strongly affected by climate change and particularly those that exhibit temperature-dependent sex-determination (TSD). Actually, predicting the embryonic response of such organism to incubation-temperature variations in natural conditions remains challenging. In order to assess the vulnerability of sea turtles, primary sex-ratio estimates should be produced at pertinent ecological time and spatial scales. Although information on this important demographic parameter is one of the priorities for conservation purpose, accurate methodology to produce such an estimate is still lacking. The most commonly used method invocates incubation duration as a proxy for sex-ratio. This method is inappropriate because temperature influences incubation duration during all development whereas sex is influenced by temperature during only part of development. The thermosensitive period of development for sex determination (TSP) lies in the middle third of development. A model of embryonic growth must be used to define precisely the position of the TSP at non-constant incubation temperatures. The thermal reaction norm for embryonic growth rate have been estimated for 4 distinct populations of the globally distributed and threatened marine turtle Caretta caretta. A thermal reaction norm describes the pattern of phenotypic expression of a single genotype across a range of temperatures. Moreover, incubation temperatures have been reconstructed for the last 35 years using a multi-correlative model with climate temperature. After development of embryos have been modelled, we estimated the primary sex-ratio based on the duration of the TSP. Our results suggests that Loggerhead sea turtles nesting phenology is linked with the period within which both sexes can be produced in variable proportions. Several hypotheses will be discussed to explain why Caretta caretta could be more resilient to climate change than generally thought for sex determination.
Forecasting extinction risk with nonstationary matrix models.
Gotelli, Nicholas J; Ellison, Aaron M
2006-02-01
Matrix population growth models are standard tools for forecasting population change and for managing rare species, but they are less useful for predicting extinction risk in the face of changing environmental conditions. Deterministic models provide point estimates of lambda, the finite rate of increase, as well as measures of matrix sensitivity and elasticity. Stationary matrix models can be used to estimate extinction risk in a variable environment, but they assume that the matrix elements are randomly sampled from a stationary (i.e., non-changing) distribution. Here we outline a method for using nonstationary matrix models to construct realistic forecasts of population fluctuation in changing environments. Our method requires three pieces of data: (1) field estimates of transition matrix elements, (2) experimental data on the demographic responses of populations to altered environmental conditions, and (3) forecasting data on environmental drivers. These three pieces of data are combined to generate a series of sequential transition matrices that emulate a pattern of long-term change in environmental drivers. Realistic estimates of population persistence and extinction risk can be derived from stochastic permutations of such a model. We illustrate the steps of this analysis with data from two populations of Sarracenia purpurea growing in northern New England. Sarracenia purpurea is a perennial carnivorous plant that is potentially at risk of local extinction because of increased nitrogen deposition. Long-term monitoring records or models of environmental change can be used to generate time series of driver variables under different scenarios of changing environments. Both manipulative and natural experiments can be used to construct a linking function that describes how matrix parameters change as a function of the environmental driver. This synthetic modeling approach provides quantitative estimates of extinction probability that have an explicit mechanistic basis.